"Knowledge management and predictive analytics are considered to be unusual partners in today’s technology. However, they can be very good tools that would solve current problems in valuing data. Predictive analytics has now become one of the forecasting tools that is of huge help in information management. Its application in IT project development risk management is very important, where a lot of raw data is involved with risk analysis and prediction. The use of IT project risk management as supported by knowledge management KM will help increase the success rate of IT projects. Knowledge management will bring about additional value to the data needed. This paper presents the usage of KM and predictive analytics to increase the success ratings of projects by predicting the risks that might happen during project development. It explores how KM and predictive analytics can identify risks in IT project development and give recommendations in evaluating the risks that could affect successful completion of IT projects. Mia Torres-Dela Cruz | Subashini A/P Ganapathy | Noor Zuhaili Binti Mohd Yasin ""Knowledge Management and Predictive Analytics in IT Project Risks"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Advanced Engineering and Information Technology , November 2018, URL: https://www.ijtsrd.com/papers/ijtsrd19142.pdf
Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/19142/knowledge-management-and-predictive-analytics-in-it-project-risks/mia-torres-dela-cruz"
Artificial intelligence has been a buzz word that is impacting every industry in the world. With the rise of such advanced technology, there will be always a question regarding its impact on our social life, environment and economy thus impacting all efforts exerted towards sustainable development. In the information era, enormous amounts of data have become available on hand to decision makers. Big data refers to datasets that are not only big, but also high in variety and velocity, which makes them difficult to handle using traditional tools and techniques. Due to the rapid growth of such data, solutions need to be studied and provided in order to handle and extract value and knowledge from these datasets for different industries and business operations. Numerous use cases have shown that AI can ensure an effective supply of information to citizens, users and customers in times of crisis. This paper aims to analyse some of the different methods and scenario which can be applied to AI and big data, as well as the opportunities provided by the application in various business operations and crisis management domains.
ANALYZING AND IDENTIFYING FAKE NEWS USING ARTIFICIAL INTELLIGENCEIAEME Publication
The main reason behind the spread of fake news is because of many fake and hyperpartisan sites present on the Internet. These fake sites try to manipulate the truth which creates misunderstanding in society. Therefore, it is important to detect fake news and try to make people aware of the truth. This paper gives an insight into how to detect fake news using Machine Learning and Deep Learning Techniques. On observing our data, we have categorized our data into five attributes namely Title, Text, Subject, Date, and Labels. In order to develop an efficient fake news detection system, the feature along with its degree of impact on the system must be taken into consideration. This paper attempts at providing a detailed analysis of detecting fake news using various models such as LSTM, ANN, Naïve Bayes, SVM, Logistic Regression, XGBoost, and Bert.
IMPORTANCE OF PROCESS MINING FOR BIG DATA REQUIREMENTS ENGINEERINGijcsit
Requirements engineering (RE), as a part of the project development life cycle, has increasingly been recognized as the key to ensure on-time, on-budget, and goal-based delivery of software projects. RE of big data projects is even more crucial because of the rapid growth of big data applications over the past few years. Data processing, being a part of big data RE, is an essential job in driving big data RE process successfully. Business can be overwhelmed by data and underwhelmed by the information so, data processing is very critical in big data projects. Employing traditional data processing techniques lacks the invention of useful information because of the main characteristics of big data, including high volume, velocity, and variety. Data processing can be benefited by process mining, and in turn, helps to increase the productivity of the big data projects. In this paper, the capability of process mining in big data RE to discover valuable insights and business values from event logs and processes of the systems has been highlighted. Also, the proposed big data requirements engineering framework, named REBD, helps software requirements engineers to eradicate many challenges of big data RE.
Requirements engineering (RE), as a part of the project development life cycle, has increasingly been recognized as the key to ensure on-time, on-budget, and goal-based delivery of software projects. RE of big data projects is even more crucial because of the rapid growth of big data applications over the past few years. Data processing, being a part of big data RE, is an essential job in driving big data RE process successfully. Business can be overwhelmed by data and underwhelmed by the information so, data processing is very critical in big data projects. Employing traditional data processing techniques lacks the invention of useful information because of the main characteristics of big data, including high volume, velocity, and variety. Data processing can be benefited by process mining, and in turn, helps to increase the productivity of the big data projects. In this paper, the capability of process mining in big data RE to discover valuable insights and business values from event logs and processes of the systems has been highlighted. Also, the proposed big data requirements engineering framework, named REBD, helps software requirements engineers to eradicate many challenges of big data RE.
A COMPREHENSIVE STUDY ON POTENTIAL RESEARCH OPPORTUNITIES OF BIG DATA ANALYTI...ijcseit
Companies, organizations and policy makers shake out with flood flowing volume of transactional data,
accumulating trillions of bytes of information about their customers, suppliers and operations. The advanced networked sensors are being implanted in devices such as mobile phones, smart energy meters,automobiles and industrial machines that sense, generate and transfer data to multiple storage devices. In fact, as they go about their business and interact with individuals, they are producing an incredible amount of fatigue digital data. Social media sites, smart phones, and other customer devices have allowed billions
of individuals around the world to contribute to the amount of data available. In addition, the extremely
increasing size of multimedia data has also take part a key role in the rapid growth of data. The technology
of high-definition video creates more than 2,000 times as many bytes as necessary to store as normal text
data. Moreover, in a digitized world, consumers are leaving enormous amount of data about their day-today
communicating, browsing, buying, sharing, searching and so on. As a result, it evolved as a big data and in turn has motivated the advances in big data analytics paradigms, endorsed as a basic motivation factor for the present researchers.
Artificial intelligence has been a buzz word that is impacting every industry in the world. With the rise of such advanced technology, there will be always a question regarding its impact on our social life, environment and economy thus impacting all efforts exerted towards sustainable development. In the information era, enormous amounts of data have become available on hand to decision makers. Big data refers to datasets that are not only big, but also high in variety and velocity, which makes them difficult to handle using traditional tools and techniques. Due to the rapid growth of such data, solutions need to be studied and provided in order to handle and extract value and knowledge from these datasets for different industries and business operations. Numerous use cases have shown that AI can ensure an effective supply of information to citizens, users and customers in times of crisis. This paper aims to analyse some of the different methods and scenario which can be applied to AI and big data, as well as the opportunities provided by the application in various business operations and crisis management domains.
ANALYZING AND IDENTIFYING FAKE NEWS USING ARTIFICIAL INTELLIGENCEIAEME Publication
The main reason behind the spread of fake news is because of many fake and hyperpartisan sites present on the Internet. These fake sites try to manipulate the truth which creates misunderstanding in society. Therefore, it is important to detect fake news and try to make people aware of the truth. This paper gives an insight into how to detect fake news using Machine Learning and Deep Learning Techniques. On observing our data, we have categorized our data into five attributes namely Title, Text, Subject, Date, and Labels. In order to develop an efficient fake news detection system, the feature along with its degree of impact on the system must be taken into consideration. This paper attempts at providing a detailed analysis of detecting fake news using various models such as LSTM, ANN, Naïve Bayes, SVM, Logistic Regression, XGBoost, and Bert.
IMPORTANCE OF PROCESS MINING FOR BIG DATA REQUIREMENTS ENGINEERINGijcsit
Requirements engineering (RE), as a part of the project development life cycle, has increasingly been recognized as the key to ensure on-time, on-budget, and goal-based delivery of software projects. RE of big data projects is even more crucial because of the rapid growth of big data applications over the past few years. Data processing, being a part of big data RE, is an essential job in driving big data RE process successfully. Business can be overwhelmed by data and underwhelmed by the information so, data processing is very critical in big data projects. Employing traditional data processing techniques lacks the invention of useful information because of the main characteristics of big data, including high volume, velocity, and variety. Data processing can be benefited by process mining, and in turn, helps to increase the productivity of the big data projects. In this paper, the capability of process mining in big data RE to discover valuable insights and business values from event logs and processes of the systems has been highlighted. Also, the proposed big data requirements engineering framework, named REBD, helps software requirements engineers to eradicate many challenges of big data RE.
Requirements engineering (RE), as a part of the project development life cycle, has increasingly been recognized as the key to ensure on-time, on-budget, and goal-based delivery of software projects. RE of big data projects is even more crucial because of the rapid growth of big data applications over the past few years. Data processing, being a part of big data RE, is an essential job in driving big data RE process successfully. Business can be overwhelmed by data and underwhelmed by the information so, data processing is very critical in big data projects. Employing traditional data processing techniques lacks the invention of useful information because of the main characteristics of big data, including high volume, velocity, and variety. Data processing can be benefited by process mining, and in turn, helps to increase the productivity of the big data projects. In this paper, the capability of process mining in big data RE to discover valuable insights and business values from event logs and processes of the systems has been highlighted. Also, the proposed big data requirements engineering framework, named REBD, helps software requirements engineers to eradicate many challenges of big data RE.
A COMPREHENSIVE STUDY ON POTENTIAL RESEARCH OPPORTUNITIES OF BIG DATA ANALYTI...ijcseit
Companies, organizations and policy makers shake out with flood flowing volume of transactional data,
accumulating trillions of bytes of information about their customers, suppliers and operations. The advanced networked sensors are being implanted in devices such as mobile phones, smart energy meters,automobiles and industrial machines that sense, generate and transfer data to multiple storage devices. In fact, as they go about their business and interact with individuals, they are producing an incredible amount of fatigue digital data. Social media sites, smart phones, and other customer devices have allowed billions
of individuals around the world to contribute to the amount of data available. In addition, the extremely
increasing size of multimedia data has also take part a key role in the rapid growth of data. The technology
of high-definition video creates more than 2,000 times as many bytes as necessary to store as normal text
data. Moreover, in a digitized world, consumers are leaving enormous amount of data about their day-today
communicating, browsing, buying, sharing, searching and so on. As a result, it evolved as a big data and in turn has motivated the advances in big data analytics paradigms, endorsed as a basic motivation factor for the present researchers.
This paper presents a project management methodology - developed part of an engineering doctorate research at Warwick University - for managing large scale IT projects with a focus on national ID programmes. The methodology was mainly tested in the United Arab Emirates (UAE) and was followed in three GCC countries. The research demonstrated that by following a formal structured methodology, governments will have better visibility and control over such programmes. The implementation revealed that the phases and processes of the proposed methodology supported the overall management, planning, control over the project activities, promoted effective communication, improved scope and risk management, and ensured quality deliverables.
Study and analysis of E-Governance Information Security (InfoSec) in Indian C...IOSRjournaljce
The purpose of the study is to explore and find a research gap in E-Governance Information Security (InfoSec) domain in Indian Context. The study identifies the research gap in E-Governance InfoSec domain and substantiates given research gap with relevant literature review. The study outcomes clearly depict the requirement of research in the field of InfoSec in e-governance domain in a country like India.
