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Using Ensemble Model to Reduce Downtime in Manufacturing Industry: An Advanced Diagnostic Framework for Early Failure Detection
The fourth industrial resolution marks a significant shift that uses emerging technologies such as intelligent automation, extensive machine-to-machine communication, and the internet of things (IoT) to modernize conventional manufacturing and industrial methods. The examination of vast data gathered in modern industrial facilities has not only greatly leveraged artificial intelligence (AI) tools but has also driven the development of innovative technologies. In this context, a novel framework for predictive maintenance in the production sector is introduced in this research, which depends on an ensemble model. First, a set of input features are collected from sensors. Then, data normalization technique is applied to standardize and prepare data for further analysis. These normalized input features are then used to train an ensemble classifier. In the ensemble model, multilayer perceptron (MLP), K-nearest neighbors (KNN), and support vector machine (SVM) are serve as base classifiers. Efficacy of the designed framework is validated using predictive maintenance dataset. Results demonstrated that the proposed ensemble model exhibited improved accuracy compared to individual base classifiers. The results further demonstrated that the implemented model had superior efficiency compared to the other benchmark models. 2025 selection and editorial matter, Amit Kumar Tyagi, Shrikant Tiwari, and Gulshan Soni; individual chapters, the contributors. -
Automated neurological brain disease detection in magnetic resonance imaging using deep learning approaches
A neurological type of brain disease called multiple sclerosis (MS) impairs how well the nervous system is able to function efficiently and causes people to experience visual, sensory, and problems with movement. Multiple methods of detection have been proposed so far for diagnosing MS; among them, magnetic resonance imaging (MRI) has drawn a lot of interest from healthcare providers. The ability to quickly diagnose lesions related to MS depends on a fundamental understanding of the anatomy and workings of the brain that MRI technology provides doctors. Using an MRI for diagnosing MS is tedious, time-consuming, and prone to human error. In the present investigation, lesion activity involves preprocessing and segmentation of the MS images from two time points using deep learning approaches. 2024 by IGI Global. All rights reserved. -
Unobtrusive Engagement Detection through Semantic Pose Estimation and Lightweight ResNet for an Online Class Environment
Analysing student engagement in a class through unobtrusive methods enhances the learning and teaching experience. During these pandemic times, where the classes are conducted online, it is imperative to efficiently estimate the engagement levels of individual students. Helping teachers to annotate and understand the significant learning rate of the students is critical and vital. To facilitate the analysis of estimating the engagement levels among students, this paper proposes a dual channel model to precisely detect the attention level of individual students in a classroom. Considering the possible inaccuracy of emotion recognition, a dual channel is configured with a Lightweight ResNet model for macro-level attention estimation and a 3d pose estimation using Euler angles for Pitch, yaw and roll that is trained, validated and tested on the Daisee database. The Emotional detection extracts the context of Engaged, frustrated, confused and disgust as higher levels of classroom attention cognition while the facial pose coordinates provide the real-time movement of the faces in the video to provide a series of engaged and disengaged coordinates. The Lightweight ResNet Model achieves a 95.5% accuracy and the Pose estimation test is able to distinguish the test videos at 92% as Engaged and Bored on the Daisee Dataset. The Overall Accuracies using the Dual channel was curated to 87%. 2023 Scrivener Publishing LLC. -
Security and privacy aspects in intelligence systems through blockchain and explainable AI
Explainable AI (XAI) is a method of creating artificial intelligence (AI) systems that are transparent and understandable to humans. By allowing people to understand how the system arrived at its conclusions or suggestions, XAI systems strive to make AI more accountable, trustworthy, and ethical. Responsibility, trust, ethics, regulation, and innovation are some of the societal ramifications of XAI. By making AI systems more transparent, XAI fosters accountability. This means that consumers will be able to understand how the system made its decisions and hold it accountable if something goes wrong. By making the decision-making process more transparent, XAI fosters trust between people and AI systems. This boosts user trust in the system and encourages wider adoption of AI technologies. It also contributes to the ethical design of AI systems by making the decision-making process public in order to uncover and mitigate biases and other ethical issues that may occur in AI systems. It aids regulators and policymakers in understanding and regulating AI systems. XAI gives insight into how AI systems operate, which can assist regulators in developing laws that promote ethical and responsible AI use. Because XAI can help developers better and innovate new systems by making it easier for them to design new AI systems and by providing insights into how AI systems work. The proposed chapter will focus on important aspects of algorithmic bias and changing notions of privacy in XAI, which will necessitate the need for AI systems that can adapt accountability, trust, ethics, and compliance with regulations, as well as produce better innovation that can benefit humanity. More openness, greater control over personal data, new types of data privacy, and newer privacy networks are all required. To address algorithmic bias in XAI, it is critical to build the system so that it is aware of the possibility of bias and actively mitigates it. This can involve employing diverse and representative data, inspecting the system for unwanted