The book presents selected papers from the 18th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, held on December 16–18, 2022, in Kitakyushu, Japan. It is divided into two volumes and discusses latest research outcomes in the field of Information Technology (IT) including but not limited to information hiding, multimedia signal processing, big data, data mining, bioinformatics, database, industrial and internet of things, and their applications.

This volume addresses selected aerothermodynamic design problems for three vehicle classes: winged reentry, non-winged reentry, and airbreathing hypersonic flight vehicles. Following an introductory chapter, the book presents the basics of flight trajectory mechanics, giving the aerothermodynamicist an understanding of the principal issues relevant to the field. In the following chapters, specific aerothermodynamic phenomena are discussed for the three vehicle classes, major simulation problems are singled out, and particular trends are examined. Available coefficients of longitudinal motion are presented for a variety of shapes of operational and studied vehicles, and aerothermodynamic issues of stabilization, trim, and control devices are treated.

Soft Computing in Green and Renewable Energy Systems provides a practical introduction to the application of soft computing techniques and hybrid intelligent systems for designing, modeling, characterizing, optimizing, forecasting, and performance prediction of green and renewable energy systems. Research is proceeding at jet speed on renewable energy (energy derived from natural resources such as sunlight, wind, tides, rain, geothermal heat, biomass, hydrogen, etc.) as policy makers, researchers, economists, and world agencies have joined forces in finding alternative sustainable energy solutions to current critical environmental, economic, and social issues. The innovative models, environmentally benign processes, data analytics, etc. employed in renewable energy systems are computationally-intensive, non-linear and complex as well as involve a high degree of uncertainty. Soft computing technologies, such as fuzzy sets and systems, neural science and systems, evolutionary algorithms and genetic programming, and machine learning, are ideal in handling the noise, imprecision, and uncertainty in the data, and yet achieve robust, low-cost solutions. As a result, intelligent and soft computing paradigms are finding increasing applications in the study of renewable energy systems. Researchers, practitioners, undergraduate and graduate students engaged in the study of renewable energy systems will find this book very useful.

This book comprises the select proceedings of the International Conference in Power, Energy, Control, Signals and Systems (IPECS) 2022. The book focuses on intelligent solutions for smart grids and smart cities. The content of this book is designed to develop many innovative ideas for an energy-efficient and sustainable future. It focuses on recent technological advances and challenges in the field of grid integration of renewable energy resources, AI/ML in power and energy systems, security enhancement of power systems/electronics using advanced ML techniques for integration of renewable energies, electric vehicle-energy storage, and battery charging technologies, etc.

This book comprises proceedings of the 2022 International Forum “Science and Global Challenges of the XXI Century”. The main principle of the Forum’s program is interdisciplinarity, the formation of end-to-end innovation chains: fundamental and applied research, technology development, implementation, and wide application of networks and systems. In 2022, the central theme of the forum is innovations and technologies in interdisciplinary applications. The book covers a wide range of knowledge-communication methodologies and effective technologies for processing data in various forms and areas.

This book presents advances on the state of the art in smart cities systems and applications based on the proof of concept and prototyping for smart cities in an interdisciplinary context of engineering and information sciences. Smart cities have emerged as highly complex technological endeavors that combine knowledge and technology from many disciplines ranging from information sciences to engineering. Due to their complex nature, the modeling, development, and prototyping of applications in smart cities present a myriad of challenges, including technical, economic, and social ones, across application subdomains such as smart transportation, social welfare, tourism, and smart industry. It becomes difficult or sometimes impossible to provide a solution for such potential research issues and challenges from a traditional disciplinary-approach only; to tackle such research issues and to make the paradigm of smart cities a reality, interdisciplinary approaches are deemed necessary. Readers, developers, practitioners, and policy-makers in the field find in the book insights, experiences, findings, and perspectives on smart cities applications with an emphasis on real-life prototyping, beyond the confines of laboratory experiments.

