AI for Scientific Discovery provides an accessible introduction to the wide-ranging applications of artificial intelligence technologies in scientific research and discovery across the full breadth of scientific disciplines. Artificial intelligence technologies support discovery science in multiple different ways. They support literature management and synthesis, allowing the wealth of what has already been discovered and reported on to be integrated and easily accessed. They play a central role in data analysis and interpretation - in the context of what is called 'data science'. AI is also helping to combat the reproducibility crisis in scientific research, by underpinning the discovery process with AI-enabled standards and pipelines, support the management of large-scale data and knowledge resources so that they can be shared, integrated and serve as a background 'knowledge ecosystem' into which new discoveries can be embedded. However, there are limitations to what AI can achieve and its outputs can be biased and confounded thus should not be blindly trusted. The latest generation of hybrid and 'human-in-the-loop' AI technologies have as their objective a balance between human inputs and insights and the power of the number-crunching and statistical inference at massive scale that AI technologies are best at.

AI Metaheuristics for Information Security in Digital Media examines the latest developments in AI-based metaheuristics algorithms with applications in information security for digital media. It highlights the importance of several security parameters, their analysis, and validations for different practical applications. Drawing on multidisciplinary research including computer vision, machine learning, artificial intelligence, modified/newly developed metaheuristics algorithms, it will enhance information security for society. It includes state-of-the-art research with illustrations and exercises throughout.

This book provides readers to the vision of Society 5.0, which was originally proposed in the fifth Basic Science and Technology Plan by Japan's government for a technology-based, human-centered society, emerging from the 4th industrial revolution (Industry 4.0). The implementation of AI and other modern techniques in a smart society requires automated data scheduling and analysis using smart applications, a smart infrastructure, smart systems, and a smart network. Features Provides an overview of basic concepts of Society 5.0 as well as the main pillars that supports the implementation of Society 5.0. Contains the most recent research analysis in the domain of computer vision, signal processing and computing sciences for facilitating the smart homes, buildings, transport, facilities, environmental conditions and cities, and the benefits these offer to a nation. Presents the readers with practical approaches of using AI and other algorithms for smart ecosystem to deals with human dynamics, the social objects, and their relations. Deals with the utilization of AI tools and other modern techniques for smart society as well as the current challenging issues and its solutions for transformation to Society 5.0. This book is aimed at graduate and post graduate students, researchers, academicians working in the field of computer science, artificial intelligence, and machine learning.

Provides comprehensive research ideas about Edge-AI technology that can assist doctors in making better data-driven decisions and will provide insights to researchers about healthcare industry, trends and future perspective. Examines how healthcare systems of the future will operate, by augmenting clinical resources and ensuring optimal patient outcomes. Provides insight about how Edge-AI is revolutionizing decision making, early warnings for conditions, and visual inspection in healthcare. Highlight trends, challenges, opportunities and future areas where Healthcare informatics deal with accessing vast data sets of potentially life-saving information.

This book is written in a clear and thorough way to cover both the traditional and modern uses of Artificial Intelligence and soft computing. It gives an in-depth look at mathematical models, algorithms, and real-world problems that are hard to solve in MATLAB. The book is intended to provide a broad and in-depth understanding of fuzzy logic controllers, genetic algorithms, neural networks, and hybrid techniques such as ANFIS and the GA-ANN model. Key Features: A detailed description of basic intelligent techniques(Fuzzy logic, Genetic algorithm & neural network using MATLAB) A detailed description of the hybrid intelligent technique: Adaptive fuzzy inference technique(ANFIS) Formulation of the nonlinear model like Analysis of ANOVA & Response Surface Methodology Variety of solved problem on ANOVA & RSM Case studies of above mentioned intelligent techniques on the different process control system This book can be used as a handbook and a guide for students of all engineering disciplines, operational research areas, computer applications, and for various professionals who work in the optimization area.

How could Finance benefit from AI? How can AI techniques provide an edge? Moving well beyond simply speeding up computation, this book tackles AI for Finance from a range of perspectives including business, technology, research, and students. Covering aspects like algorithms, big data, and machine learning, this book answers these and many other questions.

