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A multi-preference integrated algorithm for deep learning based recommender framework
Nowadays, the online recommender systems based collaborative filtering methods are widely employed to model long term user preferences (LTUP). The deep learning methods, like recurrent neural networks (RNN) have the potential to model short-term user preferences (STUP). There is no dynamic integration of these two models in the existing recommender systems. Therefore, in this article, a multi-preference integrated algorithm (MPIA) for deep learning based recommender framework (DLRF) is proposed to perform the dynamic integration of these two models. Moreover, the MPIA addresses improper data and to improve the performance for creating recommendations. This algorithm is depending on an enhanced long short term memory (LSTM) with additional controllers to consider relative information. Here, experiments are carried out by Amazon benchmark datasets, then obtained outcomes are compared with other existing recommender systems. From the comparison, the experimental outcomes show that the proposed MPIA outperforms existing systems under performance metrics, like area under curve, F1-score. Consequently, the MPIA can be integrated with real time recommender systems. 2022 John Wiley & Sons, Ltd. -
Enhancing Mobile DeFi Transactions Through Blockchain Adoption: A Pythagorean Fuzzy AHP Study
Blockchain technology has emerged as a pivotal enabler for innovation in mobile decentralized finance (DeFi) ecosystems. This study ememploys the Pythagorean Fuzzy Analytic Hierarchy Process (PF-AHP) to identify and rank critical enablers driving blockchain adoption for enhancing mobile DeFi transactions. A structured three-stage methodology evaluates twenty-four sub-criteria across operational, managerial, and strategic dimensions. Results emphasize managerially focused factorssuch as reduced foreign exchange (FX) transfer costs and open-source adaptabilityas the most critical enablers, followed by operational drivers like transparency. Sensitivity analysis confirmed the ro-robustness of these findings. The results offer actionable insights for fintech practitioners, digital strategists, and policymakers seeking to optimize blockchain-based mobile financial platforms. By contributing to improved financial inclusion, operational efficiency, and regulatory alignment, the study supports broader welfare enhancement in the digital economy. The proposed PF-AHP framework provides an empirical decision-making tool to guide innovation and strategic planning in financial technology services. Yogesh Kumar Jain et al. -
Reinforcement Learning-Driven Innovation Clusters: Strategic Planning for Sustainable Corporate Growth
This paper explores the role of reinforcement learning (RL) in optimizing innovation clusters to foster sustainable corporate growth. We go on to establish how RL allows organizations to optimize core performance metrics (innovation output, profit growth, sustainability impact and resource allocation efficiency), and show in dynamic datasets how a network of simulated strategic decisions were made in an innovation ecosystem. Moreover, it highlights the ability of RL to adapt to ever changing industries and implement long term strategic plans besides traditional strategic practices. The results demonstrate that RL-based methods contribute to unleashing innovation and profitabilising the companies, but also to more sustainable operations, bringing into proportion the growth and social responsibility. These results demonstrate RL as an implication tool with a strong future for optimizing corporate strategies that serves as an incentive for further innovation, translating into long-term viability and success. 2025 IEEE. -
Enhancing Stock Market Price Prediction with Advanced Machine Learning Techniques: A Comparative Study
The non-linearity and intrinsic volatility of financial markets make accurate stock price prediction an important but challenging undertaking. This research proposes a Gated Recurrent Unit (GRU)-based model to forecast the stock prices of Tata Consultancy Services (TCS) using 18 years of historical data sourced from Yahoo Finance, comprising features such as Date, Open, High, Low, Close, Adjusted Close, and Volume. The methodology includes data preprocessing steps such as feature selection using Recursive Feature Elimination (RFE), normalization with standard scaling, and data splitting into 70% training and 30% testing sets. The proposed GRU model was evaluated and benchmarked against existing models including Long Short-Term Memory (LSTM), Linear Regression (LR), and Decision Tree (DT), using performance metrics such as Root Mean Squared Error (RMSE) and R2 score. Experimental outcomes revealed that the GRU model achieved the best performance with an RMSE of 0.045, outperforming LSTM (38.19), LR (8.66), and DT (5.22). The study's findings have important implications for algorithmic trading and well-informed investment choices, since the GRU model effectively captures temporal trends in stock data while minimizing prediction mistakes. 2025 IEEE. -
Leveraging AI and Machine Learning for Healthcare Accessibility: Enhancing Clinical Decision Support Systems in Rural Africa
