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                <text>The United Nations (UN) Sustainable Development Goals (SDGs) ensure inclusive and equitable quality education for promoting lifelong learning. Inclusive education fosters an environment for access to quality education by addressing diversity and barriers that can cause exclusion. COVID-19 has reimagined Higher Education with new challenges and opportunities for the present and future. Digital divide, gender inequality, addressing specially-abled students, and a non-inclusive learning environment are the major barriers to inclusive education. Inclusive education ensures that no one leaves behind, and higher education institutes can enhance their capacity building to promote inclusivity for the common good. Employability is one of the key concepts in higher education that builds the workforce and contributes to nation-building. With COVID-19, nature of work has seen radical changes; hence, graduate attributes have evolved with the 21st-century skills. The chapter emphasizes the role of inclusive education and reimagining higher education with suggestions to using existing strategies in life-long and futuristic inclusive learning.  The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023, corrected publication 2024.</text>
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                <text>Improving Inclusivity in Higher Education: Addressing the Digital Divide in the COVID Pandemic, pp. 203-216.</text>
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                <text>Biju S., School of Business and Management, Christ University, Bengaluru, India; Pallath V., Medical Education focuses on Faculty Development, Faculty of Medicine, Universiti Malaya (UM), Kuala Lumpur, Malaysia; More B., Manipal Environment and Conservation Students Club, United Arab Emirates; Valsaraj B.P., Department of Community and Mental Health, College of Nursing, Sultan Qaboos University, Muscat, Oman; Ng K.H., International Organization of Medical Physics, Universiti Malaya, Kuala Lumpur, Malaysia</text>
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                <text>Future Innovation in Healthcare by Spatial Computing using ProjectDR</text>
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                <text>Spatial Computation is the next step in the continuing convergence between the digital and physical realms. It is a set of inventions and developments that can better our lives through learning the real world, acknowledging and connecting our connection to, and traveling through various locations in the world. The lack of modern, precise, and effective diagnosis limits the rehabilitation of patients, despite technical advancements in medicines. The capabilities of spatial computing are expanded in a healthcare framework during the care and treatment of the patient. In this article, our purpose is to clarify the function of ProjectDR in the field of healthcare, which enables the display of medical images, such as CT scans and MRI results, directly on the patient's body in a manner that moves as patients do.   2021 IEEE.</text>
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                <text>Proceedings of the 3rd International Conference on Inventive Research in Computing Applications, ICIRCA 2021, pp. 829-833.</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>Sasi A., School of Engineering, Presidency University, Department of Computer Science and Engineering, Karnataka, Bengaluru, India; Ravichandran S.K., School of Engineering and Technology, Christ University, Department of Computer Science and Engineering, Karnataka, Bengaluru, India</text>
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                <text>In the competitive world of contemporary business, the challenge of developing marketing strategies that bridge the gap between traditional and innovative techniques has become more critical than ever. As marketing shifts between physical and digital realms, companies grapple with the central question of how to navigate this evolution successfully. The key lies in data - the linchpin that can unravel vital problems in modern marketing. The need for sustainable and effective marketing strategies permeates all sectors, emphasizing the urgency for businesses to combine traditional methods with innovative approaches, such as harnessing alternative data and leveraging AI-based solutions. Future of Customer Engagement Through Marketing Intelligence emerges as a compelling solution to the pressing challenges faced by businesses in this transformative landscape. It offers a step-by-step roadmap, guiding readers on how market intelligence can utilize data and transform it into actionable insights. By emphasizing the crucial role of data in crafting great marketing strategies, the book advocates for a deep understanding of market-supported content and factual data. It asserts that marketing intelligence, encompassing data collection, analysis, and strategic utilization, is the key to becoming customer-centric, understanding market demands, and gaining a competitive advantage. Designed with a comprehensive and practical approach, the book's objectives align with addressing the emerging trends and challenges in customer engagement driven by marketing intelligence. It caters to a diverse audience, including marketing professionals, data analysts, business leaders, academics, researchers, consultants, technology developers, and policymakers. By delving into various topics, from AI-driven customer experiences to the application of advanced technologies like text mining and blockchain, the book serves as a valuable resource for navigating the evolving landscape of customer engagement and marketing intelligence. Ultimately, it stands as a beacon, illuminating the path toward sustainable and responsible customer engagement strategies in the ever-evolving world of marketing.  2024 by IGI Global. All rights reserved.</text>
