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                <text>Debsarma, Anirban; Sarkar, Sreemoyee</text>
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                <text>Intersecting queer rights and legislative theatre in India: advocacy narrative of power, justice and expression</text>
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                <text>Research in Drama Education;Volume;30;Issue;3;pp.662-678</text>
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                <text>&lt;a href="https://doi.org/10.1080/13569783.2025.2513608" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1080/13569783.2025.2513608&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105010196621?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105010196621?origin=resultslist&lt;/a&gt;</text>
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                <text>Debsarma A.; Sarkar S., Department of International Studies, Political Science and History, CHRIST University, Bangalore, India</text>
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                <text>Queer activism and Legislative Theatre (LT) converge in myriad ways at their intersection, influencing and shaping each other. The present work investigates how LT can help to identify queer marginalisation in the fissured legal paradigm of India. It explores how LT can address the hegemonic silencing of the queer from an advocacy perspective. Our conviction is that the LT challenges the entrenched power structures against a queer-inclusive democratic space, offers a blueprint to advance queer dialogue, and coalition-building for legislation and policy discussions. It is the time when such a potent artistic activism must shape the public discourse.  2025 Informa UK Limited, trading as Taylor &amp;amp; Francis Group.</text>
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                <text>Intersection of AI and business intelligence in data-driven decision-making</text>
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                <text>In today's rapidly evolving business landscape, organizations are inundated with vast amounts of data, making it increasingly challenging to extract meaningful insights and make informed decisions. The traditional business intelligence (BI) approach must often address the complexity and speed required for effective decision-making in this data-rich environment. As a result, many businesses need help to leverage their data to drive sustainable growth and remain competitive. Intersection of AI and Business Intelligence in Data-Driven Decision-Making presents a transformative solution to this pressing challenge. By exploring the convergence of artificial intelligence (AI) and BI, our book provides a comprehensive framework for leveraging AI-powered BI to revolutionize data analysis, predictive modeling, and decision-making processes. Readers will gain valuable insights into practical applications, emerging trends, and ethical considerations, inspiring and exciting them about the potential of AI in driving business success. Through in-depth discussions, case studies, and best practices, this book equips professionals, researchers, and students with the knowledge and tools needed to navigate the complexities of AI-powered business intelligence. Whether you're looking to predict trends, analyze consumer behavior, or optimize supply chains, this book offers actionable strategies and techniques for implementing AI-powered BI solutions in your organization.  2024 by IGI Global. All rights reserved.</text>
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                <text>Natarajan A.K.; Galety M.G.; Iwendi C.; Das D.; Shankar A.</text>
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                <text>Intersection of AI and Business Intelligence in Data-Driven Decision-Making, pp. 1-486.</text>
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                <text>&lt;a href="https://doi.org/10.4018/979-8-3693-5288-5" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.4018/979-8-3693-5288-5&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215356172&amp;amp;doi=10.4018%2F979-8-3693-5288-5&amp;amp;partnerID=40&amp;amp;md5=878d751b15cd07279579681d7520cc41" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215356172&amp;amp;doi=10.4018%2f979-8-3693-5288-5&amp;amp;partnerID=40&amp;amp;md5=878d751b15cd07279579681d7520cc41&lt;/a&gt;</text>
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                <text>ISBN: 979-836935289-2; 979-836935288-5</text>
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                <text>Natarajan A.K., Samarkand International University of Technology, Uzbekistan; Galety M.G., Samarkand International University of Technology, Uzbekistan; Iwendi C., University of Bolton, United Kingdom; Das D., Christ University, India; Shankar A., University of Warwick, United Kingdom</text>
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                <text>Interval-Valued Fuzzy Trees and Cycles</text>
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                <text>Interval-valued fuzzy tree (IVFT) and interval-valued fuzzy cycle (IVFC) are defined in this chapter. We characterize interval-valued fuzzy trees. We also prove that if G is an IVFG whose underlying crisp graph is not a tree then G is an IVFT if and only if G contains only ? strong arcs and weak arcs. It is shown that an IVFG G whose underlying crisp graph is a cycle is an IVFC if and only if G has at least two ? strong arcs.  2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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                <text>Philip A.M.; Kalayathankal S.J.; Kureethara J.V.</text>
