This paper analyzes the effect of Information Technology on professionals, academicians and students in
perspective of their relations, education, job purpose, health, entertainment and electronic business that
can bring changes in society. Technology can have both positive and negative consequences for people of
different walks of life at different times. The need is to understand the true impact of internet on the society
so that people can start thinking and build a healthy society. In this paper, an empirical study is considered
60 persons; a causal loop model is formed relating the parameters on the basis of data collected. These
parameters are used to form the fuzzy dynamic model to analyze the effect of the internet on the society.
The model is analyzed and suitable solutions are proposed to counter the negative effect of internet on our
society.
FACIAL AGE ESTIMATION USING TRANSFER LEARNING AND BAYESIAN OPTIMIZATION BASED...sipij
Â
Age estimation of unrestricted imaging circumstances has attracted an augmented recognition as it is
appropriate in several real-world applications such as surveillance, face recognition, age synthesis, access
control, and electronic customer relationship management. Current deep learning-based methods have
displayed encouraging performance in age estimation field. Males and Females have a variable type of
appearance aging pattern; this results in age differently. This fact leads to assuming that using gender
information may improve the age estimator performance. We have proposed a novel model based on
Gender Classification. A Convolutional Neural Network (CNN) is used to get Gender Information, then
Bayesian Optimization is applied to this pre-trained CNN when fine-tuned for age estimation task.
Bayesian Optimization reduces the classification error on the validation set for the pre-trained model.
Extensive experiments are done to assess our proposed model on two data sets: FERET and FG-NET. The
experimentsâ result indicates that using a pre-trained CNN containing Gender Information with Bayesian
Optimization outperforms the state of the arts on FERET and FG-NET data sets with a Mean Absolute
Error (MAE) of 1.2 and 2.67 respectively.
Multi-objective NSGA-II based community detection using dynamical evolution s...IJECEIAES
Â
Community detection is becoming a highly demanded topic in social networking-based applications. It involves finding the maximum intraconnected and minimum inter-connected sub-graphs in given social networks. Many approaches have been developed for communityâs detection and less of them have focused on the dynamical aspect of the social network. The decision of the community has to consider the pattern of changes in the social network and to be smooth enough. This is to enable smooth operation for other community detection dependent application. Unlike dynamical community detection Algorithms, this article presents a non-dominated aware searching Algorithm designated as non-dominated sorting based community detection with dynamical awareness (NDS-CD-DA). The Algorithm uses a non-dominated sorting genetic algorithm NSGA-II with two objectives: modularity and normalized mutual information (NMI). Experimental results on synthetic networks and real-world social network datasets have been compared with classical genetic with a single objective and has been shown to provide superiority in terms of the domination as well as the convergence. NDS-CD-DA has accomplished a domination percentage of 100% over dynamic evolutionary community searching DECS for almost all iterations.
Understanding Userâs Acceptance of Personal Cloud Computing: Using the Techno...Maurice Dawson
Â
Personal Cloud Computing (PCC) is a rapidly growing technology, addressing the market demand of individual users for access to available and reliable resources. But like other new technologies, concerns and issues have surfaced with the adoption of PCC. Users deciding whether to adopt PCC may be concerned about the ease of use, usefulness, or security risks in the cloud. Negative attitudes toward using a technology have been found to negatively impact the success of that technology. The purpose of this study was to understand usersâ acceptance of PCC. The population sample consisted of individual users within the United States between 18 and 80 years of age. The theoretical framework utilized in this study was based on the technology acceptance model (TAM). A web survey was conducted to assess the measurement and understanding of patterns demonstrated by participants. Our results shows that in spite of the potential benefits of PCC, security and privacy risks are deterring many users from moving towards PCC.
Extending UTAUT to explain social media adoption by microbusinessesDebashish Mandal
Â
This paper establishes inadequacies of the Unified Theory of Acceptance and Use of Technology (UTAUT) theory to explain social media adoption by microbusinesses. Literature review confirms the explaining power of UTAUT in variety of technology adoption by businesses. This paper uses UTAUT theory to implement social media technology in microbusinesses. Canonical action research method is adopted to introduce social media in microbusinesses. A post positivist approach is used to report the results based on a predetermined premise. It was found that the major constructs of performance and effort expectancy played insignificant role in establishing behavioural and adoption intention of social media by microbusinesses. Social influence and facilitating condition did not influence the behavioural intentions of the microbusiness owners. Individual characteristics and codification effort dominated the use behaviour. Goal of gaining customers leads to behavioural modification resulting in replacing of behavioural intention with goals as a superior method of predicting adoption behaviour within the context of microbusinesses. This paper extends the UTAUT to explain social media adoption in microbusinesses.
DEEP-LEARNING-BASED HUMAN INTENTION PREDICTION WITH DATA AUGMENTATIONijaia
Â
Data augmentation has been broadly applied in training deep-learning models to increase the diversity of
data. This study ingestigates the effectiveness of different data augmentation methods for deep-learningbased human intention prediction when only limited training data is available. A human participant pitches
a ball to nine potential targets in our experiment. We expect to predict which target the participant pitches
the ball to. Firstly, the effectiveness of 10 data augmentation groups is evaluated on a single-participant
data set using RGB images. Secondly, the best data augmentation method (i.e., random cropping) on the
single-participant data set is further evaluated on a multi-participant data set to assess its generalization
ability. Finally, the effectiveness of random cropping on fusion data of RGB images and optical flow is
evaluated on both single- and multi-participant data sets. Experiment results show that: 1) Data
augmentation methods that crop or deform images can improve the prediction performance; 2) Random
cropping can be generalized to the multi-participant data set (prediction accuracy is improved from 50%
to 57.4%); and 3) Random cropping with fusion data of RGB images and optical flow can further improve
the prediction accuracy from 57.4% to 63.9% on the multi-participant data set.
Development of durian leaf disease detection on Android device IJECEIAES
Â
Durian is exceedingly abundant in the Philippines, providing incomes for smallholder farmers. But amidst these things, durian is still vulnerable to different plant diseases that can cause significant economic loss in the agricultural industry. The conventional way of dealing plant disease detection is through naked-eye observation done by experts. To control such diseases using the old method is extensively laborious, time-consuming and costly especially in dealing with large fields. Hence, the proponentâs objective of this study is to create a standalone mobile app for durian leaf disease detection using the transfer learning approach. In this approach, the chosen network MobileNets, is pre-trained with a large scale of general datasets namely ImageNet to effective function as a generic template for visual processing. The pre-trained network transfers all the learned parameters and set as a feature extractor for the target task to be executed. Four health conditions are addressed in this study, 10 per classification with a total of 40 samples tested to evaluate the accuracy of the system. The result showed 90% in overall accuracy for detecting algalspot, cercospora, leaf discoloration and healthy leaf.
FACIAL AGE ESTIMATION USING TRANSFER LEARNING AND BAYESIAN OPTIMIZATION BASED...sipij
Â
Age estimation of unrestricted imaging circumstances has attracted an augmented recognition as it is
appropriate in several real-world applications such as surveillance, face recognition, age synthesis, access
control, and electronic customer relationship management. Current deep learning-based methods have
displayed encouraging performance in age estimation field. Males and Females have a variable type of
appearance aging pattern; this results in age differently. This fact leads to assuming that using gender
information may improve the age estimator performance. We have proposed a novel model based on
Gender Classification. A Convolutional Neural Network (CNN) is used to get Gender Information, then
Bayesian Optimization is applied to this pre-trained CNN when fine-tuned for age estimation task.
Bayesian Optimization reduces the classification error on the validation set for the pre-trained model.
Extensive experiments are done to assess our proposed model on two data sets: FERET and FG-NET. The
experimentsâ result indicates that using a pre-trained CNN containing Gender Information with Bayesian
Optimization outperforms the state of the arts on FERET and FG-NET data sets with a Mean Absolute
Error (MAE) of 1.2 and 2.67 respectively.
Multi-objective NSGA-II based community detection using dynamical evolution s...IJECEIAES
Â
Community detection is becoming a highly demanded topic in social networking-based applications. It involves finding the maximum intraconnected and minimum inter-connected sub-graphs in given social networks. Many approaches have been developed for communityâs detection and less of them have focused on the dynamical aspect of the social network. The decision of the community has to consider the pattern of changes in the social network and to be smooth enough. This is to enable smooth operation for other community detection dependent application. Unlike dynamical community detection Algorithms, this article presents a non-dominated aware searching Algorithm designated as non-dominated sorting based community detection with dynamical awareness (NDS-CD-DA). The Algorithm uses a non-dominated sorting genetic algorithm NSGA-II with two objectives: modularity and normalized mutual information (NMI). Experimental results on synthetic networks and real-world social network datasets have been compared with classical genetic with a single objective and has been shown to provide superiority in terms of the domination as well as the convergence. NDS-CD-DA has accomplished a domination percentage of 100% over dynamic evolutionary community searching DECS for almost all iterations.
Understanding Userâs Acceptance of Personal Cloud Computing: Using the Techno...Maurice Dawson
Â
Personal Cloud Computing (PCC) is a rapidly growing technology, addressing the market demand of individual users for access to available and reliable resources. But like other new technologies, concerns and issues have surfaced with the adoption of PCC. Users deciding whether to adopt PCC may be concerned about the ease of use, usefulness, or security risks in the cloud. Negative attitudes toward using a technology have been found to negatively impact the success of that technology. The purpose of this study was to understand usersâ acceptance of PCC. The population sample consisted of individual users within the United States between 18 and 80 years of age. The theoretical framework utilized in this study was based on the technology acceptance model (TAM). A web survey was conducted to assess the measurement and understanding of patterns demonstrated by participants. Our results shows that in spite of the potential benefits of PCC, security and privacy risks are deterring many users from moving towards PCC.