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                <text>Future of Customer Engagement Through Marketing Intelligence, pp. 1-286.</text>
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                <text>Sinha M., Christ University, India; Bhandari A., Presidency University, India; Priya S.S., Lal Bahadur Shastri Institute of Management, India; Kabiraj S., He University of Applied Sciences, Finland</text>
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                <text>Future of knowledge management in investment banking: Role of personal intelligent assistants</text>
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                <text>investment banking; knowledge management; machine learning and industrial revolution; Personal intelligent assistants; structural equation modelling</text>
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                <text>Purpose: The studys objective focuses on investigating the involvement of Personal Intelligent Assistants (PIAs) in the Knowledge Management Process (KMP) in Investment Banking Companies leading to Industrial Revolution 5.0 leading to effective Organizational Knowledge Management. Design/Methodology: A Self-administered Survey Questionnaire was circulated to 695 employees of Investment Banking Companies operating in Bangalore, Mumbai, Delhi, Hyderabad, Chennai, and Pune using the Cluster Sampling method. The Covariance-based Structural Equation Modelling (CB-SEM) and Gradient Boosting Regression technique of Machine Learning were used to validate the hypothesis through JASP V.18 Software. Knowledge Creation, Knowledge Sharing, Knowledge Retrieval, Knowledge Application, and Organizational Knowledge Management are the crucial constructs considered in the study. Findings: The results revealed that Knowledge Application is the most influencing factor in effective organizational Knowledge management among the Investment Banks followed by Knowledge Sharing. It also emphasizes that they have a weak Knowledge retrieval process and minimal efforts taken to create knowledge within these banks. Implications: The PIAs can facilitate effective Data Analysis and research in managing vast data eliminating the repeated tasks in portfolio reconciliation and offering personalized recommendations to manage portfolios. It enables in compliance, risk management, client relationship management, real-time monitoring and leveraged decision-making through predictive analysis.  The Author(s) 2024.</text>
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                <text>The increase in the dispatchable amount of renewable energy and rural access to the point is proposed. The fuel is used to generate power and electrical energy for the machine. This causes the electricity to manage the single connection point to analyze the hybrid generations. Improving this hybrid generator of renewable power resources can be enabled for the analysis. Photovoltaic power sources have been introduced for converting the power loads and the dumps. The vehicle energy power management technique and the renewable energy system have been used for the analysis. This study shows how vehicle and renewable energy management can help develop geothermal against hydrothermal vents. Hydropower and vehicles can enable bioethanol for vehicle biodiesel. This study allows for the analysis of hydrothermal and biodiesel. In this study, the power of the energy enables the hybrid system, and the combination of the power generator to access the vehicle is proposed.  2023</text>
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                <text>Computers and Electrical Engineering, Vol-111</text>
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                <text>Kannan N., Department of Electrical Engineering, Faculty of Engineering, Rabigh, King Abdulaziz University, Jeddah, Saudi Arabia; Upreti K., Department of Computer Science, CHRIST (Deemed to be University), Delhi NCR, Ghaziabad, India; Pradhan R., GLA University, Mathura, India; Dhingra M., Department of Mathematics and Statistics, Manipal University Jaipur, Rajasthan, Jaipur, 303007, India; Kalimuthukumar S., Department of Biomedical Engineering, Kalasalingam Academy of Research and Education, India; Mahaveerakannan R., Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Tamil Nadu, Chennai, India; Gayathri R., Department of Computer Science and Engineering, PSNA College of Engineering and Technology, Dindigul, India</text>
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                <text>Nanotechnology for Nucleic Acid Delivery;pp.231-253</text>
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                <text>Singh M., Department of Pharmaceutics, Dr Karigowda College of Pharmacy, Karnataka, Hassan, India; Patil A., Department of Pharmaceutics, KLE College of Pharmacy, Karnataka, Rajajinagar, Bangalore, India; Tomar R.S., Department of Electronics and Computer Engineering, Anand School of Engineering and Technology, Sharda University, Uttar Pradesh, Agra, India; Sharma G.K., Sharda School of Pharmacy, Sharda University, Uttar Pradesh, Agra, India; Lakshmi K., Department of Pharmacy, Chettinad School of Pharmaceutical Sciences, Chettinad Hospital and Research Institute, Chettinad Academy of Research and Education, Tamil Nadu, Kelambakkam, India; Anjali P.K., Department of Economics, CHRIST, Deemed to Be University, Karnataka, Bangalore, India; Aher V.D., Department of Pharmaceutical Medicine, Maharashtra University of Health Sciences, Maharashtra, Nashik, India</text>
