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31.
BAT algorithm for improving fuzzy C-means clustering for location allocation of rural kiosks in developing countries under e-governance
Rajan Gupta, Sunil K. Muttoo, Saibal K. Pal, 2016, original scientific article

Abstract: Rural Kiosks are important infrastructural pillar in rural regions for internet and basic technology facility all around the world. They are also known as Tele-centers or Common Service Centers and are majorly used by government to promote Electronic Governance. The major characteristic of setting up of Rural Kiosk is their appropriate location so that people from rural region can avail the services at minimum travel cost and time. There are lot of traditional schemes used by researchers in past for location allocation but this paper proposes the usage of Fuzzy C-Means clustering and BAT algorithm to optimize the location of Rural Kiosk. The meta-heuristic approach has produced better results as compared to normal graph theories in past. The experiment has been conducted on a random data set of 72 village locations from India and their clusters are formed. It is found that using only Fuzzy C-Means clustering to allocate the center and by using it in combination with BAT algorithm produced up to 25% of efficient results. This can drastically help the key stakeholders in allocation of these Rural Kiosks at right places so as to maximize their utility.
Keywords: BAT algorithm, location allocation, rural kiosks, fuzzy C-means, e-governance, tele-centers, common service centers
Published in RUNG: 01.04.2021; Views: 1853; Downloads: 0
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32.
Implementation & analysis of integrated utility system in developing nation like India
Rajan Gupta, Sunil K. Muttoo, Saibal K. Pal, 2016, original scientific article

Abstract: Public utility systems are prevalent around the world but are struggling in developing nations like India to work efficiently. Integration of different utilities can be a possible solution on the technology front, so that more requests can be handled with lesser problems. This study provides the implementation design and benefits of an already proposed integration system by the same authors. It is found that Data Storage, Access Time, Transaction Cost, security cost and server’s busy time can become more effective if the implementation of integration system can be put in place. The working prototype is based on three utilities (Gas, Power & Water) of Delhi-NCR, India.
Keywords: information systems, utility system, India, developing nation
Published in RUNG: 01.04.2021; Views: 1880; Downloads: 56
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33.
Binary division fuzzy C-means clustering and particle swarm optimization based efficient intrusion detection for e-governance systems
Sunil K. Muttoo, Saibal K. Pal, 2016, original scientific article

Abstract: With the rapid rise of technology, many unusual and unwanted patterns have been observed in the communication network andrespective systems. This may be attributed to the increase of external threats that cause many security concerns. Such anomalies and unusual behavior lead to a strong need of studying and designing the Intrusion Detection Systems and Clustering. Currently,a variety of clustering methods and their combinations are used to develop an efficient intrusion detection system, but some metrics like low detection rate and high false alarm rate make these models unsatisfactory. The problem of local minima for clustering technique makes their search ability less efficient. An evolutionary technique called particle swarm optimization algorithm, that is based on swarm intelligence, shows a high global maxima search capability. In this paper, these two techniques have been combined to present a novel approach called fuzzy based particle swarm algorithm for the implementation of intrusion detection system. The experiment was conducted on a new data set called Kyoto data set with more number of anomalies. The obtained results were compared with two traditional clustering techniques based on K-Means and Fuzzy C-Means. It was observed that the proposed algorithm outperformed the other two traditional methods on the basis of the Detection Rate and False Alarm rate. In past some researchers have presented the combination of Fuzzy Based Particle Swarm Optimization algorithm to improve the intrusion detection rate,but this rate has been further improved because the algorithm performance depends on the termination condition and the fitness function value which are new in the proposed algorithm. Moreover, cluster numbers have been considered differently in the past, whereas the proposed algorithm works only on binary clustering.
Keywords: intrusion detection, fuzzy C-means clustering, particle swarm optimization, detection rate, e-governance
Published in RUNG: 01.04.2021; Views: 1842; Downloads: 0
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34.
Internet traffic surveillance & network monitoring in India : case study of NETRA
Rajan Gupta, Sunil K. Muttoo, 2016, original scientific article