Extending UTAUT to explain social media adoption by microbusinessesDebashish Mandal
Â
This paper establishes inadequacies of the Unified Theory of Acceptance and Use of Technology (UTAUT) theory to explain social media adoption by microbusinesses. Literature review confirms the explaining power of UTAUT in variety of technology adoption by businesses. This paper uses UTAUT theory to implement social media technology in microbusinesses. Canonical action research method is adopted to introduce social media in microbusinesses. A post positivist approach is used to report the results based on a predetermined premise. It was found that the major constructs of performance and effort expectancy played insignificant role in establishing behavioural and adoption intention of social media by microbusinesses. Social influence and facilitating condition did not influence the behavioural intentions of the microbusiness owners. Individual characteristics and codification effort dominated the use behaviour. Goal of gaining customers leads to behavioural modification resulting in replacing of behavioural intention with goals as a superior method of predicting adoption behaviour within the context of microbusinesses. This paper extends the UTAUT to explain social media adoption in microbusinesses.
DEEP-LEARNING-BASED HUMAN INTENTION PREDICTION WITH DATA AUGMENTATIONijaia
Â
Data augmentation has been broadly applied in training deep-learning models to increase the diversity of
data. This study ingestigates the effectiveness of different data augmentation methods for deep-learningbased human intention prediction when only limited training data is available. A human participant pitches
a ball to nine potential targets in our experiment. We expect to predict which target the participant pitches
the ball to. Firstly, the effectiveness of 10 data augmentation groups is evaluated on a single-participant
data set using RGB images. Secondly, the best data augmentation method (i.e., random cropping) on the
single-participant data set is further evaluated on a multi-participant data set to assess its generalization
ability. Finally, the effectiveness of random cropping on fusion data of RGB images and optical flow is
evaluated on both single- and multi-participant data sets. Experiment results show that: 1) Data
augmentation methods that crop or deform images can improve the prediction performance; 2) Random
cropping can be generalized to the multi-participant data set (prediction accuracy is improved from 50%
to 57.4%); and 3) Random cropping with fusion data of RGB images and optical flow can further improve
the prediction accuracy from 57.4% to 63.9% on the multi-participant data set.
Development of durian leaf disease detection on Android device IJECEIAES
Â
Durian is exceedingly abundant in the Philippines, providing incomes for smallholder farmers. But amidst these things, durian is still vulnerable to different plant diseases that can cause significant economic loss in the agricultural industry. The conventional way of dealing plant disease detection is through naked-eye observation done by experts. To control such diseases using the old method is extensively laborious, time-consuming and costly especially in dealing with large fields. Hence, the proponentâs objective of this study is to create a standalone mobile app for durian leaf disease detection using the transfer learning approach. In this approach, the chosen network MobileNets, is pre-trained with a large scale of general datasets namely ImageNet to effective function as a generic template for visual processing. The pre-trained network transfers all the learned parameters and set as a feature extractor for the target task to be executed. Four health conditions are addressed in this study, 10 per classification with a total of 40 samples tested to evaluate the accuracy of the system. The result showed 90% in overall accuracy for detecting algalspot, cercospora, leaf discoloration and healthy leaf.
PSO OPTIMIZED INTERVAL TYPE-2 FUZZY DESIGN FOR ELECTIONS RESULTS PREDICTIONijfls
Â
Interval type-2 fuzzy logic systems (IT2FLSs), have recently shown great potential in various applications with dynamic uncertainties. It is believed that additional degree of uncertainty provided by IT2FL allows for better representation of the uncertainty and vagueness present in prediction models. However, determining the parameters of the membership functions of IT2FL is important for providing optimum
performance of the system. Particle Swarm Optimization (PSO) has attracted the interest of researchers due to their simplicity, effectiveness and efficiency in solving real-world optimization problems. In this paper, a novel optimal IT2FLS is designed, applied for predicting winning chances in elections. PSO is
used as an optimized algorithm to tune the parameter of the primary membership function of the IT2FL to improve the performance and increase the accuracy of the IT2F set. Simulation results show the superiority of the PSO-IT2FL to the similar non-optimal IT2FL system with an increase in the prediction.
A Comparative Analysis of Data Privacy and Utility Parameter Adjustment, Usin...Kato Mivule
Â
Kato Mivule, Claude Turner, "A Comparative Analysis of Data Privacy and Utility Parameter Adjustment, Using Machine Learning Classification as a Gauge", Procedia Computer Science, Volume 20, 2013, Pages 414-419, Baltimore MD, USA
FACTORS INFLUENCING THE ADOPTION OF E-GOVERNMENT SERVICES IN PAKISTANMuhammad Ahmad
Â
E-government provides opportunities to deliver various services more effectively and better serve citizens. In developing countries, e-government initiatives provide services that have been previously inaccessible to their citizens. However, e-government initiatives in developing countries are still in their infancy and face a wide range of barriers that restrict wide-spread use. Like many other developing countries, Pakistan has a low level of e-government services adoption. Previous research has investigated e-government services in developing countries from the organizational perspective. However, the research stream suffers from an absence of studies that have investigated e-government from a citizenâs perspective. The success of e-government services depends on government support as well as on citizenâs adoption. This paper aims to fill this gap by exploring the challenges and barriers of e-government services from the userâs perspective. In this study, an amended version of the UTAUT model is used to investigate the factors influencing the uptake of e-government services in Pakistan. The results show that the factors influencing the adoption of e-government services in Pakistan are related to ease of use, usefulness, social influence, technological issues, lack of awareness, data privacy, and trust. Implications for e-businesses and government policy decision makers are also considered in this study.
EXTENSION OF TECHNOLOGY ACCEPTANCE MODEL (TAM): A STUDY ON INDIAN INTERNET BA...IAEME Publication
Â
Internet banking plays significant role in the development of banking business in our country. An application of electronic service brings predominant changes in the way of doing banking transactions. In simpler terms, internet banking refers to banking through bankâs website with the help of internet connection. Internet banking provides lot of benefits to the customers as well as the banks. Internet banking provides different kinds of services to the customers in the form checking balances, account statement, pay utility bills etc
Analysis of the User Acceptance for Implementing ISO/IEC 27001:2005 in Turkis...IJMIT JOURNAL
Â
This study aims to develop a model for the user acceptance for implementing the information security standard (i.e. ISO 27001) in Turkish public organizations. The results of the surveys performed in Turkey reveal that the legislation on information security public which organizations have to obey is significantly related with the user acceptance during ISO 27001 implementation process. The fundamental components of our user acceptance model are perceived usefulness, attitude towards use, social norms, and performance expectancy.
The internet of things is an emerging technology that is currently present in most processes and devices, allowing to improve the quality of life of people and facilitating the access to specific information and services. The main purpose of the present article is to offer a general overview of internet of things, based on the analysis of recently published work. The added value of this article lies in the analysis of the main recent publications and the diversity of applications of internet of things technology. As a result of the analysis of the current literature, internet of things technology stands out as a facilitator in business and industrial performance but above all in improving the quality of life. As a conclusion to this document, the internet of things is a technology that can overcome the challenges in terms of security, processing capacity and data mobility, as long as the development related to other technologies follows its expected course.
Antecedents of Knowledge Management Practices: Case of Malaysian PractitionersjournalBEEI
Â
In this paper, we investigated the knowledge management (KM) behavior of executives in Malaysia who work in different sectors and involved in Information Technology (IT) related fields. We proposed a conceptual framework based on the Theory of Reasoned Action (TRA), the Theory of Planned Behavior (TPB) and Unified Theory of Acceptance and Use of Technology (UTAUT) to study their intention and involvement in KM initiatives. The knowledge creation theory (SECI process) was employed to operationalize KM intention and KM behavior. We proposed six independent variables that represent the social-cultural nature of KM as the antecedence of KM intention. These variables are trust, management support, decentralization, IT support, performance expectancy (PE), and effort expectancy (EE). Seventy-four executives from both private and government-linked organizations responded to our online questionnaire. SmartPLS3 was used to run the analysis. The reliability was ensured with the factor loadings, Cronbachâs alpha, Composite Reliability (CR) that met the fit requirement of above 0.6, 0.7 and 0.7 respectively. The convergent validity was confirmed through average variance extracted (AVE) that met the fit requirement of above 0.5. The discriminant validity was assessed by using Fornell and Larckerâs criterion. Finally, the structural model confirmed that only PE of KM, and EE of KM are the significant predictors of KM intention and the KM intention significantly predicts KM behavior. The implications of the findings are discussed in detail at the end of the paper.
MOVIE SUCCESS PREDICTION AND PERFORMANCE COMPARISON USING VARIOUS STATISTICAL...ijaia
Â
Movies are among the most prominent contributors to the global entertainment industry today, and they
are among the biggest revenue-generating industries from a commercial standpoint. It's vital to divide
films into two categories: successful and unsuccessful. To categorize the movies in this research, a variety
of models were utilized, including regression models such as Simple Linear, Multiple Linear, and Logistic
Regression, clustering techniques such as SVM and K-Means, Time Series Analysis, and an Artificial
Neural Network. The models stated above were compared on a variety of factors, including their accuracy
on the training and validation datasets as well as the testing dataset, the availability of new movie
characteristics, and a variety of other statistical metrics. During the course of this study, it was discovered
that certain characteristics have a greater impact on the likelihood of a film's success than others. For
example, the existence of the genre action may have a significant impact on the forecasts, although another
genre, such as sport, may not. The testing dataset for the models and classifiers has been taken from the
IMDb website for the year 2020. The Artificial Neural Network, with an accuracy of 86 percent, is the best
performing model of all the models discussed.