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                <text>The convergence of artificial intelligence (AI) and nanotechnology presents exciting prospects for advancing drug delivery systems. This review explores the potential synergies between AI and nanocarrier technology to enhance drug delivery efficiency and therapeutic outcomes. We examine current developments in both fields and propose future directions for integrating AI algorithms with nanocarrier design, optimization, and personalized medicine approaches. AI can play a pivotal role in guiding the rational design of nanocarriers, optimizing drug loading and release kinetics, predicting in vivo behavior, and tailoring treatments to individual patient needs. Challenges such as regulatory hurdles, data privacy concerns, and the need for interdisciplinary collaboration are also discussed. Overall, the integration of AI with nanocarrier technology offers unprecedented opportunities to revolutionize drug delivery and improve patient care in the years to come.  2026 by Apple Academic Press, Inc.</text>
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                <text>The chapter examines mindfulness and immunology to understand how our immune system works with mindfulness practice. Research in this area calculates that mindfulness affects immune markers, including cytokines and natural killer (NK) cell activity, apart from effects shown with inflammation or immunityrelated diseases. The discussion also includes a look at newer trends, including brain imaging and more specific treatments and options provided by digitizing public health. However, the promising research limited by small sample sizes and intervention times persists. This part also advocates for increased rigorous, longer-term, cross-disciplinary work to clarify how mindfulness might influence immune health.  2025 by IGI Global Scientific Publishing. All rights reserved.</text>
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                <text>In recent years, with the rapid advancement of technology and the global shift towards digital education, e-learning has gained significant momentum from education sectors. However, there are still several challenges and areas for improvement in the field of e-learning. This work discusses several future research directions that contribute to the effective implementation and enhancement of e-learning in solving real world problems. Also, various components like pedagogical strategies, technology integration, learner support and engagement, assessment and evaluation, accessibility and inclusivity, professional development for educators, quality assurance and accreditation, and ethical and legal issues are explained towards implementation of e-learning. Hence, this chapter explains the effectiveness, accessibility, and inclusivity of e-learning as providing effective educational opportunities for learners globally.  2024, IGI Global. All rights reserved.</text>
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                <text>Architecture and Technological Advancements of Education 4.0, pp. 75-105.</text>
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                <text>In this paper, a new nature-inspire meta-heuristic algorithm called future search algorithm (FSA) is proposed for the first time to solve the simultaneous optimal allocation of distribution generation (DG) and electric vehicle (EV) fleets considering techno-environmental aspects in the operation and control of radial distribution networks (RDN). By imitating the human behavior in getting fruitful life, the FSA starts arbitrary search, discovers neighborhood best people in different nations and looks at worldwide best individuals to arrive at an ideal solution. A techno-environmental multi-objective function is formulated using real power loss, voltage stability index. The active and reactive power compensation limits and different operational constraints of RDN are considered while minimizing the proposed objective function. Post optimization, the impact of DGs on conventional energy sources is analyzed by evaluating their greenhouse gas emission. The effectiveness of the proposed methodology is presented using different case studies on Indian practical 106-bus agriculture feeder for DGs and 36-bus rural residential feeder for simultaneous allocation of DGs and EV fleets. Also, the superiority of FSA in terms of global optima, convergence characteristics is compared with various other recent heuristic algorithms.  2021, The Author(s).</text>
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                <text>Janamala V., Department of Electrical and Electronics Engineering, Faculty of Engineering, Christ (Deemed To Be University), Bangalore, 560 074, Karnataka, India; Kamal Kumar U., Department of Electrical and Electronics Engineering, Sree Vidyanikethan Engineering College, Tirupati, 517 102, Andhra Pradesh, India; Pandraju T.K.S., Department of Electrical and Electronics Engineering, Dhanekula Institute of Engineering and Technology, Vijayawada, 521 139, Andhra Pradesh, India</text>
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                <text>Future Technology and Labour - Are we Heading Towards a Jobless Future?</text>
