32
20
11858
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Dublin Core
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Title
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PHD
PhD
PhD Thesis
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61000210
Title
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Study on Graphs Associated with Groups
Subject
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Mathematics and Statistics
Description
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In this dissertation, the notions of non-inverse graphs, order sum graphs and coset newlinecomponent graphs associated with groups are introduced. These graphs are simple graphs whose vertices are the elements of the group and the adjacency between the vertices depends on certain properties of the group concerned. Vertices belonging to non-inverse graphs are adjacent if they are not inverses of each other in the group. The vertices in order sum graphs are adjacent if the sum of their orders is strictly greater than the order of the group. The vertices belonging to the coset component graphs are adjacent if their left cosets or right cosets of the subgroups of groups are equal. These algebraic graphs are studied in detail in terms of their structural characteristics, parametric properties and spectral properties. Various characterisations of these graphs are obtained in the study concerned. These notions are further extended to the concept of signed graphs and domination. Properties of signed graphs such as balance, clusterability, consistency, sign-compatibility and so on are investigated for these algebraic signed graphs. The relations between various types of domination are obtained for non-inverse graphs, order sum graphs, complement and line graphs of order sum graphs.
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Amreen, Javeria
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Author's Submission
Publisher
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Christ(Deemed to be University)
Date
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2022-01-01
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N K, Sudev.
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Open Access
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PDF
Language
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English
Type
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PhD
Identifier
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<a href="http://hdl.handle.net/10603/453574" target="_blank" rel="noreferrer noopener">http://hdl.handle.net/10603/453574</a>
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https://archives.christuniversity.in/files/original/cb9fd6e0d9c07a7b1f45b9cdf15db63c.pdf
7551f624b6e4ad80f182b40b528276cd
Dublin Core
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Title
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Thesis
PhD
PhD Thesis
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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Study on graphs associated with groups /
Subject
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Mathematics
Creator
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Amreen, Javeria. - 1840087
Source
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CHRIST (Deemed to be University)
Language
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English
Type
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PhD
-
https://archives.christuniversity.in/files/original/609a9b441a3471a02a0d124777c77dee.pdf
4c125c5aee774287d4a749eec61abad1
Dublin Core
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Title
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MPHIL
Mphil
Mphil Thesis
Dublin Core
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Title
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Influence of Parenting in Developing Youth
Identity and Participation
Creator
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AMRITA REKHI
Date
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2019
Source
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Social Work
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Title
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Articles
Article
Faculty Publications -Articles
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Title
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Dynamic route scheduler in vehicular ad hoc network for smart crowd control
Subject
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Optimal routing; Path scheduling; Traffic management; VANET; WSN
Description
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Revenue generated by tourism is positively correlated with the development of any city. In recent years, tourism is getting peak focus among the government, local bodies, and researchers. This has led to increase in initiatives to grow tourism in and across the country. Being one of the most flourishing sectors, tourism in India shows bold signals of emerging as a strong participant in the world of tourism. In addition to safeguarding its culture and deep-rooted traditional values, tourism provides a way to increase employment opportunities as well as increase the foreign exchange within the country. There are many open research problems arising in the domain, which need the attention of researchers. City traffic management is one among the major concern for cities around the world. Scheduling dynamic travel plans for tourists with crowd and traffic awareness has high scope for research. In this paper, a system is proposed which connects the vehicles to a centralized sink for getting the optimal routes. Route scheduling is done based on a prediction model. Different parameters were collected from the environment that includes crowd, traffic, and schedule of other vehicles. The system has modules like static nodes, mobile nodes, host nodes, and sink node for the control and management. Selection of path and protocol is a primary strategy to design any VANET systems. Hence, performance analysis of routing protocols for the proposed system is done as a major step in selection of protocols. Packet delivery ratio, jitter, and throughput are common measures used for the comparison of protocols. 2019, Springer-Verlag London Ltd., part of Springer Nature.
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Amritha A.P.; Sandeep J.
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Personal and Ubiquitous Computing, Vol-24, No. 4, pp. 441-449.
