Papers by Dr. Vipul Vekariya
2022 5th International Conference on Contemporary Computing and Informatics (IC3I)
2023 International Conference on Artificial Intelligence and Smart Communication (AISC)
2023 International Conference on Artificial Intelligence and Smart Communication (AISC)
Modern methods, strategies, and applications from educational data mining significantly contribut... more Modern methods, strategies, and applications from educational data mining significantly contribute to the advancement of the learning environment. The most recent development offers useful resources for analyzing the educational environment of students by examining andusing data mining and machine learning methods to analyse educational data. In today's extremely competitive and complex world, academic institutions function. University administrators frequently struggle with performance evaluation, high-quality instruction, performance evaluation methodologies, and future course of action. In order to address issues that students face while pursuing their education, these colleges must establish student intervention strategies. This systematic review examines the pertinent EDM literature from 2009 to 2021 that relates to detecting kids at risk and dropouts. The review's findings showed that a variety of Deep Learning techniques are utilized to comprehend and address the fundamental issues, including forecasting students who are at danger of dropping out of school and students who will drop out altogether. Furthermore, the majority of studies incorporate data from online learning platforms and databases of student institutions and universities. When it comes to forecasting at-risk pupils and dropout rates, ML techniques have been shown to be crucial. This has improved the students' performance.
2022 International Interdisciplinary Humanitarian Conference for Sustainability (IIHC)
2022 International Interdisciplinary Humanitarian Conference for Sustainability (IIHC)
nternational journal of communication networks and information security, Dec 23, 2022
With the increase in number of devices enabled the Internet of Things (IoT) communication with th... more With the increase in number of devices enabled the Internet of Things (IoT) communication with the centralized cloud computing model. With the implementation of the cloud computing model leads to increased Quality of Service (QoS). The cloud computing model provides the edge computing technologies for the real-time application to achieve reliability and security. Edge computing is considered the extension of the cloud computing technology involved in transfer of the sensitive information in the cloud edge to increase the network security. The real-time data transmission realizes the interaction with the high frequency to derive improved network security. However, with edge computing server security is considered as sensitive privacy information maintenance. The information generated from the IoT devices are separated based on stored edge servers based on the service location. Edge computing data is separated based in edge servers for the guaranteed data integrity for the data loss and storage. Blockchain technologies are subjected to different security problem for the data integrity Intelligent Mobile Edge Computing Integrated with Blockchain Security Analysis for Millimetre-Wave Communication
International Journal of Communication Networks and Information Security (IJCNIS)
Cyber Physical Systems (CPS) comprises of the ubiquitous object concept those are connected with ... more Cyber Physical Systems (CPS) comprises of the ubiquitous object concept those are connected with Internet to provide ability of data transmission and sensing over network. The smart appliances transmits the data through CPS devices with the implementation of Internet of Things (IoT) exhibits improved performance characteristics with significant advantages such as time savings, reduced cost, higher human comfort and efficient electricity utilization. In the minimal complexity sensor nodes cyber physical system is adopted for the heterogeneous environment for the wireless network connection between clients or hosts. However, the conventional security scheme uses the mechanisms for desktop devices with efficient utilization of resources in the minimal storage space environment, minimal power processing and limited energy backup. This paper proposed a Secure Honeynet key authentication (SHKA) model for security attack prevention through effective data monitoring with IoT 4G communicatio...
International Journal of Communication Networks and Information Security (IJCNIS)
For the healthcare framework, automatic recognition of patients’ emotions is considered to be a g... more For the healthcare framework, automatic recognition of patients’ emotions is considered to be a good facilitator. Feedback about the status of patients and satisfaction levels can be provided automatically to the stakeholders of the healthcare industry. Multimodal sentiment analysis of human is considered as the attractive and hot topic of research in artificial intelligence (AI) and is the much finer classification issue which differs from other classification issues. In cognitive science, as emotional processing procedure has inspired more, the abilities of both binary and multi-classification tasks are enhanced by splitting complex issues to simpler ones which can be handled more easily. This article proposes an automated audio-visual emotional recognition model for a healthcare industry. The model uses Deep Residual Adaptive Neural Network (DeepResANNet) for feature extraction where the scores are computed based on the differences between feature and class values of adjacent ins...
