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International Journals of Marketing and Technology(IJMT) is a refereed research journal which aims to promote the links between management and IT. The journal focuses on issues related to the …

International Journals of Marketing and Technology(IJMT) is a refereed research journal which aims to promote the links between management and IT. The journal focuses on issues related to the development and implementation of new methodologies and technologies, which improve the operational objectives of an organization. These include, among others, product development, human resources management, project management, logistics, production management, e-commerce, quality management, financial planning, risk management, decision support systems, General Management, Banking, Insurance, Economics, IT, Computer Science, Cyber Security and emerging trends in allied subjects. Thus, the journal provides a forum for researchers and practitioners for the publication of innovative scholarly research, which contributes to the adoption of a new holistic managerial approach that ensures a technologically, economically, socially and ecologically acceptable deployment of new technologies in business practice.

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  • 1. IJRIME Volume1Issue5 ISSN-2249- 1619  Sr.  TITLE & NAME OF  THE AUTHOR(S)  Page No.  No. 1  REAL TIME NETWORK MONITORING SYSTEM IN LAN ENVIRONMENT  1   M. Shoaib Yousaf , Ahmed Mattin ,  Ahsan Raza Sattar 2  QUALITY OF WORKING LIFE IN INSURANCE SECTOR  12  Rita Goyal 3  REFACTORABILITY ANALYSIS USING LINEAR REGRESSION  23  Gauri Khurana, Sonika Jindal 4  OPTIMIZING FILTERING PHASE FOR NEAR‐DUPLICATE DETECTION OF WEB PAGES   USING TDW‐MATRIX  38  Tanvi Gupta 5  STUDY AND DESIGN OF BUILDING INTEGRATED PHOTO VOLTAIC SYSTEM AT HCTM CAMPUS KAITHAL, HARYANA  47  Rajeev Kumar, Gagan Deep Singh 6  FUNDS MANAGEMENT OF ICICI BANK  64  Manju Sharma 7  EMERGING TRENDS IN HUMAN RESOURCE MANAGEMENT—A CHALLENGE TO THE ITES  77  Raunak Narayan 8  FUNDAMENTAL CHALLENGES IN EMERGENT FIELD OF SENSOR NETWORK SECURITY AND INITIAL APPROACHES TO SOLVE  88  THEM  D. P. Mishra, M. K. Kowar 9  THE ECONOMICS & BUSINESS OF EUROPEAN LEAGUE FOOTBALL  105  Rosy Kalra 10  AN ALGORITHM FOR SOLVING A CAPACITATED FIXED CHARGE BI‐CRITERION INDEFINITE QUADRATIC TRANSPORTATION  123  PROBLEM WITH RESTRICTED FLOW  S.R. Arora, Kavita Gupta 11  IMPACTS OF USE OF RFBIDW ON TAXATION  141  Sulatan Singh, Surendra Kundu, Madhu Arora 12  EVALUATION OF KNOWLEDGE MANAGEMENT LEVEL OF EDUCATIONAL INSTITUTIONS USING FCE AND AHP  148  Mohit Maheshwarkar, N. Sohani, Pallavi Maheshwarkar 13  EVALUATION OF KNOWLEDGE MANAGEMENT LEVEL OF EDUCATIONAL INSTITUTIONS USING ANALYTICAL HIERARCHY  165  PROCESS: A CASE STUDY IN INDIA  Mohit Maheshwarkar, N. Sohani, Pallvai Maheshwarkar 14  PROBE FEED RECTANGULAR PATCH MICROSTRIP ANTENNA: CAD METHODOLOGY    180  R.D. Kanphade, D.G. Wakade, N.T. Markad 15  DETERMINANTS OF GROWTH OF TOURISM INDUSTRY IN GOA: A STUDY   191  Dr. Achut Pednekar    International Journal of Research in IT, Management and Engineering www.gjmr.org
  • 2. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  REAL TIME NETWORK MONITORING SYSTEM IN LAN ENVIRONMENTM. Shoaib Yousaf *Ahmed Mattin *Ahsan Raza Sattar* ABSTRACTIn this research thesis, I have compared different NMS tools and their feature. I have alsoanalyzed the available three SNMP versions and compare them in respect of security to selectwhich one is best to use. The SNMP v1 and v2 have most of similar features but in SNMPv2some modifications were made to overcome the deficiencies in version 1. After that SNMPversion 3 (SNMPv3) added security and remotely configurations is added in the earlier versionsand SNMP v3 is now most up to date version available today. I have examines the two methodsto secure network traffic i.e. SNMP v3, the latest version and combination of SNMP with thenon secure version like Internet Protocol Security i.e. SNMP over IPSec. These two techniquesimplement authorization, safety and privacy of network traffic passing through SNMP.Keywords: NMS, LAN, SNMP, TCP /IP, IPSec.*Computer Science Department, University of Agriculture, Faisalabad, Pakistan International Journal of Research in IT, Management and Engineering www.gjmr.org 1
  • 3. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 INTRODUCTIONNetwork management systems are use to make sure accessibility and complete take care ofcomputers and network devices installed in LAN. An NMS is able of detection and reportfailures of devices configured in network to administrator efficiently. NMS continuously sendmessages across the network to all other host to confirm their status. When failures of devicesand slow responses from devices shown, then these systems send extra messages called alerts toinform system administrators regarding the problems.To have control of overall network, administrator wants to know the condition of all devices onconfigured on the network i.e. Data flowing in / out from each host etc. there is a protocolavailable within the TCP / IP suite called Simple Network Management Protocol (SNMP) tomeet this purpose (Amir and Maccane, 2003).Administrator used multiple tools for monitoring the internet as there is no restriction to selectspecific monitoring tool available. E.g. to have complete view of network devices on the internet,shared intranet, mail servers, database servers etc administrators use IP monitor software andupdate them upon receiving alerts via alarms, messages or e-mail etc is case of a connection fails(Bradley, 2002).The basic idea of this thesis is to compare the different NMS tools and their feature. In thisresearch paper we will discuss the available three SNMP versions. The SNMP v1 and v2 havemost of similar features but in SNMPv2 some modifications were made to overcome thedeficiencies in version 1. After that SNMP version 3 (SNMPv3) added security and remotelyconfigurations is added in the earlier versions and SNMP v3 is now most up to date versionavailable today. Our main target is to examines the two methods to secure network traffic (i)SNMP v3, the latest version (ii) combination of SNMP with the non secure version like InternetProtocol Security i.e. SNMP over IPSec. These two techniques implement authorization, safetyand privacy of network traffic passing through SNMP.MATERIALS & METHODSIn this section the main focus is on the design of the network management system as well as themajor parts of the system will be discus in this chapter. Also different parts and how these parts International Journal of Research in IT, Management and Engineering www.gjmr.org 2
  • 4. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 correlate each other in network management system to work will be discuss here. We are goingto compare the SNMP versions available and find out the better one to be used with networkmanagement system. Also administrator should be well aware of the security issues such asability to restore, capable to delete / add user, able to monitor network accessibility, amount oftraffic, rerouting, user authentication and response time of the faults.WORKING MECHANISMSNMP was proposed as a protocol that manages the nodes of network such as important servers,workstations, routers, switches etc. SNMP protocol is placed inside the UDP transport layerwhich is a connectionless layer in OSI model. To calculate the network performance, to locatethe hosts and resolve network problem and to update the network, SNMP is used. SNMPmanaged networks consists of there fundamental parts: NMS devices, NMS agents and NMSs.An SNMP managed device comprises of an SNMP agent which is placed inside the network andwatches all activities of network. The SNMP agent collects all the network information andstores that information to the use of this information by NMSs. All devices of network likerouters, servers, switches and printers etc are control by the NMSs in the network. An agent isplaced inside the SNMP device that is regularly watching all events of network. SNMP agent isprovided limited access to the collected data and converted this data to a readable form necessaryto use with SNMP. How NMS Works (Swee, 2006).Three versions of SNMP are most commonly used: SNMP v1, SNMP v2 and SNMP v3. Theboth versions 1 and 2 are similar in function except that in v2 security has been enhanced to International Journal of Research in IT, Management and Engineering www.gjmr.org 3
  • 5. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 overcome the security issues. Keeping in view the importance of security a new version SNMPv3 was developed that covers all the security issues and provide more features like remoteconfiguration.SNMP v1 is placed inside the layers of OSI and performs its functions independently withoutany disturbance to those OSI layers. SNMPv1 is most commonly used protocols in early daysand before the invention of next version. An NMS generates a request to devices and devicesrespond back to these requests. There are four operations used in v1: Get, Get Next, Set, andTrap. The Get command used to request objects their values by the NMS. The Get Nextoperation is used to request the next value in the table. The Set operation used to fix the valuesinside SNMP agent. The last operation that is used for updating any change of the network toNMS is Trap. The basic limitations in version 1 are the security i.e. message authentication andprotection from outside intruders. SNMP v2 was designed in 1993 to overcome above problemsand was to be an improvement of its ancestor.SNMPv2 was modified then with GetBulk and Inform operation after version 1. The GetBulkfunction collects the huge block of information simultaneously and provides access to NMS tothis information. And Inform function is used in communication of one NMS with another NMSusing trap operation and then receives a response from other NMS. The major area enhanced inSNMP v2 was security that makes developers for its invention. SNMP v2 has different messageformats. The difference in version 1 and 2 is purely in the field of security. However messageformat is same as of version 1 in the UDP for version 2. More security and remote configurationis added in newer version SNMP V3 that protects messages and provide an easy module toaccess these messages for SNMP.A new characteristic that was not available in previous versions is the user friendly view modulefor SNMPv3 addition. This feature allows the elements to control the access to the importantinformation. SNMP engine having VACM that is consists of many message formats withdifferent security models. This improvement in NMS and SNMP is suitable for all types ofhardware. In SNMPv3 security is modified into three levels: upper level is authentication andprivacy, middle level is authentication with no privacy and the bottom level is no authentication International Journal of Research in IT, Management and Engineering www.gjmr.org 4
  • 6. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 no privacy. SNMP has the ability to reboot the network devices due to its security features.Below figure 3.4.3 shows security subsystem of SNMP v3 (Swee, 2006).COMPARATIVE STUDY OF EXISTING SYSTEMSIt is a basic requirement that the network which I selected must have the capability to reduce theproblems and other issues of traffic concerning with the delay, response time and throughput.Several materials are existing on the internet or market as concern to these networks and theirrelevant problems, furthermore several procedure also exist concerning to the each kind ofnetworks. But the research is concerned with the performance analysis of NMS protocols andselecting best one protocol from them. Certain issues are there regarding to the types of traffic,throughput, latency and network availability. These issues are very common and challenging forthe administration especially in those organizations having WAN link contains the routingdevices. Such organizations can suffer from various kinds of issues regarding to the traffic delaysif the careful selection of the proper network is not made by suspicious investigation.RESULTSI have analyzed security of SNMP in this research thesis to conclude which is best to be used innetwork. I have examined two techniques of security for secure SNMP traffic: firstly SNMPv3,most up-to-date invention of SNMP and non secure version of SNMP in a combination ofInternet Protocol Security (IPSec). The security used in SNMP V2 consumes less networkcapacity as compare to SNMPv3 and also provides security to IP application which is notpossible in SNMP v3. Also reduces load on administrators in configuring, managing, andmaintaining monitoring systems so that their concentration is focused more on higher levelpolicies and critical abnormal circumstances also discusses in previous chapter.Result 1 for one variableThe network capacity used by SNMP is examine by running the SNMP agent with the help of anSNMP management function. The IPSec used a tunnel mode security mechanism tocommunicate between the gateways. Ethereal captured the IP packets generated by SNMPoperations running of the host machine are shown in below table 3.3.1. International Journal of Research in IT, Management and Engineering www.gjmr.org 5
  • 7. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  SNMP Version / Get Response Total Security Scheme V2c 78 102 180 V2c over IPSec 137 153 288 V3 noAuthNoPriv 141 165 306 V3 authNoPriv 153 177 330 V3 authPriv 168 192 358V3 noAuthNoPriv over 191 217 408 IPSec V3 authNoPriv over 209 233 440 IPSecV3 authPriv over IPSec 223 249 472Table 1 shows the SNMP-Get messages, SNMP-Response messages and the total of SNMPGet/Response sizes in byte using different security schemes for one variable.Result 2 for seven variablesThe second result is almost same as we get the first except it is obtain using 7 variables. SNMP Version / Security Get Response Total Scheme V2c 176 288 464 V2c over IPSec 233 345 578 V3 noAuthNoPriv 249 351 590 V3 authNoPriv 251 363 614 V3 authPriv 265 378 643 V3 noAuthNoPriv over IPSec 289 401 690 International Journal of Research in IT, Management and Engineering www.gjmr.org 6
  • 8. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  V3 authNoPriv over IPSec 305 417 722 V3 authPriv over IPSec 321 433 754Table 2 shows the SNMP-Get messages, SNMP-Response messages and the total of SNMPGet/Response sizes in byte using different security schemes for seven variables.From the above results we can conclude that the IPSec using authentication and triple-DESencryption scheme consume 57 bytes more than the normal IP packet moving this payload. AlsoSNMPv3 consume 89 bytes more than the normal IP packet by using HMAC-MD5- 96authentication and DES encryption schemes.RESULT 3 NETWORK CAPACITY CONSUMED BY SNMPThe SNMP agent running on gateways is used to get the processing time consumed by a secureSNMP operation. Ethereal captured the IP packets generated by the SNMP-Get operationrunning on observer host. We use node to node tunnel-mode security connection to distinguishthe source of packet and destination of packet. As DES encryption scheme processing iscomputationally extremely intensive and by using triple-DES adds three times more processingthan DES. But we can experiment to draw results to gain insight conclusions. The Processingtime interval can be define as the time from capturing the SNMP Get message by Ethereal to thetime corresponding the SNMP Response Message. Table 3.3 shows the average processing timeinterval and the standard deviation calculated for both approach. Mean Time SNMP Version / Security Scheme Standard Deviation V2c 310.4 12.2 V3 noAuthNoPriv 525.9 6.5 V3 AuthNoPriv 591.7 6.1 V3 AuthPriv 696.8 57.7 V2c over IPSerc 778.8 80.1 V3 noAuthNoPriv over IPSec 1057.0 19.4 International Journal of Research in IT, Management and Engineering www.gjmr.org 7
  • 9. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  21.2 V3 AuthNoPriv over IPSec 1160.0 V3 AuthPriv over IPSec 1457.7 79.5Table 3 shows the network capacity consumed by SNMP.RESULT 4 CAPACITY CONSUMED BY SNMP V3 FOR DISCOVERING EXCHANGEWe calculate the capacity consumed by SNMPv3 during discovering exchange for SNMP-Getmessage, its corresponding SNMP-Report message and the total bytes used in discoveryexchange. From the result shown below we can predict that a SNMPv3 discovery exchange issame in size and function to a typical SNMP Get/Response exchange. A more stylish SNMPmanagement suite remembers the most recent timeliness parameters received from eachSNMPv3 unit to which it communicates, thus reducing the need for discovery exchanges. SNMP Version Request Report Total SNMP V3 AuthPriv 102 139 241 SNMP V3 AuthPriv 159 193 352 over IPSecTable 4 shows capacity consumed by SNMP v3 for discovering exchange.RESULT 5 CAPACITY CONSUMED BY AN IPSECTo get the result of network capacity consumed by IPSec Free S/WAN IPSec tool is configuredto keep informed about security between the gateways every minute. Many of these updates arealso capture by the ethereal application running on host observer. Below table shows the IPpacket sizes (in bytes) for all nine packets captured while the initial tunnel-mode securityassociation is established. Packet # Mode Length 1 Main 204 2 Main 108 International Journal of Research in IT, Management and Engineering www.gjmr.org 8
  • 10. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  3 Main 208 4 Main 208 5 Main 96 6 Main 96 7 Quick 344 8 Quick 320 9 Quick 80Table 5 shows network capacity consumed by IPSec.SUMMARY / CONCLUSIONFrom the obtained results in previous chapter, we conclude that the version 3 of SNMP required24 % more capacity of network than the use of SNMP v2 with IPSec design. Also with thechange in the size of application layer, the output of SNMP v2 with IPSec changes significantly.Both techniques SNMPv2 over IPSec and SNMPv3 overheads network devices equally. It willdoubles the processing overhead of devices in SNMP v2 when used authentication andencryption schemes and when installing IPSec on that device. We can get better results if weused security and SNMP processing on separate devices. The security gateway is different fromnetwork devices where SNMP agent is implemented in case of SNMP v2 over IPSec. Howeverin SNMP v3 both security processing and SNMP processing are running on single devices whichcreates problems to implement SNMP v3.The discovery exchange with SNMP v3 consumes 240 more bytes of network capacity. Thecomplexity of SNMP application effect on discovery exchanges frequency. There is no AsSNMP application has no feature to store the parameters of timelines, hence efficiency ofnetwork capacity badly affected in discovering process making network more overloaded.REFERENCES International Journal of Research in IT, Management and Engineering www.gjmr.org 9
  • 11. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 Amir, E. and S. McCanne 2003. An active service framework and its application,Communications Architectures and Protocols, pp: 178–189.Apostolopoulos, T. and V. Daskalou 1995. On the Implementation of a Prototype forPerformance Management Services, IEEE symposium on computers and communications, 57-63. A research paper on a prototype for management services.Behrouz, A. F. 2004. TCP-IP Protocol Suit, McGraw Hill publication, pp: 156-163.Bettati R. 2008. Modern Fault Trace Analysis and its Capabilities Department of ComputerScience and Center for Information Assurance and Security Texas A&M University CollegeStation, TX, 77801,USABierman, A. and L. Bucci 2002. Remote Network Monitoring MIB Protocol Identifiers,Proposed technical specification for RMON2 protocol identifiers, pp: 194-220.Blum A. and D. Song 2004. Monitoring and Measurements of network bounds. In Proceedingsof the 7th International Symposium on Recent Advances in Intrusion Detection, RAID ’04,September 2004.Bradley, M. 2002. Remote Network Monitoring MIB Extensions for Switched Networksproposed technical specification for RMON of switched networks, pp: 51-68.Symantec Internet Security threat report highlights (Symantec.com),http://www.prdomain.com/companies/Symantec/newreleases/Symantec_internet_205032.htmAccessed on 15 May 2011.Chang, C. and L. Sung. 2008. Integration and Application of Web-Service-Based Expert Systemand Computer Maintenance Management Information System. In Proceedings of the 2008 IEEEAsia-Pacific Services Computing Conference, pp: 207-212.Cheswick R. 2002. Firewall and Internet Security, Addison Wesley Professional ComputingSeries; pp: 201-223. International Journal of Research in IT, Management and Engineering www.gjmr.org 10
  • 12. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 Corey V. and C. Peterman 2005. IEEE Internet Computing Volume 6, Issue 6 Pages: 60 – 66.Year of Publication: 2002 ISSN: 1089-7801Cottrell, L. and C. Logg. 2004. Network monitoring for the LAN and WAN,http://www.slac.stanford.edu/grp/scs/net/talk/ornl-96/ornl.html,A tutorial paper on monitoring onWide Area Network including the internet.Ergin, M., K. Ramachandran and M. Gruteser 2007. Understanding the effect of access pointdensity on wireless LAN performance, International Conference on Mobile Computing andNetworking Proceedings of the 13th annual ACM international conference on Mobile computingand networking, pp: 62-64.Gast, M. 2002. 802.11 wireless networks: the definitive guide, Wiley, pp: 85-89.Huges, J. 1996.Characterizing Network Behavior Using Remote Monitoring DevicesTelecommunications, pp: 43-44.Jung H.J. and J.Y.Choen 2007. Real-time network monitoring scheme based on SNMP fordynamic information, Journal of Network and computer Applications, 30 (1), pp: 331-353. International Journal of Research in IT, Management and Engineering www.gjmr.org 11
  • 13. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  QUALITY OF WORKING LIFE IN INSURANCE SECTORRita Goyal* ABSTRACTThe study of Quality of working life has been an important and critical area in management andorganizational performance from last several years especially in the LIC.. This paper aims tostudy the extent of QWL in the LIC, and explores the proposed link between the QWL andemployees productivity. Two hundred fifty employees responded to the researcher’squestionnaire. The study makes use of statistical techniques such as mean, standard deviation, ttest. ANOVA analysis to process and analysis the data collected for this study .The demographicportion of the instrument was developed by the researcher to sort out the demographicinformation. To explore difference between the means of two group t-test was applied. One wayANOVA was used for exploring the difference among more than two groups. The paper ends byoffering useful suggestions to the management involved in the operations of the corporations.Key words: Quality of working life, Insurance Sector, Competency Development, EmployeesProductivity, Work-Life Balance*Lecturer Dept. of Humanities and Social Sciences, Maharishi Markendeshwar University,Mullana (Ambala) International Journal of Research in IT, Management and Engineering www.gjmr.org 12
  • 14. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 INTRODUCTIONQuality of Working Life is a process of work organizations which enables its members at alllevels to actively participate in shaping the organization environment, methods and outcomes.Conceptual categories which together make up the quality of working life are adequate and faircompensation, safe and healthy working conditions, immediate opportunity to use and develophuman capacities, opportunity for continued growth and security, social integration in the workorganization, constitutionalization in the work organization, work and the total life space and thesocial relevance of work life. Quality of Work Life was the term actually introduced in the late1960’s. From that period till now the term is gaining more and more importance everywhere, atevery work place. Initially quality of work life was focusing on the effects of employment on thegeneral well being and the health of the workers. But now its focus has been changed. Everyorganization need to give good environment to their workers including all financial and nonfinancial incentives so that they can retain their employees for the longer period and for theachievement of the organization goals. The concept of QWL is based on the assumption that ajob is more than just a job. It is the center of a person’s life. In recent years there has beenincreasing concern for QWL due to several factors: Increase in education level and consequentlyjob aspirations of employees; Association of workers; Significance of human resourcemanagement; widespread industrial unrest; Growing of knowledge in human behaviors, etc.LITERATURE REVIEWSBear field, (2003) used 16 questions to examine quality of working life, and distinguishedbetween causes of dissatisfaction in professionals, intermediate clerical, sales and serviceworkers, indicating that different concerns might have to be addressed for different groups. Thedistinction made between job satisfaction and dissatisfaction in quality of working life reflectsthe influence of job satisfaction theories. Lawler, (2004) Quality of Working Life is not aunitary concept, but has been seen as incorporating a hierarchy of perspectives that not onlyinclude work-based factors such as job satisfaction, satisfaction with pay and relationships withwork colleagues, but also factors that broadly reflect life satisfaction and general feelings ofwell-being suggested that quality of working life was associated with satisfaction with wages,hours and working conditions, describing the “basic elements of a good quality of work life” as: International Journal of Research in IT, Management and Engineering www.gjmr.org 13
  • 15. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  safe work environment, equitable wages, Equal employment opportunities and opportunities for advancement.Waddell Jane and Carr Paul (2005) In addition to competition of globalization and products,organization face competition related to employee retention at the same time employees facecompetition for their time. As increasing number of employees face competing demands betweenwork and family, the importance of maintaining a healthy work life balance is of paramountconsideration. In spite of family- friendly policies, many employees perceive negativeconsequences associated with availing themselves of these policies. At the same time, over 50%of American employees fail to take their allotted vacation time. Failure to achieve a healthy worklife balance can lead to overload, which may result in loss of employees. Encouraging a healthywork life balance benefits both the organization and the employees. Lawler and Porter (2006).An individual’s experience of satisfaction or dissatisfaction can be substantially rooted in theirperception, rather than simply reflecting their “real world”. Further, an individual’s perceptioncan be affected by relative comparison – am I paid as much as that person - and comparisons ofinternalized ideals, aspirations, and expectations, for example, with the individual’s current stateIn summary, where it has been considered, authors differ in their views on the core constituentsof Quality of Working Life (e.g. Sirgy, Efraty, Siegel & Lee, 2001 and Warr, Cook & Wall,1979). It has generally been agreed however that Quality of Working Life is conceptually similarto well-being of employees but differs from job satisfaction which solely represents theworkplace domain. Banerjee Indranil (2006) Jobs are getting increasingly demanding, as theorganization face competition and become leaner in structure, leading to conflict betweenpeople’s professionals deliverable and personal requirements. It is acknowledged that continuousdisregard of personal issues ultimately lead to employees’ underperformance and so people oftendiscuss work life balance but seldom act on it. So, the focus now is “Who is going to bell thecat?” For tackling the problem, multi-pronged effort, comprising the organization, the employee,the Government, the Industry, the society, etc., is required. Tekuru Siva ram (2007) Work- lifebalance is all about need for individuals having complete control over their work, i.e. decidingwhen, why, where and how to work. Finding these pressures encroaching into their private lifeand time, they are unable to do anything about it and are finally squeezed out. Organizationshould consider Work –life balance as an extension of the fringe benefits offered to the International Journal of Research in IT, Management and Engineering www.gjmr.org 14
  • 16. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 employees. This will help both the employees and the organization. Aggarwala Tanuja (2007)Conflicting demands and pressures from works and life (family) can interfere with each othersince the two domains are complementary, not conflicting priorities. Acceptance of this realityby the organization and new business and societal trends, have seen the growth of family-friendly practices at work place. Adopting a win- win approach, growing number of organizationbelieve that helping employees balance and integrate their work lives with the rest of their livesleads to positive outcomes for both the employee and the employer. Work- family practicesshould be viewed as a part of overall HR and business strategy that is related to a firm’scompetitive advantage. Swamy (2007) In today’s business context the pressures of work havebeen intensifying and there is a growing feeling among employees that the demand of workbeing to dominate life and a sense of work-life imbalance is felt. The challenge of integratingwork and family life is a part of everyday reality for the majority of employees. Organizationshave to continually innovate and come up with programs that provide scope for employees tobalance their responsibility at their work place and interest they have outside work.Suman Ghalawat (2010) states that QWL is a Process of work organizations which enables itsmembers at all levels to actively  participate in shaping the organizations’ environment, methodsand outcomes. This value based process is aimed towards meeting the twin goals of enhancedeffectiveness of organization and improved quality of the life at work for employees. Work is anintegral part of our everyday life, as it is our livelihood or career or business. On an average wespend around twelve hours daily in the work place, that is one third of our entire life; it doesinfluence the overall quality of our life. It should yield job satisfaction, give peace of mind, afulfillment of having done a task, as it is expected, without any flaw and having spent the timefruitfully, constructively and purposefully. Even if it is a small step towards our lifetime goal, atthe end of the day it gives satisfaction and eagerness to look forward to the next day. The factorsthat influence and decide the Quality of Work Life are: Attitude, environment, opportunities,nature of job, people, stress level, career prospects, growth and development, risk involved andreward.OBJECTIVES OF STUDYIn light of the domain for research, the study was undertaken:- International Journal of Research in IT, Management and Engineering www.gjmr.org 15
  • 17. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 1. To examine the nature of quality of working life prevailing in some selected Branches of LIC.2. To study the differences in the perception of employees on the basis of gender.3. To study the differences in the perception of employees on the basis of designation.4. To study the differences in the perception of employees on the basis of Qualification.HYPOTHESISIn view of the objectives set for the study, following null hypothesis was formulated:Ho1.1 There is no significant difference between the perception of male and female employeesregarding quality of working life.Ho1.2There is no significant difference between the perceptions of employees at different levelsregarding quality of working lifeHo1.3 There is no significant difference between the perception of graduate and post graduateemployees regarding quality of working life.RESEARCH METHODOLOGYDataA total of 400 employees were chosen randomly from the 4branches, keeping in view their totalstrength and range of activities. Out of 400 questionnaires distributed only 250questionnaireswere received completed in all respects. Therefore with 62.5% response rate the researcher hasconducted this study.SAMPLE OF THE STUDYFollowing table represents the sample of study: Gender-wise distribution of employees N Percent Male 185 74 Female 65 26 Total 250 100 International Journal of Research in IT, Management and Engineering www.gjmr.org 16
  • 18. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  Designation-wise distribution of employees Employees N Percent Class-1 100 40 Class-11 69 27.6 Class-111 81 32. 4 Total 250 100Qualification wise distribution of Employees Employees No. Percent Graduate 140 56 Post Graduate 110 44 Total 250 100QUESTIONNAIREThe questions were designed to facilitate the respondents to identify major strengths andweakness of the Corporations and provide insights. The endeavors were to identify the keyquality of working life issues, on which employee’s perception can be obtained. The respondentswere requested specifically to ignore their personal prejudices and use their best judgment on a 5point Likert scale. The purpose of this exercise was to make the response a true reflection oforganization reality rather than an individual opinion. The 5 point of the scale indicated in thequestionnaire are- 1. Strongly disagree, 2 disagree, 3-Undecided, 4-Agree and 5- Strongly Agree.Reliability (Cronbach’s coefficient alpha) of the questionnaire has found to be 0.89.This showsdata has satisfactory internal consistency.Descriptive Analysis:Result & DiscussionThe results in the following table reveal that in the scale for quality of working Life, the highestmean score (44.29) is for male and the lowest (33.56) is for level III employees. The same hasbeen shown graphically in figure1.1 International Journal of Research in IT, Management and Engineering www.gjmr.org 17
  • 19. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 Summary of “t”test presented in the table 1.2 indicates that t-value (1.60) is significant as p-value (.110) is more than 0.05.Hence the hypothesis stating the difference is not significantbetween the perception of male and female employees regarding. Quality of working life isaccepted at 0.05 level of significance. So there is not a significant difference between theperception of male and female employees regarding quality of working life.Mean value for males (74.29) is less than females (78.89) therefore it is concluded that femaleemployees have better perception of QWC than male employees.Summary of the univariate analysis of variance presented in the table 1.3 indicates that p-value(0.232) is greater than 0.05as F value (1.469) is not significant at 0.05 level of significance.Hence the hypothesis is accepted at 0.05 level of significance, so there is no significantdifference among the perception of employees at different levels regarding quality of workinglife.Summary of “t”test presented in the table 1.4 indicates that t-value (.348) is significant as p-value (0.728) is more than 0.05.Hence the hypothesis stating, The difference is not significantbetween the perception of graduate and post graduates employees regarding QWC. “Is acceptedat 0.05 level of significance. So there is not a significant difference between the perception ofgraduate and post graduate employees regarding QWC in selected branches of LIC.Mean value for graduate (34.69) is less than Postgraduate Employees (35.58) therefore it isconcluded that post graduate employees have better perception of QWC than graduateemployees. Thus findings are:The difference is not significant between the perception of male and female employees regardingquality of working life. It shows that gender does not affect the perception of QWL System ofemployees as all are equally aware of the significance of it.There is no significant difference among the perception of employees at different levelsregarding quality of working life. As all are equally aware of the significance of it. It shows thatthe need of the employee’s development is felt in all cases. The difference is not significantbetween the perception of Graduates and Post Graduates employees regarding the quality ofwork life in selected branches of LIC. As both areas are equally related to improvement andprogress. International Journal of Research in IT, Management and Engineering www.gjmr.org 18
  • 20. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 CONCLUSIONIn LIC, Quality of Working Life principles are the principle of security, the principle of equity,the principle of individuation and the principle of democracy. On the basis of my study I can saythat employees of LIC in Northern region are happy with the working conditions of the LIC.They feel that they are safe and secure in LIC. They feel that corporation should start their owntransport facilities for the staff. However, the dissatisfaction among them is the less growthopportunities. They are not provided with extra care like health camps etc Poor work life balanceleads to many disastrous things like tardy, bad performance, lack of motivation, more errors,absence from work and so on. The worst thing is that poor work-life balance reduces workquality and productivity without any doubt. When an employee wont be able to give time to hisfamily at home, he will feel stressed out at work Sound work life balance will definitely have apositive impact on employee’s productivity. The quality of work improves significantly asemployees feel fresh and not stressed out at all.Suggestion1.Corporation must be committed to an open and transparent style of operation that includesharing appropriate information with employees and sincerely inviting their input regardingproblems opportunities and implementation of improvement plans.2. Employees must be given opportunities for advancement in the corporation.3. Traditional status barriers between different classes must be broken to permit establishment ofan atmosphere of trust and open communication.4. Employees should receive feed back on results achieved and recognition for superiorperformance. Other forms of positive reinforcement such as financial incentives should also bemade available where feasible.5. Improved communication and co-ordination among the workers and organization helps tointegrate different jobs resulting in better task performance.6. Better working condition enhances workers motivation to work in a healthy atmosphereresulting in motivation and increase in production.7. As QWL includes participation in group discussion and solving the problem, improving theskill, enhancing their capabilities and thus building confidence and increased output. International Journal of Research in IT, Management and Engineering www.gjmr.org 19
  • 21. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 REFERENCES:Anonymous (2005). Quality of Work Life Task Force looks to integrate home and work.Vanderbilt University Medical Center, House Organ. Available from http://www.Quality20%of/20%work/20% life. htm.Anbarasan, V & Mehta, N. (2009), "An Exploratory Study on Perceived Quality of Working Lifeamong Sales Professionals Employed in Pharmaceuticals, Banking, Finance and InsuranceCompanies in Mumbai", Abhigyan, 27(1): 70-81.Ebrahim (2010) “The relation between QWL and job satisfaction”, Middle –East Journal ofscientific Research 6(4), 317-323-2010.Feuer, D., Quality of work life: a cure for all ills? Training: The Magazine of Human ResourcesDevelopment, 26: 65-66, 1989.Mishra, S. & Gupta, B. (2009), "Work Place Motivators and Employees Satisfaction: A Studyon Retail Sector in India", The Journal of Industrial Relations, 44(3): 509-17.Raduan,C. R., Loosee .B., Jegak,U & Khairuddin, I. (2006), "Quality of Work Life: Implicationsof Career Dimensions", Journal of Social Sciences. 2 (2): 61-67.Sandrick k (2003). Putting the emphasis on employees as an award. Winning employer, Baptisthealth care has distant memories of the workforce shortage, Trustee. pp. 6-Straw, R.J. and C.C. Heckscher, 1984. QWL: New working relationships in the communicationindustry. Labor Studies J., Vol. 9: 261-274.Walton, R. (1973), ― Quality of Work life Indicators- Prospects and Problems- A PortigalMeasuring the Quality of working life, pp-57-70, Ottawa International Journal of Research in IT, Management and Engineering www.gjmr.org 20
  • 22. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 Table 1.1: Scale for Quality of working LifeFactor No. Mean S.DGender-Male 185 44.29 19.85Female 65 38.89 20.13Designation-Level 1 100 39.27 18.69Level 11 69 34.72 20.88Level 111 81 33.56 22.86Qualification- 140 34.69 19.34GraduatePost Graduate 110 35.58 20.95Tab 1.2 Perceptual differences between male and female employees regarding quality ofworking life.Group Sample Mean S.D. t- value df p-value sizeMale 185 44.29 19.85 1.60 248 .110EmployeeFemale 65 48.89 20.13EmployeesP>0.05 International Journal of Research in IT, Management and Engineering www.gjmr.org 21
  • 23. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 Tab.1.3 Perceptual differences between employees at different level regarding quality ofworking life. Particulars Sample size Mean d.f F value P value Class-1 100 39.27 2 1.469 0.232 Class-11 69 34.72 Class-111 81 33.56 P>0.05Tab1.4: Perceptual differences between Employees with graduate and postgraduatequalification regarding quality of working life. Particulars Sample Size Mean SD t-test df p-Value Graduate 140 34.69 19.34 .348 248 .728 Employee Postgraduate 110 35.58 20.95 EmployeesP>0.05 International Journal of Research in IT, Management and Engineering www.gjmr.org 22