Proposed T-Model to cover 4S quality metrics based on empirical study of root...IJECEIAES
There are various root causes of software failures. Few years ago, software used to fail mainly due to functionality related bugs. That used to happen due to requirement misunderstanding, code issues and lack of functional testing. A lot of work has been done in past on this and software engineering has matured over time, due to which software’s hardly fail due to functionality related bugs. To understand the most recent failures, we had to understand the recent software development methodologies and technologies. In this paper we have discussed background of technologies and testing progression over time. A survey of more than 50 senior IT professionals was done to understand root cause of their software project failures. It was found that most of the softwares fail due to lack of testing of non-functional parameters these days. A lot of research was also done to find most recent and most severe software failures. Our study reveals that main reason of software failures these days is lack of testing of non-functional requirements. Security and Performance parameters mainly constitute non-functional requirements of software. It has become more challenging these days due to lots of development in the field of new technologies like Internet of things (IoT), Cloud of things (CoT), Artificial Intelligence, Machine learning, robotics and excessive use of mobile and technology in everything by masses. Finally, we proposed a software development model called as T-model to ensure breadth and depth of software is considered while designing and testing of software.
The effect of technology-organization-environment on adoption decision of bi...IJECEIAES
Big data technology (BDT) is being actively adopted by world-leading organizations due to its expected benefits. However, most of the organizations in Thailand are still in the decision or planning stage to adopt BDT. Many challenges exist in encouraging the BDT diffusion in businesses. Thus, this study develops a research model that investigates the determinants of BDT adoption in the Thai context based on the technology-organizationenvironment (TOE) framework and diffusion of innovation (DOI) theory. Data were collected through an online questionnaire. Three hundred IT employees in different organizations in Thailand were used as a sample group. Structural equation modeling (SEM) was conducted to test the hypotheses. The result indicated that the research model was fitted with the empirical data with the statistics: Normed Chi-Square=1.651, GFI=0.895, AFGI=0.863, NFI=0.930, TLI=0.964, CFI=0.971, SRMR=0.0392, and RMSEA=0.046. The research model could, at 52%, explain decision to adopt BDT. Relative advantage, top management support, competitive pressure, and trading partner pressure show significant positive relation with BDT adoption, while security negatively influences BDT adoption.
Big Data Courses In Mumbai at Asterix Solution is designed to scale up from single servers to thousands of machines, each offering local computation and storage. With the rate at which memory cost decreased the processing speed of data never increased and hence loading the large set of data is still a big headache and here comes Hadoop as the solution for it.
http://www.asterixsolution.com/big-data-hadoop-training-in-mumbai.html
Design and Implementation Security Model for Sudanese E-governmentEditor IJCATR
Security is one of the most important issues in E-government projects. E-government applications will be increasingly used
by the citizens of many countries to access a set of services. Currently, the use of the E-government applications arises many
challenges; one of these challenges is the security issues. E-government applications security is a very important characteristic that
should be taken into account. This paper makes an analysis over the security as required for E-government and specify the risks and
challenges that faces E-government projects in Sudan. Finally, the study has proposed security model for Sudanese E-government. The
proposed security model for the Sudanese electronic government is a four layers' model that is divided into sub layers. Each layer will
mitigate group of threats related to an e-services. The model is not generic; it cannot be applied by other countries. It is precisely
designed for Sudanese situation
Video at: https://www.linkedin.com/video/live/urn:li:ugcPost:6705141260845412352/
In this talk, we will review some of the challenges related to Industry 4.0 or Factory of Future, and how can Artificial Intelligence help address them.
Examples include the use of semantic interoperability and integration to support the use of sensor collected data in decision making, the use of computer vision to identify deviations in the process and manage quality, and the use of predictive algorithms for device maintenance.
Impact of big data congestion in IT: An adaptive knowledgebased Bayesian networkIJECEIAES
Recent progress on real-time systems are growing high in information technology which is showing importance in every single innovative field. Different applications in IT simultaneously produce the enormous measure of information that should be taken care of. In this paper, a novel algorithm of adaptive knowledge-based Bayesian network is proposed to deal with the impact of big data congestion in decision processing. A Bayesian system show is utilized to oversee learning arrangement toward all path for the basic leadership process. Information of Bayesian systems is routinely discharged as an ideal arrangement, where the examination work is to find a development that misuses a measurably inspired score. By and large, available information apparatuses manage this ideal arrangement by methods for normal hunt strategies. As it required enormous measure of information space, along these lines it is a tedious method that ought to be stayed away from. The circumstance ends up unequivocal once huge information include in hunting down ideal arrangement. A calculation is acquainted with achieve quicker preparing of ideal arrangement by constraining the pursuit information space. The proposed algorithm consists of recursive calculation intthe inquiry space. The outcome demonstrates that the ideal component of the proposed algorithm can deal with enormous information by processing time, and a higher level of expectation rates.
A DECISION-MAKING MODEL FOR REINFORCING A CORPORATE INFORMATION SECURITY SYSTEMIAEME Publication
Recently, information security incidents such as personal information leakage have been regarded as serious risk factors that directly affect corporate sales reduction and corporate image loss. In order to manage information security systematically, enterprises have been introducing information security systems more than ever before. This study aims to derive major items of the information security system mainly for corporate organizational management, with a focus on the technology-organizationenvironment (TOE) framework, and suggests a direction for system build-up and management. To this end, the Analytic Hierarchy Process (AHP) was conducted on 20 items derived from previous studies. A survey was conducted among 24 individuals, including 12 corporate internal administrators and 12 corporate external consultants. As a result, it turned out that environmental factors affected the information security system more significantly among technical, organizational, and environmental factors. Notably, 'compliance with legal requirements,' 'protection of information subjects' rights,' and 'increase of the information security awareness' affected the operation of the information security system or related decision-making processes. This finding suggests that although technical and organizational management is also essential when it comes to corporate information security system operation, the system needs to respond swiftly to rapid market changes and legal and administrative changes concerning information security.
MEASURING TECHNOLOGICAL, ORGANIZATIONAL AND ENVIRONMENTAL FACTORS INFLUENCING...csandit
The main objective of this research is to identify the factors influencing the intentions to adopt
the public computing by the private sector firms. In this research the researcher examined the
ten factors influencing the cloud computing adoption using a proposed integrated model which
incorporates aspects of the Technology, Organization and Environment factors such as
Complexity, Compatibility, Security Concerns, Trialability, Cost Saving, Top Management
Support, Prior IT Experience, Organizational Readiness, Competitive Pressure and External
Support. In order to test influencing factors a survey was conducted and one hundred and
twenty two valid responses were received from IT decision makers from forty firms in different
industries. The results revealed that the Compatibility, Cost Saving, Trialability and External
Support are the main influential factors in the adoption intentions of public cloud computing.
Future research could be built on this study by developing different model for each industry
because each industry has unique characteristics that can influence the adoption of the
technological innovations.
A LITERATURE SURVEY AND ANALYSIS ON SOCIAL ENGINEERING DEFENSE MECHANISMS AND...IJNSA Journal
Social engineering attacks can be severe and hard to detect. Therefore, to prevent such attacks, organizations should be aware of social engineering defense mechanisms and security policies. To that end, the authors developed a taxonomy of social engineering defense mechanisms, designed a survey to measure employee awareness of these mechanisms, proposed a model of Social Engineering InfoSec Policies (SE-IPs), and designed a survey to measure the incorporation level of these SE-IPs. After analyzing the data from the first survey, the authors found that more than half of employees are not aware of social engineering attacks. The paper also analyzed a second set of survey data, which found that on average, organizations incorporated just over fifty percent of the identified formal SE-IPs. Such worrisome results show that organizations are vulnerable to social engineering attacks, and serious steps need to be taken to elevate awareness against these emerging security threats.
The slide has details on below points:
1. Introduction to Machine Learning
2. What are the challenges in acceptance of Machine Learning in Banks
3. How to overcome the challenges in adoption of Machine Learning in Banks
4. How to find new use cases of Machine Learning
5. Few current interesting use cases of Machine Learning
Please contact me (shekup@gmail.com) or connect with me on LinkedIn (https://www.linkedin.com/in/shekup/) for more explanation on ML and how it may help your business.
The slides are inspired by:
Survey & interviews done by me with Bankers & Technology Professionals
Presentation from Google NEXT 2017
Presentation by DATUM on Youtube
Royal Society Machine Learning
Big Data & Social Analytics Course from MIT & GetSmarter
Investment Thesis: Construction TechnologyJeffrey Bantam
The following presentation details my personal investment thesis on technology in the construction sector. Please feel free to reach out to me with any questions or comments!
Since I realized after posting the slideshow that my cover links didn't work - I've listed them here for reference:
Email: jeffreybantam@gmail.com
LinkedIn: https://www.linkedin.com/in/jeffrey-bantam-7ab54948/
Twitter: https://twitter.com/jeffreybantam
Website: https://jeffreybantam.com/
SECURETI: ADVANCED SDLC AND PROJECT MANAGEMENT TOOL FOR TI(PHILIPPINES)ijcsit
There are essential security considerations in the systems used by semiconductor companies like TI. Along
with other semiconductor companies, TI has recognized that IT security is highly crucial during web
application developers' system development life cycle (SDLC). The challenges faced by TI web developers
were consolidated via questionnaires starting with how risk management and secure coding can be
reinforced in SDLC; and how to achieve IT Security, PM and SDLC initiatives by developing a prototype
which was evaluated considering the aforementioned goals. This study aimed to practice NIST strategies
by integrating risk management checkpoints in the SDLC; enforce secure coding using static code analysis
tool by developing a prototype application mapped with IT Security goals, project management and SDLC
initiatives and evaluation of the impact of the proposed solution. This paper discussed how SecureTI was
able to satisfy IT Security requirements in the SDLC and PM phases.
There are essential security considerations in the systems used by semiconductor companies like TI. Along
with other semiconductor companies, TI has recognized that IT security is highly crucial during web
application developers' system development life cycle (SDLC). The challenges faced by TI web developers
were consolidated via questionnaires starting with how risk management and secure coding can be
reinforced in SDLC; and how to achieve IT Security, PM and SDLC initiatives by developing a prototype
which was evaluated considering the aforementioned goals. This study aimed to practice NIST strategies
by integrating risk management checkpoints in the SDLC; enforce secure coding using static code analysis
tool by developing a prototype application mapped with IT Security goals, project management and SDLC
initiatives and evaluation of the impact of the proposed solution. This paper discussed how SecureTI was
able to satisfy IT Security requirements in the SDLC and PM phases.
A SYSTEMATIC REVIEW ON MACHINE LEARNING INSIDER THREAT DETECTION MODELS, DATA...IJNSA Journal
Computers are crucial instruments providing a competitive edge to organizations that have adopted them. Their pervasive presence has presented a novel challenge to information security, specifically threats emanating from privileged employees. Various solutions have been tried to address the vice, but no exhaustive solution has been found. Due to their elusive nature, proactive strategies have been proposed of which detection using Machine Learning models has been favoured. The choice of algorithm, datasets and metrics are cornerstones of model performance and hence, need to be addressed. Although multiple studies on ML for insider threat detection have been done, none has provided a comprehensive analysis of algorithms, datasets and metrics for development of Insider Threat Detection models. This study conducts a comprehensive systematic literature review using reputable databases to answer the research questions posed. Search strings, inclusion and exclusion criteria were set for eligibility of articles published in the last decade.