International journal of engineering trends and technology, Jan 25, 2022
In today's competitive world good marketing strategy is needed to attract the customers. This... more In today's competitive world good marketing strategy is needed to attract the customers. This proposed system maintains the customer relationship using data mining with TRFM model. Clustering, Classification and Association rule are also used with TRFM model that is useful for market intelligence. Clustering is used to search out customer segments with comparable TRFM values. Classification is used to find out customer's future buying pattern. Association rule mining is used for product recommendation.
International Journal of Advance Engineering and Research Development, 2015
Privacy Concerns in LBS exist on two fronts: location privacy and query Privacy. In this paper we... more Privacy Concerns in LBS exist on two fronts: location privacy and query Privacy. In this paper we investigate issues related to query privacy. In particular, we aim to prevent the LBS server from correlating the service attribute. An important privacy issue in Location Based Services (LBS) is to hide a user's identity while still provide quality location based services. Recently, highly accurate positioning devices enable us to provide various types of location -based services. On the other hand, because position data obtained by such devices include deeply personal information, protection of location privacy is one of the most significant issues of location -based services. Therefore, we propose a technique to anonymize position data. In our proposed technique, the personal user of a location -based service generates several false position data (dummies) sent to the service provider with the true position data of the user. Because the service provider cannot distinguish the true position data, the user's location privacy is protected. But from this method traffic will be increase. As a solution, a diffuser can be placed between mobile unit location based services. Diffuser will send dummy locations to LBS and true data exchange will only be happen between mobile unit and diffuser. The traffic between mobile unit and diffuser will be decrease.
As we all know that great efforts have been taken to guarantee the efficiency of research project... more As we all know that great efforts have been taken to guarantee the efficiency of research project selection. Before research proposals are assigned to appropriate experts for evaluation, research proposals needed to be grouped according to their similarities in research topics. For grouping of the research project selection various data mining technique is being used. In this grouping of the proposal clustering is used. In clustering various technique is there from that here mainly three techniques is being used, first ASOM, second K-MEAN, and third is OPTICS. These all method is being used to cluster research proposals and support research project selection. These cluster algorithms are applied to group the proposals and the merits of each algorithm in text clustering are being used.
The development of computerized advances brings about the development of advanced cybercrimes. Cy... more The development of computerized advances brings about the development of advanced cybercrimes. Cyber-crime is a developing issue, yet the capacity law enforcement organizations to explore and effectively indict crooks for these violations are muddled. While law enforcement agencies have been leading these examinations for a long time, the recently distributed requirements evaluations all showed that there is come up short on the preparation, devices, or staff to successfully direct examinations with the volume or multifaceted nature included a large number of these cases Digital legal sciences plans to gather wrongdoing related proof from different computerized media and investigate it. This survey reviews several branches, methods, and types of evidence in the literature which extract evidence from the system and analyze them. It also discusses the challenges during the collection and analysis of low-level data from the compromised system.
Social media is a very popular way of expressing opinions and integrating with other people in th... more Social media is a very popular way of expressing opinions and integrating with other people in the online world. How to analyze user generated reviews and to classify them into different sentiment classes is gradually becoming a question that people play close attention to. This problem has become a comparison benchmark test for different classification methods. Sentiment analysis focused on social networks, product reviews, stock market, news comments, etc. In this paper, I survey the various algorithms available for sentiment analysis. Different algorithms are use like Support Vector Machine, K-Nearest Neighbor, Artificial Neural Networks, etc. Sentiment analysis is used in politics, to detect stock, to add or nix the advertisements.
Images have become one of the most efficient methods of information transfer, now a day’s images ... more Images have become one of the most efficient methods of information transfer, now a day’s images are preferred. But while transferring the images, means while communicating with each other care must be taken to check that the information reaches only to the desired receiver and not to any other sources. So there is a need of secrecy between source and destination. In order to achieve this some techniques and methods are needed. While transferring information means image has to be sent in such a way that only source and destination can have access to it and also care must be taken to see that even though images are accessed by some unauthorized sources the information is not understood to them. Digital image scrambling is one of the most prominent techniques used for secure transmission of digital images. Various image encryption algorithms based on the permutation–diffusion architecture have been proposed where, however, permutation and diffusion are considered as two separate stage...
