June 2022 - Top 10 Download Article in IJCI.pdf

June 2022: Top 10 Downloaded
Articles in Cybernetics & Informatics
International Journal on Cybernetics &
Informatics (IJCI)
https://airccse.org/journal/ijci/index.html
ISSN: 2277 - 548X (Online); 2320 - 8430 (Print)

TALENT MANAGEMENT IN EDUCATION SECTOR
Ms Shweta Tyagi1
, Prof.Dr. Gurinder Singh2
, Ms.TriptiAggarwal3
Amity International Business School,Amity University, Uttar Pradesh
ABSTRACT:
Attract, develop and retain employees by assured pipeline of knowledgeable and qualifying people
isimportant for the success of the institutions which is known as talent management. The main
issues facing by the educational institutes is shortage of competent and qualified faculties. It has
resulted in institutions focusing on how to retain the talent and how to develop
them. Where institutions are running at risk of talent crisis talent retention is the not only the choice
of the managers but also the need for the institutions.The important factors which contributes to
faculty retention and recruitment are benefits, supportive environments, spouse employment
opportunities, start-up and resources and salaries. This research
paper provides few strategies which institutions can adopt for attracting and retaining talent which i
s bestavailable for them.
KEYWORDS
Talent Retention, Talent Acquisition and Talent Development, Education Sector, Strategies.
Full Text: https://aircconline.com/ijci/V6N2/6217ijci06.pdf
Volume Url: https://airccse.org/journal/ijci/Current2017.html

REFERENCES
[1] Sandberg, J. (2000). “Understanding human competence at work: An interpretative approach”
,The Academy of Management Journal
[2] Jyotsnarani, K. (2007), "Attainment of Excellence through Higher Education" .Orrisa Review,
Feburary- March 2007
[3] Chartered Institute of Personnel and Development (CIPD) (2007). "Talent: Strategy,
management and me measurement," at Talent Management Conference on 19 June 2007. Research
Insight,CIPD
[4] Devine, M. and Powell, M. (2008). "Talent Management in the Public Sector," 360°
TheAshridge Journal Autumn,
[5] Tripathi, Pooja, Ranjan, Jayanthi and Pandeya, Tarun (2010); " PAKS: A Competency based
model for an Academic Institutions.," International Journal of Innovation, Management and
Technology vol. 1, no. 2,
[6] C.Sonia, Dr.JayashreeKrishnan(2015); “ TALENT MANAGEMENT IN HIGHER
EDUCATION SECTOR”, IRACST- International Journal of Research in Management & Technology
(IJRMT), Vol. 5, No4 International Journal on Cybernetics & Informatics (IJCI) Vol. 6, No. 1/2,
April 2017 52
[7] NORMAN RUDHUMBU (2014), “Implementation of Talent Management Strategies in Higher
Education: Evidence from Botswana”, International Journal of Higher Education Management
(IJHEM) Vol. 1 Number
[8] Babcock, P. (2006). Succession planning: Tie talent needs to current, future organizational
direction
[9] Beechler, S. & Woodward, I.C.(2009). The Global War of Talent. Journal of International
Management, 15: 273–285
[10] Bhatnagar, J., (2007). Talent management strategy of employee engagement in Indian ITES
employees: Key to retention. Employee Relations
[11] Heidke, J.D. 2006.Benefits of effective Talent Management include. ASTD
Presentation.Retrieved from
www.fasset.org.za/downloads/.../talent_man_sdf_long_article_website.pdf [Accessed 7th January
2014].
[12] Lavania, D; Sharma, H & Gupta, N. (2011).Recruitment and Retention: A Key for Managing
talent in Higher. International Journal of Enterprise Computing and Business Systems
[13] Shaffer, J. (2008). Gen Y talent: How to attract and retain the young and the restless (White
paper). Redwood Shores, CA: Saba
[14] India-Higher Education Sector Report(2012) by PwC Brand and Communications , India
[15] Michaels E., Handfield-Jones H., & Axelrod B.(2001), The War for Talent, McKinsey
Report2001.
AUTHORS
Ms Shweta Tyagi is a faculty cum senior manager with Amity University for the
last 6 years. Before that she has worked with the biggest clothing giant Zara India.
She has done enterprise management from DMS, IIT Delhi and have written several
research papers in scopus indexed journals. She is net qualified & have completed
her graduation from Delhi University.