This paper presents a project management methodology - developed part of an engineering doctorate research at Warwick University - for managing large scale IT projects with a focus on national ID programmes. The methodology was mainly tested in the United Arab Emirates (UAE) and was followed in three GCC countries. The research demonstrated that by following a formal structured methodology, governments will have better visibility and control over such programmes. The implementation revealed that the phases and processes of the proposed methodology supported the overall management, planning, control over the project activities, promoted effective communication, improved scope and risk management, and ensured quality deliverables.
Study and analysis of E-Governance Information Security (InfoSec) in Indian C...IOSRjournaljce
The purpose of the study is to explore and find a research gap in E-Governance Information Security (InfoSec) domain in Indian Context. The study identifies the research gap in E-Governance InfoSec domain and substantiates given research gap with relevant literature review. The study outcomes clearly depict the requirement of research in the field of InfoSec in e-governance domain in a country like India.
Proposed T-Model to cover 4S quality metrics based on empirical study of root...IJECEIAES
There are various root causes of software failures. Few years ago, software used to fail mainly due to functionality related bugs. That used to happen due to requirement misunderstanding, code issues and lack of functional testing. A lot of work has been done in past on this and software engineering has matured over time, due to which software’s hardly fail due to functionality related bugs. To understand the most recent failures, we had to understand the recent software development methodologies and technologies. In this paper we have discussed background of technologies and testing progression over time. A survey of more than 50 senior IT professionals was done to understand root cause of their software project failures. It was found that most of the softwares fail due to lack of testing of non-functional parameters these days. A lot of research was also done to find most recent and most severe software failures. Our study reveals that main reason of software failures these days is lack of testing of non-functional requirements. Security and Performance parameters mainly constitute non-functional requirements of software. It has become more challenging these days due to lots of development in the field of new technologies like Internet of things (IoT), Cloud of things (CoT), Artificial Intelligence, Machine learning, robotics and excessive use of mobile and technology in everything by masses. Finally, we proposed a software development model called as T-model to ensure breadth and depth of software is considered while designing and testing of software.
The effect of technology-organization-environment on adoption decision of bi...IJECEIAES
Big data technology (BDT) is being actively adopted by world-leading organizations due to its expected benefits. However, most of the organizations in Thailand are still in the decision or planning stage to adopt BDT. Many challenges exist in encouraging the BDT diffusion in businesses. Thus, this study develops a research model that investigates the determinants of BDT adoption in the Thai context based on the technology-organizationenvironment (TOE) framework and diffusion of innovation (DOI) theory. Data were collected through an online questionnaire. Three hundred IT employees in different organizations in Thailand were used as a sample group. Structural equation modeling (SEM) was conducted to test the hypotheses. The result indicated that the research model was fitted with the empirical data with the statistics: Normed Chi-Square=1.651, GFI=0.895, AFGI=0.863, NFI=0.930, TLI=0.964, CFI=0.971, SRMR=0.0392, and RMSEA=0.046. The research model could, at 52%, explain decision to adopt BDT. Relative advantage, top management support, competitive pressure, and trading partner pressure show significant positive relation with BDT adoption, while security negatively influences BDT adoption.
Big Data Courses In Mumbai at Asterix Solution is designed to scale up from single servers to thousands of machines, each offering local computation and storage. With the rate at which memory cost decreased the processing speed of data never increased and hence loading the large set of data is still a big headache and here comes Hadoop as the solution for it.
http://www.asterixsolution.com/big-data-hadoop-training-in-mumbai.html
Design and Implementation Security Model for Sudanese E-governmentEditor IJCATR
Security is one of the most important issues in E-government projects. E-government applications will be increasingly used
by the citizens of many countries to access a set of services. Currently, the use of the E-government applications arises many
challenges; one of these challenges is the security issues. E-government applications security is a very important characteristic that
should be taken into account. This paper makes an analysis over the security as required for E-government and specify the risks and
challenges that faces E-government projects in Sudan. Finally, the study has proposed security model for Sudanese E-government. The
proposed security model for the Sudanese electronic government is a four layers' model that is divided into sub layers. Each layer will
mitigate group of threats related to an e-services. The model is not generic; it cannot be applied by other countries. It is precisely
designed for Sudanese situation
Video at: https://www.linkedin.com/video/live/urn:li:ugcPost:6705141260845412352/
In this talk, we will review some of the challenges related to Industry 4.0 or Factory of Future, and how can Artificial Intelligence help address them.
Examples include the use of semantic interoperability and integration to support the use of sensor collected data in decision making, the use of computer vision to identify deviations in the process and manage quality, and the use of predictive algorithms for device maintenance.
Impact of big data congestion in IT: An adaptive knowledgebased Bayesian networkIJECEIAES
Recent progress on real-time systems are growing high in information technology which is showing importance in every single innovative field. Different applications in IT simultaneously produce the enormous measure of information that should be taken care of. In this paper, a novel algorithm of adaptive knowledge-based Bayesian network is proposed to deal with the impact of big data congestion in decision processing. A Bayesian system show is utilized to oversee learning arrangement toward all path for the basic leadership process. Information of Bayesian systems is routinely discharged as an ideal arrangement, where the examination work is to find a development that misuses a measurably inspired score. By and large, available information apparatuses manage this ideal arrangement by methods for normal hunt strategies. As it required enormous measure of information space, along these lines it is a tedious method that ought to be stayed away from. The circumstance ends up unequivocal once huge information include in hunting down ideal arrangement. A calculation is acquainted with achieve quicker preparing of ideal arrangement by constraining the pursuit information space. The proposed algorithm consists of recursive calculation intthe inquiry space. The outcome demonstrates that the ideal component of the proposed algorithm can deal with enormous information by processing time, and a higher level of expectation rates.
A DECISION-MAKING MODEL FOR REINFORCING A CORPORATE INFORMATION SECURITY SYSTEMIAEME Publication
Recently, information security incidents such as personal information leakage have been regarded as serious risk factors that directly affect corporate sales reduction and corporate image loss. In order to manage information security systematically, enterprises have been introducing information security systems more than ever before. This study aims to derive major items of the information security system mainly for corporate organizational management, with a focus on the technology-organizationenvironment (TOE) framework, and suggests a direction for system build-up and management. To this end, the Analytic Hierarchy Process (AHP) was conducted on 20 items derived from previous studies. A survey was conducted among 24 individuals, including 12 corporate internal administrators and 12 corporate external consultants. As a result, it turned out that environmental factors affected the information security system more significantly among technical, organizational, and environmental factors. Notably, 'compliance with legal requirements,' 'protection of information subjects' rights,' and 'increase of the information security awareness' affected the operation of the information security system or related decision-making processes. This finding suggests that although technical and organizational management is also essential when it comes to corporate information security system operation, the system needs to respond swiftly to rapid market changes and legal and administrative changes concerning information security.
MEASURING TECHNOLOGICAL, ORGANIZATIONAL AND ENVIRONMENTAL FACTORS INFLUENCING...csandit
The main objective of this research is to identify the factors influencing the intentions to adopt
the public computing by the private sector firms. In this research the researcher examined the
ten factors influencing the cloud computing adoption using a proposed integrated model which
incorporates aspects of the Technology, Organization and Environment factors such as
Complexity, Compatibility, Security Concerns, Trialability, Cost Saving, Top Management
Support, Prior IT Experience, Organizational Readiness, Competitive Pressure and External
Support. In order to test influencing factors a survey was conducted and one hundred and
twenty two valid responses were received from IT decision makers from forty firms in different
industries. The results revealed that the Compatibility, Cost Saving, Trialability and External
Support are the main influential factors in the adoption intentions of public cloud computing.
Future research could be built on this study by developing different model for each industry
because each industry has unique characteristics that can influence the adoption of the
technological innovations.
A LITERATURE SURVEY AND ANALYSIS ON SOCIAL ENGINEERING DEFENSE MECHANISMS AND...IJNSA Journal
Social engineering attacks can be severe and hard to detect. Therefore, to prevent such attacks, organizations should be aware of social engineering defense mechanisms and security policies. To that end, the authors developed a taxonomy of social engineering defense mechanisms, designed a survey to measure employee awareness of these mechanisms, proposed a model of Social Engineering InfoSec Policies (SE-IPs), and designed a survey to measure the incorporation level of these SE-IPs. After analyzing the data from the first survey, the authors found that more than half of employees are not aware of social engineering attacks. The paper also analyzed a second set of survey data, which found that on average, organizations incorporated just over fifty percent of the identified formal SE-IPs. Such worrisome results show that organizations are vulnerable to social engineering attacks, and serious steps need to be taken to elevate awareness against these emerging security threats.
The slide has details on below points:
1. Introduction to Machine Learning
2. What are the challenges in acceptance of Machine Learning in Banks
3. How to overcome the challenges in adoption of Machine Learning in Banks
4. How to find new use cases of Machine Learning
5. Few current interesting use cases of Machine Learning
Please contact me (shekup@gmail.com) or connect with me on LinkedIn (https://www.linkedin.com/in/shekup/) for more explanation on ML and how it may help your business.
The slides are inspired by:
Survey & interviews done by me with Bankers & Technology Professionals
Presentation from Google NEXT 2017
Presentation by DATUM on Youtube
Royal Society Machine Learning
Big Data & Social Analytics Course from MIT & GetSmarter
Investment Thesis: Construction TechnologyJeffrey Bantam
The following presentation details my personal investment thesis on technology in the construction sector. Please feel free to reach out to me with any questions or comments!
Since I realized after posting the slideshow that my cover links didn't work - I've listed them here for reference:
Email: jeffreybantam@gmail.com
LinkedIn: https://www.linkedin.com/in/jeffrey-bantam-7ab54948/
Twitter: https://twitter.com/jeffreybantam
Website: https://jeffreybantam.com/
SECURETI: ADVANCED SDLC AND PROJECT MANAGEMENT TOOL FOR TI(PHILIPPINES)ijcsit
There are essential security considerations in the systems used by semiconductor companies like TI. Along
with other semiconductor companies, TI has recognized that IT security is highly crucial during web
application developers' system development life cycle (SDLC). The challenges faced by TI web developers
were consolidated via questionnaires starting with how risk management and secure coding can be
reinforced in SDLC; and how to achieve IT Security, PM and SDLC initiatives by developing a prototype
which was evaluated considering the aforementioned goals. This study aimed to practice NIST strategies
by integrating risk management checkpoints in the SDLC; enforce secure coding using static code analysis
tool by developing a prototype application mapped with IT Security goals, project management and SDLC
initiatives and evaluation of the impact of the proposed solution. This paper discussed how SecureTI was
able to satisfy IT Security requirements in the SDLC and PM phases.