Designed to offer an accessible set of case studies and analyses of ethical dilemmas in data science. This book will be suitable for technical readers in data science who want to understand diverse ethical approaches to AI.

This book explores how to use generative adversarial networks in a variety of applications and emphasises their substantial advancements over traditional generative models. This book's major goal is to concentrate on cutting-edge research in deep learning and generative adversarial networks, which includes creating new tools and methods for processing text, images, and audio. A Generative Adversarial Network (GAN) is a class of machine learning framework and is the next emerging network in deep learning applications. Generative Adversarial Networks(GANs) have the feasibility to build improved models, as they can generate the sample data as per application requirements. There are various applications of GAN in science and technology, including computer vision, security, multimedia and advertisements, image generation, image translation,text-to-images synthesis, video synthesis, generating high-resolution images, drug discovery, etc. Features: Presents a comprehensive guide on how to use GAN for images and videos. Includes case studies of Underwater Image Enhancement Using Generative Adversarial Network, Intrusion detection using GAN Highlights the inclusion of gaming effects using deep learning methods Examines the significant technological advancements in GAN and its real-world application. Discusses as GAN challenges and optimal solutions The book addresses scientific aspects for a wider audience such as junior and senior engineering, undergraduate and postgraduate students, researchers, and anyone interested in the trends development and opportunities in GAN and Deep Learning. The material in the book can serve as a reference in libraries, accreditation agencies, government agencies, and especially the academic institution of higher education intending to launch or reform their engineering curriculum

This edited book comprises chapters that describe the IoT, machine learning, and blockchain technologies for renewable energy and modern hybrid power systems with simulation examples and case studies. After reading this book, users will understand recent technologies such as IoT, machine learning techniques, and blockchain technologies and the application of these technologies to renewable energy resources and modern hybrid power systems through simulation examples and case studies.

This textbook offers a tutorial introduction to robotics and control which is light and easy to absorb. The practice of robotics and control both involve the application of computational algorithms to data. Over the fairly recent history of the fields of robotics and control a very large body of algorithms has been developed. However this body of knowledge is something of a barrier for anybody entering the field, or even looking to see if they want to enter the field - What is the right algorithm for a particular problem?, and importantly: How can I try it out without spending days coding and debugging it from the original research papers? The author has maintained two open-source MATLAB Toolboxes for more than 10 years: one for robotics and one for vision. The key strength of the Toolboxes provides a set of tools that allow the user to work with real problems, not trivial examples. For the student the book makes the algorithms accessible, the Toolbox code can be read to gain understanding, and the examples illustrate how it can be used -instant gratification in just a couple of lines of MATLAB code. The code can also be the starting point for new work, for researchers or students, by writing programs based on Toolbox functions, or modifying the Toolbox code itself. The purpose of this book is to expand on the tutorial material provided with the toolboxes, add many more examples, and to weave this into a narrative that covers robotics and control separately and together. The author shows how complex problems can be decomposed and solved using just a few simple lines of code, and hopefully to inspire up and coming researchers. The topics covered are guided by the real problems observed over many years as a practitioner of both robotics and control. It is written in a light but informative style, it is easy to read and absorb, and includes a lot of Matlab examples and figures. The book is a real walk through the fundamentals of robot kinematics, dynamics and joint level control, and covers both mobile robots (control, path planning, navigation, localization and SLAM) and arm robots (forward and inverse kinematics, Jacobians, dynamics and joint level control). "An authoritative book, reaching across fields, thoughtfully conceived and brilliantly accomplished!" Oussama Khatib, Stanford

Cloud based Multi-Modal Information Analytics: A Hands-on Approach discusses the various modalities of data and provide an aggregated solutions using cloud. It includes the fundamentals of neural networks, different types and how it can be used for the multi-modal information analytics. The various application areas that are image-centric and video are also presented with deployment solutions in the cloud. Features Life cycle of the multi- modal data analytics is discussed with applications of modalities of text, image, and video. Deep Learning fundamentals and architectures covering CNN, RNN and its types for learning for different multi-modal networks. Applications of Multi-Modal Analytics covering Text , Speech, and Image. This book is aimed at researchers in Multi-modal analytics and related areas