DESIGN AND ANALYSIS OF DUMP BODY ON THREE WHEELED AUTO VEHICLE
1
K.Radhakrishna, 2
S. Srinivasa Rao and 3
B.Sudhakara Rao
1
Assistant professor, Department of Mechanical engineering, KLUniversity, Vijayawada, AP
2
professor, Department of Mechanical engineering, KLUniversity, Vijayawada, AP
3
Assistant professor, Department of Mechanical engineering, KLUniversity, Vijayawada, AP
ABSTRACT
In developed areas, garbage is increasing day by day to reduce the garbage, Indian automobile
industries are manufacturing different types of truck bodies. These truck bodies having large fuel
consumption due to the heavy weight of truck and bulk in size. It is difficult to travel narrow streets
and easily fail due to corrosion while contact with wet garbage and also manual interference is
needed for loading and unloading of garbage. Three wheeled auto rickshaw is best suited to reduce
this type of problem. The three wheeled auto rickshaw is a small vehicle which is ideal for short,
narrow roads as well as highway hauls for small bulky superior loads. Dump body on three
wheeled auto rickshaw is mainly desirable to pick up the smaller quantities of wastage and hand it
over to the land filler and other recycling or other treatment facilities. The main purpose of this tree
wheeled dump body is to reduce the manpower. In the present work an attempt is made to design
three wheeled dump body with a capacity of 750 kg payload. Generally the under frame of the
body is assembled first, then the base sheet side walls front and rear sheet with stiffeners are
assembled in order to complete the assembly and it’s done by using PRO/E 4.0 CAD software. The
designed three wheeled dump body has been analyzed for stress using the finite technique in
addition to payload weight of garbage as being considered to reduce fuel consumption and cost of
manufacturing two types of materials are used one is the aluminum another one is mild steel which
used supporting component in dump body. After analyzing best body is found.
KEYWORDS
Deformation, Stress intensity, Von-Misses stresses, payload.
Full Text: http://airccse.org/journal/ijci/papers/4215ijci06.pdf
Volume URL: https://airccse.org/journal/ijci/Current2015.html

REFERENCES
[1] Johaan Kraus, “Garbage collection vehicle”, Grant, March 31, 1971, publication number: US3598262 A.
[2] Ali. R, J. L. Hedges, B. Mills, (1986), “Finite element techniques are applied to determine the static
properties of and automobile body”, , I. M. E. , Proc., Vol. 185, 44/71.
[3] Kiyoshi Miki,(2000) “The outline of a theoretical analysis of bending and torsional vibrations of
bodies”, , Paper No: 690272.
[4] Curtis. F. Vail, (1993) “F. E. Methods for modeling automatic structure for their static characteristics”,
Paper No: 740005.
[5] Garrett. T.K (1 Dec. 2002), “The Motor Vehicle”, Society of Automotive Engineers,U.S.; 13th Revised
edition, Paper No: 1214.
[6] Hutton, David, V., (2004),”Fundamental of Finite Element Analysis”, Mc Graw Hill, New York.
[7] Mauritz Coetzee, (2004) “An innovative aluminum design gives a truck-body manufacturer the
competitive edge in the worldwide construction industry”.
[8] Robert. J. Melton, (1999) ‘Efforts to predict linear static dynamic and non-linear behavior of components
and structural systems’, , Paper No: 740319.
[9] Willy Peterson, (Ford Motor Co.,)(1999), ‘The finite element method for automotive body structural
analysis’, Paper No: 740319.
[10] R.S Khurmi and J.K Guptha, (1984) “Text books of machine design”. Eurasia Publishing, 1067 pages

COMPARATIVE ANALYSIS OF RETAIL SECTOR OF INDIA AND AUSTRALIA
Ms. Shweta Tyagi, prof. Dr. Gurinder Singh and Ms. Tripti Agarwal
Amity International Business School, Amity University, Noida, India
ABSTRACT
The economy of Australia and India is booming in the retail sector. All major business decisions
affecting the world across are taken and dictated by this economy. The total number of retail
businesses are around 140 000 in Australia which accounts for nearly 4.1% GDP and employment
of 10.7%. the retail industry contribution from india is more then 13% of GDP in 2011.The retail
industry has skilled quotes of labor productiveness increase during the last two many years
comparable, on average, to that of the rest of the Australian economic system.
KEYWORDS
Retail, India and Australia, Departmental Stores, Marketplace

REFERENCES
[1] Access Economics, Household E-commerce Activity and Trends in Australia, prepared for the
Department of Broadband, Communications and the Digital Economy (November 2010).
2] Apostolou, N., ‘Australia’s Retail Revolution’, Charter, vol. 82, no. 5 (Sydney 2011), pp. 1-8. Australian
Centre for Retail Studies, Australian Consumer Trends: ACRS Secondary Research Report 2010, (Monash
University, 2010).
[3] Australian Centre for Retail Studies, Retail Insights, no. 154 (February 2012). Australian Centre for
Retail Studies, Retail Trends: ABS Retail Trade Data for January 2012 (Monash University, 2012).
[4] Australian Communications and Media Authority, Australia in the Digital Economy: Consumer
Engagement in E-Commerce (November 2010).
[5] Australian Communications and Media Authority, Australia in the Digital Economy: the Shift to the
Online Environment (November 2010).
[6] Swapna, Pradhan. (2007). Retailing Management, Text & Cases (2nd ed.). New Delhi: Tata McGraw
Hill Publishing Company Limited. International Journal on Cybernetics & Informatics (IJCI) Vol. 6, No.
1/2, April 2017 76
[7] Sumedha, Kalia & Rishi, Kalia. (2011, July). Subhiksha: a battle for survival. Indian Journal of
Marketing.
[8] Dutta, K. P. (2011, July). Agricultural rural marketing in India. Indian Journal of Marketing,
[9] Hilesh, D. Vyas. (2011). Consumer purchase of consumer durables: a factorial study. Journal of
Marketing and Communication.
[10] Deepika, Jhamb & Ravi, Kiran. (2011). Organized retail in India - drivers facilitator and swot analysis.
Asian Journal of Management Research.
[11] Ihsan & Metin. (2007). Using the analytic network process (ANP) in a SWOT analysis – A case study
for a textile firm. Information Sciences.
[12]Australian Centre for Retail Studies, Retail Insights, no. 154 (February 2012). Australian Centre for
Retail Studies, Retail Trends: ABS Retail Trade Data for January 2012 (Monash University, 2012).
[13]Australian Communications and Media Authority, Australia in the Digital Economy: Consumer
Engagement in E-Commerce (November 2010).
[14] www.economicindicators.gov/
[15] www.economywatch.com/business-and-economy/us-retail-industry.html -
[16] www.census.gov/ -
[17] business.mapsofindia.com/india-retail-industry/
18] http://www.indiaretailforum.in/presentations/4-retail_story.pdf
[19] http://www.euromonitor.com/retailing-in-australia/report
[20]http://www.indiaretailing.com/2014/01/14/retail/indian-retail-analysing-the-swot-matrix/
AUTHORS
Ms Shweta Tyagi is a faculty cum senior manager with Amity University for the
last 6 years. Before that she has worked with the biggest clothing giant Zara India.
She has done enterprise management from DMS, IIT Delhi and has written several
research papers in scopus indexed journals. She is net qualified & have completed
her graduation from Delhi University.