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Springer
Date
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2020-01-01
Identifier
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<a href="https://doi.org/10.1007/s00779-019-01224-1" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s00779-019-01224-1</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067394539&doi=10.1007%2Fs00779-019-01224-1&partnerID=40&md5=47fe7fbfb8fa0eb426e5b0a515d75293" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067394539&doi=10.1007%2fs00779-019-01224-1&partnerID=40&md5=47fe7fbfb8fa0eb426e5b0a515d75293</a>
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Restricted Access
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ISSN: 16174909
Format
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Online
Language
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English
Type
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Article
Coverage
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Amritha A.P., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, Karnataka, India; Sandeep J., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, Karnataka, India
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Dublin Core
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Title
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Articles
Article
Faculty Publications -Articles
Dublin Core
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Title
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Succession planning in India: The path less traversed /
Subject
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Management
Description
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The Management Accountant, Vol.54, Issue 2, pp.30-33, ISSN No: 2581-5504.
Creator
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Amritha Bhaskar and Shibina Mohammed
Source
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<a href="https://icmai-rnj.in/index.php/maj/article/view/142009" target="_blank" title="Succession planning in India: The path less traversed" rel="noreferrer noopener">https://icmai-rnj.in/index.php/maj/article/view/142009</a>
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Institute of Cost Accountants of India
Date
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2019-12-30
Language
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English
Type
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Journal Article
-
Dublin Core
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Title
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Articles
Article
Faculty Publications -Articles
Dublin Core
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Title
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Chemical castration: Justice for victims or justice for the rapist /
Subject
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Law-Alternative Punishment
Description
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American Journal of Criminal Law, Vol.3, pp.1-5, ISSN No: 2581-5504.
Creator
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Amritha Bhaskar and Shibina Mohammed
Source
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<a href="http://www.penacclaims.com/wp-content/uploads/2018/09/Amritha-Bhaskar.pdf" target="_blank" title="Chemical castration: Justice for victims or justice for the rapist" rel="noreferrer noopener">http://www.penacclaims.com/wp-content/uploads/2018/09/Amritha-Bhaskar.pdf</a>
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Pen ACCLAIMS
Date
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2018-12-30
Language
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English
Type
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Journal Article
-
Dublin Core
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Title
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Reviews
Review
Faculty Publications- Reviews
Dublin Core
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Title
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Psychological autopsy: Overview of equivocal deaths, suicides and homicide-suicides
Subject
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Death; Equivocal; Homicide-suicide; Mental illness; Psychological autopsy; Suicide
Description
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Psychological autopsy studies are a method to understand the causes of equivocal deaths. Suicides and homicide-suicide are the result of various events. The understanding of an individual's life before their death, by interviewing the next of kin, provides some insight into the causes. The research articles dealing with psychological autopsy studies through case studies of suicide or homicide-suicide instances, obtained from different search engines, shed light on the mental health, Alcohol use disorder (AUD), and Drug use disorders (DUD) of individuals before death. The primary characteristic of suicides in a population of late twenties to early fifties was romantic relationship conflicts. In contrast, suicides in the teenage years and early twenties were characterized primarily by a lack of familial acceptability and, to a lesser extent, self-acceptance. Simultaneously, there was a high risk of suicidal behavior and commission of acts among the DUD patients, getting treatment without psychiatric diagnosis and therapy. Over time, the psychological autopsy technique has shown to be quite helpful in determining the risk factors for suicidal behavior. The study helps to develop multiple rehabilitation and mental awareness that need to be created among various populations so that the suicide and homicide-suicide rates can be reduced. 2025 Elsevier Ltd and Faculty of Forensic and Legal Medicine
Creator
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Amritha R.; Parvana P.; Riza K.S.; Arjun Rao I.