Towards A Differential Privacy and Utility Preserving Machine Learning Classi...Kato Mivule
Â
Kato Mivule, Claude Turner, Soo-Yeon Ji, "Towards A Differential Privacy and Utility Preserving Machine Learning Classifier", Procedia Computer Science (Complex Adaptive Systems), 2012, Pages 176-181, Washington DC, USA.
Data mining and machine learning have become a vital part of crime detection and prevention. In this
research, we use WEKA, an open source data mining software, to conduct a comparative study between the
violent crime patterns from the Communities and Crime Unnormalized Dataset provided by the University
of California-Irvine repository and actual crime statistical data for the state of Mississippi that has been
provided by neighborhoodscout.com. We implemented the Linear Regression, Additive Regression, and
Decision Stump algorithms using the same finite set of features, on the Communities and Crime Dataset.
Overall, the linear regression algorithm performed the best among the three selected algorithms. The scope
of this project is to prove how effective and accurate the machine learning algorithms used in data mining
analysis can be at predicting violent crime patterns.
Applying Data Privacy Techniques on Published Data in UgandaKato Mivule
Â
Kato Mivule, Claude Turner, "Applying Data Privacy Techniques on Published Data in Uganda", Proceedings of the 2012 International Conference on e-Learning, e-Business, Enterprise Information Systems, and e-Government (EEE 2012), Pages 110-115, Las Vegas, NV, USA.
Kato Mivule - Utilizing Noise Addition for Data Privacy, an OverviewKato Mivule
Â
Kato Mivule, "Utilizing Noise Addition for Data Privacy, an Overview", Proceedings of the International Conference on Information and Knowledge Engineering (IKE 2012), Pages 65-71, Las Vegas, NV, USA.
A comprehensive survey of link mining and anomalies detectioncsandit
Â
This survey introduces the emergence of link mining and its relevant application to detect
anomalies which can include events that are unusual, out of the ordinary or rare, unexpected
behaviour, or outliers.
An approach for self creating software code in bionets with artificial embryo...eSAT Publishing House
Â
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
An Investigation of Data Privacy and Utility Preservation Using KNN Classific...Kato Mivule
Â
Kato Mivule and Claude Turner, An Investigation of Data Privacy and Utility Preservation Using KNN Classification as a Gauge, International Conference on Information and Knowledge Engineering (IKE 2013), July 22-25, Pages 203-204, Las Vegas, NV, USA
INFORMATION SATURATION IN MULTISPECTRAL PIXEL LEVEL IMAGE FUSIONIJCI JOURNAL
Â
The availability of imaging sensors operating in multiple spectral bands has led to the requirement of
image fusion algorithms that would combine the image from these sensors in an efficient way to give an
image that is more informative as well as perceptible to human eye. Multispectral image fusion is the
process of combining images from different spectral bands that are optically acquired. In this paper, we
used a pixel-level image fusion based on principal component analysis that combines satellite images of the
same scene from seven different spectral bands. The purpose of using principal component analysis
technique is that it is best method for Grayscale image fusion and gives better results. The main aim of
PCA technique is to reduce a large set of variables into a small set which still contains most of the
information that was present in the large set. The paper compares different parameters namely, entropy,
standard deviation, correlation coefficient etc. for different number of images fused from two to seven.
Finally, the paper shows that the information content in an image gets saturated after fusing four images.
The Performance Evaluation of IEEE 802.16 Physical Layer in the Basis of Bit ...IJCI JOURNAL
Â
Fixed Broadband Wireless Access is a promising technology which can offer high speed data rate from transmitting end to customer end which can offer high speed text, voice, and video data. IEEE 802.16 WirelessMAN is a standard that specifies medium access control layer and a set of PHY layer to fixed and mobile BWA in broad range of frequencies and it supports equipment manufacturers due to its robust performance in multipath environment. Consequently WiMAX forum has adopted this version to develop the network world wide. In this paper the performance of IEEE 802.16 OFDM PHY Layer has been investigated by using the simulation model in Matlab. The Stanford University Interim (SUI) channel models are selected for the performance evaluation of this standard. The Ideal Channel estimation is considered in this work and the performance evaluation is observed in the basis of BER.
PSO OPTIMIZED INTERVAL TYPE-2 FUZZY DESIGN FOR ELECTIONS RESULTS PREDICTIONijfls
Â
Interval type-2 fuzzy logic systems (IT2FLSs), have recently shown great potential in various applications with dynamic uncertainties. It is believed that additional degree of uncertainty provided by IT2FL allows for better representation of the uncertainty and vagueness present in prediction models. However, determining the parameters of the membership functions of IT2FL is important for providing optimum
performance of the system. Particle Swarm Optimization (PSO) has attracted the interest of researchers due to their simplicity, effectiveness and efficiency in solving real-world optimization problems. In this paper, a novel optimal IT2FLS is designed, applied for predicting winning chances in elections. PSO is
used as an optimized algorithm to tune the parameter of the primary membership function of the IT2FL to improve the performance and increase the accuracy of the IT2F set. Simulation results show the superiority of the PSO-IT2FL to the similar non-optimal IT2FL system with an increase in the prediction.
A Comparative Analysis of Data Privacy and Utility Parameter Adjustment, Usin...Kato Mivule
Â
Kato Mivule, Claude Turner, "A Comparative Analysis of Data Privacy and Utility Parameter Adjustment, Using Machine Learning Classification as a Gauge", Procedia Computer Science, Volume 20, 2013, Pages 414-419, Baltimore MD, USA
FACTORS INFLUENCING THE ADOPTION OF E-GOVERNMENT SERVICES IN PAKISTANMuhammad Ahmad
Â
E-government provides opportunities to deliver various services more effectively and better serve citizens. In developing countries, e-government initiatives provide services that have been previously inaccessible to their citizens. However, e-government initiatives in developing countries are still in their infancy and face a wide range of barriers that restrict wide-spread use. Like many other developing countries, Pakistan has a low level of e-government services adoption. Previous research has investigated e-government services in developing countries from the organizational perspective. However, the research stream suffers from an absence of studies that have investigated e-government from a citizenâs perspective. The success of e-government services depends on government support as well as on citizenâs adoption. This paper aims to fill this gap by exploring the challenges and barriers of e-government services from the userâs perspective. In this study, an amended version of the UTAUT model is used to investigate the factors influencing the uptake of e-government services in Pakistan. The results show that the factors influencing the adoption of e-government services in Pakistan are related to ease of use, usefulness, social influence, technological issues, lack of awareness, data privacy, and trust. Implications for e-businesses and government policy decision makers are also considered in this study.
EXTENSION OF TECHNOLOGY ACCEPTANCE MODEL (TAM): A STUDY ON INDIAN INTERNET BA...IAEME Publication
Â
Internet banking plays significant role in the development of banking business in our country. An application of electronic service brings predominant changes in the way of doing banking transactions. In simpler terms, internet banking refers to banking through bankâs website with the help of internet connection. Internet banking provides lot of benefits to the customers as well as the banks. Internet banking provides different kinds of services to the customers in the form checking balances, account statement, pay utility bills etc
Analysis of the User Acceptance for Implementing ISO/IEC 27001:2005 in Turkis...IJMIT JOURNAL
Â
This study aims to develop a model for the user acceptance for implementing the information security standard (i.e. ISO 27001) in Turkish public organizations. The results of the surveys performed in Turkey reveal that the legislation on information security public which organizations have to obey is significantly related with the user acceptance during ISO 27001 implementation process. The fundamental components of our user acceptance model are perceived usefulness, attitude towards use, social norms, and performance expectancy.
The internet of things is an emerging technology that is currently present in most processes and devices, allowing to improve the quality of life of people and facilitating the access to specific information and services. The main purpose of the present article is to offer a general overview of internet of things, based on the analysis of recently published work. The added value of this article lies in the analysis of the main recent publications and the diversity of applications of internet of things technology. As a result of the analysis of the current literature, internet of things technology stands out as a facilitator in business and industrial performance but above all in improving the quality of life. As a conclusion to this document, the internet of things is a technology that can overcome the challenges in terms of security, processing capacity and data mobility, as long as the development related to other technologies follows its expected course.
Antecedents of Knowledge Management Practices: Case of Malaysian PractitionersjournalBEEI
Â
In this paper, we investigated the knowledge management (KM) behavior of executives in Malaysia who work in different sectors and involved in Information Technology (IT) related fields. We proposed a conceptual framework based on the Theory of Reasoned Action (TRA), the Theory of Planned Behavior (TPB) and Unified Theory of Acceptance and Use of Technology (UTAUT) to study their intention and involvement in KM initiatives. The knowledge creation theory (SECI process) was employed to operationalize KM intention and KM behavior. We proposed six independent variables that represent the social-cultural nature of KM as the antecedence of KM intention. These variables are trust, management support, decentralization, IT support, performance expectancy (PE), and effort expectancy (EE). Seventy-four executives from both private and government-linked organizations responded to our online questionnaire. SmartPLS3 was used to run the analysis. The reliability was ensured with the factor loadings, Cronbachâs alpha, Composite Reliability (CR) that met the fit requirement of above 0.6, 0.7 and 0.7 respectively. The convergent validity was confirmed through average variance extracted (AVE) that met the fit requirement of above 0.5. The discriminant validity was assessed by using Fornell and Larckerâs criterion. Finally, the structural model confirmed that only PE of KM, and EE of KM are the significant predictors of KM intention and the KM intention significantly predicts KM behavior. The implications of the findings are discussed in detail at the end of the paper.