There are essential security considerations in the systems used by semiconductor companies like TI. Along
with other semiconductor companies, TI has recognized that IT security is highly crucial during web
application developers' system development life cycle (SDLC). The challenges faced by TI web developers
were consolidated via questionnaires starting with how risk management and secure coding can be
reinforced in SDLC; and how to achieve IT Security, PM and SDLC initiatives by developing a prototype
which was evaluated considering the aforementioned goals. This study aimed to practice NIST strategies
by integrating risk management checkpoints in the SDLC; enforce secure coding using static code analysis
tool by developing a prototype application mapped with IT Security goals, project management and SDLC
initiatives and evaluation of the impact of the proposed solution. This paper discussed how SecureTI was
able to satisfy IT Security requirements in the SDLC and PM phases.
A SYSTEMATIC REVIEW ON MACHINE LEARNING INSIDER THREAT DETECTION MODELS, DATA...IJNSA Journal
Computers are crucial instruments providing a competitive edge to organizations that have adopted them. Their pervasive presence has presented a novel challenge to information security, specifically threats emanating from privileged employees. Various solutions have been tried to address the vice, but no exhaustive solution has been found. Due to their elusive nature, proactive strategies have been proposed of which detection using Machine Learning models has been favoured. The choice of algorithm, datasets and metrics are cornerstones of model performance and hence, need to be addressed. Although multiple studies on ML for insider threat detection have been done, none has provided a comprehensive analysis of algorithms, datasets and metrics for development of Insider Threat Detection models. This study conducts a comprehensive systematic literature review using reputable databases to answer the research questions posed. Search strings, inclusion and exclusion criteria were set for eligibility of articles published in the last decade.
the influence of machine language and data science in the emerging worldijtsrd
The study describes the machine learning language with respect to big data sciences. The process of machine learning has evolved to have grown significantly to progress in information science. This progress has led to conquer different domains and are capable of solving myriad problems and upgrading the applicative properties. Hence, the present study is drafted to highlight the importance of machine learning process and language. Anitha. S "The Influence of Machine Language and Data Science in the Emerging World" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-5 , August 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31907.pdf Paper Url :https://www.ijtsrd.com/engineering/computer-engineering/31907/the-influence-of-machine-language-and-data-science-in-the-emerging-world/anitha-s
ASCERTAINING THE INFORMATION AND COMMUNICATION TECHNOLOGY (ICT) MATURITY LEVE...ijait
Information and Communication Technology has indeed been the driving force in most economics of the
world owing to its versatility in integrating with most national sectors. Information and Communication
Technology (ICT) models have been developed with the sole aim of ascertaining the maturity level in
various economic sectors from the perspective of ICT. Due to the divergent impact of ICT in the Banking
sector in Nigeria; this research paper has attempted to ascertain the maturity level within the banking
sector using KochiKar Model: a Knowledge-driven ICT maturity model. The dataset for analysis was
obtained using structured interview approach spread across Ten (10) Nigeria banks, capturing 12
personnel’s each with an overall total of 120 respondents.The ICT maturity parameter indicators show
clearly that Application, Human Resource Infrastructure and Policy have varied ratio of: 65%, 46% , 30%
and 16%, respectively while the overall maturity index was captured at 0.40 (40%) falling into “BASIC”
level within the stages of Kochikar model measurement. These results have highlighted the need in
improving policies and infrastructures tremendously while applications and human resources can be
expanded gradually which will overall increase the maturity index level.
ASCERTAINING THE INFORMATION AND COMMUNICATION TECHNOLOGY (ICT) MATURITY LEVE...ijait
Information and Communication Technology has indeed been the driving force in most economics of the world owing to its versatility in integrating with most national sectors. Information and Communication Technology (ICT) models have been developed with the sole aim of ascertaining the maturity level in various economic sectors from the perspective of ICT. Due to the divergent impact of ICT in the Banking sector in Nigeria; this research paper has attempted to ascertain the maturity level within the banking sector using KochiKar Model: a Knowledge-driven ICT maturity model. The dataset for analysis was obtained using structured interview approach spread across Ten (10) Nigeria banks, capturing 12 personnel’s each with an overall total of 120 respondents.The ICT maturity parameter indicators show clearly that Application, Human Resource Infrastructure and Policy have varied ratio of: 65%, 46% , 30% and 16%, respectively while the overall maturity index was captured at 0.40 (40%) falling into “BASIC” level within the stages of Kochikar model measurement. These results have highlighted the need in improving policies and infrastructures tremendously while applications and human resources can be expanded gradually which will overall increase the maturity index level.
Requirements engineering (RE), as a part of the project development life cycle, has increasingly been
recognized as the key to ensure on-time, on-budget, and goal-based delivery of software projects. RE of big
data projects is even more crucial because of the rapid growth of big data applications over the past few
years. Data processing, being a part of big data RE, is an essential job in driving big data RE process
successfully. Business can be overwhelmed by data and underwhelmed by the information so, data
processing is very critical in big data projects. Employing traditional data processing techniques lacks the
invention of useful information because of the main characteristics of big data, including high volume,
velocity, and variety. Data processing can be benefited by process mining, and in turn, helps to increase
the productivity of the big data projects. In this paper, the capability of process mining in big data RE to
discover valuable insights and business values from event logs and processes of the systems has been
highlighted. Also, the proposed big data requirements engineering framework, named REBD, helps
software requirements engineers to eradicate many challenges of big data RE
Communication, culture, competency, and stakeholder that contribute to requi...IJECEIAES
In the context of software development, requirement engineering is one of the crucial phases that leads to software project success or failure. According to several disruptive changes in the software engineering landscape as well as the world’s challenge of virus pandemic, the provision of practical and innovative software applications is required. Therefore, issues resolution in requirement elicitation is potentially one of the key success factors resulting in enhanced quality of system requirement. The authors have striven to create new ways of requirement elicitation according to factor effects of communication, culture, competency, and stakeholder, by incorporating tools, processes, methods, and techniques to solve the problems comprehensively, and then proposed an adaptive and applicable conceptual framework. To illustrate these effects, the authors performed a literature review from the past 8 years, and then data analysis from interviews of 27 practitioners, observations and focus groups of software development in real-life projects.
An Investigation of Critical Failure Factors In Information Technology ProjectsIOSR Journals
Rate of failed projects in information technology system project remains high in comparison with other infrastructure or high technology projects. The objective of this paper is to determine and represent a broad range of potential failure factors during the implementation phase and cause of IS/IT Project defeat/failure. Challenges exist in order to achieve the projects goal successfully and to avoid the failure. In this research study, 12 articles were studied as significant contributions to analyze developing a list of critical failure factors of IT projects
Similar to Knowledge Management and Predictive Analytics in IT Project Risks (20)
‘Six Sigma Technique’ A Journey Through its Implementationijtsrd
The manufacturing industries all over the world are facing tough challenges for growth, development and sustainability in today’s competitive environment. They have to achieve apex position by adapting with the global competitive environment by delivering goods and services at low cost, prime quality and better price to increase wealth and consumer satisfaction. Cost Management ensures profit, growth and sustainability of the business with implementation of Continuous Improvement Technique like Six Sigma. This leads to optimize Business performance. The method drives for customer satisfaction, low variation, reduction in waste and cycle time resulting into a competitive advantage over other industries which did not implement it. The main objective of this paper ‘Six Sigma Technique A Journey Through Its Implementation’ is to conceptualize the effectiveness of Six Sigma Technique through the journey of its implementation. Aditi Sunilkumar Ghosalkar "‘Six Sigma Technique’: A Journey Through its Implementation" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64546.pdf Paper Url: https://www.ijtsrd.com/other-scientific-research-area/other/64546/‘six-sigma-technique’-a-journey-through-its-implementation/aditi-sunilkumar-ghosalkar
Edge Computing in Space Enhancing Data Processing and Communication for Space...ijtsrd
Edge computing, a paradigm that involves processing data closer to its source, has gained significant attention for its potential to revolutionize data processing and communication in space missions. With the increasing complexity and data volume generated by modern space missions, traditional centralized computing approaches face challenges related to latency, bandwidth, and security. Edge computing in space, involving on board processing and analysis of data, offers promising solutions to these challenges. This paper explores the concept of edge computing in space, its benefits, applications, and future prospects in enhancing space missions. Manish Verma "Edge Computing in Space: Enhancing Data Processing and Communication for Space Missions" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64541.pdf Paper Url: https://www.ijtsrd.com/computer-science/artificial-intelligence/64541/edge-computing-in-space-enhancing-data-processing-and-communication-for-space-missions/manish-verma
Dynamics of Communal Politics in 21st Century India Challenges and Prospectsijtsrd
Communal politics in India has evolved through centuries, weaving a complex tapestry shaped by historical legacies, colonial influences, and contemporary socio political transformations. This research comprehensively examines the dynamics of communal politics in 21st century India, emphasizing its historical roots, socio political dynamics, economic implications, challenges, and prospects for mitigation. The historical perspective unravels the intricate interplay of religious identities and power dynamics from ancient civilizations to the impact of colonial rule, providing insights into the evolution of communalism. The socio political dynamics section delves into the contemporary manifestations, exploring the roles of identity politics, socio economic disparities, and globalization. The economic implications section highlights how communal politics intersects with economic issues, perpetuating disparities and influencing resource allocation. Challenges posed by communal politics are scrutinized, revealing multifaceted issues ranging from social fragmentation to threats against democratic values. The prospects for mitigation present a multifaceted approach, incorporating policy interventions, community engagement, and educational initiatives. The paper conducts a comparative analysis with international examples, identifying common patterns such as identity politics and economic disparities. It also examines unique challenges, emphasizing Indias diverse religious landscape, historical legacy, and secular framework. Lessons for effective strategies are drawn from international experiences, offering insights into inclusive policies, interfaith dialogue, media regulation, and global cooperation. By scrutinizing historical epochs, contemporary dynamics, economic implications, and international comparisons, this research provides a comprehensive understanding of communal politics in India. The proposed strategies for mitigation underscore the importance of a holistic approach to foster social harmony, inclusivity, and democratic values. Rose Hossain "Dynamics of Communal Politics in 21st Century India: Challenges and Prospects" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64528.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/history/64528/dynamics-of-communal-politics-in-21st-century-india-challenges-and-prospects/rose-hossain
Assess Perspective and Knowledge of Healthcare Providers Towards Elehealth in...ijtsrd
