56
20
2150
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Conference Papers
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Categorizing Disaster Tweets Using Learning Based Models for Emergency Crisis Management
Subject
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Bi-LSTM; Deep Learning; Disaster Management; Disaster Tweets; Machine Learning; Natural Language Processing; Support Vector Machine; TF-IDF Vectorizer; Word2Vec Vectorizer
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Social media communication is essential to the crisis response aftermath of a massive tragedy. Facebook, Twitter, and other social media network platforms are effective instruments for connecting and fostering collaboration among catastrophe victims and other groups. As a result, numerous research publications on tweet analysis have been released. Tweet analysis during a crisis helps in understanding the nuances of the incident. Existing works primarily focused on tweet sentiment analysis and binary categorization of tweets into catastrophe relevant or not. Our work mainly categorizes catastrophe tweets into seven categories: Blizzard, earthquake, flood, hurricane, tornado, wildfire, and not-relevant tweets. Deep learning and machine learning methods were employed to categorize the tweets. The annotated data is subjected to classification using Support Vector Machine (SVM) utilizing Term Frequency-Inverse Document Frequency (TF-IDF) Vectorizer and Word2Vec Vectorizer and compares the accuracy of different kernel functions. Bidirectional Long Short Term Memory (Bi-LSTM) is used on the labeled data as a deep learning technique. SVM exhibited 88% accuracy compared to 87% for Bi-LSTM. Empirical evidence shows that our methodology is more productive and efficient than previous approaches. From this knowledge of the incident, emergency aid organizations may draw conclusions and act immediately. 2023 IEEE.
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Asinthara K.; Jayan M.; Jacob L.
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2023 9th International Conference on Advanced Computing and Communication Systems, ICACCS 2023, pp. 1133-1138.
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Institute of Electrical and Electronics Engineers Inc.
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2023-01-01
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<a href="https://doi.org/10.1109/ICACCS57279.2023.10113105" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICACCS57279.2023.10113105</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159760505&doi=10.1109%2FICACCS57279.2023.10113105&partnerID=40&md5=18858763556b708a0d2d910b5c1b9a46" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159760505&doi=10.1109%2fICACCS57279.2023.10113105&partnerID=40&md5=18858763556b708a0d2d910b5c1b9a46</a>
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ISBN: 979-835039737-6
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Online
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English
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Conference paper
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Asinthara K., Christ University, Department of Data Science, Bangalore, India; Jayan M., Christ University, Department of Data Science, Bangalore, India; Jacob L., Christ University, Department of Data Science, Bangalore, India
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Conference Papers
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Title
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Performance Analysis of Logical Structures Using Ternary Quantum Dot Cellular Automata (TQCA)-Based Nanotechnology
Subject
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Energy; J-K flip-flop; LSSD; Power; Quantum phenomenon for combinational as well as sequential logic; Schrodinger equation; TQCA
Description
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Ternary Quantum-Dot Cellular Automata (TQCA) is a developing nanotechnology that guarantees lower power utilization and littler size, with quicker speed contrasted with innovative transistor. In this article, we are going to propose a novel architecture of level-sensitive scan design (LSSD) in TQCA. These circuits are helpful for the structure of numerous legitimate and useful circuits. Recreation consequences of proposed TQCA circuits are developed by utilizing such QCA designer tool. In realization to particular specification, we need to find the parameter values by using Schrodinger equation. Here, we have optimized the different parameter in the equation of Schrodinger. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Tapna S.; Chakrabarti K.; Mukhopadhyay D.
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Lecture Notes in Networks and Systems, Vol-613 LNNS, pp. 421-441.
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Springer Science and Business Media Deutschland GmbH
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2023-01-01
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<a href="https://doi.org/10.1007/978-981-19-9379-4_31" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-9379-4_31</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161156929&doi=10.1007%2F978-981-19-9379-4_31&partnerID=40&md5=c3bfae582e402fcd7061efb1c8c48efb" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161156929&doi=10.1007%2f978-981-19-9379-4_31&partnerID=40&md5=c3bfae582e402fcd7061efb1c8c48efb</a>
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ISSN: 23673370; ISBN: 978-981199378-7
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Online
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English
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Tapna S., Durgapur Institute of Advanced Technology and Management, Durgapur, India; Chakrabarti K., Haldia Institute of Technology, Haldia, India; Mukhopadhyay D., Christ (Deemed to be University), Bengaluru, India
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Title
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Conference Papers
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Dublin Core
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Title
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A Comprehensive Investigation of Blockchain Technology's Role in Cyber Security
Subject
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blockchain; blockchain applications; blockchain future; blockchain limitations; blockchain properties; cryptocurrency; cybersecurity; privacy
Description
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In recent years, blockchain has become an extremely trending technology, capable of solving a variety of problems. One of these domains is cybersecurity, where blockchain technology has a huge scope. To dive deeper into this topic, we first need to understand the cybersecurity domain, the need for this field, and how it has become crucial to the current Information-Technology industry. Once we have a good understanding of the field of cybersecurity, we next focus on blockchain technology, its basic working process, and what makes it a trending infrastructural technology in today's world. The basic idea about the field of cybersecurity and blockchain technology can help us understand how the two different fields can be integrated to solve several problems in the cybersecurity domain. Eventually, we discuss the pros and cons of blockchain technology in cybersecurity and how the integration of the two different fields can make a difference. This study aims to explore various possibilities where blockchain technology can be utilized in several applications to solve a variety of problems in the field of cybersecurity. 2023 IEEE.
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Dixit R.R.; Gokulapriya R.
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2023 9th International Conference on Advanced Computing and Communication Systems, ICACCS 2023, pp. 386-390.
Publisher
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Institute of Electrical and Electronics Engineers Inc.