MOVIE SUCCESS PREDICTION AND PERFORMANCE COMPARISON USING VARIOUS STATISTICAL...ijaia
Â
Movies are among the most prominent contributors to the global entertainment industry today, and they
are among the biggest revenue-generating industries from a commercial standpoint. It's vital to divide
films into two categories: successful and unsuccessful. To categorize the movies in this research, a variety
of models were utilized, including regression models such as Simple Linear, Multiple Linear, and Logistic
Regression, clustering techniques such as SVM and K-Means, Time Series Analysis, and an Artificial
Neural Network. The models stated above were compared on a variety of factors, including their accuracy
on the training and validation datasets as well as the testing dataset, the availability of new movie
characteristics, and a variety of other statistical metrics. During the course of this study, it was discovered
that certain characteristics have a greater impact on the likelihood of a film's success than others. For
example, the existence of the genre action may have a significant impact on the forecasts, although another
genre, such as sport, may not. The testing dataset for the models and classifiers has been taken from the
IMDb website for the year 2020. The Artificial Neural Network, with an accuracy of 86 percent, is the best
performing model of all the models discussed.
Towards A Differential Privacy and Utility Preserving Machine Learning Classi...Kato Mivule
Â
Kato Mivule, Claude Turner, Soo-Yeon Ji, "Towards A Differential Privacy and Utility Preserving Machine Learning Classifier", Procedia Computer Science (Complex Adaptive Systems), 2012, Pages 176-181, Washington DC, USA.
Data mining and machine learning have become a vital part of crime detection and prevention. In this
research, we use WEKA, an open source data mining software, to conduct a comparative study between the
violent crime patterns from the Communities and Crime Unnormalized Dataset provided by the University
of California-Irvine repository and actual crime statistical data for the state of Mississippi that has been
provided by neighborhoodscout.com. We implemented the Linear Regression, Additive Regression, and
Decision Stump algorithms using the same finite set of features, on the Communities and Crime Dataset.
Overall, the linear regression algorithm performed the best among the three selected algorithms. The scope
of this project is to prove how effective and accurate the machine learning algorithms used in data mining
analysis can be at predicting violent crime patterns.
Applying Data Privacy Techniques on Published Data in UgandaKato Mivule
Â
Kato Mivule, Claude Turner, "Applying Data Privacy Techniques on Published Data in Uganda", Proceedings of the 2012 International Conference on e-Learning, e-Business, Enterprise Information Systems, and e-Government (EEE 2012), Pages 110-115, Las Vegas, NV, USA.
Kato Mivule - Utilizing Noise Addition for Data Privacy, an OverviewKato Mivule
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Kato Mivule, "Utilizing Noise Addition for Data Privacy, an Overview", Proceedings of the International Conference on Information and Knowledge Engineering (IKE 2012), Pages 65-71, Las Vegas, NV, USA.
A comprehensive survey of link mining and anomalies detectioncsandit
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This survey introduces the emergence of link mining and its relevant application to detect
anomalies which can include events that are unusual, out of the ordinary or rare, unexpected
behaviour, or outliers.
An approach for self creating software code in bionets with artificial embryo...eSAT Publishing House
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IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
An Investigation of Data Privacy and Utility Preservation Using KNN Classific...Kato Mivule
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Kato Mivule and Claude Turner, An Investigation of Data Privacy and Utility Preservation Using KNN Classification as a Gauge, International Conference on Information and Knowledge Engineering (IKE 2013), July 22-25, Pages 203-204, Las Vegas, NV, USA
INFORMATION SATURATION IN MULTISPECTRAL PIXEL LEVEL IMAGE FUSIONIJCI JOURNAL
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The availability of imaging sensors operating in multiple spectral bands has led to the requirement of
image fusion algorithms that would combine the image from these sensors in an efficient way to give an
image that is more informative as well as perceptible to human eye. Multispectral image fusion is the
process of combining images from different spectral bands that are optically acquired. In this paper, we
used a pixel-level image fusion based on principal component analysis that combines satellite images of the
same scene from seven different spectral bands. The purpose of using principal component analysis
technique is that it is best method for Grayscale image fusion and gives better results. The main aim of
PCA technique is to reduce a large set of variables into a small set which still contains most of the
information that was present in the large set. The paper compares different parameters namely, entropy,
standard deviation, correlation coefficient etc. for different number of images fused from two to seven.
Finally, the paper shows that the information content in an image gets saturated after fusing four images.
The Performance Evaluation of IEEE 802.16 Physical Layer in the Basis of Bit ...IJCI JOURNAL
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Fixed Broadband Wireless Access is a promising technology which can offer high speed data rate from transmitting end to customer end which can offer high speed text, voice, and video data. IEEE 802.16 WirelessMAN is a standard that specifies medium access control layer and a set of PHY layer to fixed and mobile BWA in broad range of frequencies and it supports equipment manufacturers due to its robust performance in multipath environment. Consequently WiMAX forum has adopted this version to develop the network world wide. In this paper the performance of IEEE 802.16 OFDM PHY Layer has been investigated by using the simulation model in Matlab. The Stanford University Interim (SUI) channel models are selected for the performance evaluation of this standard. The Ideal Channel estimation is considered in this work and the performance evaluation is observed in the basis of BER.
FREQUENCY RESPONSE ANALYSIS OF 3-DOF HUMAN LOWER LIMBSIJCI JOURNAL
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Frequent and prolonged expose of human body to vibrations can induce back pain and physical disorder
and degeneration of tissue. The biomechanical model of human lower limbs are modeled as a three degree
of freedom linear spring-mass-damper system to estimate forces and frequencies. Then three degree of
freedom system was analysed using state space method to find natural frequency and mode shape. A
program was develop to solve simplified equations and results were plotted and discussed in detail. The
mass, stiffness and damping coefficient of various segments are taken from references. The optimal values
of the damping ratios of the body segments are estimated, for the three degrees of freedom model. At last
resonance frequencies are found to avoid expose of lower limbs to such environment for optimum comfort.
A COMPARATIVE STUDY ON IMAGE COMPRESSION USING HALFTONING BASED BLOCK TRUNCAT...IJCI JOURNAL
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In this paper scrutinizes image compression using Halftoning Based Block Truncation Coding for color
image. Many algorithms were selected likely the original Block Truncation coding, Ordered Dither Block
Truncation Coding, Error Diffusion Block Truncation Coding , and Dot Diffused Block Truncation Coding.
These above techniques are divided image into non overlapping blocks. BTC acts as the basic compression
technique but it exhibits two disadvantages such as the false contour and blocking effect. Hence halftoning
based block truncation coding (HBTC) is used to overcome the two issues. Objective measures are used to
evaluate the image degree of excellence such as Peak Signal to Noise Ratio, Mean Square Error, Structural
Similarity Index and Compression Ratio. At the end, conclusions have shown that the Dot Diffused Block
Truncation Coding algorithm outperforms the Block Truncation Coding as well as Error Diffusion Block
Truncation Coding.
Quadrant Based DIR in CWin Adaptation Mechanism for Multihop Wireless NetworkIJCI JOURNAL
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In Multihop Wireless Networks, traffic forwarding capability of each node varies according to its level of contention. Each node can yield its channel access opportunity to its neighbouring nodes, so that all the nodes can evenly share the channel and have similar forwarding capability. In this manner the wireless channel is utilized effectively, which is achieved using Contention Window Adaptation Mechanism (CWAM). This mechanism achieves a higher end-to-end throughout but consumes the network power to a higher level. So, a newly proposed algorithm Quadrant- Based Directional Routing Protocol (Q-DIR) is implemented as a cross-layer with CWAM, to reduce the total network power consumption through limited flooding and also reduce the routing overheads, which eventually increases overall network throughput. This algorithm limits the broadcast region to a quadrant where the source node and the destination nodes are located. Implementation of the algorithm is done in Linux based NS-2 simulator
FUZZY-BASED ENERGY EFFICIENT METHOD FOR MULTIPLE ATTACKS IN SENSOR NETWORKS: ...IJCI JOURNAL
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An adversary can easily compromise sensor nodes in wireless sensor networks, and generate multiple
attacks through compromised nodes, such as false vote injection attacks and false report injection attacks.
The false vote injection attack tries to drop legitimate reports in an intermediate node, and the false report
injection attack tries to drain the energy consumption of each node. To prevent these attacks, a
probabilistic voting-based filtering scheme (PVFS) has been proposed to select verification nodes, and to
detect fabricated votes in the reports as they occur simultaneously. In this paper, we propose a method that
improves the energy efficiency of each node and the security level of the false report injection attack, while
maintaining the detection power of the false vote injection attack. Our proposed method effectively selects
verification node with considering the conditions of each node, based on a fuzzy rule-based system. The
verification node is decided through the energy remaining level, distance level, and number of detected
false votes in the fuzzy system. We evaluated the effectiveness of the proposed method, as compared to
PVFS, when two attacks occur simultaneously in the sensor network. The experimental results show that
our method saves energy by up to 8%, by improving and maintaining the defence against these multiple
attacks
The main objective of this paper is to design and develop an automatic vehicle, fully controlled by a
computer system. The vehicle designed in the present work can move in a pre-determined path and work
automatically without the need of any human operator and it also controlled by human operator. Such a
vehicle is capable of performing wide variety of difficult tasks in space research, domestic, scientific and
industrial fields. For this purpose, an IBM compatible PC with Pentium microprocessor has been used
which performed the function of the system controller. Its parallel printer port has been used as data
communication port to interface the vehicle. A suitable software program has been developed for the
system controller to send commands to the vehicle.
Continental division of load and balanced antIJCI JOURNAL
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Increasing usability of internet is creating huge data which should be managed by the industries, but this
should not affect the processing time which may create inconvenience to end user. As cloud is emerging as
back bone of IT industry there are much enhancement needed in it Many companies are switching their
data from small storage location to Cloud, The migration is done such that the companies do not have a
burden to purchase the Infrastructure they merely have to rent out the Infrastructure but the migration
should not cost on the speed of storage or retrieval of the data from the server. Load balancing is one of the
major issue in cloud computing, but these problems are Tractable There are many algorithm for load
balancing which has advantage over the other in this paper Ant colony algorithm is studied .