  • 24. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  REFACTORABILITY ANALYSIS USING LINEAR REGRESSIONGauri Khurana*Sonika Jindal ** ABSTRACT Software refactoring - improving the internal structure of the software without changing itsexternal behavior - is an important action towards avoiding software quality decay. Key tothis activity is the identification of portions of the source code that offers opportunities forrefactoring -- the so called bad smells. The underlying objective is to improve the quality ofthe software system, with regard to future maintenance and development activities. The goalof this review paper is the discussion of an approach to help on the detection of code badsmells through source code metrics and the results obtained from its use. In this discussion,we propose measure of refactorability based on the four factors- reusability,understandability, modifiability and maintainability. Since, each of the factors is intangible innature and is hard to measure. It is also proposed that they should be measured in terms ofpoint system. It is also important to bring new elements that might be affected through arefactoring sequence as, for example, structural testing requirements that can be used in thefuture as a new metric to detect refactoring opportunities.Keywords: Refactoring, reusability, understandability, modifiability, maintainability, badsmell, metrics*CSE, SBSCET, Ferozpur. PTU, Jalandhar** Assistant Professor, Department of Computer Science, SBSCET, Ferozpur. PTU,Jalandhar. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     23 
  • 25. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  1. INTRODUCTION 1.1 Introduction to refactoringRefactoring is a well-defined process that improves the quality of systems and allowsdevelopers to repair code that is becoming hard to maintain, without throwing away theexisting source code and starting again. By careful application of refactorings the system’sbehavior will remain the same, but return to a well-structured design. The use of automatedrefactoring tools makes it more likely that the developer will perform the necessaryrefactorings, since the tools are much quicker and reduce chance of introducing bugs.“Refactoring is the process of changing a software system in such a way that it does not alterthe external behavior of the code yet it improves its internal structure.”-Martin Flower inRefactoring, Improving the Design of Existing Code.Refactoring is a kind of reorganization. Technically, it comes from mathematics when youfactor an expression into an equivalence- the factors are cleaner ways of expressing the samestatement. Refactoring implies equivalence- the beginning and the end product must befunctionally identical. The shift from Structured Programming to Object-orientedProgramming is a fundamental example of refactoring. [1]“Refactoring is the process of taking an object design and rearranging it in various ways tomake the design more flexible and/or usable.” – Ralph Johnson.Four Reasons to change the code:The four primary reasons to change the code are [2]: 1. Adding a feature 2. Fixing a bug 3. Improving the design 4. Optimizing resource usage 1.2 Preserving BehaviorFeature addition and bug fixing are very much like refactoring and optimization. In all casesof changing code, we want to change some functionality, some behavior, but we want topreserve much more (see Figure 1) International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     24 
  • 26. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  Existing Behavior New Behavior Figure 1: Preserving Behavior [2]Figure 1 shows what is supposed to happen when we make changes, but what does it meanfor us practically? On the positive side, it seems to tell us what we have to concentrate on.We have to make sure that small numbers of things that we change are changed correctly. Onthe negative side, that isn’t the only thing we have to concentrate on. We have to figure outhow to preserve the rest of the behavior. The amount of behavior to be preserved is usuallyvery large.Preserving behavior is a large challenge. When we need to make changes and preservebehavior, it can involve considerable risk. [2] To mitigate risk, we have to ask threequestions: 1. What changes do we have to make? 2. How will we know that we’ve done them correctly? 3. How will we know that we haven’t broken anything? 1.3 Why do we need refactoring?The longer object oriented systems are in use, the more probable it is that these systems haveto be maintained [3], i.e. they have to be optimized to a given goal (Perfective Maintenance),they have to be corrected with respect to identified defects (Corrective Maintenance) and theyhave to be adjusted to a changing environment (Adaptive Maintenance). Whereas many ofthese activities can be subsumed under the reengineering area, there are additional changingactivities that are much less difficult to apply than typical reengineering activities, and whichdoes not change the external behavior [4]. The main goal of these “mini-reengineeringactivities” is to improve the understandability and to simplify reengineering activities. Flowercalls these activities Refactorings, which he defines a “a change made to the internalstructure of a software to make it easier to understand and cheaper to modify withoutchanging its observable behavior” [1, p. 53]. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     25 
  • 27. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 Fowler suggests four purposes of refactoring [1]: 1. Improve the design of software – Through accumulating code changes, code loses its structure, thereby increasingly drifting towards a state of decay. Refactoring can be used to cure software decay by redistributing parts of the code to the “right” places, and by removing duplicated code. The claim that refactoring can improve the design of software is confirmed by [3] with regard to cohesion and with respect to coupling, as indicators for internal software quality. Another claimed benefit in the area of improved design is improved flexibility. 2. Make software easier to understand – Refactoring can help make the code more readable by making it better communicate its purpose. A different way in which refactoring supports program understanding is in reflecting hypotheses about the purpose of the code by changing the code, and afterwards testing that understanding through rerunning the code. The suggested process to do so is to start refactoring the little details to clarify the code, thereby exposing the design. The potential to improve understandability through refactoring is confirmed by many authors [1, 3]. In more specific terms, [5] discusses how refactorings can be used to improve communicating the purpose of the code. 3. Help find bugs – Through clarifying the structure of the code, the assumptions within the code are also clarified, making it easier to find bugs. 4. Program faster – Through improving the design and overall understandability of the code, rapid software development is supported. 1.4 When should one consider refactoring?Ideally, refactoring would be part of a continuing quality improvement process. In otherwords, refactoring would be seamlessly interwoven with other day-to-day activities of everysoftware developer.Refactoring may be useful, when a bug has surfaced and the problem needs to be fixed or thecode needs to be extended. Refactoring at the same time as maintenance or adding newfeatures also makes management and developers more likely to allow it, since it will notrequire an extra phase of testing.If the developer in charge finds it difficult to understand the code, he will (hopefully) askquestions, and begin to document the incomprehensible code.Often, however, schedule pressures do not permit to implement a clean solution right away.A feature might have to be added in a hurry, a bug patched rather than fixed. In these cases, International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     26 
  • 28. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 the code in question should be marked with a FIXME note, in order to be reworked, whentime permits. Such circumstances call not for individual refactorings, but for a wholerefactoring project. When the time has come to address the accumulated problems, a scan forFIXMEs, TODOs, etc. over the code base will return all the trouble spots for review. Theycan be refactored according to priority. 2. SEMANTIC GAPThe concept of Semantic gap is relevant whenever a human activity, observation and task aretransferred into computational representation [6]. Like programs, programming languages arenot only mathematical objects but also software engineering artifacts. Describing thesemantics of real-world languages can help bring language theory to bear on both excitingand important real-world problems. Achieving this is not purely a mathematical task, butequally one of (semantic) engineering. The implementations of all major languages—especially scripting languages defined by implementations—come with large and well-structured test suites. These suites embody the intended semantics of the language. Weshould be able to use such a test suite to retrofit semantics. For this to be useful, it is notsufficient to merely create semantics for the core language [4].  More precisely the gap means the difference between contextual knowledge in a powerful language (e.g. natural language) and its reproducible and computational representation in a formal language (e.g. programming language).  The semantic gap actually opens between the selection of the rules and the representation of the task.With the passage of time, the business scenario keeps on changing and the softwaredevelopment must match the business environment. Therefore the code of any software alsochanges with respect to the business scenario. There might be architectural changes insoftware due to business reengineering process. The programmer has to rethink how to do theimplementation of the code due to changes in the requirements. So, it offers opportunity torelook, redesign, as well as refactor the code. Thus, it forces new semantics to be laid withrespect to the changing business scenario. 3. REFACTORING ACTIVITIESThe refactoring process consists of a number of different activities, each of which can beautomated to a certain extent [7]: International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     27 
  • 29. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 1. Identify where the code should be refactored;2. Determine which refactorings should be applied to the identified places;3. Guarantee that the applied refactoring preserves behavior;4. Apply the refactoring;5. Assess the effect of refactoring on software quality characteristics;6. Maintain consistency between refactored program code and other software artifacts (or vice versa).The steps taken when applying the refactoring should be small enough to oversee theconsequences they have and reproducible to allow others to understand them. Generalizedrefactoring steps in away, are mere a rule that can be applied to any structure.Refactoring not only covers the mechanics of restructuring, but also addresses the followingissues [Martin Flower]:1. Refactoring emphasizes that, in absence of more formal guarantees, testing should be used to ensure that each restructuring is behavior preserving. A rich test suite should be built, which must be run before and after each test is applied.2. Refactorings are described in a catalog, using a template reminiscent of design patterns.3. Refactorings are applied in small steps, one by one, running the test suite after every step to make it into commercial development tools. 4. METRICS FOR REFACTORABILITYThe various metrics are identified for calculating the values of four factors proposed hereseparately. Those are defined as follows: 1. LinesOfCode (NbLines): The LOC for a method is equals to the number of sequence point found for this method in the file. A sequence point is used to mark a spot in the IL code that corresponds to a specific location in the original source. Notice that sequence points which correspond to braces ‘{‘ and ‘}’ are not taken into account. Interfaces, abstract methods and enumerations have a LOC equals to 0. Only concrete code that is effectively executed is considered when computing LOC. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     28 
  • 30. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619   Namespaces, types, fields and methods declarations are not considered as line of code because they don’t have corresponding sequence points.  LOC computed from an anonymous method doesn’t interfere with the LOC of its outer declaring methods. Recommendations: Methods where LinesOfCode is higher than 20 are hard to understand and maintain. Methods where ILInstructions is higher than 40 are extremely complex and should be split in smaller methods (except if they are automatically generated by a tool). 2. LinesOfComment(NbComments): This metric can be computed only if PDB files are present and if corresponding source files can be found. The number of lines of comment is computed as follow:  For a method, it is the number of lines of comment that can be found in its body. If a method contains an anonymous method, lines of comment defined in the anonymous method are not counted for the outer method but are counted for the anonymous method.  For a type, it is the sum of the number of lines of comment that can be found in each of its partial definition.  For a namespace, it is the sum of the number of lines of comment that can be found in each of its partial definition.  For an assembly, it is the sum of the number of lines of comment that can be found in each of its source file. Notice that this metric is not an additive metric (i.e. for example, the number of lines of comment of a namespace can be greater than the number of lines of comment over all its types). Recommendations: This metric is not helpful to asses the quality of source code. We prefer to use the metric PercentageComment. 3. NbMethods: The number of methods. A method can be an abstract, virtual or non- virtual method, a method declared in an interface, a constructor, a class constructor, a finalizer, a property/indexer getter or setter, an event adder or remover. Recommendations: Types where NbMethods > 20 might be hard to understand and International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     29 
  • 31. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  maintain but there might be cases where it is relevant to have a high value for NbMethods. 4. NbFields: The number of fields. A field can be a regular field, an enumerations value or a read only or a const field. Recommendations: Types that are not enumeration and where NbFields is higher 20 might be hard to understand and maintain but there might be cases where it is relevant to have a high value for NbFields. 5. Afferent coupling (Ca): The number of types outside this assembly that depend on types within this assembly. High afferent coupling indicates that the concerned assemblies have many responsibilities. 6. Efferent coupling (Ce): The number of types outside this assembly used by child types of this assembly. High efferent coupling indicates that the concerned assembly is dependant. There is a whole range of interesting code metrics relative to coupling. The simplest ones are named Afferent Coupling (Ca) and Efferent Coupling (Ce). Basically, the Ca for a code element is the number of code elements that use it and the Ce is the number of code elements that it uses. Figure 2: Afferent and Efferent Coupling You can define Ca and Ce for the graph of assemblies dependencies, the graph of namespaces dependencies, the graph of types dependencies and the graph of methods dependencies of a code base. You can also define the Ca metric on the fields of a program as the number of methods that access the field. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     30 
  • 32. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  7. Cyclomatic Complexity (CC): Cyclomatic complexity is a popular procedural software metric equal to the number of decisions that can be taken in a procedure. Concretely, in C# the CC of a method is 1 + {the number of following expressions found in the body of the method }: if | while | for | foreach | case | default | continue | goto | && | || | catch | ternary operator? : | ?? Following expressions are notcounted for CC computation: else | do | switch | try | using | throw | finally | return | object creation | method call | field access The Cyclomatic Complexity metric is defined on methods. Adapted to the OO world, this metric is also defined for classes and structures as the sum of its methods CC. Notice that the CC of an anonymous method is not counted when computing the CC of its outer method. Recommendations: Methods where CC is higher than 15 are hard to understand and maintain. Methods where CC is higher than 30, are extremely complex and should be split in smaller methods (except if they are automatically generated by a tool). 8. Efferent coupling at method level (MethodCe): The Efferent Coupling for a particular method is the number of methods it directly depends on. 9. Afferent coupling at field level (FieldCa): The Afferent Coupling for a particular field is the number of methods that directly use it. 10. NbOverloads: The number of overloads of a method. . If a method is not overloaded, its NbOverloads value is equals to 1. This metric is also applicable to constructors. Recommendations: Methods where NbOverloads is higher than 6 might be a problem to maintain and provoke higher coupling than necessary. This feature helps reducing the number of constructors of a class. 11. Association Between Classes (ABC): The Association between Classes metric for a particular class or structure is the number of members of others types it directly uses in the body of its methods. 12. Depth of Inheritance Tree (DIT): The Depth of Inheritance Tree for a class or a structure is its number of base classes (including the System.Object class thus DIT >= International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     31 
  • 33. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  1). Recommendations: Types where DepthOfInheritance is higher or equal than 6 might be hard to maintain. However it is not a rule since sometime your classes might inherit from third-party classes which have a high value for depth of inheritance. 13. NbAssemblies: Only application assemblies are taken into account. 14. NbNamespaces: The number of namespaces. The anonymous namespace counts as one. If a namespace is defined over N assemblies, it will count as N. 15. PercentageCoverage: The percentage of code coverage by tests. Code coverage data are imported from coverage files. If you are using the uncoverable attribute feature on a method for example, if all sibling methods are 100% covered, then the parent type will be considered as 100% covered. Coverage metrics are not available if the metric LinesOfCode is not available. Recommendations: The closer to 100%, the better. 16. Relational Cohesion (H): Average number of internal relationships per type. Let R be the number of type relationships that are internal to this project (i.e. that do not connect to types outside the project). Let N be the number of types within the project. H = (R + 1)/ N. The extra 1 in the formula prevents H=0 when N=1. The relational cohesion represents the relationship that this project has to all its types. Recommendations: As classes inside an project should be strongly related, the cohesion should be high. On the other hand, too high values may indicate over- coupling. A good range for RelationalCohesion is 1.5 to 4.0. Projects where, RelationalCohesion < 1.5 or RelationalCohesion > 4.0 might be problematic. 5. RATING SCALEA rating scale is a set of categorize designed to elicit information about a quantitative or aqualitative attribute. In the social sciences, common examples are the Likert scale and 1-10rating scales in which a person selects the number which is considered to reflect theperceived quality of a product. More than one rating scale is required to measure an attitudeor perception due to the requirement for statistical comparisons between the categories in thepolytomous Rasch model for ordered categories (Andrich, 1978). 5.1 Likert scale International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     32 
  • 34. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 A Likert scale is a psychometric scale commonly used in questionnaires, and is the mostwidely used scale in survey research, such that the term is often used interchangeably withrating scale even though the two are not synonymous. When responding to a Likertquestionnaire item, respondents specify their level of agreement to a statement. The scale isnamed after its inventor, the US organizational-behavior psychologist Rensis Likert (1903-81). Each item may be analyzed separately or in some cases item responses may be summedto create a score for a group of items. Hence, Likert scales are often called summative scales.Likert scale data can, in principle, be used as a basis for obtaining interval level estimates ona continuum by applying the polytomous Rasch model, when data can be obtained that fit thismodel. In addition, the polytomous Rasch model permits testing of the hypothesis that thestatements reflect increasing levels of an attitude or trait, as intended. For example,application of the model often indicates that the neutral category does not represent a level ofattitude or trait between disagree and agree categories. Again, not every set of Likert scaleditems can be used for Rasch measurement. The data has to be thoroughly checked to fulfillthe strict formal axioms of the model.Likert scales usually have five potential choices (strongly agree, agree, neutral, disagree,strongly disagree) but sometimes go up to ten or more. The final average score representsoverall level of accomplishment or attitude toward the subject matter [8].Since, each of the factors is intangible in nature and is hard to measure. It is also proposedthat they should be measured in terms of point system as follows: Table 1: Scale of Reusability: High Reusability 10-9 Medium Reusability 8-7 Low Reusability 6-5 Very low Reusability 4-3 No Reusability 2-1 International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     33 
  • 35. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  Table 2: Scale of Maintainability: High Maintainability 10-9 Medium Maintainability 8-7 Low Maintainability 6-5 Very low Maintainability 4-3 No Maintainability 2-1 Table 3: Scale of Understandability: High Understandability 10-9 Medium Understandability 8-7 Low Understandability 6-5 Very low Understandability 4-3 No Understandability 2-1 Table 4: Scale of Modifiability: High Modifiability 10-9 Medium Modifiability 8-7 Low Modifiability 6-5 Very low Modifiability 4-3 No Modifiability 2-1 International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     34 
  • 36. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  6. CORRELATION AND REGRESSION ANALYSISCorrelation and regression are generally performed together. The application of correlationanalysis is to measure the degree of association between two sets of quantitative data. Thereare virtually no limits of applying correlation analysis to any dataset of two or more variables.It is the researcher’s responsibility to ensure correct use of correlation analysis. Correlation isusually followed by regression analysis in many applications. The main objective ofregression analysis is to explain the variation in one variable (called the dependent variable),based on the variation in one or more other variables (called the independent variables). Ifthere are only one dependent variable and only one independent variable used to explain thevariation in it, then the model is known as simple regression. If multiple independentvariables are used to explain variation in one dependent variable, it is called multipleregressions [9]. Even though the regression equation could be either linear or non-linear, welimited our discussion to linear models.From the regression analysis of the various four factors (reusability, understandability,modifiability, maintainability) separately, using their respective metrics, the analysis ofrefactorability can be done by applying linear regression over refactorability using these fourfactors. Thus, the regression equation for refactorability will be as follows: Y=a+bX1+cX2+dX3+eX4Where, Dependent Variable= YIndependent Variables are: X1, X2, X3, and X4.The above mentioned regression equation is applied to each factor that is considered to beaffecting the refactorability of the software. The underlying steps are carried out for each ofthe factor separately, by considering their respective metrics as their independent variables.Step 1: Collect the dataset containing the values for each metric identified. And based on thatdataset, the points based on the rating scale are assigned, considering the rules.Step 2: The correlation is found among the independent variables and dependent variables,for each factor affecting refactoring. The SPSS 16 tool is used to find the correlation. Thepositive value of correlation specifies that the factor is directly affected by that variable. And,the negative value shows that the factor is inversely affected by the respective variable. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     35 
  • 37. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 Step 3: The regression analysis is done to explain the variation in one variable (dependentvariable), based on the other variable (independent variable). The linear equation is used for aregression analysis and the values of the coefficients of the linear equation are determined.Step 4: The output of the regression is determined with the help of value of R-square. Themeasure of strength of association in the regression analysis is given by the determination ofR-square. The coefficient varies between 0 and 1 and represents the proportion of totalvariation in the dependent variable that is accounted by the variation in the factors.After applying all the steps to each factor, the refactorability is estimated using the linearregression equation, considering refactorability as the dependent variable and other fourfactors affecting refactoring as independent variables. The partial regression plots areobtained for each factor, the slope of which determines that the model designed to determinethe refactorability is good or bad. The linear slope of the graph determines that the modeldeveloped for refactorability based on that factor is good enough to determine therefactorability.The results of the regression analysis of all the factors, considered, that affect refactoring arestudied. Based on the results of each factor the points on the Rating scale are obtained forrefactorability. 7. CONCLUSIONSoftware Refactoring is an important area of research that promises substantialbenefits to software maintenance. Refactoring is a process that improves thequality and allows developers to repair code that is becoming hard to maintain,without throwing away the existing source code and starting again. We can returnwith a well structured and well designed code after proper application ofrefactoring techniques. By careful application of refactorings the system’s behavior willremain the same, but return to a well-structured design. The use of automated refactoringtools makes it more likely that the developer will perform the necessary refactorings, sincethe tools are much quicker and reduce chance of introducing bugs.From the literature survey of various research papers, the following factors are determined formeasuring refactoring of code and level of optimization of code namely- reusability,maintainability, understandability, modifiability. Here, we have proposed a 10-point system,to measure refactorability. The 10-point system is based on the Likert’s Rating Scale. The International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     36 
  • 38. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 metrics that affect each factor of refactoring are determined and the values are calculated.The correlation and regression analysis is performed to determine the associations andvariations among the various metrics used and their respective factors. The linear regressionequation for applying regression analysis used is given asY=a + bX1 + cX2 + dX3 + eX4Where, Y= dependent variable, a, b, c, d, e are correlation coefficients, and X1, X2, X3, X4are independent variables. The variation in independent variables affects the variation independent variable.The measure of strength of association in the regression analysis is givenby the coefficient of determination, denoted by R-square. The coefficient varies between 0and 1 and represents the proportion of total variation in the dependent variable that isaccounted for, by the variation in the factors.REFERENCES[1] Martin Flower, Kent Beck, John Brant, William F. Opdyke, Don Roberts, 1999,Refactoring: Improving the Design of Existing Code, Addison Wesley.[2] Robert C. Martin Series, 2004, Working Effectively with Legacy Code, Michael C.Feathers, Prentice Hall.[3] Frank Simon, Frank Steinbruckner, Claus Lewerentz, 2001, Metrics Based Refactorings,In: Proceedings of 5th European Conference on Software Maintenance and Reengineering,IEEE CS Press, Lisbon, Portugal, pp. 30-38.[4] Arjun Guha, Shriram Krishnamurthi, 2010, Minding the (Semantic) Gap, EngineeringProgramming Language Theory.[5] W. C. Wake, 2003. Refactoring Workbook, Addison-Wesley Longman Publishing Co.,Inc., Boston, MA, USA.[6] C. Dorai, S. Venkatesh, 2003. Bridging the Semantic Gap with Computational MediaAesthetics, IEEE Multimedia, Vol. 10, No. 2, pp.15-17.[7] Tom Mens, Tom Tourwe, 2004, A Survey of Software Refactoring, IEEE Transactions onSoftware Engineering, Vol. 30, No. 2, pp. 126-139.[8] http://www.businessdictionary.com/definition/Likert-scale.html[9] John Fox, 1997, Applied Regression Analysis, Linear Models, and Related Methods,Thousands Oaks, CA: Sage Publications. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     37 
  • 39. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  OPTIMIZING FILTERING PHASE FOR NEAR-DUPLICATE DETECTION OF WEB PAGES USING TDW-MATRIXTanvi Gupta* ABSTRACTThe voluminous amount of web documents has weakened the performance and reliability ofweb search engines. Web content mining face huge problems due to the existence of duplicateand near-duplicate web pages. These pages either increase the index storage space orincrease the serving costs thereby irritating the users. In this paper, the proposed work is tooptimize the filtering phase consists of prefix and positional filtering by adding suffix filteringwhich is a generalization of positional filtering to the suffixes of the records. The goal is toadd one more filtering method that prunes candidates that survive the prefix and positionalfiltering.Keywords: near-duplicates, TDW-matrix, Prefix-filtering, Positional-filtering, suffix-filtering*Lingaya’s University, Faridabad, India International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     38 
  • 40. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 INTRODUCTION:Over the last decade there is tremendous growth of information on World Wide Web(WWW).It has become a major source of information. Web creates the new challenges ofinformation retrieval as the amount of information on the web and number of users using webgrowing rapidly. It is practically impossible to search through this extremely large databasefor the information needed by user. Hence the need for Search Engine arises. Search Enginesuses crawlers to gather information and stores it in database maintained at search engine side.For a given users query the search engine searches in the local database and very quicklydisplays the results.But, the voluminous amount of web documents has resulted in problems for search enginesleading to the fact that the search results are of less relevance to the user. In addition to this,the presence of duplicate and near-duplicate web documents has created an additionaloverhead for the search engines critically affecting their performance. The demand forintegrating data from heterogeneous sources leads to the problem of near-duplicate webpages. Near-duplicate data bear high similarity to each other, yet they are not bitwiseidentical [2][4]. A. TDW Matrix AlgorithmTDW Matrix Algorithm is a three-stage algorithm which receives an input record and a thresholdvalue and returns an optimal set of near-duplicates. In first phase, rendering phase[3], all pre-processing are done and a weighting scheme is applied. Then a global ordering is performed to form aterm-document weight matrix. In second phase, filtering phase, two well-known filtering mechanisms,prefix filtering and positional filtering, are applied to reduce the size of competing record set andhence to reduce the number of comparisons. In third phase, verification phase, singular valuedecomposition is applied and a similarity checking is done based on the threshold value and finallywe get an optimal number of near-duplicate records. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     39 
  • 41. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  Fig.1: General Architecture [1]. B. Suffix Filtering Method:-Suffix filtering method, is a generalization of the positional filtering to the suffixes of therecords. However, the challenge is that the suffixes of records are not indexed nor their partialoverlap has been calculated. Therefore, we face the following two technical issues: (i) How to establish an upper bound in the absence of indices or partial overlap results? (ii) How to find the position of a token without tokens being indexed?The first issue is solved by converting an overlap constraint to an equivalent Hammingdistance constraint. Then lower bound the Hamming distance by partitioning the suffixes in acoordinated way. The suffix of a record x is denoted as xs. Consider a pair of records,(x, y), that meets the Jaccard similarity threshold t, and without loss of generality, |y| ≤ |x|.Since their overlap in their prefixes, is at most the minimum length of the prefixes, thefollowing upper bound can be derived in terms of the Hamming distance of their suffixes.H (xs, ys) ≤ Hmax =2|x| − 2 t/1 + t ・ (|x| + |y|) − ( t ・ |x| − t ・ |y| ) –(1)In order to check whether H (xs, ys) exceeds the maximum allowable value, an estimate of thelower bound of H (xs, ys) is provided below. First we choose an arbitrary token w from ys, International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     40 
  • 42. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 and divide ys into two partitions: the left partition yl and the right partition yr. The criterionfor thepartitioning is that the left partition contains all the tokens in ys that precede w in the globalordering and the right partition contains w (if any) and tokens in ys that succeed w in theglobal ordering. Similarly, divide xs into xl and xr using w too (even though w might notoccur in x). Since xl (xr) shares no common token with yr (yl), H(xs, ys) = H(xl, yl) + H(xr, yr).The lower bound of H (xl, yl) can be estimated as the difference between |xl| and |yl|, andsimilarly for the right partitions. Therefore,H (xs, ys) ≥ abs (|xl| − |yl|) + abs (|xr| − |yr|) -(2)Finally, we can safely prune away candidates whose lower bound Hamming distance isalready larger than the allowable threshold Hmax.RELATED WORK:A .Prefix Filtering: Consider an Ordering O of the token universe U and a set of records,each with tokens sorted in the order of O. Let the p-prefix of a record x be the first p tokensof x. If O(x, y) ≥ α, then the (|x|−α+1)-prefix of x and the (|y|−α+1)-prefix of y must share atleast one token. Prefix filtering is a necessary but not sufficient condition for the corresponding overlapconstraint, an algorithm is designed as: first build inverted indices on tokens that appear inthe prefix of each record in an indexing phase. Then generate a set of candidate pairs bymerging record identifiers returned by probing the inverted indices for tokens in the prefix ofeach record in a candidate generation phase. The candidate pairs are those that have thepotential of meeting the similarity threshold and are guaranteed to be a superset of the finalanswer due to the prefix filtering principle. Finally, in a verification phase, evaluate thesimilarity of each candidate pair and add it to the final result if it meets the similaritythreshold. B. Positional Filtering: Consider an ordering O of the token universe U and a set ofrecords, each with tokens sorted in the order of O. Let token w = x[i], w partitions the recordinto the left partition xl (w) = x [1 . . . (i − 1)] And the right partition xr(w) = x[i . . |x|]. If O(x,y) ≥ α, then for every token w x ∩ y, O (xl (w), yl(w)) + min(|xr(w)|, |yr(w)|) ≥ α. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     41 
  • 43. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 A natural idea to utilize the positional filtering principle is to combine it with the existingprefix filtering method, which already keeps tracks of the current overlap of candidate pairsand thus gives us O (xl (w), yl(w)).PROPOSED WORK:Here, I have proposed an idea of adding one more filtering technique suffix filtering , whichis a generalized form of positional filtering which will further reduce the candidate pairs size,which helps in much more efficient way to detect near-duplicates.In this new architecture, there are three phases: 1) Rendering Phase 2) Filtering Phase 3) Verification PhaseRendering Phase consists of (i) Preprocessing which includes tokenization, stemming, andstop word removal. Then (ii) Feature Weighting is done according to the proposed schemegiven in Ref.[1] on the preprocessed data .After that, (iii) Canonicalization[1]., is done. Thefinal result of this phase is the TDW Matrix [1].Filtering Phase includes (i) Prefix Filtering, the basic idea behind this filtering principle isthat if two web pages share rare tokens, there is a chance that it might be similar. Since aglobal ordering is done based on document frequencies, prefix set of a record contain raretokens. If no tokens are shared in prefix set, that record can be avoided from furtherprocessing. Once prefix filtering is over, (ii) positional filtering principle[2]. is applied inorder to prune unwanted records from candidate set C. (iii) Finally, suffix filtering[2]. is doneon the candidate pairs come from positional filtering, which uses hamming distanceconstraint(Hmax) instead of overlap constraints . The suffix of a record x is denoted as xs.Consider a pair of records, (x, y), that meets the Jaccard similarity threshold t, and withoutloss of generality, |y| ≤ |x|. Since their overlap in their prefixes, is at most the minimum lengthof the prefixes, the upper bound can be derived in terms of the Hamming distance of theirsuffixes.H (xs, ys) ≤ Hmax =2|x| − 2 t/1 + t ・ (|x| + |y|) − ( t ・ |x| − t ・ |y| )In order to check whether H (xs, ys) exceeds the maximum allowable value, an estimate of thelower bound of H (xs, ys) is provided below. The lower bound of H(xl, yl) can be estimated asthe difference between |xl| and |yl|, and similarly for the right partitions. Therefore,H (xs, ys) ≥ abs (|xl| − |yl|) + abs (|xr| − |yr|) - International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     42 
  • 44. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 Finally, we can safely prune away candidates whose lower bound Hamming distance isalready larger than the allowable threshold Hmax.Based on the records from mezzanine set M, a weight matrix A is created such that columnsrepresent documents and rows represent terms. An element aij represents the weight of theglobal feature xi in record rj-1 since the first column represents input record r. In verificationphase, (i) singular value decomposition is applied on weight matrix A and each record can berepresented as a vector in 2D space. Then Jaccard threshold 0 ≤ t ≤1, can be mapped into anangle 180 ≥ θ ≥ 0 accordingly, using the formulaθ =180*(1 – t) - (3)We can say that two records are purely dissimilar when the angle between them is 180 andthey are exactly similar if it is 0.Ultimately we get an optimum set of records by analyzing the angle of a document withrespect to input record r. If it satisfies the threshold θ, it can be marked as a near- duplicate ofr and ranked on the basis of angle. t- Jaccard Threshold -Angle O- Overlap Threshold C- Candidate Set Hmax- Hamming Constraint M- Mezzanine Set O*- Optimal set Fig. 2 :Optimizing filtering phase in general architectureProposed Algorithm for filtering PhaseInput: TDW_Matrix,Record_Set,tOutput: M International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     43 
  • 45. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 Remarks: Assume that Input_Record is represented as the first entry in TDW_MatrixFiltering (TDW_Matrix, Record_Set, t)r←TDW_Matrix[1];//prefix filteringC← φ;Prefix_Length← |r|- t.|r| +1;for all ri Record_SetPrefixi←|ri|- t.|ri| +1;for all j,k; 1≤ j ≤ Prefix_Length, 1≤ k ≤ Prefixiif (r[j] == ri[k])C← C ri;//positional filteringM1← φ;for all ri CO← t/t+1(|r|+|ri|);for all p,q; 1≤ p ≤ Prefix_Length, 1≤ q ≤ Prefixiif (r[p]==ri[q])ubound←1+ min(|r|-p, |ri|-q);if (ubound ≥ O)M1 ← M 1 ri;return M1;// suffix filtering /* x and y are tokens*/SuffixFilter(x, y, Hmax, d)M← φif d > MAXDEPTH then return abs(|x| − |y|) ; /*d-> current recursive depth*/mid ← |y| /2 ; w ← y[mid];o ← (Hmax−abs(|x|−|y|))/2 /* always divisible */; if |x| < |y| then ol ← 1, or ← 0 else ol ← 0, or ← 1; (yl, yr, f, diff) ← Partition(y,w,mid,mid); (xl, xr, f, diff) ← Partition(x,w,mid −o − abs(|x| − |y|) ・ ol, mid + o + abs(|x| − |y|) ・ or); if f = 0 then return Hmax + 1 H ← abs(|xl| − |yl|) + abs(|xr| − |yr|) + diff; International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     44 
