233 20 16481 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 A name given to the resource Faculty Publications 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/. Creator An entity primarily responsible for making the resource Helen Josephine, V.L.; Rajagopal, Manikandan; Kavitha, S.; Rajendran, Stuthi Title A name given to the resource Enhancing Sign Language Recognition Through LSTM Model Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived 4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025 - Proceedings;pp.986-989 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICSADL65848.2025.10933396" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICSADL65848.2025.10933396</a> <a href="https://www.scopus.com/pages/publications/105002463659?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105002463659?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Helen Josephine V.L., School of Business and Management, Christ University, Karnataka, Bangalore, India; Rajagopal M., School of Business and Management, Christ University, Karnataka, Bangalore, India; Kavitha S., Dayanand Sagar University, Bengaluru, India; Rajendran S., School of Business and Management, Christ University, Karnataka, Bangalore, India Description An account of the resource Sign language recognition is a remarkable task in this project completed through two state-of-the-art methods, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU). This way, the system is able to quickly process each frame of the webcam with real-time information regarding face, body and posture in order to extract critical values. this research seeks to provide the necessary resources and opportunities for deaf people to be able to communicate effectively, obtain an education and enjoy their lives as much as other human beings This makes it a very important tool for education where the system can convert sign motions into text on-the-fly. The data was collected through a live camera, and key points from face, body, and pose were detected for training the model. Kindergarten used the four categories of vegetables, fruits, colors and animals. There were 40 video sequences of 40 frames with a sign in each. the model tries to fit too much to noisy points of data. However comprehensive the training, after 19 epochs the validation accuracy is an impressive 93%. The oscillations in the truth values of models are indicative of some uncertainty in learning where the accuracy is still to be settled. The graph in general shows that the LSTM based sign language movement classifier has a good capacity to learn and identify sign language movements with high precision. 2025 IEEE. Subject The topic of the resource Education for hearing impaired; GRU; Image/video recognition; LSTM; Machine Learning; Sign Language Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833152392-3; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library 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 A name given to the resource 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 A name given to the resource Protection of Artificial Intelligence Autonomously Generated Works under the Copyright Act, 1957-An Analytical Study Subject The topic of the resource Artificial Intelligence; Autonomous Works; Copyright; Human intervention; Joint authorship Description An account of the resource Artificial Intelligence (AI) is not new anymore; it has become a new normal. In the present 3A era (Advanced, automated and autonomous), the Next Rembrandt paintings, Shimons lyrics and songs and Bot Dylans Irish folk songs are the works generated by the AI without any considerable human contribution. In the US, the Copyright Act, 1976 does not protect the works generated independently by the AI without human intervention and thus dropping such works in the public domain immediately after their creation. However, in the UK, the Copyright, Patents and the Designs Act, 1988 under Section 9 (3) attributes copyright to the person by whom the arrangements necessary for the creation of the work are undertaken in case of AI generated works. India has taken a giant leap by considering AI as the joint author along with the human responsible for the creation of work. However, there is not much comprehensive literature available that focuses on the impact of AI being considered as a joint author. This paper aims to create a concrete foundation by emphasising such impact under the Copyright Act, 1957. Furthermore, the paper considers the stance of the US, UK and Australia in protecting AI generated works to suggest measures to the current copyright regime in India. 2023, National Institute of Science Communication and Policy Research. All rights reserved. Creator An entity primarily responsible for making the resource Hema K. Source A related resource from which the described resource is derived Journal of Intellectual Property Rights, Vol-28, No. 3, pp. 193-199. Publisher An entity responsible for making the resource available National Institute of Science Communication and Policy Research Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.56042/jipr.v28i3.708" target="_blank" rel="noreferrer noopener">https://doi.org/10.56042/jipr.v28i3.708</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161890379&doi=10.56042%2Fjipr.v28i3.708&partnerID=40&md5=06a1c2cf612c9d24d97d542204af46ca" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161890379&doi=10.56042%2fjipr.v28i3.708&partnerID=40&md5=06a1c2cf612c9d24d97d542204af46ca</a> Rights Information about rights held in and over the resource All Open Access; Hybrid Gold Open Access Relation A related resource ISSN: 9717544 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource 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 Hema K., School of Law, CHRIST (Deemed to be University), National Law University, Rajasthan, Jodhpur, 342 304, India 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 A name given to the resource 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 A name given to the resource Social Identity of Kodavas Understanding Evolution and Transitions Subject The topic of the resource grounded theory; kodava; social identity Description An account of the resource The Kodavas of Kodagu district in Karnataka have a distinct social structure and follow a set of unique social codes and values peculiar to the community. Various influences have resulted in shifting social identities, which maybe a potential indicator of an identity crisis within the group. The present study follows a Constructivist Grounded Theory approach to inquiry, to arrive at an analytical schema of the process of social identity formation of the Kodavas. The analysis of data collected from forty-one middle and older adults, highlight the core traditional attributes of the Kodava identity, factors contributing to identity transition and its reflection in contemporary times. 