Abstract: Internet traffic surveillance is gaining importance in today’s digital world. Lots of international agencies are putting in efforts to monitor the network around their countries to see suspicious activities and illegal or illegitimate transmission of messages. India, being a center of attraction for terrorist activities, is also working towards the development of such surveillance systems. NETRA or Network Traffic Analysis is one such effort being taken by the Indian Government to filter suspicious keywords from messages in the network. But is it good enough to be used at the highest level for security analysis or does the system design needs to be improved as compared to other similar systems around the world; this question is answered through this study. The comparison of NETRA is done against Dish Fire, Prism, and Echelon. The design of the NETRA scheme and implementation level analysis of the system shows few weaknesses like limited memory options, limited channels for monitoring, pre-set filters, ignoring big data demands, security concerns, social values breach and ignoring ethical issues. These can be covered through alternate options which can improve the existing system. The Inclusion of self-similarity models, Self-Configuring Network Monitoring, and smart monitoring through early intrusion detections can be embedded in the architecture of existing surveillance system to give it more depth and make it more robust.
Keywords: cyber attacks, NETRA, network monitoring, network traffic analysis, surveillance system, spy system
Published in RUNG: 01.04.2021; Views: 1848; Downloads: 55
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35.
A study on cause related marketing: antecedents and consequents in relation to purchase intention of consumers in Delhi, India
Saibal K. Pal, 2017, original scientific article

Abstract: The study examines the antecedents and consequents of Cause Related Marketing (CRM) and its impact on the purchase intention of consumers directly and indirectly. The aim of the study is to understand the impact of CRM activities on the company and its brand and analyze its influence on the purchase intention of consumers. To fulfill the objectives, descriptive research with sample of 415 consumers has been used. Data is collected with the help of semi-structured questionnaires in Delhi-NCR, India from January-June 2016. To determine sample, convenience sampling is used and analysis is done using statistical techniques such as Correlation, Regression and ANOVA. The finding of the study reveals that sponsorship, market orientation and awareness of events contribute in effective implementation of cause related marketing. Also CRM influences consumer attitude, brand loyalty and corporate reputation. CRM activities were found to have a significant impact on purchase intention of consumers. Also, the findings imply that women related and anti-trafficking issues must be adopted as the central theme for CRM activities to attract more consumers to participate in the campaign. Organizations that intent to increase purchase intention of consumers can do it through Cause Related Marketing campaigns and can understand the antecedents that make CRM a successful activity with the help of this study. The study has paid attention towards conceptualization of CRM and examining the impact of various antecedents and consequences of CRM. Such exhaustive research framework has not been developed and tested by prior studies which novel in current research.
Keywords: cause related marketing, purchase intention, sponsorship, corporate credibility, market orientation, brand loyalty, consumer attitude
Published in RUNG: 01.04.2021; Views: 1872; Downloads: 0
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36.
Converting apprehensive customers to willing customers : building trust in online shopping arena
Saibal K. Pal, 2017, original scientific article

Abstract: This study focuses on knowing about the factors that can affect the trust levels of the consumers involved in online shopping. Trust has been identified as a prominent factor that ultimately leads to the transformation of the apprehensive customers into willing customers. The role of website design features and portal affiliation is tested regarding their impact in affecting the trusting beliefs of the customers. Structural Equation Modeling (SEM) was put to use to do the statistical testing on the data collected through students of tier III city of India. The results showed that the website design features have an important role to play in affecting the trusting beliefs of the people whereas portal affiliation didn’t have much of a role. The study implies that the website managers must focus on their design features if they want to gain the trust of their customers. The portal affiliation wouldn’t be fruitful in the case of a student at least. Better shoppers amongst students must be attracted towards portals through innovative designs and features.
Keywords: online shopping, building trust, website design features, portal affiliation, structural equation modelling, theory of reasoned action
Published in RUNG: 01.04.2021; Views: 1755; Downloads: 0
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37.
Meta-heuristic algorithms to improve fuzzy C-means and K-means clustering for location allocation of telecenters under e-governance in developing nations
Rajan Gupta, Sunil K. Muttoo, Saibal K. Pal, 2019, original scientific article

Abstract: The telecenter, popularly known as the rural kiosk or common service center, is an important building block for the improvement of e-governance in developing nations as they help in better citizen engagement. Setting up of these centers at appropriate locations is a challenging task; inappropriate locations can lead to a huge loss to the government and allied stakeholders. This study proposes the use of various meta-heuristic algorithms (particle swarm optimization, bat algorithm, and ant colony optimization) for the improvement of traditional clustering approaches (K-means and fuzzy C-means) used in the facility location allocation problem and maps them for the betterment of telecenter location allocation. A dataset from the Indian region was considered for the purpose of this experiment. The performance of the algorithms when applied to traditional facility location allocation problems such as set-cover, P-median, and the P-center problem was investigated, and it was found that their efficiency improved by 20%–25% over that of existing algorithms.
Keywords: ant colony optimization, bat algorithm, common service center, e-governance, fuzzy clustering, meta-heuristic algorithm, particle swarm optimization
Published in RUNG: 01.04.2021; Views: 1875; Downloads: 10
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38.
Regional e-governance development index for developing nations
Rajan Gupta, Sunil K. Muttoo, Saibal K. Pal, 2020, original scientific article