STANDARDISATION AND CLASSIFICATION OF ALERTS GENERATED BY
INTRUSION DETECTION SYSTEMS
Athira A B1
and Vinod Pathari2
1
Department of Computer Engineering ,National Institute Of Technology Calicut, India
2
Department of Computer Engineering ,National Institute Of Technology Calicut, India
ABSTRACT
Intrusion detection systems are most popular de-fence mechanisms used to provide security to IT
infrastructures. Organisation need best performance, so it uses multiple IDSs from different
vendors. Different vendors are using different formats and protocols. Difficulty imposed by this is
the generation of several false alarms. Major part of this work concentrates on the collection of
alerts from different intrusion detection systems to represent them in IDMEF(Intrusion Detection
Message Exchange Format) format. Alerts were collected from intrusion detection systems like
snort, ossec, suricata etc. Later classification is attempted using machine learning technique, which
helps to mitigate generation of false positives.
KEYWORDS
Intrusion Detection Systems, IDMEF, Snort, Suricata, ossec& WEKA

REFERENCES
[1] DARPAdataset, http://www.ll.mit.edu/mission/communications/cyber/CSTcorpora/ideval/data/.
Accessed on 03-December-2014.
[2] Ossec, http://www.ossec.net//. Accessed on 03-December-2014.
[3] Snort, https://www.snort.org/. Accessed on 03-December-2014.
[4] Suricata, https://redmine.openinfosecfoundation.org/projects/suricata/ wiki/Suricatayaml. Accessed on 2-
February-2015.
[5] HadiBahrbegi Mir Kamal Mirnia Mehdi BahrbegiElnazSafarzadeh Amir AzimiAlastiAhrabi, Ahmad
HabibizadNavin and Ali Ebrahimi, "A New System for Clustering and Classification of Intrusion Detection
System Alerts Using Self-Organizing Maps", International Journal of Computer Science and Security, 4,
2004.
[6] Neethu B, "Classification of Intrusion Detection Dataset using machine learning Approaches",
International Journal of Electronics and Com-puter Science Engineering, 1956.
[7] ChampaDey, "Reducing ids false positives using Incremental Stream Clustering (isc) Algorithm", Dept
of Computer and Systems Sci-ences, Royal Institute of Technology, Sweden, page March, JULY-
SEPTEMBER 2009.
[8] Debar H and Wespi A, "Aggregration and Correlation of Intrusion-Detection Alerts", In Proceedings of
the 4th International Symposium on Recent Advances in Intrusion detection (RAID), Springer Verlang,
California, USA, pages 85–103, 2001.
[9] KleberStroeh, Edmundo Roberto Mauro Madeira, and Siome Klein Goldenstein, "An approach to the
correlation of security events based on machine learning techniques", Journal of Internet Services and
Applications, 2013.
[10] SebastiaanTesink, "Improving intrusion detection systems through machine learning", ILK Research
Group,Technical Report Series no. 07-02, Tilburg University, page March, JULYSEPTEMBER 2007.
[11] FredrikValeur, Giovanni Vigna, and Christopher Krue, "Modeling In-trusion Alerts using idmef", IEEE
TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, 1(3), JULYSEPTEMBER 2004.
Authors
Athira A B- She received the B.Tech. Degree in computer science and engineering
from University of Calicut, Kerala, India, in 2012, and M.Tech.in computer
science and engineering (Information Security) from the National Institute of
Technology (NIT) Calicut, Kerala, India in 2015.
VinodPathari- He is working as a full time faculty in the Computer Science and
Engineering Department of NIT Calicut, Kerala, India. In addition to information
security related topics he is also interested in teaching functional programming and
software engineering.

