405
20
16481
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Articles
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Faculty Publications -Articles
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Title
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Happiness, Meaning, and Satisfaction in Life as Perceived by Indian University Students and Their Association with Spirituality
Subject
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Happiness; Meaning in life; Satisfaction; Spirituality; University students
Description
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The present study aims to examine the association between various dimensions of psychological well-being (subjective happiness, satisfaction, and meaning in life), spirituality, and demographic and socioeconomic background of university students. A total of 414 postgraduate students were selected from three different schools, viz. science, management, and social sciences/humanities of Pondicherry University (A Central University), Puducherry, India, following multistage cluster sampling method. One semi-structured questionnaire and four standardized psychological scales, viz. subjective happiness scale, satisfaction with life scale, meaning in life questionnaire, and spirituality attitude inventory, were used for data collection after checking psychometric properties of the scales. The results show that a positive significant correlation between spirituality and subjective happiness exists. Spirituality is also correlated with meaning in life and satisfaction with life scale. Statistically, no significant gender difference was observed with respect to subjective happiness, meaning, and satisfaction in life as well as spirituality although the mean score of female students was more in all the four psychological domains. Non-integrated students are found to be happier than integrated students, and statistically it was significant. Positive interpersonal relationship and congenial family environment were probed to be facilitating factors for positive mental health of university students. There is a severe need to address students mental health by every educational institution through multiple programs. 2019, Springer Science+Business Media, LLC, part of Springer Nature.
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Deb S.; Thomas S.; Bose A.; Aswathi T.
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Journal of Religion and Health, Vol-59, No. 5, pp. 2469-2485.
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Springer
Date
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2020-01-01
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<a href="https://doi.org/10.1007/s10943-019-00806-w" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s10943-019-00806-w</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85064255087&doi=10.1007%2Fs10943-019-00806-w&partnerID=40&md5=410e70e57bcc1ded3bafba2dd8ae9378" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85064255087&doi=10.1007%2fs10943-019-00806-w&partnerID=40&md5=410e70e57bcc1ded3bafba2dd8ae9378</a>
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ISSN: 224197; PubMed ID: 30963363; CODEN: JRHEA
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Online
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English
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Article
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Deb S., Department of Applied Psychology, Pondicherry University, Puducherry, India; Thomas S., Department of Psychology, CHRIST (Deemed to be University), Bangalore, India; Bose A., Department of Applied Psychology, Pondicherry University, Puducherry, India; Aswathi T., Department of Applied Psychology, Pondicherry University, Puducherry, India
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Title
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Book Chapter
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Title
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Haptics: Prominence and Challenges
Subject
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Actuator; Force feedback gaming joysticks; Gloves; Haptic; Haptic knobs; Haptic paddles; Novint Falcon; SensAbles Omni Phantom; Tactile
Description
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Derived from a Greek word meaning sense of touch, Haptic is a communication technology which applies tactile sensation for human-computer interaction with computers. Haptic technology, or haptics, is a tangible feedback technology that takes benefit of a users sense of touch by applying forces, sensations, or motions to the user. These objects are used to methodically probe human haptic capabilities, which would be complex to achieve without them. This innovative research tool gives an understanding of how touch and its core functions work. The article will provide a detailed insight into the working principles, uniqueness of the technology, its advantages and disadvantages along with some of its devices and notable applications. Future challenges and opportunities in the field will also be addressed. 2020, Springer Nature Switzerland AG.
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Sagaya Aurelia P.
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Learning and Analytics in Intelligent Systems, Vol-6, pp. 21-43.
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Springer Nature
Date
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2020-01-01
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<a href="https://doi.org/10.1007/978-3-030-35139-7_2" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-030-35139-7_2</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179869516&doi=10.1007%2F978-3-030-35139-7_2&partnerID=40&md5=10afd62c9b8039baa5d7e7b2c001bdd7" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179869516&doi=10.1007%2f978-3-030-35139-7_2&partnerID=40&md5=10afd62c9b8039baa5d7e7b2c001bdd7</a>
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ISSN: 26623447
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Online
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English
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Book chapter
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Sagaya Aurelia P., CHRIST (Deemed to be University), Bangalore, India
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Faculty Publications
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Ashoka, Kuruba; Parvathalu, Bolle; Arumugam, Subramanian
Title
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Harary Spectra and Energy of Certain Classes of Graphs
Date
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01-01-2025
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Current Organic Synthesis;Volume;22;Issue;7;pp.791-798
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<a href="https://doi.org/10.2174/0115701794330372241114102237" target="_blank" rel="noreferrer noopener">https://doi.org/10.2174/0115701794330372241114102237</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105023288676?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105023288676?origin=resultslist</a>
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Ashoka K., Department of Mathematics, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bangalore, 560029, India; Parvathalu B., Department of Mathematics, Karnatak Universitys Karnatak Arts/Science College Dharwad, Karnataka, 580001, India; Arumugam S., Department of Computer Science and Engineering, Ramco Institute of Technology Rajapalayam, Tamil Nadu, 626117, India
Description