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2023-01-01
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<a href="https://doi.org/10.1109/ICACCS57279.2023.10113026" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICACCS57279.2023.10113026</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159766687&doi=10.1109%2FICACCS57279.2023.10113026&partnerID=40&md5=d5b009304597e59c1a06a49354a199ca" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159766687&doi=10.1109%2fICACCS57279.2023.10113026&partnerID=40&md5=d5b009304597e59c1a06a49354a199ca</a>
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ISBN: 979-835039737-6
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Online
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English
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Conference paper
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Dixit R.R., Reliance Jio, Bangalore, India; Gokulapriya R., Christ (Deemed to be University), Department of Cse, Bangalore, India
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Title
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Conference Papers
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Performance Analysis of Various Machine Learning Classification Models Using Twitter Data: National Education Policy
Subject
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classifier; Decision Tree; Gaussian Naive Bayes; Logistic Regression; Machine Learning; Natural Language Processing; Random Forest; Sentiment Analysis; Support Vector Machines; Twitter; XGBoost
Description
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With the exponential growth of social networking sites, people are using these platforms to express their sentiments on everyday issues. Collection and analysis of people's reactions to purchases of products, public services, etc. are important from a marketing and innovation perspective. Sentiment analysis also called opinion mining or emotion extraction is the classification of emotions in text. This technique has been widely used over the years to determine sentiment within given text data. Twitter is a social media platform primarily used by people to express their feelings about specific events. In this paper, collected tweets about National Education Policy which has been a hot topic for a while; and analyzed them using various machine learning algorithms such as Random Forest classifier, Logistic Regression, SVM, Decision Tree, XGBoost, Naive Bayes. This study shows that the Decision tree algorithm is performing best, compare to all the other algorithms. 2023 IEEE.
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Agarwal K.; Deepa S.; Sivabalan R.V.; Balakrishnan C.
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Proceedings of the International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, ICIITCEE 2023, pp. 862-870.
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Institute of Electrical and Electronics Engineers Inc.
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2023-01-01
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<a href="https://doi.org/10.1109/IITCEE57236.2023.10091034" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/IITCEE57236.2023.10091034</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85156107398&doi=10.1109%2FIITCEE57236.2023.10091034&partnerID=40&md5=09b0f0af2fba2e04a41ce3d03fc7143f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85156107398&doi=10.1109%2fIITCEE57236.2023.10091034&partnerID=40&md5=09b0f0af2fba2e04a41ce3d03fc7143f</a>
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ISBN: 978-166546263-1
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Online
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English
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Conference paper
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Agarwal K., Christ University, Department Computer Science, Bangalore, India; Deepa S., Christ University, Department Computer Science, Bangalore, India; Sivabalan R.V., Christ University, Department Computer Science, Bangalore, India; Balakrishnan C., Christ University, Department Computer Science, Bangalore, India
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Conference Papers
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Impact of blended education system on outcome-based learning and sector skills development
Subject
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Blended Education System; Effective Education System; Outcome Based Learning; Sector Skill Development
Description
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An effective education system transforms the teaching and learning process into innovative idea generation and independent working ability. A blended education system is the representation of effective education that connects the teachers, students, and educational institutions for content development, delivery of effective teaching methods, and choice-based learning. The motive for initiating the research work was to address the demand for outcome-based learning in society that can fulfill the sector-wise human resource requirements and sector skill development. A blended education system helps to design effective courses and degrees with the capacity of choosing subjects, lectures, and teachers either in online or offline mode of education. The system may also assist in preparing the learning pattern like classroom-based learning, internship-based learning, or learning through project works. The researchers identified the dependent and independent variables with the help of expert opinion. The questionnaire was designed with all relevant questions based on the variables and refined through a pilot study. The research outcomes are described by understanding the nature of quantitative data using statistical tools like frequency distribution, t-test, and ANOVA test with the connectivity of qualitative data and the reality of social issues. 2023 IEEE.
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Podder S.K.; Samanta D.; Thomas B.; Dutta S.; Bhattacharya A.
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11th International Conference on Internet of Everything, Microwave Engineering, Communication and Networks, IEMECON 2023
Publisher
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Institute of Electrical and Electronics Engineers Inc.
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2023-01-01
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<a href="https://doi.org/10.1109/IEMECON56962.2023.10092299" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/IEMECON56962.2023.10092299</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85154549357&doi=10.1109%2FIEMECON56962.2023.10092299&partnerID=40&md5=c6e0fd2ddba0bc98e84a3da58b64ee35" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85154549357&doi=10.1109%2fIEMECON56962.2023.10092299&partnerID=40&md5=c6e0fd2ddba0bc98e84a3da58b64ee35</a>
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ISBN: 978-166547512-9
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Online
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English
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Conference paper
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Podder S.K., Dayananda Sagar College of Arts,Science and Commerce, Dept. of Commerce and Management, Karnataka, Bangalore, India; Samanta D., Rochester Institute of Technology, Rit Global Campus, Rit Kosovo (A.U.K), Dept. of Computing and Information Technologies, Kosovo, Europe, Prishtina, 10000, Serbia; Thomas B., Christ University, Dept. of Cse, Karnataka, Bangalore, India; Dutta S., Institute of Engineering & Management, Dept. of Computer Science & Applications, Kolkata, India; Bhattacharya A., Institute of Engineering & Management, Dept. of Computer Science & Applications, Kolkata, India
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Conference Papers
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3D Modelling and Rendering Using Autodesk 3ds Max
Subject
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Blended Education System; Effective Education System; Outcome Based Learning; Sector Skill Development.