Source
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Journal of Forensic and Legal Medicine, Vol-110
Publisher
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Churchill Livingstone
Date
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2025-01-01
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<a href="https://doi.org/10.1016/j.jflm.2025.102813" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.jflm.2025.102813</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85216123305&doi=10.1016%2Fj.jflm.2025.102813&partnerID=40&md5=fbda18aa3e3a528f383d2ee9a8d6fba0" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85216123305&doi=10.1016%2fj.jflm.2025.102813&partnerID=40&md5=fbda18aa3e3a528f383d2ee9a8d6fba0</a>
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Restricted Access
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ISSN: 1752928X
Format
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Online
Language
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English
Type
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Review
Coverage
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Amritha R., Department of Life Sciences, Christ University, Karnataka, Bengaluru, India; Parvana P., Department of Life Sciences, Christ University, Karnataka, Bengaluru, India; Riza K.S., Department of Life Sciences, Christ University, Karnataka, Bengaluru, India; Arjun Rao I., Department of Life Sciences, Christ University, Karnataka, Bengaluru, India
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Dublin Core
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Title
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Reviews
Review
Faculty Publications- Reviews
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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Developmental prospects of carrageenan-based wound dressing films: Unveiling techno-functional properties and freeze-drying technology for the development of absorbent films A review
Subject
The topic of the resource
Advanced wound dressings; Biodegradable dressings; Carrageenan biocomposites; Freeze-drying techniques; Wound healing process
Description
An account of the resource
This review explores the intricate wound healing process, emphasizing the critical role of dressing material selection, particularly for chronic wounds with high exudate levels. The aim is to tailor biodegradable dressings for comprehensive healing, focusing on maximizing moisture retention, a vital element for adequate recovery. Researchers are designing advanced wound dressings that enhance techno-functional and bioactive properties, minimizing healing time and ensuring cost-effective care. The study delves into wound dressing materials, highlighting carrageenan biocomposites superior attributes and potential in advancing wound care. Carrageenan's versatility in various biomedical applications demonstrates its potential for tissue repair, bone regeneration, and drug delivery. Ongoing research explores synergistic effects by combining carrageenan with other novel materials, aiming for complete biocompatibility. As innovative solutions emerge, carrageenan-based wound-healing medical devices are poised for global accessibility, addressing challenges associated with the complex wound-healing process. The exceptional physico-mechanical properties of carrageenan make it well-suited for highly exudating wounds, offering a promising avenue to revolutionize wound care through freeze-drying techniques. This thorough approach to evaluating the wound healing effectiveness of carrageenan-based films, particularly emphasizing the development potential of lyophilized films, has the potential to significantly improve the quality of life for patients receiving wound healing treatments. 2024 Elsevier B.V.
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Amruth P.; Akshay P.; Rosemol Jacob M.; Joy J.M.; Mathew S.
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International Journal of Biological Macromolecules, Vol-276
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Elsevier B.V.
Date
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2024-01-01
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<a href="https://doi.org/10.1016/j.ijbiomac.2024.133668" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.ijbiomac.2024.133668</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85198581517&doi=10.1016%2Fj.ijbiomac.2024.133668&partnerID=40&md5=f3497478739ed27b63ed5bdc9731e43d" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85198581517&doi=10.1016%2fj.ijbiomac.2024.133668&partnerID=40&md5=f3497478739ed27b63ed5bdc9731e43d</a>
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ISSN: 1418130; PubMed ID: 38992537; CODEN: IJBMD
Format
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Online
Language
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English
Type
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Review
Coverage
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Amruth P., Biochemistry and Nutrition Division, ICAR-Central Institute of Fisheries Technology, Kerala, Cochin, 682029, India, Faculty of Marine Sciences, Cochin University of Science and Technology, Kerala, Cochin, 682022, India, Department of Life Sciences, Christ University, Hosur Main Road, Bhavani Nagar, Karnataka, Bangalore, 560029, India; Akshay P., Biochemistry and Nutrition Division, ICAR-Central Institute of Fisheries Technology, Kerala, Cochin, 682029, India, Faculty of Marine Sciences, Cochin University of Science and Technology, Kerala, Cochin, 682022, India; Rosemol Jacob M., Biochemistry and Nutrition Division, ICAR-Central Institute of Fisheries Technology, Kerala, Cochin, 682029, India, Faculty of Marine Sciences, Cochin University of Science and Technology, Kerala, Cochin, 682022, India; Joy J.M., Biochemistry and Nutrition Division, ICAR-Central Institute of Fisheries Technology, Kerala, Cochin, 682029, India, Faculty of Marine Sciences, Cochin University of Science and Technology, Kerala, Cochin, 682022, India, St.Teresa's College (Autonomous), Kerala, Ernakulam, 682011, India; Mathew S., Biochemistry and Nutrition Division, ICAR-Central Institute of Fisheries Technology, Kerala, Cochin, 682029, India
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Dublin Core
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Title
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Articles
Article
Faculty Publications -Articles
Dublin Core
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Title
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Altruistic Guardians or Propagators of Regressive Norms?: A Comparative Analysis of the Savior Archetype in Contemporary Kannada Films and Soap Operas
Description
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[No abstract available]
Creator
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Amrutha D.S.; Ashwini M.