Healthcare in rural Africa is hindered by resource scarcity, limited infrastructure, and a shortage of trained professionals, contributing to high mortality and morbidity rates. This study examines the transformative potential of artificial intelligence (AI) and machine learning (ML) in clinical decision support systems (CDSS) to address these challenges. Focusing on diseases prevalent in the region, such as malaria, HIV/AIDS, and noncommunicable illnesses like diabetes, the research develops and evaluates AI-enhanced CDSS to improve diagnostic accuracy, treatment planning, and healthcare accessibility. This research contributes a framework for deploying AI-driven CDSS in resource-limited settings, with implications for enhancing global health outcomes. 2026 selection and editorial matter, Wasswa Shafik, Adel Ben Youssef, Chithirai Pon Selvan and Pushan Kumar Dutta; individual chapters, the contributors. -
Scaling the bars: The relationship between women entrepreneur well-being and work-life balance
This chapter aims to focus on women entrepreneurs, who sometimes confront the double constraints of managing both company and personal duties. This study examines the particular difficulties faced by female entrepreneurs in striking a sustainable balance, emphasising the absence of support networks like accessible childcare as well as gender stereotypes and cultural expectations. The study assesses how their productivity, well-being, and company performance are affected by a poor work-life balance. It also looks into the tactics used by female business owners to overcome these obstacles, such delegation, selfcare, and time management. In order to promote a more inclusive entrepreneurial ecosystem, the chapter also suggests legislative initiatives, such as flexible work schedules and improved support networks. 2025, IGI Global Scientific Publishing. -
Decoding Cognitive Control and Cognitive Flexibility as Concomitants for Experiential Avoidance in Social Anxiety
Background and objectives: Avoidance is regarded as a central hallmark of social anxiety. Experiential avoidance is perilous for social anxiety, specifically among university students (young adults). Additionally, cognitive control and cognitive flexibility are crucial components of executive functions for a fulfilling and healthy lifestyle. The current research is a modest attempt to understand how cognitive flexibility and cognitive control affect the emergence of experiential avoidance in social anxiety in young adults. Methods: Using an ex-post facto design, the Social Phobia Inventory was employed to screen university students with social anxiety based on which one hundred and ninety-five were identified. Thereafter, participants completed the standardized measures on experiential avoidance, cognitive control and cognitive flexibility. Results: A stepwise multiple regression analysis was computed wherein the cognitive control predicts an amount of 5% of variance towards experiential avoidance, whereas a 10% of additional variance has been contributed by cognitive flexibility. Interpretation and Conclusions: The statistical outcome indicated that cognitive control is positively associated with experiential avoidance which is a negative correlate to cognitive flexibility among university students. Both also emerged as significant predictors of experiential avoidance and add a cumulative variance of 15% towards the same. This conclusion supports the need for improved and efficient management techniques in counseling and clinical settings. The Author(s) 2024 -
Developing mathematical models to analyze economic growth patterns in emerging market dynamics
A key factor in determining national development and directing successful market strategies is economic growth. Making better judgements in developing countries is facilitated for investors and policymakers by having a better understanding of the main drivers of growth. The purpose of this paper is to use mathematical models to explain how economic growth patterns vary among the major growing nations. It examines the effects of inflation, foreign investment, trade, and current account balances on the GDP growth of five major economies India, China, Russia, Brazil, and South Africa between the year 2005 to 2025. The study presents how these variables connect to growth and vary among nations using techniques like logistic regression, linear regression, and ANOVA. TARU PUBLICATIONS. -
Climate Change, Risk Management, and ESG: An Indian Perspective