2023 Tata Institute of Social Sciences. All rights reserved. Creator An entity primarily responsible for making the resource Hema M.A.; Singh J.K. Source A related resource from which the described resource is derived Indian Journal of Social Work, Vol-84, No. 2, pp. 203-222. Publisher An entity responsible for making the resource available Tata Institute of Social Sciences Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.32444/IJSW.2023.84.2.203-222" target="_blank" rel="noreferrer noopener">https://doi.org/10.32444/IJSW.2023.84.2.203-222</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175097471&doi=10.32444%2FIJSW.2023.84.2.203-222&partnerID=40&md5=55fa90454c9dc2e76f7e1c1eb671d134" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175097471&doi=10.32444%2fIJSW.2023.84.2.203-222&partnerID=40&md5=55fa90454c9dc2e76f7e1c1eb671d134</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 195634 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource 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 Hema M.A., Department of Psychology, School of Humanities and Social Sciences, CHRIST, Deemed-to-be University, NCR, Delhi, India; Singh J.K., Defence Institute of Psychological Research (DIPR), Defence Research and Development Organisation (DRDO), New Delhi, India 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 A name given to the resource Faculty Publications 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/. Creator An entity primarily responsible for making the resource Hema, K. Title A name given to the resource AI and data-driven digital platforms: the case for establishing global minimum standards in competition law Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived International Review of Law, Computers and Technology; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1080/13600869.2025.2602114" target="_blank" rel="noreferrer noopener">https://doi.org/10.1080/13600869.2025.2602114</a> <a href="https://www.scopus.com/pages/publications/105024818808?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105024818808?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Hema K., School of Law, Christ University, Bangalore, India Description An account of the resource AI and data-driven platforms have the potential to enable foreclosures, exclusionary and exploitative practices, resulting in the distortion of competition in the digital markets. The inherent conundrum of boundary-less AI and data-driven systems and territorial application of competition laws has created problems in cross-border digital markets. Countries have adopted divergent approaches in enforcing competition law, with some following the per se rule to categorically prohibit MFN clauses and others employing the rule of reason, assessing the anti-competitiveness of such agreements based on effects. Moreover, the countries have adopted either ex-post or ex-ante or a combination of both to regulate digital markets, deepening the divergence in competition, allowing AI and data-driven practices to enable regulatory arbitrage. To establish divergences in regulating the digital markets, the research adopts a comparative approach, analysing the competition law statutes and case laws across jurisdictions. Although competition laws must duly account for domestic market conditions, bringing harmonisation in their enforcement across jurisdictions remains imperative. Adopting a global minimum standard for competition law is a necessary step towards bringing consistency in the application of the competition laws across countries and equipping the competition law enforcement body to confront AI and data-driven market distortions in cross-border digital platforms. 2025 Informa UK Limited, trading as Taylor & Francis Group. Subject The topic of the resource data-driven systems; global minimum standard; Self-preferencing Publisher An entity responsible for making the resource available Routledge Relation A related resource ISSN: 13600869; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online 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 A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter 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/. Creator An entity primarily responsible for making the resource Hema, K.; Pavithra, R. Title A name given to the resource Autonomous AI in Automotive Safety: Rethinking Tortious Liability Paradigms Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Agentic AI for Autonomous Vehicles: Safety, Reliability, Law, and Ethics;pp.321-338 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3373-7355-3.ch011" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3373-7355-3.ch011</a> <a href="https://www.scopus.com/pages/publications/105038487693?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105038487693?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Hema K., Christ University, India; Pavithra R., Gujarat National Law University, India Description An account of the resource This paper seeks to examine the application of tort law to the Automated Vehicles. Section I deals with a brief overview of the impact of AVs and tort law and the application of tortious principles. Section II discusses the concept of fault and the multiple parties to whom fault can be attributed. Furthermore, it discusses who should be blamed and to what extent. Section III discusses the tortious principles such as product liability, vicarious liability and apportionment of liability and its application to the AVs. Section IV proposes directions for future research, conclusion and recommendations for the legal challenges posed by the AVs. 2026 by IGI Global Scientific Publishing. All rights reserved. Publisher An entity responsible for making the resource available IGI Global Relation A related resource ISBN: 979-833737357-7; 979-833737355-3; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library 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 A name given to the resource 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 A name given to the resource Yield management in hotel industry: An exploratory study on selected northern states of India: A time series analysis Subject The topic of the resource Management Description An account of the resource Asian Journal of Research in Business Economics and Management, Vol. 7, Issue 3, pp. 37-63, ISSN No. 2249-7307. Creator An entity primarily responsible for making the resource Hemalatha Publisher An entity responsible for making the resource available Asian Journal of Research in Business Economics and Management Language A language of the resource English 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 A name given to the