Source
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Quarterly Review of Film and Video
Publisher
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Routledge
Date
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2023-01-01
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<a href="https://doi.org/10.1080/10509208.2023.2232713" target="_blank" rel="noreferrer noopener">https://doi.org/10.1080/10509208.2023.2232713</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164916132&doi=10.1080%2F10509208.2023.2232713&partnerID=40&md5=3d6be9628aa597f27e52d813202455d6" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164916132&doi=10.1080%2f10509208.2023.2232713&partnerID=40&md5=3d6be9628aa597f27e52d813202455d6</a>
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ISSN: 10509208
Format
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Online
Language
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English
Type
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Article
Coverage
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Amrutha D.S., Christ (Deemed to be University), India; Ashwini M., Christ (Deemed to be University), India
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Dublin Core
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Title
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Articles
Article
Faculty Publications -Articles
Dublin Core
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Title
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Evaluating the Pertinence of Pose Estimation model for Sign Language Translation
Subject
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deep learning model; landmark detection; machine learning model; pose estimation; SLR models
Description
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Sign Language is the natural language used by a community that is hearing impaired. It is necessary to convert this language to a commonly understandable form as it is used by a comparatively small part of society. The automatic Sign Language interpreters can convert the signs into text or audio by interpreting the hand movements and the corresponding facial expression. These two modalities work in tandem to give complete meaning to each word. In verbal communication, emotions can be conveyed by changing the tone and pitch of the voice, but in sign language, emotions are expressed using nonmanual movements that include body posture and facial muscle movements. Each such subtle moment should be considered as a feature and extracted using different models. This paper proposes three different models that can be used for varying levels of sign language. The first test was carried out using the Convex Hull-based Sign Language Recognition (SLR) finger spelling sign language, next using a Convolution Neural Network-based Sign Language Recognition (CNN-SLR) for fingerspelling sign language, and finally pose-based SLR for word-level sign language. The experiments show that the pose-based SLR model that captures features using landmark or key points has better SLR accuracy than Convex Hull and CNN-based SLR models. 2023 World Scientific Publishing Europe Ltd.
Creator
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Amrutha K.; Prabu P.
Source
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International Journal of Computational Intelligence and Applications, Vol-22, No. 1
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World Scientific
Date
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2023-01-01
Identifier
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<a href="https://doi.org/10.1142/S1469026823410092" target="_blank" rel="noreferrer noopener">https://doi.org/10.1142/S1469026823410092</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85158862167&doi=10.1142%2FS1469026823410092&partnerID=40&md5=eb20e29380b7d256fda5b1eef4a8cd57" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85158862167&doi=10.1142%2fS1469026823410092&partnerID=40&md5=eb20e29380b7d256fda5b1eef4a8cd57</a>
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ISSN: 14690268 | CS; 2023-2024; Vol-1; 00263-00264
Format
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Online
Language
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English
Type
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Article
Coverage
The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant
Amrutha K., Department of Computer Science, CHRIST (Deemed to Be University), Bengaluru, Karnataka, India; Prabu P., Department of Computer Science, CHRIST (Deemed to Be University), Bengaluru, Karnataka, India
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Dublin Core
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Title
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Articles
Article
Faculty Publications -Articles
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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Effortless and beneficial processing of natural languages using transformers
Subject
The topic of the resource
68T05; 68T50; ALBERTA; Attention model; BERT; GPT3; NLP; RoBERTa; Sequential model encoder-decoder
Description
An account of the resource
Natural Language Processing plays a vital role in our day-to-day life. Deep learning models for NLP help make human life easier as computers can think, talk, and interact like humans. Applications of the NLP models can be seen in many domains, especially in machine translation and psychology. This paper briefly reviews the different transformer models and the advantages of using an Encoder-Decoder language translator model. The article focuses on the need for sequence-to-sequence language-translation models like BERT, RoBERTa, and XLNet, along with their components. 2022 Taru Publications.
Creator
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Amrutha K.; Prabu P.
Source
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Journal of Discrete Mathematical Sciences and Cryptography, Vol-25, No. 7, pp. 1987-2005.
Publisher
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Taylor and Francis Ltd.