Description
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This is outlined how to create a 3D custom kitchen design, including how to set up the sources, details, work with managing various modifiers like edit poly, slice, mesh select, turbo smooth, lattice, bend, shell modifier, so to provide the kitchen an authentic appearance. The method materials are fitted to the model output, together with illuminating the environment leveraging Arnold lights that are intended to be utilized with this renderer only. It has features that are optimised for rendering with Arnold. Procedures and methods regarding rendering are indeed specified. The final rendering was made out of several drawings. Our report's intention is to develop a kitchen design that enriches models with materials and ample shapes from standard extended primitive along with the mostly utilization of pro-boolean. Finally, a material editor was used to improve the model. target illumination, too. 2023 IEEE.
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Dangi P.; Jain A.; Samanta D.; Dutta S.; Bhattacharya A.
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11th International Conference on Internet of Everything, Microwave Engineering, Communication and Networks, IEMECON 2023
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Institute of Electrical and Electronics Engineers Inc.
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2023-01-01
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<a href="https://doi.org/10.1109/IEMECON56962.2023.10092375" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/IEMECON56962.2023.10092375</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85154609607&doi=10.1109%2FIEMECON56962.2023.10092375&partnerID=40&md5=7d11966ca736815e20d007ad806cd382" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85154609607&doi=10.1109%2fIEMECON56962.2023.10092375&partnerID=40&md5=7d11966ca736815e20d007ad806cd382</a>
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ISBN: 978-166547512-9
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Online
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English
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Conference paper
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Dangi P., Christ University, Dept. of Computer Science, Karnataka, Bangalore, India; Jain A., Christ University, Dept. of Computer Science, Karnataka, Bangalore, India; Samanta D., Rit Kosovo (A.U.K), Dept. of Computing and Information Technologies, Kosovo, Europe, Prishtina, 10000, Serbia, Rochester Institute of Technology, Rit Global Campus, Kosovo, Europe, Prishtina, 10000, Serbia; Dutta S., Institute of Engineering & Management, Dept. of Computer Science & Applications, Kolkata, India; Bhattacharya A., Institute of Engineering & Management, Dept. of Computer Science & Applications, Kolkata, India
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Conference Papers
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Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
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Deploying Fact-Checking Tools to Alleviate Misinformation Promulgation in Twitter Using Machine Learning Techniques
Subject
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Fact-checking; Fake news; Misinformation; Social media; Twitter
Description
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In the present era, the rising portion of our lives is spending interactions online with social media platforms. Thanks to the latest technology adoption as well as smartphones proliferation. Gaining news from the platforms of social media is quicker, easier as well as cheaper in comparison with other traditional media platforms such as T.V and newspapers. Hence, social media is being exploited in order to spread misinformation. The study tends to construct fake corpus that comprises tweets for a product advertisement. The FakeAds corpus objective is to explore the misinformation impact on the advertising and marketing materials for a particular product as well as what kinds of products are targeted mostly on Twitter to draw the consumers attention. Products include cosmetics, fashions, health, electronics, etc. The corpus is varied and novel to the topic (i.e., Twitter role in spreading misinformation in relation to production promotion and advertising) as well as in terms of fine-grained annotations. The guidelines of the annotations were framed through the guidance of domain experts as well as the annotation is done with two domain experts, which results in higher quality annotation, through the agreement rate F-scores as higher as 0.976 using text classification. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Sethurajan M.R.; Natarajan K.
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Lecture Notes in Networks and Systems, Vol-613 LNNS, pp. 329-346.
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Springer Science and Business Media Deutschland GmbH
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2023-01-01
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<a href="https://doi.org/10.1007/978-981-19-9379-4_25" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-9379-4_25</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161107774&doi=10.1007%2F978-981-19-9379-4_25&partnerID=40&md5=c0f00698db30a83c8a829193802b3877" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161107774&doi=10.1007%2f978-981-19-9379-4_25&partnerID=40&md5=c0f00698db30a83c8a829193802b3877</a>
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ISSN: 23673370; ISBN: 978-981199378-7
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Online
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English
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Conference paper
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Sethurajan M.R., CHRIST (Deemed to Be University), Bangalore, India; Natarajan K., CHRIST (Deemed to Be University), Bangalore, India
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Conference Papers
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The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
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Performance Analysis of User Behavior Pattern Mining Using Web Log Database for User Identification
Subject
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Frequent pattern identification; Mutual pre-processing; User access pattern; Web access mining
Description
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User behavior analytics is a progressive research domain. Understanding the users behavior patterns and identifying their behavior patterns will provide solutions to many issues like identity theft and user authentication. So many research works are done in analyzing the frequent access patterns of the users by pre-processing access logs and applying various algorithms to understand the frequent access behavior of the user. From the literature, it founds that the frequent user access pattern identification needs improvement on prediction accuracy and the minimal false positives. To accomplish these, three different approaches were proposed to overcome the existing issues and intended to reduce false positives and improve the frequent pattern mining accuracy based on web access logs. Proposed methods were found to be good while compared with the existing works. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Gokulapriya R.; Ganesh Kumar R.
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Lecture Notes in Networks and Systems, Vol-627 LNNS, pp. 347-356.