resource Book Chapter Book Chapter Faculty Publications- Book Chapter 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 A name given to the resource Empowering women through livelihood interventions: Case studies from an impoverished community Subject The topic of the resource Dimensions of empowerment; Livelihood intervention; Women empowerment Description An account of the resource This chapter looks at the influence of a livelihood project in empowering women belonging to an impoverished community from one of the most backward regions of the state of Karnataka in Southern India. Jamkhandi taluq of Bagalkote district is one of the poorer taluqs in the state, with a sex ratio of 938 and a female literacy rate of 50.75%. The Centre for Social Action began working in the area around a decade ago. The livelihood project was an offshoot of a project on Population displacement that was undertaken in the region. CSA adopted the Self-Help Approach (SHA) to meet the needs of this community. This gave the necessary impetus for the creation of a livelihood project for disadvantaged women. The central theme of the chapter is to study the extent of empowerment that is evident among the project's women beneficiaries. This chapter presents the evidence of empowerment using the qualitative case study methodology using ten cases. The theoretical framework provided by the 'Three Dimensional Model of Women Empowerment' is used to present the analysis. Document review and in-depth interviews are the prominent data sets used to present the study's major findings. The hybrid approach to coding and thematic analysis is used to integrate the insights from the theory used as well as observations from the study. Both within-case analysis and cross-case analysis are used for analysis. The personal, relational, and societal dimensions of empowerment are presented through themes emerging from the data. The implication of the chapter is the reiteration of the efficacy of the model in empowering women. This model can be replicated in other project areas, and livelihood strategies can be adopted extensively. 2024 Nova Science Publishers, Inc. Creator An entity primarily responsible for making the resource Hemalatha K. Source A related resource from which the described resource is derived Models for Social Responsibility Action by Higher Education Institutions, pp. 49-70. Publisher An entity responsible for making the resource available Nova Science Publishers, Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="" target="_blank" rel="noreferrer noopener"></a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85183083167&partnerID=40&md5=baf3d48d9e08d37b97a61a7dac2ac0d5" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85183083167&partnerID=40&md5=baf3d48d9e08d37b97a61a7dac2ac0d5</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-889113251-1; 979-889113097-5 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Hemalatha K., Department of Sociology and Social Work, Christ University, Bengaluru, India 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 A name given to the resource Faculty Publications 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/. Creator An entity primarily responsible for making the resource Hemalatha Yadav, J.; Arora, Kapil; Salgotra, Priyanka; Dawod, NajimAubed; Patil, Amit Kumar; Kataria, Abhinav Title A name given to the resource Cognitive IoT-Integrated Real-Time Transaction Monitoring System for Financial Security Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Proceedings - 2025 International Conference on Recent Innovation in Science Engineering and Technology, ICRISET 2025; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICRISET64803.2025.11251638" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICRISET64803.2025.11251638</a> <a href="https://www.scopus.com/pages/publications/105031406686?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105031406686?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Hemalatha Yadav J., Alliance University, Bangalore, India; Arora K., Alliance University, Alliance School of Business, Department of Management, Bangalore, India; Salgotra P., Maharishi Markandeshwar (Deemed to be) University, Maharishi Markandeshwar Institute of Management, (Ambala) Haryana, Mullana, India; Dawod N., Al-Nisour University College, Department of Medical Laboratories, Nisour Seq. Karkh, Baghdad, Iraq; Patil A.K., Mit Art, Design and Technology University, Department of Ece, Pune, India; Kataria A., Christ Deemed to be University, Delhi NCR Campus, India Description An account of the resource As financial transactions become more complex in terms of the digitally connected environment, smart and real-time monitoring systems are required to fight off fraud and guarantee safety. The paper proposes a Cognitive IoT based Real-Time Transaction Monitoring System which is a proposed system to the financial sector. The proposed model resorts to the Z-Score normalization as a means of pre-processing the data and Recursive Feature Elimination with Random Forest as a method of selecting the most relevant features affecting the behavior of transactions. As the main type of classifier, a hybrid LSTM-Autoencoder model is used that makes it possible to reliably detect anomalies both using sequential and reconstruction-based learning. Developed on top of TensorFlow and its federated learning extensions, the system maintains the privacy of its user data by supporting decentralized training of edge devices. Experimental tests indicate higher results over the detection accuracy, which reduces false positives, and real-time reactivity. It is a scalable, safe, flexible system that can be used to monitor financial transactions efficiently, using the combined potential of the cognitive computer, the IoT environment, and powerful machine learning to respond to the dynamic nature of financial security issues. 2025 IEEE. Subject The topic of the resource Anomaly Detection; Cognitive IoT; Feature Selection; Federated Learning; Financial Security; LSTM-Autoencoder; Real-Time Monitoring Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833155833-8; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library 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 A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter 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/. Creator An entity primarily responsible for making the resource Hemalatha, S.; Ruben Anto, M.; Rajesh, Deepa; Maheswari, P.; Velmurugan, Palanivel Rathinasabapathi Title A name given to the resource Green Marketing and AI-Driven Branded Entertainment: Ethics and Opportunities Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived AI Impacts on Branded Entertainment and Advertising;pp.279-302 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3693-3799-8.ch014" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3693-3799-8.ch014</a> <a href="https://www.scopus.com/pages/publications/105007270203?