  • 46. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  if H > Hmax then return H elseHl ←SuffixFilter(xl, yl,Hmax−abs(|xr|−|yr|)−diff, d+1) ; H ← Hl + abs(|xr| − |yr|) + diff; if H ≤ Hmax then Hr ← SuffixFilter(xr, yr,Hmax − Hl − diff, d + 1) ; return Hl + Hr + diff else return H, M← M ri;//partition / *s is the set of tokens and its two subsets are sl and sr */Partition(s,w, l, r)sl ← φ ; sr ← φ; if s[l] > w or s[r] < w then return ( φ, φ, 0, 1) p ← binary search for the position of the first token in s that is no smaller than w in theglobal ordering within s[l . . r]; sl ← s[1 . . p − 1]; if s[p] = w then sr ← s[(p + 1) . . |s|]; /* skip the token w */; diff ← 0; else sr ← s[p . . |s|]; diff ← 1;return (sl, sr, 1, diff)CONCLUSION AND FUTURE WORKIn this paper, the proposed work is to add one more filtering method in filtering phase namedsuffix filtering which is a generalization of positional filtering which will further reduce thecandidate sizes. Both, positional filtering and suffix filtering are complementary to theexisting prefix filtering technique. They successfully alleviate the problem of quadraticgrowth of candidate pairs when the data grows in size. So, this will further improve the International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     45 
  • 47. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 method to detect near-duplicates. Further research works can extend this to a more efficientmethod for finding similarity joins which can be incorporated in a focused wREFERENCES:[1] Midhun Mathew, Shine N Das ,TR Lakshmi Narayanan, Pramod K Vijayaraghvan, ANovel Approach for Near-Duplicate Detection of Web Pages using TDW Matrix. (IJCA, vol19-no.7,April 2011)[2] Chuan Xiao, Wei Wang, Xuemin Lin , Jeffrey Xu Yu, Efficient Similarity Joins for NearDuplicate Detection, Proceeding of the 17th international conference on World Wide Web, pp131 – 140. April 2008.[3] Shine N Das, Midhun Mathew, Pramod K.Vijayaraghavan, An Approach for OptimalFeature Subset Selection using a New Term Weighting Scheme and Mutual Information,Proceeding of the International Conference on Advanced Science, Engineering andInformation Technology, Malaysia, 2011, pp 273-278, January 2011.[4] Gurmeet Singh Manku, Arvind Jain and Anish Das Sarma, Detecting near-duplicates forweb crawling, In Proceedings of the 16th international conference on World Wide Web, pp.141 - 150, Banff, Alberta, Canada, 2007.. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     46 
  • 48. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619   STUDY AND DESIGN OF BUILDING INTEGRATED PHOTO VOLTAIC SYSTEM AT HCTM CAMPUS KAITHAL, HARYANARajeev Kumar*Gagan Deep Singh** ABSTRACTThe depletion of fossil fuel resources on a worldwide basis has necessitated an urgent searchfor alternative energy sources to meet up the present day demands. Solar energy is clean,inexhaustible and environment-friendly potential resource among renewable energy options.But neither a standalone solar photovoltaic system nor a wind energy system can provide acontinuous supply of energy due to seasonal and periodic variations. Therefore, in order tosatisfy the load demand, grid connected energy systems are now being implemented thatcombine solar and conventional conversion units. The objective of this work is to estimate thepotential of grid quality solar photovoltaic power in HCTM Campus, Kaithal district ofHaryana and finally develop a system based on the potential estimations made for a chosenarea. Equipment specifications are provided based on the availability of the components inIndia. Annual energy generation by proposed Grid connected SPV power plant is alsocalculated. In the last, cost estimation and payback analysis of grid connected SPV powerplant is done to show whether it is economically viable or not.Keywords: diurnal variations, daily energy output, monthly energy output, grid connectedphotovoltaic (PV) system, PWM inverters, solar radiation, yearly energy output.*Department of Electrical and Electronics Engineering, Haryana College of Engineering andTechnology, Kaithal, Haryana**Department of Electrical Engineering, Guru Nanak Dev Engineering College, Ludhiana,Punjab International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     47 
  • 49. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619   1. INTRODUCTIONElectricity is obtained from the PV array most efficiently during daytime. But at night orduring cloudy periods, independent power systems use storage batteries to supply theelectricity needs. With grid interactive systems, the grid acts as the battery, supplyingelectricity when the PV array cannot. The energy storage devices viz. battery has beenavoided in this work. This approach reduces the capital as well as the running cost. We havetried to develop a grid connected photovoltaic system. Grid connected photovoltaic system iswell known in various parts of world, and several technologies are used. There have beenefforts to develop the power electronics circuitry involved. Several types of inverters havebeen designed. But our focus is to obtain the potential of grid connected photovoltaic systemin Kaithal district of Haryana and finally develop a system based on the potential estimationsmade for a chosen area. Equipment specifications are provided based on the availability ofthe components in India. Annual energy generation by proposed Grid connected SPV powerplant is also calculated. In the last, cost estimation and payback analysis of grid connectedSPV power plant is done to show whether it is economically viable or not. 2. METHODOLOGYTo find out the solar potential available at Kaithal district of Haryana, reading of solarradiation for site is required. So these readings are taken from HAREDA, Sec-26 Chandigarh.The data for solar radiation for Kaithal district of Haryana is shown in table 1 Table 1 Comparison of average solar insolation data {kwhr/m2/day} of district Kaithal Months HARSAC NASA % Deviation Jan. 2.76 3.58 22.9 Feb. 4.15 4.38 5.25 March 4.86 5.59 13 April 6.24 6.1 2.2 May 5.86 6.4 8 June 5.04 6.2 18 July 4.6 5.5 16 Aug. 4.47 5.14 13 Sep. 4.5 5.23 13 International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     48 
  • 50. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619   Oct. 4.85 4.71 2.9 Nov. 3.42 4.01 14 Dec. 2.53 3.36 24 Annual 4.44 5.02 11HARSAC: Average values from January 2003 to December 2007NASA: Average values from July 1983 to June 2005 Graph for monthly peak variation in Kaithal 8 solar insolation in  6 Kwh/m2 4 2 0 Graph 1So, in order to design building integrated PV system in HCTM campus, district Kaithal, theaverage of annual solar insolation in district Kaithal measured by two agencies i.e. HARSACand NASA is taken. According to HARSAC, annual solar insolation in Kaithal = 4.44 kwhr/m2/day.According to NASA, annual solar insolation in Kaithal = 5.02 kwhr/m2/day.So, average annual solar insolation in Kaithal = (4.44 + 5.02)/2 = 4.73kwhr/m2/day. = 4.73/6 =788.333w/m2/day.Efficiency of solar panel = 14.3% So, average peak output = 788.3×0.143 = 112.73 W/m2 International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     49 
  • 51. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619   Table 2 Load calculation of block AFan load Tube Lights 6A/3pinsocket load Coolers Computers load Total(KW) load (KW) (KW) load (KW) load (KW) (KW)262 × 80 = 286 × 40 = 77 × 40 = 3.08 6 × 300 = 26 × 300 = 7.8 45.0820.96 11.44 1.8Total load of A-Block = 45.08 KW Roof Area of Block ALength = 358 ft = 109.14 m; Breadth = 58 ft = 17.68 mRoof area = 109.14 × 17.68 = 1929.59 m2 3. ENERGY CALCULATION Table 3 Energy generated from Block AName Available Area Average Possible Energy Energyof Area (m2) used Peak Plant Generated GeneratedBlock (m2) Output Capacity per day per month (W/m2) (KW) (KW-hr) (KW-hr)A 1929.59 400 112.73 45 270 81004. SYSTEM SIZING Table 4 Solar Panel Specification Watt 180 Watt Voltage 24 Volts Current 7.5 A Type Polycrystalline Efficiency 14.3% International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     50 
  • 52. IJRIME E     Volum me1Issue5 5  ISSN‐22 249‐ 1619   Temperat ture 25 deg c Dimensio (mm) ons 1593 × 790 × 50 Area of sing panel = 1 gle 1258470 (mm m) Area of sing panel = 1 gle 1.259 meter² ² Tilt angle e(slope) of PV Module 45 degree V Mounting g Fixed TypeThe wirin diagram o PV array is shown in Figure 1 ng of gure 1 wiring diagram of PV array Fig g fPWM inv verters are used for supp u pressing the harmonics p produced aft DC to AC Conversion ter C n.The calcu ulation for fi inding the ou utput voltage of inverter is shown be e r elow: [26]Phase vo oltage= Vph= 0.4714 × Vdc= 0.4714 240= 113. 4× .136 Volts.Line volt tage = VL = 0.779 × Vdc = 0.779× 2 = 187 Volts. 240 VKVA rati = KW × assumed po ing ower factor = KW × 0.8 Interna ational Journal of Research in IT, Management and Engineering                                                             www.gjmr.org
  • 53. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619   Table 5 Solar Photovoltaic Power Plant Specification Plant Capacity 45 KW Voltage Output 240 Volts dc Current Output 187.5 A No. of Modules 250 Area 400 m2 Table 6 Inverter Specification KVA rating 36 KVA Input DC voltage 240Volts DC Input dc current 187.5A Output AC voltage 113.136 V ac (phase voltage) 187 V ac (line voltage) No. of Phases 3-φ Type PWM (for suppressing 3rd harmonics) Efficiency Almost 90-95% Total harmonic distortion < 5% Table 7 Transformer Specification KVA rating 36 KVA No of phases 3-φ Frequency rating 50 Hz Primary voltage rating 187 V Secondary voltage rating 400 V Primary current rating 192.51 A Secondary current rating 90A Connections Primary – delta (for suppressing3rd harmonics) Secondary – star International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     52 
  • 54. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619   10 to 25 taps in secondary Efficiency Almost 95 % Extra features Air cooled5. COST ANALYSIS FOR 45 KW SOLAR PV PLANT:1.Cost of solar panels: - The BP 7180 most powerful module manufactured by BP Solar isused; cost of solar panel is Rs.160 per watt.So cost of 180 watt panel is = 180 × 160 = Rs. 28, 800.Total cost of solar panels = 250 × 28800 = Rs. 72, 00000.2. Cost of 3-φ Inverter: - 36 KVA or 45 KW of an inverter /Power Conditioning Unit isused; multiply the size of the inverter by Rs. 25 per rated watt.Cost of inverter = 25 × 45,000 = Rs. 11, 25,000.3. Cost of 3-φ step up Transformer: - 36 KVA or 45 KW of a step up transformer is used;multiply the size of the transformer by Rs. 20 per rated watt.Cost of transformer = 20 × 45000 = Rs. 9, 00000.4. Cost of battery bank: - Exide Invared 400 Tubular Inverter Battery 12 V, 150Ah Price –8,400/- . 40 numbers of batteries in two strings of 20 batteries in each string are used. [34]So, cost of battery bank = 40 × 8400 = Rs 3, 36, 000.Subtotal: Rs. 95, 61, 000.5. Multiply the subtotal above by 0.2 (20%) to cover balance of system costs (wire, fuses,switches, etc.).Cost Estimate for Balance of System: (9561000 × 0.2) Rs. 19, 12, 200.Total Estimated PV System Cost is Rs. 1, 14, 73, 200.6. ANNUAL ENERGY GENERATIONThe annual energy generation from the SPV power plant has been worked out based on thedata on mean global solar radiant exposure over Haryana at district Kaithal. The mean globalsolar radiant exposure varies from 2.53 kWh/m² /day in the month of December to 6.24 kWh/m²/day in the month of April according to HARSAC and from 3.36 kWh/m² /day in themonth of December to 6.4 kWh/m²/day in the month of May according to NASA. Themonth-wise mean global solar radiant exposure is given at table below.Table 8 Mean Global Solar Radiant Exposure Kaithal, HARYANA (Acc. To HARSAC) International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     53 
  • 55. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619   Month Daily solar insolation in (kWh/m²/day) Energy Generated(kWh) Jan 2.76 4894 Feb 4.15 6646 March 4.86 8617 April 6.24 10707 May 5.86 10390 June 5.04 8648 July 4.6 8156 Aug 4.47 7926 Sept 4.5 7722 Oct 4.85 8600 Nov 3.42 5868 Dec. 2.53 4486 Monthly Average 4.44 7619 Table 9 Mean Global Solar Radiant Exposure Kaithal, HARYANA (Acc. To NASA) Month Daily solar insolation in (kWh/m²/day) Energy Generated(kWh) Jan 3.58 6348 Feb 4.38 7015 March 5.59 9912 April 6.1 10467 May 6.4 11348 June 6.2 10639 July 5.5 9752 Aug 5.14 9114 Sept 5.23 8974 Oct 4.71 8351 Nov 4.01 6881 Dec. 3.36 5957 Monthly Average 5.02 8614 Month Wise load calculation of HCTM, Campus based upon assumptions: Table 10 Month wise load assumption International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     54 
  • 56. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619   Month Type of load Load (KW) % of Total load (45 KW) Jan Lighting+ computer 18 40 Feb Lighting+ computer 18 40 March Lighting+ computer + fan load 27 60 April Lighting+ computer + fan load 38 85 May Lighting+ computer + fan load 38 85 June Lighting+ computer + fan load 12 25 July Lighting+ computer + fan load 12 25 Aug Lighting+ computer + fan load 40 90 Sept Lighting+ computer + fan load 40 90 Oct Lighting+ computer + fan load 40 90 Nov Lighting+ computer 16 35 Dec. Lighting+ computer 16 35 Table 11 Month wise load and energy generation (according to HARSAC) Month Energy consumption(KWh) Energy generated(KWh) Energy surplus (KWh) Jan 3348 4894 1546 Feb 3024 6646 3622 March 5022 8617 3595 April 6840 10707 3867 May 7068 10390 3322 June 2160 8648 6488 July 2232 8156 5924 Aug 7440 7926 486 Sept 7200 7722 522 Oct 7440 8600 1160 Nov 2880 5868 2988 Dec. 2976 4486 1510 International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     55 
  • 57. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619   Table 12 Month wise load and energy generation (according to NASA) Month Energy consumption(KWh) Energy generated(KWh) Energy surplus (KWh) Jan 3348 6348 3000 Feb 3024 7015 3991 March 5022 9912 4890 April 6840 10467 3627 May 7068 11348 4280 June 2160 10639 8479 July 2232 9752 7520 Aug 7440 9114 1674 Sept 7200 8974 1774 Oct 7440 8351 911 Nov 2880 6881 4001 Dec. 2976 5957 29817. SIMPLE PAYBACK ANALYSIS: A simplified form of cost/benefit analysis is the simple payback technique. In this method,the total first cost of the system is divided by the first-year energy cost savings produced bythe system. This method yields the number of years required for the system to pay for itself.For new construction, it can be used to evaluate conventional construction to energy-efficientdesign alternatives. In simple payback analysis, we are assuming that the service life of theenergy efficiency measure will equal or exceed the simple payback time. Simple paybackanalysis provides a relatively easy way to examine the overall costs and savings potentials for International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     56 
  • 58. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  a variety of project alternatives. While the payback period analysis does not take intoconsideration the time dependent value of money, nor the total accumulated cost or savingsover the life of the system, for systems with equal expected lives, simple payback period canbe applied to determine relative performance among alternatives.Simple Payback time (years) = Total cost of the system/ Annual Savings Energy Consumption dataThe energy consumption data from year 2010 -11 of HCTM, campus provided by accountsoffice, HCTM was used for this study and is shown in Table 13 Table 13 Energy Consumption data of HCTM, campusS.No. Month Total Units Utility Rate inclusive all charges Total Consumed (Rs./KWh) Electricity Bill (Rs.)1 Jan 50385 4.6 2,31,7712 Feb 52290 4.6 2,40,5343 March 59500 4.67 2,78,2344 April 94500 4.76 4,49,8205 May 139250 4.68 6,52,5546 June 155250 5.64 8,76,6207 July 124250 6.06 7,53,2208 Aug 136250 6.06 8,25,6759 Sep 105045 4.93 5,18,67010 Oct 93885 4.56 4,28,16311 Nov 62465 4.6 2,87,33912 Dec 53150 4.6 2,44,490 Graph for Monthly Variations in electricity bill of HCTM, Kaithal International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     57 
  • 59. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619   monthly variation in electricity bill  of  HCTM, Kaithal 1,000,000 Bill in Rs. 0 Aug Sept Dec. Feb March Oct May April Nov June Jan July Graph 2Simple Pay Back Time the total savings are given below. Table 14 – Savings for different months (According to HARSAC)S.No. Month Total Units produced with Utility Rate inclusive all charges Savings PV (Rs./KWh) (Rs.)1 Jan 4894 4.6 22,5122 Feb 6646 4.6 30,5713 March 8617 4.67 40,2414 April 10707 4.76 50,9655 May 10390 4.68 48,6256 June 8648 5.64 48,7747 July 8156 6.06 49,4258 Aug 7926 6.06 48,0319 Sep 7722 4.93 38,06910 Oct 8600 4.56 39,21611 Nov 5868 4.6 26,99212 Dec 4486 4.6 20,635Annual Savings = Rs. 4, 64,056.Simple payback time = Total cost of system / Annual savings = 1, 14, 73, 200/ 4, 64, 056 = 24.7 years (According to HARSAC) International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     58 
  • 60. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619   Table 15 – Savings for different months (According to NASA)S.No. Month Total Units produced with Utility Rate inclusive all charges Savings PV (Rs./KWh) (Rs.)1 Jan 6348 4.6 29,2002 Feb 7015 4.6 32,2693 March 9912 4.67 46,2894 April 10467 4.76 49,8225 May 11348 4.68 53,1086 June 10639 5.64 60,0037 July 9752 6.06 59,0978 Aug 9114 6.06 55,2309 Sep 8974 4.93 44,24110 Oct 8351 4.56 38,08011 Nov 6881 4.6 31,65212 Dec 5957 4.6 27,402Annual Savings = Rs. 5, 26, 393.Simple payback time = Total cost of system / Annual savings = 1, 14, 73,200/ 5, 26, 393 = 21.7 years (According to NASA) 8. CONCLUSIONThe methodology adopted seems satisfactory for determining the possible plant capacity foran arbitrarily chosen area. The design described is based on the potential measured. Systemsizing and specifications are provided based on the design made. Finally, cost analysis iscarried out for the proposed design. Total Estimated 45 KW PV System Cost is Rs. 1, 14,73,200. Annual energy generation is also calculated. From calculations done in chapter 6, it isclear that the estimated energy generated per month from block A is more than the energyrequirement. This surplus energy generated can be stored and supplied to the hostels or.residential blocks in the campus during night time or may be used when sun is not availableor can be sold to grid. . In the end of chapter 6, the simple payback period is calculatedaccording to the solar radiation data given by two agencies namely HARSAC and NASA andfound to be 24.7 years and 21.7 years respectively. From the results, it can be concluded thatat current utility rate and demand charges, the system is not economically feasible. However, International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     59 
  • 61. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  in future, at higher utility rates like Rs 10-12/Kwhr and rebates from the government orutility, the system may be cost effective. With rebates, the demand for the PV panels will risegradually leading to more production of panels and a likely drop in price thereby making thesystem more cost- effective. FUTURE SCOPE In future we will calculate the number of PV arrays and cost of the system which can meetthe load demand of all campus. In starting we have not taken into account the air-conditionersload. In future we will include the load of air-conditioners. A detailed Cost analysis can beconducted considering carbon credit to show whether it is economically viable or not. Sincethe performance of PV system is strongly dependent on loss factors such as shading, PCSlosses, mismatch, PV array temperature rise, etc. There is a necessity for reviewing these lossfactors to evaluate and analyze accurately the performance of PV system. This system can bedesigned with also some another electrical appliances like DC- DC booster for boosting upthe voltage wherever is necessary, filter for suppressing the ripples etc. Another transformerless design also can be done. DC –DC choppers with variable duty cycle can be used alongwith filters. For direct application of DC that kind of system can be designed. Intelligentdevices like microprocessors, PLC (programmable logic controller) may be added to thesystem to keep the operating point (maximum power point) for maximum efficiency. Totaken care of the uncertainty in the insolation level, use of fuzzy control can be done. Use offeedback path for automatic control-position control servo for changing the transformationratio of variac can be used. A detailed performance analysis of the present system can becarried out to show its reliability as a future work. Solar PV is a technology that offers asolution for a number of problems associated with fossil fuels. It is clean decentralized,indigenous and does not need continuous import of a resource. On top of that, India hasamong the highest solar irradiance in the world which makes Solar PV all the more attractivefor India. The state of Orissa and Andhra Pradesh also houses some of the best qualityreserves of silica. India has a large number of cells and modules manufacturers. In spite of allabove advantages Indian Photo Voltaic programme is still in the infancy stage. One of thereasons could be absence of simple, action oriented and aggressive PV policy of the countryboth in the state and central level. More quickly we do it with the professionals more weprotect our future energy security.REFERENCES International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     60 
  • 62. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  [1]. P.Sritakaew & A.Sangswang, “On the Reliability Improvement of Distribution SystemsUsing PV Grid-Connected Systems”. IEEE Asia Pacific Conference on Circuits and systems.pp. 1354 - 1357, 2006.[2]. Allen M. Barnett, “Solar electrical power for a better tomorrow”. Photovoltaic SpecialistsIEEE Conference, Page(s): 1 – 8, 1996.[3]. G. Ofualagba, “Photovoltaic Technology, Applications and Market”, IEEE Conferenceon Power and Energy society general meeting - conversion and delivery to electrical energy,Vol.21, Page(s): 1 – 5, 2008.[4]. Souvik Ganguli and Sunanda Sinha, “A Study and Estimation of Grid Quality SolarPhotovoltaic Power Generation Potential in some districts of West Bengal”. NationalConference on Trends in Instrumentation & Control Engineering, Thapar University,Patiala, Page(s): 522-528, 29-30th Oct., 2009.[5]. Wang Jianqiang & Li Jingxin, “Design and Experience of Grid-connecting PhotovoltaicPower System”, IEEE International Conference on Sustainable Energy Technology, Page(s):607 - 610, 2008. [6]. B. Marion,J. Adelstein,K. Boyle and fellows, “Performance Parameters for GridConnected PV Systems”, Photovoltaic Specialists IEEE Conference, Page(s): 1601 - 1606,2005.[7]. D. Picault, B. Raison, and S. Bacha, “Guidelines for evaluating grid connected PVsystem topologies”. IEEE International Conference on Industrial Technology. Page(s): pp. 1-5, 2009.[8]. Jinhui Xue, Zhongdong Yin, Qipeng Song, and Renzhong Shan, “Analyze and Researchof the inverter for Grid connecting photovoltaic system”, Third IEEE InternationalConference on Electric Utility Deregulation and Restructuring Power Technologies, Page(s):2530 – 2535, 2008.[9]. Eduardo Román, Ricardo Alonso & Pedro Ibañez, “Intelligent PV Module for Grid-Connected PV Systems”, IEEE Transactions on Industrial electronics, Vol.53.No.4, Page(s):1066 – 1073, August 2006.[10]. Kosuke Kurokawa, Kazuhiko Kato , Masakazu Ito , Keiichi Komoto, Tetsuo Kichim,& Hiroyuki Sugihara “The cost analysis of very large scale PV system on the world desert”.Photovoltaic Specialists IEEE Conference, Page(s): 1672 – 1675, 2002. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     61 
  • 63. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  [11]. Souvik Ganguli and Sunanda Sinha, “assessment of solar photovoltaic generationpotential & estimation of possible plant capacity for 100 m2 available area in Kolkata”,International journal of engineering research and studies, vol. 1, pages 82-92.[12].Souvik Ganguli & Sunanda Sinha , “design of a 9KW grid connected solar photovoltaicpower plant using 100 m2 available area in Patiala” , International journal of engineeringresearch and studies, vol. 1, pages 12-27.[13]. Souvik Ganguli & Sunanda Sinha,” estimation of annual energy generation from a smallgrid connected solar photo voltaic power plant in Patiala”, International journal ofengineering research and studies, vol. 2, pages 43-44.[14]. E.A. Alsema, P. Frank, K. Kato,” energy payback time of photovoltaic systems for threemajor PV applications”, 2nd world conference on photovoltaic solar energyconversion,Vienna, 6-10 July, 1998.[15]. Bangyin Liu, Chaohui Liang and Shanxu Duan,”Design Considerations and TopologySelection for DC-Module-Based Building Integrated Photovoltaic System”. 3rd IEEEconference on industrial electronics and applications, pp. 1066-1070, 2008.[16]. E.W. Smiley and L. Stamenic,” Optimization of Building Integrated Systems”. IEEE29th conference on photovoltaic specialists. pp. 1501-1503, 2002.[17]. Tymandra Blewett, Margaret Horne and Robert Hill, “Helidon Prediction of Shading onBuilding Integrated Systems”. 26th IEEE conference on photovoltaic specialist. pp. 1393-1396, 1997.[18]. H. MauNs, M. Schmid, B. Blersch, P. Lechner, H. Schade, “BIPV InstallationWorldwide in ASI Technology”. Proceeding of 3rd IEEE world conference on photovoltaicenergy conversion. Vol.3, pp. 2375-2378, 2003.[19]. Chang Ying-Pin and Shen Chung-Huang “Effects of the Solar Module Installing Angleson the Output Power” IEEE 8th international conference on electronics measurement andinstruments, pp. 1-278 - 1-282, 2007.[20]. [http:Energy Scenario] “Solar PV Industry 2010: Contemporary scenario and emergingtrends” available at www.isaonline.org/documents/ISA_SolarPVReport_May2010.pdf[21]. [http:Energy Scenario] “the solar PV landscape in India” available atwww.solarindiaonline.com/.../The_Solar_PV_Landscape.pdf[22]. [http: Solar Electric Systems] “Chapter Three Introduction to Solar Electric Systems”available at www.kysolar.org/ky_solar_energy_guide/chapters/Chapter_3_PVintro.pdf International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     62 
  • 64. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  [23]. [http: Series and Parallel connection] “Series and Parallel Wiring” available atwww.termpro.com/articles/spkrz.html.[24]. [http: BP_7180_V2] “specification of PV module” available atwww.bp.com/liveassets/bp_internet/solar/bp.../b/BP_7180_V2.pdf[25] [http: Photovoltaic modules] ―Photovoltaic modules, system and application availableat www.icpress.co.uk/etextbook/p139/p139_chap15.pdf International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     63 
  • 65. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  FUNDS MANAGEMENT OF ICICI BANKManju Sharma* ABSTRACT“The ICICI total business Rs. 52000 crores, it is a gigantic Financial Institution. Atpresent the total business is 1.91 lakh crore. The total deposits are Rs. 202017 crorestotal a advances Rs. 181206, net profit for the year Rs. 1006 crores, Net Interest incomeRs. 2035 crores on 31 March 2010.”Total Assets are worth Rs. 363400 crores, operating profits are worth Rs. 9732 crore,interest income Rs. 25707 crores. In this paper, I am trying to analyze the the fundsmanagement of ICICI bank.Keywords: Credit, Demat, Funds, Management, Trade.* Research Scholar, Singhania University International Journal of Research in IT, Management and Engineering www.gjmr.org 64
  • 66. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 ANALYSIS OF ICICI FUNDS MANAGEMENT:The huge funds available with ICICI Bank following functional activities are taken careare as: MAIN SERVICES The following are the main services:  Credit Services  Home Loan Services  Trade Services  Agricultural Services  International Banking Services  Vestro Accounts Services  Proxy Banking Services OTHER SERVICES The following are the others services:  Security Market Services  Corporate and Structural Services  Investment Services  Cash Management Services  Foreign Exchange Services  Demat Securities  Credit ServicesAbn Amro Bank, Allahabad Bank, American Express Bank, Andhra Bank, Bank of India,Canara Bank, Central Bank of India, Citibank, Corporation Bank, HDFC Bank, HSBCBank, ICICI Bank, Indian Overseas Bank, Oriental Bank of Commerce, Punjab National International Journal of Research in IT, Management and Engineering www.gjmr.org 65
  • 67. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 Bank, State Bank of India (SBI), Standard Chartered Bank, IDBI, United Bank of India,UTI Bank.The advancement of technology and the birth of competition, banks are in the race ofbecoming the best in the country. With an eye upon customer satisfaction policy they areproviding best of the best services with the minimum hazards.Banks like ABN AMRO introduced banking with a coffee. It made a tie-up with one ofthe best coffee bar in the country, Barista and remained open till late evening forcustomers with a setup of a coffee bar in the premises.Few banks have introduced world ATM card to make travelers across the globe more safeand secure. What else. Internet and Phone Banking is the call of the day for banks.In this race towards the best, selected top 20 banks in the country from all segment it isnot the ranking of banks but only for general information about the top banks in India. (I) CREDIT SERVICESICICI Banks offer a varied range of cards to suit your requirements. These cards havinga wide acceptance, nationally and internationally, coupled with benefits of channels likeInternet and Mobile, with enhance your experiences.ICICI Bank Credit Cards give you the facility of cash, convenience and a range ofbenefits, anywhere in the world. These benefits range from life time free cards, InsuranceBenefits, global emergency assistance service, discounts, utility payments, traveldiscounts and much more.The ICICI Bank Debit Card is a revolutionary form of cash that allows customers toaccess their bank account round the clock, around the world. The ICICI Bank Debit Cardcan be used for shopping at more than 100,000 merchants in India and 13 millionmerchants worldwide.Presenting ICICI Bank Travel Card. The Hassle Free way to Travel the world. Travelingwith US Dollar, Euro, Pound Sterling or Swiss Francs; Looking for security andconvenience; take ICICI Bank Travel Card. Issued in duplicate. Offers the Pin basedsecurity. Has the convenience of usage of Credit or Debit card. International Journal of Research in IT, Management and Engineering www.gjmr.org 66
  • 68. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 II) HOME LOANS – SERVICESThe ICICI Bank Home Loans are available in the following cities: * Aurangabad * Delhi * Ahmedabad * Mumbai * Bangalore * Nasik * Baroda * Nagpur * Chennai * Pune * CalcuttaLoan Amount:The loan amount is up to a maximum of 85% of the value of the property to be financed.Minimum Amount : Rs. 1 lakhMaximum Amount : Rs. 10 millionTenorThe tenor of a ICICI Bank home loan ranges from a period of 1 year to 30 yearsdepending on the type of loan availed.EligibilityThe eligibility criteria are:  The applicant should be at least 25 years of age and a maximum of 65 years at the time of loan maturity.  The applicant should have a regular source of income.Documentation:The documents required are:  Passport size photograph of all the applicants.  Residence and age verification, which may be established from the Pan Card, Election ID, Passport, Driving License or Ration Card  Bank statements for the last six months  Latest salary slip/ statement showing all deductions in case of employed applicants International Journal of Research in IT, Management and Engineering www.gjmr.org 67
  • 69. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619   Certified copies of Balance Sheets and Profit and Loss accounts, IT acknowledgments, advance tax challans (for company/ firm and personal account) for the last three years in case of self-employed applicants.  Memorandum /Articles of Associations for Companies, partnership deeds for firms and a brief profile of your company/ firm in case of self-employed applicants.Property Documents (as and where applicable):  Application form duly filled and signed.  Draft sale agreement  Previous sale agreements  NOC to mortgage from society/ builder as per our format?  Society Share Certificates  Occupancy certificate (Ready property or U/C property)  Original stamped receipts for the payments already made to the builder/ seller, till date  371 Clearance from the appropriate Income Tax authorities, if applicable.  List of additional amenities from builder where applicable.Interest Rate StructureTenure (years) Interest Rate1-5 11.25%6-20 12.75%21-30 12.85%EMI Chart per Rs. 1,00,000Tenor Interest: Interest: Interest: 11.25% 12.75% 12.85%5 years Rs. 2269 N.A. N.A.20 Years N.A. Rs.1168 N.A.30 Years N.A. N.A. Rs. 1100Note: of cause these rates are subject to change with the ordinance of RBI. International Journal of Research in IT, Management and Engineering www.gjmr.org 68
  • 70. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 Other CostsFees: 1.8% of the sanctioned Loan amount.Processing fee: Rs. 500 (at the time of application)III) TRADE SERVICESICICI Bank offers a wide range of Trade Services designed to assist you in building onyour strengths, so that your company can seize business opportunities across the world.ICICI Bank has in place a Centralized Trade Services Unit, which adheres to six sigmastandards. As a result, ICICI Bank customers experience fewer delays in receivingpayment, require less effort in locating collecting information, gain increased controlover foreign receivables and experience improved cash flows.Online Trade Services:ICICI Bank customers can effect remittances as well as get their applications for issuanceof Letters of Credit and Bank Guarantees processed online. This not only extendstremendous convenience to the entire process, but also allows the customer to enjoy thebenefits of simplified documentation, online verification of status and savings in cost andtime. Online Trade Services can be availed by enrolling for Corporate Internet Banking(CIB) offered by ICICI Bank. Online LC Online EPC Online Bank Guarantee Online Remittances Online EEFCTrack the status of your export and import bills, view details of your LCs, guarantees andforward contracts, get your export LC electronically advised – do all this and morethrough our web services.Advisory Services: International Journal of Research in IT, Management and Engineering www.gjmr.org 69
  • 71. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 Banks believe in delivering value. ICICI Bank clients can avail our advisory services onforex markets, currency movements, regulatory issues, risk management and other issuesin trade finance.Exchange RatesTrack the latest movements in currency to plan your business.Customized Solutions and New Product DevelopmentICICI Bank constantly customizes solutions and introduces innovative products for itsTrade Services clients.Export Document Tracking:Bank realizes the criticality of time in your trade transaction process. You can now trackthe status of shipment of your export documents online.Arrange for Export Credit Insurance:Export credit insurance is an important aspect of international trade. Know more aboutthe services of India’s leading export credit agencies ICICI Lombard and ECGC.Trade Regulation & Policy Update:The global trade scenario is governed by country specific as well as internationalregulation. Refer to the existing regulations and update yourself with the latest.Trade FacilitationIn a developing country like India, a number of organizations occupy the role of tradefacilitators. They are a source of valuable information, resources, services and guidanceto Indian exporters.Country ScanThe economic and political climate of a country influences business decisions of exportersand importers across the globe. Coface country reports and country ratings aid you intaking informed decisions.Concepts in International Trade:Global trade transactions are complex. The exporter and importer entering a contract isonly the beginning of a chain of events that need to be precisely coordinated. At one levelit involves document preparation, at another level it requires coordinating with thirdparty. International Journal of Research in IT, Management and Engineering www.gjmr.org 70
  • 72. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 IV) AGRICULTURE SERVICESAdopting innovative approach to Agriculture Business financing and by offeringcomplete supply chain solutions. ICICI Bank has changed the face/ dynamics ofAgriculture Business Finance in the country.ICICI Bank, India’s first universal bank, has the financial strength and the expertise tooffer probably the widest array of financial services for your business.Whatever your requirements, if you are into agriculture business, out dedicated tam ofagriculture sector specialists and finance professionals with deep understanding of thesectoral business environment will device custom solutions and offer complete supplychain solutions for your business.Whether you are in the business of Diary, Sugar, Plantations, Seed sector, FertilizerSector, Infrastructure, Markfeds or Food Processing, ICICI Bank is the one stop shop forall your financial needs.V) INTERNATIONAL BANKING SERVICES…ICICI Bank’s International Banking Division Offers a complete range of correspondentbanking services to banks and financial institutions. The products offered are as under:  Automated INR Payment Services  VOSTRO Accounts  Cross Border Trade Services  Trust and Retention Account Services  INR Agency Clearing ServicesAutomated INR Payment Services: International Journal of Research in IT, Management and Engineering www.gjmr.org 71
  • 73. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 This product offers efficient distribution of inward remittance from exchange Houses andBanks abroad.Key features of this service are:-  Web/SWIFT messaging facility  Routing of payment through our internal electric network if the account is with any of our branches.  If accounts are with other banks, distribution is achieved through bank drafts/ cheques by courier.  Cover funding through INR account/or through foreign currency accounts  On-line access to INR account if maintained  MT 950/940 facility  Dedicated helpdesk for backup and tracking  Convenience in funding/ providing coverEvolving a structure that best address the concerns of all institutions involved infinancing of the project/ other financial requirements. Key features of the product are:  Waterfall management of cash flows  Acting as paying and receiving agent  Foreign Exchange agent  Safekeeping and Custody for the underlying  Account administration  Cash escrows and security escrows  Pre constructions and post construction management of cash flows  Investment services  Regulatory liaison  Advisory Services  Electronic reporting via the Internet or specialist on-line system; Customized MIS reporting. INR Agency Clearing Services:ICICI Bank offers Clearing Services across all major centers for facilitating clearing oftheir customer cheques. Key features of the product are:  Clearing of customer cheques through our code as a sub member International Journal of Research in IT, Management and Engineering www.gjmr.org 72
  • 74. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619   Facility to issue demand drafts payable across all our branches by your branch/ branches  Collection of cheques/ instruments through our network  Funds transfer services from other centers to your branch/ branches through our networks  Customized MIS and a dedicated helpdesk.VI) VOSTRO ACCOUNTS SERVICEVOSTRO accounts provide INR account services to correspondent banks. All theaccounts are held in a special center located in our Nariman Point branch at Mumbai. Keyfeatures of the product are:  Access to our network spread across all major centers  Internet access to account  Web based messaging facility/ SWIFT based  Customized MIS  Funding convenience  Competitive tariffCross Border Trade Services:ICICI Bank offers full range of cross border trade services to its correspondent banks.This services is available across all major destinations in India with significant foreigntrade potential. We have fully integrated communication channels amongst branches,which directly helps in saving valuable time facilitating cross border transactions.  Advising and confirming of documentary letters of credit  Confirmation/ reissuance of standby LCs and guarantees.  Documentary collections/ open account transactions  Payment processing and distribution  Advising and confirming of documentary credits  Negotiation of documents  Computerized processing ensuring speedy servicesTrust and Retention Account Services: International Journal of Research in IT, Management and Engineering www.gjmr.org 73
  • 75. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 ICICI Bank is one of the leading Trust and Retention (Escrow) Account servicesproviders in India, have a considerable experience in managing various types of Trust andRetention accounts including.VII) PROXY BANKING SERVICESIndian villages were miles away from mutual funds, insurance and even equity trading.Thanks to Internet Kiosk and the ATM duo which had made it possible for rural India.This kiosk has been set up by ICICI Bank in partnership with network n-LogueCommunications in remote villages of Southern part of the country. This is known asProxy Banking. With the help of fibre optic cables, this works on wireless in local looptechnology.Reasons for Setting up of Proxy Banking  58% of rural households still do not have bank accounts.  Only 21% of rural households have access to credit from a formal source.  70% of marginal farmers do not have deposit account.  87% households have no formal credit.  Only 1% rural households rely on a loan from a financial intermediary. The loans take between 24 to 33 weeks to get sanctioned.  Consumer bribe officials to get loans approved which varies between 10 and 20 percent of the loan amount.  Branch including in rural is a loss-making.Others Services;To name a few as:  Security Market Services Corporate and Structural Services  Investment Services Cash Management Services  Foreign Exchange Services Demat Securities  Credit Services International Journal of Research in IT, Management and Engineering www.gjmr.org 74