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Aims: To investigate the H-eigenvalues and H-energy of various types of graphs, including k-fold graphs, strong k-fold graphs, and extended bipartite double graphs and establish relationships between the H-energy of k-fold and strong k-fold graphs and the H-energy of the original graph G, we explore the connection between the H-energy of extended bipartite double graphs and their ordinary energy and find the graphs that share equienergetic properties with respect to both the ordinary and Harary matrices. Background: The H-eigenvalues of a graph G are the eigenvalues of its Harary matrix H(G). The H-energy {Formula Presented} of a graph, G is the sum of the absolute values of its H-eigenvalues. Two connected graphs are said to be H-equienergetic if they have equal H-energies. They are said to A-equienergetic if they have equal A-energies. Adjacency and Harary matrices have applications in chemistry, such as finding total electron energy, quantitative structure-property relationship (QSPR), etc. Objectives: We determined the H-spectra of k-fold graphs, strong k-fold graphs and extended bipartite double graphs and established connections between the H-energy of different types of graphs and their original graph G for investigating the relationship between the H-energy of extended bipartite double graphs and their ordinary energy and the graphs that share equienergetic properties with respect to both the adjacency and Harary matrices. Methods: Spectral algebraic techniques are used to calculate the H-eigenvalues and H-energy for each type of graph and compare the H-energies of different graphs to identify the equienergetic properties and derive relationships between the H-energy of extended double cover graphs and their ordinary energy. Results: We determined the H-spectra of k-fold graphs, strong k-fold graphs and extended bipartite double graphs and established relationships between the H-energy of k-fold and strong k-fold graphs and the H-energy of the original graph G. Then, we explored the connection between the H-energy of extended bipartite double graphs and their ordinary energy and presented graphs demonstrating equienergetic properties concerning both adjacency and Harary matrices. Conclusion: The study provides insights into the H-eigenvalues, H-energy and equienergetic properties of various types of graphs. The established relationships and connections contribute to a deeper understanding of graph spectra and energy properties and the findings enhance the theoretical framework for analyzing equienergetic graphs and their spectral properties. Scope: Possible extensions of this research could include investigating additional types of graphs and exploring further explicit connections between different graph energies and spectral properties. Harary matrices are distance-based matrices, which can model distances between atoms in molecular structures and could be useful in organic synthesis to predict how molecular structures behave. 2025, Bentham Science Publishers
Subject
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equienergetic graphs; harary eigenvalues; harary energy; harary equienergetic graphs; Harary matrix; ordinary energy
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Bentham Science Publishers
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ISSN: 15701794;
Language
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English
Type
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Article
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Restricted Access; Hardcopy may be available in the library
Format
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online
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Title
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Faculty Publications
Book Chapter
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Tyagi, Ujjwal; Kumar, Amit
Title
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Hard Money vs. Soft Money and the Battle for Higher Education's Future: How Universities Can Leverage Both to Survive and Thrive
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01-01-2025
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Financial Survival in Higher Education;pp.181-209
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<a href="https://doi.org/10.4018/979-8-3373-0407-6.ch007" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3373-0407-6.ch007</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105015940359?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105015940359?origin=resultslist</a>
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Tyagi U., Christ University, India; Kumar A., Christ University, India
Description
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In the ever-evolving landscape of higher education, the debate between hard money and soft money is more than just a financial discussion it's a survival strategy. Hard money, with its stability, keeps universities running, while soft money fuels innovation and growth. But how can institutions balance the two to thrive in an era of shrinking budgets and rising demands? This chapter explores the critical differences between hard and soft money, their roles in shaping higher education, and actionable strategies for achieving financial resilience. Through real-world case studies and global insights, we uncover how universities can diversify funding, manage risks, and secure their future. Whether you're a policymaker, administrator, or educator, this chapter offers a roadmap to navigating the complex financial challenges of higher education. Don't miss this essential guide to financial survival in a changing world!. 2026 by IGI Global Scientific Publishing. All rights reserved.
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IGI Global
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ISBN: 979-833730409-0; 979-833730407-6;
Language
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English
Type
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Book chapter
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Restricted Access; Hardcopy may be available in the library
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Reviews
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Hardware in loop network simulators - An insight overview
Subject
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Hardware-in-loop; network simulators; system-in-loop
Description
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Network simulation is a method of using software or a tool which can be used to mimic the network conditions that exist in pre-defined places. This kind of simulation allows the developers, designers, researchers and the network planners to intelligently plan, design, develop and test their applications or research work in changing network conditions. With varying network conditions either because of wireless nature or because of user mobility, it is very difficult to simulate the exact network conditions with the existing network simulators. These network simulators are flexible, re-usable and reliable. But they have a limitation of not being able to replicate the actual network conditions in the laboratories. This calls for a system in the loop or hardware in the loop concept to be extended to the network simulators. The idea of system in the loop is not new. In this paper, an overview with the fundamental understanding of the hardware-in-loop concept for network simulators, their applications and a review of the existing hardware-in-loop network simulators with their advantages and disadvantages is presented. 2024 World Scientific Publishing Company.
Creator
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Sushanth G.; Ravish Aradhya H.V.