A SURVEY OF THE STATE OF THE ART IN ZIGBEE
Jobina Mary Varghese1
,Nibi K V2
,Vijo T Varghese3
and Sethuraman Rao
Amrita Center for Wireless Networks and Applications, Amrita Vishwa Vidyapeetham
Kollam, India
ABSTRACT
ZigBee is one of the most widely used wireless communication technologies. ZigBee is being
widely used for sensor communications and many other research fields. Why consider ZigBee?
Because it is cheap and has better compatibility when compared to other communication
technologies. We have given a detailed description on comparison between all the available
technologies. In this paper, we have discussed some basic concepts about ZigBee and its security
aspects in networking. We have also listed out the major manufacturers who are into the production
of the transceivers for ZigBee.
KEYWORDS
ZigBee, ZigBeePRO, Protocol stack, Security, Physical layer, Application and network layer
Full Text: https://airccse.org/journal/ijci/papers/4215ijci14.pdf

[1] Trodhanl, “Introduction to Zigbee,” Atmel Coorporration ,2006.
[2] Aamir Shaikh and Siraj Pathan, “Research on wireless sensor network Technology” , International
Journal of Information and Education Technology, Vol. 2, No. 5, October 2012. International Journal on
Cybernetics & Informatics (IJCI) Vol. 4, No. 2, April 2015 155
[3] Anneleen Van Nieuwenhuyse, Mario Alves and Anis koubaa, “Technical report on the use of the
Zigbeeprotocol for wireless sensor networks,” Technical Report HURRAY-TR-060601, 2006.
[4] Silabs,wireless ZigBee,http://www.silabs.com/products/wireless/zigbee/Pages/zigbee.aspx
[5] ZigBee Alliance, ZigBee remote control http://zigbee.org/zigbee-
fordevelopers/applicationstandards/zigbeeremotecontrol/
[6] ZigBee Alliance, smart energy http://zigbee.org/zigbee-
fordevelopers/applicationstandards/zigbeesmartenergy/
[7] ZigBee Alliance, smart energy profile 2 http://zigbee.org/zigbee-
fordevelopers/applicationstandards/zigbeesmartenergyprofile2/
[8] ZigBee Alliance, ZigBee Telecom service http://zigbee.org/zigbee-
fordevelopers/applicationstandards/zigbee-telecom-services/
[9] ZigBee Alliance, ZigBee Network devices http://zigbee.org/zigbee-
fordevelopers/applicationstandards/zigbee-telecom-services/
[10] ZigBee Alliance, ZigBee Ip Specification Zigbee.org/specification/ZigBeeIP/overview.as
[11] ZigBee Alliance, ZigBee RF4CE ,Zigbee.org
[12] ZigBee Alliance, Specification http://old.zigbee.org/Specifications.aspx
[13] Mohini Reddy,Vidya sawant, WSN based parameter monitoring and control system for DC
motor,international journal of innovative technology and exploring engineering,Feb 2014.
[14] Prof. Pravin R.Lakhe,Wireless sensor network using ZigBee, International Journal of Engineering
Research and Applications.
[15] http://www.embedded.com/design/connectivity/4419558/Zigbee-s-new-IP-specification-for-IPv6-
6LoPAN-wireless-network-designs.
[16] https://docs.zigbee.org/zigbee-docs/dcn/12/docs-12-0629-01-0mwg-zigbee-rf4ce-a-quiet-revolutionis-
underway-webinar-slides.pdf
[17] http://www.embedded.com/design/connectivity/4419558/Zigbee-s-new-IP-specification-for-IPv6-
6LoPAN-wireless-network-designs
[18] Y.Srinivas and K.Ragahava Rao , Landslide Warning System Using ZigbeeAnd GPS, IOSR Journal of
Engineering (IOSRJEN)
AUTHORS
Jobina Mary Varghese received BTech degree in Electronics and Communication from
Marian Engineering College, Kerala, India in July 20 13.She is currently pursuing
MTech in Wireless Networks and Applications from Amrita University, Kollam,
Kerala
Nibi K V received BTech degree in Electronics and Communication from Matha
College of Technology, Kerala, India in July 2012. She is currently pursuing MTech in
Wireless Networks and Applications from Amrita University, Kerala, India.

Vijo T Varghese received B.Tech degree in Electronics and Communication from
KNS Institute of Technology, Bangalore, India in July 2012. He is currently pursuing
his M.Tech in Wireless Networks and Applications from Amrita University, Kerala,
India.
Prof. Sethura man Rao is an associate professor at Amrita Center for Wireless
Networks and Applications, Amrita University, Kollam, Kerala, India. He holds a
Masters degree in Computer Science and a Bachelor's degree in Mechanical
Engineering from IIT Madras, India. He has over 20 years of international
experience in the networking industry having held technical and management
positions at Juniper Networks, Alcatel-Lucent and a few start-ups. His areas of
interest include wired and wireless LANs, wireless security, software engineering and network
management.

APPLICATION OF CLASSICAL ENCRYPTION TECHNIQUES FOR SECURING
DATA- A THREADED APPROACH
Raghu M E1
and Ravishankar K C2
1Department of CSE, Government Engineering College, Hassan, Karnataka, India,
2Department of CSE, Government Engineering College, Hassan, Karnataka, India,
ABSTRACT
The process of protecting information by transforming (encrypting) it into an unreadable format is called
cryptography. Only those who possess secret key can decipher (decrypt) the message into plain text.
Encrypted messages can sometimes be broken by cryptanalysis, also called code breaking, so there is a need
for strong and fast cryptographic methods for securing the data from attackers. Although modern
cryptography techniques are virtually unbreakable, sometimes they also tend to attack.
As the Internet, big data, cloud data storage and other forms of electronic communication become more
prevalent, electronic security is becoming increasingly important. Cryptography is used to protect e-mail
messages, credit card information, corporate data, cloud data and big data so on... So there is a need for best
and fast cryptographic methods for protecting the data. In this paper a method is proposed to protect the data
in faster way by using classical cryptography. The encryption and decryption are done in parallel using
threads with the help of underlying hardware. The time taken by sequential and parallel method is analysed.
KEYWORDS
Cloud, Data, Cryptography, Parallel cryptography, Threads.
Full Text: https://airccse.org/journal/ijci/papers/4215ijci12.pdf