An improved ant colony algorithm based onIJCI JOURNAL
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This paper presents an improved chaotic ant colony system algorithm (ICACS) for solving combinatorial
optimization problems. The existing algorithms still have some imperfections, we use a combination of two
different operators to improve the performance of algorithm in this work. First, 3-opt local search is used
as a framework for the implementation of the ACS to improve the solution quality; Furthermore, chaos is
proposed in the work to modify the method of pheromone update to avoid the algorithm from dropping into
local optimum, thereby finding the favorable solutions. From the experimental results, we can conclude
that ICACS has much higher quality solutions than the original ACS, and can jump over the region of the
local optimum, and escape from the trap of a local optimum successfully and achieve the best solutions.
Therefore, itâs better and more effective algorithm for TSP.
A M ULTI -O BJECTIVE B ASED E VOLUTIONARY A LGORITHM AND S OCIAL N ETWOR...IJCI JOURNAL
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In this paper, a multi-objective based NSGA-II algo
rithm is proposed for dynamic job-shop scheduling
problem (DJSP) with random job arrivals and machine
breakdowns. In DJSP schedules are usually
inevitable due to various unexpected disruptions. T
o handle this problem, it is necessary to select
appropriate key machines at the beginning of the si
mulation instead of random selection. Thus, this pa
per
seeks to address on approach called social network
analysis method to identify the key machines of the
addressed DJSP. With identified key machines, the e
ffectiveness and stability of scheduling i.e., make
span
and starting time deviations of the computational c
omplex NP-hard problem has been solved with propose
d
multi-objective based hybrid NSGA-ll algorithm. Sev
eral experiments studies have been conducted and
comparisons have been made to demonstrate the effic
iency of the proposed approach with classical multi
-
objective based NSGA-II algorithm. The experimental
results illustrate that the proposed method is ver
y
effective in various shop floor conditions
C OMPREHENSIVE S TUDY OF A COUSTIC C HANNEL M ODELS FOR U NDERWATER W I...IJCI JOURNAL
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In underwater acoustic communication, shallow water
and deep water are two different mediums which
exhibit many challenges to deal with due to the tim
e varying multipath and Doppler Effect in the forme
r
case and multipath propagation in the latter case.
In this paper, the characteristics of the acoustic
propagation are described in detail and channel mod
els based on the various propagation phenomena in
shallow water channel and deep water channel as wel
l are presented and the transmission losses incurre
d
in each model are thoroughly investigated. Signal t
o noise ratio (SNR) at the receiver is thoroughly
analyzed. Numerical results obtained through analyt
ical simulations carried out in MATLAB bring to lig
ht
the important issues to be considered so as to deve
lop suitable communication protocols for Underwater
Wireless Communication Networks (UWCNs) to provide
effective and reliable communication.
S ECURITY C ONSIDERATIONS IN A M ARINE C OMMUNICATION N ETWORK FOR F ISH...IJCI JOURNAL
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ith the recent advancements in and popularity of wireless ne
tworks, the security based issues are also
increasing considerably. In this paper, we look at the data s
ecurity and situational security vulnerabilities
in the communication network for fishermen at sea being develope
d by our research center. We are
proposing certain solutions and algorithms for avoiding some of the si
tuations. They are Adaptive Context-
aware Transmission Power Control (ACTPC) as a proposed solution
for preventing unauthorized users at
the maritime border, along with border alert and distress alert. Th
e algorithms are implemented using a
network of MICAz mote
E FFICIENT E NERGY U TILIZATION P ATH A LGORITHM I N W IRELESS S ENSOR...IJCI JOURNAL
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With limited amount of energy, nodes are powered by
batteries in wireless networks. Increasing the lif
e
span of the network and reducing the usage of energ
y are two severe problems in Wireless Sensor
Networks. A small number of energy utilization path
algorithms like minimum spanning tree reduces tota
l
energy consumption of a Wireless Sensor Network, ho
wever very heavy load of sending data packets on
many key nodes is used with the intention that the
nodes quickly consumes battery energy, by raising t
he
life span of the network reduced. Our proposal work
aimed on presenting an Energy Conserved Fast and
Secure Data Aggregation Scheme for WSN in time and
security logic occurrence data collection
application. To begin with, initially the goal is m
ade on energy preservation of sensed data gathering
from
event identified sensor nodes to destination. Inven
tion is finished on Energy Efficient Utilization Pa
th
Algorithm (EEUPA), to extend the lifespan by proces
sing the collecting series with path mediators
depending on gene characteristics sequencing of nod
e energy drain rate, energy consumption rate, and
message overhead together with extended network lif
e span. Additionally, a mathematical programming
technique is designed to improve the lifespan of th
e network. Simulation experiments carried out among
different relating conditions of wireless sensor ne
twork by different path algorithms to analyze the
efficiency and effectiveness of planned Efficient E
nergy Utilization Path Algorithm in wireless sensor
network (EEUPA)
C LASSIFICATION O F D IABETES R ETINA I MAGES U SING B LOOD V ESSEL A REASIJCI JOURNAL
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Retina images are obtained from the fundus camera a
nd graded by skilled professionals. However there i
s
considerable shortage of expert observers has encou
raged computer assisted monitoring. Evaluation of
blood vessels network plays an important task in a
variety of medical diagnosis. Manifestations of
numerous vascular disorders, such as diabetic retin
opathy, depend on detection of the blood vessels
network. In this work the fundus RGB image is used
for obtaining the traces of blood vessels and areas
of
blood vessels are used for detection of Diabetic Re
tinopathy (DR). The algorithm developed uses
morphological operation to extract blood vessels. M
ainly two steps are used: firstly enhancement opera
tion
is applied to original retina image to remove noise
and increase contrast of retinal blood vessels. Se
condly
morphology operations are used to take out blood ve
ssels. Experiments are conducted on publicly availa
ble
DIARETDB1 database. Experimental results obtained b
y using gray-scale images have been presented.
A UTOMATIC L OGO E XTRACTION F ROM D OCUMENT I MAGESIJCI JOURNAL
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Logo extraction plays an important role in logo ba
sed document image retrieval. Here we present a
method for automatic logo extraction from the docum
ent images that works for scanned documents
containing a logo. Proposed method uses morphologic
al operations for logo extraction. It supports
extraction of a logo with its gray level and color
information
A NALYSIS OF ANTHOCNET AND AODV P ERFORMANCE USING NS2 IJCI JOURNAL
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Adhoc wireless multi-hop Networks (AHWMNs) are buil
t with wireless nodes arranged in an adhoc manner.
Every node can forward packets and also acts as a s
ource. AODV establishes a path to receiver when it
is
needed by the sender and is on the standardization
process of Internet engineering task force.
AntHocNetwhich is based on ants foraging behavior,
includes reactive and proactive mechanisms.
AntHocNet builds the path as per the requirement of
source and maintains until the end of communicatio
n
session. In this paper performance of AODV and AntH
ocNetare analyzed at different parameters like data
rates, pause times, and speed. Metrics Packet deliv
ery ratio, Loss rate, End to End delay, jitter, and
throughput are evaluated at different simulation ti
mes. Simulation is performed using network simulat
or
NS-2.34 and 802.11b is the MAC protoco
Framework for A Personalized Intelligent Assistant to Elderly People for Acti...CSCJournals
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The increasing population of elderly people is associated with the need to meet their increasing requirements and to provide solutions that can improve their quality of life in a smart home. In addition to fear and anxiety towards interfacing with systems; cognitive disabilities, weakened memory, disorganized behavior and even physical limitations are some of the problems that elderly people tend to face with increasing age. The essence of providing technology-based solutions to address these needs of elderly people and to create smart and assisted living spaces for the elderly; lies in developing systems that can adapt by addressing their diversity and can augment their performances in the context of their day to day goals. Therefore, this work proposes a framework for development of a Personalized Intelligent Assistant to help elderly people perform Activities of Daily Living (ADLs) in a smart and connected Internet of Things (IoT) based environment. This Personalized Intelligent Assistant can analyze different tasks performed by the user and recommend activities by considering their daily routine, current affective state and the underlining user experience. To uphold the efficacy of this proposed framework, it has been tested on a couple of datasets for modelling an "average user" and a "specific user" respectively. The results presented show that the model achieves a performance accuracy of 73.12% when modelling a "specific user", which is considerably higher than its performance while modelling an "average user", this upholds the relevance for development and implementation of this proposed framework.
Predicting user behavior using data profiling and hidden Markov modelIJECEIAES
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Mental health disorders affect many aspects of patientâs lives, including emotions, cognition, and especially behaviors. E-health technology helps to collect information wealth in a non-invasive manner, which represents a promising opportunity to construct health behavior markers. Combining such user behavior data can provide a more comprehensive and contextual view than questionnaire data. Due to behavioral data, we can train machine learning models to understand the data pattern and also use prediction algorithms to know the next state of a personâs behavior. The remaining challenges for this issue are how to apply mathematical formulations to textual datasets and find metadata that aids to identify the personâs life pattern and also predict the next state of his comportment. The main idea of this work is to use a hidden Markov model (HMM) to predict user behavior from social media applications by analyzing and detecting states and symbols from the user behavior dataset. To achieve this goal, we need to analyze and detect the states and symbols from the user behavior dataset, then convert the textual data to mathematical and numerical matrices. Finally, apply the HMM model to predict the hidden user behavior states. We tested our program and identified that the log-likelihood was higher and better when the model fits the data. In any case, the results of the study indicated that the program was suitable for the purpose and yielded valuable data.