Background and Objective Telehealth has become a well known tool for the delivery of health care in Saudi Arabia, and the perspective and knowledge of healthcare providers are influential in the implementation, adoption and advancement of the method. This systematic review was conducted to examine the current literature base regarding telehealth and the related healthcare professional perspective and knowledge in the Kingdom of Saudi Arabia. Materials and Methods This systematic review was conducted by searching 7 databases including, MEDLINE, CINHAL, Web of Science, Scopus, PubMed, PsycINFO, and ProQuest Central. Studies on healthcare practitioners telehealth knowledge and perspectives published in English in Saudi Arabia from 2000 to 2023 were included. Boland directed this comprehensive review. The researchers examined each connected study using the AXIS tool, which evaluates cross sectional systematic reviews. Narrative synthesis was used to summarise and convey the data. Results Out of 1840 search results, 10 studies were included. Positive outlook and limited knowledge among providers were seen across trials. Healthcare professionals like telehealth for its ability to improve quality, access, and delivery, save time and money, and be successful. Age, gender, occupation, and work experience also affect health workers knowledge. In Saudi Arabia, healthcare professionals face inadequate expert assistance, patient privacy, internet connection concerns, lack of training courses, lack of telehealth understanding, and high costs while performing telemedicine. Conclusions Healthcare practitioners telehealth perceptions and knowledge were examined in this systematic study. Its collection of concerned experts different personal attitudes and expertise would help enhance telehealths implementation in Saudi Arabia, develop its healthcare delivery alternative, and eliminate frequent problems. Badriah Mousa I Mulayhi | Dr. Jomin George | Judy Jenkins "Assess Perspective and Knowledge of Healthcare Providers Towards Elehealth in Saudi Arabia: A Systematic Review" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64535.pdf Paper Url: https://www.ijtsrd.com/medicine/other/64535/assess-perspective-and-knowledge-of-healthcare-providers-towards-elehealth-in-saudi-arabia-a-systematic-review/badriah-mousa-i-mulayhi
The Impact of Digital Media on the Decentralization of Power and the Erosion ...ijtsrd
The impact of digital media on the distribution of power and the weakening of traditional gatekeepers has gained considerable attention in recent years. The adoption of digital technologies and the internet has resulted in declining influence and power for traditional gatekeepers such as publishing houses and news organizations. Simultaneously, digital media has facilitated the emergence of new voices and players in the media industry. Digital medias impact on power decentralization and gatekeeper erosion is visible in several ways. One significant aspect is the democratization of information, which enables anyone with an internet connection to publish and share content globally, leading to citizen journalism and bypassing traditional gatekeepers. Another aspect is the disruption of conventional media industry business models, as traditional organizations struggle to adjust to the decrease in advertising revenue and the rise of digital platforms. Alternative business models, such as subscription models and crowdfunding, have become more prevalent, leading to the emergence of new players. Overall, the impact of digital media on the distribution of power and the weakening of traditional gatekeepers has brought about significant changes in the media landscape and the way information is shared. Further research is required to fully comprehend the implications of these changes and their impact on society. Dr. Kusum Lata "The Impact of Digital Media on the Decentralization of Power and the Erosion of Traditional Gatekeepers" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64544.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/political-science/64544/the-impact-of-digital-media-on-the-decentralization-of-power-and-the-erosion-of-traditional-gatekeepers/dr-kusum-lata
Online Voices, Offline Impact Ambedkars Ideals and Socio Political Inclusion ...ijtsrd
This research investigates the nexus between online discussions on Dr. B.R. Ambedkars ideals and their impact on social inclusion among college students in Gurugram, Haryana. Surveying 240 students from 12 government colleges, findings indicate that 65 actively engage in online discussions, with 80 demonstrating moderate to high awareness of Ambedkars ideals. Statistically significant correlations reveal that higher online engagement correlates with increased awareness p 0.05 and perceived social inclusion. Variations across colleges and a notable effect of college type on perceived social inclusion highlight the influence of contextual factors. Furthermore, the intersectional analysis underscores nuanced differences based on gender, caste, and socio economic status. Dr. Kusum Lata "Online Voices, Offline Impact: Ambedkar's Ideals and Socio-Political Inclusion - A Study of Gurugram District" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64543.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/political-science/64543/online-voices-offline-impact-ambedkars-ideals-and-sociopolitical-inclusion--a-study-of-gurugram-district/dr-kusum-lata
Problems and Challenges of Agro Entreprenurship A Studyijtsrd
Noting calls for contextualizing Agro entrepreneurs problems and challenges of the agro entrepreneurs and for greater attention to the Role of entrepreneurs in agro entrepreneurship research, we conduct a systematic literature review of extent research in agriculture entrepreneurship to overcome the study objectives of complications of agro entrepreneurs through various factors, Development of agriculture products is a key factor for the overall economic growth of agro entrepreneurs Agro Entrepreneurs produces firsthand large scale employment, utilizes the labor and natural resources, This research outlines the problems of Weather and Soil Erosions, Market price fluctuation, stimulates labor cost problems, reduces concentration of Price volatility, Dependency on Intermediaries, induces Limited Bargaining Power, and Storage and Transportation Costs. This paper mainly devoted to highlight Problems and challenges faced for the sustainable of Agro Entrepreneurs in India. Vinay Prasad B "Problems and Challenges of Agro Entreprenurship - A Study" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64540.pdf Paper Url: https://www.ijtsrd.com/other-scientific-research-area/other/64540/problems-and-challenges-of-agro-entreprenurship--a-study/vinay-prasad-b
Comparative Analysis of Total Corporate Disclosure of Selected IT Companies o...ijtsrd
Disclosure is a process through which a business enterprise communicates with external parties. A corporate disclosure is communication of financial and non financial information of the activities of a business enterprise to the interested entities. Corporate disclosure is done through publishing annual reports. So corporate disclosure through annual reports plays a vital role in the life of all the companies and provides valuable information to investors. The basic objectives of corporate disclosure is to give a true and fair view of companies to the parties related either directly or indirectly like owner, government, creditors, shareholders etc. in the companies act, provisions have been made about mandatory and voluntary disclosure. The IT sector in India is rapidly growing, the trend to invest in the IT sector is rising and employment opportunities in IT sectors are also increasing. Therefore the IT sector is expected to have fair, full and adequate disclosure of all information. Unfair and incomplete disclosure may adversely affect the entire economy. A research study on disclosure practices of IT companies could play an important role in this regard. Hence, the present research study has been done to study and review comparative analysis of total corporate disclosure of selected IT companies of India and to put forward overall findings and suggestions with a view to increase disclosure score of these companies. The researcher hopes that the present research study will be helpful to all selected Companies for improving level of corporate disclosure through annual reports as well as the government, creditors, investors, all business organizations and upcoming researcher for comparative analyses of level of corporate disclosure with special reference to selected IT companies. Dr. Vaibhavi D. Thaker "Comparative Analysis of Total Corporate Disclosure of Selected IT Companies of India" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64539.pdf Paper Url: https://www.ijtsrd.com/other-scientific-research-area/other/64539/comparative-analysis-of-total-corporate-disclosure-of-selected-it-companies-of-india/dr-vaibhavi-d-thaker
The Impact of Educational Background and Professional Training on Human Right...ijtsrd
This study investigated the impact of educational background and professional training on human rights awareness among secondary school teachers in the Marathwada region of Maharashtra, India. The key findings reveal that higher levels of education, particularly a master’s degree, and fields of study related to education, humanities, or social sciences are associated with greater human rights awareness among teachers. Additionally, both pre service teacher training and in service professional development programs focused on human rights education significantly enhance teacher’s knowledge, skills, and competencies in promoting human rights principles in their classrooms. Baig Ameer Bee Mirza Abdul Aziz | Dr. Syed Azaz Ali Amjad Ali "The Impact of Educational Background and Professional Training on Human Rights Awareness among Secondary School Teachers" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64529.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/education/64529/the-impact-of-educational-background-and-professional-training-on-human-rights-awareness-among-secondary-school-teachers/baig-ameer-bee-mirza-abdul-aziz
A Study on the Effective Teaching Learning Process in English Curriculum at t...ijtsrd
“One Language sets you in a corridor for life. Two languages open every door along the way” Frank Smith English as a foreign language or as a second language has been ruling in India since the period of Lord Macaulay. But the question is how much we teach or learn English properly in our culture. Is there any scope to use English as a language rather than a subject How much we learn or teach English without any interference of mother language specially in the classroom teaching learning scenario in West Bengal By considering all these issues the researcher has attempted in this article to focus on the effective teaching learning process comparing to other traditional strategies in the field of English curriculum at the secondary level to investigate whether they fulfill the present teaching learning requirements or not by examining the validity of the present curriculum of English. The purpose of this study is to focus on the effectiveness of the systematic, scientific, sequential and logical transaction of the course between the teachers and the learners in the perspective of the 5Es programme that is engage, explore, explain, extend and evaluate. Sanchali Mondal | Santinath Sarkar "A Study on the Effective Teaching Learning Process in English Curriculum at the Secondary Level of West Bengal" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd62412.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/education/62412/a-study-on-the-effective-teaching-learning-process-in-english-curriculum-at-the-secondary-level-of-west-bengal/sanchali-mondal
The Role of Mentoring and Its Influence on the Effectiveness of the Teaching ...ijtsrd
This paper reports on a study which was conducted to investigate the role of mentoring and its influence on the effectiveness of the teaching of Physics in secondary schools in the South West Region of Cameroon. The study adopted the convergent parallel mixed methods design, focusing on respondents in secondary schools in the South West Region of Cameroon. Both quantitative and qualitative data were collected, analysed separately, and the results were compared to see if the findings confirm or disconfirm each other. The quantitative analysis found that majority of the respondents 72 of Physics teachers affirmed that they had more experienced colleagues as mentors to help build their confidence, improve their teaching, and help them improve their effectiveness and efficiency in guiding learners’ achievements. Only 28 of the respondents disagreed with these statements. With majority respondents 72 agreeing with the statements, it implies that in most secondary schools, experienced Physics teachers act as mentors to build teachers’ confidence in teaching and improving students’ learning. The interview qualitative data analysis summarized how secondary school Principals use meetings with mentors and mentees to promote mentorship in the school milieu. This has helped strengthen teachers’ classroom practices in secondary schools in the South West Region of Cameroon. With the results confirming each other, the study recommends that mentoring should focus on helping teachers employ social interactions and instructional practices feedback and clarity in teaching that have direct measurable impact on students’ learning achievements. Andrew Ngeim Sumba | Frederick Ebot Ashu | Peter Agborbechem Tambi "The Role of Mentoring and Its Influence on the Effectiveness of the Teaching of Physics in Secondary Schools in the South West Region of Cameroon" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64524.pdf Paper Url: https://www.ijtsrd.com/management/management-development/64524/the-role-of-mentoring-and-its-influence-on-the-effectiveness-of-the-teaching-of-physics-in-secondary-schools-in-the-south-west-region-of-cameroon/andrew-ngeim-sumba
Design Simulation and Hardware Construction of an Arduino Microcontroller Bas...ijtsrd
This study primarily focuses on the design of a high side buck converter using an Arduino microcontroller. The converter is specifically intended for use in DC DC applications, particularly in standalone solar PV systems where the PV output voltage exceeds the load or battery voltage. To evaluate the performance of the converter, simulation experiments are conducted using Proteus Software. These simulations provide insights into the input and output voltages, currents, powers, and efficiency under different state of charge SoC conditions of a 12V,70Ah rechargeable lead acid battery. Additionally, the hardware design of the converter is implemented, and practical data is collected through operation, monitoring, and recording. By comparing the simulation results with the practical results, the efficiency and performance of the designed converter are assessed. The findings indicate that while the buck converter is suitable for practical use in standalone PV systems, its efficiency is compromised due to a lower output current. Chan Myae Aung | Dr. Ei Mon "Design Simulation and Hardware Construction of an Arduino-Microcontroller Based DC-DC High-Side Buck Converter for Standalone PV System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64518.pdf Paper Url: https://www.ijtsrd.com/engineering/mechanical-engineering/64518/design-simulation-and-hardware-construction-of-an-arduinomicrocontroller-based-dcdc-highside-buck-converter-for-standalone-pv-system/chan-myae-aung
