Exploring Psychology Social Innovation And Advanced Applications Of Machine Learning

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Exploring Psychology Social Innovation And Advanced Applications Of Machine Learning

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Author : Raygoza-L., Maria E.
language : en
Publisher: IGI Global
Release Date : 2025-03-06

Exploring Psychology Social Innovation And Advanced Applications Of Machine Learning written by Raygoza-L., Maria E. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-06 with Computers categories.

Machine learning (ML algorithms can be used to better understand human behavior in its various developmental stages and to assist in addressing psychological issues. Additionally, in the realm of mental health and well-being, algorithms can assist with early detection of disorders and customization of treatments as well as personalize recommendations and suggestions based on user behavior. By focusing on user experience and usability, ML may be used to address challenges faced by private enterprises and social issues. Exploring Psychology, Social Innovation and Advanced Applications of Machine Learning explores the relationships between human psychology and machine learning technology, enabling researchers to delve into areas such as user interface design, ethics in artificial intelligence, and the social impact of algorithms. Furthermore, it promotes interdisciplinary collaboration by bringing together perspectives from different fields, which could stimulate new research and innovative approaches in the field of machine learning. Covering topics such as industrial processes, digital therapy, and machine vision, this book is an excellent resource for psychologists, computer scientists, engineers, healthcare practitioners, educators, business leaders, policymakers, professionals, researchers, scholars, academicians, and more.

Artificial Intelligence And Machine Learning For Enhancing Resilience Concepts Applications And Future Directions

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Author :
language : en
Publisher: Deep Science Publishing
Release Date : 2025-07-01

Artificial Intelligence And Machine Learning For Enhancing Resilience Concepts Applications And Future Directions written by and has been published by Deep Science Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-01 with Computers categories.

As contemporary societies face unprecedented challenges such as mounting mental health issues, environmental crises, and socioeconomic insecurity, the urgency of developing objective, scalable, and dynamic methodologies to study resilience has never been greater. This book arises at the intersection of cutting-edge technology and human insight. It focuses on the possibility for AI and ML to transform resilience assessment, prediction, and interventions across the individual, organizational, and ecological levels. The chapters included in this book represent an organized synthesis of cutting-edge science, pragmatic applications, and prospective potential. With machine learning algorithms to estimate psychological resilience and AI-based models for climate change adaptation and ecosystem management, this book demonstrates the rich innovations that are emerging at the cross-sector of technology and resilience science. Perhaps most importantly, this book does not gloss over the urgent ethical, technical, and regulatory issues that arise when AI is introduced to sensitive topics such as mental health and environmental management. Questions about data privacy, algorithmic bias, model interpretability, and equitable technology deployment are thoroughly investigated, providing lessons learned and suggestions for moving ahead. A significant strength of this work is its global focus. Showcasing work from contributors of various methodologies and regions provides the latest views on new methodologies, strategies for practical implementation, and on what still needs to be invented. This guarantees that the publication engages with the messy socio-cultural and environmental contexts in which these interventions work and that it doesn’t just mirror technological possibilities. For academicians, practitioners, technologists, and policymakers, this book is both a fundamental reference and an outlook resource. It provides: Holistic examination of AI and ML in the context of psychological, organizational, and ecological resilience. In-depth reviews on methodological innovations, such as deep learning, natural language processing, and sensor-based assessments. Unprecedented appraisals of barriers to implementation, with ethical and regulatory considerations. We trust that this book will inspire conversation, fuel innovation, and support a future in which technology supplements, rather than replaces, human ability to adapt, recover, and flourish. We encourage readers to critique the content, to reflect on how AI, ML, and resilience intersect in their particular contexts, and to join us in shaping a future where technological and human resilience evolve together.

Transformative Lean Six Sigma Techniques For The Quality 5 0 Paradigm

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Author : de Sá, José Carlos Vieira
language : en
Publisher: IGI Global
Release Date : 2025-07-30

Transformative Lean Six Sigma Techniques For The Quality 5 0 Paradigm written by de Sá, José Carlos Vieira and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-30 with Business & Economics categories.

In the shift from Industry 4.0 to Industry 5.0, where human-machine collaboration, personalization, and sustainability are prioritized, Lean Six Sigma (LSS) plays a critical role in shaping efficient and adaptive production systems. By integrating emerging technologies like blockchain, internet of things (IoT), artificial intelligence (AI), and autonomous robots, LSS evolves to meet the complex demands of modern industries. This transformation not only enhances operational excellence but also supports smarter decision-making, greater transparency, and reduced waste. As a result, sectors are seeking improvements in customization, worker empowerment, and overall system resilience. The impact is a more sustainable and human-centric industrial future. Transformative Lean Six Sigma Techniques for the Quality 5.0 Paradigm explores the integration of LSS with the emerging framework of Industry 5.0. It additionally emphasizes the importance of adopting sustainable and human-centric approaches within the LSS framework. Covering topics such as autonomous robots, ethical leadership, and sustainability, this book is an excellent resource for industry professionals, process improvement specialists, quality managers, operations leaders, researchers, academicians, and more.