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105007270203?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Hemalatha S., Department of Commerce, Hindustan Institute of Technology and Science, India; Ruben Anto M., School of Business and Management, Christ University, India; Rajesh D., Academy of Maritime Education and Training, India; Maheswari P., Faculty of Management, SRM Institute of Science and Technology, India; Velmurugan P.R., Berlin School of Business and Innovation, Germany Description An account of the resource This chapter explores the fusion of green marketing and AI-driven branded entertainment, focusing on ethical, strategic, and creative innovations in sustainable advertising. As brands increasingly adopt green marketing to resonate with environmentally conscious consumers, artificial intelligence (AI) is transforming the way branded content is produced, personalized, and delivered. The chapter discusses ethical concerns, such as transparency, data privacy, and potential manipulation, while highlighting the strategic benefits of AI in promoting sustainability. It also examines the evolving role of advertising professionals, emphasizing the new competencies required to navigate this AI-driven landscape. Case studies of successful campaigns illustrate how AI can effectively engage audiences and drive sustainable consumer behavior. 2025, IGI Global Scientific Publishing. Publisher An entity responsible for making the resource available IGI Global Relation A related resource ISBN: 979-836933800-1; 979-836933799-8; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library 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 A name given to the resource 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 A name given to the resource Assessment of diversity, abundance, and seasonal variatons of bird species in Bengaluru District, India during COVID-19 lockdown Subject The topic of the resource Avian abundance; bird diversity; conservaton; lockdown efects; polluton indices; species evenness; species richness; threatened species; water bodies Description An account of the resource The study investgates bird populaton dynamics in Bengaluru, India, post-lockdown, focusing on occurrence, seasonal abundance, species diversity, richness, dominance, and evenness. It covers 55 bird species across 52 genera, grouped into 32 families within 13 orders, with a notable peak in winter. Various indices, including Shannon Wiener, Margalefs, Pielous, and Simpsons, reveal signifcant seasonal diferences in bird populaton characteristcs. The Rock Pigeon Columba livia dominates, while the Black-headed Ibis Threskiornis melanocephalus is less prevalent. The study identfes Near Threatened species like Black-headed Ibis and Oriental Darter Anhinga melanogaster, along with Least Concern species per the IUCN Red List. Common species include Rock Pigeon, Large-billed Crow Corvus macrorhynchos, House Crow Corvus splendens, Black Drongo Dicrurus macrocercus, Brown Shrike Lanius cristatus, Common Myna Acridotheres trists, Jungle Myna Acridotheres fuscus, Red-whiskered Bulbul Pycnonotus jocosus, and Streak-throated Swallow Petrochelidon fuvicola. The study aims to inform improved management and conservaton strategies for Bengalurus diverse bird species. Hemanth et al. 2024. Creatve Commons Atributon 4.0 Internatonal License. JoTT allows unrestricted use, reproducton, and distributon of this artcle in any medium by providing adequate credit to the author(s) and the source of publicaton Creator An entity primarily responsible for making the resource Hemanth H.; Vinanthi R.K.S.; Paari K.A. Source A related resource from which the described resource is derived Journal of Threatened Taxa, Vol-16, No. 1, pp. 24557-24567. Publisher An entity responsible for making the resource available Zoo Outreach Organisation Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.11609/jott.8639.16.1.24557-24567" target="_blank" rel="noreferrer noopener">https://doi.org/10.11609/jott.8639.16.1.24557-24567</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185461643&doi=10.11609%2Fjott.8639.16.1.24557-24567&partnerID=40&md5=1099e8ccfbc1c814f8b74f6ad1aa35ef" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185461643&doi=10.11609%2fjott.8639.16.1.24557-24567&partnerID=40&md5=1099e8ccfbc1c814f8b74f6ad1aa35ef</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 9747893 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource 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 Hemanth H., Department of Lifesciences, CHRIST (Deemed to be University), Dharmaram College Road, Hosur Road, Karnataka, Bengaluru, 560029, India; Vinanthi R.K.S., Department of Lifesciences, CHRIST (Deemed to be University), Dharmaram College Road, Hosur Road, Karnataka, Bengaluru, 560029, India; Paari K.A., Department of Lifesciences, CHRIST (Deemed to be University), Dharmaram College Road, Hosur Road, Karnataka, Bengaluru, 560029, India 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 A name given to the resource Book Chapter Book Chapter Faculty Publications- Book Chapter 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 A name given to the resource Advancing Nutrient Removal and Resource Recovery Through Artificial Intelligence: A Comprehensive Analysis and Future Perspectives Subject The topic of the resource Artificial intelligence (AI); Environmental engineering; Nutrient removal; Resource recovery; Sustainable innovations; Wastewater treatment Description An account of the resource The increasing difficulties associated with effectively controlling wastewater treatment operations while simultaneously satisfying the imperatives of nutrient removal and resource recovery have necessitated the use of advanced technology. This book chapter provides a comprehensive analysis of the use of artificial intelligence (AI) methods within this complex context. Utilizing a vast array of scholarly investigations and real-world implementations, this study explores the intricate domain of wastewater treatment, providing a comprehensive understanding of how artificial intelligence algorithms are used to enhance the efficiency of nutrient removal procedures and expedite the recovery of valuable resources. This chapter presents a thorough examination of the impact of artificial intelligence (AI) on sustainable innovations in wastewater treatment facilities. It accomplishes this through a comprehensive analysis of relevant data and the inclusion of real-world case studies. The findings of this research highlight the transformative effect of AI on conventional approaches to wastewater treatment, enabling the adoption of environmentally friendly and resource-efficient practices. The integration of artificial intelligence (AI) with wastewater management offers a fascinating story that highlights the shifting paradigm in the field of environmental engineering and the efficient exploitation of resources. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. Creator An entity primarily responsible for making the resource Hemanth K.S.; Deepika T.; Lakshmi V. Source A related resource from which the described resource is derived Springer Water, Vol-Part F3340, pp. 83-116. Publisher An entity responsible for making the resource available Springer Nature Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-3-031-67237-8_4" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-67237-8_4</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85202513607&doi=10.1007%2F978-3-031-67237-8_4&partnerID=40&md5=075d127bbfdc3782ba701281ccae418c" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85202513607&doi=10.1007%2f978-3-031-67237-8_4&partnerID=40&md5=075d127bbfdc3782ba701281ccae418c</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23646934 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Hemanth K.S., School of Computer Science and Applications, REVA University, Bengaluru, India, Department of Computer Science, Christ University, Bangalore, India; Deepika T., School of Computer Science and Applications, REVA University, Bengaluru, India; Lakshmi V., School of Computer Science and Applications, REVA University, Bengaluru, India 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 A name given to the resource Book Chapter Book Chapter Faculty Publications- Book Chapter 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 A name given to the resource Early stage detection of osteoarthritis of the joints (hip and knee) using machine learning Subject The topic of the resource Data-driven approach; Early OA detection; Ethical considerations; Machine learning (ML); Traditional diagnosis limitations Description An account of the resource This study explores the developing relationship between health care and technology, with a special emphasis on the use of machine learning (ML) algorithms to detect early stage osteoarthritis (OA) in the hip and knee joints. OA, a substantial worldwide health problem, requires improved diagnosis techniques. In this analysis, we illuminate the limitations of traditional methods, emphasizing the inherent subjectivity of clinical assessments and the delay in detection using routine imaging techniques. The research investigates the potential of ML to bring about significant changes. It focuses on combining various algorithms with extensive datasets and highlights the need to select relevant features and prepare the data to improve the accuracy of the models. The use of ML is closely connected to ethical issues, which include the protection of data privacy and the capacity to comprehend the models used. To bridge the gap between theory and practice, the chapter presents concrete examples of ML's practical use in detecting OA, opening possibilities for customized therapy and enhanced patient results. The chapter also highlights potential areas for future study, emphasizing the urgent requirement for additional progress in ML-based early detection techniques to alleviate the worldwide impact of OA. 2025 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies. Creator An entity primarily responsible for making the resource Hemanth K.S.; Tigulla D.; Lakshmi V.; Buhari S. Source A related resource from which the described resource is derived Diagnosing Musculoskeletal Conditions using Artifical Intelligence and Machine Learning to Aid Interpretation of Clinical Imaging, pp. 39-64. Publisher An entity responsible for making the resource available Elsevier Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1016/B978-0-443-32892-3.00003-8" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/B978-0-443-32892-3.00003-8</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85213517235&doi=10.1016%2FB978-0-443-32892-3.00003-8&partnerID=40&md5=5feb555353195ee4f5dc8fa3c5c58d00" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85213517235&doi=10.1016%2fB978-0-443-32892-3.00003-8&partnerID=40&md5=5feb555353195ee4f5dc8fa3c5c58d00</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-044332892-3; 978-044332893-0 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Hemanth K.S., Department of Computer Science, Christ University, Karnataka, Bangalore, India; Tigulla D., REVA University, School of Computer Science and Applications, Karnataka, Bengaluru, India; Lakshmi V., REVA University, School of Computer Science and Applications, Karnataka, Bengaluru, India; Buhari S., Universiti Teknologi Brunei, School of Business, Bandar Seri Begawan, Brunei Darussalam 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 A name given to the resource Faculty Publications 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/. Creator An entity primarily responsible for making the resource Hemanth Kumar, N.; Keshavamurthy, R.; Adarsha, H.; Aniruddha Ram, H.R.; Bhandarkar, Vivek Title A name given to the resource Impact of Carbon Nanofiber Fillers on Surface Finish and Dimensional Accuracy in FDM-printed Polymer Composites Parts Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Journal of Advanced Manufacturing Systems; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1142/S0219686727500661" target="_blank" rel="noreferrer noopener">https://doi.org/10.1142/S0219686727500661</a> <a href="https://www.scopus.com/pages/publications/105039666775?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105039666775?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Hemanth Kumar N., Department of Mechanical Engineering, Nitte Meenakshi Institute of Technology, Bangalore, India; Keshavamurthy R., Department of Mechanical and Automobile Engineering, Christ University, Bangalore, India; Adarsha H., Department of Mechanical Engineering, Jain University, Bangalore, India; Aniruddha Ram H.R., Department of Mechanical Engineering, Jyothy Institute of Technology, Bangalore, India; Bhandarkar V., Department of Mechanical Engineering, Dayananda Sagar College of Engineering, Bangalore, India Description An account of the resource This paper examines the effect of carbon nanofiber (CNF) reinforcement on the surface finish and dimensional accuracy of the polylactic acid (PLA) composite produced using fused deposition modeling (FDM). Twin-screw compounding was used to prepare PLA-CNF composite filaments with 03wt.