Sustainable Energy by Paul A. Adekunte | Matthew N. O. Sadiku | Janet O. Sadikuijtsrd
Energy becomes sustainable if it meets the needs of the present without compromising the ability of future generations to meet their own needs. Some of the definitions of sustainable energy include the considerations of environmental aspects such as greenhouse gas emissions, social, and economic aspects such as energy poverty. Generally far more sustainable than fossil fuel are renewable energy sources such as wind, hydroelectric power, solar, and geothermal energy sources. Worthy of note is that some renewable energy projects, like the clearing of forests to produce biofuels, can cause severe environmental damage. The sustainability of nuclear power which is a low carbon source is highly debated because of concerns about radioactive waste, nuclear proliferation, and accidents. The switching from coal to natural gas has environmental benefits, including a lower climate impact, but could lead to delay in switching to more sustainable options. “Carbon capture and storage” can be built into power plants to remove the carbon dioxide CO2 emissions, but this technology is expensive and has rarely been implemented. Leading non renewable energy sources around the world is fossil fuels, coal, petroleum, and natural gas. Nuclear energy is usually considered another non renewable energy source, although nuclear energy itself is a renewable energy source, but the material used in nuclear power plants is not. The paper addresses the issue of sustainable energy, its attendant benefits to the future generation, and humanity in general. Paul A. Adekunte | Matthew N. O. Sadiku | Janet O. Sadiku "Sustainable Energy" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64534.pdf Paper Url: https://www.ijtsrd.com/engineering/electrical-engineering/64534/sustainable-energy/paul-a-adekunte
Concepts for Sudan Survey Act Implementations Executive Regulations and Stand...ijtsrd
This paper aims to outline the executive regulations, survey standards, and specifications required for the implementation of the Sudan Survey Act, and for regulating and organizing all surveying work activities in Sudan. The act has been discussed for more than 5 years. The Land Survey Act was initiated by the Sudan Survey Authority and all official legislations were headed by the Sudan Ministry of Justice till it was issued in 2022. The paper presents conceptual guidelines to be used for the Survey Act implementation and to regulate the survey work practice, standardizing the field surveys, processing, quality control, procedures, and the processes related to survey work carried out by the stakeholders and relevant authorities in Sudan. The conceptual guidelines are meant to improve the quality and harmonization of geospatial data and to aid decision making processes as well as geospatial information systems. The established comprehensive executive regulations will govern and regulate the implementation of the Sudan Survey Geomatics Act in all surveying and mapping practices undertaken by the Sudan Survey Authority SSA and state local survey departments for public or private sector organizations. The targeted standards and specifications include the reference frame, projection, coordinate systems, and the guidelines and specifications that must be followed in the field of survey work, processes, and mapping products. In the last few decades, there has been a growing awareness of the importance of geomatics activities and measurements on the Earths surface in space and time, together with observing and mapping the changes. In such cases, data must be captured promptly, standardized, and obtained with more accuracy and specified in much detail. The paper will also highlight the current situation in Sudan, the degree to which survey standards are used, the problems encountered, and the errors that arise from not using the standards and survey specifications. Kamal A. A. Sami "Concepts for Sudan Survey Act Implementations - Executive Regulations and Standards" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd63484.pdf Paper Url: https://www.ijtsrd.com/engineering/civil-engineering/63484/concepts-for-sudan-survey-act-implementations--executive-regulations-and-standards/kamal-a-a-sami
Towards the Implementation of the Sudan Interpolated Geoid Model Khartoum Sta...ijtsrd
The discussions between ellipsoid and geoid have invoked many researchers during the recent decades, especially during the GNSS technology era, which had witnessed a great deal of development but still geoid undulation requires more investigations. To figure out a solution for Sudans local geoid, this research has tried to intake the possibility of determining the geoid model by following two approaches, gravimetric and geometrical geoid model determination, by making use of GNSS leveling benchmarks at Khartoum state. The Benchmarks are well distributed in the study area, in which, the horizontal coordinates and the height above the ellipsoid have been observed by GNSS while orthometric heights were carried out using precise leveling. The Global Geopotential Model GGM represented in EGM2008 has been exploited to figure out the geoid undulation at the benchmarks in the study area. This is followed by a fitting process, that has been done to suit the geoid undulation data which has been computed using GNSS leveling data and geoid undulation inspired by the EGM2008. Two geoid surfaces were created after the fitting process to ensure that they are identical and both of them could be counted for getting the same geoid undulation with an acceptable accuracy. In this respect, statistical operation played an important role in ensuring the consistency and integrity of the model by applying cross validation techniques splitting the data into training and testing datasets for building the geoid model and testing its eligibility. The geometrical solution for geoid undulation computation has been utilized by applying straightforward equations that facilitate the calculation of the geoid undulation directly through applying statistical techniques for the GNSS leveling data of the study area to get the common equation parameters values that could be utilized to calculate geoid undulation of any position in the study area within the claimed accuracy. Both systems were checked and proved eligible to be used within the study area with acceptable accuracy which may contribute to solving the geoid undulation problem in the Khartoum area, and be further generalized to determine the geoid model over the entire country, and this could be considered in the future, for regional and continental geoid model. Ahmed M. A. Mohammed. | Kamal A. A. Sami "Towards the Implementation of the Sudan Interpolated Geoid Model (Khartoum State Case Study)" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd63483.pdf Paper Url: https://www.ijtsrd.com/engineering/civil-engineering/63483/towards-the-implementation-of-the-sudan-interpolated-geoid-model-khartoum-state-case-study/ahmed-m-a-mohammed
Activating Geospatial Information for Sudans Sustainable Investment Mapijtsrd
Sudan is witnessing an acceleration in the processes of development and transformation in the performance of government institutions to raise the productivity and investment efficiency of the government sector. The development plans and investment opportunities have focused on achieving national goals in various sectors. This paper aims to illuminate the path to the future and provide geospatial data and information to develop the investment climate and environment for all sized businesses, and to bridge the development gap between the Sudan states. The Sudan Survey Authority SSA is the main advisor to the Sudan Government in conducting surveying, mappings, designing, and developing systems related to geospatial data and information. In recent years, SSA made a strategic partnership with the Ministry of Investment to activate Geospatial Information for Sudans Sustainable Investment and in particular, for the preparation and implementation of the Sudan investment map, based on the directives and objectives of the Ministry of Investment MI in Sudan. This paper comes within the framework of activating the efforts of the Ministry of Investment to develop technical investment services by applying techniques adopted by the Ministry and its strategic partners for advancing investment processes in the country. Kamal A. A. Sami "Activating Geospatial Information for Sudan's Sustainable Investment Map" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd63482.pdf Paper Url: https://www.ijtsrd.com/engineering/information-technology/63482/activating-geospatial-information-for-sudans-sustainable-investment-map/kamal-a-a-sami
Educational Unity Embracing Diversity for a Stronger Societyijtsrd
In a rapidly changing global landscape, the importance of education as a unifying force cannot be overstated. This paper explores the crucial role of educational unity in fostering a stronger and more inclusive society through the embrace of diversity. By examining the benefits of diverse learning environments, the paper aims to highlight the positive impact on societal strength. The discussion encompasses various dimensions, from curriculum design to classroom dynamics, and emphasizes the need for educational institutions to become catalysts for unity in diversity. It highlights the need for a paradigm shift in educational policies, curricula, and pedagogical approaches to ensure that they are reflective of the diverse fabric of society. This paper also addresses the challenges associated with implementing inclusive educational practices and offers practical strategies for overcoming barriers. It advocates for collaborative efforts between educational institutions, policymakers, and communities to create a supportive ecosystem that promotes diversity and unity. Mr. Amit Adhikari | Madhumita Teli | Gopal Adhikari "Educational Unity: Embracing Diversity for a Stronger Society" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64525.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/education/64525/educational-unity-embracing-diversity-for-a-stronger-society/mr-amit-adhikari
Integration of Indian Indigenous Knowledge System in Management Prospects and...ijtsrd
The diversity of indigenous knowledge systems in India is vast and can vary significantly between different communities and regions. Preserving and respecting these knowledge systems is crucial for maintaining cultural heritage, promoting sustainable practices, and fostering cross cultural understanding. In this paper, an overview of the prospects and challenges associated with incorporating Indian indigenous knowledge into management is explored. It is found that IIKS helps in management in many areas like sustainable development, tourism, food security, natural resource management, cultural preservation and innovation, etc. However, IIKS integration with management faces some challenges in the form of a lack of documentation, cultural sensitivity, language barriers legal framework, etc. Savita Lathwal "Integration of Indian Indigenous Knowledge System in Management: Prospects and Challenges" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd63500.pdf Paper Url: https://www.ijtsrd.com/management/accounting-and-finance/63500/integration-of-indian-indigenous-knowledge-system-in-management-prospects-and-challenges/savita-lathwal
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The COVID 19 pandemic has highlighted the crucial need of preventive measures, with widespread use of face masks being a key method for slowing the viruss spread. This research investigates face mask identification using deep learning as a technological solution to be reducing the risk of coronavirus transmission. The proposed method uses state of the art convolutional neural networks CNNs and transfer learning to automatically recognize persons who are not wearing masks in a variety of circumstances. We discuss how this strategy improves public health and safety by providing an efficient manner of enforcing mask wearing standards. The report also discusses the obstacles, ethical concerns, and prospective applications of face mask detection systems in the ongoing fight against the pandemic. Dilip Kumar Sharma | Aaditya Yadav "DeepMask: Transforming Face Mask Identification for Better Pandemic Control in the COVID-19 Era" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64522.pdf Paper Url: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/64522/deepmask-transforming-face-mask-identification-for-better-pandemic-control-in-the-covid19-era/dilip-kumar-sharma
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Efficient and accurate data collection is paramount in clinical trials, and the design of Electronic Case Report Forms eCRFs plays a pivotal role in streamlining this process. This paper explores the integration of machine learning techniques in the design and implementation of eCRFs to enhance data collection efficiency. We delve into the synergies between eCRF design principles and machine learning algorithms, aiming to optimize data quality, reduce errors, and expedite the overall data collection process. The application of machine learning in eCRF design brings forth innovative approaches to data validation, anomaly detection, and real time adaptability. This paper discusses the benefits, challenges, and future prospects of leveraging machine learning in eCRF design for streamlined and advanced data collection in clinical trials. Dhanalakshmi D | Vijaya Lakshmi Kannareddy "Streamlining Data Collection: eCRF Design and Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd63515.pdf Paper Url: https://www.ijtsrd.com/biological-science/biotechnology/63515/streamlining-data-collection-ecrf-design-and-machine-learning/dhanalakshmi-d
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Knowledge Management and Predictive Analytics in IT Project Risks
1. @ IJTSRD | Available Online @ www.ijtsrd.com | Special Issue Publication | November 2018
ISSN No: 2456
International Journal of Trend in Scientific
Research and
International Conference on Advanced Engineering
and Information Technology (ICAEIT
Knowledge Managem
Analytics in
Mia Torres-Dela Cruz1
, Subashini A/P Ganapathy
1
Faculty of Engineering and Technology, Linton University College, Mantin, Malaysia
2
School of Electrical, Electronic and Mechanical Engineering, Institute Teknologi Pertama, Mantin, Malaysia
ABSTRACT
Knowledge management and predictive analytics are
considered to be unusual partners in today’s
technology. However, they can be very good tools
that would solve current problems in valuing data.