Sustainable Approaches In Spatial Design

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Author : Geçimli, Meryem
language : en
Publisher: IGI Global
Release Date : 2025-06-20

Sustainable Approaches In Spatial Design written by Geçimli, Meryem and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-20 with Architecture categories.

Sustainability attracts the attention of spatial design disciplines and other academics. The spatial design and structural activities of sustainability have three main sections, which are ecological, economic, and socio-cultural sustainability. These sections take into account factors such as the life cycle of people and materials, the influence of different lifestyles, and energy consumption. The insights from sustainability have important implications for housing models that balance flexibility, sustainability, and cultural relevance. Sustainable Approaches in Spatial Design explores the shifting changes in the dynamics of and environmental concerns surrounding the rapid increase in urbanization. It highlights the need for mindful consumption in diverse geographical and socio-economic settings to support global sustainability. Covering topics such as cost-effective sampling, greenhouse gas (GHG), and daylight calculation methods, this book is an excellent resource for architects, urban planners, policymakers, sustainability experts, engineers, economists, sociologists, professionals, researchers, scholars, academicians, and more.

Computer Assisted Experiment Design In Psychology

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Author : St. Clements University Academic Staff - Türkiye
language : en
Publisher: Prof. Dr. Bilal Semih Bozdemir
Release Date :

Computer Assisted Experiment Design In Psychology written by St. Clements University Academic Staff - Türkiye and has been published by Prof. Dr. Bilal Semih Bozdemir this book supported file pdf, txt, epub, kindle and other format this book has been release on with Education categories.

Computer-Assisted Experiment Design in Psychology The Need for Efficient Experiment Design Understanding Experiment Design Challenges Limitations of Traditional Experiment Design Methods Introducing Computer-Assisted Experiment Design Benefits of Computer-Assisted Experiment Design Improved Statistical Power and Precision Enhanced Experimental Control and Validity Reduced Time and Resources for Experiment Execution Optimized Participant Recruitment and Allocation Key Considerations in Computer-Assisted Experiment Design Experimental Variables and Hypotheses Identifying Independent and Dependent Variables Establishing Appropriate Control Conditions Minimizing Confounding Factors Designing Data Collection Protocols Selecting Appropriate Outcome Measures Ensuring Ethical Considerations Leveraging Computational Algorithms in Experiment Design Factorial Designs and Response Surface Methodology Adaptive Designs and Sequential Experimentation Bayesian Optimization and Adaptive Randomization Machine Learning Approaches in Experiment Design Case Studies in Computer-Assisted Experiment Design Improving Clinical Trial Design and Efficiency Enhancing Behavioral Intervention Studies Optimizing User Experience Research Integrating Computer-Assisted Design with Existing Workflows Overcoming Challenges and Limitations Ensuring Reproducibility and Transparency Addressing Regulatory Concerns and Best Practices Ethical Considerations in Automated Experiment Design Training and Upskilling Researchers Collaboration between Researchers and Computer Scientists The Future of Computer-Assisted Experiment Design Emerging Trends and Innovations Integrating with Artificial Intelligence and Machine Learning Enhancing Interdisciplinary Collaboration Expanding Applications beyond Psychology Ensuring Responsible and Equitable Implementation Conclusion: Unlocking the Potential of Computer-Assisted Experiment Design

Deep Reinforcement Learning And Its Industrial Use Cases

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Author : Shubham Mahajan
language : en
Publisher: John Wiley & Sons
Release Date : 2024-10-01

Deep Reinforcement Learning And Its Industrial Use Cases written by Shubham Mahajan and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-01 with Computers categories.

