Surbhi Bhatia Khan – författare

Advanced Data Mining Tools and Methods for Social Computing explores advances in the latest data mining tools, methods, algorithms and the architectures being developed specifically for social computing and social network analysis. The book reviews major emerging trends in technology that are supporting current advancements in social networks, including data mining techniques and tools. It also aims to highlight the advancement of conventional approaches in the field of social networking. Chapter coverage includes reviews of novel techniques and state-of-the-art advances in the area of data mining, machine learning, soft computing techniques, and their applications in the field of social network analysis. Provides insights into the latest research trends in social network analysis Covers a broad range of data mining tools and methods for social computing and analysis Includes practical examples and case studies across a range of tools and methods Features coding examples and supplementary data sets in every chapter

Researches and Applications of Artificial Intelligence to Mitigate Pandemics: History, Diagnostic Tools, Epidemiology, Healthcare, and Technology offers readers an interdisciplinary view of state-of-art research related to the COVID-19 outbreak, with a focus on tactics employed to model the number of cases of COVID-19 (time series modeling), models employed to diagnostics COVID-19 based on images, and the panoramic of COVID-19 since its discovery and up to this book's publication. This book showcases the algorithms and models available to manage pandemic data, the role of AI, IoT and Mathematical Modeling, how to prevent and fight COVID-19, and the existing medical, social and pharmaceutical support.

Chapters cover methods and protocols, the basics and history of diseases, the fast diagnosis of disease with different automated algorithms and artificial intelligence tools and techniques, the methods of handling epidemiology for mitigating the spread of disease, artificial intelligence and mathematical modeling techniques, and how mental and physical health is affected with social media usage.

Explains novel and hybrid high quality artificial intelligence methodologies, techniques, algorithms, architectures, tools and methods to cope with pandemics Covers rapid point-of-care diagnostics, presents details on varied mathematical models developed to control epidemiology, and lists existing measures to disseminate the spread of infection using computational methods Highlights the negative effect of social media and other sources by applying preventive measures to combat depression and anxiety

Innovations in Artificial Intelligence and Human Computer Interaction in the Digital Era investigates the interaction and growing interdependency of the HCI and AI fields, which are not usually addressed in traditional approaches. Chapters explore how well AI can interact with users based on linguistics and user-centered design processes, especially with the advances of AI and the hype around many applications. Other sections investigate how HCI and AI can mutually benefit from a closer association and the how the AI community can improve their usage of HCI methods like "Wizard of Oz� prototyping and "Thinking aloud� protocols.

Moreover, HCI can further augment human capabilities using new technologies. This book demonstrates how an interdisciplinary team of HCI and AI researchers can develop extraordinary applications, such as improved education systems, smart homes, smart healthcare and map Human Computer Interaction (HCI) for a multidisciplinary field that focuses on the design of computer technology and the interaction between users and computers in different domains.

Presents fundamental concepts of both HCI and AI, addressing a multidisciplinary audience of researchers and engineers working on User Centered Design (UCD), User Interface (UI) design, and User Experience (UX) designExplores a broad range of case studies from across healthcare, industry, and educationInvestigates multiple strategies for designing and developing intelligent user interfaces to solve real-world problemsOutlines research challenges and future directions for the intersection of AI and HCI

In recent years, deep learning has shown great potential in transforming various fields including healthcare. With the abundance of healthcare data being generated every day, there is a pressing need to develop efficient algorithms that can process and analyze this data to improve patient care and treatment outcomes.Handbook of Deep Learning Models for Healthcare Data Processing: Disease Prediction, Analysis, and Applications covers a wide range of deep learning models, techniques, and applications in healthcare data processing, analysis, and disease prediction, providing a comprehensive overview of the field. It focuses on the practical application of deep learning models in healthcare and offers step-by-step instructions for building and deploying models and using real-world examples. The handbook discusses the potential future applications of deep learning models in healthcare, such as precision medicine, personalized treatment, and clinical decision support. It also addresses the ethical considerations associated with the use of deep learning models in healthcare, such as privacy, security, and bias. It provides technical details on deep learning models, including their architecture, training methods, and optimization techniques, making it useful for data scientists and researchers.Written to be a comprehensive guide for healthcare professionals, researchers, and data analysts, this handbook is an essential need for those who are interested in using deep learning models to analyze and process healthcare data. It is also suitable for those who have a basic understanding of machine learning and want to learn more about the latest advancements in deep learning in healthcare.

