Pub Date : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776386
M. Dadhich, Ruchi Doshi, S. Mathur, Rajesh Meena, Rajat Kumar Gujral, P. Dhotre
One of the most remarkable changes in the academic Diaspora is the international creation of virtual platforms, which has given rise to a new edge system of learning. Covid-19 presents a unique and severe problem on every front. The nationwide shutdown by the administration aims to control the diffusion of Covid-19 at education institutions across the country. Many (local, national, and worldwide) institutions have implemented a reliable and beneficial contactless atmosphere for students and faculties to maintain the continuity of learning. As a result, teachers and students are greatly influenced by the new-age virtual teaching method adopted and implemented. The survey respondents were picked by a combination of online surveys and personality tests, and then the questionnaire they were given included both closed- and open-ended items. The numbers of university and secondary school portals have recently seen an upward trend. So, to better investigate the abilities of teachers and learners to identify the efficiency of dominating content delivery methods, a hybrid approach of the exploratory study was employed. Students and faculty, 140 each who have taken web-based learning at 25 Indian institutions, are sampled using a snowball sampling methodology. The results of the t-test demonstrated a considerable divergence in teaching-learning impressions between faculty and students on three manifests ($mathrm{p} < 0.005$). Learners' responses differed from faculty responses, and statistically significant differences were found, such as scientific material can be taught effectively online, improved technocratic pedagogy is the core part of e-learning, reliance on computers/connectivity.
{"title":"Empirical Study of Awareness towards Blended e-learning Gateways during Covid-19 Lockdown","authors":"M. Dadhich, Ruchi Doshi, S. Mathur, Rajesh Meena, Rajat Kumar Gujral, P. Dhotre","doi":"10.1109/CCGE50943.2021.9776386","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776386","url":null,"abstract":"One of the most remarkable changes in the academic Diaspora is the international creation of virtual platforms, which has given rise to a new edge system of learning. Covid-19 presents a unique and severe problem on every front. The nationwide shutdown by the administration aims to control the diffusion of Covid-19 at education institutions across the country. Many (local, national, and worldwide) institutions have implemented a reliable and beneficial contactless atmosphere for students and faculties to maintain the continuity of learning. As a result, teachers and students are greatly influenced by the new-age virtual teaching method adopted and implemented. The survey respondents were picked by a combination of online surveys and personality tests, and then the questionnaire they were given included both closed- and open-ended items. The numbers of university and secondary school portals have recently seen an upward trend. So, to better investigate the abilities of teachers and learners to identify the efficiency of dominating content delivery methods, a hybrid approach of the exploratory study was employed. Students and faculty, 140 each who have taken web-based learning at 25 Indian institutions, are sampled using a snowball sampling methodology. The results of the t-test demonstrated a considerable divergence in teaching-learning impressions between faculty and students on three manifests ($mathrm{p} < 0.005$). Learners' responses differed from faculty responses, and statistically significant differences were found, such as scientific material can be taught effectively online, improved technocratic pedagogy is the core part of e-learning, reliance on computers/connectivity.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126612552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776398
Aparna S. Nagure, S. Shahapure
The rainfall-runoff analysis and modeling have been the subject of a large number of research activities and a range of types of models have been developed in the last few decades, to predict the runoff well in advance to avoid the huge amount of losses due to floods. However, all these research activities are focused on the result and accuracy of models and their comparative study. It often remains unclear which model is best under which conditions. It is necessary to select the appropriate rainfall-runoff model for the watershed area according to its physical/chemical/biological characteristics. In this paper, one of the significant characteristics of the watershed that is the size of the case study area is selected as a parameter to understand how it affects the selection of the model. To understand this, 42 research papers published between 2000 to 2019 have been reviewed and categorized according to the size of the watershed, climatic conditions, and type of models used for rainfall-runoff analysis. The result obtained indicates that for major research work, black box models or data-driven models have been used for the watershed of size ranging between 250 km2 to 10000 km2. Similarly, maximum work is carried out for medium size watershed areas.