  • 76. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 BIBLIOGRAPHY1. Ahmed, K. & Nicholls, D., “The impact of non-financial company characteristics on mandatory disclosure compliance in developing countries: the case of Bangladesh”, The International Journal of Accounting Education and Research, 1994, pp: 62-77.2. Baker, Kent H. & Haslem, J.A., “Information Needs of Individual Investors”, The Journal of Accountancy, November 1973, pp: 64-69.3. Barrett, M. E., “The extent of disclosure in annual reports of large companies in seven countries”, The International Journal of Accounting Education and Research, 1977, pp: 1-25.4. Barrett, M. Edgar, “Financial Reporting Practices: Disclosure and Comprehensiveness in International Setting”, Journal of Accounting Research, Vol. 14 No.1, Spring 1976, pp: 10-26.5. Buzby, S.L., “Company Size, Listed Versus Unlisted Stocks and the Extent of Financial Disclosure”, Journal of Accounting Research’, Vol. 13, 1975, pp: 16-37.6. Buzby, Stephen L., “Selected Items of Information and Their Disclosure in Annual Reports”, The Accounting Review, Vol. XLIX No. 3, July 1974, pp: 423- 435.7. Cayanan, Arthur S., “An Assessment Of The Financial Reporting Practices Of Some Listed Philippine Banks In 2008”, Philippine Management Review, 2009, Vol.16, pp :13 -23.8. Chander, Subhash, “Regulation of Corporate Disclosure Practices in India”, Indian Journal of Accountancy, Vol. XXXV (2), June 2005, pp: 20-28.9. Chandra, Gyan, “A Study of the Consensus on Disclosure among Public Accountants and Security Analysts”, The Accounting Review, October 1974, pp: 733-742.10. Chandra, Gyan, “Corporate Business Reporting Consensus between Preparers and Auditors”, Journal of Accounting and Finance, Vol. 16 No.1, October 2001 – March 2002, pp: 3-22. International Journal of Research in IT, Management and Engineering www.gjmr.org 75
  • 77. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 11. Chandra, Gyan, “Information Needs of Security Analysts”, The Journal of Accountancy, December 1975, pp: 65-70.12. Chipalkatti, Niranjan, “Market Microstructure Effects of the Transparency of Indian Banks”, National Stock Exchange, India Working Paper No.51, 2002, pp: 1-36.13. Choi, Frederick D.S., “Financial Disclosure and Entry to the European Capital Market”, Journal of Accounting Research, autumn 1973, pp: 159-174.14. Chow, Chee W. & Wong-Boren, Adrian, “Voluntary Financial Disclosures by Mexican Firms,” The Accounting Review, July 1987, pp: 533-41.15. Cooke, T.E., “An Assessment of Voluntary Disclosure in the Annual Reports of Japanese Corporations”, International Journal of Accounting, 1991, pp: 174-189.16. Cooke, T.E., “The Impact of Size, Stock Market Listing and Industry, Type on Disclosure in the Annual Reports of Japanese Listed Corporations”, Accounting and Business Research, 1992, pp: 229-237.17. Coombs, H.M. & Tayib, M., “Developing a Disclosure Index of Local Authority Published Accounts – A comparative study of local authority published financial reports between the U.K. and Malaysia”, www.glam.ac.uk/kus/1244/ publications.1998. International Journal of Research in IT, Management and Engineering www.gjmr.org 76
  • 78. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  EMERGING TRENDS IN HUMAN RESOURCE MANAGEMENT— A CHALLENGE TO THE ITESRaunak Narayan* ABSTRACTToday’s euphoric corporate environment has posed daunting challenges for human resourcemanagement. While demand for manpower is rising, supply is not able to keep pace. While wagebills are bloating, quality of manpower is deteriorating. And while, there is a surfeit ofgraduates, their employability is low, due to poor skills. This is just the ideal setting for themanagement to shed its decades of inhibition take centre stage and dictate strategy alongsideother key functions such as finance, marketing and sales.Human resource management (HRM) is a process of bringing people and organizations togetherso that the goals of each other are met. Over the years, highly skilled and knowledge based jobsare increasing while low skilled jobs are decreasing. This calls for future skill mapping throughproper HRM initiatives. Globalization of the world economy and several other trends are againtriggering changes in how companies manage and utilize their human resources.The Indian Information Technology Enabled Services (ITes) industry has been one of the greatsuccess stories of modern India. An industry that did not exist two decades ago is now the breadand butter of the nation and the envy to the world. It has created international benchmark forquality, proving to the world and to ourselves that Indian companies can compete globally andwin on quality. It has demonstrated what can be achieved by unleashing the power of middleclass, first generation entrepreneurship in India.Hence, The ITes organizations which is working on the principle of attracting, managing,nurturing and retaining their employees is moving ahead with the competition and is havingcompetitive advantage over other organizations. And to adopt this principle, now it has becomevery essential to face the challenges posed by the new trends of HR. It is this theme upon whichthis paper has been worked out. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     77 
  • 79. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 Keywords—Human Resource Management, Information Technology Enabled Services (ITes),Competitive Advantage, Attrition, BPOINTRODUCTIONIn the life of any nation, company or individual, movement is life and stagnation is death.Therefore, as long as companies are growing, they are fully alive. Organizations must movecontinuously from one process to another, from one strategy to another, and from one structureto another. So long as we are renewing these kinds of things and re-looking at them, that’s wheregrowth and achievement comes in. Human Resource Management (HRM) has evolvedconsiderably over the past century, and experiences a major transformation in form and functionprimarily within the past two decades. Driven by a number of significant internal and externalenvironmental forces, HRM has progressed from a largely maintenance function, to what manyscholars and practitioners today regard as the source of sustained competitive advantage fororganizations operating in a global economy. Human Resource (HR) is the only function wherebuilding capabilities takes place—building capabilities of organization and individuals. And thatis why HR will have to build organizations whether it is ITes or any other. Building,grooming/preparing people, building different kind of mindsets, defining roles and making themunderstand what kind of society and landscape is going to emerge, become extremely important.ITes is defined as outsourcing of processes that can be enabled with information technology andcovers diverse areas like finance, HR, administration, health care, telecommunication,manufacturing, etc. Armed with technology and manpower, these services are provided from e-enabled locations. ITes is a catchall term used for the myriad processes that ant bureaucraticentity undertakes in servicing its employees, vendors, customers. The Indian Ites industry hasrapidly opened up, expanded, matured and with a wave of consolidation has scripted newinitiatives.*University of Calcutta International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     78 
  • 80. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 With substantial evolution being witnessed, India has become the ideal and most preferredoffshore destination. Numerous factors such as supply of skilled manpower, global standardtelecom infrastructure, proactive and positive policy environment and friendly corporate taxpolicies have given India an edge in the global marketplace. In spite of offering distinctadvantages such as cost competitiveness, highly skilled labor and a high level of servicematurity, the industry witnessed certain unique challenges especially in the area of HR. Ofmyriad HR-related challenges faced by the industry, the critical ones are the attrition and scarcityof professionals equipped with necessary domain knowledge and communication skills. Despitebeing global phenomena, these challenges have become a matter of concern in Indian ITesindustry.EMERGING TRENDS IN HROver the years, highly skilled and knowledge based jobs are increasing while low skilled jobs aredecreasing. This calls for future skill mapping through proper HRM initiatives. Indianorganizations are also witnessing a change in systems, management cultures and philosophy dueto the global alignment of Indian organizations. Hence, it is necessary for the management toinvest considerable time and amount, to learn the changing scenario of the HR in the 21stcentury. In order to survive the competition and be in the race, HR department shouldconsciously update itself with the transformation in HR and be aware of the HR issues croppingup. With high attrition rates, poaching strategies of competitors, there is a huge shortage ofskilled employees and hence, a company’s HR activities play a vital role in combating this crisis.Suitable HR policies that would lead to the achievement of the organization as well as theindividual’s goals should be formulated.Some recent trends that are being observed are as follows: Traditional HR Practice Emerging HR practice Administrative Role Strategic Role Reactive Proactive International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     79 
  • 81. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  Separate from Company Mission Key part of Organizational Mission Production Focus Service Focus Functional Organization Process based Organization People as expenses People as key Investments/ AssetsTo leapfrog ahead of competition in this world of uncertainty, organizations have introduced six-sigma practices. Six-sigma uses rigorous analytical tools with leadership from the top anddevelops a method for sustainable improvement. These practices improve organizational valuesand helps in creating defect free products or services at minimum costs.  Human resource outsourcing is a new accession that makes a traditional HR department redundant in an organization  With the increase of global job mobility, recruiting competent people is also increasingly becoming difficult, especially in India. Therefore, organizations are required to work out a retention strategy for the existing skilled manpower.  To have a competitive advantage over rivals, organizations are working on the principle of Attracting, Managing, Nurturing and Retaining their employees.  Companies no more believe in the tall hierarchical structures, and cubical with closed doors of the boss, but have given way for flat organizational structures with more spans of control and less chain of command. In place of being the autocratic leader or manager, they play the role of team builders, mentors, coach, or counselors.  Following the principles of retaining the brains in the organization, the policies have become more and more flexible providing alternative and flexible work schedule. Flexi time, compressed week, job sharing, etc  Organizations today are not only making the structure and policies employee friendly rather they are trying to improve the quality of work life where International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     80 
  • 82. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  employees can enjoy their working and will be able to manage the balance between work life and personal life. They provide them the in-house facility of health club, yoga, meditation, alternative work schedule, picnics, and family get together where they can reduce their stress and strains. They also provide educational and medical facility.  Training and Development are the other areas where organizations are trying to take the lead over other organizations so that employees can be made multi- skilled to handle multiple tasks. The new horizon has opened up where the organizations competing are clubbing together to form the network of talents.  Other areas where remarkable changes are being made are in communication pattern. Gone are those days when employees feared talking to their bosses. Things are replaced by cross communication, gang plank mechanism, open door policy, internet, intranet, mentoring, counseling, coaching, etc. Communication is no more restricted to form top to bottom rather bottom to up is encouraged more in the organization to make functioning more smooth and to have grievance free, satisfied employees.  With the continuous rise in competition, business cannot flourish if individualism is prevailing in the organization. Therefore, to meet the need of the time the growing organizations are following collectivism culture, where working in groups and teams are emphasized.  Performance appraisal has also taken a new shape. It is not confined to the boss and subordinates, rather more emphasis is being given on overall appraisal of the employees (360 degree appraisal). Employees are also given opportunities for succession growth.The ITes industry, which is rapidly growing industry in India, is not an exclusive of the abovestated emerging trends; moreover it is mainly the cause and effected industry for the changes inHRM. Hence, it is very essential to know the challenges posed by those merging HR trends toITes industry. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     81 
  • 83. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 CHALLENGES OF EMERGING HR TRENDS TO ITES  Attracting and Retaining Talent—The ITes industry has, during the last decade, been probably the most attractive sector to workin. It has therefore been able to get nest talent. The challenge now is to safeguard and build onthis prime position. Attractive compensation, challenging assignments, good working conditionsand growth opportunities are amongst the main determinants of where talent gravitates, alongwith the indefinable “glamour value” of a company. Taking care of these parameters is anecessary task for the ITes industry.  High level of AttritionWhile India does have a large talent pool, not all are ‘industry –ready’ or equipped with thenecessary skill sets to become useful to the companies. This means there is plenty of supply atthe entry level but huge gaps in the middle and senior management levels. This has resulted inincreased levels of poaching and attrition cases. Presently, the average attrition rate faced by thisindustry is somewhere around 30-35 percent.  Not a serious career optionAnother very critical issue of concern for HR managers is that most students and professionalsworking in call centers do not see this industry as a long-term career option due to the inherentnature of the job (monotonous and lacking challenges), most of the time there is low interest inthe work.  Mismatch of ExpectationsExpectations mismatch leads to higher attrition. This is partly due to the perceptions created inthe general public with respect to the career growth, type of work, compensation offered,competition, etc. Many a times, people are not able to create a work-life balance and often optout. The right positioning will help attract the right profile of associates , which will International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     82 
  • 84. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 automatically manage their expectations from the industry and this will, in turn lead to lowerattrition rates.  Communication IssueLack of effective communication is another contentious issue. The absence of regular, two-waycommunication between agents, their team managers and the senior management is a commoncomplaint in the industry.  High training costsOn an average, the ITes companies incur three types of training costs—voice/ accent, soft skillsand process training. For a start-up, in the initial stage the training costs will be high. It generallyaccounts for four months salary of employee hired, though the actual training would be probablybeing for just a month.  Generating motivation and increasing efficiencyGenerating motivation and increasing efficiency is far more difficult in situations where the jobis repetitive and routine, as in many ITes operations. This is a real challenge to managers. This isimportant because a key part of India’s value proposition as the outsourcing destination is basedon productivity and quality- factors that depend critically on motivation.  CompensationCompensation is probably the single most important parameter in most cases. The challenge hereis to provide an attractive package in context of rising expectations, and yet minimize overallcost escalation. In this situation, “poaching” people from other companies by offering higher paypackages is self-defeating for the industry as a whole. An important correction lies in ensuring anever-growing and sufficiently large supply pipeline for fresh entrants.  The challenges of workplace diversityThe future success of any organization relies on the ability to manage a diverse body of talentthat can bring innovative ideas, perspectives and views to their work. The challenge faced ofworkplace diversity can be turned into a strategic organizational asset if an organization is able International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     83 
  • 85. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 to capitalize on this melting pot of diverse talents. With the mixture of talents of diverse culturalbackgrounds, genders, ages, and lifestyles, an organization can respond to business opportunitiesmore rapidly and creatively, especially in the global arena, which must be one of the importantorganizational goals to be attained. More importantly, if the organizational environment does notsupport diversity broadly, one risks losing talent to competitors.  Dearth of innovative and efficient HR professionalAIMA 2003 report projected that tourism and IT/ ITes would generate between 20- 72 millionjobs by 2020. Most of this employment-generation is happening in people-intensive sectors.Thus, the need for a strong HR backbone arises. Even at a very conservative estimate we arelooking at least 5 million new jobs in the next five years. And a quick calculation would showthat even if we need one HR professional for 1000 employees, one needs at least 5000 new HRprofessionalsFew Solutions  Moving towards ‘B class’ citiesDue to the high demand and supply gap and scaling attrition numbers, many companies aremoving towards ‘B class’ cities like Chandigarh, Bhopal, Lucknow and Dehradun, to attracttalent and set up their operations. In Karnataka, the ITes companies are looking towardsMangalore, Hubli, and Mysore rather than concentrating only in Bangalore.Looking for career oriented employees—there is also a change in employee profile, withorganizations looking for older and experienced people who will bring in stability. Therequirement is for those people for whom salary is not just a pocket money, but a careeropportunity. The ideal employees for BPOs would be people from the middle and lower-middleincome households, who are willing to work hard and have a strong sense of responsibility anddedication towards their employers. Initially, though it might lead to scaling training costs, as thesection might lack in basic communication and soft skills.  Proper rewarding A research report says that in today’s scenario. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     84 
  • 86. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619   70% of your employees are less motivated than they used to be  80% of your employees could perform significantly better if they wanted to  50% of your employees only put enough effort into their work to keep their jobOne might be aware of Employee reward covers how people are rewarded on accordance withtheir value to an organization. The ways in which people are valued can make a considerableimpact on the effectiveness of the organization, and is at the heart of the employmentrelationship.  Educating about career opportunitiesThe common misconception is that there are only three position in ITes or BPOs-that of anagent, a team leader and the project leader. There is however more to it. According to DeepakDhawan, VP (HR) of EXL Services, there is an immense opportunity for professionals with aCA or MBA background: “An individual can choose from managing quality, get into training,Sex sigma process, problem solving equations, relationship management, HR and workflowactivities or business development”.  Government initiativesNasscom has recently started a project with different private players training institutes andacademia in Andhra Pradesh, Karnataka and Kerala, for preparing “employable” ITes workforce.According to A. Sundararajan, IT secretary of Kerala, “It will help chart out indicative domain-wise manpower requirement projections from the industry. Skill set standardization, Governmentrecognized certification in ITes, and inclusion of ITes as a discipline in graduate studies byuniversities will help in making ITes as a career choice by students”.  Creating effectiveness and efficiency through motivationEmpowering, engaging and energizing employees are established ways of creating effectivenessand efficiency through motivation. Organizational structures, systems and procedures arefacilitators of these, and companies need to focus greater attention on these aspects.  Providing an excellent physical work environment International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     85 
  • 87. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 The ITes industry has to provide an excellent physical work environment. It needs to continue tobe a leader in providing these facilities, including food, fitness and sports facilities. While these“add-ons” are not inconsequential, work satisfaction through challenging, cutting-edgeassignments, and substantial growth prospects are definitely major determinants for retention.  Consider the employees as a resourceThe statement “people are our greatest asset”, though a cliché that is often heard in corporateboardrooms is, nevertheless, true in most industries. However, nowhere are human resources ascritically important as in the ITes sector. Human resources are not only the drivers and principalvalue-creators of the output of this industry; they are also the intellectual capital or the“infrastructure investment”.  HR managers should evolve with new rolesWith the increase in competition, locally or globally, organizations must become more adaptable,resilient, agile and customer-focused to succeed. And within this change in environment, the HRprofessional has to evolve to become a strategic partner, an employee sponsor or advocate,change mentor within the organization. The HR manager will also promote and fight for values,ethics, beliefs, and spirituality within the organizations.  Improving employabilityDespite the large number of students graduating, it is common to hear companies complain aboutnot finding suitable candidates. The updating of syllabi and ensuring relevant content would beuseful. In addition, it would be worthwhile to include some basic IT courses for the Science,Mathematics, and Commerce and Economics students. This would enable graduates in thesestreams to be considered for employment in a number of ITes jobs.CONCLUSIONTo conclude, change is necessary to survive. Those who change with the change survive andthose don’t vanish. What is today may be obsolete tomorrow. It is necessary to upgrade andrestructure every time to withstand and face the situations. HR policies of the ITes organizationshould also be changed with the time and new strategies, policies should come up to retain the International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     86 
  • 88. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 talents in the organization to increase the success ratio in today’s competitive globalenvironment. HR managers have to manage all the challenges that they would face fromrecruiting employees, training them, and developing strategies for retaining them and building upan effective career management system for them. Just taking care of employees would not beenough; new HR initiatives should also focus on the quality needs, customer-orientation,productivity, stress, team work and leadership building.REFERENCES [1] Dr. Nagaraju Battu (2007), “Human Resource Development”[2] Dr. Pritam Singh- HR, The Taskmaster, Times of India daily Ascent, 24th November, 2010[3] Prof. Anitha H.S. “Succession Planning”, “Benchmarking for Infusing Competitive Cultureamong Indian PSUs” and “Commercial viability of PSUs”, Deccan Herald, August 25,2009[4] Mrs. Soumya K.R. (2010) “Assessment of training need and evaluation of trainingeffectiveness on employees of select ITes in Bangalore”[5] Dr. Alvin Chan (2010), “Challenges of HRM”[6] Rituparna Banerjee (2010), “Emerging trends on HRM”[7] Punita Jasrotia Phukan (2009), “Changing HR paradigm in the ITes sector”[8] K.P. Kanchana (2009), “Emerging trends in HR”[9] Sanjeev Sharma, “Retention Strategies in ITes-BPO industry”[10] www.bpoindia.org International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     87 
  • 89. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  FUNDAMENTAL CHALLENGES IN EMERGENT FIELD OF SENSORNETWORK SECURITY AND INITIAL APPROACHES TO SOLVE THEMD. P. Mishra*M. K. Kowar ** ABSTRACTRapid technological growth in the area of micro electro-mechanical systems (MEMS) hasspurred the development of small inexpensive sensors capable of intelligent sensing. Asignificant amount of research has been done in the area of connecting large numbers of thesesensors to create robust and scalable Wireless Sensor Networks (WSNs). Proposed applicationsfor WSNs include habitat monitoring, battlefield surveillance, and security systems. Althoughindividual sensor nodes have limited capabilities, WSNs aim to be energy efficient, self-organizing, scalable, and robust. Almost all of the research is centered on meeting thesechallenges, but relatively little work has been done on security issues related to sensor networks.The resource scarcity, ad-hoc deployment, and immense scale of WSNs make securecommunication a challenging problem. Since the primary consideration for sensor networks isenergy efficiency, security schemes must balance their security features against thecommunication and computational overhead. Paper will describe the fundamental challenges inthe emergent field of sensor network security and the initial approaches to solve them.Keywords: Security, Sensor Networks*Department of Computer Science & Engineering, BIT, Durg** Department of Electronics & Telecommunication Engineering, BIT, Durg International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  88
  • 90. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 INTRODUCTION & MOTIVATIONRapid technological growth in the areas of micro electro-mechanical systems and miniaturizationhas spurred the development of a new kind of network. This network is composed of small,inexpensive sensors capable of intelligent sensing. Much research has been done with the aim ofconnecting large numbers of these sensors to create robust and scalable Wireless SensorNetworks (WSNs) on the order of hundreds of thousands of devices. Communication usuallyconsists of source nodes which sense the data and return it to sink nodes over multiple hops.Sink nodes may be ordinary sensor nodes or specialized base stations with greater resources.Sensor network proponents envision a future in which thousands to millions of tiny sensordevices will be embedded in almost every aspect of life. The goal is to create intelligentenvironments capable of collecting massive amounts of information, recognizing significantevents automatically, and responding appropriately. Sensor networks facilitate “large-scale, real-time data processing in complex environments” [14]. If sensor networks are to attain theirpotential, however, secure communication techniques must be developed in order to protect thesystem and its users. The need for security in military applications is obvious, but even morebenign uses, such as home health monitoring, require confidentiality so widespread deploymentand overall success of sensor networks will be directly related to their security strength.SENSOR SECURITY CHALLENGESThe nature of large, ad-hoc, wireless sensor networks presents significant challenges in designingsecurity schemes. Some of the most pronounced challenges are described below.Wireless MediumThe pervasive applications proposed for sensor networks necessitate wireless communicationlinks. Furthermore, the ad-hoc deployment of sensor motes makes wired communicationcompletely inappropriate. The wireless medium is inherently less secure because its broadcastnature makes eavesdropping simple. Any transmission can easily be intercepted, altered, orreplayed by an adversary. The wireless medium allows an attacker to easily intercept validpackets and easily inject malicious ones. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  89
  • 91. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 Ad-Hoc DeploymentThe ad-hoc nature of sensor networks means no structure can be statically defined beforehand.The network topology is always subject to changes due to node failure, addition, or mobility.Nodes may be deployed by air drop, so nothing is known of the topology prior to deployment.Since nodes may fail or be replaced the network must support self-configuration. Securityschemes must be able to operate within this dynamic environment.Hostile EnvironmentMost challenging factor is the hostile environment in which sensor nodes function. Motes facethe possibility of destruction or (perhaps worse) capture by attackers. Since nodes may be in ahostile environment, attackers can easily gain physical access to the devices. Attackers maycapture a node, physically disassemble it, and extract from it valuable information (e.g.cryptographic keys). The highly hostile environment represents a serious challenge for securityresearchers.Resource ScarcityThe extreme resource limitations of sensor devices pose considerable challenges to resource-hungry security mechanisms. A representative example of a sensor device is the Mica mote. Ithas a 4 MHz Atmel ATMEGA103 CPU with 128 KB of instruction memory, 4 KB of RAM fordata, and 512 KB of flash memory [7]. The radio operates at up to 40 Kbps bandwidth at a rangeof a few dozen meters. Such hardware constraints necessitate extremely efficient securityalgorithms in terms of bandwidth, computational complexity, and memory.Immense ScaleFinally, the proposed scale of sensor networks poses a significant challenge for securitymechanisms. Simply networking tens to hundreds of thousands of nodes has proven to be asubstantial task. Security mechanisms must be scalable to very large networks while maintaininghigh computation and communication efficiency.ATTACKS & DEFENSES International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  90
  • 92. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 Security goals for sensor networks include the same four primary objectives as conventionalnetworks: availability, confidentiality, integrity, and authentication. Although sensor networksecurity is characterized by the same properties as traditional network security. Karlof andWagner identify two major classes of attackers: mote-class and laptop-class. Mote-class attackersare constrained to the CPU, power, bandwidth, and range limitations of the mote platform.Laptop-class attackers, however, may possess more powerful hardware such as a faster CPU, alarger battery, a high-power radio transmitter, or a sensitive antenna. This section examines thesecurity attacks and corresponding defenses at each level of the network.Physical LayerAttacks at the physical level include radio signal jamming and tampering with physical devices.Jamming- well-known attack on wireless communication is simply interference with the radiofrequencies used by a device’s transceiver. It represents an attack on the availability of anetwork, thus creating a denial-of-service condition [14].The standard defense against jamming involves the use of spread-spectrum or frequency hoppingtechniques. Prevention of denial of service attacks is a difficult task. Since most sensor networkscurrently use single frequency communication, Wood, Stankovic, and Son have proposed aJammed Area Mapping (JAM) service which emphasizes detection and adaptation in response tojamming. They assume that only a portion of the network is being jammed and attempt to mapthis area so it can be avoided. Nodes in the affected area switch to low power mode. Informationabout jammed areas is passed to the network layer so it can successfully route packets around thedead areas. If spread spectrum techniques cannot be incorporated into motes, then detectionalgorithms such as JAM may be important in defending against jamming attacks.Tampering A second problematic issue at the physical layer is the relative ease and potentialharm of device tampering. This problem is exacerbated by the large-scale, ad-hoc, pervasivenature of sensor networks. Access to thousands of nodes spread over several kilometers cannotbe completely controlled [14]. Attackers may very well have greater physical access to nodesthan the network administrator. Nodes may be captured, interrogated, and compromised without International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  91
  • 93. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 difficulty. While node destruction is undesirable, node compromise may be even more dangerousbecause of the cryptographic material compromised.Link LayerThe link and media access control (MAC) layer handles neighbor-to-neighbor communicationand channel arbitration. Like the physical layer, the link layer is particularly susceptible to denialof service attacks.Collision If an adversary can generate a collision of even part of a transmission, he can disruptthe entire packet [Perrig, Stankovic, and Wagner 2004]. A single bit error will cause a CRCmismatch and possibly require retransmission. In some MAC protocols, a corrupted ACK maycause exponential back-off and unnecessarily increase latency. Although error-correcting codesprotect against some level of packet corruption, intentional corruption can occur at levels whichare beyond the encoding scheme’s ability to correct. The advantage, to the adversary, of thisMAC level jamming over physical layer jamming is that much less energy is required to achievethe same effect: preventing devices from successfully transmitting packets.Exhaustion Another malicious goal is the exhaustion of a network’s battery power [10]. Inaddition to the previous types of attacks, exhaustion may also be induced by an interrogationattack. In the IEEE 802.11-based protocols, for example, Request To Send (RTS) and Clear ToSend (CTS) packets are used to reserve bandwidth before data transmission. A compromisednode could repeatedly send RTS packets in order to elicit CTS packets from a targeted neighbor,eventually consuming the battery power of both nodes [10].Unfairness A more subtle goal of the previously described attacks may be unfairness in theMAC layer [10]. A compromised node can be altered to intermittently attack the network insuch a way that induces unfairness in the priorities for granting medium access. This weak formof denial of service might, for example, increase latency so that real-time protocols miss theirdeadlines [10].Network Layer International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  92
  • 94. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 The network layer is responsible for routing packets across multiple nodes. Due to the ad-hocnature of sensor networks, every node must assume routing responsibilities. WSNs areparticularly vulnerable to routing attacks because every node is essentially a router.Classifications of routing attacks are summarized below and are followed by a general discussionof secure routing techniques.False Routing Information The most direct attack on routing is to spoof, alter, or replay routinginformation. This false information may allow adversaries to create routing loops, attract or repeltraffic, shorten or extend route lengths, increase latency, and even partition the network[7].Clearly, the falsification of routing information can cripple a network. The standard solutionis to require authentication for routing information,Selective Forwarding Selective forwarding is a more subtle attack in which some packets arecorrectly forwarded but others are silently and intentionally dropped. A compromised node couldbe configured to drop all packets, creating a so-called black hole. Since the network is capable ofhandling node failure it may conclude that the compromised node has failed and find anotherroute. If the compromised node selectively forwards packets, the neighboring nodes will believethat the malicious node is still functioning correctly and continue to route packets to the node.Sinkhole Attack In the sinkhole attack, a node spuriously advertises a very good route to a sinknode (base station) in order to lure all nearby traffic to itself. Thus all traffic within some sphereof influence is drawn into the sinkhole centered at the compromised node. This attack enables theselective forwarding attack along with other attacks. An adversary mounting a laptop-class attackmay actually provide the fastest route to a sink by using its greater range to reach the sink in asingle hop.Sybil Attack The Sybil attack occurs when a single node claims to be other nodes in the network.Geographic routing protocols are particularly vulnerable to the Sybil attack since they aredesigned with the assumption that no node can be in two places at once. If a node lies about itlocation, it can significantly disrupt routing performance in geographic routing protocols. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  93
  • 95. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 Wormhole Attack The wormhole attack is used to convince two possibly distant nodes that theyare neighbors so that the attacker can place himself on the route between them. Basically, theadversary tunnels messages from one part of the network to another through an out-of-boundchannel available only to the attacker. Wormholes typically involve two colluding nodes.HELLO Flood Attack The Hello flood attack, a novel attack proposed by Karlof and Wagner,exploits routing protocols that require periodic HELLO packets be transmitted to announce thepresence of a node. Nodes which receive a HELLO packet assume they are within radio range ofthe sender, i.e., the sender is a neighboring node. This assumption may be false in the case of alaptop-class attacker. An adversary with a powerful transmitter may be able to transmit a singleHELLO packet to every node in the network and convince every node that it is a one-hopneighbor. As a result, the network is left in a state of confusion. If, for example, the attackeradvertises a very quick route to a base station in the HELLO packet, many non-neighbor nodeswill attempt to route packets through the malicious node. In actuality, however, they will besending packets into oblivion. Karlof and Wagner point out that this attack is actually a “one-way, broadcast wormhole.” The simplest solution for this attack is to verify the bidirectionalityof a link before acting on its information. Essentially, routing messages from one-way links areignored. Karlof and Wagner propose an identity verification protocol to defend against theHELLO flood attack.Acknowledgement Spoofing The last routing attack Karlof and Wagner identify is theacknowledgement spoofing attack. Several routing protocols rely on link layeracknowledgements for determining next-hop reliability. If an adversary can respond for weak ordead nodes, he can deceive the sender about the strength of the link and effectively mount aselective forwarding attack. The artificial reinforcement allows the attacker to manipulate therouting through the weak or dead node.There have been several approaches to defend against network layer attacks. Authentication andencryption are a first step, but more proactive techniques such as monitoring, probing, and International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  94
  • 96. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 transmitting redundant packets have also been suggested. Secure routing methods protect againstsome of previous attacks. Proposed techniques are described below.Authentication & Encryption Link layer authentication and encryption protect against mostoutsider attacks on a sensor network routing protocol. Even a simple scheme which uses aglobally shared key will prevent unauthorized nodes from joining the topology of the network. Inaddition to preventing selective forwarding and sinkhole attacks, authentication and encryptionalso make the Sybil attack impossible because nodes will not accept even one identity from themalicious node [7]. SPINS and TinySec are two proposed solutions for link level encryption andauthentication.Monitoring A more active strategy for secure routing is for nodes to monitor their neighbors andwatch for suspicious behavior [14]. In this approach, nodes act as “watchdogs” to monitor thenext hop transmission of the packet.Probing Another proactive defense against malicious routers is probing [14]. This methodperiodically sends probing packets across the network to detect blackout regions. Sincegeographic routing protocols have knowledge of the physical topology of the network, probing isespecially well-suited to their use.Redundancy is another strategy for secure routing [14]. An inelegant approach, redundancysimply transmits a packet multiple times over different routes. Hopefully, at least one route isuncompromised and will correctly deliver the message to the destination.PROPOSED SOLUTIONSWhile the majority of the research in sensor networks has focused on making them feasible anduseful, a few researchers have proposed solutions to the security issues discussed previously.Sensor network security mechanisms can be divided into two categories: communicationprotocols and key management architectures. Communication protocols deal with the International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  95