Date
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2022-01-01
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<a href="https://doi.org/10.1080/09720529.2022.2133239" target="_blank" rel="noreferrer noopener">https://doi.org/10.1080/09720529.2022.2133239</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143499677&doi=10.1080%2F09720529.2022.2133239&partnerID=40&md5=57c51a912f413b0bf7ccc4e1774ee473" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143499677&doi=10.1080%2f09720529.2022.2133239&partnerID=40&md5=57c51a912f413b0bf7ccc4e1774ee473</a>
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ISSN: 9720529
Format
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Online
Language
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English
Type
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Article
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Amrutha K., Department of Computer Science, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Prabu P., Department of Computer Science, CHRIST (Deemed to be University), Karnataka, Bengaluru, India
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Conference Papers
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Title
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ML based sign language recognition system
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Automated SLR; Classification models; Feature extraction; Preprocessing; Segmentation
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This paper reviews different steps in an automated sign language recognition (SLR) system. Developing a system that can read and interpret a sign must be trained using a large dataset and the best algorithm. As a basic SLR system, an isolated recognition model is developed. The model is based on vision-based isolated hand gesture detection and recognition. Assessment of ML-based SLR model was conducted with the help of 4 candidates under a controlled environment. The model made use of a convex hull for feature extraction and KNN for classification. The model yielded 65% accuracy. 2021 IEEE.
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Amrutha K.; Prabu P.
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2021 International Conference on Innovative Trends in Information Technology, ICITIIT 2021
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Institute of Electrical and Electronics Engineers Inc.
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2021-01-01
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<a href="https://doi.org/10.1109/ICITIIT51526.2021.9399594" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICITIIT51526.2021.9399594</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104831889&doi=10.1109%2FICITIIT51526.2021.9399594&partnerID=40&md5=46dea1c1a1f0e4fb41987b4917a0c61b" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104831889&doi=10.1109%2fICITIIT51526.2021.9399594&partnerID=40&md5=46dea1c1a1f0e4fb41987b4917a0c61b</a>
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ISBN: 978-166540467-9
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Online
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English
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Conference paper
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Amrutha K., CHRIST(Deemed to Be University), Dept. of Computer Science, Bangalore, India; Prabu P., CHRIST(Deemed to Be University), Dept. of Computer Science, Bangalore, India
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Conference Papers
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A Comparative Study on Indian Sign Language Representation
Subject
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continuous sign language; Indian sign language; isolated sign language; sign language recognition system
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Communication among people can happen with the help of verbal or nonverbal language. Nonverbal communication is shared only among the hearing and speech impaired and is not common among others. Non-verbal communication is also different for different countries around the world. A solution to remove the gap between verbal and non-verbal communicators is to create an automated language translation model that can effortlessly convert sign language to text or audio. This area has been under research for a long time, but an economical and robust system that can efficiently convert signs into speech still does not exist. This paper focuses on different approaches that were put forward to turn Indian sign language into audio signals. The Sign Language Recognition (SLR) system is classified as isolated and continuous sign language models based on its input. 2021 IEEE.
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Amrutha K.; Prabu P.
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2021 International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation, ICAECA 2021
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Institute of Electrical and Electronics Engineers Inc.
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2021-01-01
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<a href="https://doi.org/10.1109/ICAECA52838.2021.9675678" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICAECA52838.2021.9675678</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125007329&doi=10.1109%2FICAECA52838.2021.9675678&partnerID=40&md5=dea4cd7784fceb333711694dc44108d2" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125007329&doi=10.1109%2fICAECA52838.2021.9675678&partnerID=40&md5=dea4cd7784fceb333711694dc44108d2</a>
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ISBN: 978-166542829-3
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Online
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English
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Conference paper
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Amrutha K., CHRIST(Deemed to Be University), Dept. of Computer Science, Bangalore, India; Prabu P., CHRIST(Deemed to Be University), Dept. of Computer Science, Bangalore, India
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Human Body Pose Estimation and Applications
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2D pose estimation; 3D pose estimation; Body modelling; Holistic Pipeline estimation; MediaPipe; Sign language recognition
Description
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Human Pose Estimation is one of the challenging yet broadly researched areas. Pose estimation is required in applications that include human activity detection, fall detection, motion capture in AR/VR, etc. Nevertheless, images and videos are required for every application that captures images using a standard RGB camera, without any external devices. This paper presents a real-time approach for sign language detection and recognition in videos using the Holistic pose estimation method of MediaPipe. This Holistic framework detects the movements of multiple modalities-facial expression, hand gesture and body pose, which is the best for the sign language recognition model. The experiment conducted includes five different signers, signing ten distinct words in a natural background. Two signs, 'blank' and 'sad, ' were best recognized by the model. 2021 IEEE.