{"title":"Effect of Watershed Characteristics on a Rainfall Runoff Analysis and Hydrological Model Selection - A review","authors":"Aparna S. Nagure, S. Shahapure","doi":"10.1109/CCGE50943.2021.9776398","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776398","url":null,"abstract":"The rainfall-runoff analysis and modeling have been the subject of a large number of research activities and a range of types of models have been developed in the last few decades, to predict the runoff well in advance to avoid the huge amount of losses due to floods. However, all these research activities are focused on the result and accuracy of models and their comparative study. It often remains unclear which model is best under which conditions. It is necessary to select the appropriate rainfall-runoff model for the watershed area according to its physical/chemical/biological characteristics. In this paper, one of the significant characteristics of the watershed that is the size of the case study area is selected as a parameter to understand how it affects the selection of the model. To understand this, 42 research papers published between 2000 to 2019 have been reviewed and categorized according to the size of the watershed, climatic conditions, and type of models used for rainfall-runoff analysis. The result obtained indicates that for major research work, black box models or data-driven models have been used for the watershed of size ranging between 250 km2 to 10000 km2. Similarly, maximum work is carried out for medium size watershed areas.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128961435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776440
Md. Rekib Ahmed, Neeraj Bhadani, I. Chakraborty
With the emergence of deep neural networks along with high-end computers that can process deep architectures, there has been a lot of research when Computer Vision and Natural Language Processing has been fused into a single problem. To enable students and researchers to deep dive into multimodal deep learning Facebook AI Research team published a dataset on hateful meme classification “The Hateful Meme Challenge Dataset” in May 2020 that gave us the motivation to test ourselves and an opportunity to learn more about the dataset. The rise of communication on the internet with memes as a medium, they have been used to convey incorrect information, political agendas and also has led to cyberbullying, trolling etc. This results in the need of creating an automated tool that can detect such hateful content published on the internet and remove it at the root level before it does any harm. This paper intends to adopt Unimodal Text and Image models using Bert, LSTM and VGG16, Resnet50, SE-Resnet50, XSE-Resnet architectures and combining them into Multimodal models for effective prediction of a hateful meme. The paper compares various architectures both unimodal models and multimodal models on the evaluation metrics AUC-ROC score, F1 score and accuracy score.)
{"title":"Hateful Meme Prediction Model Using Multimodal Deep Learning","authors":"Md. Rekib Ahmed, Neeraj Bhadani, I. Chakraborty","doi":"10.1109/CCGE50943.2021.9776440","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776440","url":null,"abstract":"With the emergence of deep neural networks along with high-end computers that can process deep architectures, there has been a lot of research when Computer Vision and Natural Language Processing has been fused into a single problem. To enable students and researchers to deep dive into multimodal deep learning Facebook AI Research team published a dataset on hateful meme classification “The Hateful Meme Challenge Dataset” in May 2020 that gave us the motivation to test ourselves and an opportunity to learn more about the dataset. The rise of communication on the internet with memes as a medium, they have been used to convey incorrect information, political agendas and also has led to cyberbullying, trolling etc. This results in the need of creating an automated tool that can detect such hateful content published on the internet and remove it at the root level before it does any harm. This paper intends to adopt Unimodal Text and Image models using Bert, LSTM and VGG16, Resnet50, SE-Resnet50, XSE-Resnet architectures and combining them into Multimodal models for effective prediction of a hateful meme. The paper compares various architectures both unimodal models and multimodal models on the evaluation metrics AUC-ROC score, F1 score and accuracy score.)","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121943102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776387
Mitali Patil, Harsha Kalmath, Khushboo Chamedia, Shreya Pandey, Shilpa Deshpande, N. Kurkure, G. Misra
Cloud computing technology in recent years has seen rapid growth with a number of institutions and organizations adopting it, for its scalable, extensible and rapidly available services. Many scientific institutions over the years have been executing high performance jobs on traditional high-performance computing (HPC) clusters, but the ever-increasing use of resources calls for optimizing the existing infrastructure to deliver better ubiquitous services. This paper presents the implementation of OpenStack cloud computing platform for executing scientific applications at IISER, Pune. This platform additionally can be tailored to serve the institute's need and requirements. The paper also analyses and discusses the effectiveness of our deployment method, concluding with some feasible scenarios that are achievable to make the cloud scalable and heterogeneous.
