Mansaf Alam – författare

Extended Reality for Healthcare Systems: Recent Advances in Contemporary Research focuses on real world applications in medicine, also providing an overview of emerging technologies. The book includes case studies that break down the ways in which this technology has and can be used, while also taking readers through evidence, best practices and obstacles. Sections emphasize evidence, research-based practices and work. Content coverage includes Enhancing Medical Education with AR/VR, and XR: The Future of Surgery and Building Systems for Enhanced Health, and more. Readers will learn how to use this technology to improve existing systems by enhancing precision and reducing costs.

Other sections cover extended reality in elderly care and remote monitoring of patients, building systems for enhanced health, including telehealth and telepsychiatry, using AR and VR in medical education, and designing technology for use in telesurgery.

Offers advice on the development of state-of-the-art tech-driven healthcare systems and technologies for improving the quality of healthcare Focuses on healthcare solutions that are inclusive and cost-effective Discusses the future, limitations and challenges associated with the use and adoption of XR for healthcare

Big Data Analytics: Applications in Business and Marketing explores the concepts and applications related to marketing and business as well as future research directions. It also examines how this emerging field could be extended to performance management and decision-making. Investment in business and marketing analytics can create value through proper allocation of resources and resource orchestration process. The use of data analytics tools can be used to diagnose and improve performance. The book is divided into five parts. The first part introduces data science, big data, and data analytics. The second part focuses on applications of business analytics including:Big data analytics and algorithmMarket basket analysisAnticipating consumer purchase behaviorVariation in shopping patternsBig data analytics for market intelligenceThe third part looks at business intelligence and features an evaluation study of churn prediction models for business Intelligence. The fourth part of the book examines analytics for marketing decision-making and the roles of big data analytics for market intelligence and of consumer behavior. The book concludes with digital marketing, marketing by consumer analytics, web analytics for digital marketing, and smart retailing. This book covers the concepts, applications and research trends of marketing and business analytics with the aim of helping organizations increase profitability by improving decision-making through data analytics.

Big Data Analytics: Applications in Business and Marketing explores the concepts and applications related to marketing and business as well as future research directions. It also examines how this emerging field could be extended to performance management and decision-making. Investment in business and marketing analytics can create value through proper allocation of resources and resource orchestration process. The use of data analytics tools can be used to diagnose and improve performance. The book is divided into five parts. The first part introduces data science, big data, and data analytics. The second part focuses on applications of business analytics including:Big data analytics and algorithmMarket basket analysisAnticipating consumer purchase behaviorVariation in shopping patternsBig data analytics for market intelligenceThe third part looks at business intelligence and features an evaluation study of churn prediction models for business Intelligence. The fourth part of the book examines analytics for marketing decision-making and the roles of big data analytics for market intelligence and of consumer behavior. The book concludes with digital marketing, marketing by consumer analytics, web analytics for digital marketing, and smart retailing. This book covers the concepts, applications and research trends of marketing and business analytics with the aim of helping organizations increase profitability by improving decision-making through data analytics.

The main objective of this book is to introduce cyber security using modern technologies such as Artificial Intelligence, Quantum Cryptography, and Blockchain. This book provides in-depth coverage of important concepts related to cyber security. Beginning with an introduction to Quantum Computing, Post-Quantum Digital Signatures, and Artificial Intelligence for cyber security of modern networks and covering various cyber-attacks and the defense measures, strategies, and techniques that need to be followed to combat them, this book goes on to explore several crucial topics, such as security of advanced metering infrastructure in smart grids, key management protocols, network forensics, intrusion detection using machine learning, cloud computing security risk assessment models and frameworks, cyber-physical energy systems security, a biometric random key generator using deep neural network and encrypted network traffic classification. In addition, this book provides new techniques to handle modern threats with more intelligence. It also includes some modern techniques for cyber security, such as blockchain for modern security, quantum cryptography, and forensic tools. Also, it provides a comprehensive survey of cutting-edge research on the cyber security of modern networks, giving the reader a general overview of the field. It also provides interdisciplinary solutions to protect modern networks from any type of attack or manipulation. The new protocols discussed in this book thoroughly examine the constraints of networks, including computation, communication, and storage cost constraints, and verifies the protocols both theoretically and experimentally. Written in a clear and comprehensive manner, this book would prove extremely helpful to readers. This unique and comprehensive solution for the cyber security of modern networks will greatly benefit researchers, graduate students, and engineers in the fields of cryptography and network security.