Assessment of the main features of the model of dissemination of information ...IJECEIAES
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Social networks provide a fairly wide range of data that allows one way or another to evaluate the effect of the dissemination of information. This article presents the results of a study that describes methods for determining the key parameters of the model needed to analyze and predict the dissemination of information in social networks. An approach based on the analysis of statistical data on user behavior in social networks is proposed. The process of evaluating the main features of the model is described, including the mathematical methods used for data analysis and information dissemination modeling. The study aims to understand the processes of information dissemination in social networks and develop recommendations for the effective use of social networks as a communication and brand promotion tool, as well as to consider the analytical properties of the classical susceptible-infected-removed (SIR) model and evaluate its applicability to the problem of information dissemination. The results of the study can be used to create algorithms and techniques that will effectively manage the process of information dissemination in social networks.
Predicting depression using deep learning and ensemble algorithms on raw twit...IJECEIAES
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Social network and microblogging sites such as Twitter are widespread amongst all generations nowadays where people connect and share their feelings, emotions, pursuits etc. Depression, one of the most common mental disorder, is an acute state of sadness where person loses interest in all activities. If not treated immediately this can result in dire consequences such as death. In this era of virtual world, people are more comfortable in expressing their emotions in such sites as they have become a part and parcel of everyday lives. The research put forth thus, employs machine learning classifiers on the twitter data set to detect if a personâs tweet indicates any sign of depression or not.
Issues in Information SystemsVolume XII, No. 2, pp. 67-73-.docxvrickens
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Issues in Information Systems
Volume XII, No. 2, pp. 67-73-, 2011
Information Technology Ethics: A Research Framework
Issues in Information Systems
Volume X, Issue X, pp. x-x, Year
INFORMATION TECHNOLOGY ETHICS: A RESEARCH FRAMEWORK
Richard V. McCarthy, Quinnipiac University, [email protected]
Leila Halawi, Nova Southeastern University, [email protected]
Jay E. Aronson, The University of Georgia, [email protected]
ABSTRACT
Information technology has become so pervasive that opportunities for abuses abound. IT Ethics has taken on increasing importance as the size and complexity of IT issues continues to grow. This paper outlines a research framework to analyze: Do significant ethical differences exist amongst undergraduate and graduate MIS students?
Keywords: Information Technology (IT), Ethics, IT and Ethics
INTRODUCTION
We live in an information society. Most people live and work within the context of information technology (Abratt, Nel, & Higgs, 1992). IT enhances leisure time and enriches culture by expanding the distribution of information, relieves pressures on urban areas by enabling individuals to work from home or remote-site offices (Garcia, 2009), changes the way we work, and the way we work with one another. In terms of productivity and speed of communications, these changes have been mostly positive (Benham, 1995). But what have been the costs? IT introduces change that creates new ethical issues.
Ethical Theories and IT
Gates (1995) suggested that the study of computer ethics is needed because there is a vacuum of policies surrounding the new possibilities. He defines computer ethics as the analysis of the nature and social impact of computer technology and the corresponding formulation and justification of policies for the ethical use of such a technology.
RESEARCH METHODOLOGY
Our research centered upon the following research question: Do significant ethical differences exist amongst undergraduate and graduate MIS students in the United States?
The research hypotheses to be tested are as follows:
H1: Computer information systems undergraduate and graduate students have the same ethical beliefs
H2: Female computer information systems students and male computer information systems students have the
same ethical beliefs.
To test these hypotheses a subset of five ethical scenarios that were utilized by Athey (2011) to test if significant ethical differences existed amongst manager was used along with one ethical scenario that was developed based upon an actual case from the researcherâs university. According to Jones (2014), âthe scenario technique has been shown to be useful in eliciting attitudes by personalizing the issuesâ (p. 15).
RESULTS
Eighty-seven scenarios were administered and the demographics of the sample population are shown in Table 1. The sample population had more males (70.1%) than females (29.9%).
A Chi-Square test was performed to test each of the three hypotheses. The first ...
Alcohol consumption in higher education institutes is not a new problem; but excessive drinking by
underage students is a serious health concern. Excessive drinking among students is associated with a number
of life-threatening consequences that include serious injuries; alcohol poisoning; temporary loss of
consciousness; academic failure; violence, unplanned pregnancy; sexually transmitted diseases, troubles with
authorities, property damage; and vocational and criminal consequences that could jeopardize future job
prospects. This article describes a learning technique to improve the efficiency of academic performance in
the educational institutions for students who consume alcohol. This move can help in identifying the students
who need special advising or counselling to understand the danger of consuming alcohol. This was carried
out in two major phases: feature selection which aims at constructing diverse feature selection algorithms
such as Gain Ratio attribute evaluation, Correlation based Feature Selection, Symmetrical Uncertainty and
Particle Swarm Optimization Algorithms. Afterwards, a subset of features is chosen for the classification
phase. Next, several machine-learning classification methods are chosen to estimate the teenagerâs alcohol
addiction possibility. Experimental results demonstrated that the proposed approach could improve the
accuracy performance and achieve promising results with a limited number of features.
A web-based survey and theoretical research focuses mainly on the hazards that children are exposed to while surfing the digital world. It addresses the problem from parents/caregivers perspective and tries to shed light over the best ways of understanding and precautionary means. It is important for families to take all preventive measures to protect their kids from such hazards.
PSO OPTIMIZED INTERVAL TYPE-2 FUZZY DESIGN FOR ELECTIONS RESULTS PREDICTIONijfls
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Interval type-2 fuzzy logic systems (IT2FLSs), have recently shown great potential in various applications
with dynamic uncertainties. It is believed that additional degree of uncertainty provided by IT2FL allows
for better representation of the uncertainty and vagueness present in prediction models. However,
determining the parameters of the membership functions of IT2FL is important for providing optimum
performance of the system. Particle Swarm Optimization (PSO) has attracted the interest of researchers
due to their simplicity, effectiveness and efficiency in solving real-world optimization problems. In this
paper, a novel optimal IT2FLS is designed, applied for predicting winning chances in elections. PSO is
used as an optimized algorithm to tune the parameter of the primary membership function of the IT2FL to
improve the performance and increase the accuracy of the IT2F set. Simulation results show the superiority
of the PSO-IT2FL to the similar non-optimal IT2FL system with an increase in the prediction.
Framework for an Intelligent Affect Aware Smart Home Environment for Elderly ...CSCJournals
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The population of elderly people has been increasing at a rapid rate over the last few decades and their population is expected to further increase in the upcoming future. Their increasing population is associated with their increasing needs due to problems like physical disabilities, cognitive issues, weakened memory and disorganized behavior, that elderly people face with increasing age. To reduce their financial burden on the world economy and to enhance their quality of life, it is essential to develop technology-based solutions that are adaptive, assistive and intelligent in nature. Intelligent Affect Aware Systems that can not only analyze but also predict the behavior of elderly people in the context of their day to day interactions with technology in an IoT-based environment, holds immense potential for serving as a long-term solution for improving the user experience of elderly in smart homes. This work therefore proposes the framework for an Intelligent Affect Aware environment for elderly people that can not only analyze the affective components of their interactions but also predict their likely user experience even before they start engaging in any activity in the given smart home environment. This forecasting of user experience would provide scope for enhancing the same, thereby increasing the assistive and adaptive nature of such intelligent systems. To uphold the efficacy of this proposed framework for improving the quality of life of elderly people in smart homes, it has been tested on three datasets and the results are presented and discussed.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
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Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
DevOps and Testing slides at DASA ConnectKari Kakkonen
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My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
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Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
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In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
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Clients donât know what they donât know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clientsâ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
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Are you looking to streamline your workflows and boost your projectsâ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, youâre in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part âEssentials of Automationâ series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Hereâs what youâll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
Weâll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Donât miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
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After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more âmechanicalâ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
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Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
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4. Demo
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Orchestrator execution result
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SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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Intelligent analysis of the effect of internet
1. International Journal on Cybernetics & Informatics (IJCI) Vol. 3, No. 3, June 2014
DOI: 10.5121/ijci.2014.3302 11
INTELLIGENT ANALYSIS OF THE EFFECT OF INTERNET
SYSTEM IN SOCIETY
Rashmi Chahar1
, Ashish Chandiok2
and D. K. Chaturvedi3
1,2,3
Dayalbagh Educational Institute, Dayalbagh, Agra, Uttar Pradesh, India
ABSTRACT
This paper analyzes the effect of Information Technology on professionals, academicians and students in
perspective of their relations, education, job purpose, health, entertainment and electronic business that
can bring changes in society. Technology can have both positive and negative consequences for people of
different walks of life at different times. The need is to understand the true impact of internet on the society
so that people can start thinking and build a healthy society. In this paper, an empirical study is considered
60 persons; a causal loop model is formed relating the parameters on the basis of data collected. These
parameters are used to form the fuzzy dynamic model to analyze the effect of the internet on the society.
The model is analyzed and suitable solutions are proposed to counter the negative effect of internet on our
society.
KEYWORDS
Internet, Society, Causal loop, Fuzzy
1. INTRODUCTION
The continuous changing technology has brought effect on social and economic consequences on
different aspects of our daily life. Two aspects of this technology emerged are âPositive and
Negative impactâ on the users. Our approach is to avoid wrong choices otherwise our technology
will destroy us. The internet has influenced different aspects of society. It is important for us to
understand the consequences of internet on the people life and habits. A. Venkatesh [1] surveyed
in his paper that all technologies create an impact of some sort like attributes and behavior toward
entertainment and the interaction between families. Cole [2] assessed the need of the internet as a
mainstream medium that may soon be as pervasive as television, although the speed of its
diffusion seems much faster. Kraut et. al [3] conducted a longitudinal study of the effects of the
internet on social involvement and psychological effect of the internet, decreased community
within the family, decreased local social network, lethargy and depressions. In a report of SIQSS,
N. Nie [4] has sustained the negative consequences of the internet. Kraut and Katz et. al. [3] has
shown that the internet has a negative effect on society.