REFERENCES
[1] Karthikeyan .S, Sairamn, Manikandan .G, Sivaguru J, “A Parallel Approach for Improving Data
Security”, Journal of Theoretical and Applied Information Technology , Vol. 39 No.2, 15 May 2012, p . no
119-125.
[2] Osama Khalifa [2] “ The performance of cryptographic algorithms in the age of Parallel computing”,
M.sc thesis, August-2011, Heriot Watt University School Of Mathematical and Computer Science.
[3] Vinodh Gopal , Jim Guilford, Wajdi Feghali, “Cryptographic Performance on the 2nd Generation Intel®
Core™ processor family”, white paper - 2011.
[4] H. Naveen, M. Ramesh [4] “Parallel AES Encryption Engines for Many-Core Processor Arrays”,
International Journal of Innovative Research in Computer and Communication Engineering, (An ISO 3297:
2007 Certified Organization) Vol.2, Special Issue 1, March 2014
[5] M. Tahghighi, S. Turaev, R. Mahmod, A. Jafaar and M. Md. Said, "The Cryptanalysis and Extension of
the Generalized Golden Cryptography", IEEE conference on open system, September 2011, Lankawi,
Malaysia. International Journal on Cybernetics & Informatics (IJCI) Vol. 4, No. 2, April 2015 132
[6] Joseph Raphael, Dr. V. Sundaram, "Secured Communication through Fibonacci Numbers and Unicode
Symbols", International Journal of Scientific & Engineering Research, Volume 3, Issue 4, April-2012, ISSN
2229-5518.
[7] Salem Sherif Elfard. “University Bulletin – ISSUE “ No.- 15 – Vol . 2- 2013
[8] K C Ravishankar and M G Venkateshmurthy, “ Pixel Compaction and Encryption for Secure Image
Transmission” , National Conference on Intelligent Data Analytics and Pattern Discovery -2007, BIT
Sathyamangalam, March 15-16, 2007.
AUTHORS
Mr. Raghu M E has got B.E. from UBDTCE, Davangere in 1998, M.Tech from JNNCE,
Shivamogga, in 2003. He served at BCE from 2000-2003 and in JNNCE, Shimoga, Karnataka
India from 2003-2010. He is currently serving as Associate Professor of CSE in GEC, Hassan.
His areas of interest include Cryptography, Compiler Designs, Image Processing and
Computer Graphics. He has 3 International and 3 national publications to his credit.
K. C. Ravishankar has got his B.E. from MCE, Hassan in 1990, M.Tech from IIT, Delhi in
1998 and Ph.D. from Visvesvaraya Technological University in 2009. He has served at
Malnad College of Engineering, Hassan, and Karnataka India from 1990-2010. He is
currently serving as Professor and Head of CSE in GEC, Hassan. His areas of interest include
Databases, Image Processing and Cryptography. He has 4 International and 12 national

SURVEY PAPER ON OUT LIER DETECTION USING FUZZY LOGIC BASED METHOD
Deepa Verma, Rakesh Kumar and Akhilesh Kumar
Department of Information Technology, Rajkiya Engineering College, Ambedkar Nagar
(U.P) – 224 122, India
ABSTRACT
Fuzzy logic can be used to reason like humans and can deal with uncertainty other than
randomness. Outlier detection is a difficult task to be performed, due to uncertainty involved in it.
The outlier itself is a fuzzy concept and difficult to determine in a deterministic way. fuzzy logic
system is very promising, since they exactly tackle the situation associated with outliers. Fuzzy
logic that addresses the seemingly conflicting goals (i) removing noise, (ii) smoothing out outliers
and certain other salient feature. This paper provides a detailed fuzzy logic used for outlier
detection by discussing their pros and cons. Thus this is a very helpful document for naive
researchers in this field
KEYWORDS
Data mining, fuzzy logic, Outlier Detection. Artificial Intelligent Information Systems