Source
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International Journal of Modeling, Simulation, and Scientific Computing, Vol-15, No. 1
Publisher
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World Scientific
Date
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2024-01-01
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<a href="https://doi.org/10.1142/S1793962324300012" target="_blank" rel="noreferrer noopener">https://doi.org/10.1142/S1793962324300012</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150152645&doi=10.1142%2FS1793962324300012&partnerID=40&md5=b523cba776eab053a9008822757eaa82" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150152645&doi=10.1142%2fS1793962324300012&partnerID=40&md5=b523cba776eab053a9008822757eaa82</a>
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ISSN: 17939623
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Online
Language
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English
Type
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Review
Coverage
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Sushanth G., Department of Electronics and Communication Engineering, R. V. College of Engineering, Affiliated to Vtu, Belagavi, Karnataka, Bengaluru, India, Department of Electronics and Communication Engineering, Christ University, Karnataka, Bengaluru, India; Ravish Aradhya H.V., Department of Electronics and Communication Engineering, R. V. College of Engineering, Affiliated to Vtu, Belagavi, Karnataka, Bengaluru, India
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Book Chapter
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Title
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Harmonizing financial systems for a greener future: Exploring sustainable finance strategies in India
Description
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Sustainable finance represents the next biggest transformation in the financial sector to aid the process of sustainable development. Sustainable finance comprises traditional investment which provides financial profits as well as financing the projects or investments that have social, economic and governance impact. The transition from traditional investment to sustainable finance is underway in different markets at different capacities. This study seeks to examine the performance of sustainability indices representing sustainable finance in the Indian and global markets by analysing returns. It was found that sustainable finance gained significant appreciation in the Indian market. In comparing the performance of sustainability indices in developing and developed markets, there was no development divide identified. In this path towards widespread adoption of sustainable finance, data science as a field also provides promising applications for facilitating this transformation. 2024, IGI Global. All rights reserved.
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Vellaiyan S.; Loganathan S.; Pachiyappan S.; John Paul Raj V.
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Recent Developments in Financial Management and Economics, pp. 294-310.
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IGI Global
Date
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2024-01-01
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<a href="https://doi.org/10.4018/979-8-3693-2683-1.ch016" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3693-2683-1.ch016</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190861555&doi=10.4018%2F979-8-3693-2683-1.ch016&partnerID=40&md5=ed6b809993517a01b6d15a08e09f6530" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190861555&doi=10.4018%2f979-8-3693-2683-1.ch016&partnerID=40&md5=ed6b809993517a01b6d15a08e09f6530</a>
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ISBN: 979-836932684-8; 979-836932683-1
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Online
Language
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English
Type
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Book chapter
Coverage
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Vellaiyan S., Christ Univerisity, India; Loganathan S., Christ Univerisity, India; Pachiyappan S., Christ Univerisity, India; John Paul Raj V., Christ Univerisity, India
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Book Chapter
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Harmonizing human resource strategies navigating employer branding in sustainable organizations
Description
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In the framework of sustainable businesses, this chapter examines the synergies between employer branding and human resource (HR) strategies. In order to establish a harmonic organizational framework, this chapter thoroughly investigates how HR practices might be strategically aligned with sustainability goals. It explores the opportunities and challenges of managing employer branding within sustainable business practices. It sheds light on specific variables and practices that must be considered to develop an employer brand that reflects the organization's commitment to sustainability. In order to create an integrated, attractive, and socially responsible employer brand, it is important to align their human resources practices with sustainability initiatives. It provides insights into the strategic integration of employer branding and human resources, presenting a roadmap for businesses looking to match their HR procedures with sustainability programs. 2024, IGI Global. All rights reserved.
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Francis S.; Rangasamy S.
Source
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Building Sustainable Human Resources Management Practices for Businesses, pp. 190-203.
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IGI Global
Date
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2024-01-01
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<a href="https://doi.org/10.4018/979-8-3693-1994-9.ch011" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3693-1994-9.ch011</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85191516389&doi=10.4018%2F979-8-3693-1994-9.ch011&partnerID=40&md5=1b65c5e205f9ae0163b48d2c2584b5e5" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85191516389&doi=10.4018%2f979-8-3693-1994-9.ch011&partnerID=40&md5=1b65c5e205f9ae0163b48d2c2584b5e5</a>
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ISBN: 979-836931995-6; 979-836931994-9
Format
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Online
Language
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English
Type
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Book chapter
Coverage
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Francis S., Christ University, India; Rangasamy S., Christ University, India
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Dublin Core
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Faculty Publications
Book Chapter
Faculty Publications- Book Chapter
Dublin Core
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Balaji, K.
Title
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Harnessing AI and blockchain in sustainability assurance: Trends shaping the future of verification
Date
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01-01-2025
Source
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Navigating Trust in Sustainability Reporting and Assurance;pp.215-242
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<a href="https://doi.org/10.4018/979-8-3373-0117-4.ch007" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3373-0117-4.ch007</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105000142517?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105000142517?origin=resultslist</a>
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Balaji K., Christ University, Bengaluru, India
Description
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The integration of artificial intelligence (AI) and blockchain technology is revolutionizing sustainability assurance, setting new benchmarks for transparency, accuracy, and accountability. This article explores current trends and innovative applications of AI and blockchain in verifying corporate sustainability efforts, from automated data analysis to secure, decentralized record- keeping. By leveraging AI for real- time monitoring and data insights, organizations can better track environmental and social impacts, while blockchain ensures data integrity and traceability across supply chains. These advancements enhance stakeholder trust and support regulatory compliance, addressing increasing demands for robust sustainability verification in global markets. Furthermore, the paper discusses challenges such as data privacy and implementation costs, offering insights into the potential long- term impact of these technologies on corporate governance. By examining recent case studies and market trends, this article outlines a future where technology-d riven assurance processes. 2025, IGI Global Scientific Publishing. All rights reserved.