features, offering detailed explanations, and incorporating a wide range of stakeholders in the system's development and deployment. The envisaged report provides a framework that combines XAI and blockchain to provide a secure and transparent way to store and track the provenance of data used by XAI systems, validate the performance of AI models stored on the blockchain on decentralized systems so that the models are stored and executed on a distributed network of nodes rather than a centralized server, and create a token-based economy that encourages data sharing and AI development. Tokens can be used to compensate individuals and organizations who contribute data or algorithms to the blockchain or who employ AI models stored on the blockchain. Overall, the combination of XAI and blockchain can lead to more trustworthy, transparent, and decentralized AI systems. This approach can have a significant impact on various industries such as finance, healthcare, and supply chain management by increasing efficiency, reducing costs, and improving data privacy and security. 2024 Elsevier Inc. All rights reserved. -
Quantum approaches to sustainable resource management in supply chains
Quantum computing leverages the principles of quantum mechanics to process information in ways that classical computers cannot. This capability is particularly advantageous for solving complex optimization problems that are common in supply chain management. Quantum algorithms, such as the quantum approximate optimization algorithm (QAOA) and quantum annealing, have shown promise in efficiently solving these problems by exploring numerous potential solutions simultaneously and identifying optimal strategies. The purpose of this chapter is to investigate the rapidly developing topic of quantum computing and its potential applications in managing sustainable resources within supply chains. Traditional resource allocation methods often struggle to maximize efficiency while minimizing environmental impact. However, new developments in quantum computing have opened up potentially fruitful pathways for addressing these issues. This study aims to explore how quantum computing can revolutionize through an examination of quantum algorithms, optimization approaches, and case studies. 2024 by IGI Global. All rights reserved. -
The Evolution of Forecasting Techniques: Traditional Versus Machine Learning Methods
Forecasting is used effectively and efficiently to support decision-making for the future. Over time, several methods have been created to conduct forecasting. Finding a forecasting technique with the ability to provide the best estimate of the system being modeled has always been a challenge. The selection and comparison criteria for forecasting methodologies can be organized in a variety of ways. Accurate forecasting has a great demand for various fields like weather prediction, economic condition, business forecasting, demand and supply forecasts and many more. When deciding whether to utilize a certain model to predict future events, accuracy is very important. In every field, machine learning (ML) algorithms are being used to forecast future events. These algorithms can handle more complex data and make predictions that are more accurate. Based on the least values of forecasting errors, forecasters create a model to determine the best strategy for prediction. For centuries, forecasting has been used to assist individuals in making future-related decisions. In the past, forecasts were based on intuition and experience, but as technology has advanced, so have forecasting methods. Currently, advanced ML models and methods for data analysis are used to provide forecasts. To forecast the future, these models incorporate a range of inputs, including historical data, present trends, and economic indicators. Forecasting is a vital tool for businesses to employ when making future plans. It is used in a wide range of industries, from finance to weather prediction. 2024 Sachi Nandan Mohanty, Preethi Nanjundan and Tejaswini Kar. -
Public Policy, Policy Research, and School Counseling in India
This chapter discusses the development of school counseling in India and examines public policy and policy research that influence the practice of school counseling. The chapter traces the history of school counseling in India followed by an examination of the contribution of several public policies that has implications for the professional practice of school counseling in India from post independent India. Public policies and programs from the sectors of education, health and mental health, family welfare, and department of children and women are evaluated for their implications for school-based counseling services. The chapter also examines the existing policy research base. Research related to school mental health and systematic reviews on child and adolescent mental health are reviewed and their implications for school counseling examined. The chapter concludes by discussing the policy gaps and highlighting specific recommendations for the practice of school-based counseling in India. The authors suggest several recommendations including the identification of education and health policies that can be achieved by having counselors in schools, an evaluation of existing policies and programs to determine the current level of implementation, and development of school counseling competencies and high-quality training models to build competencies in school counseling. Springer International Publishing AG 2017. -
Managing stress, traumatic experiences, life skill training, and leading with a purpose
This chapter examines the obstacles encountered by minority women pursuing leadership positions in K-12 education, focusing on the interconnectedness of gender and ethnicity. This work explores the intricate terrain of stress and trauma, examining particular obstacles such as marginalization and microaggressions, thereby emphasizing the necessity for specialized assistance. The chapter delivers valuable insights regarding stress management and purposeful leadership, including Mindfulness, life skill training, tension reduction, professional assistance, mentorship, and peer support. The text highlights the significance of effective stress management in cultivating a supportive educational environment. The text culminates in an appeal for empowerment, emphasizing the capacity of obstacles to be catalysts for change in the direction of inclusivity and diversity for minority women leaders who strive to shape a diverse and progressive future. 2024, IGI Global. All rights reserved. -