The long internet usage was analyzed by Young [5]. It was coined Internet addiction disorder.
Persons with IAD can exhibit symptoms, suffer drawbacks and face consequences that are similar
to individual addicted to alcohol, gambling, narcotics shopping and compulsive behavior. These
persons find the virtual environment to be more attractive than everyday reality. Their daily lives
are dominated by their need to be online. This is affecting millions of American, Europeans and
even in Asian countries.
2. International Journal on Cybernetics & Informatics (IJCI) Vol. 3, No. 3, June 2014
12
2. STATEMENT OF PROBLEM
As the use of internet is growing rapidly each year, the negative internet effect has become a
problem among the users. Internet users may come from all walks of life and as a result, they are
suffering in the main aspects of everyday life in situations such as education, job, family and
social relationship. In this work the relationship is formed between the different parameters and
analyzes the effect of internet on considering professionals, academicians and students. The
parameters considered are made more understandable by designing a questionnaire and taking
interviews to analyze the effect of the internet on society using intelligent system.
3. METHODOLOGY
Fig.1. Flow Chart for the Intelligent Analysis using Causal loop and Fuzzy logic
*Input for each fuzzy rule based on Causal link is from the Survey result represented as COG%
3.1. Data source
The sample is taken from the population having different demographics like teens and adults of
different professions like academicians, professionals and students. 50% ratio of male and female
are taken. In this paper data is not analyzed separately, but the relationship between parameters is
taken. Degree of agree is calculated from the center of gravity method.
3.2. Causal Loop Diagram.
On the basis of the parameters an internet system is formed with the help of a causal loop
diagram. Causal loop diagramming (CLD) encourages the modeler to conceptualize a real world
system in terms of feedback loops [6]. Causal loop plays two important roles in system dynamics
studies. First, during model development, they serve as preliminary sketches of causal
hypotheses. Second, the causal loop diagram can simplify the illustration of a model [7].
CLD is a foundational tool used in system dynamics [8]. A method of analysis used to develop
and understand the complex system. It provides the systematic feedback in the processes by the
variable x affects variable y and, in turn y affects z variable through a chain of causes & effects.
The behavior of the entire system is discovered with CLD [9] [10]. CLD can focus on the entire
system [16]. There are linguistic variables in our system and hence fuzzy logic is used.
3. International Journal on Cybernetics & Informatics (IJCI) Vol. 3, No. 3, June 2014
13
3.3. Fuzzy Set Theoretic Approach.
Natural language abounds with vague and imprecise concepts, such as âAnjali is tallâ, âhe has
acute painâ. Such statements are difficult to translate into more precise language without losing
some of their semantic values [11] [12].
Fuzzy logic is a superset of conventional (Boolean) logic that has been extended to handle the
concept of partial truth values between completely true and completely false [13] [14]. It was
introduced by Dr. Lofti Zadeh of University of California, Berkley in the year 1965. Fuzzy
system combines fuzzy sets with fuzzy rules to produce overall complex nonlinear behavior [17].
Fuzzy formulation can help to achieve tractability, robustness and lower solution cost [15].
4. SURVEY AND EXPERIMENT RESULT
According to data survey an intelligent model is formed to analyze the effect of the internet on
society. The complete research is done in four phases represented as below:
1. Data Collection: Primary Data is collected using the survey method of preparing
questionnaire. The samples are taken from a population by using random sampling
considering students, academicians and professionals with both male and female in all
entities.
2. Data Tabulation: The data collected is tabulated in terms of frequency response from the
questionnaire, based on Likert scale and then the centre of gravity for the degree of agree
is calculated for each parameter.
3. Data Analysis: The data are analyzed using causal loop and fuzzy system models to
determine the effect of the internet in society.
4. Data representation: The output results are represented by graphs and tables.
4.1. Model development Phase
Step1 (Data Collection) - The questionnaire is prepared using the given parameters and survey is
done by asking the respondent in terms of strongly disagree, disagree, neutral, agree and strongly
agree for each parameter. The response was taken for both male and female from each group of
students, academicians, and professionals.
The following parameters were chosen in the questionnaire
1. Long Internet Usage (LIU)
2. Internet Usage for Job purpose (IJP)
3. Easy Internet Access (EIA)
4. Internet Entertainment Engagement (IEE)
5. Internet Usage Cost (IUC)
6. Medical problems (MP)
7. Ethical Problems (EP)
8. Social restrictions (SR)
9. Lethargy uses the Internet (LUI)
10. Psychological Problem (PP)
11. Spoilage of teenagers (SOT)
12. Crime Uplift (CU)
13. E-business (EB)
Step 2 (Data Tabulation) - The second step in the model development phase is the identification
of variables and tabulation of response from the survey. The variance identified are tabulated in
terms of frequency and center of gravity for the degree of agree is calculated between 0-100%
scale as shown in Table 1.
4. International Journal on Cybernetics & Informatics (IJCI) Vol. 3, No. 3, June 2014
14
Table 1. Tabulated results prepared from surveys using Likert Scale
Parameters SD D N A SA COG
(%)
LIU 3 8 6 24 19 76.2
IJP 0 4 4 23 29 85.6
EIA 0 1 4 25 30 88.0
IEE 2 5 12 27 14 75.2
IUC 16 27 8 8 1 43.6
MP 0 3 11 25 21 81.2
EP 4 7 14 27 7 68.8
SR 4 7 15 25 9 69.2
LUI 0 3 11 37 9 77.2
PP 3 7 18 22 10 69.6
SOT 1 4 8 21 26 82.2
CU 2 1 5 30 18 81.6
EB 3 0 4 23 30 85.6
SD = Strongly Disagree, D= Disagree, N= Neutral, A=Agree, SA = Strongly Agree, COG =
Centre of Gravity.
Step 3 (Data Analysis) â For Data analysis, intelligent system is developed having two parts, the
first part is the causal loop for formation of relationship between parameters, and the second part
is fuzzy logic for determining the result of the effect of the internet in the society.
Causal links have been developed between a pair of variables under Ceteris paribus condition
(keeping other variables constant) as in the system dynamics methodology. From these causal
links, a causal loop diagram is drawn as shown in the fig. 4.1.
Fig.2. Causal loop diagram for Internet System
Fuzzy knowledge base is developed from causal links. The fuzzy rules are formed for a cause-
effect relationship between independent parameters and dependent parameters to determine the
output in terms of dependencies.
Rule 1: If EIA is high, then LIU high ELSE if EIA is medium then LIU is medium ELSE if EIA
is low then LIU is LOW.
5. International Journal on Cybernetics & Informatics (IJCI) Vol. 3, No. 3, June 2014
15
Rule 2: If IUC is low, then LIU is high ELSE if IUC is medium then LIU is medium ELSE if
IUC is high then LIU is LOW.
Rule 3: EIA is low and IUC is low, then IJP and IEE and EB are medium ELSE if EIA is low and
IUC is medium then IJP and IEE and EB are medium low. ELSE if EIA is low and IUC is high
then IJP and IEE and EB are low ELSE if EIA is medium and IUC is low then IJP and IEE and
EB are medium high ELSE if EIA is medium and IUC is medium then IJP and IEE and EB are
medium ELSE if EIA is medium and IUC is high then IJP and IEE and EB are medium low
ELSE if EIA is high and IUC is low then IJP and IEE and EB are high ELSE if EIA is high and
IUC is medium then IJP and IEE and EB are medium high ELSE if EIA is high and IUC is high
then IJP and IEE and EB are medium.
Rule 4: If LIU is high, then PP and EP and MP and LUI are high ELSE if LIU is medium then
PP and EP and MP and LUI are medium ELSE if LIU is low then PP and EP and MP and LUI are
low.
Rule 5: If EIA is low and PP is low then CU and SOT are low ELSE if EIA is low and PP is
medium then CU and SOT are medium low ELSE if EIA is low and PP is high then CU and SOT
is medium ELSE if EIA is medium and PP is low, then CU and SOT are medium low ELSE if
EIA is medium and PP is medium then CU and SOT are medium ELSE if EIA is medium and PP
is high, then CU and SOT are medium high ELSE if EIA is high and PP is low, then CU and
SOT are medium ELSE if EIA is high and PP is medium then CU and SOT are medium high
ELSE if EIA is high and PP is high then CU and SOT are high.
Rule 6: If LUI and MP is high, then SR is high ELSE If LUI and MP are medium, then SR is
medium ELSE If LUI and MP is low then SR is low.
Rule 7: If EP and CU and SOT and SR are low, then NEIS is low ELSE If EP and CU and SOT
and SR are the medium, then NEIS is medium ELSE If EP and CU and SOT and SR are high then
NEIS is high.
Rule 8: If EB and IJP and IEE are high, then PEIS is high ELSE If EB and IJP and IEE are the
medium, then PEIS is medium ELSE If EB and IJP and IEE are low then PEIS is low.
The results for fuzzy relationship considering each rule are implemented and shown in the figure:
Step 4 (Data Representation)
Fuzzy rule 1 is implemented for the total range representing one to one positive cause effect
relationship. The input variable is taken as Easy Internet Access and the output variable is taken
Long internet usage. The Causal link is represented in Fig.3 and fuzzy rule output in Fig.4.