This book provides a comprehensive overview of the intersection of computational intelligence, health informatics, and computer-aided diagnosis (CAD). The book explores and highlights the latest advancements, methodologies, applications, and tools in these fields.Advances in Computational Intelligence for Health Informatics and Computer-Aided Diagnosis: Methods, Applications, and Tools covers a broad spectrum of computational intelligence approaches, from basic concepts to advanced methodologies. The focus on health informatics reflects the book's commitment to researching data integration, privacy issues, and interoperability issues that are crucial in today's healthcare landscape. The book's core is its in-depth examination of CAD systems, which encompasses numerous healthcare sectors and underlines the technological complexity involved in building accurate and efficient diagnostic tools. Some of the other key areas covered include: medical imaging analysis, disease identification and diagnosis, and drug research and development. It also provides case studies that demonstrate how computational intelligence methods are applied in real-world healthcare scenarios, giving readers a practical understanding of the subject matter. The authors then discuss future trends and directions in computational intelligence for health informatics.The book is designed to serve as a guide to for academics, professionals, and students who are curious about the challenges of integrating contemporary computational approaches into medical diagnostics and decision support.

This book provides a comprehensive overview of the intersection of computational intelligence, health informatics, and computer-aided diagnosis (CAD). The book explores and highlights the latest advancements, methodologies, applications, and tools in these fields.Advances in Computational Intelligence for Health Informatics and Computer-Aided Diagnosis: Methods, Applications, and Tools covers a broad spectrum of computational intelligence approaches, from basic concepts to advanced methodologies. The focus on health informatics reflects the book's commitment to researching data integration, privacy issues, and interoperability issues that are crucial in today's healthcare landscape. The book's core is its in-depth examination of CAD systems, which encompasses numerous healthcare sectors and underlines the technological complexity involved in building accurate and efficient diagnostic tools. Some of the other key areas covered include: medical imaging analysis, disease identification and diagnosis, and drug research and development. It also provides case studies that demonstrate how computational intelligence methods are applied in real-world healthcare scenarios, giving readers a practical understanding of the subject matter. The authors then discuss future trends and directions in computational intelligence for health informatics.The book is designed to serve as a guide to for academics, professionals, and students who are curious about the challenges of integrating contemporary computational approaches into medical diagnostics and decision support.

This book provides a comprehensive exploration of Industry 6.0, which marks the convergence of intelligent systems, machine learning (ML), deep learning, and human–robot collaboration (HRC) in various sectors. It focuses on how these technologies enable businesses to harness insights from vast datasets, optimize operations, forecast maintenance requirements, and mitigate outages. In this comprehensive book, the authors cover the major aspects of Industry 6.0, including the latest advances in technology, new applications, and the many challenges that accompany the process that is changing it. This book acts as a compass, guiding readers through the labyrinth of Industry 6.0, revealing the complex interactions between technologies, new applications, innovations, and business ecosystems. From a multidisciplinary perspective, the book explores the far‑reaching impact of Industry 6.0 on the business world, revealing its potential to increase productivity, improve decision‑making, and open new opportunities for development. Discusses the transformative impact of Industry 6.0 driven by the convergence of artificial intelligence (AI), ML, and the industrial internet of things (IIoT) in manufacturing Explores the transformative potential of HRC in modern manufacturing, emphasizing the ability of HRC to boost productivity, flexibility, and safety Compares several service models in cloud computing, with a focus on private, public, and community cloud deployment methods Presents information about autism spectrum disorder (ASD) in children and the advanced technology of convolutional neural networks used to detect autism in children Describes the accurate diagnosis of Alzheimer’s disease through integrating state‑of‑the‑art technologies, especially deep learning Focuses on digital adaptation in India’s agricultural sector, especially Uttar Pradesh, highlighting challenges and prospects Presents a visionary leap into Agriculture 6.0, where technology and tradition converge for sustainable farming solutions Provides the mitigation strategies for climate change over multiple locations Explores the transformative impact of recent computational intelligence advancements in vehicle surveillance and recognition, particularly through CCTV analysis Focuses on the exploration and development of a supply chain network design (SCND) model of milk productsThis book will be of interest to researchers, academics, practitioners, technology providers, undergraduate and postgraduate students, scholars, consultants, advisors, and doctors. It can be used by undergraduate and postgraduate students pursuing Industry 6.0 programs in computer science and engineering across the globe.