This book serves as a bridge connecting the theoretical foundations of DRL with practical, actionable insights for implementing these technologies in a variety of industrial contexts, making it a valuable resource for professionals and enthusiasts at the forefront of technological innovation. Deep Reinforcement Learning (DRL) represents one of the most dynamic and impactful areas of research and development in the field of artificial intelligence. Bridging the gap between decision-making theory and powerful deep learning models, DRL has evolved from academic curiosity to a cornerstone technology driving innovation across numerous industries. Its core premise—enabling machines to learn optimal actions within complex environments through trial and error—has broad implications, from automating intricate decision processes to optimizing operations that were previously beyond the reach of traditional AI techniques. “Deep Reinforcement Learning and Its Industrial Use Cases: AI for Real-World Applications” is an essential guide for anyone eager to understand the nexus between cutting-edge artificial intelligence techniques and practical industrial applications. This book not only demystifies the complex theory behind deep reinforcement learning (DRL) but also provides a clear roadmap for implementing these advanced algorithms in a variety of industries to solve real-world problems. Through a careful blend of theoretical foundations, practical insights, and diverse case studies, the book offers a comprehensive look into how DRL is revolutionizing fields such as finance, healthcare, manufacturing, and more, by optimizing decisions in dynamic and uncertain environments. This book distills years of research and practical experience into accessible and actionable knowledge. Whether you’re an AI professional seeking to expand your toolkit, a business leader aiming to leverage AI for competitive advantage, or a student or academic researching the latest in AI applications, this book provides valuable insights and guidance. Beyond just exploring the successes of DRL, it critically examines challenges, pitfalls, and ethical considerations, preparing readers to not only implement DRL solutions but to do so responsibly and effectively. Audience The book will be read by researchers, postgraduate students, and industry engineers in machine learning and artificial intelligence, as well as those in business and industry seeking to understand how DRL can be applied to solve complex industry-specific challenges and improve operational efficiency.

Intangibles In The Knowledge Economy

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Author : Eduardo Luis Soares Tomé
language : en
Publisher: Springer Nature
Release Date : 2025-06-30

Intangibles In The Knowledge Economy written by Eduardo Luis Soares Tomé and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-30 with Business & Economics categories.

This book features selected chapters from the proceedings of the Multidisciplinary Conference on Intangibles (TAKE), held in Lisbon, Portugal, in July 2024. The chapters cover a wide range of topics , including human resource development, intellectual capital, knowledge management, logistics, retailing, public policy, innovation and entrepreneurship, business models, competitiveness, and accounting. The book is a valuable resource for researchers, practitioners, and industry experts interested in shaping the future of the knowledge economy.

Ai Applications In Psychology

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Author : DR. DILEEP KUMAR MOHANACHANDRAN
language : en
Publisher: SRJX RESEARCH AND INNOVATION LAB LLP
Release Date : 2025-06-05

Ai Applications In Psychology written by DR. DILEEP KUMAR MOHANACHANDRAN and has been published by SRJX RESEARCH AND INNOVATION LAB LLP this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-05 with Computers categories.

Structure and Organization The book is structured into eleven comprehensive chapters, each addressing a key thematic area where AI intersects with psychology: Chapters 1–3 introduce the foundations: the historical context, the core technologies (AI, machine learning, NLP, etc.), and the significance of AI in research and cognitive modeling. Chapters 4–7 explore domain-specific applications: clinical psychology, behavioral analysis, cognitive assessment, educational psychology, and developmental tracking. Chapter 8 focuses on AI’s role in cultural and social psychology, sentiment analysis, group behavior, and bias detection. Chapter 9 dives deep into neuropsychology and brain-computer interfacing, discussing computational neuroscience and neuroimaging with AI tools. Chapter 10 addresses ethical, philosophical, and societal implications including AI consciousness, privacy, and accountability. Chapter 11 offers real-world case studies and implementations, showcasing successful AI projects and collaborations between psychologists and technologists. Why This Book Now? AI is no longer confined to data science labs or Silicon Valley prototypes. AI-powered chatbots are already assisting in therapy, virtual assistants are supporting cognitive exercises, and brain-computer interfaces are restoring communication in locked-in patients. Yet, as these tools become more widespread, psychologists must not be passive observers. They must become co-creators, ensuring that AI systems are grounded in psychological theory and ethical consideration. The timing of this book reflects a critical inflection point: just as psychology helped shape early cognitive science, it must now guide the ethical evolution of artificial intelligence. By bringing together insights from clinical psychology, behavioral science, cognitive modeling, and AI engineering, we provide readers with a holistic view of how these fields coalesce to enhance mental well-being, research precision, and human understanding. An Interdisciplinary Conversation This book is a product of dialogue—between technology and psychology, data and theory, machine precision and human intuition. It draws from diverse research traditions and emerging practices across psychology, computer science, neuroscience, ethics, and education. Readers will find discussions on how AI is used to analyze therapy transcripts, simulate human learning, predict behavior in organizational settings, and model decision-making under uncertainty. Moreover, the chapters present AI not as a threat, but as a powerful enabler—capable of complementing the psychologist’s insight with data-driven clarity. However, this integration requires psychologists to understand fundamental AI concepts and AI engineers to respect psychological complexity. This is the bridge we aim to build. Human-Centric AI A key theme throughout the book is the vision for human-centric AI—systems designed not just for efficiency, but for empathy, accessibility, and inclusivity. Whether it is through adaptive learning platforms for students with learning disabilities, mental health chatbots for isolated populations, or ethical frameworks for responsible AI deployment, the goal is the same: to develop technologies that serve humanity rather than supplant it. Human-centric AI also implies that users—patients, therapists, researchers, and communities—remain at the center of AI development. Transparent design, cultural sensitivity, explainability, and privacy protection are not optional features; they are fundamental principles that must be embedded in every application. A Vision for the Future As we prepare for a future where AI becomes even more intertwined with human thought and behavior, we must ask vital questions: How do we ensure fairness and inclusivity in AI models? Can AI simulate consciousness or empathy? What happens when therapy is partially or fully automated? How do we train the next generation of AI-psychology practitioners? This book does not pretend to answer all these questions definitively. Rather, it aims to spark informed inquiry, provide foundational knowledge, and inspire a generation of psychologists, technologists, educators, and students to co-create responsible AI solutions. We envision a future where AI can: Predict mental health crises before they occur. Provide personalized and culturally competent therapy. Simulate cognitive and emotional processes for deeper understanding. Enhance early diagnosis of neurodevelopmental disorders. Empower marginalized populations with accessible, stigma-free care.