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Springer Science and Business Media Deutschland GmbH
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2023-01-01
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<a href="https://doi.org/10.1007/978-981-19-9858-4_29" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-9858-4_29</a>
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ISSN: 23673370; ISBN: 978-981199857-7
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Online
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English
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Conference paper
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Gokulapriya R., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST(Deemed to be University), Karnataka, Bangalore, India; Ganesh Kumar R., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST(Deemed to be University), Karnataka, Bangalore, India
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Conference Papers
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Title
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Creation of Bookshelf Using Autodesk 3ds Max: 3D Modelling and Rendering
Subject
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3D Modelling; Arnold light; Edit Poly; ProBoolean; Twist Modifier
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The step-by-step process of creating a bookshelf design is specified, including the ProBoolean compound primitive, applying edit poly modifier, using detach option, making use of lattice modifier, using bend modifier, using twist modifier. The manner in which materials are added to the model, together with environment lighting and renderer configuration, is defined. Procedures and methods for rendering are also defined. What we aim to achieve through our research is to create a Bookshelf design that uses materials to enhance the models. The shapes used in the model were Box, Teapot, sphere, chamfercyl, Oiltank, ProBoolean compound. The modifiers used were edit poly, bend, twist, lattice. Afterwards we used the Arnold light and material editor to enhance and glorify the model. 2023 IEEE.
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Jain A.; Dangi P.; Samanta D.; Dutta S.; Bhattacharya A.; Joseph N.P.
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11th International Conference on Internet of Everything, Microwave Engineering, Communication and Networks, IEMECON 2023
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Institute of Electrical and Electronics Engineers Inc.
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2023-01-01
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<a href="https://doi.org/10.1109/IEMECON56962.2023.10092371" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/IEMECON56962.2023.10092371</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85154548537&doi=10.1109%2FIEMECON56962.2023.10092371&partnerID=40&md5=3563a1b465800429fe5c19e089334a48" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85154548537&doi=10.1109%2fIEMECON56962.2023.10092371&partnerID=40&md5=3563a1b465800429fe5c19e089334a48</a>
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ISBN: 978-166547512-9
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Online
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English
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Conference paper
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Jain A., Christ University, Dept. of Computer Science, Karnataka, Bangalore, India; Dangi P., Christ University, Dept. of Computer Science, Karnataka, Bangalore, India; Samanta D., Rit Kosovo (A.U.K), Dept. of Computing and Information Technologies, Kosovo, Europe, Prishtina, 10000, Serbia, Rochester Institute of Technology, Rit Global Campus, Kosovo, Europe, Prishtina, 10000, Serbia; Dutta S., Institute of Engineering & Management, Dept. of Computer Science & Applications, Kolkata, India; Bhattacharya A., Institute of Engineering & Management, Dept. of Computer Science & Applications, Kolkata, India; Joseph N.P., Christ University, Dept. of Computer Science, Karnataka, Bangalore, India
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Conference Papers
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An Improved Artificial Intelligence based Service Quality to Increase Customer Satisfaction and Customer Loyalty in Banking Sector
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AISAQUAL Banking; BANQUAL; SERQUAL; Service; Tangibility
Description
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This study clarifies and determines how service quality affects customer loyalty and reliability. The support of quality in the open and private financial sphere and understanding of its connection to customer loyalty and conduct goal Utilizing an upgraded SERVQUAL (BANQUAL) tool with 26 items, the review was conducted among 802 bank customers. The social goal battery was used to estimate the clients' expected conduct. The expert used a seven-point Likert scale to assess the standard and saw service quality (implementation), as well as the social expectations of the clients. The most reliable tool to quantify the conceptualization of the differentiation score is the BANQUAL instrument. It is used to evaluate gaps in service between assumptions and perceptions of service quality. The SERVQUAL instrument is modified to make it suitable in the banking industry. Questions on parking at the bank, the variety of things and programmes available, and the banks' genuine efforts to address customer grievances are added to the instrument (Responsiveness). The writing audit was sufficiently compiled from many sources, reflecting both an Indian and foreign environment. The postulation included several hypotheses then examined using structural equation modelling. To meet the exploration goals, the views were tested using the products AMOS and SISS. The data were analysed using corroborative and explorative element research to confirm the BANQUAL instrument's dependability and legitimacy of the financial business execution and service quality aspects. The resulting CFA model value exhibits excellent psychometric qualities. Professional businesses and clients increasingly use artificial intelligence support specialists (AISA) for management. However, no measure measuring the support quality can fully capture the essential factors affecting AISA service quality. By developing a scale for evaluating the quality of AISA service, this study seeks to solve this deficiency(AISAQUAL). 2023 IEEE.
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Shunmugasundaram M.; Ganesh K.S.; Gnanapragash T.J.; John E.P.; Raj J.P.; Smitha V.
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2nd International Conference on Sustainable Computing and Data Communication Systems, ICSCDS 2023 - Proceedings, pp. 433-439.
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Institute of Electrical and Electronics Engineers Inc.
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2023-01-01
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<a href="https://doi.org/10.1109/ICSCDS56580.2023.10105048" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICSCDS56580.2023.10105048</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159146276&doi=10.1109%2FICSCDS56580.2023.10105048&partnerID=40&md5=30ff5b06fbd8e93c1499d6803d5caab5" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159146276&doi=10.1109%2fICSCDS56580.2023.10105048&partnerID=40&md5=30ff5b06fbd8e93c1499d6803d5caab5</a>
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ISBN: 978-166549199-0
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Online
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English
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Conference paper
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Shunmugasundaram M., Scad College of Eng. & Tech, Tamilnadu, Tirunelveli, India; Ganesh K.S., Lead College of Management, Kerala, Palakkad, India; Gnanapragash T.J., Christ Deemed to Be University, School of Business & Management, Bangalore, India; John E.P., Srm Institute of Science and Technology, Chennai, India; Raj J.P., Christ University, School of Business and Management, India; Smitha V., Lead College of Management, Kerala, Palakkad, India
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Title
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Conference Papers
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Systematic Review on Humanizing Machine Intelligence and Artificial Intelligence
Subject
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Artificial Intelligence; Cognitive Intelligence; Humanizing; Machine Learning; Social Interactions;
Description
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In this era, Machine Learning is transforming human lives in a very different way. The need to give machines the power to make decisions or giving the moral compass is a big dilemma when humanity is more divided than it has ever been. There are two main ways in which law and AI interact. AI may be subject to legal restrictions and be employed in courtroom procedures. The world around us is being significantly and swiftly changed by AI in all of its manifestations. Public law includes important facets such as nondiscrimination law and labor law. In a manner similar to this when artificial intelligence (AI) is applied to tangible technology like robots. In certain cases, artificial intelligence (AI) might be hardly noticeable to customers but evident to those who built and are using it. The behavior research offers suggestions for how to build enduring and beneficial interactions between intelligent robots and people. The human improvement is main obstacles in the development and implementation of artificial intelligence. Best practices in this area are not governed by any one strategy that is generally acknowledged. Machine learning is about to revolutionize society as it is know it. It is crucial to give intelligent computers a moral compass now more than ever before because of how divided mankind is. Although machine learning has limitless potential, inappropriate usage might have detrimental long-term implications. It will think about how, for instance, earlier cultures built trust and improved social interactions via creative answers to many of the ethical issues that machine learning is posing now. 2023 IEEE.