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                <text>Technological innovations and the invention of machines powered by Artificial intelligence2have changed the way we work, interact and carry on our everyday lives. Automation wave has revolutionized the manner in which the traditional manufacturing and service-oriented industries are functioning today. The first industrial revolution was triggered with the invention of steam engine and also led to mechanical production. The invention of electricity and assembly lines resulted in the second industrial revolution where mass production became feasible. The third industrial revolution was driven by computer, digital technology and the internet. The future technologies have resulted in the fourth industrial revolution. The new age technological innovations and inventions such as the automated robots; big data and analytics; augmented reality; the cloud; cyber security; additive manufacturing; horizontal and vertical integration; the internet of things are transforming industrial production and labour relations. There is a drastic improvement in the entire chain of production ranging from design up to productivity, the speed and the quality at which the goods are produced. As a result of the new age technologies various concerns are raised especially its impact on the employment. Many labourers are rendered unemployed and redundant due to automation. The question that arises is whether we are approaching a jobless future?? The job market in India is also undergoing a transformation and posing many social, economic, legal and ethical challenges. Job structure is changing and the workers need to equip themselves with new skills to fit into the new jobs that are emerging as a result of technological innovation. The education system in any country plays a pivotal role in the overall development of an economy as it caters to the needs of the trained and skilled manpower. It is vital for the education system in the country to re-orient itself to cater to the needs of the students to fit into the changing paradigm. The focus of the education needs to be on imparting life-skills and to improve the thinking, problem-solving and decision-making ability of the individuals in a society. In the light of the above, it is also important to address and discuss the various changes, issues and challenges that are taking place in the labour market including the impact of these technologies on the working hours, wages, the working environment and the labour relations amongst others.  2019, Department of Law, University of North Bengal. All rights reserved.</text>
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                <text>The human ability to seamlessly integrate information from various sensory channelssight, sound, touchhas long inspired researchers in artificial intelligence. This ability to learn from and reason with multimodal datatext, speech, vision, and moreforms the core of multimodal learning. This abstract delves into the theoretical foundations of multimodal learning, explores its cutting-edge advancements, and critically examines the path toward practical applications in diverse fields. At its heart, multimodal learning seeks to exploit the inherent complementarity between different data modalities. Text, for instance, provides rich semantic meaning, while visual data offers valuable context. Speech captures the nuances of emotion and prosody often absent in text. By learning from these combined modalities, models can achieve a more comprehensive understanding of the world around them. Recent years have witnessed significant progress in multimodal learning architectures. Deep learning approaches, particularly convolutional neural networks and recurrent neural networks, have proven adept at capturing complex relationships within individual modalities. New architectures like multimodal transformers further bridge the gap by allowing models to learn joint representations across different modalities. These advancements pave the way for a paradigm shift in areas like computer vision, natural language processing, and robotics. In computer vision, multimodal learning allows models to not only recognize objects in images but also understand the context and actions depicted. By incorporating textual descriptions or speech narratives alongside visual data, models can achieve better scene understanding, image captioning, and action recognition. This has applications in autonomous vehicles, where understanding traffic signs, pedestrians, and road conditions is crucial, and in video surveillance systems, where interpreting visual cues alongside spoken dialogue improves anomaly detection.  2026 Elsevier Inc. All rights reserved.</text>
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                <text>Sinha, Ashmita; Jha, Babita</text>
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                <text>Future Trends in Social Sustainability in Manufacturing Supply Chains</text>
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                <text>Enhancing Social Sustainability in Manufacturing Supply Chains;pp.163-198</text>
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                <text>Sinha A., Christ University, India; Jha B., Christ University, India</text>
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                <text>The future approach to social sustainability in the manufacturing supply chains is determined by various factors such as changes in consumer trends, changes in laws and regulations and advancement in technology. Consumers will make sure that the social or environmental costs that come with products are mitigated and thus the organizations will be forced to embrace transparency and accountability in their operations. As the trend of more responsible and eco- friendly consumerism filters down, any manufacturer worth its salt will work to guarantee fair labor, wages and working conditions within their supply chains. At the same time, there will be expectations for the introduction of more strict social sustainability norms. Increased demand for supply chain disclosure policies, especially regarding labor and sourcing standards, will be developed by state and non- state actors towards manufacturers. This will lead to increased responsibility and adherence among sectors and more eco-friendly business practices across the world.  2025, IGI Global Scientific Publishing.</text>