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IGI Global
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ISBN: 979-833730119-8; 979-833730117-4;
Language
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English
Type
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Book chapter
Rights
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Restricted Access; Hardcopy may be available in the library
-
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Title
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Faculty Publications
Book Chapter
Faculty Publications- Book Chapter
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Pandey, Ananya
Title
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Harnessing AI for Environmental Hazard Mitigation and Resilience: Pathways to a Safer Future
Date
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01-01-2025
Source
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Geostatistical Insights on Mapping Flood Hazards and Wetland Dynamics;pp.151-178
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<a href="https://doi.org/10.4018/979-8-3373-3206-2.ch006" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3373-3206-2.ch006</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105021731585?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105021731585?origin=resultslist</a>
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Pandey A., Christ University, Bangalore, India
Description
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This chapter explores the transformative potential of artificial intelligence (AI) in mitigating environmental hazards and enhancing resilience to climate- related challenges. AI technologies are revolutionizing environmental monitoring, risk assessment, and disaster response through advanced data analytics, machine learning, and predictive modeling. By leveraging AI, stakeholders can predict and mitigate the impacts of natural disasters, improve resource management, and foster resilient infrastructures. The chapter examines the various applications of AI in hazard prediction, such as flood forecasting, wildfire management, and storm tracking, alongside its role in real- time monitoring and adaptive response systems. Furthermore, it highlights the ethical considerations, challenges, and limitations of deploying AI in environmental management. Through case studies and emerging practices, this chapter outlines pathways for harnessing AI to safeguard communities and ecosystems, ensuring a more resilient and sustainable future. 2025 by IGI Global Scientific Publishing. All rights reserved.
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IGI Global
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ISBN: 979-833733208-6; 979-833733206-2;
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English
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Faculty Publications
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Pandey, Ananya
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Harnessing Artificial Intelligence for Sustainable Innovation and Policy: The Eco-Intelligence
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01-01-2025
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Leveraging AI for Inclusive and Equitable Development;pp.159-178
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<a href="https://doi.org/10.4018/979-8-3373-2387-9.ch008" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3373-2387-9.ch008</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105023253977?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105023253977?origin=resultslist</a>
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Pandey A., Christ University, Bangalore, India
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Artificial Intelligence (AI) is revolutionizing sustainable innovation and policymaking by optimizing resource management, enhancing environmental monitoring, and fostering circular economies. This chapter explores Eco-Intelligence-the integration of AI-driven analytics, predictive modeling, and automation in addressing environmental challenges. By leveraging machine learning, and digital twins, AI enables real-time decision-making for climate adaptation, carbon footprint reduction, and green supply chains. Also, AI-driven regulatory frameworks enhance compliance with sustainability standards, bridging the gap between technological advancement and environmental governance. However, ethical concerns, algorithmic biases, and data privacy issues pose challenges to AI's effective deployment in sustainability policy. This chapter critically examines the intersection of AI, environmental stewardship, and regulatory landscapes, proposing a balanced approach to harness AI's potential for long-term ecological and economic resilience. 2026, IGI Global Scientific Publishing. All rights reserved.
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IGI Global
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ISBN: 979-833732389-3; 979-833732387-9;
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English
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Faculty Publications
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Rajak, Akash; Kumar, Amit; Singh, Shweta; Vidushi; Verma, Ankit; Mishra, Siddheshwari Dutt
Title
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Harnessing Behavioural Insights for Autism Spectrum Disorder Prediction via Machine Learning
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01-01-2025
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2025 12th International Conference on Reliability, Infocom Technologies and Optimization ,Trends and Future Directions, ICRITO 2025;
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<a href="https://doi.org/10.1109/ICRITO66076.2025.11241561" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICRITO66076.2025.11241561</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105029842779?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105029842779?origin=resultslist</a>
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Rajak A., Kiet Group of Institutions, Delhi-NCR, Ghaziabad, India; Kumar A., Kiet Group of Institutions, Delhi-NCR, Ghaziabad, India; Singh S., Kiet Group of Institutions, Delhi-NCR, Ghaziabad, India; Vidushi, Christ (Deemed to be University), Bengaluru, India; Verma A., Kiet Group of Institutions, Delhi-NCR, Ghaziabad, India; Mishra S.D., Mriirs, Faridabad, India
Description
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This paper exploration has been done for predicting autism spectrum disorder or ASD while using certain machine learning classifiers. The multisource dataset used, covers behavioral, genetic, neuroimaging and sensor data. The classifiers used are: Random Forest, AdaBoost, Extra Trees, Logistic Regression, K Neighbors, and Bernoulli Naive Bayes. The results achieved are: The Bernoulli Naive Bayes (92.10%), Random Forest (91.53%) and Logistic Regression (91.34%). AdaBoost and Extra Trees performed well with accuracies 90.34% and 90.20%, respectively. K Neighbors Classifier had the lowest accurate outcome with 87.65%. This study explores improving ASD diagnosis, highlighting the effectiveness of various models and emphasizing the need for further research to address challenges such as model interpretability and data quality. 2025 IEEE.