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Amrutha K.; Prabu P.; Paulose J.
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3rd IEEE International Virtual Conference on Innovations in Power and Advanced Computing Technologies, i-PACT 2021
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Institute of Electrical and Electronics Engineers Inc.
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2021-01-01
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<a href="https://doi.org/10.1109/i-PACT52855.2021.9696513" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/i-PACT52855.2021.9696513</a>
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ISBN: 978-166542691-6
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Online
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English
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Conference paper
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Amrutha K., CHRIST (Deemed to Be University), Dept. of Computer Science, Bengaluru, India; Prabu P., CHRIST (Deemed to Be University), Dept. of Computer Science, Bengaluru, India; Paulose J., CHRIST (Deemed to Be University), Dept. of Computer Science, Bengaluru, India
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61000287
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A Frame Work For Continous Indian Sign Language Recognition Using Computer Vision
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Computer Science
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Sign language is a non-vocal, visually oriented natural language used by the hearing newlineimpaired and the hard-for-hearing part of society. It combines multiple modalities newlinelike hand movements, facial expressions and body poses. Static gestures involve basic finger movements such as numbers and alphabets, dynamic signs include words, and a sign sentence consists of grammatically connected and meaningful dynamic words. Sign Language Translation (SLT) models have been an actively evolving research topic under computer vision. One of the most challenging aspects in earlier iterations of SLTs was accurately capturing the intricate and constantly changing hand movements and facial expressions characteristic of sign language. newlineHowever, the advent of deep learning models has facilitated significant advancements in the field, particularly in the realm of continuous sign language translation. newlineThe research endeavours to develop a lightweight deep-learning framework newlinespecifically tailored for the translation of Indian Sign Language (ISL) into text and newlineaudio. The proposed framework introduces two collaborative deep-learning components that extract and classify features synergistically. The ISL video sequence serves as the input, which undergoes feature extraction utilizing the Inception V3 architecture, enabling the extraction of features from each frame. Classification models tend to be bulky and intricate, consuming substantial memory space and requiring extended training periods. This challenge has been addressed by introducing a lightweight LSTM model, which effectively utilizes the feature map generated by the Inception model for accurate classification. It is important to note that each sign possesses unique characteristics yet exhibits similar feature maps. The performance of the framework is assessed based on the speed and accuracy achieved in converting the input video into text and audio formats.
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Amrutha, K
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Author's Submission
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Christ(Deemed to be University)
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2023-01-01
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Prabhu, P
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Open Access
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PDF
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English
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PhD
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<a href="http://hdl.handle.net/10603/540379" target="_blank" rel="noreferrer noopener">http://hdl.handle.net/10603/540379</a>
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61000064
Title
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A Mixed methods study of psyhosocial factors in career decision making in adolescents
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Psychology
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Career choice is an important developmental task in adolescence and is influenced by many factors. Using a mixed methods research design, this study aimed to understand career decision making and factors influencing the same in adolescents. In the quantitative phase the relationship between career maturity and perceived parenting style, personality traits, metacognition, socio- economic status, gender, college type, stream of study and decision status was studied in students studying in II Year Pre- University in Bangalore, India. Career decisions, personal and family factors in career decision making were explored in the qualitative phase. Informed consent was obtained from the participants and parents of the participants of the study. newlineQuantitative data was collected from 548 students studying in Arts, Science and Commerce stream in second year Pre- University in Bangalore. Students from eight private and seven government colleges were recruited for the study. Quantitative data was collected using a socio- demographic data sheet, Career Maturity Inventory, Parental Authority Questionnaire, Neo Five Factor Inventory and Metacognitive Awareness Inventory. The scales were translated to Kannada and back translated. In the qualitative phase, data was collected through a semi- structured interview schedule designed for this study. 30 students who were a part of the quantitative phase took part in this phase. The interviews were audio-recorded and transcribed for analysis. Statistical analysis was done to analyze quantitative data. Descriptive statistics, correlation, regression analysis, t tests and one-way ANOVA was done. Qualitative data was analyzed by template analysis and themes were derived from the data. The results revealed associations between personality traits neuroticism, openness and conscientiousness and specific aspects of career maturity attitude and competence.