  • 97. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 cryptographic algorithms used to achieve availability, confidentiality, integrity, andauthentication. Key management architectures handle the complexities of creating anddistributing keys used by communication protocols.Communication ProtocolsCurrently there have been two major secure communication protocols proposed for sensornetworks: SPINS [2] and TinySec [Karlof, Sastry, and Wagner 2004]. Both protocols work at thelink level to provide message confidentiality, authentication, and integrity using symmetriccryptography. The limited memory and CPU speeds of sensor nodes almost completely excludethe use of asymmetric cryptography sensor networks.SPINS SPINS (Security Protocols for Sensor Networks) is comprised of two link layerprotocols: SNEP and µTELSA. SNEP (Secure Network Encryption Protocol) provides dataconfidentiality, two-party authentication, and data freshness. Perrig et al. identify three patternsof communication in sensor networks: node to base station, base station to node, and base stationto all nodes. SNEP handles the first two types, and µTELSA handles the last. In order tominimize computation and memory requirements, SNEP bases all symmetric cryptographicprimitives (encryption, message authentication code, hash, and random number generator) on thesame block cipher, RC5. Another design goal is to minimize communication overhead. This isaccomplished by reducing the packet overhead to 8 bytes and by storing state information insteadof transmitting it with each packet.SNEP supports data authentication, replay protection, and semantic security [11]. Authenticationis provided by calculating and appending a message authentication code (MAC) to eachmessage. A MAC is essentially a cryptographically secure checksum [Karlof, Sastry, andWagner 2004]. The MAC is recalculated upon reception and compared to the value in thetransmission. To implement replay protection, SNEP requires a synchronized counter value ateach node. The MAC is calculated using a secret key and the counter. As a result, out-of-syncpackets will not be accepted. SPINS includes a counter exchange protocol for synchronizingcounter values between two hosts. Although maintaining a synchronized counter adds significant International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  96
  • 98. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 overhead, it allows semantic security, a strong security property which assures that identicalmessages are encrypted differently each time they are encrypted. For example, if a sensor issimply reporting YES or NO regarding the occurrence of some event, an attacker may be able todiscover the encrypted value of NO and subsequently be able to understand all encryptedtransmissions. By encrypting the data based on the counter as well as the key, each NO willencrypt differently.μTELSA, the second part of SPINS, provides authenticated broadcast for sensor networks. Thegoal of μTELSA is to allow base stations to transmit authenticated broadcasts to all of the nodeswhile preventing a compromised node from forging messages from the sender. μTELSA usessymmetric mechanisms to create an asymmetric system using a loosely synchronized clock.Receivers buffer broadcast packets until they receive the decryption key which is disclosed oncein a specified time interval (epoch). The keys are calculated using a one-way hash function (F)and are disclosed in the reverse order that they are generated. Once a node receives a key, it canapply the same hash function to calculate the keys for previous epochs and decrypt bufferedpackets. Figure 1 illustrates this process. Figure 1: μTELSA key disclosure and computation. Each hash mark denotes an epoch. P1, P2,…P7 represent packets.SPINS performs reasonably well according to its authors. Although key setup is expensive (4ms), encrypting a 16 byte message and calculating its MAC only takes 2.5 ms. The limitedbandwidth of the test platform, 10 kbps, allows time to perform key setup, encryption, and MACcalculation for every packet. The performance of μTELSA is bounded by the amount of bufferspace available. Consequently, key disclosures must happen relatively frequently and must bereliably received.The stated limitations of SPINS are that it does not completely deal with compromised nodes andit does not deal with denial-of-service attacks. SPINS merely ensures that a comprised nodedoes not reveal the key to every node in the network. Additionally, SNEP needs tightsynchronization of counters since they are not transmitted. Another design weakness is the International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  97
  • 99. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 dependence of μTELSA on buffering packets. The extremely limited storage space characteristicof sensors devices makes buffering particularly unattractive.TinySec TinySec is a more recent solution to the sensor link layer security problem. TheTinySec protocol provides access control, message integrity, and message confidentiality.TinySec explicitly omits replay protection, recommending it be performed at the applicationlayer. The designers of the protocol emphasized usability and transparency in hopes of increasingTinySec’s adoption. To this end, TinySec has been incorporated into the official release ofTinyOS, the small, event-driven operating system designed for sensor motes. Unlike SPINS,TinySec has been fully implemented and exhibits promising performance. Encryption andauthentication can be performed in software with only 10% energy overhead and 8% increasedlatency.TinySec operates in two modes: authenticated encryption (TinySec-AE) and authentication only(TinySec-Auth). Like SPINS, TinySec implements authentication and integrity by the use ofmessage authentication codes (MACs). TinySec uses a cipher block chaining construction (CBC-MAC) for computing and verifying MACS because of its efficiency and speed. TinySec’sdesigners make authentication mandatory but encryption optional because not all messages needto be kept secret. Message authentication and integrity, both provided by the MAC, are criticalfor security since they block invalid senders and protect the data from corruption. The MACprotects the entire contents of the packet, including header information. Since the 2 byte CRC ofa normal TinyOS packet is redundant, it is replaced by a 4 byte MAC. IV Dest AM Len Src Ctr Data MAC (2) (1) (1) (2) (2) (0 - 29) (4) (a) Tiny-Sec AE Packet Format Dest AM Len Data MAC (2) (1) (1) (0 - 29) (4) (b) Tiny-Sec Authentication Packet Format Dest AM Len Grp Data MAC (2) (1) (1) (1) (0 - 29) (4) (c) Tiny-OS Packet Format Figure:2 International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  98
  • 100. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 Figure 2: TinyOS and TinySec packet formats. The byte size of each field is indicated. Hatchedfields are protected by the MAC. In TinySec-AE, the dark grey data portion is encrypted.This effectively adds only 2 bytes of overhead for authentication. Refer to Figure 2(b) for anillustration of the TinySec-Auth packet format.If confidentiality of message contents is required by the application, TinySec-AE is used. Forencryption, TinySec uses the Skipjack block cipher by default but also supports RC5. In order toprovide semantic security, TinySec uses an initialization vector (IV) to encrypt each packet andsends this value in each packet. To minimize packet size overhead, the entire header contents(destination, AM, length, and source) and a 2 byte counter are used as the IV. This effectivelygives an 8 byte IV for the cost of only 2 bytes. Figure 2(c) illustrates this structure. Sufficientlylong IVs are critical because repeated IVs leak information about a cryptosystem. In the case ofthe CBC cipher used by TinySec, only the length of the longest shared prefix of two messages isrevealed if the entire 8 byte IV repeats. A repetition only occurs when one node sends twopackets to the same destination with the same AM type, length, and counter value. Given the lowdata rate for sensor nodes, the probability for such a repetition is low.The performance of TinySec has proven that sensor network security can be efficiently done insoftware. TinySec requires 728 bytes of RAM and 7146 bytes of program space. The energyoverhead imposed by TinySec is 3% for TinySec-Auth and 10% for TinySec-AE. The extracomputation increases the time to transmit a packet 1.6% for TinySec-Auth and 7.9% forTinySec-AE. The energy, bandwidth, and latency of TinySec are all less than 10% and duealmost entirely to the increased packet length. Not surprisingly, TinySec is being used by severalother research projects throughout the country. With its impressive performance and ease of use,TinySec is the best sensor network security communication protocol to date.Key Management ArchitecturesDespite TinySec’s merits as a communication protocol, it does not even attempt to solve theissue of key management. Key management handles the generation and secure distribution ofcryptographic keys as well as techniques to protect the network from lost keys. A variety of International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  99
  • 101. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 strategies exist for accomplishing this task. Some of the major approaches are summarizedbelow.LEAP The efficiency and speed of symmetric algorithms are well suited to sensor nodes andhave been the default choice for sensor network designers. Most symmetric schemes require keysbe loaded onto devices before deployment. Using a different key for every link provides the bestsecurity against compromised nodes but is incompatible with the basic nature of sensornetworks. Sensor networks rely on data aggregation and in-network processing to increasenetwork efficiency. Nodes along the path consolidate data to reduce the overall number ofmessages in the network. This cannot take place if messages are encrypted. In an effort tobalance these two extremes, LEAP [14] utilizes four types of keys for different security levels.LEAP supports an individual key shared only with the base station, a pairwise key shared withanother sensor node, a cluster key shared with multiple neighboring nodes, and a group keyshared by all the nodes in the network. The advantage of LEAP is that it supports in-networkprocessing while minimizing the security impact of a compromised node to the node’simmediate neighbors. LEAP provides a key for every need. This property offers convenience atthe cost of storage space and complexity, neither of which are abundantly available to sensornodes.LKHW Another approach to key management is to use a hierarchy to store keys. Pietro et al.propose a scheme based on Logical Key Hierarchy (LKH) built on top of directed diffusion.Directed diffusion is a data-centric routing protocol that uses exploratory flooding to find thebest path to send events of interest. The extension of LKH over directed diffusion comprises theLKH Wireless (LKHW) protocol. LKHW is a secure multicast scheme that enforces backwardand forward secrecy. New nodes cannot decrypt old traffic, and evicted nodes cannot decryptfuture traffic. LKHW uses a tree structure to store keys. The root of the tree serves as the keydistribution center (KDC), and each leaf represents a user. Each leaf stores the set of keysbelonging to its direct ancestors up to the KDC. The reason for using a tree structure is toincrease the efficiency of re-keying. Re-keying occurs whenever a node joins or leaves the International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  100
  • 102. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 group. The energy required for re-keying is shown to be approximately logarithmic to the groupsize.Random Key Predistribution Another novel approach to key management is random keypredistribution [2]. In this strategy, a random pool of keys from the key space is preloaded intoeach node. Two nodes must find a common key in their sets in order to communicate. Achallenge-response protocol is used to verify that two nodes have a key in common.TinyPK Despite the fact that asymmetric cryptography has been almost universally consideredto be too resource-intensive for use in sensor networks, there have been some efforts to adaptpublic cryptography techniques to sensor devices. TinyPK [13] is one such project that uses theRSA cryptosystem to handle symmetric key distribution. To minimize calculations by the sensormotes, e=3 is used as the public exponent. Encryption simply requires cubing a 1024-bit numberand taking its residue modulo a large prime number. Implementing a public-key system requiresa modest amount of infrastructure including a Certificate Authority (CA). The CA’s public key ispreloaded onto each node and is used to verify messages from the CA. Despite the adaptations,TinyPK still performs slowly by current standards. Table 1 summarizes the operation times forRSA encryption at various key sizes. RSA Key Size Time (sec) 512 3.8 768 8.0 1024 14.5Table 1: RSA encryption (exponentiation) timesWatro et al. confess that the current implementation is too slow for RSA private operations(decryption) since execution times would be on the order of tens of minutes. They suggest usingTinyPK as a method of authenticating external parties to the sensor network and moving thecomputationally expensive operations to the external device when possible. Although public keycryptography possesses many advantages in handling key management, it is currently infeasible International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  101
  • 103. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 for node-to-node communication in sensor networks. Perhaps asymmetric techniques will beviable on more powerful hardware of the future. Most researchers predict, however, that deviceswill ride Moore’s Law down the price curve instead of increasing in speed. If this is the case,then algorithmic optimizations will be required for public-key systems.CONCLUSIONSensor networks hold the potential to transform the way computing affects life. In order to reachthis potential, secure communication must be achieved. The wireless, ad-hoc, resource-limitednature of sensor networks creates substantial challenges for researchers. At the physical layer,probable attacks include frequency jamming and device tampering, two techniques with knownsolutions but entailing greater financial cost. The link layer of sensor networks is also susceptibleto denial of service attacks in the form of maliciously induced collisions and exhaustion attacks.The network layer is particularly vulnerable since every node in a sensor network is a router.Although link layer encryption and authentication serve as a first layer of defense, maximumsecurity can only be achieved by designing routing algorithms with security in mind. SPINS andTinySec satisfactorily address the issue of link layer encryption, authentication, and integrity butrequire key management architectures to be practical. Current key management solutions are notsufficiently adapted to the unique requirements of sensor networks. If sensor networks are toreach their potential, secure communication must exist.REFERENCES[1] Agrawal, Dharma P.; Qing-An Zeng. 2003. Introduction to Wireless and Mobile Systems. Brooks/Cole – Thompson, Pacific Grove, CA.[2] Chan, H., A. Perrig, and D. Song. Random Key Predistribution Schemes for Sensor Networks. IEEE Symposium on Security and Privacy (SP) (May 11 - 14, 2003).[3] Hill, Jason, Robert Szewczyk, Alec Woo, Seth Hollar, David Culler, and Kristofer Pister. System architecture directions for networked sensors. In Proceedings of the Ninth International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS IX) (November 2000). International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  102
  • 104. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  [4] Hu, Y.C., A. Perrig, and D.B. Johnson. Rushing Attacks and Defense in Wireless Ad Hoc Network Routing Protocols. Proceedings of the ACM Workshop on Wireless Security (WiSe03) (San Diego, California, September 19, 2003). [5] Huang, Q., J. Cukier, H. Kobayashi, B. Liu, and J. Zhang. Fast Authenticated Key Establishment Protocols for Self-Organizing Sensor Networks. Proceedings of the Workshop on Wireless Sensor Networks and Applications, (WSNA03) (San Diego, California, September 19, 2003). [6] Jolly, G., M.C. Kuscu, P. Kokate, and M. Younis. A Low-Energy Key Management Protocol for Wireless Sensor Networks. IEEE Symposium on Computers and Communications (ISCC03). (Kemer – Antalya, Turkey, June 30 - July 3 2003). [7] Karlof C. and D. Wagner. Secure Routing in Wireless Sensor Networks: Attacks and Countermeasures. Proceedings of the First IEEE International Workshop on Sensor Network Protocols and Applications (SNPA03) (11 May 2003). [8] Karlof, Chris, Naveen Sastry, and David Wagner. TinySec: A Link Layer Security Architecture for Wireless Sensor Networks. Proceedings of the Second ACM Conference on Embedded Networked Sensor Systems (SenSys’04) (November 3 - 5, 2004). [9] Law, Y. W., S. Dulman, S. Etalle, and P. Havinga. Assessing Security-Critical Energy- Efficient Sensor Networks. 18th IFIP TC11 Int. Conf. on Information Security, Security and Privacy in the Age of Uncertainty (SEC) (Athens, Greece, May 2003).[10] Perrig, Adrian, John Stankovic, and David Wagner. Security in Wireless Sensor Networks. Communications of the ACM, Volume 47, Issue 6 (June 2004): 53-57.[11] Perrig, Adrian, Robert Szewczyk, Victor Wen, David Culler, and J.D. Tygar. SPINS: Security protocols for sensor networks. In The Seventh Annual International Conference on Mobile Computing and Networking (MobiCom 2001), (2001).[12] Pietro, R.D., L.V. Mancini, Y.W. Law, S. Etalle, and P. Havinga. LKHW: A Directed Diffusion-Based Secure Multicast Scheme for Wireless Sensor Networks. International Conference on Parallel Processing Workshops (ICPPW03) (Kaohsiung, Taiwan. October 6 - 9, 2003).[13] Warto, Ronald, Derrick Kong Sue-fen Cuti, Charles Gardiner, Charles Lynn, and Peter Kruus. TinyPK: Securing Sensor Networks with Public Key Technology. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  103
  • 105. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 [14] Wood, A.D. and J.A. Stankovic. Denial of Service in Sensor Networks. IEEE Computer, Volume: 35, Issue: 10 (Oct. 2002):48-56.[15] Wood, A.D., J.A. Stankovic, and S.H. Son. JAM: A Jammed-Area Mapping Service for Sensor Networks. In The 24th IEEE International Real-Time Systems Symposium (RTSS) (Cancun, Mexico, December 2003). International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  104
  • 106. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  THE ECONOMICS & BUSINESS OF EUROPEAN LEAGUE FOOTBALL Dr. Rosy Kalra* ABSTRACTFootball is the most popular sport in the world & certainly one of the most lucrative businesses.It remains unparalleled in generating emotion & passion across the planet irrespective of thedivide & differences separating people. Furthermore, Football is a surprisingly resilient industry& not only weathered the storm of the global financial crisis that crippled major Europeaneconomies, but emerged unscathed & stronger from it all. Just a look into the latest revenuefigures amongst the richest European League clubs confirms this belief as their combinedrevenue has for the first time exceeded the €4 billion mark with almost all the clubs managing toimprove upon their last years performance.Key Terminology: Amortization -The annual cost of writing down the cost of buying newplayers*Assistant Professor, Amity Business School, Amity University, Noida (UP). International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  105
  • 107. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  INTRODUCTIONAmongst a seemingly positive ambit, there lies great churning not only in the operation of theFootball clubs but also the governing regulations. The major concern stem from the almostprecipitous levels of debt prevailing amongst the richest, most successful & popular EuropeanLeague clubs. 56% of the 733 clubs that had an audit done by UEFA (Union of EuropeanFootball Associations) suffered a loss. In the English Premier League alone 14 of the 20 clubsmade a loss in their most recent accounts.But what is more worrying is that debt levels continue to increase at an alarming rate & shows nosign of abating. As Football clubs continue to grow more & more indebted serious question arebeing leveled at the sustainability of the various business models prevalent amongst EuropeanFootball Clubs.The above developments subsequently are of major significance to one of the most popular &lucrative football leagues in Europe – The English Premier League. The success & consistentpresence of English clubs in the latter stages of the elite European competitions display theimportance of top tier English Football clubs & therefore how the top English Football clubsadapt to the changing landscape has deep ramifications in the evolution of the EuropeanFootballing landscape in the long run.LITERATURE REVIEWThe review of literature was carried to explore the ways & techniques that could be used to betterunderstand & interpret the Football industry & its true economic reality. The review of literaturefacilitated comparison of the results of previous analysis & the results of this study. Hence,review of literature has been instrumental in giving a better meaning to this study & has been asource of guidance for carrying out this study. Some of them include-Babatunde Buraimo and Rob Simmons (2006) model the impacts of market size and teamcompetition for fan base on matchday attendance in the English Premier League over the period1997-2004 using a large panel data set. It constructs a comprehensive set of control variables anduse tobit estimation to overcome the problems caused by sell-out crowds. It also accounts forunobserved influences on attendance by means of random effects attached to home teams. Also International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  106
  • 108. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 treatment of market size, with its use of Geographical Information System techniques, is moresophisticated than in previous attendance demand studies. The European Club Footballing Landscape report by UEFA (2008) is an 80-page report published in four languages – English, French, German and Russian – and the analyses contained within have formed an important basis for recent discussions on financial fair play, as well as contributing to increased transparency in club football – one of UEFAs key club licensing objectives. The report also deals with non-financial areas such as competition structures and attendance trends and, for the first time, features a pan-European analysis of stadium ownership and licensing results. The Bundesliga’s report on “The Economic State of Professional Football” The DFL released report detailing the economic state of professional football in Germany & includes the financial results that had previously been part of the DFL’s Bundesliga Report. The release presents the particulars of increased revenue & increased equity in the German league but also points to the subsequent increase in the prevailing debt levels inspite of strong performances in the elite European competitions translating to higher prize money payouts. Deloitte’s Annual Review of Football Finance describes a comparative survey of revenue among European clubs through its annual editions of Deloitte’s Football Money League. It details its finding through a football “Rich List”, ranking the top 20 European clubs on the basis of their financial clout & turnover. The Football Money league profiles the highest earning clubs in the world’s most popular sport & is considered the most contemporary and reliable analysis of clubs’ relative financial performance. There are a number of methods that can be used to determine clubs’ relative size – including measures of fan base, attendance, broadcast audience, or on-pitch success. However, the Money League focuses on the clubs themselves, comparing revenue from day to day football operations which we believe is the best publicly available financial comparison. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  107
  • 109. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 RESEARCH METHODOLOGYType of Research: Analytical research uses facts and information already available, and analyzes these to make a critical evaluation of the material. This study is an analytical research carried out to critically examine the functioning of Elite European League Football with a focus towards top English Football clubs & to study the viability of the various prevalent economic models existing within the Football industry. For the analysis historical data of past six years (2004-2009) has been taken spanning the top clubs in England.Objective(s)  Determine functional sustainability amongst current operating practices of financial indiscipline in Major football clubs  To evaluate the colossal debt levels prevalent at the top echelons of club football,  To determine the adequacy of legislations governing major clubs.Data Analysis Method Description1) Critical analysis of the financials of Football clubs qualifying for UEFA’s elite Europeancompetition spanning England’s Top Tier Football Clubs2) To analyse the revenue streams & expenditure patterns of major football enterprisesincluding review of Balance Sheets released by individual clubs wherever applicable.3) To examine the correlation between transfers spend & player wages contributing towardsfinancial brinkmanship between clubs.4) Excerpts of interview & opinions of top football experts including analysis of newspaperreports & articles by eminent football authors. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  108
  • 110. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 DATA ANALYSIS & INTERPRETATIONFor any credible analysis of the health of football finances, it is imperative to objectivelyexamine the biggest & the most lucrative money spinning Football leagues & their domesticclubs. Therefore the English Premier League which is the worlds most watched associationfootball league & consequently the worlds most lucrative football league in terms of revenue,with combined club revenues of over £2 billion in 2008–09 exceeding that of Spains La Ligaand Germanys Bundesliga , form the crux of the focus in examining the status of Football’sfinancial Landscape. ARSENAL Football ClubArsenals financial results for the year ended 31 May 2010, have been nothing short of recordbreaking with revenue of £380 million (Year 2009 £313 million) and profit before tax of £56million (Year 2009 £46 million).Another notable figure was that of Profit Before Tax which wasup 23%, from previous year’s profit of £35 million.But the most impressive element was that this enabled the club to repay £130 million of bankloans, thereby reducing the net debt to £136 million from just under £300 million. So any further International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  109
  • 111. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 sales on the property front will generate surplus cash as the property business is now essentiallydebt-free. This is especially credit worthy given the downturn in the property market arising outof recession. Table 1: Arsenal- Profit GrowthArsenal has earned significant property revenue - £157 million from £88 million previously asdisplayed in Table 1. But this was also marked by a subsequent growth in expenses as well, sothe profit from property only increased marginally from £6 million to £11 million. But clearly,the £45 million football profit still drives the business. There is also some hefty gains that can benow anticipated generating surplus cash from property sales. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  110
  • 112. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 Given the healthy numbers, operating profit for the football business actually fell by a third (£10million) to £20 million from £30 million. Also there was a small decrease in revenues by £2million attributed to the economic downturn & fewer home games. But at the same time, higherwages also increased expenses by £8 million. Fortunately, the football operating profit of £45million pre-tax profit (including player sales) more than made up for the rise in expenses..In the last three years alone, Arsenal have produced combined pre-tax profits of £138 million –an astonishing figure in the world of football.Arsenal’s profit growth has been largely driven byimpressive revenue growth which has ballooned to £223 million from £115 million, almostdouble in the last 5 years consequently placing Arsenal 5th in the last year’s Deloittes MoneyLeague.Arsenal’s revenue growth is a consequence of moving into their new stadium & not televisionunlike the vast majority of other clubs in the English league. Gate receipts doubled to £90million from £44 million, reflected in the steep change in revenue figures from the year 2007after moving into Ashburton Grove. The £20 million “mortgage” is now easily serviced fromadditional £50 million revenue per season generated as a result of the increased capacity stadium.Television Broadcast rights has been the biggest revenue driver for all clubs including arsenal. In2010 alone, Arsenal’s television revenue jumped to £85 million from £73 million, a 15%increase. Still as a percentage of revenue, the clubs dependence on T.V Broadcast revenue isrelatively small at 38% than compared to other clubs as shown in Table 2 International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  111
  • 113. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 Table 2: Revenue of Premier League 2008/09One aspect where Arsenal lags behind their competitors, especially the continental Europeanteams, is in Commercial Revenue. In spite of weak figures in this section which is much lowerthan that of other big English clubs, there was actually a decline of £4 million generating a totalof only £44 million.Arsenal have already moved to address this glaring void with the new CEO Ivan Gazidisstrengthening the clubs commercial team with high profile recruits with an aim to significantlybolster Commercial revenue while aggressively exploring overseas markets including in theMiddle East, Far East and the USA while expanding retail presence through international brandbuilding. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  112
  • 114. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 On the cost side, reflecting the resigning of many players on long term contracts have resulted ina rise in wages to £111 million, a jump of 6% .They also include the strengthening of theexecutive team, which must come at a price, though theoretically should also increase revenue.Also as a result of wage increases, the wages to turnover ratio has increased reversing the trendof the last 3 years although this still remains the runner-up in terms of the best wages to turnoverratio prevalent in the English League. Figure 1: Wages vs. TurnoverThe entry of the Russian oil tycoon Roman Abramovich through his purchase of ChelseaFootball Club in 2003 heralded a new era in football & its operations where balancing books was International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  113
  • 115. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 considered no longer an important requirement. As attempts to keep up & compete with RomanAbramovich’s Chelsea, many clubs followed its method of purchasing success & glory throughwielding the cheque book, often without considering neither the cost nor its consequences.Remarkably, arsenal in this turbulent period has remained one of the only few clubs to earn asurplus of £2 million in player transfers... This figure pales in comparison to the huge sumssplashed in the transfer market by other clubs, the likes of Manchester City, Chelsea, Liverpooland Manchester United. This approach of being averse to spending huge amounts of money byrisking financial collapse & bankruptcy is especially laudable in the context of the free spendingcompetitors.Another impressive performance has been in the clubs property venture which subsequentlyearned the club a significant £157 million from the sale of apartments as part of the Queenslandredevelopment project undertaken by the club. This deserves special praise as such results wereachieved in the face of one of the worst recessions the world has witness coupled with thesubsequent downturn in the property market which had, at time forced the club into requestingextension of the deadline for the repayment of the bank loan. This has significantly curtailed &subsequently eliminated the property debt, enabling the club bring down its gross level of debt to£263 million. The net debt is significantly lowered to only £136 million if one takes into accountthe cash balances of £128 million as shown in Figure 2. Figure 2: Annual Debt International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  114
  • 116. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  Chelsea Football Club LimitedThe entry of the Russian oil tycoon Roman Abramovich through his purchase of ChelseaFootball Club in 2003 heralded a new era in football & its operations where balancing books wasconsidered no longer an important requirement. As attempts to keep up & compete with RomanAbramovich’s Chelsea, many clubs followed its method of purchasing success & glory throughwielding the cheque book, often without considering neither the cost nor its consequences. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  115
  • 117. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 A look at Chelsea’s financial accounts reveals few distinct points, the foremost being that theclub held the rather unenviable record for the highest wage bill ever accounted for by a Club inthe English premier League at the time of submission of the Club’s accounts in the year 2009.This mammoth wage bill & high transfer spending is in stark contrast to the often announcedgoal of breaking even as stated by the then CEO of the Club Peter Kenyon.As displayed in Table 3, Chelsea have incurred continual losses since 2004 with the £44.4m lossincurred in the 2009..Although the clubs have managed to consistently reduce losses (until 2010where excess of £70 million in losses were disclosed) it does not detract from the fact that thedeficit was massive in the form of £140 million back in the year 2005. As the clubs managementinsist that the losses are on a downward trajectory, Chelsea’s recent foray into the transfermarker splashing in excess of £70 million on just two players (Fernando Torres & David Luis)especially after recently announcing massive losses does not augur well for the financial healthof the club. Table 3: Chelsea Football Club Profit and Loss Account International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  116
  • 118. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 From the £140 million back in the year 2005, losses have now reduced to £44.4 million, a netreduction of about £95.6 million. But significantly nearly 80% of this reduction can be attributedto have come from the transfer market, i.e. £74m with £40.4 million higher profit on account ofplayer sales notwithstanding lower amortization which is £33.6 million lower & fewertermination payments. This translates into only £8.7 million of the reduction actually comingfrom football operations. In the context of the T.V broadcast bonanza era the results are adampener to say the least. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  117
  • 119. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 In spite of the Clubs keenness to pat them on the back regarding improvement in cash flows thenet cash outflow from operating activities of £13.1m 2009 is exactly the same as it was in 2004& still is in the negative.Another moot point being the revised valuations of the players in the balance sheet, intangibleassets (basically net book value of the players) have decreased from £143.6m to £77.8m by£65.8m in just twelve months. This is further compounded by the fact that the squad now needsmajor replacements & for the club itself the vicious cycle of debts & losses shows no sight of anend.Therefore, it is clear that Chelsea need to find ways of reaching the elusive break-even target andthe right way is to increment revenue.. In the long-term it is vital to leverage Brand Chelsea toincrease commercial revenue in a significant way if the club is to progress financially. Thisinvolves exploring sponsorship revenue & stadium naming rights in which Chelsea lags behindin comparison with the other big four of the league.Revenue from T.V Broadcasting rights is at a healthy £79.1 million, behind only ManchesterUnited in the league. In addition to this, like other English football clubs Chelsea too will receivean additional windfall of funds as a result of the new agreement on overseas rights, translatinginto an extra £7.5m per annum for the next three years for the club. There seems to be littlerevenue potential left for the club to pursue to achieve its target of breaking even, as a resultDeloittes in their annual football review report quoted, “the club faces a significant challenge toregain a top five position in our Money League.”Therefore, it is clear that the club is significantly farther from attaining its stated financialobjectives while struggling to break free from its dependence on its Russian owner. The club atthe very least has to start thinking about the changing footballing landscape & evolve into aviable business. A good start would be to stop hemorrhaging further losses & significantlyimprove bottom lines.FINDINGS & RECOMMENDATIONSAccording to UEFA report 54% of Europes top-division teams reported operating losses (beforetransfers) in the 2008 financial year. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  118
  • 120. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 The above analysis of top English clubs provides clear warnings of financial mismanagement &unsustainability. In addition, it is clear from the above analysis of the top clubs in Europe thatvery few manage to generate profits & fewer still can lay claim to have a viable & sustainablebusiness model. This is a stark indictment of not only the larger governance of the sport wherelackadaisical financial excesses have not only been tolerated but encouraged as also thequestionable conduct of individual football clubs in England & across Europe adopting irrationalfinancial measures leading themselves to precipitous levels of unsustainable wage inflation &debt.Amidst this backdrop of financial excesses & subsequent losses the German Bundesliga is theflag bearer & role model for the much touted UEFA fair play regulations. The German footballassociation’s success can be gauged from the fact that no Bundesliga club has ever gonebankrupt during a running competition or was unable to complete the season. The Bundesliga’ssuccess in this matter spans 40 years with member clubs operating for years with positive results& definitely offers approaches that can be adopted elsewhere to restore financial perspectiveamong the other European footballing heavyweights. It owes its success to a robust licensingsystem, exercising rigorous financial control over member clubs where expenditure is strictlyrequired to be in line with existing revenues thus limiting the possibilities for using incomingcapital to replace revenues.Spiraling wage inflation is a serious concern affecting football clubs. A salary cap vis-à-visMajor league baseball would be difficult to implement in the sport of football. Another effectiveapproach therefore, would be to strictly enforce wage discipline among football clubs byestablishing the maximum limit that the club can spend on player salaries based upon apercentage of their turnover. This would ensure that if even a club over extends itself financiallywhile purchasing a player, his wages would have to necessarily come from the revenuesgenerated by the club. Thus such clubs would have to exercise prudence to see if they can affordthe player’s wages before making a purchase decision in the transfer market.When one considers the complexity of football when compared to a more traditional business, itis strange that it is subject to the current “one size fits all” model of legislation. Few other International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  119
  • 121. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 businesses pay vast fees to secure employees, nor do they pay their employees in a complexmanner that includes basic pay, image rights and performance-related bonuses, and yet nospecial demands are made of football clubs to disclose this clearly in their annual financialstatements.Naturally, this has big implications for financial transparency within the industry. With outsideobservers relying on measures such as wages as a percentage of a club’s turnover to gauge aclub’s sustainability, the lack of breakdown of the “wage” mean that one struggles to draw anyreliable conclusions.CONCLUSIONEven in the game of Football, questions of financial prudence & perspective ultimately seek theirresolution through optimum balance, and the same is true for the economics of sport. Thechallenge for the sport is to find a dynamic balance between desire for success and moneynecessary to analytically grasp the passionate and pragmatic complexities of the beautiful game.A strong revolutionary wind is blowing through Europe’s footballing landscape providing acompelling paradigm shift in how the business of football functions & evolves.UEFA has produced a club licensing benchmarking report on European club football – thebroadest of its kind ever undertaken – covering financial results from more than 600 top-divisionclubs from UEFAs 53 member national associations forming an important basis for recentdiscussions on financial fair play, as well as contributing to increased transparency in clubfootball – one of UEFAs key club licensing objectives.All in all, it is clear that while many clubs are continuing to operate successfully, there are manyoperating less-sustainable strategies. Reports indicate that 54% of Europes top-division teamsreported operating losses (before transfers) in the 2008 financial year.While some clubs in every UEFA member association were able to break even, the analysesidentify other signs of financial overstretching and clubs living beyond their current means.Amid the record Broadcast deals & revenues there are some increasingly clear warning signs.The many clubs across Europe that continue to operate on a sustainable basis are finding itincreasingly difficult to coexist & compete with clubs that incur losses & transfer fees beyond International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  120