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autism spectrum disorder; machine learning; neural networks; random forest; stress management; support vector machines
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Institute of Electrical and Electronics Engineers Inc.
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ISBN: 979-833155421-7;
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English
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Singh, Shalini; Singh, Pooja; Pandey, Samriddhi; Yadav, Shubhanker
Title
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Harnessing Digital Finance for Sustainability and Equity in Marine and Seaside Economies
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01-01-2025
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World Sustainability Series;Volume;Part F794;pp.107-125
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<a href="https://doi.org/10.1007/978-3-031-92390-6_6" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-92390-6_6</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105014400130?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105014400130?origin=resultslist</a>
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Singh S., Assistant Professor, School of Commerce, Finance and Accountancy, CHRIST (Deemed to Be University), Bengaluru, India; Singh P., Freelancer, Researcher, Gujarat, India; Pandey S., Student, BCOM (Applied Finance and Analytics), School of Commerce, Finance and Accountancy, CHRIST (Deemed to Be University), Bengaluru, India; Yadav S., Assistant Professor, Jaipuria Institute of Management, Lucknow, India
Description
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The integration of digital finance into marine and seaside economies offers transformative potential to foster sustainability, equity, and economic growth. This chapter explores the role of financial technology (FinTech) in addressing the unique challenges faced by coastal and marine industries, including resource depletion, economic instability, and socio-environmental disparities. It highlights how innovations like blockchain, artificial intelligence (AI), and mobile financial platforms can enhance financial inclusion for coastal communities, streamline investment in sustainable marine projects, and promote transparent governance. Through case studies and data-driven analysis, the chapter investigates global best practices where digital finance has enabled resource optimisation, resilience in the face of climate change, and support for blue economy initiatives. By examining the interplay of technology, finance, and sustainability, this chapter aims to provide actionable insights into leveraging digital finance for building resilient and equitable marine ecosystems, contributing to a sustainable blue economy. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
Subject
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Artificial intelligence (AI); Blockchain; Blue economy governance; Digital finance; Financial technology (FinTech); Marine economies; Seaside economies; Sustainable blue economy; Sustainable development
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Springer Science and Business Media Deutschland GmbH
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ISSN: 21997373;
Language
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English
Type
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Book chapter
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Harnessing digital innovation for inclusive tourism: Role of emerging technologies in creating accessibility and equity
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Accessibility; Emerging technologies; Equity; Inclusive tourism; Travelers with special needs
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The rapid advancement of digital technologies has ushered in a new era for the tourism industry, presenting unprecedented opportunities to enhance inclusivity, accessibility, and equity in travel experiences. This study investigates the transformative potential of emerging technologies in fostering a more inclusive tourism landscape. Specifically, it examines how selected digital innovations such as artificial intelligence (AI), augmented and virtual reality (AR/VR), mobile applications, and wearable devices are shaping the accessibility and equity of tourism for diverse populations. This chapter begins with a comprehensive literature review, highlighting current trends, challenges, and existing studies on inclusive practices in the tourism sector. The paper delves into a detailed analysis of each emerging technology, showcasing successful integration examples from real-world cases. It evaluates the benefits and potential challenges of adopting these technologies, especially in enhancing accessibility for travelers with disabilities. The examination addresses physical, sensory, and cognitive accessibility barriers, providing insights into how technology reshapes travel experiences for diverse individuals. This chapter delves into the role of emerging digital innovations in fostering equity within the tourism sector. By facilitating cross-cultural connections and enhancing access to tech-driven travel experiences, these technologies contribute to a more inclusive landscape. The study scrutinizes socioeconomic dimensions, shedding light on the holistic impact of tech integration. While acknowledging challenges and ethical concerns, responsible technology deployment is endorsed to counterbalance drawbacks and bridge the digital divide, enabling marginalized communities to leverage the benefits of this digital transformation. The implications of this study are relevant for businesses, policymakers, and tourism stakeholders. The chapter concludes by providing practical recommendations for the responsible incorporation of emerging technologies and emphasizing the long-term sustainability of inclusive digital innovations. By shedding light on the transformative potential of these technologies and outlining guidelines for their application, this research contributes to the evolution of a more accessible, equitable, and inclusive tourism industry. 2024 Nova Science Publishers, Inc. All rights reserved.
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Elangovan N.; Sreedhara R.; Chennattuserry J.C.; Varghese B.
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Inclusive Business Approaches in Tourism: Stakeholder Engagement, pp. 77-101.
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Nova Science Publishers, Inc.