REFERENCES
[1] Varun chandola, arindam banerjee and vipin kumar, outlier detection : a survey
[2] Chiu, S. L. (1994). Fuzzy model identification based on cluster estimation. Journal of Intelligent and
Fuzzy Systems, 2, 267–278
[3] Hodge, V. and J. Austin, A Survey of Outlier Detection Methodologies, Artificial Intelligence Review,
Vol. 22, 2004, pp. 85–126.
[4] Victoria J. Hodge and Jim Austin, A Survey of Outlier Detection Methodologies, Kluwer Academic
Publishers, 2004.
[5] L.Zadeh, Fuzzy sets, Inform. And control, vol.8, pp. 338-353, ,1965.
[6] Sankar K. Pal, P. Mitra, Data Mining in Soft Computing Framework: A Survey, IEEE transactions on
neural networks, vol. 13, no. 1, January 2002.
[7] E. Cox, Fuzzy Modeling And Genetic Algorithms For Data Mining And Exploration, Elsevier, 2005.
[8] Bezdek, J, L. Hall, and L. Clarke, Review of MR Image Segmentation Techniques Using Pattern
Recognition, Medical Physics, Vol. 20, No. 4, 1993, pp. 1033–1048.
[9] Pham, D, Spatial Models for Fuzzy Clustering, Computer Vision and Image Understanding, Vol. 84, No.
2, 2001, pp. 285–297.
[10] Rignot, E, R. Chellappa, and P. Dubois, Unsupervised Segmentation of Polarimetric SAR Data Using
the Covariance Matrix, IEEE Trans. Geosci. Remote Sensing, Vol. 30, No. 4, 1992, pp. 697–705.
[11] Al- Zoubi, M. B., A. Hudaib and B Al- Shboul A Proposed Fast Fuzzy C-Means Algorithm, WSEAS
Transactions on Systems, Vol. 6, No. 6, 2007, pp. 1191-1195.
[12] Maragos E. K and D. K. Despotis, The Evaluation of the Efficiency with Data Envelopment Analysis in
Case of Missing Values: A fuzzy approach, WSEAS Transactions on Mathematics, Vol. 3, No. 3, 2004, pp.
656-663.
[13] Binu Thomas and Raju G, A Novel Fuzzy Clustering Method for Outlier Detection in Data Mining,
International Journal of Recent Trends in Engineering, Vol. 1, No. 2, May 2009.
[14] Moh'd Belal Al-Zoubi, Ali Al-Dahoud, Abdelfatah A. Yahya, New Outlier Detection Method Based on
Fuzzy Clustering, WSEAS transactions on information science and applications, Issue 5, Volume 7, May
2010, pp. 681 – 690.
[15] Hawkins, S.; He, X.; Williams, G.J. & Baxter, R.A., Outlier detection using replicator neural networks.
Proceedings of the 5th international conference on Knowledge Discovery and Data Warehousing, 2002.
[16] R. Hecht-Nielsen. Replicator neural networks for universal optimal source coding. Science, 269 (1860-
1863), 1995.
[17] Williams, G.; Baxter, R.; He, H. & Hawkison,S., A comparative study of RNN for outlier detection in
data mining, Proceedings of the IEEE International Conference on Data Mining, pp. 709–712, 9-12
December 2002, Australia.
[18] Nag, A.K.; Mitra, A. & Mitra, S., Multiple outlier Detection in Multivariate Data Using SelfOrganizing
Maps Title, Computational Statistical, N.20, 2005, pp.245-264.
[19] Peng Yang, Qingsheng Zhu and Xun Zhong, Subtractive Clustering Based RBF Neural Network Model
for Outlier Detection, Journal Of Computers, Vol. 4, No. 8, August 2009, pp. 755-762.
[20] N. P. Jawarkar, R. S. Holambe and T. K. Basu, Use of fuzzy min-max neural network for speaker
identification, Proc. IEEE Int. Conference on Recent Trends in Information Technology (ICRTIT 2011),
MIT, Anna university, Chennai, Jun.-3-5, 2011.
[21] S. S. Panicker, P. S. Dhabe, M. L. Dhore, Fault Diagnosis Using Fuzzy Min-Max Neural Network
Classifier, CiiT International Journal of Artificial Intelligent Systems and Machine Learning, Issue Jul.
2010. http://www.ciitresearch.org/aimljuly2010.html.
[22] M. Mohammadi, R. V. Pawar, P. S. Dhabe, Heart Diseases Detection Using Fuzzy Hyper Sphere
Neural Network Classifier, CiiT International Journal of Artificial Intelligent Systems and Machine
Learning, Issue July 2010. http://www.ciitresearch.org/aimljuly2010.html.

[23] Wang G., Jinxing Hao, Jian Ma, Lihua Huang, A new approach to intrusion detection using Artificial
Neural Networks and fuzzy clustering. Expert Systems with Applications (2010),
doi:10.1016/j.eswa.2010.02.102
[24] Gath, I and A. Geva, Fuzzy Clustering for the Estimation of the Parameters of the Components of
Mixtures of Normal Distribution, Pattern Recognition Letters, Vol. 9, 1989, pp. 77-86.
[25] Cutsem, B and I. Gath, Detection of Outliers and Robust Estimation using Fuzzy Clustering,
Computational Statistics & Data Analyses, Vol. 15, 1993, pp. 47-61
AUTHORS
Akhilesh Kumar graduated from Mahatma Ghandhi Mission’s college of Engg. and
technology, Noida, Uttar Pradesh in Computer Science & Engineering in 2010. He has
been M.Tech in the department of Computer Science & Engineering, Kamla Nehru
Institute of Technology, Sultanpur (Uttar Pradesh). SinceAugust2012, he has been with
the Department of Department of Information Technology, Rajkiya EngineeringCollege,
Ambedkar Nagar, as an Assistant Professor.His area of interests includes Computer
Networks and Mobile ad-hoc Nerwork.
Rakesh Kumar was born in Bulandshahr (U.P.), India, in 1984. He received the B.Tech. degree in
Information Technology from Kamla Nehru Institute of Technology, Sultanpur (U.P.),
India, in 2007, and the M.Tech. degrees in ICT Specialization with Software
Engineering from the Gautam Buddha University, Greater Noida, Gautam Budh Nagar,
Uttar Pradesh, India, in 2012.In 2007, he joined the Quantum Technology, New Delhi
as a Software Engineer and Since August 2012, he has been with the Department of
Department of Information Technology, Rajkiya Engineering College, Ambedkar
Nagar, as an Assistant Professor. His current research interests include Computer
Network, Multicast Security, Sensor Network and data mining. He is a Life Member of the Indian Society
for Technical Education (ISTE), and he is a Nominee Member of Computer society of In dia.