Predictive analytics has now become one of the
forecasting tools that is of huge help in information
management. Its application in IT project
development risk management is very important,
where a lot of raw data is involved with risk analysis
and prediction. The use of IT project risk management
as supported by knowledge management (KM) will
help increase the success rate of IT projects.
Knowledge management will bring about additional
value to the data needed. This paper presents the
usage of KM and predictive analytics to in
success ratings of projects by predicting the risks that
might happen during project development. It explores
how KM and predictive analytics can identify risks in
IT project development and give recommendations in
evaluating the risks that could affect successful
completion of IT projects.
Keywords: Knowledge Management, Predictive
Analytics, Big Data Analytics, Software Project, Risk
Prediction
1. INTRODUCTION
The predicament of IT projects today shows that
despite the new technologies, new processes, and
sophisticated systems today, IT development success
is still lower than expected. Still, billions of dollars
are being wasted because of project failures.
@ IJTSRD | Available Online @ www.ijtsrd.com | Special Issue Publication | November 2018
ISSN No: 2456 - 6470 | www.ijtsrd.com | Special Issue Publication
International Journal of Trend in Scientific
Research and Development (IJTSRD)
International Conference on Advanced Engineering
and Information Technology (ICAEIT-2017)
Knowledge Management and Predictive
Analytics in IT Project Risks
Subashini A/P Ganapathy2
, Noor Zuhaili Binti Mohd Yasin
Faculty of Engineering and Technology, Linton University College, Mantin, Malaysia
School of Electrical, Electronic and Mechanical Engineering, Institute Teknologi Pertama, Mantin, Malaysia
Knowledge management and predictive analytics are
considered to be unusual partners in today’s
technology. However, they can be very good tools
that would solve current problems in valuing data.
as now become one of the
forecasting tools that is of huge help in information
management. Its application in IT project
development risk management is very important,
where a lot of raw data is involved with risk analysis
ject risk management
as supported by knowledge management (KM) will
help increase the success rate of IT projects.
Knowledge management will bring about additional
value to the data needed. This paper presents the
usage of KM and predictive analytics to increase the
success ratings of projects by predicting the risks that
might happen during project development. It explores
how KM and predictive analytics can identify risks in
IT project development and give recommendations in
d affect successful
Knowledge Management, Predictive
Analytics, Big Data Analytics, Software Project, Risk
The predicament of IT projects today shows that
processes, and
sophisticated systems today, IT development success
is still lower than expected. Still, billions of dollars
are being wasted because of project failures.
The year 2013 has shown a stagnation of IT project
success [1]. Although that year w
rate of success started increasing, there is still the
need for IT projects to improve its success rate. The
nature of IT projects is that the entire process entails
high risks. Risks in IT projects are many, varied and
the probability and impact of these major risks are
mostly between low to high.
Risk identification and management are the main
concerns in every IT project.
analytics partnership will be a big help.
occur in each phase such as risk in
requirement, risk in design of the software, human
resource, technical, integration of modules, feasibility,
etc. As each project is unique and distinct, the risk
varies and measuring the risk is very important. It is
said that “if senior managers fail to detect such risks,
it is possible that such projects may collapse
completely” [2].
The use of IT project risk management requires
analysis of a lot of data from
analyses the uncertain events of the project, the
probability of it happening, its impact to the
organization and their causes and effects. Since there
are many risks involved in the IT project, specific data
is needed to be organized and accessed. Big data
predictive analytics could be potential tools for risk
management activity [2].
Why KM and risk analysis? Seemingly, there is a
vague relationship between
KM. In 2009, a study by Rodriquez and Edward [3]
@ IJTSRD | Available Online @ www.ijtsrd.com | Special Issue Publication | November 2018 P - 209
Special Issue Publication
International Conference on Advanced Engineering
ent and Predictive
Zuhaili Binti Mohd Yasin2
Faculty of Engineering and Technology, Linton University College, Mantin, Malaysia
School of Electrical, Electronic and Mechanical Engineering, Institute Teknologi Pertama, Mantin, Malaysia
stagnation of IT project
success [1]. Although that year was also the time the
rate of success started increasing, there is still the
need for IT projects to improve its success rate. The
nature of IT projects is that the entire process entails
high risks. Risks in IT projects are many, varied and
and impact of these major risks are
Risk identification and management are the main
project. KM and predictive
analytics partnership will be a big help. The risk can
occur in each phase such as risk in understanding the
requirement, risk in design of the software, human
resource, technical, integration of modules, feasibility,
etc. As each project is unique and distinct, the risk
varies and measuring the risk is very important. It is
managers fail to detect such risks,
it is possible that such projects may collapse
The use of IT project risk management requires
from the IT project. It
analyses the uncertain events of the project, the
lity of it happening, its impact to the
organization and their causes and effects. Since there
are many risks involved in the IT project, specific data
is needed to be organized and accessed. Big data
predictive analytics could be potential tools for risk
Why KM and risk analysis? Seemingly, there is a
risk management and
KM. In 2009, a study by Rodriquez and Edward [3]
2. International Journal of Trend in Scientific Research and Development (IJTSRD) | ISSN: 2456-647
@ IJTSRD | Available Online @ www.ijtsrd.com | Special Issue Publication | November 2018 P - 210
reasoned that through the use of knowledge
management processes, there can be improvement for
enterprise-wide implementation of risk management.
They claimed that application of KM processes to
enterprise risk management (ERM), has a perceived
value to ERM especially knowledge sharing and
quality of communication. However, the authors
concluded that although there exists a relationship
between ERM and knowledge sharing, it is
significantly low.
From the study above, further studies have opened up
to which this paper has taken advantage of. Since the
KM community has expressly matured, and new
technologies have cropped up since 2009 when
Rodriguez and Edward has done the study, the
perception of users may have changed. Also, the
inclusion of predictive analysis may increase the
relationship of KM and risk management.
As such, this paper explores Knowledge Management
(KM) combined with big data tools, specifically,
predictive analytics, in identifying risk data in IT
projects, and predicting which risks are most likely to
happen. It will show how these two technologies can
be used together to enhance the value of the data that
will be extracted and used to predict IT project risks
thereby improving the success rates for completing IT
projects. The result will be a risk framework that can
as a guideline for any IT project.
2. KM and Predictive Analysis Combined
The following are some literature that discuss
predictive risk analysis using KM processes in
different applications.
Knowledge exists when data and information are
applied (Becerra-Fernandez 2004 [4]; Beckett et al
2000[5]; Raisinghani et al 2002[6]). It has been
pointed out that big data, information and knowledge
are not the same and many researchers use the term
casually.
KM is very important in the 1990’s because it was
supposed to help organizations to have competitive
advantage and work effectively through sharing and
re-use of knowledge within the organization. In the
market place of e-business, KM initiatives are used to
systematically leverage information and expertise in
improving organizational responsiveness, data
delivery, innovation, competency and efficiency
(Stromquis and Samoff 2000[7]; Storey and Barnett
2000[8]; Desouza 2003[9]).
Turban and Jay (2001)[10], defined KM as a process
that helps organization like retail bank to identify,
select, organize, disseminate and transfer important
data and expertise information which are part of the
organizational memory resides within the
organization in an unstructured manner. This enables
effective and efficient problem solving, dynamic
learning, strategic planning and decision making in
big data.
Davenport et al. (2015)[11] has outlined a number of
potential benefits that organizations can achieve by
means of using big data relating to knowledge
management. Organizations focus on data flows as
opposed to stocks. It is also reported to have
increasing reliance on data scientists and product
developers rather than data analysts. Finally, they are
gradually detaching analytics away from IT tasks and
bringing into core businesses and operational
functions. In this manner, organizations can create
precious knowledge and exploit it for improved
knowledge management and competitive market
advantage. Thus, it can be inferred that big data and
analytics contributes towards real time knowledge
management. Big data is also deemed as a knowledge
asset and as such state-of-the-art knowledge
management has gained substantial impetus due to the
use of big data analytics for knowledge creation and
management.
McAfee et al (2012)[12] argue that one of the
objectives of knowledge management is to assimilate
data from different perspectives and analyze them to
extract value for effective decision making. This is
now a lot simpler to accumulate data from different
big data sources and apply big data analytics to
generate value from it so that organizations can use it
in decision making. For example, expedia.com which
is one of the foremost travel websites has invested a
large amount of money to use big data analytics to
generate valuable insights from the huge amount of
data that is generated from everyday use of the site.
On the other side, they analyze the market strategies
that attract the customers who visit their website and
establish a contributory relationship between their
adopted strategies and customers’ response. In this
manner, the company generates useful insights by
analyzing the big data and decides on how to use this
valuable information in improving business strategy.
3. International Journal of Trend in Scientific Research and Development (IJTSRD) | ISSN: 2456-647
@ IJTSRD | Available Online @ www.ijtsrd.com | Special Issue Publication | November 2018 P - 211
This serves as an unambiguous instance of how big
data is related to knowledge management. One of the
big challenge faced by industries today is that to come
up with this type of strategic information which help
them to make prompt, accurate, and effective tactical
decisions.
Credit card companies through big data analytics of
huge web monitoring and call center activities data
can make better decision regarding personalized
customer offers and improved business strategies. In
this manner, they are exploiting the concept of real
time knowledge generation from big data analytics
(Davenport et al. 2013) [11].