Abstract Mr. Kofi Annan, the Secretary General of the United Nations Organization remarked that the world is reaching the tipping point beyond which climate change may become irreversible. If this happens, we risk denying present and future genera-tions the right to a healthy and sustainable planet that the whole of humanity stands to lose (RBI, Reserve Bank of India Publication, 2022). Climate change has negatively impacted humanity. It has become a focal point of discussion amongst researchers, academicians, and policymakers alike. It has become imperative for companies to assess and mitigate climate risks as a part of the sustainability journey. Many investors and lenders are integrating ESG aspects, including climate risk, into their investment decision-making processes. The Securities Exchange Board of India (SEBI) intro-duced Business Responsibility and Sustainability Reporting (BRSR), which is a comprehensive framework that seeks disclosures regarding the ESG performance of the companies (SEBI, 2021). However, one of the glaring issues is that most of the disclosures are voluntary in nature, and there are no penalties prescribed for non-disclosure by listed companies in India. In this chapter, we delve into risks posed by climate change on businesses and understand the significance of including the aspect of climate change in corporate planning and strategies. Another important aspect that has been discussed in the chapter is how ESG can be used to address the risks, issues, and challenges posed as a result of climate change. Further, a comparative approach has been adopted to understand the ESG policy framework in India and some prominent jurisdictions like the US, the UK, China, and Japan. We are of the view that framing policies related to mandatory ESG reporting for listed companies and compliance with ESG norms will be the deciding factor for the existence, future readiness, and sustainability of Indian businesses. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Climate Change, Risk Management, and ESG: An Indian Perspective
Abstract Mr. Kofi Annan, the Secretary General of the United Nations Organization remarked that the world is reaching the tipping point beyond which climate change may become irreversible. If this happens, we risk denying present and future genera-tions the right to a healthy and sustainable planet that the whole of humanity stands to lose (RBI, Reserve Bank of India Publication, 2022). Climate change has negatively impacted humanity. It has become a focal point of discussion amongst researchers, academicians, and policymakers alike. It has become imperative for companies to assess and mitigate climate risks as a part of the sustainability journey. Many investors and lenders are integrating ESG aspects, including climate risk, into their investment decision-making processes. The Securities Exchange Board of India (SEBI) intro-duced Business Responsibility and Sustainability Reporting (BRSR), which is a comprehensive framework that seeks disclosures regarding the ESG performance of the companies (SEBI, 2021). However, one of the glaring issues is that most of the disclosures are voluntary in nature, and there are no penalties prescribed for non-disclosure by listed companies in India. In this chapter, we delve into risks posed by climate change on businesses and understand the significance of including the aspect of climate change in corporate planning and strategies. Another important aspect that has been discussed in the chapter is how ESG can be used to address the risks, issues, and challenges posed as a result of climate change. Further, a comparative approach has been adopted to understand the ESG policy framework in India and some prominent jurisdictions like the US, the UK, China, and Japan. We are of the view that framing policies related to mandatory ESG reporting for listed companies and compliance with ESG norms will be the deciding factor for the existence, future readiness, and sustainability of Indian businesses. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Exploring Reproductive Autonomy Among Economically Dependent Married Women: A Qualitative Study
This qualitative study explores how economic dependency within a system of patriarchy shapes the experiences of reproductive autonomy among nine married women aged 2050 years (mean age 44.6 years) in India. In-depth interviews were conducted using purposive and snowball sampling. Data were analyzed using Braun and Clarkes reflexive thematic analysis. Eight themes revealed three interconnected layers: structural forces (economic dependency and familial control), negotiated agency (micro-level resistance within patriarchal constraints), and cultural reproduction (culturally embedded gendered norms). Findings connect to feminist standpoints and Marxist feminist theories, demonstrating the need for interventions addressing economic independence within larger structural and cultural transformation. 2026 Society for Menstrual Cycle Research. -
A study on the awareness and use of ambient advertising /
A common question that arises in the minds of people with reference to advertising is: ‘in the near future, would any place be off-limits to advertising?’ Without much thought, a wellknown person would answer: ‘No’. The introduction of Ambient Advertising has increased the possibility of the answer to this question being affirmative. Ambient advertising is a new form of advertising tactic that has recently been introduced in India with a view of promoting and selling products/services, and brands. -
Navigating the Complexities of Indoor Air Quality: Critical Analysis of Key Pollutants and Monitoring Sites
