Thipendra P Singh – författare

This book covers aspects of data science and predictive analytics used in the oil and gas industry by looking into the challenges of data processing and data modelling unique to this industry. It includes upstream management, intelligent/digital wells, value chain integration, crude basket forecasting, and so forth. It further discusses theoretical, methodological, well-established, and validated empirical work dealing with various related topics. Special focus has been given to experimental topics with various case studies.

Features:

This book is aimed at professionals and graduate students in petroleum engineering, upstream industry, data analytics, and digital transformation process in oil and gas.

This book covers aspects of data science and predictive analytics used in the oil and gas industry by looking into the challenges of data processing and data modelling unique to this industry. It includes upstream management, intelligent/digital wells, value chain integration, crude basket forecasting, and so forth. It further discusses theoretical, methodological, well-established, and validated empirical work dealing with various related topics. Special focus has been given to experimental topics with various case studies.

Features:

This book is aimed at professionals and graduate students in petroleum engineering, upstream industry, data analytics, and digital transformation process in oil and gas.

Social media and crowdsourcing are important tools for solving complex problems. The benefit of crowdsourcing is that it leverages the power of human intelligence cost effectively and with less time. Social Media and Crowdsourcing: Application and Analytics examines the concepts of social media and crowdsourcing as well as their analytical aspects. It explores how these technologies contribute to the real world and examines such applications as promoting social good, agriculture, healthcare, tourism, disaster management, education, crime control, and cultural heritage. The book also looks at ethical issues in crowdsourcing and future scenarios and challenges for policy. Highlights of the book include the following:

Expanding the overarching concept of utilizing social media and crowdsourcing to solve various real-life problems, this book discusses how to bring together the wisdom of crowds for various decision-making problems in agriculture, disaster management, and healthcare. It addresses the various ethical issues arising out of various crowdsourcing-based applications. It puts forward diverse methodologies to involve crowdsourcing in education to implement new strategies to enhance learning outcomes. This book also addresses various problem-solving techniques for recommender applications in the travel and tourism industry.

Providing a systematic discussion of the many sectors using crowdsourcing as an essential part of social innovation, this book is a theoretical and methodological look at the application of social media.

Social media and crowdsourcing are important tools for solving complex problems. The benefit of crowdsourcing is that it leverages the power of human intelligence cost effectively and with less time. Social Media and Crowdsourcing: Application and Analytics examines the concepts of social media and crowdsourcing as well as their analytical aspects. It explores how these technologies contribute to the real world and examines such applications as promoting social good, agriculture, healthcare, tourism, disaster management, education, crime control, and cultural heritage. The book also looks at ethical issues in crowdsourcing and future scenarios and challenges for policy. Highlights of the book include the following:

Expanding the overarching concept of utilizing social media and crowdsourcing to solve various real-life problems, this book discusses how to bring together the wisdom of crowds for various decision-making problems in agriculture, disaster management, and healthcare. It addresses the various ethical issues arising out of various crowdsourcing-based applications. It puts forward diverse methodologies to involve crowdsourcing in education to implement new strategies to enhance learning outcomes. This book also addresses various problem-solving techniques for recommender applications in the travel and tourism industry.

Providing a systematic discussion of the many sectors using crowdsourcing as an essential part of social innovation, this book is a theoretical and methodological look at the application of social media.

Navigation has become highly intelligent over the last 100 years. Today, we have autonomous navigation in several vehicles that is being revolutionized through computational intelligence. This book, Advances in Autonomous Navigation through Intelligent Technologies, presents today’s issues, solutions, and adaptation techniques for creating safe autonomous navigating vehicles with the use of advanced technologies.

The chapters in the book discuss autonomous navigation as a major issue in robotics and artificial intelligence. The book covers a range of topics that include the architecture of autonomous navigation, algorithms for robot positioning and navigation, methodologies for controlling autonomous systems, self-learning routing protocols for autonomous unmanned aerial networks (A-UAN), and more. The book also covers the concepts and algorithms of mobile devices, sensors, and IoT and other related components required for autonomous navigation. The book includes a survey on smart intrusion detection-enabled flying ad hoc networks (FANETs) (a decentralized communication system solely formed by unmanned aerial vehicles) in healthcare.

Key highlights:

Presenting cutting-edge research in the field of autonomous navigation, this book will serve as a valuable resource for academics, researchers, and others interested in learning about and comprehending the many advancements in autonomous navigation.

Navigation has become highly intelligent over the last 100 years. Today, we have autonomous navigation in several vehicles that is being revolutionized through computational intelligence. This book, Advances in Autonomous Navigation through Intelligent Technologies, presents today’s issues, solutions, and adaptation techniques for creating safe autonomous navigating vehicles with the use of advanced technologies.

The chapters in the book discuss autonomous navigation as a major issue in robotics and artificial intelligence. The book covers a range of topics that include the architecture of autonomous navigation, algorithms for robot positioning and navigation, methodologies for controlling autonomous systems, self-learning routing protocols for autonomous unmanned aerial networks (A-UAN), and more. The book also covers the concepts and algorithms of mobile devices, sensors, and IoT and other related components required for autonomous navigation. The book includes a survey on smart intrusion detection-enabled flying ad hoc networks (FANETs) (a decentralized communication system solely formed by unmanned aerial vehicles) in healthcare.

Key highlights:

Presenting cutting-edge research in the field of autonomous navigation, this book will serve as a valuable resource for academics, researchers, and others interested in learning about and comprehending the many advancements in autonomous navigation.

This book explores the transformative role of artificial intelligence (AI) in healthcare, emphasizing its shift from a futuristic concept to an essential part of modern medical systems. The articles cover a range of AI applications, from disease diagnosis and drug design to patient engagement and mental health treatment. Advances in machine learning (ML) and deep learning (DL) technologies have opened new possibilities for diagnosing complex conditions, with examples like predictive analysis for health risks and early diagnosis of diseases such as breast cancer and diabetic retinopathy. Additionally, AI''s role in treating mental health disorders is highlighted. While AI offers vast benefits, the book stresses the importance of ethical considerations, such as patient privacy and equitable access. It also addresses challenges in integrating AI within existing healthcare systems, underscoring collaboration among stakeholders as crucial. This book ultimately provides a comprehensive look at AI’s potential to reshape healthcare.

This book highlights and attempts to fill a crucial gap in the existing literature by providing a comprehensive exploration of the emerging field of neuro-symbolic AI. It introduces the concept of neuro-symbolic AI, highlighting its fusion of symbolic reasoning and machine learning. The book covers symbolic AI and knowledge representation, neural networks and deep learning, neuro-symbolic integration approaches, reasoning and inference techniques, applications in healthcare and robotics, as well as challenges and future directions. By combining the power of symbolic logic and knowledge representation with the flexibility of neural networks, neuro-symbolic AI offers the potential for more interpretable and trustworthy AI systems. This book is a valuable resource for researchers, practitioners, and students interested in understanding and applying neuro-symbolic AI.