The main objective of this book is to introduce cyber security using modern technologies such as Artificial Intelligence, Quantum Cryptography, and Blockchain. This book provides in-depth coverage of important concepts related to cyber security. Beginning with an introduction to Quantum Computing, Post-Quantum Digital Signatures, and Artificial Intelligence for cyber security of modern networks and covering various cyber-attacks and the defense measures, strategies, and techniques that need to be followed to combat them, this book goes on to explore several crucial topics, such as security of advanced metering infrastructure in smart grids, key management protocols, network forensics, intrusion detection using machine learning, cloud computing security risk assessment models and frameworks, cyber-physical energy systems security, a biometric random key generator using deep neural network and encrypted network traffic classification. In addition, this book provides new techniques to handle modern threats with more intelligence. It also includes some modern techniques for cyber security, such as blockchain for modern security, quantum cryptography, and forensic tools. Also, it provides a comprehensive survey of cutting-edge research on the cyber security of modern networks, giving the reader a general overview of the field. It also provides interdisciplinary solutions to protect modern networks from any type of attack or manipulation. The new protocols discussed in this book thoroughly examine the constraints of networks, including computation, communication, and storage cost constraints, and verifies the protocols both theoretically and experimentally. Written in a clear and comprehensive manner, this book would prove extremely helpful to readers. This unique and comprehensive solution for the cyber security of modern networks will greatly benefit researchers, graduate students, and engineers in the fields of cryptography and network security.

Big Data Analytics: Digital Marketing and Decision-Making covers the advances related to marketing and business analytics. Investment marketing analytics can create value through proper allocation of resources and resource orchestration processes. The use of data analytics tools can be used to improve and speed decision-making processes.Chapters examining analytics for decision-making cover such topics as: Big data analytics for gathering business intelligenceData analytics and consumer behaviorThe role of big data analytics in organizational decision-makingThis book also looks at digital marketing and focuses on such areas as: The prediction of marketing by consumer analyticsWeb analytics for digital marketingSmart retailingLeveraging web analytics for optimizing digital marketing strategiesBig Data Analytics: Digital Marketing and Decision-Making aims to help organizations increase their profits by making better decisions on time through the use of data analytics. It is written for students, practitioners, industry professionals, researchers, and faculty working in the field of commerce and marketing, big data analytics, and organizational decision-making.

Big Data Analytics: Digital Marketing and Decision-Making covers the advances related to marketing and business analytics. Investment marketing analytics can create value through proper allocation of resources and resource orchestration processes. The use of data analytics tools can be used to improve and speed decision-making processes.Chapters examining analytics for decision-making cover such topics as: Big data analytics for gathering business intelligenceData analytics and consumer behaviorThe role of big data analytics in organizational decision-makingThis book also looks at digital marketing and focuses on such areas as: The prediction of marketing by consumer analyticsWeb analytics for digital marketingSmart retailingLeveraging web analytics for optimizing digital marketing strategiesBig Data Analytics: Digital Marketing and Decision-Making aims to help organizations increase their profits by making better decisions on time through the use of data analytics. It is written for students, practitioners, industry professionals, researchers, and faculty working in the field of commerce and marketing, big data analytics, and organizational decision-making.

This book covers various topics related to marketing and business analytics. It explores how organizations can increase their profits by making better decisions in a timely manner through the use of data analytics. This book is meant for students, practitioners, industry professionals, researchers, and academics working in the field of commerce and marketing, big data analytics, and organizational decision-making. Highlights of the book include: The role of Explainable AI in improving customer experiences in e-commerce Sentiment analysis of social media Data analytics in business intelligence Federated learning for business intelligence AI-based planning of business management An AI-based business model innovation in new technologies An analysis of social media marketing and online impulse buying behaviourAI-Based Data Analytics: Applications for Business Management has two primary focuses. The first is on analytics for decision-making and covers big data analytics for market intelligence, data analytics and consumer behavior, and the role of big data analytics in organizational decision-making. The book’s second focus is on digital marketing and includes the prediction of marketing by consumer analytics, web analytics for digital marketing, smart retailing, and leveraging web analytics for optimizing digital marketing strategies.