Cloud Computing is further generation technology for IT enterprise. Cloud processing has turned o... more Cloud Computing is further generation technology for IT enterprise. Cloud processing has turned out to be basic popular expression in the Information Technology and is a next stage in the advancement of Internet, The Load adjusting issue of cloud processing is a vital issue and basic segment for satisfactory operations in distributed computing framework and it can likewise keep the fast improvement of distributed computing. Numerous customers from all around the globe are requesting the different administrations at quick rate in the current time. Albeit different load adjusting calculations have been outlined that are productive in ask designation by the choice of right virtual machines. In this proposed work, a hybrid load administration calculation has been proposed for circulation of the whole approaching solicitation among the virtual machines viably. Both Static and Dynamic load is to be mixed and this algorithm improved sufficiently and incorporating the paradigm of parallel a...
Advances in Intelligent Systems and Computing, 2016
In mobile cloud computing, data storage and its processing is done externally from the mobile dev... more In mobile cloud computing, data storage and its processing is done externally from the mobile devices. The mobile user can access the applications or data from cloud servers (Dinh et al., Wireless Commun. Mobile Comput. 13(8), 1587–1611 [1]). The client can store his/her multimedia data to the cloud storage server. The client may be given assurance that the access rights of data will only be restricted to authorized access. The cloud service provider assures the clients for proper security, data confidentiality, and privacy for data in their service level agreement (SLA). Clients may be given full assurance in proper privacy policies and procedures for data safety in cloud but there may be risk of unauthorized access of client sensitive data by cloud service provider or cloud attacker. Another risk is the mobility of data. Data may be transferred from one location to other locations. Frequently, data may be transferred from one place to another place so there may be security concerns of data while mobility. To secure the client’s confidential data, we propose a framework designed with modified RSA encryption technique so that client’s multimedia data may be preserved before storing on the cloud from client side.
Indian Journal of Applied Research, Dec 1, 2014
Privacy Concerns in LBS exist on two fronts: location privacy and query Privacy. In this paper we... more Privacy Concerns in LBS exist on two fronts: location privacy and query Privacy. In this paper we investi- gate issues related to query privacy. In particular, we aim to prevent the LBS server from correlating the service attribute. An important privacy issue in Location Based Services (LBS) is to hide a user's identity while still pro- vide quality location based services. Recently, highly accurate positioning devices enable us to provide various types of location-based services. On the other hand, because position data obtained by such devices include deeply personal information, protection of location privacy is one of the most significant issues of location-based services. Therefore, we propose a technique to anonymize position data. In our proposed technique, the personal user of a location-based service generates several false position data (dummies) sent to the service provider with the true position data of the user. Because the service provider cannot distinguish the true position data, the user's location privacy is protected. But from this method traffic will be increase. As a solution, a diffuser can be placed between mobile unit location based services. Diffuser will send dummy locations to LBS and true data exchange will only be happen between mo- bile unit and diffuser. The traffic between mobile unit and diffuser will be decrease.
IEEE Explore, 2023
Modern methods, strategies, and applications from educational data mining significantly contribut... more Modern methods, strategies, and applications from educational data mining significantly contribute to the advancement of the learning environment. The most recent development offers useful resources for analyzing the educational environment of students by examining andusing data mining and machine learning methods to analyse educational data. In today's extremely competitive and complex world, academic institutions function. University administrators frequently struggle with performance evaluation, high-quality instruction, performance evaluation methodologies, and future course of action. In order to address issues that students face while pursuing their education, these colleges must establish student intervention strategies. This systematic review examines the pertinent EDM literature from 2009 to 2021 that relates to detecting kids at risk and dropouts. The review's findings showed that a variety of Deep Learning techniques are utilized to comprehend and address the fundamental issues, including forecasting students who are at danger of dropping out of school and students who will drop out altogether. Furthermore, the majority of studies incorporate data from online learning platforms and databases of student institutions and universities. When it comes to forecasting at-risk pupils and dropout rates, ML techniques have been shown to be crucial. This has improved the students' performance.
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Papers by Dr. Vipul Vekariya