This book provides a comprehensive exploration of Industry 6.0, which marks the convergence of intelligent systems, machine learning (ML), deep learning, and human–robot collaboration (HRC) in various sectors. It focuses on how these technologies enable businesses to harness insights from vast datasets, optimize operations, forecast maintenance requirements, and mitigate outages. In this comprehensive book, the authors cover the major aspects of Industry 6.0, including the latest advances in technology, new applications, and the many challenges that accompany the process that is changing it. This book acts as a compass, guiding readers through the labyrinth of Industry 6.0, revealing the complex interactions between technologies, new applications, innovations, and business ecosystems. From a multidisciplinary perspective, the book explores the far‑reaching impact of Industry 6.0 on the business world, revealing its potential to increase productivity, improve decision‑making, and open new opportunities for development. Discusses the transformative impact of Industry 6.0 driven by the convergence of artificial intelligence (AI), ML, and the industrial internet of things (IIoT) in manufacturing Explores the transformative potential of HRC in modern manufacturing, emphasizing the ability of HRC to boost productivity, flexibility, and safety Compares several service models in cloud computing, with a focus on private, public, and community cloud deployment methods Presents information about autism spectrum disorder (ASD) in children and the advanced technology of convolutional neural networks used to detect autism in children Describes the accurate diagnosis of Alzheimer’s disease through integrating state‑of‑the‑art technologies, especially deep learning Focuses on digital adaptation in India’s agricultural sector, especially Uttar Pradesh, highlighting challenges and prospects Presents a visionary leap into Agriculture 6.0, where technology and tradition converge for sustainable farming solutions Provides the mitigation strategies for climate change over multiple locations Explores the transformative impact of recent computational intelligence advancements in vehicle surveillance and recognition, particularly through CCTV analysis Focuses on the exploration and development of a supply chain network design (SCND) model of milk productsThis book will be of interest to researchers, academics, practitioners, technology providers, undergraduate and postgraduate students, scholars, consultants, advisors, and doctors. It can be used by undergraduate and postgraduate students pursuing Industry 6.0 programs in computer science and engineering across the globe.

Sustainable UAV Ecosystems: Integrating Blockchain, Quantum, and AI for Smart Mobility and SDG Innovation provides a comprehensive examination of technologies enabling secure, intelligent, and sustainable UAV ecosystems for smart mobility and digital infrastructure. It presents theoretical foundations and practical methodologies integrating artificial intelligence, blockchain, post-quantum cryptography and cloud-edge computing for resilient UAV communications. It not only explores predictive intelligence, adaptive routing, swarm intelligence and decentralized control in autonomous aerial networks but also highlights applications in smart-city logistics, disaster response, environmental monitoring and precision agriculture. Emphasis is placed on energy-efficient operations, low-carbon mobility and sustainable UAV systems aligned with Sustainable Development Goals (SDGs).Key Features:Illustrates the design and integration of secure and sustainable UAV ecosystems, including intelligent aerial networks, smart mobility infrastructures, and autonomous drone operations.Emphasizes the role of artificial intelligence and intelligent analytics in UAV systems by leveraging advanced techniques such as predictive intelligence, adaptive routing, and swarm intelligence for cooperative aerial operations.Presents practical applications of UAV technologies in smart-city logistics, disaster response, environmental monitoring, and precision agriculture to support efficient and sustainable services.Covers cybersecurity mechanisms and post-quantum cryptographic models for protecting UAV communications, aerial networks, and decentralized drone infrastructures.Showcases the integration of blockchain, distributed cloud–edge computing, and decentralized control frameworks to enable trustworthy, scalable, and resilient UAV ecosystems.This book is suitable for senior undergraduates, graduate students, and academic researchers in computer science, artificial intelligence, aerospace engineering, robotics, communication engineering, and smart mobility systems, as well as policymakers and industry practitioners working on sustainable UAV technologies and intelligent aerial infrastructures.

Secure Energy Optimization: Leveraging Internet of Things and Artificial Intelligence for Enhanced Efficiency is essential for anyone looking to navigate the transformative landscape of energy management, as it expertly combines the principles of IoT and AI with real-world case studies to provide actionable insights for achieving sustainable and efficient energy optimization. Energy is rapidly changing, with an emphasis on sustainable and efficient energy use. In this context, the combination of Internet of Things (IoT) and Artificial Intelligence (AI) technologies has emerged as a potent technique for optimising energy use, improving efficiency, and enhancing overall energy security. Secure Energy Optimization: Leveraging Internet of Things and Artificial Intelligence for Enhanced Efficiency provides a comprehensive review of how IoT and AI can be used to accomplish safe energy optimisation. Readers will gain an understanding of the underlying principles of IoT and AI, as well as their applications in energy efficiency and the problems and hazards related to their adoption. They will investigate the successful integration of IoT and AI technologies in energy management systems, smart grids, and renewable energy sources using real-world case studies and examples. By bringing together theoretical notions, cutting-edge research, and practical examples, this book bridges the gap between theory and implementation.

This book discusses automated computing systems which are mostly powered by intelligent technologies like artificial intelligence, machine learning, image recognition, speech processing, cloud computing, etc., to perform complex automated tasks which are not possible by traditional computing systems. The chapters are extended version of research works presented at third PhD Research Symposium in various advanced technologies used in the field of computer science. This book provides an opportunity for the researchers to get ideas regarding the ongoing works that help them in formulating problems of their interest. The academicians can also be benefited to know about the current research trends that smooth the way to guide their students to carry out research work in the proper direction. The industry people will be also facilitated to know about the current advances in research work and materialize the research work into industrial applications.

This book focuses on the sustainable security practices in the domain of blockchain, quantum, and post-quantum technologies dealing with the real-time applications.

This book focuses on the sustainable security practices in the domain of blockchain, quantum, and post-quantum technologies dealing with the real-time applications.