This book focuses on data analytics with machine learning using IoT and blockchain technology. Integrating these three fields by examining their interconnections, Intelligent Data Analytics, IoT, and Blockchain examines the opportunities and challenges of developing systems and applications exploiting these technologies. Written primarily for researchers who are working in this multi-disciplinary field, the book also benefits industry experts and technology executives who want to develop their organizations’ decision-making capabilities. Highlights of the book include:Using image processing with machine learning techniquesA deep learning approach for facial recognitionA scalable system architecture for smart cities based on cognitive IoTSource authentication of videos shared on social mediaSurvey of blockchain in healthcareAccident prediction by vehicle trackingBig data analytics in disaster managementApplicability, limitations, and opportunities of blockchain technologyThe book presents novel ideas and insights on different aspects of data analytics, blockchain technology, and IoT. It views these technologies as interdisciplinary fields concerning processes and systems that extract knowledge and insights from data. Focusing on recent advances, the book offers a variety of solutions to real-life challenges with an emphasis on security.

This book focuses on data analytics with machine learning using IoT and blockchain technology. Integrating these three fields by examining their interconnections, Intelligent Data Analytics, IoT, and Blockchain examines the opportunities and challenges of developing systems and applications exploiting these technologies. Written primarily for researchers who are working in this multi-disciplinary field, the book also benefits industry experts and technology executives who want to develop their organizations’ decision-making capabilities. Highlights of the book include:Using image processing with machine learning techniquesA deep learning approach for facial recognitionA scalable system architecture for smart cities based on cognitive IoTSource authentication of videos shared on social mediaSurvey of blockchain in healthcareAccident prediction by vehicle trackingBig data analytics in disaster managementApplicability, limitations, and opportunities of blockchain technologyThe book presents novel ideas and insights on different aspects of data analytics, blockchain technology, and IoT. It views these technologies as interdisciplinary fields concerning processes and systems that extract knowledge and insights from data. Focusing on recent advances, the book offers a variety of solutions to real-life challenges with an emphasis on security.

This book covers various topics related to marketing and business analytics. It explores how organizations can increase their profits by making better decisions in a timely manner through the use of data analytics. This book is meant for students, practitioners, industry professionals, researchers, and academics working in the field of commerce and marketing, big data analytics, and organizational decision-making. Highlights of the book include: The role of Explainable AI in improving customer experiences in e-commerce Sentiment analysis of social media Data analytics in business intelligence Federated learning for business intelligence AI-based planning of business management An AI-based business model innovation in new technologies An analysis of social media marketing and online impulse buying behaviourAI-Based Data Analytics: Applications for Business Management has two primary focuses. The first is on analytics for decision-making and covers big data analytics for market intelligence, data analytics and consumer behavior, and the role of big data analytics in organizational decision-making. The book’s second focus is on digital marketing and includes the prediction of marketing by consumer analytics, web analytics for digital marketing, smart retailing, and leveraging web analytics for optimizing digital marketing strategies.

In today’s world, characterized by volatility, uncertainty, complexity, and ambiguity (VUCA), traditional finance is no longer sufficient to meet the challenges of fast-paced and interconnected global markets. To thrive in this dynamic environment, financial institutions, professionals, and policymakers are increasingly turning to AI. AI-Driven Finance in the VUCA World explores how AI is becoming ever more critical in the financial industry.This book looks at the impact of AI on investment strategies. AI-powered algorithms exhibit the capacity to scrutinize extensive datasets to unveil masked patterns and investment opportunities. From quantitative trading algorithms adept at capitalizing on market inefficiencies to robot-advisors offering individualized investment counsel, AI profoundly reconfigures the investment landscape. In a VUCA world, risk management is paramount, and regulatory scrutiny is tighter than ever. AI’s ability to assess risks in real time is critical in identifying anomalies and predicting potential crises. The book examines how AI enhances risk assessment, fraud detection, and compliance to provide institutions with a proactive edge in safeguarding operations and assets. This text also looks at the following:AI-driven chatbots, virtual assistants, and recommendation engines that revolutionize customer interactions, enhance engagement, and improve retention ratesThe ethical challenges surrounding AI in finance, including bias in algorithms, data privacy, and the responsible use of AICase studies on how AI can solve specific industry challenges and drive innovationThe future of finance is intertwined with AI, and this book looks to this future by discussing emerging trends and possibilities. It explores the potential of quantum computing in finance, the role of AI in sustainability and ESG investing, and the implications of AI-powered regulatory technologies. Seeking to provide valuable insights for financial professionals, the book is equally valuable to researchers, policymakers, and anyone interested in the future of finance. It bridges the gap between theory and practice, offering actionable insights that can be immediately applied in the real world.