Date
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2024-01-01
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<a href="" target="_blank" rel="noreferrer noopener"></a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85206280011&partnerID=40&md5=41e04f8a0fe86bda5cc7571d59be1fac" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85206280011&partnerID=40&md5=41e04f8a0fe86bda5cc7571d59be1fac</a>
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ISBN: 979-889530032-9; 979-889113988-6
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Online
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English
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Book chapter
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Elangovan N., Christ University, Bangalore, India; Sreedhara R., Christ University, Bangalore, India; Chennattuserry J.C., Christ University, Bangalore, India; Varghese B., Christ University, Bangalore, India
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Faculty Publications
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Ellikkal, Adil; Park, Jin Yong; Thangam, Dhanabalan; Akanksha
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Harnessing Digital Marketing for Promoting Green Finance: A Strategic Approach to Building Climate Resilience
Date
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01-01-2026
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World Sustainability Series;Volume;Part F1959;pp.453-472
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<a href="https://doi.org/10.1007/978-3-032-19076-5_23" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-032-19076-5_23</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105040018368?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105040018368?origin=resultslist</a>
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Ellikkal A., Presidency Business School, Presidency College, Bengaluru, India; Park J.Y., Konkuk University, Seoul, South Korea; Thangam D., Presidency Business School, Presidency College, Bengaluru, India; Akanksha, Christ (Deemed to be University), Bengaluru, India
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The study intents to utilize digital marketing strategies in order to foster green finance and influence climate-resilient?financial practices. Utilizing 250 survey respondents, the paper investigates how digital marketing intensity, content quality and platform interactiveness influence critical psychological dimensions (perceived green?value perception, trust in green finance and perceived transparency). SEM analysis shows that digital marketing exerts a significant positive effect on these?mediators, and the aforementioned mediators significantly affect individual green financial product investment intention. Furthermore, investment intention is found to be the most significant predictor of climate-resilient financial behavior, suggesting that behavioral pathways are instrumental to understanding the?digital engagementsustainable finance value chain. The findings provide an insight to the importance of transparent, trustworthy and engaging digital communication as a strategy for reducing information?asymmetry and building consumer trust towards green finance offering. Drawing on literature in sustainable finance, behavioral economics and digital communication, this contribution to a nascent literature on the use of digital tools to strengthen climate resilience?presents opportunities associated with each. The research also has practical implications for policy makers and financial institutions that wish to promote pro-environmental behaviour in the financing sphere with digital?means. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
Subject
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Climate resilience; Digital marketing; Green finance; Sustainable investment and consumer behavior
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Springer Science and Business Media Deutschland GmbH
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ISSN: 21997373;
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English
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Book chapter
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Faculty Publications
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Thadathil, Ditto Abraham; Varghese, Anitha
Title
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Harnessing immobilized copper salophen complex for the electrochemical synthesis of phenazine
Date
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01-01-2025
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Electrochimica Acta;Volume;527;Issue;;Article No.;146265;
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<a href="https://doi.org/10.1016/j.electacta.2025.146265" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.electacta.2025.146265</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105002766934?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105002766934?origin=resultslist</a>
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Thadathil D.A., Department of Chemistry, Christ University, Karnataka, Bengaluru, 560029, India, Centre for Renewable Energy and Environmental Sustainability, Christ University, Karnataka, Bengaluru, 560029, India; Varghese A., Department of Chemistry, Christ University, Karnataka, Bengaluru, 560029, India, Centre for Renewable Energy and Environmental Sustainability, Christ University, Karnataka, Bengaluru, 560029, India
Description
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This study introduces a novel approach utilizing a modified electrode, denoted as Cu-PDABA-CFP, as a pivotal catalyst in the electrochemical synthesis of phenazine. Through bulk electrolysis of o-phenylene diamine in an acetonitrile medium, facilitated by lithium perchlorate as the supporting electrolyte, the electrode serves as a fundamental component in this synthetic endeavor. The modification process entails the immobilization of a copper-salophen complex, synthesized in accordance with established literature protocols, onto the electrode surface. Surface characterization of the modified electrode was meticulously conducted to get critical insights into the structural morphology and topographical features of the electrode surface, pivotal for understanding its electrochemical behavior. Concurrently, electrochemical characterization studies were undertaken to evaluate the inherent activity of the modified electrode. To elucidate the intricate electrochemical reaction mechanism underlying the synthetic transformation, an exhaustive screening of reaction conditions was meticulously undertaken. The findings presented herein contribute not only to advancing our fundamental understanding of electrochemical processes but also hold promise for the development of novel electrochemical methodologies with broader applicability in synthetic chemistry and materials science. 2025 Elsevier Ltd
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Copper-salophen complex; Electro-organic synthesis; Electrochemical coupling; Phenazine; Transition-metal
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Elsevier Ltd
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ISSN: 134686; CODEN: ELCAA
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English
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Article
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online
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Faculty Publications
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Chatterjee, Soham; Gupta, Ritwika Das; Latifi, Shpetim; Behera, Tapan Kumar
Title
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Harnessing Insights for Optimizing Healthcare: Disease Prediction and Beyond
Date
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01-01-2025
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Lecture Notes in Electrical Engineering;Volume;1269;pp.333-343
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<a href="https://doi.org/10.1007/978-981-97-9515-4_25" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-97-9515-4_25</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105003894903?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105003894903?origin=resultslist</a>