  • 122. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 their means & reporting losses year after year, without themselves following the same approachat the same time succumbing to a vicious cycle of debt.Unless there is a comprehensive overhaul in the way football clubs operate & conduct business,there is a distinct possibility of grave consequences.REFERENCES Rodney Fort and Joel Maxcy, " Competitive Balance in Sports Leagues: An Introduction” Journal of Sports Economics, (2003) Babatunde Buraimo and Rob Simmons, “Market size and attendance in English Premier League Football” The Department of Economics, Lancaster University Management School, Lancaster LA1 4YX,UK, (2006) Leit˜ao, Jo˜ao, “The Taylor Effect on the Performances of the Red Devil’s Football Brand”, University of Beira Interior, (2007) The Bundesliga’s report on “The Economic State of Professional Football” The UEFA Club Licensing and Financial Fair Play Regulations Report http://soccernet.espn.go.com/news/story/_/id/874859/gordon-taylor:-football-facing- government-intervention?cc=4716 http://www.thesun.co.uk/sol/homepage/sport/football/3392577/Chelseas-wage-bill-is-an- amazing-172million.html http://www.telegraph.co.uk/sport/football/competitions/premier-league/8314698/English- clubs-defy-the-economic-recession-to-retain-elite-status-in-European-money-league.html http://www.espnstar.com/football/premierleague/news/detail/item581775/Clarke:-Level-of- football-debt-precipitous/ http://en.wikipedia.org/wiki/Uefa International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  121
  • 123. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  http://en.wikipedia.org/wiki/UEFA_Champions_League http://en.wikipedia.org/wiki/FIFA http://en.wikipedia.org/wiki/Premier_League International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  122
  • 124. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  AN ALGORITHM FOR SOLVING A CAPACITATED FIXED CHARGE BI-CRITERION INDEFINITE QUADRATIC TRANSPORTATION PROBLEM WITH RESTRICTED FLOWS.R. Arora*Kavita Gupta** ABSTRACTIn this paper a capacitated fixed charge bi-criterion indefinite quadratic transportation problemwith restriction on the total flow is studied. An algorithm to find the efficient cost time trade offpairs in a capacitated fixed charge bi-criterion indefinite quadratic transportation problem withbounds on rim conditions is developed. The algorithm is developed by forming a related fixedcharge indefinite quadratic transportation problem and it is shown that to each basic feasiblesolution called corner feasible solution to related transportation problem, there is acorresponding feasible solution to this restricted flow problem. It is also shown that the efficientcost time trades off pairs to the given problem are derivable from this related problem thealgorithm is illustrated with the help of a numerical example.Keywords: optimum time cost trade off, capacitated transportation problem, fixed charge, bi-criterion indefinite quadratic transportation problem, restricted flow.* Ex-Principal, Hans Raj College, University of Delhi, Delhi-110007, India** Department of Mathematics, Jagan Institute of Management Studies, 3 Institutional Areas,Sector-5, Rohini, Delhi, India International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  123
  • 125. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 1. INTRODUCTIONThe fixed charge transportation problem was originally formulated by G.B Dantzig andW.Hirisch [8] in 1954.Thirwani et.al. [9] in 1997 developed an algorithm for finding the timecost trade off pairs in a fixed charge bi-criterion transportation problem with restricted flow.Later, Arora et.al [1-2] also studied the indefinite quadratic transportation problem.Another important class of transportation problem consists of capacitated transportation problem.If the total flow in a transportation problem with bounds on rim conditions is also specified, theresulting problem makes the transportation problem more realistic. Moreover, if the totalcapacity of each route is also specified then optimal solution of such problems is of greaterimportance which gives rise to a capacitated transportation problem. Many researchers like A.KBit et.al. [6], K.Dahiya et.al. [7] Have contributed in this field.In 1976, Bhatia et .al. [5] provided the time cost trade off pairs in a linear transportationproblem. Then in 1994, Basu et.al. [4] Developed an algorithm for the optimum time cost tradeoff pairs in a fixed charge linear transportation problem giving same priority to cost as well astime. Arora et.al. [3] Studied time cost trade off pairs in an indefinite quadratic transportationproblem with restricted flow.In this paper, a capacitated fixed charge indefinite quadratic transportation problem with boundson rim conditions giving same priority to cost and time is studied along with restriction on thetotal flow. An algorithm to identify the efficient cost time trade off pairs for the problem isdeveloped.2. PROBLEM FORMULATIONLinear functions are widely used in modeling a mathematical optimization problem. Alsoquadratic functions and quadratic problems are the least difficult to handle out of all non linearprogramming problems. A fair number of functional relationships occurring in the real world aretruly quadratic. For example-Kinetic energy carried by a rocket or an atomic particle isproportional to the square of its velocity. There are many non linear relationships occurring innature that are capable of being approximated by quadratic functions.Consider a capacitated fixed charge bi-criterion indefinite quadratic transportation problem givenby International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  124
  • 126. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619       (P1): min   cijxij    dijxij    Fi, max  tij / xij  0     i, j  I  J  iI jJ    iI jJ  iI  Subject to ai   xij  Ai i  I (1) jJ bj   xij  Bj j  J (2) iI l ij  x ij  u ij   i, j  I  J (3)     x ij  P   min   Ai,  Bj     (4) iI jJ   iI jJ  I = {1, 2 … m} is the index set of m origins. J = {1, 2… n} is the index set of n destinations. xij = number of units transported from origin i to the destination j. cij = variable cost of transporting one unit of commodity from ith origin to the jth destination. dij = the per unit damage cost or depreciation cost of commodity transported from the ith origin to the jth destination. lij and uij are the bounds on number of units to be transported from the ith origin to the jth destination. ai and Ai are the bounds on the availability at the ith origin, i I bj and Bj are the bounds on the demand at the jth destination, j J tij is the time of transporting goods from ith origin to the jth destination. Fi is the fixed cost associated with ith origin. For the formulation of Fi (i=1,2 … m), we assume that Fi (i = 1, 2 .. m) has p number of steps so that p Fi   Fil il , i = 1, 2 … m l 1 International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  125
  • 127. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  n Where,  il = 1 if Fi = x j1 ij  ail ,l=1,2,3……..p, i=1,2,……m =0 otherwise Here, 0 = ai1 < ai2 … < aip ai1, ai2 …,< aip (i = 1,2, … m) are constants and Fil are the fixed costs.  i= 1, 2 …m, l =1,2 ..pIn the problem (P1), we need to minimize the total transportation cost and the depreciation costsimultaneously. Also we need to minimize the fixed cost associated with ith origin and the timeof transportation from ith origin to jth destination. Sometimes, situations arise when one wishes tokeep reserve stocks at the origins for emergencies, there by restricting the total transportation   flow to a known specified level, say P   min   Ai,  Bj   .This flow constraint changes the   jJ    iI structure of the transportation problem.In order to solve the problem (P1), we separate it in to two problems (P2) and (P3) where      (P2): minimize the cost function    cijxij     dijxij    Fi  subject to (1),(2),(3) and (4).  iI jJ    iI jJ  iI    (P3): minimize the time function max  t ij / x ij  0  subject to (1), (2), (3) and (4). iI, jJ  The flow constraint in the problem (P1) implies that a total   Ai  P  of the source reserves  iI   have to be kept at the various sources and a total   Bj  P  of destination slacks is to be  jJ retained at the various destinations. Therefore an extra destination to receive the source reservesand an extra source to fill up the destination slacks are introduced.In order to solve the problem (P2) we convert it in to a related problem (P2´) given below.      (P2´): min Z     cijyij     dijyij    Fi  subject to  iI jJ    iI jJ  iI  yjJ ij  Ai  i  I (5) International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  126
  • 128. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 yiI ij  Bj j  J (6)l ij  y ij  u ij   i, j  I  J (7)0  ym  1, j  Bj  bj j  J0  yi, n 1  A i  ai i Iym  1, n  1 0Ai = Ai iI, A m+1 = B jJ j -P , Bj = Bj jJ , Bn+1 =  A -P iI icij = cij , iI, jJ, cm+1,j = ci,n+1 = 0 iI, jJ, cm+1,n+1 = Md´ij = dij iI, jJ, dm+1,j = di,n+1 = 0 iI, jJ; d´m+1,n+1 = MFi = Fi i=1,2 …m, Fm+1 = 0Where I = {1, 2 … m, m+1}, J = {1, 2, … n, n+1}In order to solve the problem (P3), we convert it to a related problem (P3´) givenbelow.(P3´): min T  max t ij / yij  0  i  I  and  j  J  subject toyjJ ij  Ai  i  I y iI ij  Bj j  J l ij  y ij  u ij   i, j  I  J0  ym  1, j  B j  b j j  J0  yi, n  1  A i  ai i  Iym  1, n  1 0Ai = Ai iI, A m+1 = B jJ j -P, Bj = Bj jJ , Bn+1 =  A -P iI icij = cij , iI, jJ, cm+1,j = ci,n+1 = 0 iI, jJ, cm+1,n+1 = Md´ij = dij iI, jJ, d´m+1,n+1 = Mt´ij= tij   i, j  I  J ,t´m+1,j = t´i,n+1= 0 iI, jJ International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  127
  • 129. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 t´m+1,n+1 > max tij / xij  0 i  I, j  JTo obtain the set of efficient time cost trade off pairs, we first solve (P2´) and read the time withrespect to the minimum cost Z where time T is given by problem (P3´)At the first iteration, let Z1* be the minimum total cost of the problem (P2) and T1* be theoptimal time of the problem (P3) with respect to Z1* , then any schedule which is completedearlier than T1* would cost more than Z1* . So (Z1* , T1*) is the first time cost trade off pair at thefirst iteration.After modifying the costs with respect to the time obtained, a new optimal cost is obtained andtime is read with respect to the new optimal cost .This procedure is called re-optimizationprocedure. Let after q th iteration, the problem becomes infeasible. Thus, we get the followingcomplete set of time-cost trade off pairs.(Z1*, T1*) ( Z2*, T2*),( Z3*,T3*),…………….( Zq*, Tq*) where Z1* ≤ Z2* ≤ Z3*≤………..≤Zq* and T 1* ≥ T2* ≥ T3*………..≥ Tq* with strict inequality holding in atleast one of the twoconditions .The pairs so obtained are pareto optimal solutions of the given problem. Then weidentify the minimum cost Z1* and minimum time T q* among the above trade off pairs. The pair(Z1*, T q*) with minimum cost and minimum time is termed as the ideal pair which can not beachieved in practical situations.3. THEORETICAL DEVELOPMENT:Theorem 1: Let X = {Xij} be a basic feasible solution of problem (P2´) with basis matrix B.Then it will be an optimal basic feasible solution ifR 1ij  ij  z1(d ij z 2ij)  z 2 (cij z1ij) ij(cij z1ij)(d ij z 2 ij)    Fij  0 (i, j)  N 1  AndR 2 ij  ij ij(cij z1ij)(d ij z 2ij)  z1(d ij z 2ij)  z 2 (cij z1ij)    Fij  0 (i, j)  N 2  Such thatu 1  v1j  cij i  (i, j)  B (8)u i2  v 2  dij j  (i, j)  B (9)u1  v1j  z1 i ij  (i, j)  N 1 And N2 (10) International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  128
  • 130. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 u i2  v 2  zij  (i, j)  N 1 And N2 j 2 (11) F ij Is the change in fixed cost F i when some non basic variable xij enters the basis. iIz1 = value of  c x iI jJ ij ij at the current basic feasible solution corresponding to the basis B.z2 = value of  d x iI jJ ij ij at the current basic feasible solution corresponding to the basis B. ij = level at which a non basic cell (i,j) enters the basis replacing some basic cell of B.N1 and N2 denotes the set of non basic cells (i,j) which are at their lower bounds and upperbounds respectively.Note: u1 , v1j , u i2 , v 2 are the corresponding dual variables which are determined by using equations i j(8) to (11) and taking one of the ui ,s or vj ,s. as zero.Proof: Let z0 be the objective function value of the problem (P2).Let z0 =z1z2 + F0 where F0 = F i iI  Let z be the objective function value at the current basic feasible solution X= {xij}corresponding to the basis B obtained on entering the non basic cell xij  N1 in to the basis whichundergoes change by an amount ij given bymin{uij – lij ; xij - lij for all basic cells (i,j) with a (-  )entry in the  -loop; uij – xij for all basiccells (i,j) with a (+  )entry in the  -loop}. Then z =  z1  ij  cijz1    z 2  ij  dijzij    F0  Fij    ij       2  z - z0 = z1z2 + z2 ij (cij-z1ij) + z1 ij (dij – z2ij) + ij (cij-z1ij) (dij – z2ij) - z1z2 +  F ij 2 = ij [z2 (cij-z1ij) + z1 (dij – z2ij) + ij (cij-z1ij) (dij – z2ij)]+  F ij This basic feasible solution will give an improved value of z if z < z0 .It implies that ij [z2 (cij-z ij) + z1 (dij – z ij) +  ij (cij-z ij) (dij – z ij)]+  F ij < 0 1 2 1 2 (12)Therefore one can move from one basic feasible solution to another basic feasible solution onentering the cell (i,j)  N1 in to the basis for which condition (12) is satisfied.It will be an optimal basic feasible solution if International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  129
  • 131. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 R1  ij z1(dijzij )z 2(cijz1 )ij(cijz1 )(dijzij )  Fij  0(i, j)  N1 ij   2 ij ij 2  Similarly, when non basic variable xij  N2 undergoes change by an amount ij thenz - z =  ij [  ij (cij-z ij) (dij – z ij)- z2 (cij-z ij) - z1 (dij – z ij) +]+  F ij < 0 0 1 2 1 2It will be an optimal basic feasible solution ifR ij  ij ij(cijz1 )(dijzij )z1(dijzij )z 2(cijz1 )  Fij  0(i, j)  N 2 2   ij 2 2 ij  Definition: Corner feasible solution: A basic feasible solution {yij} i  I´, j  J´ to (P2´) iscalled a corner feasible solution (cfs) if ym+1,n+1 = 0Theorem 2. A non corner feasible solution of (P2´) cannot provide a basic feasible solution to(P2).Proof: Let {yij}I´ xJ´ be a non corner feasible solution to (P2´).Then ym+1,n+1 =  (>0)Thus y iI i, n  1   yi, n  1  ym  1, n  1 iI =  yi, n  1   iI =  Ai  P (13) iIyiI i, n  1   Ai  (P   ) iINow, for i  I,yjJ  ij  A i  Ai (14) yij   AiiI jJ  iI(13) and (14) implies that  y iI jJ ij  PThis implies that total quantity transported from the sources in I to the destinations in J is P + > P, a contradiction to assumption that total flow is P and hence {yij}I´ xJ´ cannot provide afeasible solution to (P2).Lemma 1: There is a one –to-one correspondence between the feasible solution to (P2) and thecorner feasible solution to (P2´). International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  130
  • 132. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 Proof: Let {xij}I xJ be a feasible solution of (P2).So {xij}I xJ will satisfy (1) to (4).Define {yij}I´ xJ´ by the following transformationyij = xij ,i  I, j  Jyi,n+1 = Ai - x jJ ij , i Iym+1,j = Bj - x iI ij , j Jym+1,n+1 = 0It can be shown that {yij} so defined is cfs to (P2´).Relation (1) to (3) implies thatl ij  y ij  u ij for all i  I, j  J0  yi, n 1  A i  ai , i I0  ym  1, j  Bj  bj , j Jym+1,n+1 ≥ 0Also for i  Iy yjJ  ij jJ ij  yi, n  1   x ij  Ai   x ij  Ai  A i jJ jJFor i = m+1yjJ  m  1, j   yij  ym  1, n  1   (B j   x ij) jJ jJ iI = B x jJ j iI jJ ij = B P jJ j = A´m+1  yij  A i ;  i  I  jJ Similarly, it can be shown that y iI ij  Bj ;  j  J Therefore {yij}I´ xJ´ is a cfs to (P2´).Conversely, let {yij}I´ xJ´ be a cfs to (P2´).Define xij , i  I, j  J by the following transformation.xij= yij , i  I, j  J International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  131
  • 133. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 It implies that l i j  x i j  u i j , i  I, j  JNow for i  I, the source constraints in (P2´) impliesyjJ  ij  A i  A iy jJ ij  yi, n  1  Ai  ai   yij  Ai (Since 0 ≤ yi,n+1 ≤ Ai –ai , i  I) jJHence, ai  x jJ ij  Ai , i  ISimilarly, for j  J, bj   xij  Bj iIFor i= m+1yjJ  m  1, j  A m 1   Bj  P jJ  ym  1, j   Bj  P Because ym+1,n+1 = 0 jJ jJNow, for j  J the destination constraints in (P2´) givey iI ij  ym  1, j  BjTherefore,   yij   ym  1, j   Bj iI jJ jJ jJy  B yiI jJ ij jJ j jJ m  1, j P   xij  P iI jJTherefore {xij}I xJ is a feasible solution to (P2)Remark 1: If (P2´) has a cfs, then since c´m+1,n+1=M and d´m+1,n+1= M, it follows that non cornerfeasible solution cannot be an optimal solution of (P2´) .Lemma 2: The value of the objective function of problem (P2) at a feasible solution {xij}I x J isequal to the value of the objective function of (P2´) at its corresponding cfs {yij}I´xJ´ andconversely.Proof: The value of the objective function of problem (P2) at a feasible solution {xij}I x J is International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  132
  • 134. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619        cijxij     dijxij    Fi  iI jJ   iI jJ  iI   cij = cij, i  I, j  J     xij = yij, i  I, j  J  c = c   i,n +1 m+1, j = 0; i  I, j  J            cijyij    dijyij    Fi  Because d i,n+1 = d m+1, j = 0; i  I, j  J   iI jJ    iI jJ  iI      y m 1,n 1  0   F = 0, F = Fi, i  I   m+1 i     = the value of the objective function of (P2´) at the corresponding cfs {yij}I´xJ´The converse can be proved in a similar way.Lemma 3: There is a one –to-one correspondence between the optimal solution to (P2) andoptimal solution to the corner feasible solution to (P2´). Proof: Let {xij}I  J be an optimal solution to (P2) yielding objective function value z0 and  {yij}I  J be the corresponding cfs to (P2´). Then by Lemma 2, the value yielded by {yij}I  J is z0 ..If possible,let {yij}I  J be not an optimal solution to (P2´). Therefore, there exists a cfs {y ij} to (P2´) with the value z1 < z0. Let {x ij} be the corresponding feasible solution to (P2).Then by lemma 2,       cijx ij    dijx ij    Fi  = z , a contradiction to the assumption that {xij}I  J is an 1 iI jJ   iI jJ  iI  optimal solution of (P2).Similarly, an optimal corner feasible solution to (P2´) will give anoptimal solution to (P2).Theorem 3: Optimizing (P2´) is equivalent to optimizing (P2) provided (P2) has a feasiblesolution.Proof: As (P2) has a feasible solution, by lemma 1, there exists a cfs to (P2´).Thus by remark 1;an optimal solution to (P2´) will be a cfs. Hence, by lemma 3,an optimal solution to (P2) can beobtained.4. ALGORITHM: International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  133
  • 135. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 Step1: Given a capacitated fixed charge bi-criterion indefinite quadratic transportation problemwith restricted flow (P1), separate the problem (P1) in to two problems (P2) and (P3).Form therelated transportation problems (P2´) and (P3´).Find a basic feasible solution of problem (P2´)with respect to variable cost only. Let B be its corresponding basis.Step 2: Calculate the fixed cost of the current basic feasible solution and denote it by F(current) mWhere F (current) = F i 1 iStep 3(a): Find  F ij  F ( N B )  F (cu rren t ) where F (NB) is the total fixed cost obtainedwhen some non basic cell (i,j) enters the basis.(b) Calculate ij ,(cij-z1ij) , (dij – z2ij), z1, z2 for all non basic cells such thatu 1  v1j  cij i  (i, j)  Bu i2  v 2  dij j  (i, j)  Bu1  v1j  z1 i ij  (i, j)  N 1 And N2u i2  v 2  zij  (i, j)  N 1 And N2 j 2z1 = value of  c x iI jJ ij ij at the current basic feasible solution corresponding to the basis Bz2 = value of  d x iI jJ ij ij at the current basic feasible solution corresponding to the basis B. ij = level at which a non basic cell (i,j) enters the basis replacing some basic cell of B.N1 and N2 denotes the set of non basic cells (i,j) which are at their lower bounds and upperbounds respectively.Note: u1 , v1j , u i2 , v 2 are the dual variables which are determined by using the above equations and i jtaking one of the ui, s or vj, s. as zero.(c) Find R1 (i, j)  N1 and R ij(i, j)  N2 where ij 2R1  ij z1(dijzij )z 2(cijz1 )ij(cijz1 )(dijzij )  Fij  0(i, j)  N1 and ij   2 ij ij 2  R ij  ij ij(cijz1 )(dijzij )z1(dijzij )z 2(cijz1 )  Fij  0(i, j)  N 2 2   ij 2 2 ij  N1 and N2 denotes the set of non basic cells (i,j) which are at their lower bounds and upperbounds respectively. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  134
  • 136. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 Step 4: If R1  0(i, j)  N1 and R ij  0(i, j)  N 2 then the current solution is optimal to (P2´).Go ij 2to step 5.Otherwise, some (i,j)  N1 for which R 1  0 or some (i,j)  N2 for which R ij  0 will ij 2enter the basis. Go to step 2.Step 5: Let Z1 be the optimal cost of (P2´) yielded by the basic feasible solution {y´ij}.Step 6: Find T1 where T1 = max{tij /y´ij > 0 } from the problem (P3´).Then the correspondingpair (Z1 , T1 ) will be the first time cost trade off pair for the problem (P1).To find the next besttime-cost trade off pair, go to step 7.Step7: Define cij1 = M if tij ≥T1 cij if tij < T1where M is a sufficiently large positive number. Form the corresponding capacitated fixed 1charge quadratic transportation problem with variable cost cij .Repeat the above process till theproblem gets infeasible. The complete set of time cost trade off pairs of (P1) at the end of qthiteration are given by (Z1,T1),(Z2,T2)……….(Zq,Tq) where Z1 ≤ Z2 ≤ …..≤ Zq and T1 ≥T2≥……≥Tq. with strict inequality holding in atleast one of the two conditions.Remark 2: The pair (Z1, Tq) with minimum cost and minimum time is the ideal pair whichcannot be achieved in practice except in some trivial case.Convergence of the algorithm: The algorithm will converge after a finite number of stepsbecause the choice of cij, s in step 7 will ensure an infeasible solution after a finite number ofiterations.5. NUMERICAL ILLUSTRATION:Consider a 3 x 3 capacitated fixed charge bi-criterion indefinite quadratic transportationproblem with restricted flow .Table 1 gives the values of cij, dij, Ai ,Bj for i=1,2,3 and j=1,2,3 International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  135
  • 137. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 Table 1: cost matrix of problem (P2) D1 D2 D3 AiO1 5 9 9 30O2 4 6 2 40 3 7 4O3 2 1 1 50 2 9 4Bj 30 20 30 ,s ,s Note: values in the upper left corners are cij and values in lower left corners are dij fori=1,2,3.and j=1,2,3. 3 3 3 x1j ≤ 30, x2j ≤40, 10 ≤ x3j ≤ 50, 5≤ 3Also, 3 ≤ j1 10≤ j1 j1 x i 1 i1 ≤30 , 3 3 5≤  xi2 ≤ 20, 5 ≤ i 1 x i 1 i3 ≤ 301≤ x11 ≤ 10 , 2 ≤ x12 ≤ 10 , 0 ≤ x13 ≤ 5 ,0≤ x21 ≤ 15 , 3 ≤ x22 ≤ 15 , 1 ≤ x23 ≤ 20 , 0≤ x31≤ 20 ,0≤ x32≤ 13, 0≤ x33≤ 25F11= 100, F12 = 50, F13 = 50, F21 = 150, F22 = 100, F23 = 50, F31= 200, F32= 150, F33 = 100 3Fi = F  l 1 il il where for i= 1, 2, 3 3 il = 1 if x j1 ij 0 0 otherwise International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  136
  • 138. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  3 i 2 = 1 if x j1 ij  10 0 otherwise 3 i3 = 1 if x j1 ij  20 0 otherwise Table 2 gives the values of t ij, s for i=1, 2, 3 and j=1, 2, 3Table 2: Time matrix of problem (P3) D1 D2 D3O1 15 8 13O2 10 13 14O3 12 10 9  3 3 Let the restricted flow be P = 40 where P = 40 < min   Ai  120,  Bj  80   i 1 j1 Introduce a dummy origin and a dummy destination in Table 1 with ci4 = 0 = d i4 for all i = 1,2 ,3and c4j = 0 = d4jfor all j = 1,2,3 . c44=d44=M where M is a large positive number. Also we have0≤ x14 ≤ 27 , 0≤ x24 ≤ 30 , 0 ≤ x34 ≤ 40 , 0 ≤ x41 ≤ 25 , 0 ≤ x42 ≤ 15 , 0 ≤ x43 ≤ 25 and F4j = 0 forj=1,2,3,4 In this way , we form the problem (P2´).Similarly on introducing a dummy origin and adummy destination in Table 2 with ti4 = 0 for i=1,2 ,3and t4j= 0 for j=1,2,3, 3 t44 > max tij / xij  0 i  I, j  J ,we form problem (P3´) . Also, B4 =  A  P =120-40 = 80 i 1 i 3and A4=  B  P = 80-40 = 40 j1 jNow we find an initial basic feasible solution of problem (P2´) which is given in table 3 below. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  137
  • 139. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  Table 3: A basic feasible solution of problem (P2´) D1 D2 D3 D4 u1 i ui2 F(current)O1 5 1 9 2 9 0 27 1 4 100 4 2 1 0O2 4 6 3 2 7 0 30 2 4 150 3 7 4 0O3 2 20 1 1 7 0 23 1 4 450 2 9 4 0 O4 0 9 0 15 0 16 M 0 0 0 0 0 0 Mvj1 0 0 0 -1vj2 0 0 0 -4 Note: entries of the form a and b represent non basic cells which are at their lower and upper bounds respectively. Entries in bold are basic cells. F (current) = 700, z1 = 102, z2 = 125 Table 4: Computation of R1 , R ij ij 2 NB O1D1 O1D2 O1D3 O2D1 O2D2 O2D4 O3D1 O3D2  ij 7 7 5 6 6 7 16 7 cij  z1 ij 4 8 8 2 4 -1 1 0dij  zij 2 0 -2 -3 -1 3 0 -2 5F(NB) 600 600 700 700 700 700 700 700  F ij -100 -100 0 0 0 0 0 0R1 ij 3400 4688 2870 816 5268 3570 2R ij 875 752 International Journal of Research in IT, Management and Engineering                                                              www.gjmr.org  138
  • 140. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 Since R1 ≥ 0  (i, j)  N 1 and R ij  0(i, j)  N2 , the solution in table 3 is an optimal solution ij 2of (P2´) and hence yields an optimal solution of (P2).Therefore minimum cost = (102 x 125) +700 = 13450 and corresponding time is T1 = 15. Hence the first time cost trade off pair is (13450,15) M if t ij  T1  15  1  Define cij =  1  and solving the resulting problem, the next trade off pair is cij if t ij < T  15  (13450, 14). Similarly, the other pairs are (14266, 13), (14266, 12), (16500, 10).6. CONCLUSION:In order to solve a capacitated fixed charge bi – criterion indefinite quadratic transportationproblem, given problem is separated in to two problems. One of them being an indefinitequadratic transportation problem has its optimal solution at an extreme point. After calculatingthe cost, corresponding time is read. This is the first cost time trade off pair. Proceeding likes thiswe get the various trade off pairs.REFERENCES[1] Arora, S.R., Khurana, A., “A paradox in an indefinite quadratic transportation problem”,International Journal of Management and Systems, 18, (2002), 301-318[2] Arora, S.R., Khurana, A., “Three dimensional fixed charge bi – criterion indefinite quadratictransportation problem”,Yugoslav Journal of Operations Research,14(1),(2004),83-97[3] Arora, S.R., Thirwani, D., Khurana, A.,“An algorithm for solving fixed charge bi – criterionindefinite quadratic transportation problem with restricted flow”, International Journal ofoptimization: Theory, Methods and Applications,1(4),(2009),367-380[4] Basu, M, Pal, B.B and Kundu, A., “An algorithm for the optimum time cost trade off in afixed charge bi-criterion transportation problem’’, Optimization, 30, (1994), 53-68 International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  139
  • 141. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 [5] Bhatia, H.L, Swarup, K and Puri , M.C., ‘‘Time cost trade off in a transportation problem’’,Opsearch, 13(3-4),(1976),129-142[6] Bit, A.K. Biswal, M.P. , Alam, S.S., “Fuzzy Programming technique for multi- objectivecapacitated transportation problem” , Journal of Fuzzy Mathematics,1(2),(1993),367-376[7] Dahiya, K. and Verma, V., ‘‘Capacitated transportation problem with bounds on rimconditions’’, Europeon journal of Operational Research, 178, (2007), 718-737[8] Hirisch, W.M. and Dantzig, G.B., ‘‘the fixed charge problem’’, Naval Research LogisticsQuarterly, 15(3), (1968), 413-424[9] Khanna,S. , Thirwani,D. and Arora, S.R., ‘‘An algorithm for solving fixed charge bi –criterion transportation problem with restricted flow”, Optimization, 40,(1997),193-206 International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  140
  • 142. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619   IMPACTS OF USE OF RFBIDW ON TAXATIONProf Sulatan Singh*Prof Surendra Kundu**Ms. Madhu Arora** ABSTRACTThe CBDT is statutory authority for policy and planning of direct taxes in India.Businessintelligence (BI) mainly refers to computer-based techniques used in identifying, extracting, andanalyzing business data, such as sales revenue by products and/or departments, or by associatedcosts and incomes.Computerized processing of returns all over the country introduced in 2002.To enhance revenue realization and catch tax evaders quickly, the Central Board of Direct Taxesis working on a comprehensive data warehousing system which will transform the functioning ofthe Income Tax Department called Revenue Forecasting & Business Intelligence DataWarehouse(RFBIDW).From data pertaining to mobile users to electoral records and database ofhigh net worth individuals, a universe of diverse information will be assembled in the I-Twarehouse for analysis and generating credible information and reports for investigationpurposes and revenue forecasting. Present study conceptual in nature is based on analyzingimpact of RFBIDW on taxation and found that it will be a remarkable step if used honestly andintelligently.*Chairman, CDLU, Sirsa**Professor, CDLU, Sirsa***Research Scholar, CDLU, Sirsa International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org      141 
  • 143. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  INTRODUCTIONKautilya’s Arthasastra was the first authoritative text on public finance, administration and thefiscal laws in this country. His concept of tax revenue and the on-tax revenue was a uniquecontribution in the field of tax administration. It was he, who gave the tax revenues its dueimportance in the running of the State and its far-reaching contribution to the prosperity andstability of the Empire. It is truly a unique treatise. It lays down in precise terms the art of statecraft including economic and financial administration.The introduction of electronic filing of I-T returns, e-payment of taxes, establishment of thenational network (TAXNET), and consolidation of the Regional Computer Centers into theNational Data Center have laid the foundation for the next generation administrative reforms inthe Department with the Computerised processing of returns all over the country introduced in2002.Net direct tax collection in the current financial year is higher by 6.7% at R1,27,858croreasagainst R1,19,849 crore collected from 1st April to 15thSeptember last year. The net collectionhas been impacted by R61, 000crore of refunds. Gross direct tax mop-up duringthe period hasbeen R1,88,868crore, a growth of 29.5% over the previous year’s collection during the period ofR1,45,825crore.(Source: http://www.indianexpress.com) this can be increased to standards ifgovernment shift attention from individual assessed to groups such as families, business groups,trades, dealers in particular items and intermediaries for curbing tax evasion.RESEARCH METHODOLOGYThe design of the research helps to get the ways for doing the work. Summary of the proposedresearch work is given as under:.As the purpose of research is to discover answers to questions through the application ofscientific procedures, research objectives can be one of the following categories:1. Exploratory research to gain familiarity with a phenomenon or to achieve new insightsinto it.2. Descriptive research is to portray accurately the characteristics of a particular individual,situation or a group. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org      142 
  • 144. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  3. Diagnostic research is to determine the frequency with which something occurs or with itis associated with something else.4. Hypothesis testing research to test a hypothesis of a causal relationship between variablesPresent study is conceptual in nature research of an exploratory rOBJECTIVES OF THE STUDY: i. To study about the present system for business intelligence for tax used. ii. To analyze the concept of RFBIDW iii. To understand impacts of using RFBIDW on present system iv. To suggest changes if any for improvement of proposed data warehouse.Data Collection:Secondary data available on official website of CBDT, journals, newspapers and books has beenconsidered for studyhas been duly acknowledged in references.Time period: This study has been done in October-November 2011.data after study may vary dueto vastness and changing nature of subject.Limitation of the study:Due to vastness, time bound and complexity of subject only RFBIDW is main focus of the study.Innovations in future may provide scope for future researchers in this context.AnalysisCommon functions of business intelligence technologies are reporting, online analyticalprocessing, analytics, data mining, process mining, complex event processing, businessperformance management, benchmarking, and text mining and predictive analytics. Informationavailable with the ministry of corporate affairs, select data from excise and Customs and theGoods and Services Tax, customised data from think-tanks such as CMIE and data received fromother enforcement agencies in India and abroad, will also be available at the facility, to be knownas the Revenue Forecasting & Business Intelligence Data Warehouse (RFBIDW). International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org      143 
  • 145. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  Table 1:External data Internal data BaseRFBIDW Information on PAN e-filing data tax deduction at source share transaction tax payment annual information return on high value transaction specific information gathered by central information branchWith this, RFBIDW is also expected to have certain locally relevant information, especially forinvestigation, and also specialized database on venture intelligence, trade analyst reports, equityanalysis and fiscal reports.According to an internal estimate of the department, the size to be handled by the I-T warehousecould be around four billion data pieces. The Integrated Taxpayer Database Management Systemalone has over 600 million pieces of information, mobile numbers would throw up around 1.2billion data pieces and PAN database had 120 million entries. Besides, there would be local dataand also information gathered from different sources.The idea behind RFBIDW was to shift attention from individual assesse to groups such asfamilies, business groups, trades, dealers in particular items and intermediaries for curbing taxevasion.By using the warehouse, the risk assessment wing of the department would prepare and updatethe database created on suspect intermediaries and known offenders and also organized schemesof tax avoidance and evasion. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org      144 
  • 146. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  Table 2:Examples of tax evasion failing to report all income claiming deductions for expenses not incurred or legally deductible claiming input credits for goods or services that GST has not been paid on not reporting cash wages not forwarding tax withheld from employees wages to the ATO not withholding tax from a workers wages (for example, paying in cash) not paying employee super entitlements not lodging tax returns in an attempt to avoid payment Not lodging a tax return to avoid child care or other obligation.Tax evasion is an activity commonly associated with businesses that use cash transactions, whichgives them the opportunity not to declare it and pay tax on it.Investigation unit of the departmentwould be able to quickly develop a 360-degree profile of suspected tax evaders from RFBIDWinformation and intelligence. The forecasting section would prepare reports on the basis ofRFBIDW data on the revenue potential in specific areas and provide inputs for policy decisions.Table 3:Data from following sources will be cleaned and profiled:SOURCES DATAINTERNAL DATABASES PAN / E-Filing / TDS, OLTAS, CIB, Annual Information Return, Share Transaction TaxEXTERNAL DATABASES Mobile phone, MCA database, GST / Excise / Customs, CMIE, Capital Line, Other Enforcement International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org      145 
  • 147. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619   agencies, Current / alternate addressesLOCAL DATABASES Locally relevant databases with specific relevance for investigation purposesSPECIALIZED DATABASE Venture Intelligence, Trade Analyst Reports, Equity Analysis Reports, Fiscal Reports etc MIS Reports Analytic Reports DataFindings and SuggestionsKautilya has also described in great detail the system of tax administration in the MauryanEmpire People who were suffering from diseases or were minor and students were exemptedfrom tax or given suitable remissions. The revenue collectors maintained up-to-date records ofcollection and exemptions. The total revenue of the State was collected from a large number ofsources as enumerated above. There were also other sources like profits from Stand land (Sita)religious taxes (Bali) and taxes paid in cash (Kara). Vanikpath was the income from roads andtraffic paid as tolls. If RFBIDW is used honestly and intelligently its 360 degree profile will beuseful to detect black money and tax evasions. It will cover a large section of society and will notconsider small groups, individual assess. Plans are afoot to assemble critical data from varioussources under one umbrella to nab tax evaders and better policy-making.REFERNCES:NEWSPAPERSBUSINESS STANDARD SEPTEMBER 14, 2011 International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org      146 
  • 148. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619   1. http://www.business-standard.com/india/news/cbdts-business-intelligence-data-warehousing-to- boost-tax-mop-up/449094/ 2. http://en.wikipedia.org/wiki/Business_intelligence 3. http://www.information-management.com/white_papers/1210202- htmlhttp://www.cainindia.org/news/9_2011/cbdts_business_intelligence_data_warehousing_to_b oost_tax_mopup.html 4. http://incometaxindia.gov.in/ccit/CBDT.asp: 5. http://www.indianexpress.com 6. http://www.incometaxindia.gov.in/archive/BreakingNews_FMSpeech_05312010.pdfhttp: //www.business-standard.com/india/) 7. http://www.ato.gov.au/corporate/content.aspx?doc=/content/30331.htmhttp://www.incom etaxindia.gov.in/HISTORY/PRE-1922.ASP International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org      147 
  • 149. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  EVALUATION OF KNOWLEDGE MANAGEMENT LEVEL OF EDUCATIONAL INSTITUTIONS USING FCE AND AHPMohit Maheshwarkar* Dr. N. Sohani**Pallavi Maheshwarkar*** ABSTRACTKnowledge Management (KM) comprises a range of strategies and practices used in anorganization to identify, create, represent, distribute, and enable adoption of insights andexperiences. Such insights and experiences comprise knowledge, either embodied in individualsor embedded in organizational processes or practice. Today many enterprises’ main profitgradually relies on the innovation, which should be established on the knowledge managementsystem. However, the cost of executing the project of knowledge management is always high, andto build up a set of effective criterion to realize the achievement of the project is significant. Thisresearch bases on the key success factors of the KM project and applies to the FuzzyComprehensive Evaluation (FCE) and Analytical Hierarchy Process (AHP) to calculate the levelof Knowledge Management for Educational Institutions.Keywords: Knowledge Management, FCE, AHP.*Assist. Professor, R.I.T, Indore (M.P)**Reader, I.E.T, D.A.V.V. , Indore (M.P)***Assist. Professor, P.I.T.S, Ujjain (M.P) International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     148 
  • 150. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 I. INTRODUCTIONKnowledge Management (KM) comprises a range of strategies and practices used in anorganization to identify, create, represent, distribute, and enable adoption of insights andexperiences. Such insights and experiences comprise knowledge, either embodied in individualsor embedded in organizational processes or practice. Knowledge management is a managementwhose core is knowledge, and a series of process management that is collections, organization,innovation, diffusion, use and development of knowledge on which production and operation ofenterprises relies. It is a management philosophy and methods, through the systematic use ofinformation content, processes and expert skills; it can improve the innovative capability ofenterprises and rapid response capability. Knowledge management is a process. The content ofknowledge management includes the contents of a system, not only referring only to a particularaspect. The main content of knowledge management should include four parts: knowledgeacquisition, knowledge management systems, knowledge sharing, and knowledge utilization.These four sections are closely connected, interdependent and mutually reinforcing. EducationalInstitutions face huge competition.Due to the introduction of competition in the market, theseEducational Institutions face unprecedented challenges. Therefore, KM is of extreme importanceto these institutions.II. EVALUATION OF EDUCATIONAL INSTITUTIONS’ KNOWLEDGEMANAGEMENT LEVELKnowledge management underlines the learning and inheritance of human knowledge, andemphasize on creation, accumulation, use and updates of internal knowledge. Through theimplementation of knowledge management, colleges can update and manage their knowledgeinnovation to create favorable conditions and environment, and can achieve the best combinationand effective use of the knowledge of their faculty members .Therefore, the introduction ofknowledge management theory to these institutions is the only way to survival and development.To gain a leading edge in the competition, colleges faced with the primary task is to enhance theability of individual faculty members. Through the strengthening and aggregation of individualcapacities, we can improve the overall organizations ability to win competitive advantage in themanagement, knowledge and talent areas. The Educational Institutions perform a difficult task of International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     149 