Computer vision-based crack-like object detection has many useful applications, such as pavement surface inspection, underground pipeline inspection, bridge cracking monitoring, railway track assessment, etc. However, in most contexts, cracks appear as thin, irregular long-narrow objects, and often are buried into complex, textured background with high diversity which make the crack detection very challenging. During the past a few years, the deep learning technique has achieved great success and has been utilized for solving a variety of object detection problems. However, using deep learning for accurate crack localization is non-trivial. This book discusses crack-like object detection problem in a comprehensive way. It starts by discussing traditional image processing approaches for solving this problem, and then introduces deep learning-based methods. The book provides a comprehensive review of object detection problems and focuses on the most challenging problem, crack-like object detection, to dig deep into the deep learning method. It includes examples of real-world problems, which are easy to understand and could be a good tutorial for introducing computer vision and machine learning.

Technologies such as artificial intelligence have led to significant advances in science and medicine, but have also facilitated new forms of repression, policing and surveillance. AI policy has become without doubt a significant issue of global politics. The Global Politics of Artificial Intelligence tackles some of the issues linked to AI development and use, contributing to a better understanding of the global politics of AI. This is an area where enormous work still needs to be done, and the contributors to this volume provide significant input into this field of study, to policy makers, academics, and society at large. Each of the chapters in this volume works as freestanding contribution, and provides an accessible account of a particular issue linked to AI from a political perspective. Contributors to the volume come from many different areas of expertise, and of the world, and range from emergent to established authors.

This book provides an introduction to the mathematics needed to model, analyze, and design feedback systems. It is an ideal textbook for undergraduate and graduate students, and is indispensable for researchers seeking a self-contained reference on control theory. Unlike most books on the subject, "Feedback Systems" develops transfer functions through the exponential response of a system, and is accessible across a range of disciplines that utilize feedback in physical, biological, information, and economic systems.

Karl Astrom and Richard Murray use techniques from physics, computer science, and operations research to introduce control-oriented modeling. They begin with state space tools for analysis and design, including stability of solutions, Lyapunov functions, reachability, state feedback observability, and estimators. The matrix exponential plays a central role in the analysis of linear control systems, allowing a concise development of many of the key concepts for this class of models. Astrom and Murray then develop and explain tools in the frequency domain, including transfer functions, Nyquist analysis, PID control, frequency domain design, and robustness. They provide exercises at the end of every chapter, and an accompanying electronic solutions manual is available. "Feedback Systems" is a complete one-volume resource for students and researchers in mathematics, engineering, and the sciences.Covers the mathematics needed to model, analyze, and design feedback systems Serves as an introductory textbook for students and a self-contained resource for researchers Includes exercises at the end of every chapter Features an electronic solutions manual Offers techniques applicable across a range of disciplines "

How could Finance benefit from AI? How can AI techniques provide an edge? Moving well beyond simply speeding up computation, this book tackles AI for Finance from a range of perspectives including business, technology, research, and students. Covering aspects like algorithms, big data, and machine learning, this book answers these and many other questions.

This book provides a first-of-its-kind approach for using blockchain to enhance resilience in disaster supply chain and logistics management, especially when dealing with dynamic communication, relief operations, prioritization, coordination, and distribution of scarce resources - these are elements of volatility, uncertainty, complexity, and ambiguity (VUCA) describing a dynamic environment that now form the "new norm" for many leaders. Blockchain-Enabled Resilience: An Integrated Approach for Disaster Supply Chain and Logistics Management analyzes the application of blockchain technology used to enable resilience in a disaster supply chain network. It discusses IoT and DVFS algorithms for developing a network-based simulation and presents advancements in disaster supply chain strategies using smart contacts for collaborations. The book covers how success is based on collaboration, coordination, sovereignty, and equality in distributing resources and offers a theoretical analysis that reveals that enhancing resilience can improve collaboration and communication and can result in more time-efficient processing for disaster supply management. This book provides a first-of-its-kind approach for managers and policy-makers as well as researchers interested in using blockchain to enhance resilience in disaster supply chains, especially when dealing with dynamic communication, relief operations, prioritization, coordination, and distribution of scarce resources. Practical guidance is provided for managers interested in implementation. A robust research agenda is also provided for those interested in expanding present research.