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Abraham J.; Cherian G.J.; Jayapandian N.
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Proceedings of the 2023 2nd International Conference on Electronics and Renewable Systems, ICEARS 2023, pp. 1092-1097.
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Institute of Electrical and Electronics Engineers Inc.
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2023-01-01
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<a href="https://doi.org/10.1109/ICEARS56392.2023.10084967" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICEARS56392.2023.10084967</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85153398264&doi=10.1109%2FICEARS56392.2023.10084967&partnerID=40&md5=a2cf9cb05beb60e58bd6c6e73a01bbb2" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85153398264&doi=10.1109%2fICEARS56392.2023.10084967&partnerID=40&md5=a2cf9cb05beb60e58bd6c6e73a01bbb2</a>
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ISBN: 979-835034664-0
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Online
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English
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Conference paper
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Abraham J., Deemed to Be University, Christ, Department of CSE, Bangalore, India; Cherian G.J., Deemed to Be University, Christ, Department of Mechanical Engineering, Bangalore, India; Jayapandian N., Deemed to Be University, Christ, Department of CSE, Bangalore, India
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Conference Papers
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Dynamic Load Scheduling Using Clustering for Increasing Efficiency of Warehouse Order Fulfillment Done Through Pick and Place Bots
Subject
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Clustering; Dynamic order allocation; Fuzzy C-means clustering; Machine Learning; Master Bot; Order picking; Slave Bot; Swarm robotics
Description
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The domain of warehouse automation has been picking up due to the vast developments in e-commerce owing to growing demand and the need to improve customer satisfaction. The one crucial component that needs to be integrated into large warehouses is automated pick and place of orders from the storage facility using automated vehicles integrated with a forklift (Pick and Place bots). Even with automation being employed, there is a lot of room for improvement with the current technology being used as the loading of the bots is inefficient and not dynamic. This paper discusses a method to dynamically allocate load between the Pick and Place BOTs in a warehouse during order fulfillment. This dynamic allocation is done using clustering,an unsupervised Machine Learning algorithm. This paper discusses using fuzzy C-means clustering to improve the efficiency of warehouse automation. The discussed algorithm improves the efficiency of order fulfillment significantly and is demonstrated in this paper using multiple simulations to see around 35% reduction in order fulfillment time and around 55% increase in efficiency. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Baby C.T.; Baby C.J.
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Lecture Notes in Networks and Systems, Vol-613 LNNS, pp. 315-328.
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Springer Science and Business Media Deutschland GmbH
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2023-01-01
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<a href="https://doi.org/10.1007/978-981-19-9379-4_24" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-9379-4_24</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161111558&doi=10.1007%2F978-981-19-9379-4_24&partnerID=40&md5=51b96dff55a99fcf2532421246140493" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161111558&doi=10.1007%2f978-981-19-9379-4_24&partnerID=40&md5=51b96dff55a99fcf2532421246140493</a>
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ISSN: 23673370; ISBN: 978-981199378-7
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Online
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English
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Conference paper
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Baby C.T., CHRIST (Deemed to be University), Bangalore, 560029, India; Baby C.J., Fupro Innovation Private Limited, Mohali, 160055, India
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Title
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Conference Papers
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Title
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A Novel Steganographic Approach for Image Encryption Using Watermarking
Subject
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AES; DCT; DFT; DWT; PSNR; Steganography; SVD; Watermark
Description
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Steganography is a technique for obfuscating secret information by enclosing it in a regular, non-secret file or communication; the information is subsequently extracted at the intended location. Steganography can be used in addition to encryption to further conceal or safeguard data. Watermarking is one such technique practiced in the area of steganography. Watermarking can be practiced via multiple algorithmic techniques like Discrete Wavelength Transform (DWT), Discrete Cosine Transform (DCT), Singular Value Decomposition (SVD), Discrete Fourier Transform (DFT). In this study, a combination of such approaches along with AES encrypted watermarked images has been implemented. Validation of these techniques has been achieved by evaluating the Peak Signal to Noise Ratio (PSNR). 2023 IEEE.
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Nanjundan P.; Singh D.; Vij A.; George J.P.
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2023 9th International Conference on Advanced Computing and Communication Systems, ICACCS 2023, pp. 1465-1470.
Publisher
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Institute of Electrical and Electronics Engineers Inc.