% CNF with extrusion of filaments (L/D ratio 30:1, 120rpm). To prepare rectangular specimens (10 10 20mm), the filaments were printed with the nozzle size of 0.4 mm, the layer thickness of 0.1 mm, the infill density of 100%, and the print speed of 5 mm/s. Dimensional accuracy was assessed by a digital vernier caliper with a resolution of 0.01 mm, and surface roughness (Ra) was measured by a digital surface tester that was stylus-based. Every measurement was averaged three times, and the statistical examination of percent deviation and variance analysis of compositions was done. Findings show that CNF addition was important with respect to the dimensional stability and surface finish. The volume variation of the print decreased to 0.20% of PLA/3 wt.% CNF compared to 0.30% of neat PLA, which is a 33% smaller variation of the dimensional accuracy. The surface roughness also reduced as 0.70 ?m of neat PLA was reduced to 0.42 ?m of PLA/3 wt.% CNF, which is a 40% decrease. It was statistically tested that trends of consistent improvement were observed between compositions. The findings indicate that CNF reinforcement results in a higher level of geometric accuracy and less surface morphology in FDM-printed polymer composites. 2026 World Scientific Publishing Company. Subject The topic of the resource Carbon nanofibers; dimensional accuracy; fused deposition modeling (FDM); polymer composites; surface roughness Publisher An entity responsible for making the resource available World Scientific Relation A related resource ISSN: 2196867; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online 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 A name given to the resource 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 A name given to the resource Evaluation of mechanical properties of e-glass and coconut fiber reinforced with polyester and epoxy resin matrices Subject The topic of the resource Aerospace; microstructural study & morphological features; Stiffness; Weight percentage Description An account of the resource Composite manufacturing is the novel branch of science, which finds its immense applications in various industries such as sporting, automotive, aerospace and marine industries. The superior properties of composites such as stiffness, better mechanical properties, low density and light weight make it a candidate in engineering applications. The need for seeking alternate materials with increased performance in the field of composites revived this research, to prepare fiber reinforced composites by hand layup method using E-glass and coconut fibers with length 5-6 mm. The resin used in the preparation of composites was epoxy and polyester. Fiber reinforced composites were synthesized at 18:82 fiber-resin weight percentages. Samples prepared were tested to evaluate its mechanical and physical properties, such as tensile strength, flexural strength, impact strength, hardness and scanning electron microscope (SEM). Scanning electron microscope analysis revealed the morphological features. E-glass fiber reinforced epoxy composite exhibited better mechanical properties than other composite samples. The cross linking density of monomers of the epoxy resin and addition of the short chopped E-glass fibers enhanced the properties of E-glass epoxy fiber reinforced composite. TJPRC Pvt. Ltd. Creator An entity primarily responsible for making the resource Hemanth R.D.; Senthil Kumar M.; Gopinath A.; Natrayan L. Source A related resource from which the described resource is derived International Journal of Mechanical and Production Engineering Research and Development, Vol-7, No. 5, pp. 13-20. Publisher An entity responsible for making the resource available Transstellar Journal Publications and Research Consultancy Private Limited (TJPRC) Date A point or period of time associated with an event in the lifecycle of the resource 2017-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.24247/ijmperdoct20172" target="_blank" rel="noreferrer noopener">https://doi.org/10.24247/ijmperdoct20172</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028553124&doi=10.24247%2Fijmperdoct20172&partnerID=40&md5=e341ae9e7f9cdda9f6f5fe5e57af50eb" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028553124&doi=10.24247%2fijmperdoct20172&partnerID=40&md5=e341ae9e7f9cdda9f6f5fe5e57af50eb</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 22496890 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource 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 Hemanth R.D., SMBS, VIT University, Chennai, Tamil Nadu, India; Senthil Kumar M., SMBS, VIT University, Chennai, Tamil Nadu, India; Gopinath A., Department of Mechanical Engineering, Christ University, Bangalore, India; Natrayan L., SMBS, VIT University, Chennai, Tamil Nadu, India 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 A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter 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/. Creator An entity primarily responsible for making the resource Hemanth, D. Title A name given to the resource Benefits of AI in the Food Industry Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived AI Innovations for Improving the Food Industry;pp.1-36 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3693-9884-5.ch001" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3693-9884-5.ch001</a> <a href="https://www.scopus.com/pages/publications/105023946582?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105023946582?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Hemanth D., Christ University, India Description An account of the resource Artificial Intelligence is increasingly becoming a transformative force in the food industry, reshaping how food is produced, processed, and delivered. The current research on the impact of Artificial Intelligence on improving operational effectiveness in the food industry. Firstly, it emphasizes how AI technologies enhance production processes and optimize supply chain management while prioritizing food safety. By employing predictive analytics and automation, AI contributes to minimizing waste, maximizing resource use, and upholding high-quality standards throughout the production cycle. Secondly, the study investigates how AI boosts customer interaction by offering personalized experiences and streamlined service delivery. By evaluating consumer preferences and behaviors, AI allows food enterprises to customize their offerings, ultimately resulting in heightened customer satisfaction and loyalty. Through this investigation, the research seeks to provide practical insights and best practices for food sector stakeholders aiming to exploit AI for better operational results. 