Handbook Of Organizational Creativity

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Author : Roni Reiter-Palmon
language : en
Publisher: Elsevier
Release Date : 2023-06-22

Handbook Of Organizational Creativity written by Roni Reiter-Palmon and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-22 with Psychology categories.

Handbook of Organizational Creativity: Leadership, Interventions, and Macro Level Issues, Second Edition covers creativity from many perspectives in two unique volumes, including artificial Intelligence work, creativity within specific applied domains (e.g., engineering, science, therapy), and coverage of leadership. The book includes individual, team and organizational level factors and includes organizational interventions to facilitate creativity (such as training). Chapters focus on creative abilities and creative problem-solving processes, along with individual differences such as motivation, affect and personality. New chapters include the neuroscience of creativity, creativity and meaning, morality/ethicality and creativity, and creative self-beliefs. Sections on group level phenomena examine team cognition, team social processes, team diversity, social networks, and multi-team systems and creativity. Final coverages includes different types and approaches to leadership, such as transformational leadership, ambidextrous leadership leader-follower relations, and more. - Focuses on the key need to increase creativity and innovation in organizations - Identifies factors influencing organizational creativity in specific subject domains - Discusses effects of rewards, training, and performance management on creativity - Contains new coverage of virtual teams, creative meetings, and multiteam systems - Presents interventions to improve organizational creativity - Explores use of AI, technology, and design thinking for organizational creativity - This expanded second edition is divided into two volumes. For further information on Individual and Group Level Influences visit https://shop.elsevier.com/books/handbook-of-organizational-creativity/reiter-palmon/978-0-323-91840-4

Introducing Hr Analytics With Machine Learning

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Author : Christopher M. Rosett
language : en
Publisher: Springer Nature
Release Date : 2021-06-14

Introducing Hr Analytics With Machine Learning written by Christopher M. Rosett and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-14 with Psychology categories.

This book directly addresses the explosion of literature about leveraging analytics with employee data and how organizational psychologists and practitioners can harness new information to help guide positive change in the workplace. In order for today’s organizational psychologists to successfully work with their partners they must go beyond behavioral science into the realms of computing and business acumen. Similarly, today’s data scientists must appreciate the unique aspects of behavioral data and the special circumstances which surround HR data and HR systems. Finally, traditional HR professionals must become familiar with research methods, statistics, and data systems in order to collaborate with these new specialized partners and teams. Despite the increasing importance of this diversity of skill, many organizations are still unprepared to build teams with the comprehensive skills necessary to have high performing HR Analytics functions. And importantly, all these considerations are magnified by the introduction and acceleration of machine learning in HR. This book will serve as an introduction to these areas and provide guidance on building the connectivity across domains required to establish well-rounded skills for individuals and best practices for organizations when beginning to apply advanced analytics to workforce data. It will also introduce machine learning and where it fits within the larger HR Analytics framework by explaining many of its basic tenets and methodologies. By the end of the book, readers will understand the skills required to do advanced HR analytics well, as well as how to begin designing and applying machine learning within a larger human capital strategy.