Indoor Air Quality (IAQ) plays a crucial role in human health, as individuals spend a significant portion of their time indoors. Many existing studies overlook the compounded effects of common environmental factors like temperature and humidity, as well as the health risks posed by long-term exposure to indoor pollutants. However, this review tries to explore how modern building materials, and indoor activities impact IAQ, with a focus on key pollutants such as ultrafine particulate matter (PM2.5 and smaller), volatile organic compounds ammonia, formaldehyde, chlorine, and radon. The review emphasizes the need for more research on IAQ, especially in developing regions, heritage settlements, and the need for standardized evaluation approaches. Moreover, there is a need of practical and affordable solutions that integrate advanced sensing technologies, real-time data insights, and easy-to-use systems to enable people to aware and take control of their IAQ. This review highlights the importance of more rigorous research, creative strategies, and strong policy support to address these challenges, particularly for communities in developing regions, crowded spaces, and vulnerable populations. The main motive is to enhance understanding of indoor air pollution and promote the development of healthier, more sustainable indoor environments. The objective is to support SDG-3 Good Health and Well Being, SDG-11 Sustainable Cities and Communities, SDG-13 Climate Action. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. -
The role of digital technologies in open innovation
This chapter explores how digital platforms serve as enablers of open innovation by connecting diverse networks of individuals, companies, and institutions. It examines how platforms like GitHub, Innocentive, and Quirky facilitate collaboration, knowledge exchange, and co-creation between internal and external stakeholders, including startups, big enterprises, independent innovators, and research institutes. The chapter also addresses challenges such as security issues, intellectual property concerns, and management complexities in collaborative processes. It discusses best practices for leveraging digital platforms effectively in open innovation, aiming to foster sustainability, adaptability, and continuous growth in a dynamic market. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Development of a VR-Based Solid Waste Management Awareness Platform Utilizing YOLOv12 and MSCNN
Waste management is not an issue concerning an individual but a collective responsibility. It refers to our environment. Our project, 'Solid Waste Management,' verifies the efficacy of virtual reality, a novel learning modality for the user, acquiring knowledge of waste segregation and the right way of waste disposal simulation through virtual reality. The implication of virtual reality's addition into the educational system was analyzed through the acceptance of the model and the acquisition of knowledge through the task performed by the user. The simulation and the environment of virtual reality are implemented through the use of Spatial Awareness, Haptic Simulation, Hand Tracking using HCI, and Immersive Learning Environment for a genuine simulation experience for the user. The simulation environment and software were developed using the Unity environment creating a gamified world using a 3D environment and the Blender software used for the development of the 3D models. The simulation environment's implementation into the various HMD devices also used the OpenXR plugin. The simulation is further segmented into two parts: interior and exterior waste management. This novel simulation technique will not only enable the acquisition of the most requisite skills of waste segregation but also the acquisition of environment knowledge and the promotion of people towards sustainable practices. 2026 IEEE. -
AI-Driven Consumer Behavior and Decision Making
Artificial Intelligence (AI) has transformed consumer behavior and decision-m aking, impacting purchasing habits, brand relationships, and marketing efforts. This systematic review synthesizes evidence on AI- influenced consumer behavior, analyzing its effects on attitudes, likes, and decision- making. Major areas of study encompass AI- facilitated recommendation systems, personalized engagement marketing, AI in online advertising, and AI- facilitated automation in retail and service sectors. The research presents both the benefits and pitfalls of AI integration, such as better customer experiences, data privacy fears, and information cocoons. AI has revolutionized conventional marketing practices by facilitating hyper-personalization and predictive analyses, engaging customers while incurring ethical issues. Research also highlights the importance of AI in sectors like fashion, entertainment, and business- to- business (B2B) marketing, offering insights into consumer trust and perceptions of privacy. 2026, IGI Global Scientific Publishing. All rights reserved. -
Next-gen cloud intelligence: Cognitive computing for a sustainable digital future