2026, IGI Global Scientific Publishing. All rights reserved. Publisher An entity responsible for making the resource available IGI Global Relation A related resource ISBN: 979-836939886-9; 979-836939884-5; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library 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 A name given to the resource Faculty Publications 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/. Creator An entity primarily responsible for making the resource Hemanth, Hinnakki; Paari, Kuppusamy Alagesan Title A name given to the resource Pediococcus pentaceous-mediated fermentation of Gracilaria corticate: A sustainable reutilisation of renewable resource to enhance its nutritional profile, optimised through response surface methodology for improved growth and pathogenic resistance in Oreochromis niloticus Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Research Journal of Biotechnology;Volume;21;Issue;1;pp.297-308 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.25303/211rjbt2970308" target="_blank" rel="noreferrer noopener">https://doi.org/10.25303/211rjbt2970308</a> <a href="https://www.scopus.com/pages/publications/105025362573?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105025362573?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Hemanth H., Department of Life Sciences, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bengaluru, 560029, India; Paari K.A., Department of Life Sciences, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bengaluru, 560029, India Description An account of the resource Seaweed, as a functional food and a sustainable alternative to synthetic additives, is gaining attention. It can enhance the nutritive value, improve antioxidant properties and mitigate oxidative stress induced by pathogens. This study investigates the utilisation of fermented seaweeds in feed formulations to reduce oxidative stress, improve fish health and enhance disease resistance. Seaweeds Gracilaria corticate, rich in bioactive compounds such as polyphenols and antioxidants, were fermented using probiotic Pediococcus pentosaceus MK459540. Nile tilapia (Oreochromis niloticus) was fed a diet supplemented with fermented seaweed, which indicates lower levels of Superoxide Dismutase (SOD), Glutathione (GSH) and Glutathione-S-Transferase (GST) activities compared to control and non-fermented seaweeds when challenged with Vibrio harveyi, Aeromonas hydrophila and a mixture of both pathogens. These findings highlight the potential of seaweed, a sustainable and renewable marine resource in advancing aquaculture practices by promoting fish health and immunity. 2026, World Researchers Associations. All rights reserved. Subject The topic of the resource Box-Behnken model; Functional foods; Solid state fermentation Publisher An entity responsible for making the resource available World Researchers Associations Relation A related resource ISSN: 9736263; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online 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 A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter 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/. Creator An entity primarily responsible for making the resource Hemanth, K.S.; Fathima, Noorain; Sridhar, G.D. Title A name given to the resource Hormone Balancing Through Nutrition:Nutritional Strategies and AI Tools to Balance Hormones Associated with PCOS Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived AI-Based Nutritional Intervention in Polycystic Ovary Syndrome (PCOS);pp.213-231 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-96-2120-0_8" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-96-2120-0_8</a> <a href="https://www.scopus.com/pages/publications/105008681205?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105008681205?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Hemanth K.S., Department of Computer Science, Christ University, Karnataka, Bangalore, India; Fathima N., School of Computer Science and Application, REVA University, Karnataka, Bangalore, India; Sridhar G.D., School of Computer Science and Application, REVA University, Karnataka, Bangalore, India Description An account of the resource Polycystic ovary syndrome (PCOS) causes a worldwide disturbance in hormonal equilibrium, leading to a growing need for individualized, non-pharmaceutical therapies. Studies on AI-driven technologies in PCOS have uncovered a groundbreaking approach to regulating hormones through dietary changes. AI algorithms examine individual data, integrating genetics, biomarkers, and dietary habits to provide a distinct metabolic and hormonal profile. Suggested options consist of adaptable meal plans that can adapt to immediate fluctuations in blood sugar and hormones, maximizing nutrition to regulate hormones, reduce inflammation, and enhance general well-being. Additionally, these recommendations provide predictive insights to enable proactive alterations to ones diet. The comprehensive evaluation of limitations and moral considerations about AI highlights the necessity for human expertise and safeguarding of data privacy. Concrete instances from reality and current scientific investigation demonstrate the capacity of AI to enhance the capabilities of women suffering from polycystic ovary syndrome (PCOS). Proposing the integration of AI into evidence-based dietary practices anticipates a future in PCOS care that is tailored, proactive, and data-driven, with the ability to maximize hormonal equilibrium and improve womens well-being. This concise investigation provides significant perspectives for healthcare practitioners engaged in the treatment of PCOS and associated endocrine problems. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. Subject The topic of the resource AI-driven personalized nutrition; Data privacy and ethics; Hormonal regulation; PCOS management; Predictive and proactive care Publisher An entity responsible for making the resource available Springer Nature Relation A related resource ISBN: 978-981962120-0; 978-981962119-4; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library 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 A name given to the resource Faculty Publications 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/. Creator An entity primarily responsible for making the resource Hemanth, K.S.; Harisha Naik, T.; Kartik, N.; Kumar, N. Nanda; Senthilkumar, S.; Ramya, R. Title A name given to the resource Attentional Deep Learning with Inverse Transform Sampling for Robust Respiratory Sound Classification Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Journal of Information Technology Management;Volume;18;Issue;1;pp.123-140 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.22059/jitm.2026.1062557" target="_blank" rel="noreferrer noopener">https://doi.org/10.22059/jitm.2026.1062557</a> <a href="https://www.scopus.com/pages/publications/105038337718?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105038337718?