Fig.3. Cause effect relationship between EIA and LIU
6. International Journal on Cybernetics & Informatics (IJCI) Vol. 3, No. 3, June 2014
16
Fig.4. Fuzzy output between Easy Internet Access (%) and Long Internet Usage (%)
Fuzzy rule 2 is implemented for the total range representing one to one negative cause effect
relationship. The input variable is taken as Internet Usage Cost and output variable is taken as
Long Internet Usage. The Causal link is represented in Fig.5 and fuzzy rule output in Fig.6
Fig.5. Cause effect relationship between IUC and LIU
Fig.6. Fuzzy output between Internet Usage Cost (%) and Long Internet Usage (%)
Fuzzy rule 3 is implemented taking an Easy Internet Access and Internet Usage Cost as input and
Internet job purpose as output. The Causal link is represented in Fig.7 and fuzzy rule output in
Fig.8.
Fig.7. Cause effect relationship between EIA, IUC and IJP
7. International Journal on Cybernetics & Informatics (IJCI) Vol. 3, No. 3, June 2014
17
Fig.8.Fuzzy rule output between Internet Usage Cost (%), Easy Internet Access (%) and Internet Job
Purpose (%)
Fuzzy rule 4 is implemented taking Long internet usage as input while Psychological problem,
Ethical problem, Medical Problem and Lethargy problem as output. The Causal link is
represented in Fig.9 and fuzzy rule output in Fig.10.
Fig.9. Cause effect relationship between LIU with PP, EP, MP and LUI
Fig.10. Fuzzy output between Long internet Usage (%) with Psychological Problem (%), Ethical Problem
(%), Medical Problem (%) and Lethargy (%)
Fuzzy rule 5 is implemented taking Easy internet Access and Psychological Problem as input and
Spoilage of teenagers as output. The Causal link is represented in Fig.11 and fuzzy rule output in
Fig.12.
Fig.11. Cause effect relationship between EIA, PP and SOT
8. International Journal on Cybernetics & Informatics (IJCI) Vol. 3, No. 3, June 2014
18
Fig.12. Plot between Psychological Problem (%), Easy Internet Access (%) and Spoilage of teenagers (%)
Fuzzy rule 6 is implemented taking Easy internet Access and Psychological Problem as input and
Spoilage of teenagers as output. The Causal link is represented in Fig.13 and fuzzy rule output in
Fig.14.
Fig.13. Cause effect relationship between MP, LUI and SR
Fig.14. Plot between Medical Problems (%), Lethargy (%) and Social Restriction (%)
Fuzzy rule 7 and Fuzzy rule 8 are implemented using the cause effect relationship to determine
the negative and positive effect of the internet on the society by moving in the causal relationship.
Fuzzy rule 7: One to one cause effect relationship is shown in Fig.15 and fuzzy rule output in
Fig.19.
Fig.15. Cause effect relationship between EP, SR, CU, SOT and NEIS
9. International Journal on Cybernetics & Informatics (IJCI) Vol. 3, No. 3, June 2014
19
Ethical problems, social restriction, crime uplift and spoilage of teenagers are taken as input. The
negative effect of internet on society is taking as output. Fuzzy model is created with input
membership functions as shown in Fig.16.
Fig.16. Input membership function for fuzzy rule 7 and 8
The output membership functions are created for the negative effect of internet on society Fig 17.
Fig.17. Output membership function for fuzzy rule 7 and 8
The effect of Ethical Problems and Spoilage of teenagers in society, creating negative effect is
shown in Fig 18.
Fig.18. Plot between Ethical Problems (%), Spoilage of Teenagers (%) and Negative effect of Internet on
Society (%)
Considering all the input parameters for complete range the variation of Negative Effect
10. International Journal on Cybernetics & Informatics (IJCI) Vol. 3, No. 3, June 2014
20
Fig.19. Plot for Negative effect of Internet on Society with variation of input parameters
Fuzzy rule 8 one to one cause effect relationship is represented by the Causal link is represented
in Fig.20 and fuzzy rule output in Fig.22.
.
Fig.20. Cause effect relationship between IJP, EB, IEE and PEIS
Internet Job Purpose, Internet Entertainment Engagement, Ebusiness is taken as input and
Positive Effect of Internet on Society is taken as the output. The membership function is defined
as for fuzzy rule 8 shown in Fig.21.
Fig.21. Plot between Internet entertainment engagements (%), E-business (%) and Positive Effect of
Internet on Society (%)
11. International Journal on Cybernetics & Informatics (IJCI) Vol. 3, No. 3, June 2014
21
Fig.22. Plot for Positive effect on Society with variation of input parameters
According to fuzzy rules the positive effect and negative effect of internet usage is determined for
academicians, professionals, students on the basis of gender by doing inference. Table 2
represents the percentage positive effect and negative effect.
Table 2. Positive and Negative Effect of internet usage in society
Category Gender
PEIS
(%)
NEIS
(%)
Professional M+F 80.4 76
Academicians M+F 80.7 79.4
Students M+F 80.6 77.9
Professionals+
Academicians+ Students
M 80.7 79.2
Professionals+
Academicians+ Students
F 79.1 77
Professionals+
Academicians+ Students
M+F 80.7 77.9
PEIS = Positive effect of internet on society, NEIS= Negative effect of internet on society,
M=male, F=female.
According to survey parameters, the output for positive effect and negative effect of internet is
shown in table II. Although positive effects of internet are high, but simultaneously the negative
effect is also high. This is a major problem for the society. The internet negative effect is arising
due to use of internet for gambling in virtual casinos, playing games, chatting with strangers, day
trading, watching violence and pornography, searching for information not relevant to work. The
effect is that the people start getting restless, irritable, guilty, excess fatigue, anxious and also
suffer from depression. The professionals loose the interest in the work and hence it drops the
productivity. Although the merits of the Internet make it an ideal research tool, but students surf
irrelevant websites, engage in chat room gossip, converse with Internet pen pals, and play
interactive games at the cost of productive activity. This cause student as well as teachers to
become lethargic, compels them to say lie to others, lose concentration on studies, decline in
results. To avoid such negative impact of internet on society, people should start social interaction
with people, spend some time outside in the early morning and evening doing exercises and
meeting friends.
12. International Journal on Cybernetics & Informatics (IJCI) Vol. 3, No. 3, June 2014
22
5. CONCLUSIONS
In this paper, the results of the survey and fuzzy experiments on the negative and positive effect
of the internet on society are presented. The results suggest that the negative effect of internet like
medical problem, social restriction, psychological problems, spoilage of teenagers is occurring
which may result in a chronic disease and destroy our society. Necessary steps should be taken to
remove the problems, so that the internet can be used for the welfare of society.
REFERENCES
[1]A.Venkatesh, (1985) âA conceptualization of household/technology Interactionâ, Advances in
consumer research, Vol.12, pp189-194.
[2]J.I Cole âthe Impact of internet on our Social, Political and Economic lifeâ. UCCLA centre of
communicating policy.
[3]R, kraut, M.Patterson, V.Lundmark, (1998) âA social Technology that reduce social involvement and
psychological wellbeingâ, American Psychologist 53 (a).
[4]N. Nie, (2000) âStudy of Social consequences of the internetâ, Stanford Institute of quantitative study of
society (SIQSS).
[5]J.katz, P.Aspeden, (1997) âMotivation for the barriers to internet usageâ, Internet research Electronic
Networking application and policy, Vol. 7, pp170.
[6]Richardson, G. P., (1986) âProblems with causalâloop diagramsâ, System Dynamics Review, 2(2),
pp158-170.
[7]Kim, D. H., (1992) âGuidelines for drawing causal loop diagramsâ, The Systems Thinker, 3(1), pp5-6.
[8]Wolstenholme, E. F., (1999) âQualitative vs. quantitative modelling: the evolving balanceâ, Journal of
the Operational Research Society, pp422-428.
[9]Anderson, V., & Johnson, L. (1997). Systems thinking basics. Pegasus Communications.
[10]Morecroft, J. D. (1982) âA critical review of diagramming tools for conceptualizing feedback system
modelsâ, Dynamica, 8(1), pp20-29.
[11]Sugeno, M., & Yasukawa, T., (1993) âA fuzzy-logic-based approach to qualitative modellingâ, IEEE
Transactions on fuzzy systems, 1(1), pp7-31.
[12]Yager, R. R., & Filev, D. P. (1994). Essentials of fuzzy modelling and control. New York.
[13]Mamdani, E. H. (1977) âApplication of fuzzy logic to approximate reasoning using linguistic
synthesisâ, Computers, IEEE Transactions on, 100(12), pp1182-1191.
[14]Pavelka, J. (1979) âOn Fuzzy Logic I Manyâvalued rules of inferenceâ, Mathematical Logic Quarterly,
25(3â6), pp45-52.
[15]Ross, T. J. (2009). Fuzzy logic with engineering applications. John Wiley & Sons.
[16]Chaturvedi, D. K., (2005) âDynamic model of HIV/AIDS Population of Agra Regionâ, Int.J.Environ.
Res. Public Health, 2(3), pp420-429.
[17]D.K. Chaturvedi, (2008) Soft computing techniques and its applications in Electrical Engineering,
Studies in Computational Intelligence (SCI) 103.
Authors
Rashmi Chahar is working in the field of intelligent systems. Her focus is to develop
expert systems for the welfare of the society. She has published papers in journals and
conferences and conducted workshops for improvement of research.
Ashish Chandiok is working in the field of Cognitive systems. His focus is to develop
cognitive systems for industrial application. He has published several papers in journals and
given expert lectures in the field of soft computing, Research Methodology and intelligent
systems.
Prof. D. K. Chaturvedi is working in the field of Soft Computing, Cognitive systems and
Conscious System. He has published 90 journals, authored two books published in Springer
and CRC. He has guided several PhD Students in the field of soft computing and intelligent
system.