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Chatterjee S., Department of Statistics and Data Science, CHRIST Deemed to be University, Bangalore, India; Gupta R.D., Department of Statistics and Data Science, CHRIST Deemed to be University, Bangalore, India; Latifi S., Department of Computer Science, AAB College, Pristina, Kosovo; Behera T.K., Technical Architect, Independent Researcher, Boston, MA, United States
Description
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This study offers a novel method for developing classification approaches for disease prediction. Exploratory analysis and meticulous data preprocessing were conducted to understand the relationships between symptoms and illnesses. The research involved assessing various machine learning models, including the random forest classifier, through cross-validation techniques, resulting in the identification of a high-performing model with an impressive accuracy rate. In addition, this study incorporates data visualization techniques to gain insights into symptomdisease connections. The studys focus on data visualization and optimization strategies in health demonstrates the potential to transform healthcare by providing precise diagnoses and predicting diseases, ultimately improving patient outcomes. This research underscores the efficacy of data-driven techniques and their integration into recommendation and disease prediction systems, emphasizing the significance of data visualization and optimization strategies in health. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
Subject
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Classification; Data analysis; Data visualization; Disease prediction; Healthcare; Machine learning; Optimization strategies
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Springer Science and Business Media Deutschland GmbH
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ISSN: 18761100; ISBN: 978-981979514-7;
Language
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English
Type
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Conference paper
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Conference Papers
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Harnessing Machine Learning for Mental Health: A Study on Classifying Depression-Related Social Media Posts
Subject
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Classification Models; Depression; Mental Health; Social Media Posts
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This study is of particular relevance in the way it identifies depression-related content on social media using a machine learning model to classify posts and comments. This dataset, encompassing around 6500 entries from various platforms including Facebook, was rigorously annotated by four proficient English-speaking undergraduate students together with the final label which is established via majority voting. Data Preprocessing, initial cleaning, normalization and TF-IDF feature creation through vectorization for the output of POS tags. The different machine learning models that were trained and tested are Logistic Regression, Random Forest, SVM (Support Vector Machine), Naive Bayes Gradient Boosting Algorithm K-NN (K nearest Neighbors) AdaBoost Decision Tree. Authors evaluated the models and measured their accuracy, precision score, recall rate (also known as sensitivity) in addition to F1-score. Gradient Boost, Random Forest, and SVM were top performers among which Gradient boosting was found to be an overall best one with almost 98.5%. They show that machine learning model can successfully predict the label of social media posts, as a way for accurately identifying depression from text data. This detailed model performance evaluation is useful in understanding what each approach does well and poorly, shedding light into whether they are / would be actually suitable for real-world applications. This study not only developed discriminative classifiers, but also included detailed analysis of their performance which should hopefully guide future work and help in practical implementations for real-time mental health monitoring. Through this work, this study aim to facilitate timely identification of depression-related posts, ultimately supporting mental health awareness and intervention efforts on social media platforms. 2024 IEEE.
Creator
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Varalakshmi C.; Christina S.; Lakshmi M.B.; Parthiban R.; Basha M.S.A.; Sucharitha M.M.
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Proceedings of NKCon 2024 - 3rd Edition of IEEE NKSS's Flagship International Conference: Digital Transformation: Unleashing the Power of Information
Publisher
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Institute of Electrical and Electronics Engineers Inc.
Date
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2024-01-01
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<a href="https://doi.org/10.1109/NKCon62728.2024.10775133" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/NKCon62728.2024.10775133</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215267566&doi=10.1109%2FNKCon62728.2024.10775133&partnerID=40&md5=40454881d15f309d4f58ff19132f489e" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215267566&doi=10.1109%2fNKCon62728.2024.10775133&partnerID=40&md5=40454881d15f309d4f58ff19132f489e</a>
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ISBN: 979-835036456-9
Format
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Online
Language
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English
Type
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Conference paper
Coverage
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Varalakshmi C., Andhra Loyola College, Department of Mba, Andhra Pradesh, Vijayawada, India; Christina S., Christ (Deemed to Be University), Department of Professional Studies, Bengaluru, India; Lakshmi M.B., Christ (Deemed to Be University), Department of Professional Studies, Bengaluru, India; Parthiban R., Christ (Deemed to Be University), Department of Professional Studies, Bengaluru, India; Basha M.S.A., Gitam (Deemed to Be University), Gitam School of Business, Bengaluru, India; Sucharitha M.M., Christ (Deemed to Be University), Department of Professional Studies, Bengaluru, India
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Faculty Publications
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Dkhar, Josaiah Murfeal; John, Tegil; Rai, Pranab
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Harnessing Machine Learning toOptimize Social Media Marketing
Date
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01-01-2026
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Lecture Notes in Networks and Systems;Volume;1497 LNNS;pp.581-598
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<a href="https://doi.org/10.1007/978-981-96-9184-5_43" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-96-9184-5_43</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105028353338?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105028353338?origin=resultslist</a>
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Dkhar J.M., Christ University, Bengaluru, India; John T., Christ University, Bengaluru, India; Rai P., Christ University, Bengaluru, India
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Machine learning (ML) has transformed the way digital advertising is done and analyzed by social media data. This paper explores ML in targeted advertising, including techniques such as supervised learning, neural networks, and NLP. While ML improves campaign precision and consumer engagement, it also presents challenges such as algorithmic bias, data privacy concerns, and computational scalability. This study is a synthesis of existing research and explores real-world applications, providing a critical analysis of MLs capacity to optimize social media advertising. It argues that while ML may provide exceptional possibilities for customization and engagement, its success can only be ensured through appropriate ethical practices, transparency, and innovation in technology. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.