In today’s world, characterized by volatility, uncertainty, complexity, and ambiguity (VUCA), traditional finance is no longer sufficient to meet the challenges of fast-paced and interconnected global markets. To thrive in this dynamic environment, financial institutions, professionals, and policymakers are increasingly turning to AI. AI-Driven Finance in the VUCA World explores how AI is becoming ever more critical in the financial industry.This book looks at the impact of AI on investment strategies. AI-powered algorithms exhibit the capacity to scrutinize extensive datasets to unveil masked patterns and investment opportunities. From quantitative trading algorithms adept at capitalizing on market inefficiencies to robot-advisors offering individualized investment counsel, AI profoundly reconfigures the investment landscape. In a VUCA world, risk management is paramount, and regulatory scrutiny is tighter than ever. AI’s ability to assess risks in real time is critical in identifying anomalies and predicting potential crises. The book examines how AI enhances risk assessment, fraud detection, and compliance to provide institutions with a proactive edge in safeguarding operations and assets. This text also looks at the following:AI-driven chatbots, virtual assistants, and recommendation engines that revolutionize customer interactions, enhance engagement, and improve retention ratesThe ethical challenges surrounding AI in finance, including bias in algorithms, data privacy, and the responsible use of AICase studies on how AI can solve specific industry challenges and drive innovationThe future of finance is intertwined with AI, and this book looks to this future by discussing emerging trends and possibilities. It explores the potential of quantum computing in finance, the role of AI in sustainability and ESG investing, and the implications of AI-powered regulatory technologies. Seeking to provide valuable insights for financial professionals, the book is equally valuable to researchers, policymakers, and anyone interested in the future of finance. It bridges the gap between theory and practice, offering actionable insights that can be immediately applied in the real world.

This book combines cutting-edge advancements in neuroscience-inspired artificial intelligence, edge computing, and sustainable practices, presenting a compelling narrative for researchers, industry professionals, and policymakers alike. It discusses the principles of neuroscience that inspire artificial intelligence development, including neural dynamics, spiking neural networks, and the role of biological intelligence in creating adaptive systems.Features:Illustrates how artificial intelligence is revolutionizing areas such as climate modelling, green energy solutions, resource management, and precision farming.Addresses critical issues such as replicating human cognition responsibly, addressing bias in artificial intelligence systems, protecting user privacy, and minimizing the environmental impact of artificial intelligence.Discusses energy-efficient artificial intelligence, ethical considerations, and advanced concepts like neuromorphic computing and federated learning.Explores the convergence of neuroscience and edge computing, demonstrating real-world applications in healthcare, agriculture, robotics, and environmental sustainability.Explains principles of neuroscience that inspire artificial intelligence development, including neural dynamics, spiking neural networks, and the role of biological intelligence in creating adaptive systems.It is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, computer science and engineering, and environmental engineering.

This books objective is to explore the concepts and applications related to Internet of Things with the vision to identify and address existing challenges. Studies investigate applications for crowd sensing and sourcing, as well as smart applications to healthcare solutions, agriculture and intelligent disaster management.

This books objective is to explore the concepts and applications related to Internet of Things with the vision to identify and address existing challenges. Studies investigate applications for crowd sensing and sourcing, as well as smart applications to healthcare solutions, agriculture and intelligent disaster management.

This book includes peer-reviewed contributions presented at the International Conference on Data Analytics in Business and Marketing, ICDABM 2022. The book covers topics in data analytics, intelligent data, data management in business and marketing, big data, computational intelligence, and communication networks.