Abstract: E-governance has proven to be instrumental in the expansion and evolution of how governments interact with and deliver services to their citizens. The United Nations (UN) E-Governance Development Index (EGDI) is the most widely used metric for assessment of e-governance development; however, this metric is not appropriate for assessment at the regional level, especially for developing nations. Therefore, the authors have studied various factors in the context of developing nations, such as the Online Availability and Performance Index, Telecommunications Index, Human Capital Index, E-governance-related Infrastructure Index, and E-governance Performance Index, with the aim of analyzing the success and implementation rate of e-governance activities across the different regions of a developing nation like India. The results showed that the UN's EGDI is not suitable for assessment at a regional level and that adding new components to the model helps to achieve better results for around 30% of the regions under study. The rankings, which were calculated through the new model and compared against other standard indices, obtained good correlations, proving the validity of the new model. India, as a developing nation, was the region selected for the experimental work. Central governments, state governments, investors, stakeholders, and government consultants can obtain benefits through this research.
Keywords: e-governence, India, e-governance development index
Published in RUNG: 01.04.2021; Views: 1824; Downloads: 47
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39.
Analysis of COVID-19 tracking tool in india: case study of aarogya setu mobile application : Case Study of Aarogya Setu Mobile Application
Rajan Gupta, Manan Bedi, Prashi Goyal, Srishti Wadhera, Vaishnavi Verma, 2020, original scientific article

Abstract: COVID-19 tracking tools or contact-tracing apps are getting developed at a rapid pace by different governments in their respective countries. This study explores one such tool called Aarogya Setu, developed by the Government of India. It is a mobile application developed under the Health Ministry, as a part of the E-Governance initiative, to track and sensitize the citizens of India in a joint battle against COVID-19 spread. The study aims to understand various useful features of this tool and to present different concepts of data science applied within the application along with its importance in managing the ongoing pandemic. The App uses Bluetooth and GPS technologies to alert a user when they are nearby a COVID-19 infected person. The application uses various Data Science concepts such as Classification, Association Rule Mining, and Clustering to analyze COVID-19 spread in India. The study also shows potential upgradations in the application, which includes usage of Artificial Intelligence and Computer Vision to detect COVID-19 patients. The study would be useful for mobile technology professionals, data science professionals, medical practitioners, health-related frontline workers, public administrators, and government officials.
Keywords: COVID-19, India, contact-tracing, tracking tool, Bluetooth, GPS, COVID19 reporting tool, Aarogya Setu
Published in RUNG: 01.04.2021; Views: 1927; Downloads: 60
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40.
Machine learning models for government to predict COVID-19 outbreak
Rajan Gupta, Gaurav Pandey, Poonam Chaudhary, Saibal K. Pal, 2020, original scientific article

Abstract: The COVID-19 pandemic has become a major threat to the whole world. Analysis of this disease requires major attention by the government in all countries to take necessary steps in reducing the effect of this global pandemic. In this study, outbreak of this disease has been analysed and trained for Indian region till 10th May, 2020, and testing has been done for the number of cases for the next three weeks. Machine learning models such as SEIR model and Regression model have been used for predictions based on the data collected from the official portal of the Government of India in the time period of 30th January, 2020, to 10th May, 2020. The performance of the models was evaluated using RMSLE and achieved 1.52 for SEIR model and 1.75 for the regression model. The RMSLE error rate between SEIR model and Regression model was found to be 2.01. Also, the value of R0, which is the spread of the disease, was calculated to be 2.84. Expected cases are predicted around 175K--200K in the three-week time period of test data, which is very close to the actual numbers. This study will help the government and doctors in preparing their plans for the future.
Keywords: COVID-19, India, spread exposed infected recovered model, regression model, machine learning, predictions, forecasting
Published in RUNG: 01.04.2021; Views: 2146; Downloads: 83
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