Cognitive cloud computing is an innovative paradigm that links intelligent systems with cloud infrastructure having distributed and scalable capabilities. Next-generation cloud intelligence is explored with regard to the foundational principles, enabling technologies, and emerging applications. It focuses on cognition cloud systems to maximize energy efficiency, improve predictive analytics, and encourage human-centric computing for various domains such as education, healthcare, finance, and environmental management, including sustainability. Some of the enabler technologies for AI are natural language processing, computer vision, and speech recognition, and the advancement of AI integration, neuromorphic computing, and quantum-enhanced models. The coming of bloc, edge, and the cognitive security mechanisms make it the basis for an invulnerable, transparent, and context-aware system. The chapter also explores green data centers, energy-efficient algorithms, and circular economy principles. The ethical development of cognitive cloud systems is critically analyzed, and data privacy, algorithmic bias, explainability, and regulatory frameworks are considered as challenges for their ethical development. In general, the contribution of this work is to provide a complete framework for the analysis of the impact that cognitive computing can have to make over cloud-based ecosystems as intelligent, adaptable, and eco-friendly platforms through the means of digital infrastructure and AI-driven services. 2026 selection and editorial matter, Jossy George, Kamal Upreti, Ramesh Chandra Poonia, Ankit Gautam, and Danish Nadeem; individual chapters, the contributors. -
Data-driven education: Leveraging big data, AI, and machine learning for smarter learning environments
Big Data, artificial intelligence (AI), and machine learning are transforming education with self-paced learning, precise insights, and automated decisions. The effects these technologies have on education are transformative, especially when it comes to improving student achievement, advancing administrative operations, and personalizing the learning experience, as stated in this chapter. Big Data collects and analyzes immense volumes of data, while AI powers automation, makes predictions, automates evaluations, and enables the possibility of adaptive learning. Chatbots, recommendation engines, and tutoring systems enhance student-focused digital education. Still, integrating these technologies comes with challenges such as privacy and ethical issues, algorithm discrimination, and data security concerns. Some of the new trends are explainable AI (XAI) for ethical decision-making, blockchain and federated learning for privacy-preserving analytic systems, and verifiable credentials. In addition, XR, AI-based virtual laboratories, and neurosymbolic AI will have great consequences on the future learning environment. AI in education offers scalability and inclusivity but demands ethical regulation, governance, and resource management. This chapter recommends sustained effort in research, policy changes, and ethical integration of AI for the best possible use thereof. The education sector, by incorporating human-centered AI approaches, can create a just, sustainable future of learning that is accessible to all students around the world. 2026 Elsevier Inc. All rights reserved. -
The convergence of IoT, ML, and big data in self-service innovation
Internet of Things, Machine Learning, and Big Data analytics have been bringing a transformation to self-service technologies with automation, personalization, and operations efficiencies. IoT captures the data in real-time by linked sensors; ML will try to find the patterns, providing the output; and Big Data would analyze large datasets to deliver actionable insights. All three together bring smarter and adaptive systems in retail, health care, and rural service industries. The applications include inventory management, personalized healthcare forecasting, and community kiosks. While these innovations are achieved, interoperability, scalability, and high implementation costs in rural areas are some of the persistent challenges. This can be addressed by taking advantage of edge computing, cloud solutions, and the collaboration of stakeholders. Further innovations like 5G and federated learning will shape self-service technologies in the future to deliver efficient, inclusive, and innovative solutions. 2026, IGI Global Scientific Publishing. -
Artificial Intelligence and Machine Learning in Advanced Materials Science: A New Era of Innovation
The increase of artificial intelligence (AI) and machine learning (ML) in the discovery, design, and optimization of new materials is causing a rapid acceleration of the field of materials science. This chapter addresses the principles for how artificial intelligence and machine learning can enable the predictive modeling, high-throughput screening, and smartproduction ofpolymers, alloys, ceramics, and nanomaterials. Emphasized are some of the techniques, such as hybrid approaches to artificial intelligence and physics, generative models, and reinforcement learning. Some important problems in the chapter are spoken about: lack of standards, incoherence of data, and unfeasibility of explaining the models. Along with that, this also attempts to investigate how the advantages of upcoming malware such as quantum computing, edge synthetic intelligence, and open information facilities can reinforce the research and innovation in the forthcoming age of materials. 2026 by IGI Global Scientific Publishing. All rights reserved.