  • 151. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 handling the future of the country.They provide services which lead and represent the nation atthe global level. The evaluation of level of knowledge management is the important work whichshould be considered as a primary task from educatioal point of view for the country.In theevaluation the level of a college’s knowledge management, the objective has great significancefor the development of facilities provided to the students. For this purpose we follow theprinciples of scientific, systematic, hierarchical nature, practicality and operability.III. ANALYTICAL HIERARCHY PROCESSThe Analytic Hierarchy Process (AHP) is a structured technique for helping people deal withcomplex decisions. Rather than prescribing a "correct" decision, the AHP helps people todetermine one. An AHP hierarchy is a structured means of describing the problem at hand. Itconsists of an overall goal, a group of options or alternatives for reaching the goal, and a groupof factors or criteria that relate the alternatives to the goal. In most cases the criteria are furtherbroken down into sub criteria, sub-sub criteria, and so on, in as many levels as the problemrequires (Fig. 1).The hierarchy can be visualized as a diagram like the one below, with the goalat the top, the alternatives at the bottom, and the criteria filling up the middle. In such diagrams,each box is called a node. The boxes descending from any node are called its children. The nodefrom which a child node descends is called its parent. Applying these definitions to the diagrambelow, the five Criteria are children of the Goal, and the Goal is the parent of each of the fiveCriteria. Each Alternative is the child of each of the Criteria, and each Criterion is the parent ofthree Alternatives. Fig. 1 – Hierarchical Structure for AHP (Thomas L. Saaty, 2008) International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     150 
  • 152. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 Once the hierarchy is built, the decision makers systematically evaluate its various elements,comparing them to one another in pairs. In making the comparisons, the decision makers can useconcrete data about the elements, or they can use their judgments about the elements relativemeaning and importance. It is the essence of the AHP that human judgments, and not just theunderlying information, can be used in performing the evaluations. For this purpose a pair wisecomparison scale is used, which is shown in the Table 1 given below. After that AHP convertsthe evaluations to numerical values that can be processed and compared over the entire range ofthe problem. A numerical weight or priority is derived for each element of the hierarchy,allowing diverse and often incommensurable elements to be compared to one another in arational and consistent way. This capability distinguishes the AHP from other decision makingtechniques. In the final step of the process, numerical priorities are derived for each of thedecision alternatives. Since these numbers represent the alternatives relative ability to achievethe decision goal, they allow a straightforward consideration of the various courses of action. Table.1– Pair Wise Comparison Scale (Thomas L. Saaty, 2008)Saaty (2008) developed the following steps for applying AHP: i. Define the problem and determine its goal, International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     151 
  • 153. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  ii. Structure the hierarchy with the decision maker’s objective at the top with the intermediate levels capturing criteria on which subsequent levels depend and the bottom level containing the alternatives, and iii. Construct the set of n× n pair wise comparison matrices for each to the lower levels with one matrix for each element in the level immediately above. The pair wise comparisons are made suing the relative measurement scale (as discussed above). The pair wise comparisons capture a decision maker’s perception of which element dominates the other. iv. There are n(n-1)/2 judgments required to develop the set of matrices in step 3. Reciprocals are automatically assigned in each pair wise comparison. v. The hierarchy synthesis function is used to weight the eigenvectors by the weights of the criteria and the sum is taken over all weighted eigenvector entries corresponding to those in the next lower level of the hierarchy. vi. After all the pair wise comparisons are completed, the consistency of the comparisons is assessed by using the Eigen value, λ, to calculate a consistency index, CI: CI = (λ-n)/ (n-1). Where n is the matrix size. Judgment consistency can be checked by taking the consistency ratio (CR) of CI with the appropriate value in table 2, given below. Saaty [1980] suggests that the CR is acceptable if it does not exceed 0.10. If the CR is greater than 0.10, the judgment matrix should be considered inconsistent. To obtain a consistent matrix, the judgments should be reviewed and repeated. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     152 
  • 154. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  Table.2- Average Random Consistency Index Size of 1 2 3 4 5 6 7 8 9 10 Matrix Random 0.00 0.00 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.49 ConsistencyIV. LITRETURE REVIEWRobert G. and Eure P.E (2009) tell that Knowledge needs to be managed by the enterprise as anenterprise asset. They also focus on knowledge management. According to them Knowledgemanagement provides tools to achieve optimum effectiveness. They also insisted to include theKM as a topic in the Systems Engineering Handbook. Rizwana Irfan and Maqbool uddin-Shaikh(2010) find that data and knowledge coming from heterogeneous sources and formats arerequired to be efficiently extracted, transformed and stored for decision making. Their proposalprovides qualitative approach for enhancing the existing conceptual model for knowledgeprocessing to do transformation.NIU Dongxiao and LI Jianqing (2010) investigate that Knowledge management is a process toimprove the competitiveness of enterprises and identify the knowledge, acquire it and play itsfull role in the process. Knowledge Management is a new tool in management studies and apowerful tool for the development, use and sublimation of enterprise knowledge resources. Theyconclude that if the power generation companies want to sustain competitive advantage in theknowledge economy era, they should be started a developed corporate culture based onknowledge management-oriented as soon as possible, so that the organizations innovativecapacity and creativity of staffs personal mutually promote and make common progress. Qian-Wang Deng and Yong-Zheng Tian (2008) used an approach of integrating knowledgemanagement process models into product development process models. In the approach, amethod named knowledge-based engineering process model is adopted as the method of International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     153 
  • 155. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 modeling a product development process. To realize the integration between knowledgemanagement process model sand the product development process models, a basic rule,considering the knowledge management process as a special kind of sub-process in productdevelopment processes, is followed. Maryam Alavi and Dorothy E. Leidner (1999) focus onachieving the correct amount and type of accurate knowledge and garnering support forcontributing to the Knowledge Management System (KMS). Yang Tong (2009) classifies andconcludes the risks existed in knowledge management from a view of identification. Theresearch has been divided into following aspects of knowledge assets at risk: the risk ofknowledge spillovers, knowledge conversion risk, the risk of wastage, leakage risks, contractualrisks, moral hazard from Knowledge and knowledge of risk vector.Thomas L. Saaty (2008) tells that the Analytic Hierarchy Process (AHP) is a theory ofmeasurement through pair wise comparisons and relies on the judgments of experts to derivepriority scales. It is these scales that measure intangibles in relative terms. The comparisons aremade using a scale of absolute judgments that represents how much more; one elementdominates another with respect to a given attribute. The judgments may be inconsistent, and howto measure inconsistency and improve the judgments, when possible to obtain better consistencyis a concern of the AHP. The derived priority scales are synthesized by multiplying them by thepriority of their parent nodes and adding for all such nodes. He also tells that Analytic HierarchyProcess (AHP) is a theory of relative measurement with absolute scales of both tangible andintangible criteria based on the judgment of knowledgeable and expert people. How to measureintangibles is the main concern of the mathematics of the AHP. The AHP reduces amultidimensional problem into a one dimensional one. Decisions are determined by a singlenumber for the best outcome or by a vector of priorities that gives an ordering of the differentpossible outcomes. We can also combine our judgments or our final choices obtained from agroup when we wish to cooperate to agree on a single outcome.Jay Liebowitz (2005) discusses about the novel approach in applying the analytic hierarchyprocess (AHP) to generate the ratio scores for the valued graphs to be used in Social NetworkAnalysis (SNA) in order to develop a knowledge map of the organization. According to him itquantifies subjective judgments used in decision-making, and has been applied in numerousapplications throughout the world. Kamal M. Al-Subhi and Al-Harbi (2001) tell that the International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     154 
  • 156. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 Analytical Hierarchy Process (AHP) as a potential decision making method for use in projectmanagement. They used contractor prequalification problem as an example. For this ahierarchical structure is constructed for the prequalification criteria and the contractors wishingto prequalify for a project. They found that by applying the AHP, the prequalification criteria canbe prioritized and a descending-order list of contractors can be made in order to select the bestcontractors to perform the project. Their paper presents group decision-making using the AHP.Heung-Suk Hwang et al. (2005) used a supplier selection analysis model with the help of AHPmethod.V. THE EVALUATING MODEL CONSTRUCTIONWhen enterprises evaluate a thing, which have n index factors, they are marked asc1,c2,c3………………… cn. These index factors compose a finite set C.C = { c1,c2,c3………..cn}According to actual needs, the revies are divided into m degree v1,v2,v3………..vm. theycompose a finite set of reviews V.V= {v1,v2,v3……………..vm}When enterprises need to value a thing from a several different aspects, te result is compressive.The result is a fuzzy set B from reviews set V. Because V is a finite set, B is also a finite set.B = b1/v1+ b2/v2 + b3/v3+bm/vm. (1)It abbreviate as m dimension fuzzy vectors:B= {b1, b2, b3………………bm}Its case is V, and bj is the membership of the corresponding elements in B and bj Є [0,1] =1,2,3…………m.In the actual evaluating, the importance of each element is different. This is an objective fact.The set of factors is fuzzy one. A, which is the elements set U in the case; A is also a finite set.So the factor set is also a finite fuzzy set. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     155 
  • 157. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 A = a1/c1 + a2/c2 + r11 r12 ……. r1ma3/c3……………………. an/cn r 21 r22 …….. r2mSimilarly, A can also be said by n-dimensional fuzzy vectors. : : : :A = (a1, a2, a3………………… : : : : an )Its case us C, ai is the r n1 r n2 …….. rnm membershipof the corresponding elements in A, ai Є[0, 1], Σi=1n ai = 1.The fuzzy comprehension evaluation is to optimize the fuzzy set A by fuzzy relation B = ARB= A.R = (a1, a2, a3………..an).This is fuzzy comprehension evaluation model. B is the result of the fuzzy comprehensionevaluation, and it is m- dimensional fuzzy row vectors; A is the weight set of the model, and it isn- dimensional fuzzy row vectors; R is the fuzzy relations from C to V, and it is a n×m matrix, inwhich the rij is the possibility of remark j for element i.(Ting Wang at el.2010)VII. CASE STUDY Here the Educational Institutions selected for the analysis are three in nos. and all are the engineering institutions. The basic reason behind this selection is that today, the students of these collages are facing a lot of problems regarding their studies, faculties, practicals provided by the institution etc. In this paper we test the knowledge management level of colleges’ on the anvil of different criteria. The selected criteria are : Teaching Practices, Practical Training and Examination Pattern. These criteria are sub divided in sub criteria the details of which are given as follows. Fig.3 shows the hierarchical structure. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     156 
  • 158. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  Fig.2 – Hierarchical Structrue for Knowledge Management Level Evaluation  Conceptual teaching by the faculty: It defines how serious is the faculty about the concept making of the student.  Expert Lectures: Expert lectures provide easy to grasp approach and make the students aware of the current practices running on in the company.  Level of study material provided: The study material provided/ suggested should be such that it should not be treated as bunch of useless papers by the students.  Levels of practicals conducted: Practicals conducted should not fulfill only the basic requirements of the syllabus. Practicals should be designed in order to make the concepts of the students clearer about the subject.  No. of practicals conducted: Numbering of the practicals conducted should be such that it should clear almost each topic of the syllabus.  Educational Visits: These are directly hand to mouth approach and should not be neglected or underestimated in any case. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     157 
  • 159. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619   Projects delivered and guided: Projects delivered for submission must be carefully analyzed and reviewed by the departmental faculty members before assigning the students.  Level of question paper: Initial test paper designed for the students should be easy in order to see where the student is lacking. After problem Remidification, the later stages of the question paper may be modified on the basis of complexity.  Frequency of tests: The tests carried out by the institution should not daily but frequently.  Problem Remidification: After declaring the test’s results, each of the paper must be shown before the students in the class and there should be a large problem solving session in order to magnify the problems of the students.The detailed evaluation plan is given as follows: A. Determine the reviews set, V= {Strongest, Stronger, Strong, Weak and Weaker} to determine the KM level. The factors are constructed on the basis of examination of the education system analyzed by various experts, faculty members, students and parents. B. Comparison matrix is constructed according to hierarchical structure model for one institution. Here, in this paper we have chosen total no. of institutions as three out of which evaluation details of one institution are provided. The analysis of others will be similar to the first one. Table.2- Comparison matrix for C- Ck C C1 C2 C3 W C1 1 1/5 1/3 0.1042 C2 5 1 3 0.6372 C3 3 1/3 1 0.2583 International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     158 
  • 160. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  Σ 9 1.5333 4.333 1.000 λ max = 3.0341, CI = 0.0179, RI= 0.58, CR = 0.0332 < 0.10 Calculations for λ max, CI, RI and CR: λ max = 9(0.1042) + 1.5333(0.6372)+ 4.333(0.2583) = 3.0341 CI = (3.0358- 3)/2 = 0.0179 RI = 0.58 (From Table.1) & CR = CI/RI = 0.0179/0.58 = 0.030 < 0.10 Table.3 - Comparison Matrix for Ck- Cij C C11 C12 C13 W C11 1 1/3 1/5 0.1061 C12 3 1 1/3 0.2604 C13 5 3 1 0. 6334 λ max = 3.0385, CI = 0.0192, RI= 0.58, CR = 0.0332 < 0.10 Table.4 - Comparison Matrix for C2- Cij C C21 C22 C23 C24 W C21 1 3 1/3 1 0. 20087 C22 1/3 1 1/5 1/3 0.07885 C23 3 5 1 3 0.51941 C24 1 3 1/3 1 0.20087 λ max = 4.0428, CI = 0.01426, RI= 0.90, CR = 0.0158 < 0.10 International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     159 
  • 161. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  Table.5 - Comparison Matrix for C3- Cij C C1 C2 C3 W C1 1 1/5 1/3 0.1042 C2 5 1 3 0.6372 C3 3 1/3 1 0.2583λ max = 3.0341, CI = 0.0179, RI= 0.58, CR = 0.0332 < 0.10 C. Students, parents and faculty members gave their opinions on the basis of questionnaire given to them for the purpose of evaluation of level of knowledge management. On the basis of these opinions, experts give the weights to different colleges. Table.6-Weights for Teaching Practices Ck TEACHING PRACTICES (1.042) Cij 0.1061 0.2604 0. 6334 Strongest 0.3 0.4 0.3 Stronger 0.4 0.3 0.2 Strong 0.2 0.1 0.2 Weak 0.1 0.1 0.2 Weaker 0 0.1 0.1 International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     160 
  • 162. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  Table.7-Weights for Practical Training Ck PRACTICAL TRAINING (0.6372) Cij 0. 20087 0.07885 0.51941 0.20087 Strongest 0.3 0.4 0.3 0.3 Stronger 0.3 0.2 0.2 0.4 Strong 0.2 0.1 0.2 0.2 Weak 0.1 0.1 0.2 0.1 Weaker 0.1 0.1 0.1 0 Table.8-Weights for Exam Pattern Ck EXAM PATTERN (0.2583) Cij 0.1042 0.6372 0.2583 Strongest 0.4 0.2 0.4 Stronger 0.2 0.4 0.2 Strong 0.1 0.3 0.1 Weak 0.2 0.1 0.1 Weaker 0.1 0 0.2 International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     161 
  • 163. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 The above digitals can be used to investigate,B1= (0.1061 0.2064 0.6334) 0.3 0.4 0.2 0.1 0 0.4 0.3 0.1 0.1 0.1 0.3 0.2 0.2 0.2 0.1 B1 = (0.3044 0.2310 0.1685 0.1579 0.0840)Similarly, we can getB2 = (0.3079 0.2603 0.1921 0.1519 0.0799), andB3 = (0.2724 0.3274 0.2274 0.1104 0.0621)So, B = Uk . B1 B2 B3OR= (0.1042 0.6372 0.2583). 0.3044 0.2310 0.1685 0.1579 0.0840 0.3079 0.2603 0.1921 0.1519 0.0799 0.2724 0.3274 0.2274 0.1104 0.0621B = (0.2983 0.2745 0.1987 0.1418 0.0757)If V= (2,1,0,-1,-2), then the result will beKML1 = (0.2983 0.2745 0.1987 0.1418 0.0757). (2,1,0,-1,-2)KML1 = 0.5779, where KM1.= Knowledge Management level of Ist college. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     162 
  • 164. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 Proceeding in the similar manner we can get KML2 = 0.1310 and KML3 = 0.6995.The above result shows that KM level of third educational institution is best among all the threeinstitutions.VII. CONCLUSIONSToday, colleges play an important role in shaping the future of the country, so the evaluation oftheir knowledge management level is of great significance. In this paper, we have used theAnalytical Hierarchy process combined with Fuzzy Comprehensive Evaluation Technique toevaluate the level of knowledge management for Educational Institutions which seems to beworthwhile in taking such a type of decisions, as it gives the results in the form of numericalquantities which is very helpful in understanding the underlying problem. From this researchwork we can conclude that the average knowledge management level of the EducationalInstitutions is still very low and there is a strong need of taking corrective actions in thisdirection.REFERENCES 1 Heung-Suk Hwang, Chiung Moon, Chun-Ling Chuang and Meng-Jong Goan3 (2005). Supplier Selection and Planning Model Using AHP. International Journal of the Information Systems for Logistics and Management (IJISLM), Vol. 1, No. 1, pp. 47-53 (2005) 2 Jay Liebowitz (2005) Linking Social Network Analysis with the Analytic Hierarchy Process for Knowledge Mapping in Organizations Journal Of Knowledge Management Vol. 9 NO. 1 2005, pp. 76-86, Q Emerald Group Publishing Limited, ISSN 1367-3270 3 Kamal M. Al-Subhi Al-Harbi (2001). Application of the AHP in Project Management. International Journal of Project Management 19 (2001) 4 Maryam Alavi and Dorothy E. Leidner (1999). Knowledge Management Systems: Issues, Challenges, and Benefits. Association for Information Systems. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     163 
  • 165. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  5 NIU Dongxiao, LI Jianqing (2010), Evaluation on the Level of generation Enterprise Knowledge Management Based on AHP and Gray Relational Analysis. IEEE International Conference. 6 Qian-Wang Deng, Yong-Zheng Tian (2008). Modeling Knowledge Management Processes from Perspectives of Knowledge Agents. IEEE International Conference. 7 Rizwana Irfan, Maqbool uddin-Shaikh (2010). Enhanced Knowledge Management Process for Group Decision Making. Second IEEE International Conference on Future Information Technology and Management Engineering. 8 Robert G. and Eure, P.E (2009). Knowledge Management As an Integral Component of Systems Engineering .Incose International Council of System Engineering. 9 Thomas L. Saaty (2008). Decision Making with the Analytic Hierarchy Process. Int. J. Services Sciences, Vol. 1, No. 1, 2008. 10 Yang Tong (2009) Summary Research of Risk Identification in the Process of Knowledge Management. Second IEEE International Conference on Future Information Technology and Management Engineering. 11 Ting Wang and Lifeng Li (2010). A New Hybrid Method to Evaluate the HPR Performance Based on FCE and AHP. Third IEEE, Computer society’s International Conference on Knowledge Discovery and Data Mining. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     164 
  • 166. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  EVALUATION OF KNOWLEDGE MANAGEMENT LEVEL OF EDUCATIONAL INSTITUTIONS USING ANALYTICAL HIERARCHY PROCESS: A CASE STUDY IN INDIAMohit Maheshwarkar*N. Sohani, **Pallvai Maheshwarkar*** ABSTRACTKnowledge Management (KM) comprises a range of strategies and practices used in anorganization to identify, create, represent, distribute, and enable adoption of insights andexperiences. Such insights and experiences comprise knowledge, either embodied in individualsor embedded in organizational processes or practice. Today many enterprises’ main profitgradually relies on the innovation, which should be established on the knowledge managementsystem. However, the cost of executing the project of knowledge management is always high, andto build up a set of effective criterion to realize the achievement of the project is significant. Thisresearch bases on the key success factors of the KM project and applies to the AnalyticalHierarchy Process (AHP) to calculate the level of Knowledge Management for EducationalInstitutions in an Indian city, Indore.Keywords: Knowledge Management, Analytical Hierarchy Process.*Assist. Professor, R.I.T, Indore (M.P)** Reader ,I.E.T, D.A.V.V. , Indore (M.P)***Assist. Professor, P.I.T.S, Ujjain (M.P) International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  165
  • 167. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  I. INTRODUCTIONKnowledge Management (KM) comprises a range of strategies and practices used in anorganization to identify, create, represent, distribute, and enable adoption of insights andexperiences. Such insights and experiences comprise knowledge, either embodied in individualsor embedded in organizational processes or practice. Knowledge management is a managementwhose core is knowledge, and a series of process management that is collections, organization,innovation, diffusion, use and development of knowledge on which production and operation ofenterprises relies. It is a management philosophy and methods, through the systematic use ofinformation content, processes and expert skills; it can improve the innovative capability ofenterprises and rapid response capability. Knowledge management is a process. The content ofknowledge management includes the contents of a system, not only referring only to a particularaspect. The main content of knowledge management should include four parts: knowledgeacquisition, knowledge management systems, knowledge sharing, and knowledge utilization.These four sections are closely connected, interdependent and mutually reinforcing. EducationalInstitutions face huge competition. Due to the introduction of competition in the market in Indian, these Educational Institutions face unprecedented challenges. Therefore, KM is of extremeimportance to these institutions.II. EVALUATION OF EDUCATIONAL INSTITUTIONS’ KNOWLEDGEMANAGEMENT LEVELKnowledge management underlines the learning and inheritance of human knowledge, andemphasize on creation, accumulation, use and updates of internal knowledge. Through theimplementation of knowledge management, colleges can update and manage their knowledgeinnovation to create favorable conditions and environment, and can achieve the best combinationand effective use of the knowledge of their faculty members .Therefore, the introduction ofknowledge management theory to these institutions is the only way to survival and development.To gain a leading edge in the competition, colleges faced with the primary task is to enhance theability of individual faculty members. Through the strengthening and aggregation of individualcapacities, we can improve the overall organizations ability to win competitive advantage in themanagement, knowledge and talent areas. The Educational Institutions perform a difficult task ofhandling the future of the country.They provide services which lead and represent the nation at International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  166
  • 168. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 the global level. The evaluation of level of knowledge management is the important work whichshould be considered as a primary task from educatioal point of view for the country.In theevaluation the level of a college’s knowledge management, the objective has great significancefor the development of facilities provided to the students. For this purpose we follow theprinciples of scientific, systematic, hierarchical nature, practicality and operability.III. ANALYTICAL HIERARCHY PROCESSThe Analytic Hierarchy Process (AHP) is a structured technique for helping people deal withcomplex decisions. Rather than prescribing a "correct" decision, the AHP helps people todetermine one. An AHP hierarchy is a structured means of describing the problem at hand. Itconsists of an overall goal, a group of options or alternatives for reaching the goal, and a groupof factors or criteria that relate the alternatives to the goal. In most cases the criteria are furtherbroken down into sub criteria, sub-sub criteria, and so on, in as many levels as the problemrequires (Fig. 1).The hierarchy can be visualized as a diagram like the one below, with the goalat the top, the alternatives at the bottom, and the criteria filling up the middle. In such diagrams,each box is called a node. The boxes descending from any node are called its children. The nodefrom which a child node descends is called its parent. Applying these definitions to the diagrambelow, the five Criteria are children of the Goal, and the Goal is the parent of each of the fiveCriteria. Each Alternative is the child of each of the Criteria, and each Criterion is the parent ofthree Alternatives. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  167
  • 169. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  Fig. 1 – Hierarchical Structure for AHP (Thomas L. Saaty, 2008)Once the hierarchy is built, the decision makers systematically evaluate its various elements,comparing them to one another in pairs. In making the comparisons, the decision makers can useconcrete data about the elements, or they can use their judgments about the elements relativemeaning and importance. It is the essence of the AHP that human judgments, and not just theunderlying information, can be used in performing the evaluations. For this purpose a pair wisecomparison scale is used, which is shown in the Table.2 given below. After that AHP convertsthe evaluations to numerical values that can be processed and compared over the entire range ofthe problem. A numerical weight or priority is derived for each element of the hierarchy,allowing diverse and often incommensurable elements to be compared to one another in arational and consistent way. Priorities are numbers associated with the nodes of the hierarchy.The priority of the Goal is taken as 1.000. The priorities of the children of any Criterion can alsovary but will always add up to 1.000, as will those of their own children, and so on down thehierarchy. If the priorities within every group of child nodes are equal then the priorities arecalled Default Priorities. The priority of an attribute with respect to the ultimate goal is calledGlobal Priority. The priorities indicate the relative weights given to the items in a given group ofnodes. Depending on the problem at hand, "weight" can refer to importance, or preference, orlikelihood, or whatever factor is being considered by the participants. This capabilitydistinguishes the AHP from other decision making techniques. In the final step of the process,numerical priorities are derived for each of the decision alternatives. Since these numbersrepresent the alternatives relative ability to achieve the decision goal, they allow astraightforward consideration of the various courses of action. Table 1 – Pair Wise Comparison Scale (Thomas L. Saaty, 2008) International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  168
  • 170. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 Saaty (2008) developed the following steps for applying AHP: i. Define the problem and determine its goal, ii. Structure the hierarchy with the decision maker’s objective at the top with the intermediate levels capturing criteria on which subsequent levels depend and the bottom level containing the alternatives, and iii. Construct the set of n× n pair wise comparison matrices for each to the lower levels with one matrix for each element in the level immediately above. The pair wise comparisons are made suing the relative measurement scale (as discussed above). The pair wise comparisons capture a decision maker’s perception of which element dominates the other. iv. There are n(n-1)/2 judgments required to develop the set of matrices in step 3. Reciprocals are automatically assigned in each pair wise comparison. v. The hierarchy synthesis function is used to weight the eigenvectors by the weights of the criteria and the sum is taken over all weighted eigenvector entries corresponding to those in the next lower level of the hierarchy. vi. After all the pair wise comparisons are completed, the consistency of the comparisons is assessed by using the Eigen value, λ, to calculate a consistency index, CI: CI = (λ-n)/ (n-1). Where n is the matrix size. Judgment consistency can be checked by taking the consistency ratio (CR) of CI with the appropriate value in table 2, given below. Saaty [1980] suggests that the CR is acceptable if it does not exceed 0.10. If the CR is greater than 0.10, the judgment matrix should be considered inconsistent. To obtain a consistent matrix, the judgments should be reviewed and repeated. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  169
  • 171. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  Table.2- Average Random Consistency Index Size of 1 2 3 4 5 6 7 8 9 10 Matrix Random 0.00 0.00 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.49 ConsistencyIV. LITRETURE REVIEWRobert G. and Eure P.E (2009) tell that Knowledge needs to be managed by the enterprise as anenterprise asset. They also focus on knowledge management. According to them Knowledgemanagement provides tools to achieve optimum effectiveness. They also insisted to include theKM as a topic in the Systems Engineering Handbook. Rizwana Irfan and Maqbool uddin-Shaikh(2010) find that data and knowledge coming from heterogeneous sources and formats arerequired to be efficiently extracted, transformed and stored for decision making. Their proposalprovides qualitative approach for enhancing the existing conceptual model for knowledgeprocessing to do transformation.NIU Dongxiao and LI Jianqing (2010) investigate that Knowledge management is a process toimprove the competitiveness of enterprises and identify the knowledge, acquire it and play itsfull role in the process. Knowledge Management is a new tool in management studies and apowerful tool for the development, use and sublimation of enterprise knowledge resources. Theyconclude that if the power generation companies want to sustain competitive advantage in theknowledge economy era, they should be started a developed corporate culture based onknowledge management-oriented as soon as possible, so that the organizations innovativecapacity and creativity of staffs personal mutually promote and make common progress. Qian-Wang Deng and Yong-Zheng Tian (2008) used an approach of integrating knowledgemanagement process models into product development process models. In the approach, amethod named knowledge-based engineering process model is adopted as the method ofmodeling a product development process. To realize the integration between knowledgemanagement process model sand the product development process models, a basic rule,considering the knowledge management process as a special kind of sub-process in product International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  170
  • 172. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 development processes, is followed. Maryam Alavi and Dorothy E. Leidner (1999) focus onachieving the correct amount and type of accurate knowledge and garnering support forcontributing to the Knowledge Management System (KMS). Yang Tong (2009) classifies andconcludes the risks existed in knowledge management from a view of identification. Theresearch has been divided into following aspects of knowledge assets at risk: the risk ofknowledge spillovers, knowledge conversion risk, the risk of wastage, leakage risks, contractualrisks, moral hazard from Knowledge and knowledge of risk vector.Thomas L. Saaty (2008) tells that the Analytic Hierarchy Process (AHP) is a theory ofmeasurement through pair wise comparisons and relies on the judgments of experts to derivepriority scales. It is these scales that measure intangibles in relative terms. The comparisons aremade using a scale of absolute judgments that represents how much more; one elementdominates another with respect to a given attribute. The judgments may be inconsistent, and howto measure inconsistency and improve the judgments, when possible to obtain better consistencyis a concern of the AHP. The derived priority scales are synthesized by multiplying them by thepriority of their parent nodes and adding for all such nodes. He also tells that Analytic HierarchyProcess (AHP) is a theory of relative measurement with absolute scales of both tangible andintangible criteria based on the judgment of knowledgeable and expert people. How to measureintangibles is the main concern of the mathematics of the AHP. The AHP reduces amultidimensional problem into a one dimensional one. Decisions are determined by a singlenumber for the best outcome or by a vector of priorities that gives an ordering of the differentpossible outcomes. We can also combine our judgments or our final choices obtained from agroup when we wish to cooperate to agree on a single outcome.Jay Liebowitz (2005) discusses about the novel approach in applying the analytic hierarchyprocess (AHP) to generate the ratio scores for the valued graphs to be used in Social NetworkAnalysis (SNA) in order to develop a knowledge map of the organization. According to him itquantifies subjective judgments used in decision-making, and has been applied in numerousapplications throughout the world. Kamal M. Al-Subhi and Al-Harbi (2001) tell that theAnalytical Hierarchy Process (AHP) as a potential decision making method for use in projectmanagement. They used contractor prequalification problem as an example. For this ahierarchical structure is constructed for the prequalification criteria and the contractors wishingto prequalify for a project. They found that by applying the AHP, the prequalification criteria can International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  171
  • 173. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 be prioritized and a descending-order list of contractors can be made in order to select the bestcontractors to perform the project. Their paper presents group decision-making using the AHP.Heung-Suk Hwang et al. (2005) used a supplier selection analysis model with the help of AHPmethod.V. CASE STUDY In this paper we test the knowledge management level of colleges’ on the anvil of different criteria. The selected evaluationa criteria are : Conceptual Teaching, Practical Assessment, Expert Lecture Criteria, Educational Visits and Problem Sorting. This evaluation criterion has been developed on the basis of literature review and a series of informal discussions with a large number of academicians. On these selected criteria different Educational Institutions will be tested. Here the Educational Institutions selected for the analysis are three in nos. Fig.2 shows the hierarchical structure. Fig.2 – Hierarchical Structrue for Knowledge Management Level EvaluationA. Comparison of CriterionOn making pairwise comparisons of all the five criterias we will get the following combinations.  Conceptual Teaching Vs. Practical Assessment  Conceptual Teaching Vs. Expert Lecture Criteria  Conceptual Teaching Vs. Educational Visits  Conceptual Teaching Vs. Problem Sorting  Practical Assessment Vs. Expert Lecture Criteria  Practical Assessment Vs. Educational Visits International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  172
  • 174. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619   Practical Assessment Vs. Problem Sorting  Expert Lecture Criteria Vs. Educational Visits  Expert Lecture Criteria Vs. Problem Sorting  Educational Visits Vs. Problem SortingAs a result of these pair wise comparisons we will get the following pairwise comparison matrix: Table.3- Pairwise Comparison Matrix for different criteria Expert Conceptual Practical Educational Problem From/To Lecture Teaching Assessment Visits Sorting Criteria Conceptual Teaching 1 1 5 3 4 Practical Assessment 1 1 1 4 4 Expert Lecture Criteria 1/5 1 1 4 5 Educational Visits 1/3 1/4 1/4 1 5 Problem Sorting 1/4 1/4 1/5 1/5 1On solving the above matrix analytically or simply putting the values in AHP software we willget the following results: International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  173
  • 175. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  Table.4- Priority values for different criteria S.No Criteria Priority 1. Conceptual Teaching 0.3545 2. Practical Assessment 0.263 3. Expert Lecture Criteria 0.21656 4. Educational Visits 0.1139 5. Problem Sorting 0.05142C.I. = 0.070911, R.I. = 1.12, C.R. = 0.0625<0.10 B. Comparion of InstitutionsNow the priorities for the Educational Institutions were calculated. For the purpose ofcomparison of evaluation of level of conceptual teaching, syatametically disigned quesitonnirewas given to the students and the results were plotted on a pairwise comparison matrix, given asfollows: Table.5- Pairwise comparison matrix for Conceptual Teaching Criteria From/To A B C A 1 1/3 1/5 B 3 1 1/3 C 5 3 1On solving the above matrix we will get the following priority values: International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  174
  • 176. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  Table.6- priority values for Conceptual Teaching Criteria COLLEGES PRIORITIES (LOCAL) PRIORITIES (GLOBAL) A 0.106 0.037577 B 0.2604 0.09231 C 0.633345 0.22452C.I.= 0.0192555, R.I.=0.58, C.R.=0.033<0.10Proceeding in the similar manner we will get the different priority matrices and different valuesof priorities for different criteria. The details of matrices along with the results are given asfollows: Table.7- Pairwise comparison matrix for Practical Assessment Criteria From/To A B C A 1 5 6 B 1/5 1 3 C 1/6 1/3 1 Table.8- priority values for Practical Assessment Criteria COLLEGES PRIORITIES (LOCAL) PRIORITIES (GLOBAL) A 0.70708 0.1859 B 0.20141 0.05297 C 0.0915 0.0240C.I. =0.0470076, R.I.=0.58, C.R.=0.0810<0.10 International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  175
  • 177. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  Table.9- Pairwise Comparison for Expert Lecture Criteria From/To A B C A 1 1/4 2 B 4 1 5 C 1/2 1/5 1 Table.10- Priority values for Expert Lecture Criteria COLLEGES PRIORITIES (LOCAL) PRIORITIES (GLOBAL) A 0.2014 0.043615 B 0.6806 0.147390 C 0.1179 0.025532C.I. =0.0122975, R.I. =0.58, C.R. = 0.0210<0.10 Table.11- Pairwise Comparison for Educational Visits Criteria From/To A B C A 1 4 8 B 1/4 1 5 C 1/8 1/5 1 Table.12- Priority values for Educational Visits Criteria COLLEGES PRIORITIES (LOCAL) PRIORITIES (GLOBAL) A 0.6893 0.07851 B 0.2437 0.02775 C 0.0666 0.00758C.I. =0.0470076, R.I. =0.58, C.R. = 0.0810<0.10 International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  176
  • 178. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  Table.13- Pairwise comparison matrix for Problem Sorting Criteria From/To A B C A 1 3 9 B 1/3 1 7 C 1/9 1/7 1 Table.14 – Priority values for Problem Sorting Criteria COLLEGES PRIORITIES (LOCAL) PRIORITIES (GLOBAL) A 0.6486 0.03335 B 0.2946 0.015148 C 0.0567 0.00291C.I. =0.0401499, R.I. =0.58, C.R. =0.0692<0.10Finally, on adding up the priority values for different criteria we will get the value of knowledgemanagement level for an institution. Table.15- Comprehensive Evaluation of Educational Institutions Evaluation of Knowledge Management Level – An AHP Approach Conceptual Practical Expert Lecture Educational ProblemCOLLEGES /CRITERIA TOTAL Teaching Assessment Criteria Visits Sorting A 0.037577 0.1859 0.043615 0.07851 0.03335 0.378952 B 0.09231 0.05297 0.147390 0.02775 0.015148 0.335568 C 0.22452 0.0240 0.025532 0.00758 0.00291 0.284542 0.3545 0.263 0.21656 0.1139 0.05142 1.00000 TOTAL 1.000000 International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  177