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Amtoor Pavana Rao
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Author's Submission
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Christ(Deemed to be University)
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2017-01-01
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Jayasankara Reddy, K
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Open Access
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PDF
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English
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PhD
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<a href="http://hdl.handle.net/10603/149833" target="_blank" rel="noreferrer noopener">http://hdl.handle.net/10603/149833</a>
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Conference Papers
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Enhancing red wine quality prediction through Machine Learning approaches with Hyperparameters optimization technique
Subject
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Grid search; Hyperparameter tuning; Machine learning classifiers; Red wine; Regressors
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In light of the intricacy of the winemaking process and the wide variety of elements that could affect the taste and quality of the finished product, predicting red wine quality is difficult. ML methods have been widely used in forecasting red wine quality from its chemical characteristics in recent years. This Paper evaluated the comparison of classification and regression methods to predict the quality of red wine and performed the initial data analysis and exploratory data analysis on the data. This study implemented different Classifiers and Regressors that were trained and tested. Contrasted and Comparative analysis of the accuracies of eight models with hyperparameter tuning optimization, including Logistic Regression, Gradient Boosting, Extra Tree, Ada Boost, Random Forest, Support Vector Classifier, and Decision Tree, Knn and measured the classification report with F1, Accuracy, and Recall Scores. For Imbalance data, SMOTE Classifier was used. This study performed the Cross-validation technique, such as Grid search and with the best hyperparameters tuning. The study's findings demonstrated that the Gradient Boosting technique accurately predicted red wine quality. This research shows the promising results of Gradient Boosting for predicting red wine quality and adds important context to the usage of machine learning classifiers for this challenge. 2023 IEEE.
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Amzad Basha M.S.; Desai K.; Christina S.; Sucharitha M.M.; Maheshwari A.
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2023 2nd International Conference on Electrical, Electronics, Information and Communication Technologies, ICEEICT 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/ICEEICT56924.2023.10157719" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICEEICT56924.2023.10157719</a>
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ISBN: 979-835039763-5
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Online
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English
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Conference paper
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Amzad Basha M.S., GITAM School of Business, Gandhi Institute of Technology and Management (Deemed to Be University), Bengaluru, India; Desai K., Christ (Deemed to Be University), Department of Professional Studies, Bengaluru, India; Christina S., Christ (Deemed to Be University), Department of Professional Studies, Bengaluru, India; Sucharitha M.M., Christ (Deemed to Be University), Department of Professional Studies, Bengaluru, India; Maheshwari A., School of Commerce, Finance, Christ (Deemed to Be University), Department of Commerce, Ghaziabad, India
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Conference Papers
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Unraveling Campus Placement Success Integrating Exploratory Insights with Predictive Machine Learning Models
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EDA; Machine Learning; Performance analysis; Placement Prediction; Students
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The dynamics of campus placements have garnered considerable attention in recent years, with educational institutions, students, and employers all keenly invested in understanding the factors that drive successful recruitment. This surge in interest stems from the potential implications for academic curricula, student preparation, and hiring strategies. In this study, we aimed to unravel the myriad factors that influence a student's placement success, drawing from a comprehensive dataset detailing a range of academic and demographic attributes. Our methodology combined thorough exploratory data analysis with advanced predictive modeling. The exploratory phase unveiled notable patterns, particularly highlighting the roles of gender, academic performance analysis, Degree and MBA specialization in placement outcomes. In the predictive modeling phase, the spotlight was on state-of-the-art machine learning models, with a particular emphasis on their capacity to forecast placement success. Notably, algorithms like Logistic Regression and Support Vector Machines not only confirmed the insights from our exploratory analysis but also showcased remarkable predictive prowess, with accuracy scores nearing perfection. These findings not only demonstrate the capabilities of machine learning in the academic and recruitment spheres but also emphasize the enduring importance of core academic achievements in influencing placement outcomes. As a prospective direction, future research might benefit from examining how placement trends evolve over time and integrating qualitative insights to provide a holistic view of the campus recruitment process. 2023 IEEE.