A NOVEL APPROACH TO ERROR DETECTION AND CORRECTION OF C
PROGRAMS USING MACHINE LEARNING AND DATA MINING
Prof. KhushaliDeulkar1
, Jai Kapoor2
, Priya Gaud3
, Harshal Gala4
Department Of Computer Engineering D.J Sanghvi College Of Engineering
,Mumbai, India
ABSTRACT
There has always been a struggle for programmers to identify the errors while executing a
program- be it syntactical or logical error. This struggle has led to a research in identification of
syntactical and logical errors. This paper makes an attempt to survey those research works which
can be used to identify errors as well as proposes a new model based on machine learning and data
mining which can detect logical and syntactical errors by correcting them or providing suggestions.
The proposed work is based on use of hashtags to identify each correct program uniquely and this
in turn can be compared with the logically incorrect program in order to identify errors.
KEYWORDS
Machine Learning Device(MLD), Data Mining Device(DMD), Databases, Hash-tag.

REFERENCES
[1] K K Sharma, Kunal Banerjee, IndraVikas, ChittaranjanMandal, “Automated Checking of the Violation
of Precedence of Conditions in else-if Constructs in Student’s Programs”, IEEE International Conference on
MOOC, Innovation and Technology in Education (MITE), 2014
[2] YuriyBrun, Michael D. Ernst, “Finding latent code errors via machine learning over program
executions”, Proceedings of the 26th International Conference on Software Engineering (ICSE).,2004
[3] Tatiana Vert, Tatiana Krikun, Mikhail Glukhikh, “Detection of Incorrect Pointer Dereferences for
C/C++ Programs using Static Code Analysis and Logical Inference”, Tools& Methods of Program Analysis,
2013.
[4] George Stergiopoulos, PanagiotisKatsaros, DimitrisGritzalis, “Automated detection of logical errors in
programs”, Springer-Verlag Berlin Heidelberg 2014.
[5] PrakashMurali, AtulSandur, Abhay Ashok Patil, “Correction of Logical Errors in C programs using
Genetic Algorithm Techniques”, International Journal of Recent Trends in Engineering, Vol. 1, No. 2, May
2009.
[6] M. I. Glukhikh, V. M. Itsykson, and V. A. Tsesko, “Using Dependencies to Improve Precision of Code
Analysis”, Automatic Control and Computer Sciences, 2012. International Journal on Cybernetics &
Informatics (IJCI) Vol. 5, No. 2, April 2016 39
[7] V. Neelima, Annapurna. N, V. Alekhya, Dr. B. M. Vidyavathi, “Bug Detection through Text Data
Mining”, International Journal of Advanced Research in Computer Science and Software Engineering, May
2013.
[8] Data Mining, available at: https://www.wikipedia.org/
[9]DataMining,availableat:
http://www.anderson.ucla.edu/faculty/jason.frand/teacher/palace/datamining.html

BORDER SECURITY ROBOT
Minni Mohan1
And Siddharth Shelly2
1Department of electronics and communication, M.A College of Engineering,
Kothamangalam,A P J Abdul Kalam Technological University, Kerala, India 2Associate
Prof, Department of electronics and communication Engineering, Mar Athanasius College of
Engineering, Kothamangalam, Kerala, India
ABSTRACT
The ordinary border patrol system suffers from intensive human involvement. Recently unmanned
border patrol system consist of high tech devices, like unmanned aerial vehicles, unattended ground
sensors, and surveillance towers equipped with wireless camera. However, any single technique
encounters inextricable problems, such as high false alarm rate and line of sight constrains. There
require a coherent system that co-ordinates various technologies to improve the system accuracy.
In this project general idea of boarder security robot, wireless sensor network architecture for
border patrol system, is introduced. Border security robot utilize a PIR sensor for human detection,
a metal detector to detect the presence of explosives and a wireless camera for monitoring the
scenario continuously at the remote station. Mechanical control of robotic vehicle along with
robotic arm can be done from the remote station. This is initiated with a Bluetooth module.
KEYWORDS
PIC, PIR, Metal detector, Wireless camera

REFERENCES
[1] Zhi Sun, Pu Wang, Mehmet C,Vuran,Mznah A. Al-Rodhaan,Abdullah M.Al-Dhelaan,Ian F.Akyildiz ,
(2011),"BorderSense: Border patrol through advanced wireless sensor networks”, Ad Hoc Networks 9 pp.
468–477
[2] K. V. S. S. S. S. Sairam, N. Gunasekaran, S. Rama Reddy, (2002), "Bluetooth in Wireless
Communication", IEEE Communications Magazine ,pp.90-96
[3] Francesco Balena ,"Programming Microsoft Visual Basic 6.0", Publisher: Microsoft Press,1999
[4] I.F. Akyildiz, T. Melodia, K. Chowdhury,(2008) “Wireless multimedia sensor Networks : applications
and testbeds”, Proceedings of the IEEE 96 (10) pp. 1588–1605
[5] Ariponnammal S and Natarajan S (1994) “Control system for a mobile robot”, Pramana Journal of
PhysicsVol.42,No:1,pp.421-425
AUTHOR
Minni Mohan Graduated (B-tech)in Electronics and Communication Engineering from
Mahathma Gandhi University and currently pursuing M Tech in VLSI and Embedded
System in APJ Abdul Kalam Technological University, Kerala, India.
Siddharth Shelly is a faculty member of Mar Athanasius College of Engineering,
Kothamangalam, Kerala, India. He received his B.Tech from Mahatma Gandhi University,
Kottayam and M.Tech degree from the Amrita School of Engineering, Coimbatore, India.
His current research focus is in the area of vehicular ad hoc networks, embedded systems.