  • 179. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 According to the evaluation system, the grades of "very high”, "Medium" and "low", are setrespectively. On this basis the colleges are evaluated. Table.16- Evaluation of Knowledge management level S.No College Knowledge Management Level 1. A Very High 2. B Medium 3. C LowVI. CONCLUSIONSToday, colleges play an important role in shaping the future of the country, So the evaluation oftheir knowledge management level is of great significance. In this paper, we have used theAnalytical Hierarchy process to evaluate the level of knowledge management for EducationalInstitutions which seems to be worthwhile in taking such a type of decisions, as it gives theresults in the form of numerical quantities which is very helpful in understanding the underlyingproblem. From this research work we can conclude that the average knowledge managementlevel of the Educational Institutions is still very low and there is a strong need of takingcorrective actions in this direction.REFERENCES 1 Heung-Suk Hwang, Chiung Moon, Chun-Ling Chuang and Meng-Jong Goan3 (2005). Supplier Selection and Planning Model Using AHP. International Journal of the Information Systems for Logistics and Management (IJISLM), Vol. 1, No. 1, pp. 47-53 (2005) International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  178
  • 180. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  2 Jay Liebowitz (2005) Linking Social Network Analysis with the Analytic Hierarchy Process for Knowledge Mapping in Organizations Journal Of Knowledge Management Vol. 9 NO. 1 2005, pp. 76-86, Q Emerald Group Publishing Limited, ISSN 1367-3270 3 Kamal M. Al-Subhi Al-Harbi (2001). Application of the AHP in Project Management. International Journal of Project Management 19 (2001) 4 Maryam Alavi and Dorothy E. Leidner (1999). Knowledge Management Systems: Issues, Challenges, and Benefits. Association for Information Systems. 5 NIU Dongxiao, LI Jianqing (2010), Evaluation on the Level of generation Enterprise Knowledge Management Based on AHP and Gray Relational Analysis. IEEE International Conference. 6 Qian-Wang Deng, Yong-Zheng Tian (2008). Modeling Knowledge Management Processes from Perspectives of Knowledge Agents. IEEE International Conference. 7 Rizwana Irfan, Maqbool uddin-Shaikh (2010). Enhanced Knowledge Management Process for Group Decision Making. Second IEEE International Conference on Future Information Technology and Management Engineering. 8 Robert G. and Eure, P.E (2009). Knowledge Management As an Integral Component of Systems Engineering .Incose International Council of System Engineering. 9 Thomas L. Saaty(2008). Decision Making with the Analytic Hierarchy Process. Int. J. Services Sciences, Vol. 1, No. 1, 2008. 10 Yang Tong (2009) Summary Research of Risk Identification in the Process of Knowledge Management. Second IEEE International Conference on Future Information Technology and Management Engineering. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org  179
  • 181. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  PROBE FEED RECTANGULAR PATCH MICROSTRIP ANTENNA: CAD METHODOLOGYDr. R.D. Kanphade*Dr. D.G. Wakade**Prof. N.T. Markad*** ABSTRACTAntenna is a means for radiating or receiving radio waves. In addition to receiving ortransmitting energy, an antenna is used in an advanced wireless system is usually required tooptimize the radiation energy in same direction and suppress it in others. A micro strip patchantenna also referred to as patch antenna is a narrowband, wide beam antenna fabricated byetching the antenna element patch in metal trace bonded to an insulating dielectric substratewith a continuous metal layer bonded to opposite side of substrate which forms a ground plane.Probe feed rectangular patch Micro strip antenna simulated in FDTD software IE3D. Proposednovel probe feed rectangular patch microstrip antenna is presented. It has a return loss of -23.5dBat a frequency of 1.88GHZ. Antenna offers VSWR 1.15at a frequency of 1.88GHZ.Antenna offers a band width of 14 MHZ. By observing a smith chart it is seen that antenna offersresistive, capacitive and inductive impedance. Antenna offers unidirectional radiation pattern.Unidirectional radiation pattern plays important role in next generation mobile communicationand computing Due to unidirectional radiation pattern cost of power of a mobile communicationsystem is reduced. Probe feed rectangular patch micro strip antenna offer an antenna efficiencyof 87%. Also antenna offers radiation efficiency of 86%. The exact location of the probe whichcan guarantee the desired performance is not given in the literature. So, hit and trial method isused to locate the co-ordinates of the probe feed which can provide satisfactory output. Usinghit and trial, the co-ordinates of the probe were found to be (x, y) =(6,2).KEYWORDS: Probe feed, Micro strip patch antenna, Efficiency, Radiation efficiency, VSWR,Smith chart.*Principal,Dhole Patil College of Engineering,Wagholi,Pune**Director,P.R.Patil College of Engineering,Amravati***Associate Professor,BVCOE,Deptt. Of ECE International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     180 
  • 182. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 [I] INTRODUCTIONIn telecommunication; there are several types of micro strip antennas( also known as printedantennas) the most common of which is the micro strip patch antenna or patch antenna. A patchantenna is a narrowband, wide-beam antenna fabricated by etching the antenna element patternin metal bonded to an insulating dielectric substrate with a continuous metal layer bonded to theopposite side of the substrate which forms a ground plane. Common micro strip antennaradiator shapes are square, rectangular, circular and elliptical but any continuous shape ispossible. Some patch antennas eschew a dielectric substrate and suspend a metal patch in airabove a ground plane using dielectric spacers, the resulting structure is less robust but providesbetter band width. Because such antennas have a very low profile; are mechanically rugged andcan be conformable, they are often mounted on the exterior of aircraft and spacecraft or areincorporated into mobile radio communication devices; [1].Micro strip antennas are also relatively inexpensive to manufacture and design because of thesimple two dimensional physical geometry. They are usually employed at UHF and higherfrequencies because the size of the antenna is directly tied to the wavelength at the resonancefrequency [2].A single patch antenna provides a maximum directive gain of around -6 dBi. It is relatively easyto print on array of patches on a single (large) substrate using lithographic techniques. Patcharrays can provide much higher gain than a single patch at little additional cost; matching andphase adjustment can be performed with printed micro strip feed structures, again in the someoperation that form the radiating patches. The ability to create high gain arrays in a low profileantenna is one reason that patch arrays are common on [3] airplanes and in other militaryapplication. An array antenna is a special arrangement of basic antenna components involvingnew factors and concepts. Before you begin studying about arrays, you need to study some newterminology [4].An array antenna is made up of more than one ELEMENT, but the basic elements is generallythe dipole. Sometimes the basic element is made longer or shorter than a half-wave, but thedeviation usually is not great [4] [5]. Typically an antenna is tuned for a specific frequency and iseffective for a range of frequencies that are usually on that resonant frequency. Some antenna International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     181 
  • 183. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 design have multiple resonant frequencies, and some are relatively effective over very broadrange of frequencies. [6]Gain as a parameter measures the efficiency of a given antenna with respect to a given norm,usually achieved by modification of its directionality. An antenna with a low gain emitsradiation with about the same power in all directions, whereas high gain antenna will radiate inparticular direction. The radiation pattern of an antenna is the geometric pattern of the relativefield strengths of field emitted by the antenna. In field of antenna the term “radiation pattern”most commonly refers to directional (angular) dependence of radiation from the antenna or othersource. Usually, the directivity is expressed in dBi. The reason that the units are dBi, (decibelrelative to an isotropic radiations that for n isotropic radiator, the radiated lower density is aconstant and therefore equals the average radiated power density ( the denominator). The angleacross the main lobe of an antenna pattern, between the two directions, at which, the antenna’ssensitivity is half its maximum value at the centre of the lobe. It is abbreviated as HPBW[7][8].As an electromagnetic wave travels through the different parts of the antenna system (radio, feedline, antenna, free space) it may encounter differences in impendence (E/H; V/I, etc.) At eachinterface, depending on the impedance match, some fraction of the wave’s energy will reflectedback to the source [5], forming a standing wave in the feed line. The ratio of maximum power tominimum power in the wave can be ratio (SWR). A SWR of 1:1 is ideal. A SWR of 1.5:1 isconsidered to be marginally acceptable in low power application. Efficiency is the ratio ofpower actually radiated to the power put into antenna terminals. The bandwidth of an antennais the range of frequencies over which it is effective, usually centered on the resonant frequency.The band width of antenna may be increased by several techniques, including using thickerwires, replacing wires with cages to simulate a thicker wire, tapering antenna components (likein a feed horn); and combining multiple antenna into a single assembly and allowing the naturalimpedance to select correct antenna, small antenna are usually preferred for convenience, butthere is a fundamental limit relating bandwidth, size and efficiency. The polarization of anantenna is the orientation of the electric field (E-plane) of the radios waves with respect to theEarth’s surface and is determined by physical structure of the antenna and by its orientation. Ithas nothing in common with antenna directionality terms: horizontal, vertical and circular (9)[10] International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     182 
  • 184. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 In high performance aircraft, satellite and missile applications, where size, weight, cost,performance, ease of installation and aerodynamic profile are constraints, and low profileantenna may be required. To meet there requirement microstrip antenna can be used. Theseantennas are low profile, conformable to planar and non-planar surfaces. Simple andinexpensive to manufacture using modern printed-circuit technology. Mechanically robust whenmounted on rigid surfaces compatible with MMIC design [11].There are many configurations that can be used to feed micro strip antenna. The four mostpopular are :-  Microstrip line  Coaxial cable  Aperture coupling  Proximity couplingThe micro strip line feed is easy to fabricate; simple to match by controlling the inset positionand rather simple to model. Because the dimensions of the patch re finite along the length andwidth; the fields at the edges of the patch undergo fringing. The amount of fringing is a functionof the dimensions of the patch and the height of the substrate. Due to fringing field antennaradiate. Fringing Fields Shown in Figure 1.Figure 1 Fringing Field Figure 2 Patch Antenna International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     183 
  • 185. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 [II] FEED NETWORKFeed is of different types but most popular feed are –  Transformer feed  Microstrip line feed  Coaxial cable feed  Aperture coupling feed  Proximity coupling feed.Out of above mentioned feed for micro strip patch antenna feed applied to it is transformer feedtype. Suppose impendence at antenna is 100Ω by transformer type feed 100Ω . This 50Ωimpendence known as terminating impendence. Terminating impendence matches to probeimpedance hence power delivered to micro strip patch antenna is maximum. [11]The exact location of the probe which can guarantee the desired performance is not given in theliterature. So, hit and trial method is used to locate the co-ordinates of probe feed which canprovide satisfactory output. Using hit and trial, the co-ordinates of the probe were found to be(x,y) =(6,2).[III] DESIGN OF RECTANGULAR PATCH ANTENNA WITH PROBE FEED.The three essential parameters for the design of a rectangular patch antenna are:- The resonantfrequency of the antenna must be selected appropriately. The personal communication system(PCS) uses the frequency range from 1850-1990 MHZ. Hence the antenna design must be ableto operate in this frequency range. The resonant frequency selected for our design is 1.9 GHZ.The dielectric material selected for our design is FR4 which has a dielectric constant of 4.4. Asubstrate with a high dielectric constant has been selected since it reduces the dimensions of theantenna.For the micro strip patch antenna to be used in cellular phones, it is essential that the antenna isnot bulky. Hence, the height of the dielectric substrate is selected as 1.6mm.  Calculation of width (W) :- The width of the micro strip patch antenna is given by : International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     184 
  • 186. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  W= C____________ 2f0√(Єr+1/2)Substituting C=3e8m/s ; Єr= 4.4 and f0 = 1.9GHZWe get W = 0.048 m = 48.0mm  Calculation of Effective dielectric constant (Єreff) :- The effective dielectric constant is calculated as : Єreff = (Єr+1)/(Єr-1)/2[1+12h/w]-1/2Substituting Єr =4.4; w= 48.0mm and h=1.6mm we get Єreff =4.14  Calculation of the Effective length (Leff) :- The effective length is given as Leff = C/(2 f0√Єreff).Substituting Є reff=4.14,c=3e8m/s and f0=1.9 GHz.Weget : Leff = 0.0388m = 38.8mm  Calculation of the length extension (∆ L):- The length extension is given as :Substituting the values, we get; ∆ L=.412h(Єreff+ .3)( w/h+.264)/(Єreff.-.258)(w/h+.8)  Calculation of actual length of patch (L):- The actual length is obtained by: L= (Leff .– 2∆L ) Substituting the values, we get: L= 37.3mm In general, top view of probe, Feed rectangular patch micro strip antenna is shown in Fig.2. Geometry probe feed patch antenna shown in Figure.2.[IV] RESULTS AND ANALYSIS International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     185 
  • 187. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 The design analysis gave the following results. Radiation pattern of probe feed rectangular patchmicro strip antenna is shown in Figure.3. The radiation pattern of probe feed rectangular patchmicro strip antenna is unidirectional. This unidirectional radiation pattern plays important role innext generation mobile communication and computing. Due to unidirectional radiation patterncost of power of mobile communication is reduced.Gain v/s frequency plot of probe feed rectangular patch micro strip antenna is shown in Figure.4.From this plot, it is seen that antenna offers return loss of -23.5 dB at a frequency of 1.88 GHZ.VSWR V/S frequency plot shown in Figure 5, From Figure 5 it is seen that antenna has a VSWRof 1.15 at a frequency of 1.88 GHZ. Smith chart shown in Figure 6. From smith chart it is seenthat antenna offered resistive, capacitive as well as inductive impendence. Figure. 7 showsefficiency v/s frequency plot. From this plot it is seen that probe feed rectangular patch microstrip antenna offered antenna efficiency of 87% and radiation efficiency of 86%. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     186 
  • 188. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  Figure 3 RADIATION PARTTREN  Figure 4 RETURN LOSS  Figure 5 VSWR  Figure 6 EFFICIENCY  International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     187 
  • 189. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  Figure 7 SMITH CHART [V] CONCLSIONIt is seen that the design adopted for the probe feed rectangular micro strip patch antenna areaccurate. This antenna can be used at 1.88 GHZ frequency for mobile communication andcomputing applications where the frequency of operation is 1.88 GHZ. For antenna to work properly the VSWR must be less than two and return loss must be less than10dB, only then the antenna will radiate or receive the power with minimum reflection. Asdesigned antenna has a return loss -23.5dB and VSWR 1.15 at a frequency of 1.88 GHZ, so thisantenna is used in mobile communication and computing satisfactorily. Probe feed rectangularmicro strip antenna are ideal for mobile communication, application where weight is the mainconstraint. Due to unidirectional radiational pattern antenna plays important role in nextgeneration mobile communication and computing. Cost of power of mobile communicationsystem is saved due to this antenna.[VI] REFERENCES[1] Y Li, C. Chen, Y.cho “ A unified optimization Framework for microelectronics Industry”Department of communication Engineering, national chiao Tung university, Taiwan International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     188 
  • 190. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 [2] Tang, W.chow, Y,many microstrip line Discontinuities on one General Field – Based circuitmodel, city university of Hon Kong, china University of waterloo, Canada.[3] Caver K, and Mink J,. Micro strip Antenna Technology, IEEE, Transactions on Antenna andpropagation, vol.29, No. 1, January 1981.[4] D.N. Schaubert, “Micro strip antennas, “ Electromagnetic, vil.12, pp.381-401, 1992.[5] G.W. Garvin, R.E.Munson, L.T. Ostwald and K.G.Schroeder,” Low pro file electricallysmall missile base mounted micro strip antenna,” in Dig int-syom... Antenna Propagation soc,urbana, IL, June 1975, pp. 224-247.[6] J.Q.Howell “Micro strip antennas” IEEE Trans Antenna propagation, vol. AP-23, No. 1,pp.. 90-93, Jan 1975.[7] I.R.J.Mailloux, J.Mcilvenna and N. Kernweis, “Micro strip array technology” IEEETrans. Antenna and propagation, vol.AP-29 No. 1, pp 25-38, Jan.1981.[8] H.D.Weinschel, “Progress report on development of micro strip cylindrical arrays forsounding rockets,” physic. And Sci. Lab, NEW Mexico state univ, LAS Cruces, 1973.[9] J.R. James and G.J. Wilson, “New design techniques for microstrip antenna array” inproc. 5th European Micro. Conf, Hamburg, Sept. 1975, pp. 102-106.[10] Balanis, Antenna theory.[11] R.D.Kanphade, D.G.Wakade and N.T.Markad “Micro strip patch antenna : computerAided Design Methology, International Journal of Electronics Communication Engineering,Rohini, New Delhi, Octomber 2011.[12] FDTD IE3D Reference Manual, Fremont : Zealand software Inc, 2006.[16]K. Dessouky & 1. Ho, Propagation Results from the Sat el 1 i t e- l a Experiment , KAT-XQuart er l y , JPL, No. 17, October 1988, pp7-12. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     189 
  • 191. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619 [17]J. P. McCeehan and A. Bateman, Phase-locked transparent tone-in-band TTIB: A newspectrum configuration particularly suited to the transmission of data over SSB mobile radionetworks, IEEE Trans on Conun~, Vol.COM-32, No.1, Jan. 1984, pp 81-87.[18]A. Kanso, Novel Signal Processing Techniques for Pilot-Based SSB Mobile Radio Systems,Ph.D Thesis, Dept. of Elec. Eng., Univ of Bath, Bath UK, 1985.[19]A. Bateman and D.M. Haines, Direct Conversion Transceiver for Compact Low-CostPortable Mobile Radio Terminals, This conference Record.[20]A. Baternan, R.J. Wilkinson and J.D.Marvi11, The Application of Digital Signal Processingto Transmitter Linearisation, IEEE Eurocon 88, Stockholm, Sweden, 13h-17th July 1988.[21]C.R. Green, A.A. Lane, R. Shulka and P.N. Tombs,GaAs MMICs for use in Phased Array Radar T/R Modules, IEE Colloquium on Electronically ScannedAntennas, 21 January 1988, London, UK.756[22]Advances in smart antenna system. Dr. D.G. Wakade and D.G. Rameshwer kawitkar SSGMcollege of Engineering shegaon 444203 . received on 19th Jan 2005 accepted on 26th June 2005.Journal of scientific and industrial research Vol.64, September 2005, PP 660- 665 International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     190 
  • 192. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619   DETERMINANTS OF GROWTH OF TOURISM INDUSTRY IN GOA: A STUDYDr. Achut Pednekar* ABSTRACTGoa is known as the beach country of India. As per the projection made by the consultants,around 1.6 million tourists are expected by the turnoff and with an expected average annualgrowth rate of 6.36 per cent, the total traffic in the horizon year i.e. 2021 would increase to 3.2million. The resultant growth in tourist traffic is infuse a heavy and steady to upgrade andaugment the present infrastructures, hence the study. A multiple regression coefficient has beenutilized to analyze the relationship between the arrival of tourists and the expenditure plan.Apart from this, the trends of tourist’s arrivals as well as foreign charter flights have beenconsidered and analyzed with the help of percentage change method. Implications of theresearch are that expenditure plan is not only the factors which are influencing the tourists inGoa. Government of Goa should introduce and enhance new tourism and existing activities i.e.adventure tourism, cultural heritage tourism, pilgrim tourism, business tourism, sports tourism,and education and medical tourism. The existing facilities are not sufficient and shouldchannelize way to identify infrastructure and other developmental needs for tourism.Keywords: Goa, Receipt, Capital, Expenditure Plan*D.M’s College, Goa International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     191 
  • 193. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  INTRODUCTIONThe World Tourism Organization (WTO) in its Tourism 2020 vision has estimated that therewould be about 1.0 billion total international tourists in all countries in the world in the year2010 and 1.6 billion in 2020 compared to 0.57 billion in 1995. According to WTO estimatesEurope will continue to remain the most popular tourist destination with about 0.7 billion touristsestimated for the year 2020. East Asia and Pacific region will surpass America by 2010 tobecome the second most visited destination. International tourists in South Asia is expected at0.2 billion in 2020 which is almost five times that of 1995 but still quite low compared to otherdestinations. India is expected to fuel 4.5 times growth in international tourist’s arrival, between1995 and 2020.Goa has attracted 1.2 million of tourist traffic in the year 1997. As per the projection made by theconsultants, around 1.6 million tourists are expected by the turnoff and with an expected averageannual growth rate of 6.36 per cent, the total traffic in the horizon year i.e. 2021 would increaseto 3.2 million. It is projected that in 2021 domestic tourists would be 2 times the present leveland foreign tourist would be 4 times the present level and overall about 2.5 times.(TourismMaster Plan : Goa 2011 Final Report February 2001)The resultant growth in tourist traffic is infuse a heavy and steady to upgrade and augment thepresent infrastructures. Therefore urgent efforts are required from the state to upgrade andaugment the present infrastructure stock to meet future requirement.The Government of Goa has declared Tourism as an Industry with effect from 01/04/2000. TheMaster Plan for tourism development upto 2011 A.D. has been prepared. The Tourism Policy ofthe State has also been framed. Since a large multitude of the people in Goa are economicallydependent on tourism and related activities a decisive promotional thrust and reworking of theappropriate tourism model have been identified as key elements in placing the potential of ourtouristic state on a higher growth orbit. Tourism sector has been accorded the status of industryentitling the hospitality sector to avail of benefits of concession available on water and powertariffs, relief in service tax, luxury tax on hotel rooms and sales tax on cooked foods as well asnon alcoholic beverages in restaurants. The tourism departmental has proposed some newprojects like development of the tourism jetty and parking lot at Panaji, Paryatan Bhavan at PattoPanaji, beach safety management system in the form of up gradation of access of tourist International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     192 
  • 194. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  destination in the state, development of eco-tourism project for state of goa, capacity buildingorganization of workshops/seminars/training programmes etc for improvement of tourismmanpower. The above infrastructure development projects have been processed for centralfinancial assistance to the tune of Rs. 7182.66 lakh with state component of Rs. 961.34 lakh.Since it is decided to utilize proposed land for golf course at betul for food and park auxiliary,town and country planning department has been requested to suggest suitable site for setting upof golf course in the state.Development of infrastructure facilities, beautification of important tourist destinations,improvement of roads in tourism circuit, appointment of more life guards and improvement ofdifferent safety measures have been continuing in order to improve services to the touristsvisiting the state. Department of tourism has already entrusted the work to a competentorganization “M/s Drishthi special Response Service, Pvt Ltd, Mumbai”.Special Tourist Security force named as Tourist Security Organisation is proposed to beformulated in order to provide additional protection and guidance to the tourists visiting the state.Goa Heritage Tourism Scheme has been formulated which is approved by the Government and isbeing implemented. The objective of this scheme is to restore and maintain ancestral houses ofgoa by giving financial assistance with subsidy to the interested parties. In order to promote eco-tourism, the Forest Department has been idenfied as nodal agency.TOURISM MARKETING AND PROMOTIONTourism has become a highly competitive industry. The department of tourism has strengthenedits marketing strategy by envisaging various publicity measures viz organizing road shows,advertising through print and electronic media, participating in various travels marts. Thedepartment of tourism participated in travel related overseas events like, road show at Durbanand cape town in south Africa, Leisure-08 at Moscow, WTM-2008 at London and domesticevents in India, like TTF at Jamshedpur, TTF at Hyderabad, TT F at Ahmadabad, ITM at Jaipur,Rajasthan, TTE at Chennai, Discovery India. The Department also organized Explore theIncredible State in Mumbai in coordination with Goa Tourism Corporation, Goa. Some festivalsare organized at state level to attract the domestic as well as foreign tourists such as carnival, International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     193 
  • 195. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  Shigmotsav, Saraswat food festival, wine festival etc. Fund for organizing these festivals areprovided by Tourism Department in order to promote tourism.REVIEW OF LITERATUREThe Consulting Engineering Services (I) Ltd. New Delhi in his Tourism Master Plan: Goa –2011 Final Report February 2001 has carefully studied views expressed by the Goa Chamberof Commerce & Industry. GCCI have stressed on creation of facilities in order to sustain growthof tourism in Goa.Abhinav K. Raina Director, Centre for Tourists and Heritage Research Dayanand College,Ajmer in his presentation in the 3rd Bi-annual referred international journal held on 23/01/2011topic entitle “Development of Health Tourism services – A Study” stated that there is a needfor a training in the field of medical facilities in order to further boost tourism industry.Tourism in Goa: A perspective (Collection of Domestic Tourism Statistics for the State ofGoa) in their survey report highlighted that almost 42.05% of the domestic tourist and 43.2% offoreign tourist rated local transport services as good, with 12.1% and 10.8% respectively, ratingit as poor. 14.32% of domestic and 12.9% foreign tourists, reported the accommodation units asexcellent while 10.57% of domestic and 6.7% foreign tourists rated it as poor. 36.79% foreigntourists and 35.1% domestic tourists rated quality of entertainment facilities as excellent. Almost40.71% of domestic tourists and 42.1% foreign tourists rated the tourist attractions in Goa as“Very Good”. Almost 61.3% of domestic tourists and 59.8% of foreign tourists rated shoppingfacilities as adequate.RESEARCH OBJECTIVES1. To study and analysis of trends of tourist arrivals in goa.2. To study and analysis of trends of arrivals of foreign charter flights.3. To ascertain the relationship between arrival of tourist with expenditure plan.HypothesisThere is a significant relationship between arrivals of tourist with revenue and capital outlay ontourism. (Expenditure plan)RESEARCH METHODOLOGY International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     194 
  • 196. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  The study is based on secondary data conducted in the state of goa. Data is collected from Govtof Goa Department of tourism. Secondary data also has been collected by referring to variousjournals, published and unpublished texts, books, reports, newspapers and net.Data analysis was carried out by using the statistical program packages SPSS. The otherstatistical techniques used for data analysis is percentage change method.In order to know the aforementioned hypothesis, expenditure plan and arrivals of tourists fromthe period 2000-01 to 2010-11 has been considered.I TREND ANALYSIS OF TOURIST ARRIVALS IN GOAGrowth of tourism in Goa has been phenomenal. Growth of tourism has led to economic growth,improved infrastructure and quality of life. Construction boom has led to increased urbanization.Changes in pattern of livelihood and socio cultural changes have also occurred. People fromdifferent parts of the country has come and settled in Goa in search of livelihood. There is also alarge expatriate community who come to enjoy the beauty of the land of sun and sea. Rapidchanges in economy, society and culture have led to greater inclination among the people to earnquick money along with increased Westernization and growth in consumerism.Eco Tourism has been promoted to develop the Hinterland, so that people living in these areascan reap the benefits of tourism. Express ways are envisaged in an effort to shorten distancesbetween either extremities of the State, and these expressways will be connected to the goldenquadrilateral. Beach-life safety programme implemented successfully is probably the first of itskind project in the country. Table – I Trends showing number of tourist arrivals in goa Year Domestic Foreign Total % Change 1985 682545 92667 775212 - 1986 736548 97533 834081 7.6 1987 766846 94602 861448 3.3 1988 761859 93076 854935 -0.7 1989 771013 91430 862443 0.9 1990 776993 104330 881323 2.2 1991 756786 78281 835067 -5.6 International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     195 
  • 197. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619   1992 774568 121442 896010 7.3 1993 798576 170658 969234 8.2 1994 849404 210191 1059595 9.3 1995 878487 229218 1107705 4.5 1996 888914 237216 1126130 1.7 1997 928925 261673 1190598 5.7 1998 953212 275047 1228259 3.2 1999 960114 284298 1244412 1.3 2000 976804 291709 1268513 1.9 2001 1120242 260071 1380313 8.8 2002 1325296 271645 1596941 15.7 2003 1725140 314357 2039497 27 .7 2004 2085729 363230 2448959 20.1 2005 1965343 336803 2302146 -6.0 2006 2098654 380414 2479068 7.7 2007 2208986 388457 2597443 4.8 2008 2020416 351123 2371539 -8.7 2009 2127063 376640 2503703 5.5Economic survey 2008-09 International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     196 
  • 198. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  Figure – I Chart showing number of tourist arrivals in Goa 3000000 2500000 2000000 1500000 DOMESTIC FOREIGN 1000000 TOTAL % CHANGE 500000 0 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 ‐500000The share of domestic overnight visitors was 84.50% & foreign overnight visitors were 15.50%in the total overnight visitors in the state. Total domestic tourist estimated was 18.99 lakh, International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     197 
  • 199. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  foreign tourists 3.48 lakh, and total tourists 22.47 lakh. Estimated day tourists are 2.42 lakh andtotal tourists & day tourists combined is estimated to 24.89 lakh.During the years from 1990 to 1998, the share of foreign tourists as share of total tourists visitinggoa has considerably increased from 11.83 per cent in 1990 to 22.39 per cent in 1998. This issignificantly higher than the normal trend of about 3.37 per cent (1997) of foreign touristsobserved in India. In between the year 1991 has seen a drastic fall in the arrival of foreigntourists which may be attributed to unstable socio-political situation in the country. As per theTourism Department, in the year 2008, 2020416 domestic tourists’ and 351123 foreign tourists,whereas, in 2009, 2127063 domestic tourists and 376640 foreign visited Goa. As per EconomicSurvey released by the Government, contribution of tourism is 33 percent of the total GDP.The growth of tourist in Goa is due various reasons. Place of tourist interest are so numerous andof varied nature that it is not easy to describe these places comprehensively. In general the touristspots of Goa are counted more like, Shrines, Forts, places of historical importance, springs, lakesand birds, sanctuaries, religious centers, science spots, sea beaches, summer resorts, waterfallsand wild lives etc. Goa has been one of the major tourist destinations in India for foreign visitors.Its share is around 11 per cent of the total foreigners visiting the country.II TREND ANALYSIS OF ARRIVALS OF FOREIGN CHARTERFLIGHTS Table –II Trends showing arrivals by foreign charter flights Year Number of flights Passengers 2000-01 419 116992 2001-02 279 76410 2002-03 384 94350 2003-04 523 126255 2004-05 690 158993 2005-06 719 180310 2006-07 720 169836 2007-08 710 175951 2008-09 615 145428 International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     198 
  • 200. IJRIME E     Volum me1Issue5  ISSN‐ ‐2249‐ 16 619   Econom survey 2008-09 micFigure II Chart sho I owing arriva by foreig charter f als gn flights 200000 180000 160000 140000 120000 100000 80000 NUMBER OF FLIGHTS 60000 PASSENG GERS 40000 20000 0On accou of aggre unt essive media campaign undertaken by the Depa a artment, the actual tour in e ristflow to t state has reached to more than 2.60 million marks for the calenda year 2007 To the s o n r ar 7.cater to i increased tou urist traffic i flow, the h in hotel bed ca apacity has g gone up to 42 2145 for the year e2008.During t tourist seaso 2007-200 710 char flights h on 08, rter have brough in 175951 tourists an 48 ht 1 ndcondor F Flights has brought in 10043 tourist During t current s b ts. the season 2008-09, 615 Ch harterFlights in ncluding Con ndor Flights has brought in 145428 foreign touri t ists’ to the S State.In spite o the adver effect of terrorist att of rse f tack in Mum mbai and int ternational m market reces ssion,there wa good resp as ponse from tourists vis siting Goa. Arrivals of foreign tou f urists as we as elldomestic tourists rea c ached to 388 8457 and 220 08986 respectively, for t year 200 and durin the the 07 ngyear 200 351123 foreign and 2020416 do 08, f omestic tou urist visited the state. The state rec ceives Inter rnational Jour rnal of Resear rch in IT, Man nagement and d Engineering g                                                             www.gjmr.org  199 
  • 201. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  tourists from more than 25 different countries including UK, Germany, Sweden, Switzerland,Finland, Russia, etc. About 39% of the tourists came from UK followed by Russia, Germany,Finland and France.III THE RELATIONSHIP BETWEEN ARRIVAL OF TOURIST WITHEXPENDITURE PLAN Data was tabulated in Microsoft Excel Sheet and the data edited, coded and verified for validity.The data was analyzed using statistical package for social sciences software.Table III showing the arrival of tourists and expenditure plan for the year 2000-01 to 2010-11year Tourist(y) Revenue(x1) Capital(x2)2000-2001 1268513 2.2 42001-2002 1380313 5.3 72002-2003 1596941 13 62003-2004 2039497 7 0.00332004-2005 2448959 4.3 12005-2006 23021146 24 22006-2007 2479068 7.23 12007-2008 2597443 5 22008-2009 2020416 0.26 02009-2010 2127063 10 242010-2011 21123000 7.2 8Source: Department of tourism, Govt. of Goa.Note: Compilation of secondary data International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     200 
  • 202. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619   Table IV: Pearson Correlations between tourist and capital tourist capital Variables tourist Pearson 1 -0.158 Correlation Sig. (2-tailed) 0.644 N 11 11 capital Pearson -0.158 1 Correlation Sig. (2-tailed) 0.644 N 11 11The result of Table I shows that there is (- 0.158) negative insignificant correlation between thetourist and capital. International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     201 
  • 203. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619   Table V: Pearson Correlations between capital and revenue capital revenue Variables capital Pearson 1 0.144 Correlation Sig. (2-tailed) 0.673 N 11 11 revenue Pearson 0.144 1 Correlation Sig. (2-tailed) 0.673 N 11 11The result of Table II shows that there is (+0.144) positive insignificant correlation between thecapital and revenue. Table VI: Pearson Correlations between revenue and tourist revenue Tourist variables International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     202 
  • 204. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619   revenue Pearson 1 0.174 Correlation Sig. (2-tailed) 0.609 N 11 11 tourist Pearson 0.174 1 Correlation Sig. (2-tailed) 0.609 N 11 11 The result of Table III shows that there is (+0.174) positive insignificant correlation between thetourist and revenue. Table VII: Model Summary of the Regression of arrival of tourist and capital and revenue Adjusted R Std. Error of the R R Square Square Estimate Model 1 0.254(a) 0.064 -0.170 481324.74843 1. Predictors: (Constant), revenue, capital Table IX Multiple Regression Analysis of Expenditure plan Coefficient (a) Unstandardized Standardized Coefficients Coefficients Std. Variables B Error Beta t Sig. (Constant) 1986566.0 249673. 7.957 0.000 International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     203 
  • 205. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619   16 080 capital - 22294.2 -0.186 -0.540 0.604 12028.573 41 revenue 24015.3 13951.539 0.201 0.581 0.577 97 Dependent Variable: touristAs seen from the table, revenue and capital have determined only 06 percent of the variance oftourist. In the regression model both are insignicant, capital and revenue are not the only factorswhich are influencing the tourists in Goa. There are other factors responsible for which the studyhas to be done.CONCLUSIONImplications of the research are that capital and revenue are not the only factors which areinfluencing the tourists in Goa. The various factors that have contributed to this rise in domestictourism in the country are: increased disposable income of the middle class; increasedurbanization and stress of living in cities and towns; increased ownership of cars, which ismaking domestic tourism more attractive; especially among the upper-middle and middleclasses; improved employment benefits, such as the leave travel concession; development ofinexpensive mass transport and improved connections to various places of tourist interest;increased number of cheap accommodations and resorts, greater advertising targeted at domestictourists both by the central and the state governments, as well as the tourist industry, andincreasing of time-sharing in holiday spent, among the middle class.Government of Goa should introduce and enhance new tourism and existing activities i.e.adventure tourism, cultural heritage tourism, pilgrim tourism, business tourism, sports tourism,and education and health tourism. The existing facilities are not sufficient and should channelizeway to identify infrastructure and other development needs for tourism.REFERENCESBooks International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     204 
  • 206. IJRIME     Volume1Issue5   ISSN‐2249‐ 1619  Batra G.S.and A.S Chawla (1995) Tourism Management: A Global Perspective, Deep and DeepPublications, New Delhi.Chawla R. (2005) Ecotourism Planning and Management, Sonali Publications, New Delhi.Chawla R. (2006) Responsible Tourism, Sonali Publications, New Delhi.Chawla R. (2006) Agri- Tourism, Sonali Publications, New Delhi.MagazinesDe Costa I. (2005) Need for a New Approach, Goa Today.De Souza R. (2006) Boosting State Tourism, Goa Today.De Costa I. (2005) Need for a New Approach, Goa Today.ReportTourist Statistics 2006-07, Department Of Tourism, GoaTourism Master Plan: Goa – 2011 Final Report February 2001Websites log on 18-07-2011http://www.hindu.comhttp://www.goa-tourism.comwww.gdrc.orgwww.ecoindia.com/sustainable-tourismwww.du.ac.in/coursematerial/ba/tourism/Lesson21-23banglanatak dot com research report –Goa.pdf (application/pdfobject)Websites log on 25-07-2011http://tourism.visitcalifornia.com/Research/www.mcos.com/Tourism_Industry.htmwww.mcos.com/Healthcare_Industry.htmhttp://goacom.blogspot.com/2009/01/goa-beach-strip-of-paradise.html International Journal of Research in IT, Management and Engineering                                                             www.gjmr.org     205 

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