{"title":"OpenStack Cloud Deployment for Scientific Applications","authors":"Mitali Patil, Harsha Kalmath, Khushboo Chamedia, Shreya Pandey, Shilpa Deshpande, N. Kurkure, G. Misra","doi":"10.1109/CCGE50943.2021.9776387","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776387","url":null,"abstract":"Cloud computing technology in recent years has seen rapid growth with a number of institutions and organizations adopting it, for its scalable, extensible and rapidly available services. Many scientific institutions over the years have been executing high performance jobs on traditional high-performance computing (HPC) clusters, but the ever-increasing use of resources calls for optimizing the existing infrastructure to deliver better ubiquitous services. This paper presents the implementation of OpenStack cloud computing platform for executing scientific applications at IISER, Pune. This platform additionally can be tailored to serve the institute's need and requirements. The paper also analyses and discusses the effectiveness of our deployment method, concluding with some feasible scenarios that are achievable to make the cloud scalable and heterogeneous.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125838826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776410
Niteesh Kumar, Pranav P, Vishal Nirney, G. V.
Headways in deep learning has enabled the creation of fraudulent digital content with ease. This fraudulent digital content created is entirely indistinguishable from the original digital content. This close identicalness has what it takes to cause havoc. This fraudulent digital content, popularly known as deepfakes having the potential to change the truth and decay faith, can leave impressions on a large scale and even our daily lives. Deepfake is composed of two words, the first being deep: deep learning and the second being fake: fake digital content. Artificial intelligence forming the nucleus of any deepfake formulation technology empowers it to dodge most of the deepfake detection techniques through learning. This ability of deepfakes to learn and elude detection technologies is a matter of significant concern. In this research work, we focus on our efforts towards the detection of deepfake images. We follow two approaches for deepfake image detection, and the first is to build a custom CNN based deep learning network to detect deepfake images, and the second is to use the concept of transfer learning.
{"title":"Deepfake Image Detection using CNNs and Transfer Learning","authors":"Niteesh Kumar, Pranav P, Vishal Nirney, G. V.","doi":"10.1109/CCGE50943.2021.9776410","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776410","url":null,"abstract":"Headways in deep learning has enabled the creation of fraudulent digital content with ease. This fraudulent digital content created is entirely indistinguishable from the original digital content. This close identicalness has what it takes to cause havoc. This fraudulent digital content, popularly known as deepfakes having the potential to change the truth and decay faith, can leave impressions on a large scale and even our daily lives. Deepfake is composed of two words, the first being deep: deep learning and the second being fake: fake digital content. Artificial intelligence forming the nucleus of any deepfake formulation technology empowers it to dodge most of the deepfake detection techniques through learning. This ability of deepfakes to learn and elude detection technologies is a matter of significant concern. In this research work, we focus on our efforts towards the detection of deepfake images. We follow two approaches for deepfake image detection, and the first is to build a custom CNN based deep learning network to detect deepfake images, and the second is to use the concept of transfer learning.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"113 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133351012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776419
Harsh D Shah, Vinayak Tupe, Amit Rathod, Sohel Shaikh, Nilesh J. Uke
Virtual Tour can be created stored in some MB's or GB's and can be accessed by a user from any corner of the world having a strong internet connection. Many colleges have represented their campus in digital format so many student's can have an idea how college campus looks. The way of representing virtual tour of most of the colleges are the same using a 360-degree virtual tour which are the 2D images stitched together to form a long continuous image. But our virtual has real objects that are represented in a 3D Gaming environment. We have combined the idea of 3D Gaming and 360-degree images to create an actual campus environment where user can move around. We have used First Person Perspective Approach which results in when the user controls it he feels that he is walking on a real college campus. For this, we have developed our 3D Model using as popular open-source modelling tool Blender2.8. And for giving a taste of gaming we are exporting our model into the web using the Babylon.js library which is new in the market but provides all assets to develop a 3D game. So are represent our virtual in a unique way where a user has all control and can roam inside the college campus smoothly.