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2023-01-01
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<a href="https://doi.org/10.1109/ICACCS57279.2023.10112772" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICACCS57279.2023.10112772</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159767750&doi=10.1109%2FICACCS57279.2023.10112772&partnerID=40&md5=01979ddd767e699461a0fc53ae4a8ad4" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159767750&doi=10.1109%2fICACCS57279.2023.10112772&partnerID=40&md5=01979ddd767e699461a0fc53ae4a8ad4</a>
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ISBN: 979-835039737-6
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Online
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English
Type
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Conference paper
Coverage
The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant
Nanjundan P., Christ University, Department of Data Science, Pune, Lavasa, India; Singh D., CIMB AI Labs, Department of Data Science, India; Vij A., Elastic Run, Department of Data Science, India; George J.P., Christ University, Department of Data Science, Pune, Lavasa, India
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Conference Papers
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Adopting Metaverse as a Pedagogy in Problem-Based Learning
Subject
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Metaverse; Pedagogy; Problem-Based Learning; Virtual Learning
Description
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Pedagogical practices vary from time to time based on the requirement of various academic disciplines. Course instructors are constantly searching for inclusive and innovative pedagogies to enhance learning experiences. The introduction of Metaverse can be observed as an opportunity to enable the course instructors to combine virtual reality with augmented reality to enable immersive learning. The scope of immersive learning experience with Metaverse attracted many major universities in the world to try Metaverse as a pedagogy in fields such as management studies, medical education, and architecture. Adopting Metaverse as a pedagogy for problem-based learning enables the course instructors to create an active learning space that tackles the physical barriers of traditional pedagogical practices of case-based learning facilitating collaborative learning. Metaverse, as an established virtual learning platform, is provided by Meta Inc., providing the company a monopoly over the VR-based pedagogy. Entry of other tech firms into similar or collaborative ventures would open up a wide array of virtual reality-based platforms, eliminating the monopoly and subsequent dependency on a singular platform. The findings of the study indicate that, currently, the engagements on Metaverse are limited to tier 1 educational institutions worldwide due to the initial investment requirements. The wide adoption of the Metaverse platform in future depends on the ability of the platform providers to bridge the digital gap and facilitate curricula development. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Baby R.; Siby A.; Joseph J.J.; Zacharias P.
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Lecture Notes in Networks and Systems, Vol-671 LNNS, pp. 287-295.
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Springer Science and Business Media Deutschland GmbH
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2023-01-01
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<a href="https://doi.org/10.1007/978-3-031-31153-6_24" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-31153-6_24</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161155731&doi=10.1007%2F978-3-031-31153-6_24&partnerID=40&md5=7bd3d872e71deb8b86fd5c754618f673" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161155731&doi=10.1007%2f978-3-031-31153-6_24&partnerID=40&md5=7bd3d872e71deb8b86fd5c754618f673</a>
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ISSN: 23673370; ISBN: 978-303131152-9
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Online
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English
Type
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Conference paper
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Baby R., School of Sciences, CHRIST (Deemed to be University), Bangalore, India; Siby A., School of Commerce, Finance and Accountancy, CHRIST (Deemed to be University), Bangalore, India; Joseph J.J., School of Commerce, Finance and Accountancy, CHRIST (Deemed to be University), Bangalore, India; Zacharias P., School of Humanities and Social Sciences, CHRIST (Deemed to be University), Bangalore, India
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Conference Papers
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Implementation of Supervised Pre-Training Methods for Univariate Time Series Forecasting
Subject
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Deep Learning; Machine Learning; Pre-training; Time Series Forecasting
Description
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There has been a recent deep learning revolution in Computer Vision and Natural Language Processing. One of the biggest reasons for this has been the availability of large-scale datasets to pre-train on. One can argue that the Time Series domain has been left out of the aforementioned revolution. The lack of large scale pretrained models could be one of the reasons for this.While there have been prior experiments using pre-trained models for time series forecasting, the scale of the dataset has been relatively small. One of the few time series problems with large scale data available for pre-training is the financial domain. Therefore, this paper takes advantage of this and pretrains a ID CNN using a dataset of 728 US Stock Daily Closing Price Data in total, 2,533,901 rows. Then, we fine-tune and evaluate a dataset of the NIFTY 200 stocks' Closing Prices, in total 166,379 rows. Our results show a 32% improvement in RMSE and a 36% improvement in convergence speed when compared to a baseline non pre trained model. 2023 IEEE.
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Khanna V.; Joshua J.; Pramila R.M.
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2023 2nd International Conference for Innovation in Technology, INOCON 2023
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Institute of Electrical and Electronics Engineers Inc.
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2023-01-01
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<a href="https://doi.org/10.1109/INOCON57975.2023.10101327" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/INOCON57975.2023.10101327</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85158004628&doi=10.1109%2FINOCON57975.2023.10101327&partnerID=40&md5=4afe75f47e918cb0daf9c01c4f0fd4f0" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85158004628&doi=10.1109%2fINOCON57975.2023.10101327&partnerID=40&md5=4afe75f47e918cb0daf9c01c4f0fd4f0</a>
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ISBN: 979-835032092-3
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Online
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English
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Conference paper
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Khanna V., Christ (Deemed to Be University)Lavasa, Department of Data Science, Maharashtra, Pune, India; Joshua J., Christ (Deemed to Be University)Lavasa, Department of Data Science, Maharashtra, Pune, India; Pramila R.M., Christ (Deemed to Be University)Lavasa, Department of Data Science, Maharashtra, Pune, India
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Conference Papers
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The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
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Comparative Analysis of CPI prediction for India using Statistical methods and Neural Networks
Subject
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ARIMA; Consumer Price Index; GRU; Holt-Winters; LSTM; RNN; SARIMA; Stacked LSTM
Description
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Inflation is one of the main issues affecting the world economy right now, necessitating the accurate inflation prediction for the development of tools and policies by the monetary authorities to prevent extreme price volatility. Expectations of inflation influence many financial and economic actions, and this dependence motivates economists to develop techniques for precise inflation forecasting. Nearly everyone in the economy is impacted by inflation, including lending institutions, stock brokers, and corporate financial officials. In many cases, inflation determines whether a firm will accept a particular project or if banks will make a particular loan. These different economic actors can modify their financial portfolios, strategic goals, and upcoming investments if they are able to forecast changes in inflation rates. The multiple interaction economic components that depend on inflation will be better understood by economic agents operating in a business context if inflation forecasting accuracy is improved. There are numerous techniques to forecast inflation ranging from basic statistical methods to complex neural network methods. Therefore, this paper employs LSTM model to train and analyze the Consumer Price Index (CPI) indicators to obtain inflation-related prediction results. The experimental results on historical data show that the statistical model has good performance in predicting India's inflation rate compared to deep learning methods in case of smaller dataset. 2023 IEEE.