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                <text>Metaverse for Sustainable Development: Trends and Applications;pp.37-57</text>
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                <text>Dhatterwal J.S., School of Computer Science &amp;amp; Artificial Intelligence, SR University, Telangana, Warangal, India; Kaswan K.S., School of Computer Science and Engineering, Galgotias University, Greater Noida, India; Sharma V., Department of Computer Science, Christ University, Bengaluru, India; Balusamy B., Shiv Nadar Institute of Eminence, Delhi NCR Campus, Uttar Pradesh, Greater Noida, India</text>
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                <text>The term metaverse is used to describe the interconnected network of technologies such as the Internet of Things (IoT), blockchain, artificial intelligence (AI), and other fields of technology, such as the medical field. Similar to how the Internet of Things and the Metaverse are digital twins, the latter makes extensive use of the former in its simulated office. In the blockchain-based Metaverse, this data serves as a means of tracing the provenance of various pieces of information. Such information is becoming useful in the Metaverse, which is used to train AI. With the help of AI and blockchain technology, Metaverse creates a digital virtual world where people may securely and freely participate in social and economic activities that go beyond the bounds of the actual world. In this article, we will discuss the technology used by the metaverse and the possibilities that exist for the metaverse in the healthcare arena.  2025 Scrivener Publishing LLC.</text>
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                <text>avatar; blockchain; edge computing; IoT; Metaverse; virtual reality</text>
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          <element elementId="39">
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                <text>Srivastava, Mitali; Ghazala, Saibaa</text>
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                <text>Future-Proofing Sustainable Urban Development: Harnessing Fuzzy Logic for Smart Cities</text>
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                <text>Fuzzy Logic in Smart Sustainable Cities;pp.215-257</text>
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                <text>&lt;a href="https://doi.org/10.1201/9781003636724-9" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1201/9781003636724-9&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105004606702?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105004606702?origin=resultslist&lt;/a&gt;</text>
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                <text>Srivastava M., CHRIST (Deemed to be University), Delhi NCR, India; Ghazala S., CHRIST (Deemed to be University), Delhi NCR, India</text>
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                <text>Urban development is the biggest challenge in this era of rapid urbanization. This chapter proposes a new approach to tackle this challenge by incorporating fuzzy logic in smart cities. Fuzzy logic is known for handling uncertainty and vagueness thus it is a way to navigate the complexities of urban planning and governance. Incorporating fuzzy logic in a smart city framework is an opportunity to improve decision-making, optimize resource allocation, and reduce the risks of urban development. 216This chapter explores many facets of fuzzy logic and sustainable urban development in a legal context. It starts by giving an overview of the urbanization and sustainability challenges and sets the stage for the discussion of fuzzy logic as a tool to address these challenges. The concept of smart sustainable cities is explained, including the principles and components that make up them. Fuzzy logic in smart cities is the central theme of this chapter. By explaining the concept of fuzzy logic and its applications in an urban context, the chapter shows how it can manage the uncertainties of the urban environment. It also investigates the legal implications of incorporating fuzzy logic in urban governance structures. Through regulatory frameworks and case studies, the chapter discusses legal issues and challenges of integrating fuzzy logic in decision-making. The chapter also looks into the need for adaptive governance structures to accommodate the dynamic nature of smart sustainable cities. It proposes ways to integrate fuzzy logic in existing legal frameworks and flexibility and adaptability in urban governance. From case studies to best practices, the chapter gives insights into the successful implementation of fuzzy logic in smart sustainable cities, which are useful for policymakers and urban planners. In summary, the chapter shows the potential of fuzzy logic to future-proof sustainable urban development in the legal sector. To promote interdisciplinary discussion and provide practical recommendations, it contributes to the discourse on using fuzzy logic for sustainable urban governance. This chapter is a trigger for new approaches to urbanization and sustainability in a legal context.  2025 Jenny Stanford Publishing Pte. Ltd. All rights reserved.</text>
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                <text>Fuzzy logic; Smart Cities; Sustainable urban development; Urban governance</text>
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                <text>Fuzzy based Controller for Bi-Directional Power Flow Regulation for Integration of Electric Vehicles to PV based DC Micro-Grid</text>