Research results obtained by Hair Jr.(2007)[13]
demonstrate that predictive analytics and big data
provide impressive support for emerging business
including product development and distribution (Hair
Jr et al 2007) [13]. The examples given above
evidently offer an indication of how big data and
knowledge management are interlinked and industries
are reaping benefits of big data by generating valuable
knowledge. Thus, it can be called as big data based on
knowledge management that takes full advantage of
big data analytics to enhance revenue generation and
sales and to reduce risk associated with incurred cost.
According to Fearnley (2013)[14], the reason why big
data’s predictive analytics is the focus today is
because in the recent financial crisis, many market
participants and regulators discovered that their data
architecture and IT systems could not support
monitoring and managing a broad spectrum of risks.
Regulators want more frequent reporting of a wide
variety of risks and expect firms to be able to respond
quickly to ad hoc requests. So to meet more timely
and detailed management and regulatory
requirements, firms are increasingly investing in open
source software solutions (such as Hadoop and Map
Reduce).
A most related study is by Rekha and Parvathi
(2015)[2], who made a survey of on Big Data
Analytics and its application to Software Project
Risks. The authors have concluded that big data
analytics’ tools can be used to predict the risk
encountered in software project and provide
recommendation for it. This paper further instigated in
practical way on how a big data tool – predictive
analytics - could be employed for project risk.
3. IT. Project Risks
There are so many risks involved with IT project
development. Risk identification and management is a
crucial part of IT project management. Florentine [1]
stated in her article that the trend for IT projects has
finally turned around. Accordingly, from 2013 the
failures in IT projects have increased up to 2016.
However, in 2017, there were indications that failures
in IT projects have decreased. This was corroborated
by Ebad [15], who said that in 2016, IT projects in
developing countries still suffer from high failure
rates. The paper made a thorough study of IT projects
in Saudi Arabia to discuss and identify what are the
causes of IT project failures of organizations in Saudi
Arabia.
Yazdanifard and Ratsiepe [16] claimed that “Poor risk
management as a whole is one of the major aspects
causing projects to collapse, and this has become an
obstacle to each and every project tht is being
developed nowadays.” Accordingly, poor risk
management in itself brings about new risks into the
project. This being said, there is an urgent need to find
a system that could more efficiently identify IT
project risks and mitigate so as to continuously
increase success rate in IT project development.
It is not a secret that even the simplest IT project can
get very complicated due to external factors but this is
hardly a comfort. A typical IT project has many inter-
dependent components and modifications and delays
in one component can easily affect everything else. In
many tech areas it is the same, so no matter how good
a project manager is, there are factors nobody can
predict or expect. Still, when one is experienced and
is aware of the common IT project risks, it is easy to
spot early the project risk symptoms and react
adequately before everything collapses [17].
Risk Management is the process of identifying,
assessing, responding to, monitoring, and reporting
risks. Risk identification will involve the project team,
appropriate stakeholders, and will include an
evaluation of environmental factors, organizational
culture and the project management plan including the
project scope. Careful attention will be given to the
project deliverables, assumptions, constraints, WBS,
cost/effort estimates, resource plan, and other key
project documents.
All risks identified will be assessed to identify the
range of possible project outcomes. Qualification will
4. International Journal of Trend in Scientific Research and Development (IJTSRD) | ISSN: 2456-647
@ IJTSRD | Available Online @ www.ijtsrd.com | Special Issue Publication | November 2018 P - 212
be used to determine which risks are the top risks to
pursue and respond to and which risks can be ignored.
The probability and impact of occurrence for each
identified risk will be assessed by the project
manager, with input from the project team.
Different authors have categorized IT project risks,
one is Stoy [17] who identified five common risks
including: mid-project scope change, delay in
schedule due to unexpected situation, technical
limitations, no problem reported, and key employee
quits. Another article [18] also identified five types of
risks in software development which are: new and
unproven technologies, user and functional
requirements, application and system architecture,
performance, and organizational. But Mar [19] was
more thorough, categorizing risks to 22 groups and
identifying specific risks for each category which
totals to 130 risks, sample shown in table 1.
Table 1: IT Project Risks 1-27
Table 2: IT Project Risks 28-46
Table 3: IT Project Risks 47-130
Table 4: IT Project Risks 51-82
5. International Journal of Trend in Scientific Research and Development (IJTSRD) | ISSN: 2456-647
@ IJTSRD | Available Online @ www.ijtsrd.com | Special Issue Publication | November 2018 P - 213
Table 4: IT Project Risks 51-82
4. Methodology
The study explored common practices of IT
development risk prediction and how these can be
improved with new tools using the predictive
analytics and knowledge management. It will use
predictive analytics particularly for project
development risks. The different variables of IT
development risks will likewise be studied and find
out what information, how much information and
when information are required and how these are
treated for predictive purposes.
The fact-finding techniques used in this study are
document review, benchmarking and simulation.
The project involved review of the different big data
predictive analytics and chose which one is suitable
for predicting risks in software development projects.
Among those considered were PredictIO and
RapidMiner. RapidMiner [20] was chosen because it
was easier to use and is also opensource.
The study used benchmarking methodology,
particularly the best practices where researchers chose
the organizations that are on the leading edge of the
industry. The researcher studied existing practices of
predictive analytics for software project risks and
captured best practices. Simulation, big data
predictive analytics tool will be applied to the data
from the simulation and measurements will be done
using an open source software called RapidMiner.
The resulting data will be used to design the risk
management.
The data gathered from all these fact finding
techniques would be collated, analyzed and evaluated
using RapidMiner to predict the risks.
The project used decision trees as the tool to predict
the outcome of risks taken from the selected software
development projects.
5. Data Analysis and Results
Developers and other stakeholders identify the unique
risks of the project. Data from the benchmarking that
was conducted were taken, and from these the most
probable risks for the specific project was extracted.
From the extracted risks, a comparison was made with
the identified unique risks and evaluation was done to
get further the impact, probability and cost values for
the specific risks. This was then simulated using the
RapidMiner software. The risk analysis tool that was
chosen from RapidMiner is the decision tree analysis
because it is used for determining net outcomes from
both positive and negative risk events since the
probability is 100% or 1.0 in any set of outcomes.
Data that have been extracted from benchmarking and
comparison with the current project under study. Data
were collated and encoded for further computation.
The project used MS Excel data to encode the data
and these data is converted it to RapidMiner
algorithm.
The following figures are samples of the RapidMiner
processes given the data that has been gathered using
the decision tree tool.
Figure 1: Decision Tree for scope too large Risk
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The next process is to set the decision tree. This is
connected to the imported Excel file, thus, the
connection to the first process which is read excel file.
The decision tree in Figure 1 is the result of analysis
of a file consisting of the risk of the product being too
large. The factors of the risk are being considered too
large, binomial type, number of team
members/employees working on the project, numeric
type, priority, multi-choice, and probability, numeric.
The consideration that the project is too large is set as
the label and the rest are attributes.
The decision tree shows the decision as to whether it
is considered too large or not, given the probability
and the priority. From the diagram, when the
probability is less or equal to 84, it is deemed a large
product. Greater than 84 would depend on the
priority, if it is high, then it is not large, low priority is
yes, it is a large product. As for medium priority,
when the probability is greater than 68 then it is no,
otherwise, it is yes.
6. KM Framework in Risk Management
As predictive analytics are used in the procedure of
risk management, KM processes are utilized as
strategies in IT project risk management. Based on
Barquin’s [21] KM framework, the following matrix,
in table 3, was adapted as risk management guidelines
for IT projects.
Table 3: KM Process Framework for Risk Management
KM Process Risk Management
1. Capture tacit
knowledge and
make it explicit.
Knowledge of risks and other things important for the project shouldn’t be
exclusively kept by individuals who may not stay with the team. They should be
shared so other people within the team may also use them for leverage.
2. Identify and nurture
communities of
practice.
Everyone must be able to share information of what they do and how they do it so
that in their absence someone can still do their job.
3. Find and
disseminate best
practices.
Benchmark from other organizations to learn practices that can be adapted when
applicable to the project.
4. Develop locators of
both experts and
expertise.
Keep and share a record and locator for experts for people in the project team to
contact when they need them for consultation.
5. Feature
collaboration tools
and resources.
Enhance information sharing specially about risk management by empowering
project team members with collaboration tools.
6. Implement
enterprise portals as
gateways to
corporate
knowledge.
Create and implement organization-wide portals for easy to reach knowledge on
security, emergency response, and compliance to save time from gathering data or
searching for information and documents.
7. Have clear
taxonomies for
major knowledge
domains.
Strengthen taxonomies and naming conventions to be able to find and access
relevant documents and other contents easily when truly needed. Without such is
to bring in more risks into projects and processes.
8. Have a solid
enterprise IT
architecture.
Systems and processes must be a perfect fit and must have a sturdy IT
architecture, preferably as services to be invoked through an architecture that is
service-oriented.
9. Build robust data
warehousing and
business intelligence
architectures.
Data warehouses can be extremely powerful platforms for analysis and report
generators. When implementing and utilizing risk management systems they are
helpful to analyze trends and report unusual patterns of behavior from usage and
access data.
10. Focus on knowledge
about the customer.
Helps the organization deal with customers and risk management focus
stakeholders such as, users of the systems, people who are potential hackers,
suppliers, experts, employees, and other. Knowing who they are is essential for
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authentication and verification, but so is knowing their preferences and other
attributes in serving the legitimate ones better and preempting the bad guys from
doing harm.
11. Use storytelling as a
springboard to
action.
Nothing captures attention better than a story. Witness the attention to risk
management that the VA incident has generated. The power of the narrative
should be harnessed to move enterprises to action when and where it is needed in
the context of managing risk.
12. Assure culture
rewards knowledge
sharing.
If good security practices are to be disseminated and shared, if retiring employees
need to pass on what they know about emergency response or compliance, there
must have a corporate culture that actively rewards such open behavior. Avoid
knowledge hoarding as a common practice for job protection.
13. Focus the enterprise
on learning.
Learning is the acquisition of knowledge and the organization must focus on this
to constantly bring in new knowledge. This is because of emerging new threats
and new tools to address them.
14. Provide the
leadership to make
KM a priority.
Leaders must make KM a priority and use KM techniques to assess and mitigate
risks. Support from the top is essential.
6. Conclusion
Even today in the advent of advanced technologies,
still a large percentage of IT project developments
have failed. This is largely due to lack of management
of resources and the large part is not being able to
understand and avoid the risks that a ny project would
encounter. In every IT project, a lot of risks are
encountered. Because of the large amount of data to
be analyzed, predictive analytics is a very good tool to
use in order to forecast what might happen and the
risks may be mitigated or controlled before it will
happen. Added to that, the use of KM processes
would help in managing the risks.
Predictive analytics combined with KM are helpful
tools to predict the occurrence of risks and would be
important information to ensure the success of IT
projects. The use of software tools such as
RapidMiner is an efficient way to use predictive
analytics to evaluate and predict the risks in IT
projects.
The project has produced an efficient way to predict
the risks that are encountered by IT projects and a KM
framework is adapted. Future studies in this topic may
be done but using different methods where predictive
analytics and KM may also be used.
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