Life skills for personal well-being
This investigation examines the integrative and transformative qualities of service learning in higher education, specifically focusing on its contribution to developing personal well-being-related life skills. By integrating significant community service with academic goals, service learning provides a comprehensive educational experience. Its defined components, theoretical framework, and real-world applications underscore the subject's significance. Student experiences and case studies illustrate its influence on empathy, resiliency, and communication. Strategic implementation approaches serve as a compass for purposeful undertakings. Service learning connects theoretical concepts with practical application, cultivating globally literate and socially conscious individuals who can navigate the everchanging realm of higher education. 2024, IGI Global. -
Empowering indigenous adolescents: Life skills development and transformative student engagement through service-learning
This chapter synthesizes results from examining service-learning initiatives tailored for Indigenous adolescents. The authors emphasize customized educational approaches, community collaboration, and cultural sensitivity. The Paniya Tribes case study in Wayanad illustrates efforts of this kind that seek to address historical inequities and enhance students' academic performance, life skills, and engagement. The enduring impact extends beyond academics, empowering young people to take on leadership roles. Cultural sensitivity and the responsible application of technology are two factors that can significantly impact Indigenous education's trajectory in the future. Implementing suggested strategies and optimal methods advances inclusive and culturally attuned education, thereby preserving Indigenous cultures and fostering sustainable development. 2024, IGI Global. All rights reserved. -
Microfinance Sector and the Supportive Role of Regulator in its Transformation: A Case Study from India
Microfinance is a proven business model to deliver financial services to unbanked. In the beginning years of microfinance, Non-Governmental Organizations (NGOs) were engaged in microfinance initiative and used to raise capital through grants for their microfinance program, similar to other grant-based development initiatives. To become self-sustainable financial institutions, NGOs started to transform their microfinance initiatives to a for-profit legal entity. Microfinance experienced commercialization in the process of transformation which neglected the basics of microfinance, especially in protecting the interest of clients. Supportive role of regulator transformed the Indian microfinance sectors and formed sustainable financial institutions. The successful story of Reserve Bank of Indias (RBI) intervention in shaping Indian microfinance sector counters the argument of free market principle in fixing the interest rate and healthy regulation for microfinance institutions. Supportive role of Reserve Bank of India created win-win situation for both microfinance borrowers, microfinance institutions and other stakeholders for the long-term sustainability. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021. -
Bridging the Digital Chasm: A Comprehensive Analysis of the Digital Divide in Shaping Healthcare Professionals
Industry 5.0 has ushered in a transformative era for the healthcare industry, propelling it towards a digitally empowered ecosystem. This paradigm shift underscores the indispensability of integrating advanced digital technologies into healthcare, not merely as an option but as a crucial necessity. This research delves into the profound impact of Industry 5.0 on healthcare, emphasizing the intersection of digital technologies, patient-centric care, and sustainable practices. Central to the investigation is the digital divide, which manifests as a catalytic intrusion into the healthcare sector's digital landscape. Regardless of demographic considerations among healthcare providers, the existing digital divide manifests in varying levels of access, skill, and offline outcomes and benefits. Our study meticulously explores the intricate dynamics of the digital divide within healthcare professionals, highlighting its influence on micro-level patient experience. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
The Women Leadership: A Catalytic Role of Digital Divide Through Digital Ecosystem
The digitalization of the macro environment of an organization and digital upskilling and digital capital formation in the micro level of human capital paves women an opportunity to ladder up in the organization in various job roles leading to women leadership. The sociodemographic, psychological, socioeconomic, and cultural factors to the digital divide predominantly determine digital capital formation. Every attempt of women to surpass the digital divide obstacle to digital capital formation enables women capital to leadership characteristics. The study proposes a conceptual framework by extricating the past scholarly works on digital divide, digital capital, technology leadership, and women leadership. The preferences and choices of women leading to leadership skills through technology by encapsulating digital capital formation are meritorious in the research inquiry. The individual factors and organization factors are taken to the moderating variables in the association of digital capital to the women leadership. The study finds the need of ICT and digital upskilling among the women professionals in industry and catalytic role of digital capital formation by surpassing the digital divide. The empirical study on the concept formulation is highly recommendable for the future study. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
EdTech tools for sustainable practices: A green revolution in education