Covers principles of Ionic Polymer Metal Composites (IPMC), manufacturing processes, applications and future possibilities in a systematic manner Highlights IPMC practical applicability in biomedical engineering domain Explores single-walled carbon nanotubes (SWNT) based IPMC soft actuators Discusses IPMC applications in underwater areas Includes IPMC application in robotics focussing on special compliant mechanism

Focuses on several core aspects of Industry 4.0 on computer vision & imaging. Highlights several exciting techniques for disease prediction, NLP, image captioning, flood level assessment, crop classifications, and fabrication of smart wheelchairs. Covers several chapters on Natural Language Processing (NLP), focusing on Bangla language. Chapters presented in a step-by-step manner so that young minds can understand and implement easily.

The book investigates various MPPT algorithms, and the optimization of solar energy using machine learning and deep learning. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in diverse engineering domains including electrical, electronics and communication, computer, and environmental. This book: Discusses data acquisition by the internet of things for real-time monitoring of solar cells. Covers artificial neural network techniques, solar collector optimization, and artificial neural network applications in solar heaters, and solar stills. Details solar analytics, smart centralized control centers, integration of microgrids, and data mining on solar data. Highlights the concept of asset performance improvement, effective forecasting for energy production, and Low-power wide-area network applications. Elaborates solar cell design principles, the equivalent circuits of single and two diode models, measuring idealist factors, and importance of series and shunt resistances. The text elaborates solar cell design principles, the equivalent circuit of single diode model, the equivalent circuit of two diode model, measuring idealist factor, and importance of series and shunt resistances. It further discusses perturb and observe technique, modified P&O method, incremental conductance method, sliding control method, genetic algorithms, and neuro-fuzzy methodologies. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in diverse engineering domains including electrical, electronics and communication, computer, and environmental.

Discusses advancements in the field of Human Machine Interface. Provides practical knowledge in biomedical signal processing, AI and ML using MATLAB. Introduces biomedical signals for HMI applications. Discusses Augmented Reality/Virtual reality based HMI. Explores advancements in nanotechnology, user interface design and interactive systems.

Explores text mining and IoT applications for monitoring and controlling smart industrial systems Describes the key principles and techniques for Big-data analytics, security, and optimization for industrial applications. Provides context-aware insights, human-centric industry, smart computing for next-generation industry

Artificial Intelligence for Capital Market throws light on application of AI/ML techniques in the financial capital markets. This book discusses the challenges posed by the AI/ML techniques as these are prone to "black box" syndrome. The complexity of understanding the underlying dynamics for results generated by these methods is one of the major concerns which is highlighted in this book: Features: Showcases artificial intelligence in finance service industry Explains Credit and Risk Analysis Elaborates on cryptocurrencies and blockchain technology Focuses on optimal choice of asset pricing model Introduces Testing of market efficiency and Forecasting in Indian Stock Market This book serves as a reference book for Academicians, Industry Professional, Traders, Finance Mangers and Stock Brokers. It may also be used as textbook for graduate level courses in financial services and financial Analytics.

Directs the attention to the smart digital healthcare system in this COVID-19 pandemic. Simulates novel investigations and how they will be beneficial in understanding the pandemic. Presents the latest ideas developed for data scientists, doctors, engineers, and economists. Analyses the various issues related to computing, AI apps, big data analytic techniques, and predictive scientific skill gaps. Explains some interesting and diverse types of challenges and data-driven healthcare applications.