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          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
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              <elementText elementTextId="186556">
                <text>Active power flow control; DER; Fuzzy Logic; G2V; Micro-grid; V2G</text>
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          </element>
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                <text>Utilization of Electric Vehicle as an auxiliary power source to a DC micro-grid for active power regulation is examined here. This paper focus on development of a Fuzzy based controller capable of regulating the bi-directional active power flow between a 10 kW DC Micro-grid and an Electric Vehicle. The system enables to balance the load on grid by performing peak shaving during peak hours and valley filling during off-peak hours. The load curve of Bangalore city for a typical day was taken as the reference and was used to implement the power flow control. The DC grid was designed for a 10 kW PV based micro-grid. The integrated DC micro-grid was simulated on MATLAB/Simulink platform and the obtained characteristics demonstrate that the power flow from grid to vehicle and vehicle to grid during the peak and off-peak periods respectively. The auxiliary battery pack was stressed only to 10.7 % of its 1C-rating leaving scopes for higher level power transmission possible between the systems.  2019 IEEE.</text>
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                <text>Jose C.P.; Haneesh K.M.</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>Jose C.P., Electrical and Electronics Engineering, CHRIST, Deemed to be University, Bangalore, India; Haneesh K.M., Electrical and Electronics Engineering, CHRIST, Deemed to be University, Bangalore, India</text>
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                <text>Bavirthi, Swathi Sowmya; Manikandan, M.; Rajagopal, Manikandan; Leelavathy, S.; Rao, K. Srinivas</text>
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                <text>Fuzzy Computational Intelligence in Personalized Medicine and Diagnosis</text>
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                <text>01-01-2025</text>
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                <text>Fuzzy Information and Engineering;Volume;17;Issue;4;pp.472-483</text>
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                <text>&lt;a href="https://doi.org/10.26599/FIE.2025.9270073" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.26599/FIE.2025.9270073&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105027403258?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105027403258?origin=resultslist&lt;/a&gt;</text>
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                <text>Bavirthi S.S., Chaitanya Bharathi Institute of Technology, IT Dept., Hyderabad, 500075, India; Manikandan M., School of Computing, SRM Institute of Science and Technology, Faculty of Engineering and Technology, Department of Computational Intelligence, Chennai, 603203, India; Rajagopal M., School of Business and Management, Christ university, Bangalore, 560029, India; Leelavathy S., Department of AI&amp;amp;DS, Panimalar engineering college, Chennai, 503200, India; Rao K.S., MLR Institute of Technology, Department of Computer Science and Engineering, Hyderabad, 722003, India</text>
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                <text>The development of fuzzy computational intelligence (FCI) has emerged as an effective method for personalized medicine and diagnosis. FCI effectively handles uncertainty and imprecision in medical data, facilitating patient-specific treatment recommendations. Conventional diagnostic and treatment methods typically rely on fixed threshold-based approaches, which fail to account for individual variations in patient responses, leading to suboptimal treatment outcomes. This study proposes the personalized treatment recommendation using fuzzy logic (PTR-FC) framework for diabetes (DB) patients to address these challenges. The framework integrates patient-specific data such as blood glucose levels, diet, exercise, and medication history into the fuzzy inference system (FIS), supporting personalized treatment recommendations. The treatment plans are dynamically adapted based on individual patient outcomes using linguistic factors and fuzzy rules (FR). The proposed method dynamically adjusts recommendations in real time, potentially enhancing personalized treatment and improving decision-making in DB management. Additionally, it promotes lifestyle modifications while reducing the risk of medication-induced complications. The effectiveness of the proposed method was compared to conventional methods, demonstrating improved treatment accuracy, increased patient adherence, and reduced adverse health risks. The PTR-FC framework offers a more adaptive and effective approach to DB management, ensuring better patient outcomes.  2009 Tsinghua University Press.</text>
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                <text>computational intelligence; diabetes management; fuzzy logic (FL); medical decision support; personalized medicine; treatment optimization</text>
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                <text>Tsinghua University Press</text>
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                <text>ISSN: 16168658;</text>
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                <text>All Open Access; Gold Open Access</text>
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