{"title":"A Progressive Web App for Virtual Campus Tour","authors":"Harsh D Shah, Vinayak Tupe, Amit Rathod, Sohel Shaikh, Nilesh J. Uke","doi":"10.1109/CCGE50943.2021.9776419","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776419","url":null,"abstract":"Virtual Tour can be created stored in some MB's or GB's and can be accessed by a user from any corner of the world having a strong internet connection. Many colleges have represented their campus in digital format so many student's can have an idea how college campus looks. The way of representing virtual tour of most of the colleges are the same using a 360-degree virtual tour which are the 2D images stitched together to form a long continuous image. But our virtual has real objects that are represented in a 3D Gaming environment. We have combined the idea of 3D Gaming and 360-degree images to create an actual campus environment where user can move around. We have used First Person Perspective Approach which results in when the user controls it he feels that he is walking on a real college campus. For this, we have developed our 3D Model using as popular open-source modelling tool Blender2.8. And for giving a taste of gaming we are exporting our model into the web using the Babylon.js library which is new in the market but provides all assets to develop a 3D game. So are represent our virtual in a unique way where a user has all control and can roam inside the college campus smoothly.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134233580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776479
Swati V. Patel, Satyen Parikh, Savan H. Patel
In India, specifically in North Gujarat region most of the farmers are small or marginal farmers who don't have a much hectors of land. In that case famers cannot effort their own tube wells to irrigate their crops. To come up with this situation they are sharing one tube well and paying to tube well owner for the water they used this culture is called Shared Tube well culture. The adoption of smart irrigation system is automates the water conveying system to the harvests to guarantee every one of the crops ensure sufficient water for their healthy growth, to diminish the measure of water squandered in irrigation, and to limit the financial cost for the users.
{"title":"Irrigation to Smart Irrigation and Tube Well Users","authors":"Swati V. Patel, Satyen Parikh, Savan H. Patel","doi":"10.1109/CCGE50943.2021.9776479","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776479","url":null,"abstract":"In India, specifically in North Gujarat region most of the farmers are small or marginal farmers who don't have a much hectors of land. In that case famers cannot effort their own tube wells to irrigate their crops. To come up with this situation they are sharing one tube well and paying to tube well owner for the water they used this culture is called Shared Tube well culture. The adoption of smart irrigation system is automates the water conveying system to the harvests to guarantee every one of the crops ensure sufficient water for their healthy growth, to diminish the measure of water squandered in irrigation, and to limit the financial cost for the users.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114721432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776418
Kuldeep Hule, Arjun Dashrath, Ashwin Gupta
In the last decade, the blockchain industry has solidified itself as one of the most secure forms of data storage. The emergence of extremely secure cryptocurrencies that have a plethora of advantages over regular internet banking has brought about a revolutionary change in the banking industry. The mobile payment users have skyrocketed with an estimated proximity mobile payment transaction user count of 1.31 billion in 2023. Therefore, there is a need for a cryptocurrency based unified payment interface (UPI) that would grant additional security and improve the transaction process drastically over the existing mobile payment system. We worked out on this aspect and proposed a scheme that would allow mobile devices to mine blocks themselves and generate their own transactions rather than depending on third-party services or bank servers.