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                <text>Lecture Notes in Networks and Systems, Vol-462, pp. 251-263.</text>
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                <text>Springer Science and Business Media Deutschland GmbH</text>
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                <text>&lt;a href="https://doi.org/10.1007/978-981-19-2211-4_22" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-981-19-2211-4_22&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135024157&amp;amp;doi=10.1007%2F978-981-19-2211-4_22&amp;amp;partnerID=40&amp;amp;md5=e779c72e2dac69e5e6c1a543e107dcd9" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135024157&amp;amp;doi=10.1007%2f978-981-19-2211-4_22&amp;amp;partnerID=40&amp;amp;md5=e779c72e2dac69e5e6c1a543e107dcd9&lt;/a&gt;</text>
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                <text>ISSN: 23673370; ISBN: 978-981192210-7</text>
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                <text>Philip A.M., Assumption College, Changanacherry, India; Kalayathankal S.J., Jyothi Engineering College, Thrissur, India; Kureethara J.V., Christ University, Bangalore, India</text>
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          <element elementId="50">
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                <text>Interventions for the improvement of social skills in autism spectrum disorder in India: A systematic review</text>
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          <element elementId="49">
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                <text>Autism spectrum disorder; Intervention; Social skills</text>
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                <text>Background: The increasing prevalence of Autism Spectrum Disorders (ASD) in India is in a gaping contrast with the existing interventions in India. Though several interventions have proved their efficiency in foreign countries, such studies within India are scarce. Aims: This review attempts to systematically examine the different intervention practices that include improvement of social skills in ASD that is practiced in India as revealed through published literature on the same. Methods: Studies published from 2000 to 2020 were selected for the study. Evidence is presented for nine treatment categories: Behavior-based interventions, Developmental Interventions, TEACHH approach, Parent-mediated Interventions, speech-based Interventions, electronics-based interventions, augmentative and alternative communication, play-based interventions and Yoga-based interventions. These studies were drawn from databases Ebsco, Proquest, PubMed, MEDLINE, science direct and Google Scholar. Though a definitive conclusion cannot be drawn without a meta-analysis, the available evidence is gathered and evaluated in the present review. Results: The review has proved to be a reliable summary of the interventions that include improvement of social skills in ASD that is practiced in India. Conclusions: Parent-mediated interventions may be more appropriate for the resource-poor settings of India, when developmental interventions may be more appropriate for the resourcerich settings of India. The scarcity of published literature on the topic in India is also a significant factor that highlighted itself through the research.  2021, Indian Association for Child and Adolescent Mental Health. All rights reserved.</text>
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                <text>Alexander A.E.; Padmakumari P.; Padavan I.D.</text>
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                <text>Journal of Indian Association for Child and Adolescent Mental Health, Vol-17, No. 2, pp. 178-203.</text>
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                <text>Indian Association for Child and Adolescent Mental Health</text>
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              <elementText elementTextId="118613">
                <text>2021-01-01</text>
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                <text>William A.A., Christ University, India; Nanjundan P., Christ University, India; Thomas J., Christ University, India</text>
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                <text>In this age of AI, the unison of man and machine is going to be more prominent than ever, thus creating a need to understand the underlying framework that is adopted by app designers and developers from a psychological point of view. Research on the various benefits and harmful effects of user experience design and furthermore developing interventions and regulations to moderate the use of dark strategies in digital tools is the need of the hour. This paper calls for an ethical consideration of designing the experience of users by looking at the unethical practices that exist currently. The purpose of the study was to understand the cognitive, behavioural and affective experience of dark patterns in end users. There is a scarcity in the scientific literature with regard to dark patterns. This paper adopts the methodology of user cognitive walkthrough with 6 participants whose transcripts were analysed using thematic network analyses. The results are presented in the form of a thematic network. A few examples of the themes found are the experience of manipulation in users, rebellious attitudes, and automatic or habitual responses. These findings provide a basis for an in-depth understanding of dark patterns in user experience and provide themes that will help future researchers and designers develop ethical and more enriching user experiences for users.  2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.</text>