DESIGN ANDIMPLEMENTATION OF EFFICIENT TERNARY CONTENT
ADDRESSABLE MEMORY
Gangadhar Akurathi1
, Suneel kumar Guntuku2
and K.Babulu3
1
Department of ECE, JNTUK-UCEV, Vizianagaram, Andhra Pradesh, India 2
Department of
ECE, JNTUK-UCEV, Vizianagaram, Andhra Pradesh, India 3
Department of ECE, JNTUK-
UCEK, Kakinada, Andhra Pradesh, India
ABSTRACT
A CAM is used for store and search data and using comparison logic circuitry implements the table
lookupfunction in a single clock cycle. CAMs are main application of packet forwarding and
packet classification in Network routers. A Ternary content addressable memory(TCAM) has three
type of states ‘0’,’1’ and ‘X’(don’t care) and which is like as binary CAM and has extra feature of
searching and storing. The ‘X’ option may be used as ‘0’ and ‘1’. TCAM performs high-speed
search operation in a deterministic time. In this work a TCAM circuit is designed by using current
race sensing scheme and butterfly matchline (ML) scheme. The speed and power measures of both
the TCAM designs are analysed separately. A Novel technique is developed which is obtained by
combining these two techniques which results in significant power and speed efficiencies.
KEYWORDS
Content Addressable Memory (CAM) Circuit, XOR-based conditional keeper, Ternary Content
Addressable Memory (TCAM)Circuit,Pseudo-Footless Clock Data Pre-charge Dynamic Match line
(PFCDPD)Architecture.

REFERENCES
[1] Byung-Do Yang, “Low-Power Effective Memory-Size Expanded Ternary Content Addressable Memory
(TCAM) Using Data-Relocation Scheme,” IEEE Journal of Solid State Circuits, Vol.50, No.10, Oct 2015.
[2] Ray C.C.Cheung,ManishK.Jaiswal, and Zahid Ullah, “Z-TCAM: An SRAM-based Architecture for
TCAM,” IEEE Trans on very large scale Integration (VLSI) systems , Digital Object Identifier
10.1109/TVLSI.2014.2309350.
[3] Kiat Seng Yeo, Shoushun Chen, Anh-Tuan Do, and Zhi-Hui Kong, “A High Speed Low Power CAM
With a Parity Bit and Power-Gated ML Sensing,” IEEE Trans. On very large scale Integration (VLSI)
Systems, Vol.21, NO.1, Jan 2013.
[4] Shun-Hsun Yang, in-Fu Li, and Yu-Jen Huang, “A Low-Power Ternary Content Addressable Memory
with Pai-Sigma Match lines,” IEEE Trans. On very large scale Integration (VLSI) Systems, Vol.20, NO.10,
Oct 2012.
[5] Byung-Do Yang, Yong-Kyu Lee, Si-Woo Sung, Jae-Joong Min, Jae-Mun Oh, and Hyeong-Ju Kang, “A
Low Power Content Addressable Memory Using Low Swing Search Lines,” IEEE Trans. On circuits and
systems-I: Regular Papers, Vol.58, No.12, Dec 2011.
[6] Manoj Sachdev, Wilson Fung, Nitin Mohan and Derek Wright, “A Low-Power Ternary CAM with
Positive-Feedback Match-Line Sense Amplifiers,” IEEE Trans. On circuits and systems-I: Regular Papers,
Vol.56, No.3, March 2009.
[7] Yuan-Hong Liao and Yen-Jen Chang, “Hybrid-Type CAM Design for Both Power and Performance
Efficiency,”IEEE Trans. On very large scale Integration (VLSI) Systems, Vol.16, NO.8, Aug 2008.
[8] Baeg.S, “Low-power ternary content addressable memory design using a segmented match line,” IEEE
Trans. Circuits Syst.,Vol. 55,no. 6,pp. 1485-1494, July 2008.
[9] Nitin Mohan, Manoj Sachdev and Derek Wright, Wilson Fung, "Design Techniques and Test
Methodology for Low-Power TCAMs" IEEE Transactions on Very Large Scale Integration (VLSI)
Systems, Vol. 14, No. 6, June 2006.
[10] I.Arsovski, A.Sheikholeslami, and T.Chandler, “A Ternary content addressable memory based on 4T
static storage and including a current race sensing scheme,” IEEE J.Solid-State circuits, vol.38, no. 1, pp.
155-158,Jan2003

June 2022 - Top 10 Download Article in IJCI.pdf

Recommended

Recommended

More Related Content

Similar to June 2022 - Top 10 Download Article in IJCI.pdf

Similar to June 2022 - Top 10 Download Article in IJCI.pdf (20)

Recently uploaded

Recently uploaded (20)

June 2022 - Top 10 Download Article in IJCI.pdf