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Amzad Basha M.S.; Kumar Raju R.P.; Oveis P.M.; Sarim M.
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7th IEEE International Conference on Computational Systems and Information Technology for Sustainable Solutions, CSITSS 2023 - Proceedings
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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/CSITSS60515.2023.10334118" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/CSITSS60515.2023.10334118</a>
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ISBN: 979-835034314-4
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Online
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English
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Conference paper
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Amzad Basha M.S., Gitam School of Business, Gandhi Institute of Technology and Management (Deemed to Be University), Bengaluru, India; Kumar Raju R.P., Christ (Deemed to Be University), Department of Professional Studies, Bengaluru, India; Oveis P.M., Gitam School of Business, Gandhi Institute of Technology and Management (Deemed to Be University), Bengaluru, India; Sarim M., Gitam School of Business, Gandhi Institute of Technology and Management (Deemed to Be University), Bengaluru, India
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Conference Papers
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Exploring Machine Learning Models to Predict the Diamond Price: A Data Mining Utility Using Weka
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Diamonds; M5P; Machine Learning Classifiers; REP Trees and Data Mining; Weka
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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>
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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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Insider attack detection using deep belief neural network in cloud computing
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Cloud computing; Deep belief neural network; Insider attack; Network security; Privacy; Security; User interaction behavior
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Cloud computing is a high network infrastructure where users, owners, third users, authorized users, and customers can access and store their information quickly. The use of cloud computing has realized the rapid increase of information in every field and the need for a centralized location for processing efficiently. This cloud is nowadays highly affected by internal threats of the user. Sensitive applications such as banking, hospital, and business are more likely affected by real user threats. An intruder is presented as a user and set as a member of the network. After becoming an insider in the network, they will try to attack or steal sensitive data during information sharing or conversation. The major issue in today's technological development is identifying the insider threat in the cloud network. When data are lost, compromising cloud users is difficult. Privacy and security are not ensured, and then, the usage of the cloud is not trusted. Several solutions are available for the external security of the cloud network. However, insider or internal threats need to be addressed. In this research work, we focus on a solution for identifying an insider attack using the artificial intelligence technique. An insider attack is possible by using nodes of weak users systems. They will log in using a weak user id, connect to a network, and pretend to be a trusted node. Then, they can easily attack and hack information as an insider, and identifying them is very difficult. These types of attacks need intelligent solutions. A machine learning approach is widely used for security issues. To date, the existing lags can classify the attackers accurately. This information hijacking process is very absurd, which motivates young researchers to provide a solution for internal threats. In our proposed work, we track the attackers using a user interaction behavior pattern and deep learning technique. The usage of mouse movements and clicks and keystrokes of the real user is stored in a database. The deep belief neural network is designed using a restricted Boltzmann machine (RBM) so that the layer of RBM communicates with the previous and subsequent layers. The result is evaluated using a Cooja simulator based on the cloud environment. The accuracy and F-measure are highly improved compared with when using the existing long short-term memory and support vector machine. 2022 CRL Publishing. All rights reserved.
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Anakath A.S.; Kannadasan R.; Joseph N.P.; Boominathan P.; Sreekanth G.R.
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Computer Systems Science and Engineering, Vol-41, No. 2, pp. 479-492.
Publisher
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Tech Science Press
Date
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2022-01-01
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<a href="https://doi.org/10.32604/csse.2022.019940" target="_blank" rel="noreferrer noopener">https://doi.org/10.32604/csse.2022.019940</a>
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All Open Access; Hybrid Gold Open Access
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ISSN: 2676192; CODEN: CSSEE
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Online
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English
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Article
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Anakath A.S., School of Computing, E.G.S. Pillay Engineering College, Tamilnadu, Nagapattinam, 611002, India; Kannadasan R., Department of Software Systems, School of Computer Science and Engineering (SCOPE), Vellore Institute of Technology University, Tamilnadu, Vellore, 632014, India; Joseph N.P., Department of Computer Science, CHRIST(Deemed to be University), Bengaluru, 560029, India; Boominathan P., Department of Information Security, School of Computer Science and Engineering (SCOPE), Vellore Institute of Technology University, Tamilnadu, Vellore, 632014, India; Sreekanth G.R., Department of Computer Science and Engineering, Kongu Engineering College, Tamilnadu, Erode, 638060, India