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Singh A.; Shukla B.; Jos J.
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2023 2nd International Conference for Innovation in Technology, INOCON 2023
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Institute of Electrical and Electronics Engineers Inc.
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2023-01-01
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<a href="https://doi.org/10.1109/INOCON57975.2023.10101073" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/INOCON57975.2023.10101073</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85158028795&doi=10.1109%2FINOCON57975.2023.10101073&partnerID=40&md5=af2acde42f28062b99ddbb6361718b71" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85158028795&doi=10.1109%2fINOCON57975.2023.10101073&partnerID=40&md5=af2acde42f28062b99ddbb6361718b71</a>
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ISBN: 979-835032092-3
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Online
Language
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English
Type
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Conference paper
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Singh A., Christ (Deemed to Be University), Dept. of Data Science, Pune, India; Shukla B., Christ (Deemed to Be University), Dept. of Data Science, Pune, India; Jos J., Christ (Deemed to Be University), Dept. of Data Science, Pune, India
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Conference Papers
Conference Paper
Faculty Publications- Conference Papers
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The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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Exploring Machine Learning Models to Predict the Diamond Price: A Data Mining Utility Using Weka
Subject
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Diamonds; M5P; Machine Learning Classifiers; REP Trees and Data Mining; Weka
Description
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In contrast to gold and platinum, whose values may be fairly determined, determining a diamond's worth involves a far more complex set of considerations. The appropriate rate is based on many factors, not just one of the stones. Diamonds are graded based on their appearance, carat weight, cut quality, and how well they have presented dimensions like a table's surface, depth, and breadth. In order to accurately forecast diamond prices, this study seeks to develop the most effective approaches possible. Different machine learning classifiers are trained on the diamond dataset to forecast diamond prices based on the features. This article shows how to analyze diamond prices using WEKA's data mining software. Diamond data have been utilized for this study. These methods include M5P, Random Forest, Multilayer perceptron, Decision Stump, REP Trees, and M5Rules. For the purpose of estimating the cost of a diamond, different Machine Learning classifiers are compared and contrasted. Performance measures and analysis showed that Random Forest was the best-performing classifier. Experimental findings show, as shown by the coefficient of correlation that Random Forest is better than other classification methods. 2023 IEEE.
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Amzad Basha M.S.; Martha Sucharitha M.; Devi A.U.; Ashok M.; Oveis P.M.
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2023 9th International Conference on Advanced Computing and Communication Systems, ICACCS 2023, pp. 1870-1877.
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Institute of Electrical and Electronics Engineers Inc.
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2023-01-01
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<a href="https://doi.org/10.1109/ICACCS57279.2023.10112851" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICACCS57279.2023.10112851</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159759512&doi=10.1109%2FICACCS57279.2023.10112851&partnerID=40&md5=6c631cc0867d58c451f9af2b29e04c1e" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159759512&doi=10.1109%2fICACCS57279.2023.10112851&partnerID=40&md5=6c631cc0867d58c451f9af2b29e04c1e</a>
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ISBN: 979-835039737-6
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Online
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English
Type
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Conference paper
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Amzad Basha M.S., Gandhi Institute of Technology and Management (Deemed to be University), GITAM School of Business, Bengaluru, India; Martha Sucharitha M., Deemed to be University, Department of Professional Studies Christ, Bengaluru, India; Devi A.U., SRM Valliammai Engineering College, Department of Management Studies, Chengalpattu, India; Ashok M., Rajalakshmi Institute of Technology, Department of Computer Science and Engineering, Chennai, India; Oveis P.M., Gandhi Institute of Technology and Management (Deemed to be University), GITAM School of Business, Bengaluru, India
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Title
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Conference Papers
Conference Paper
Faculty Publications- Conference Papers
Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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Computational Modelling of Complex Systems for Democratizing Higher Education: A Tutorial on SAR Simulation
Subject
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Colaboratory; Jupyter; Python; Reproducible research; SAR
Description
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Engineering systems like Synthetic Aperture Radar (SAR) are complex systems and require multi-domain knowledge to understand. Teaching and learning SAR processing is intensive in terms of time and resources. It also requires software tools and computational power for preprocessing and image analysis. Extensive literature exists on computational models of SAR in MATLAB and other commercial platforms. Availability of computational models in open-source reproducible platforms like Python kernel in Jupyter notebooks running on Google Colaboratory democratizes such difficult topics and facilitates student learning. The model, discussed here, generates SAR data for a point scatterer using SAR geometry, antenna pattern, and range equation and processes the data in range and azimuth with an aim to generate SAR image. The model demonstrates the generation of synthetic aperture and the echo signal qualities as also how the pulse-to-pulse fluctuating range of a target requires resampling to align the energy with a regular grid. The model allows for changing parameters to alter for resolution, squint, geometry, radar elements such as antenna dimensions, and other factors. A successful learning outcome would be to understand where parameters need to be changed, to affect the model in a specific way. Factors affecting Range Doppler processing are demonstrated. Use of the discussed model nullifies use of commercial software and democratizes SAR topic in higher education. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Govind P.J.; Kumar N.