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Digital advertisement; Machine learning; NLP; Social media marketing
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Springer Science and Business Media Deutschland GmbH
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ISSN: 23673370; ISBN: 978-981969183-8;
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English
Type
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Conference paper
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Restricted Access; Hardcopy may be available in the library
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Conference Papers
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Harnessing Medical Databases and Data Mining in the Big Data Era: Advancements and Applications in Healthcare
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Big data; Data mining; Medical database
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In the contemporary period of Big Data, the healthcare industry is witnessing a transformative paradigm shift, propelled by the convergence of medical databases and data mining technology. This research paper delves into the multifaceted application of this synergy, offering a comprehensive overview of its implications and opportunities. With the exponential growth of healthcare data, the utilisation of medical databases serves as the bedrock for data mining techniques, fostering critical advancements in diagnosis, treatment, and patient care. Through this research, we explore the integration of electronic health records, genomic data, and clinical databases, unveiling new dimensions of predictive analytics, patient profiling, and disease monitoring. Moreover, we assess the ethical and privacy concerns entailed in this data-rich landscape, emphasising the need for robust governance and security measures. Our paper encapsulates the evolving landscape of health care, demonstrating the immense potential and the ethical responsibilities accompanying this groundbreaking merger of technology and medicine in the period of Big Data. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
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Ranjith Kumar G.; Nassa V.K.; Manikandan K.; Suribabu P.; Pandian P.M.; Acharjee P.B.
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Smart Innovation, Systems and Technologies, Vol-390, pp. 153-165.
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Springer Science and Business Media Deutschland GmbH
Date
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2024-01-01
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<a href="https://doi.org/10.1007/978-981-97-2716-2_15" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-97-2716-2_15</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201065839&doi=10.1007%2F978-981-97-2716-2_15&partnerID=40&md5=04d6a7d2f8f154bab88d600fac72df21" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201065839&doi=10.1007%2f978-981-97-2716-2_15&partnerID=40&md5=04d6a7d2f8f154bab88d600fac72df21</a>
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Restricted Access
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ISSN: 21903018; ISBN: 978-981972715-5
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Online
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English
Type
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Conference paper
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Ranjith Kumar G., School of Computer Science and Artificial Intelligence, SR University, Telangana, Warangal, India; Nassa V.K., Department of Information Communication Technology (ICT), Tecnia Institute of Advanced Studies(Delhi), Affiliated With Guru Gobind Singh Indraprastha University, Delhi, India; Manikandan K., Department of Pharmaceutical Analysis, SRM College of Pharmacy, SRM Institute of Science and Technology, Kattankulathur, Kanchipuram, SRM Nagar, 603203, India; Suribabu P., Computer Science and Engineering, JNTU Hyderabad, Hyderabad, India; Pandian P.M., Department of Chemistry, Saveetha Engineering College, Chennai, Thandalam, India; Acharjee P.B., Computer Science, CHRIST University Pune Lavasa Campus, Lavasa, India
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The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
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Faculty Publications
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Faculty Publications -Articles
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The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
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Suma, G.R.; T, Apoorva; Pooja, K.R.; Nizam, Aatika; Hegde, Sumanth; R, Harini; Nagaraju, G.
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Harnessing MnMoO4 nanoparticles for eco-conscious effluent degradation and catalytic applications
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01-01-2025
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Nanotechnology for Environmental Engineering;Volume;10;Issue;3;Article No.;71;
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<a href="https://doi.org/10.1007/s41204-025-00466-0" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s41204-025-00466-0</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105013843716?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105013843716?origin=resultslist</a>
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Suma G.R., Siddaganga Institute of Technology, Tumakuru, India; T A., Siddaganga Institute of Technology, Tumakuru, India; Pooja K.R., Rani Channamma University, Belagavi, India; Nizam A., CHRIST (Deemed to be University), Bangalore, India; Hegde S., CHRIST (Deemed to be University), Bangalore, India; R H., Siddaganga Institute of Technology, Tumakuru, India; Nagaraju G., Siddaganga Institute of Technology, Tumakuru, India
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The increasing need for green technology solutions to reduce water pollution and enhance sustainable catalysis has prompted the research for efficient photocatalysts. In this research, a green synthesis method was adopted to synthesize MnMoO4 NPs using solution combustion route followed by calcination. Synthesized MnMoO4 showed superior photocatalytic performance under visible light, with 91% degradation of Rose Bengal dye in aqueous medium indicates its potentiality for wastewater treatment. The material also showed catalytic efficiency in the coupling reaction of aniline and dimedone as model substrates for the synthesis of ?-enaminone derivatives, displaying its usability in organic catalysis. The work highlights the dual functional ability of MnMoO4 both an organic catalyst and a photo-catalyst, providing a green path for synthetic and environmental applications. The dual functionality combined with green fabrication process exemplifies the novelty and applicability of this article. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.
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Green synthesis; Organic catalysis; Photocatalysis; Recyclability; Rose Bengal; ?-enaminones
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Springer Science and Business Media Deutschland GmbH
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ISSN: 23656379;
Language
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English
Type
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Article
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Restricted Access; Hardcopy may be available in the library
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online