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Hemanth K.S., Department of Computer Science, Christ University, Bengaluru, India; Harisha Naik T., Department of Computer Applications, Presidency College, Bangalore, India; Kartik N., Department of Commerce, Manipal Academy of Higher Education, Manipal, India; Kumar N.N., Department of Computer Science and Engineering, Excel Engineering College, Tamilnadu, Komarpalayampalyam, India; Senthilkumar S., Department of Computer Science and Engineering, Vinayaka Mission`s Kirupananda Variyar Engineering College, (Vinayaka Mission`s Research Foundation), Salem, India; Ramya R., Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Tamilnadu, Erode, India Description An account of the resource The necessity for efficient breathing sound classification systems originates from respiratory diseases, which impair oxygen-carbon dioxide exchange and impact lung function. Feature extraction and pattern categorization are general components of such systems. Because of their effectiveness with big datasets, deep neural networks have acquired popularity recently in the category of breathing sounds. Enhancing medical care requires cooperation amongst researchers, medical professionals, and patients. An attentional deep learning model with inverse transform sampling is presented in this study to classify respiratory diseases from audio data. Robust models were developed to classify and detect respiratory elements using the Respiratory Sound dataset. The primary objectives include effectively determining lung sounds and determining respiratory illnesses. The architectures of CNN, VGG16, and ResNet50 were developed to extract features and categorize data. Also, the pre-trained models ResNet50 and VGG16 identify critical characteristics in spectrum pictures more accurately. Inverse transfer sampling is used to rectify class imbalance in respiratory datasets. The models achieved 98% accuracy with the CNN model, 83% accuracy with VGG16, and 95% accuracy with ResNet50. Moreover, LSTM and CRNN models offer more information on how respiratory illnesses are classified. 2026, Hemanth K S, Harisha Naik T, N Kartik, N Nanda kumar, S Senthilkumar and Ramya R. Subject The topic of the resource CNN; Deep Neural Network; Inverse Transform Sampling; Pre-trained Models; Respiratory Diseases Publisher An entity responsible for making the resource available University of Tehran Relation A related resource ISSN: 20085893; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online 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 A name given to the resource Faculty Publications 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/. Creator An entity primarily responsible for making the resource Hemavathi, P.S.; Munavalli, Rahul; Pavithra, N.; Nanjappa, Manjunath; Harshavardhana, C.N. Title A name given to the resource QSPR ANALYSIS OF ANTI-ASTHMATIC DRUGS USING REDEFINED FIRST ZAGREB POWER INDEX Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Global and Stochastic Analysis;Volume;13;Issue;2;pp.1-25 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.64837/GSA.13.2.1" target="_blank" rel="noreferrer noopener">https://doi.org/10.64837/GSA.13.2.1</a> <a href="https://www.scopus.com/pages/publications/105039324527?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105039324527?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Hemavathi P.S., Department of Mathematics, Siddaganga Institute of Technology, Tumakuru, 572103, India; Munavalli R., Department of Mathematics, Vidyavardhaka College of Engineering, Mysuru, 570006, India; Pavithra N., Department of Mathematics, CHRIST (Deemed to be University), Bengaluru, 560 029, India, Department of Mathematics, Government Engineering College, Chamarajanagar, 571 313, India; Nanjappa M., Department of Sciences and Humanities, School of Engineering and Technology, CHRIST (Deemed to be University), Bengaluru, 560 074, India; Harshavardhana C.N., Department of Mathematics, Government Science College (Autonomous), Hassan, 573 201, India Description An account of the resource In this paper, we introduce a novel degree-based topological in-dex, the Redefined First Zagreb Power Index (ReZG1P I(G)). Explicit formu-lae for ReZG1P I(G) are derived for several standard graphs. Furthermore, we investigate the quantitative structureproperty relationship (QSPR) of anti-asthmatic drugs. The study reveals a strong correlation between the physicochemical properties of these drugs and their corresponding ReZG1P I(G), reflecting the structural representation of molecules as graphs. Finally, we establish linear and quadratic regression models between the proposed molec-ular descriptor and the physicochemical properties of anti-asthmatic drugs. 2026, MUK Publications and Distribution. All rights reserved. Subject The topic of the resource Maximum degree; Minimum degree; QSPR anal-ysis; Topological indices Publisher An entity responsible for making the resource available MUK Publications and Distribution Relation A related resource ISSN: 22489444; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource All Open Access; Bronze Open Access Format The file format, physical medium, or dimensions of the resource online https://archives.christuniversity.in/files/original/7a8b25c774d0382af3917bfd74e8fb7f.pdf c52cd22cf8e3e1f404b9fc1e0eb63de2 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 A name given to the resource MASTERS Masters' Dissertation Masters Dissertation 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 A name given to the resource Portrayal of African Americans in hollywood movies released from 2006-2013 / Creator An entity primarily responsible for making the resource Hemrom, Augustine Sahay. - 1424004 Date A point or period of time associated with an event in the lifecycle of the resource 2016-01-28 Source A related resource from which the described resource is derived Master of Arts in Communication and Media Studies Subject The topic of the resource Media Studies Description An account of the resource Racial stereotypes in American movies have mirrored our general public's predominant philosophies and have impacted our belief systems since the film business started. This study relates to the portrayal of how African Americans are projected in the certain movies from a particular time period from 2006-2013. Generalizations of blacks as lethargic, imbecilic, absurd, apprehensive, easygoing, reckless, infantile, rough, sub-human, and creature like, are widespread in today's general public. These debasing generalizations are fortified and upgraded by the negative depiction of blacks in the media. Publisher An entity responsible for making the resource available CHRIST (Deemed To Be University) Contributor An entity responsible for making contributions to the resource Department of Media Studies Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Masters Dissertation