The rapid advancement of Education Technology (EdTech) offers promising opportunities for educational institutions to integrate sustainable business practices into their operations and curriculum. The integration of EdTech into sustainability education has emerged as a powerful tool to promote environmental awareness, foster sustainable behavior, and address the pressing challenges of climate change and resource depletion. This chapter explores the growing significance of EdTech in sustainability education, analyzing its potential to cultivate a generation of environmentally conscious and responsible global citizens. It also aims at identifying and examining the most prominent emerging EdTech tools specifically designed to promote sustainability in educational settings. Furthermore, it aims to comprehend the institutional elements that have successfully incorporated and expanded the utilization of EdTech tools to promote enduring business practices. Additionally, the chapter addresses the challenges and obstacles faced by educational institutions in adopting and implementing these technologies and propose strategies to overcome these barriers. 2024 Allam Hamdan. All rights reserved. -
Redefining Organizational Sustainability Through Revamping Digital Capital
[No abstract available] -
Impact of 3D printed components and ventilators on COVID-19
The disease caused by a virus known as the novel Coronavirus, also known as "COVID-19" by the public, was classified as a major epidemic by the World Health Organisation in 2019. Each country across the globe is affected by COVID-19. While writing this, over 150 million people were affected by the fast-spreading deadly pandemic, and over 3.5 million deaths due to COVID-19 were reported worldwide as per WHO's official COVID-19 dash panel-https://covid19.who.int/Economy and social life of no territory on earth was left unaffected by the COVID-19. Now vaccines are ready, it may take a reasonable amount of time to complete the vaccination process. One major challenge was the need for more support equipment like Beds, Oxygen Cylinders, and Ventilators. Improvisation in the mass production of many critical components, especially those supporting 3D printing technology, has shown some well-managed results in handling the shortage of many critical components. This chapter examines and describes how 3D printing technologies were used during the dangerous pandemic. It aims to describe many 3D-printed devices like face masks, face shields, various valves, etc. It also makes an effort to point out the dominant drawbacks of additive manufacturing technology in this area and examines the options for a future pandemic. 2023 Bentham Science Publishers. All rights reserved. -
Waste Management: Learning and Challenges from a Case Study of a University Model in India
Christ University (CU) has implemented an integral and sustainable waste-management system for better environmental impacts on its five campuses in India. The university has well established zero-waste campaigns. The waste-management model is introduced at CU campuses with multiple purposes: 1) for a cleaner environment on the campus, 2) to create an educational impact on students on waste management, 3) to initiate a movement towards a zero-waste society in India and 4) to employ people living around its campuses. The Christ University waste-management model is done through three different segments/wings: 1) solid waste management, 2) wet waste management and 3) wastewater management. The amount of waste recycled for each year is measured, and the processes are documented. The model is a replicable, sustainable and socially impactful model for managing waste on university campuses for more significant societal impacts. 2024 CRC Press. -
Developing authentic thought leaders through the DREAMS model of social action
DREAMS is a three-year curriculum-based after-school intervention program for enhancing leadership qualities among the underprivileged and college/university youngsters. It is an innovative model providing a platform for the mentors and the mentees to share their thoughts and knowledge and create a future generation with a growth mindset. The current world is expecting authentic thought leadership among its workforces. This leadership would help the constantly changing world to guide and lead the followers effectively for a better outcome. This study explores the impact of the DREAMS intervention program by Christ University in entrenching authentic thought leadership among its undergraduates. The study employs a qualitative approach to explore the perceptions among Christ University undergraduates about the contributions the DREAMS has made to their leadership development. The study finds evidence that DREAMS initiatives at Christ University have transformed undergraduates into authentic thought leaders. 2024 Nova Science Publishers, Inc. -
Involvement of Social Enterprises in Promoting Sustainable Agricultural Practices: The Case of Uravu and Buffalo Back
Social enterprises are not-for-profit or for-profit organizations that work for the development of the community in different ways and are sustainable through their products or services. One such initiative of social enterprises is supporting and promoting agriculture and agricultural products. This chapter focuses on two social enterprises, Uravu and Buffalo Back, which work with farm products and their role in promoting sustainable agriculture practices. The primary data are collected through personal interviews with top-level managers, and secondary data are collected from websites and other published documents. This study looks at the concept of sustainability in terms of finitude, fragility and fairness. These two case studies explain how social enterprises promote the development of agriculture. The former organization ensures the communitys livelihood through farming support, upgrading local knowledge, technologies, skill development and marketing their commodities. The latter focuses on promoting farmers to focus on sustainable organic farming techniques and selling their products to customers. This study can help future entrepreneurs understand different models they can use to develop the agricultural sector through their social actions. 2024 by World Scientific Publishing Co. Pte. Ltd.