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Lecture Notes in Networks and Systems, Vol-613 LNNS, pp. 723-734.
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Springer Science and Business Media Deutschland GmbH
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2023-01-01
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<a href="https://doi.org/10.1007/978-981-19-9379-4_52" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-9379-4_52</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161159942&doi=10.1007%2F978-981-19-9379-4_52&partnerID=40&md5=4fbc35a7d0928619019b0d0917cb2770" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161159942&doi=10.1007%2f978-981-19-9379-4_52&partnerID=40&md5=4fbc35a7d0928619019b0d0917cb2770</a>
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ISSN: 23673370; ISBN: 978-981199378-7
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Online
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English
Type
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Conference paper
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Govind P.J., CHRIST (Deemed to be University), Kengeri, Bangalore, India; Kumar N., CHRIST (Deemed to be University), Kengeri, Bangalore, India
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Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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Conference Papers
Conference Paper
Faculty Publications- Conference Papers
Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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Identifying a Range of Important Issues to Improve Crop Production
Subject
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accuracy; agriculture; classifiers; Crop; Machine Learning; Predictive Techniques
Description
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Crop yield production value update has a beneficial practical impact on directing agricultural production and informing farmers of changes in crop market prices. The main objective of the suggested method is to put the crop selection technique into practise so that it may be used to address a variety of issues facing farmers and the agricultural industry. As a result, the yield rate of crop production is maximised, which benefits our Indian economy. land conditions of several kinds. So, using a ranking system, the quality of the crops are determined. This procedure also alerts farmers to the rate of crops of low and high quality. Due to the use of multiple classifiers, using an ensemble of classifiers paves the way for better prediction decisions. The decision-making process for selecting the output of the classifiers also incorporates a rating system. The price of a crop that will produce more is predicted using this method. 2023 IEEE.
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Geetha C.; Thaiyalnayaki S.; Vetriveeran D.; Jeyanthi P.; Selvapriya B.
Source
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2023 9th International Conference on Advanced Computing and Communication Systems, ICACCS 2023, pp. 522-525.
Publisher
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Institute of Electrical and Electronics Engineers Inc.
Date
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2023-01-01
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<a href="https://doi.org/10.1109/ICACCS57279.2023.10112663" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICACCS57279.2023.10112663</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159766498&doi=10.1109%2FICACCS57279.2023.10112663&partnerID=40&md5=ab4cdf2bfb599463fd814f3b67c3b271" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159766498&doi=10.1109%2fICACCS57279.2023.10112663&partnerID=40&md5=ab4cdf2bfb599463fd814f3b67c3b271</a>
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ISBN: 979-835039737-6
Format
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Online
Language
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English
Type
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Conference paper
Coverage
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Geetha C., Sathyabama Institute of Science & Technology, Department of IT, Chennai, India; Thaiyalnayaki S., Bharath Institute of Higher Education and Research, Department of CSE, Chennai, India; Vetriveeran D., Bharath Institute of Higher Education and Research, Department of CSE, Chennai, India, CHRIST (Deemed to Be University), Department of CSE, Kengeri Campus, Bangalore, India; Jeyanthi P., Sathyabama Institute of Science & Technology, Department of IT, Chennai, India; Selvapriya B., Bharath Institute of Higher Education and Research, Department of CSE, Chennai, India
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Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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Conference Papers
Conference Paper
Faculty Publications- Conference Papers
Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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Advancements in Cyber Security and Information Systems in Healthcare from 2004 to 2022: A Bibliometric Analysis
Subject
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Bibliometric Analysis; Citation Analysis; Cyber Security; Healthcare; Information Systems
Description
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The main goals of the multifaceted healthcare system were to prevent, identify, and treat illnesses or conditions that affect human health. As the usage of IT in healthcare increased, the complexities in managing the IT infrastructure also increase, emphasizing the need of robust cyber security systems. The study aims to emphasize the advancements made in cyber security and information systems in healthcare, based on bibliometric analysis. 5,487 document's metadata was obtained from Scopus and data was analyzed using Vos Viewer. Ranking of articles was done with average yearly citations of the publications. Bibliometric analysis was performed based on 'bibliographic coupling of countries', 'co-occurrence of all keywords', 'author-based co-authorship', and 'term co-occurrence based on text data'. It was found that United States had the maximum publications (1337). 'Department of Information Systems and Cyber Security, The University of Texas at San Antonio, United States' is the most influential organization with 159 publications. IEEE Access is the most preferred platform for publication related to cyber security and information systems in healthcare (231 publications). 167 publications have received more than 100 citations. Choo K. K.R. is the most influential author with 185 publications. 2023 IEEE.
Creator
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Nair S.V.R.; Saha S.K.
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Proceedings of 2023 International Conference on Intelligent Systems, Advanced Computing and Communication, ISACC 2023
Publisher
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Institute of Electrical and Electronics Engineers Inc.
Date
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2023-01-01
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<a href="https://doi.org/10.1109/ISACC56298.2023.10084049" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ISACC56298.2023.10084049</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85153394358&doi=10.1109%2FISACC56298.2023.10084049&partnerID=40&md5=43100d1ad6f66197e855d72419a15807" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85153394358&doi=10.1109%2fISACC56298.2023.10084049&partnerID=40&md5=43100d1ad6f66197e855d72419a15807</a>
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ISBN: 979-835039938-7
Format
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Online
Language
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English
Type
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Conference paper
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Nair S.V.R., School of Business and Management, Christ University, Bangalore, India; Saha S.K., School of Business and Management, Christ University, Bangalore, India