{"title":"Self-Mining Blockchain Mobile Unified Payment Interface","authors":"Kuldeep Hule, Arjun Dashrath, Ashwin Gupta","doi":"10.1109/CCGE50943.2021.9776418","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776418","url":null,"abstract":"In the last decade, the blockchain industry has solidified itself as one of the most secure forms of data storage. The emergence of extremely secure cryptocurrencies that have a plethora of advantages over regular internet banking has brought about a revolutionary change in the banking industry. The mobile payment users have skyrocketed with an estimated proximity mobile payment transaction user count of 1.31 billion in 2023. Therefore, there is a need for a cryptocurrency based unified payment interface (UPI) that would grant additional security and improve the transaction process drastically over the existing mobile payment system. We worked out on this aspect and proposed a scheme that would allow mobile devices to mine blocks themselves and generate their own transactions rather than depending on third-party services or bank servers.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115801131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776360
Vikas Rattan, Shikha Sharma, R. Mittal, Varun Malik
It is the dream of every student to attain an excellent career with decent remuneration. It will be an additional benefit if they get a high-profile job during their campus placement before they leave. The campus placement activities with the right resources at the right time and with minimal cost are of the greatest benefit to undergraduates regardless of any stream viz. engineering, business, medical, or sciences. The scope of the paper is to prepare an automated model that predicts or analyzes the probability of students getting positioned in a company by salient parameters like academic performance in terms of CGPA, test marks, or other professional degree evaluations and another non-academic parameter such as gender. For this intention, one of the classification algorithms named Decision Tree and up sampling technique “Synthetic Minority Oversampling Technique” had been used. The outcome of this analysis shall lend a hand to the organization to propose an approach that enhances the performance of students to get a better job in the pre-final years.
{"title":"Applying SMOTE with Decision Tree Classifier for Campus Placement Prediction","authors":"Vikas Rattan, Shikha Sharma, R. Mittal, Varun Malik","doi":"10.1109/CCGE50943.2021.9776360","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776360","url":null,"abstract":"It is the dream of every student to attain an excellent career with decent remuneration. It will be an additional benefit if they get a high-profile job during their campus placement before they leave. The campus placement activities with the right resources at the right time and with minimal cost are of the greatest benefit to undergraduates regardless of any stream viz. engineering, business, medical, or sciences. The scope of the paper is to prepare an automated model that predicts or analyzes the probability of students getting positioned in a company by salient parameters like academic performance in terms of CGPA, test marks, or other professional degree evaluations and another non-academic parameter such as gender. For this intention, one of the classification algorithms named Decision Tree and up sampling technique “Synthetic Minority Oversampling Technique” had been used. The outcome of this analysis shall lend a hand to the organization to propose an approach that enhances the performance of students to get a better job in the pre-final years.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116251897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776421
R. Mittal, A. Mittal, Arun Aggarwal
Indian m-health app Aarogya Setu has made a significant contribution in terms of contactability tracing and disease management during the initial days of the COVID-19 pandemic, with its contact tracking approach to infectious individuals and its health tips for eliminating new coronaviruses. The goal of this study is to forecast whether or not Indian consumers will continue to use this app. According to previous studies, the context or setting has a substantial impact on the customer's perceived value. The current study's unique setting is to investigate the parameters impacting Indians' ongoing use of the mobile mHealth app AarogyaSetu. An extended technology adoption model (TAM) has been proposed and tested to achieve this wide goal, with the addition of three additional constructs: social influence, health consciousness, and trust in the app developer.
{"title":"Modeling the Prediction of Continued Usage of COVID-19 mhealth App in India","authors":"R. Mittal, A. Mittal, Arun Aggarwal","doi":"10.1109/CCGE50943.2021.9776421","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776421","url":null,"abstract":"Indian m-health app Aarogya Setu has made a significant contribution in terms of contactability tracing and disease management during the initial days of the COVID-19 pandemic, with its contact tracking approach to infectious individuals and its health tips for eliminating new coronaviruses. The goal of this study is to forecast whether or not Indian consumers will continue to use this app. According to previous studies, the context or setting has a substantial impact on the customer's perceived value. The current study's unique setting is to investigate the parameters impacting Indians' ongoing use of the mobile mHealth app AarogyaSetu. An extended technology adoption model (TAM) has been proposed and tested to achieve this wide goal, with the addition of three additional constructs: social influence, health consciousness, and trust in the app developer.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128509869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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