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                <text>Communications in Computer and Information Science, Vol-1832 CCIS, pp. 609-618.</text>
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                <text>Intricate Plane of Adversarial Attacks in Sustainable Territory and the Perils faced Machine Intelligent Models</text>
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                <text>Adversarial AI; Cyber security; Deep Learning; Generative Adversarial Networks(GANs); Machine learning; Sustainability</text>
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                <text>The issue of model security and reliability in Artificial Intelligence (AI) is a concern due to adversarial attacks. In order to tackle this issue, researchers have developed sustainable defense strategies, but certain challenges remain. These challenges involve transferability, higher computing costs, and adaptability. Striking a balance between accuracy and robustness is difficult, as defense mechanisms often come with trade-offs between the two. Real-world situations demonstrate the practical implications of sustainable adversarial AI. For example, it improves the security of self-driving vehicles, enhances the accuracy of medical imaging diagnoses, and incorporates AI-driven defenses into network intrusion detection and phishing detection systems. It is crucial to consider ethical aspects throughout this process. Future trends in adversarial AI research for cybersecurity will involve ensemble defense mechanisms, adversarial learning from limited data, and hybrid attacks. By embracing the evolving landscape, researchers and practitioners can develop sustainable AI systems that are more secure and resilient, effectively countering adversarial threats.   2023 IEEE.</text>
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                <text>Sai Susmitha K.S., Deemed to Be University, Kalinga Institute of Industrial Technology, India; Srimlika N., Deemed to Be University, Kalinga Institute of Industrial Technology, India; Sharma V., Deemed to Be University, CHRIST, Delhi NCR, India; Almusawi M., The Islamic University, College of Technical Engineering, Najaf, Iraq; Mishra S., Deemed to Be University, Kalinga Institute of Industrial Technology, India</text>
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                <text>Restricted Access; Hardcopy may be available in the library</text>
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                  <text>Faculty Publications</text>
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                <text>Cherian, Merin; Mangam, Tabitha Agnes</text>
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                <text>Introduction to connecting coalitions</text>
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                <text>01-01-2025</text>
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                <text>Discrete Mathematics, Algorithms and Applications;Issue;;Article No.;2550158;</text>
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                <text>&lt;a href="https://doi.org/10.1142/S1793830925501587" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1142/S1793830925501587&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105022625275?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105022625275?origin=resultslist&lt;/a&gt;</text>
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                <text>Cherian M., Department of Mathematics, Christ (Deemed to be University), Karnataka, Bengaluru, India; Mangam T.A., Department of Mathematics, Christ (Deemed to be University), Karnataka, Bengaluru, India</text>
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                <text>A connecting coalition in a graph G(V;E) consists of two disjoint vertex subsets V1 and V2 of V (G), where neither G[V1] nor G[V2] is a connected graph but G[V1 [V2] is a con- nected graph. A connecting coalition partition is a vertex partition ? = fV1; V2; : : : ; Vkg, and the maximum cardinality of all possible ? is called the connecting coalition number, ?(G). Some bounds on the coalition number ?(G) are found, and graphs having ?(G) = 2 are characterized. Further, the existence of connecting coalition partitions in graphs is explored.  2025 World Scientific Publishing Company.</text>
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                <text>coalition partition; Connected graphs; induced subgraphs</text>
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                <text>World Scientific</text>
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                <text>ISSN: 17938309;</text>
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                <text>Restricted Access; Hardcopy may be available in the library</text>
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                <text>online</text>
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