This book systematically discusses the intelligent scheduling problem of complex semiconductor manufacturing systems from theory to method and then to application. The main contents include data-driven scheduling framework of semiconductor manufacturing system, data preprocessing of semiconductor manufacturing system, correlation analysis of performance index of semiconductor production line, intelligent release control strategy, dynamic dispatching rules simulating pheromone mechanism, and load balancing dynamic scheduling of semiconductor production line, performance index-driven dynamic scheduling method of semiconductor production line, scheduling trend of semi-conductor manufacturing system in big data environment.

The two volume set CCIS 775 and 776 constitutes the refereed proceedings of the First International Conference on Computational Intelligence, Communications, and Business Analytics, CICBA 2017, held in Kolkata, India, in March 2017.
The 90 revised full papers presented in the two volumes were carefully reviewed and selected from 276 submissions. The papers are organized in topical sections on data science and advanced data analytics; signal processing and communications; microelectronics, sensors, intelligent networks; computational forensics (privacy and security); computational intelligence in bio-computing; computational intelligence in mobile and quantum computing; intelligent data mining and data warehousing; computational intelligence.

This book (proceedings of ISMS 2022) is intended to be used as a reference by students and researchers who collect scientific and technical contributions with respect to models, tools, technologies and applications in the field of information systems and management science. This textbook shows how to exploit information systems in a technology-rich management field. The book introduces concepts, principles, methods, and procedures that will be valuable to students and scholars in thinking about existing organization systems, proposing new systems, and working with management professionals in implementing new information systems.

This book addresses many applications of artificial intelligence in robotics, namely AI using visual and motional input. Robotic technology has made significant contributions to daily living, industrial uses, and medicinal applications. Machine learning, in particular, is critical for intelligent robots or unmanned/autonomous systems such as UAVs, UGVs, UUVs, cooperative robots, and so on. Humans are distinguished from animals by capacities such as receiving visual information, adjusting to uncertain circumstances, and making decisions to take action in a complex system. Significant progress has been made in robotics toward human-like intelligence; yet, there are still numerous unresolved issues. Deep learning, reinforcement learning, real-time learning, swarm intelligence, and other developing approaches such as tiny-ML have been developed in recent decades and used in robotics.

This book addresses many applications of artificial intelligence in robotics, namely AI using visual and motional input. Robotic technology has made significant contributions to daily living, industrial uses, and medicinal applications. Machine learning, in particular, is critical for intelligent robots or unmanned/autonomous systems such as UAVs, UGVs, UUVs, cooperative robots, and so on. Humans are distinguished from animals by capacities such as receiving visual information, adjusting to uncertain circumstances, and making decisions to take action in a complex system. Significant progress has been made in robotics toward human-like intelligence; yet, there are still numerous unresolved issues. Deep learning, reinforcement learning, real-time learning, swarm intelligence, and other developing approaches such as tiny-ML have been developed in recent decades and used in robotics.

This book comprises the proceedings of the 4th International Conference on Machine Intelligence and Signal Processing (MISP2022). The contents of this book focus on research advancements in machine intelligence, signal processing, and applications. The book covers the real-time challenges involved while processing big data analytics and stream processing with the integration of smart data computing services and interconnectivity. It also includes the progress in signal processing to process the normal and abnormal categories of real-world signals such as signals generated from IoT devices, smart systems, speech, videos and involves biomedical signal processing: electrocardiogram (ECG), electroencephalogram (EEG), magnetoencephalography (MEG), electromyogram (EMG), etc. This book proves to be a valuable resource for those in academia and industry.

This book comprises the proceedings of the 4th International Conference on Machine Intelligence and Signal Processing (MISP2022). The contents of this book focus on research advancements in machine intelligence, signal processing, and applications. The book covers the real-time challenges involved while processing big data analytics and stream processing with the integration of smart data computing services and interconnectivity. It also includes the progress in signal processing to process the normal and abnormal categories of real-world signals such as signals generated from IoT devices, smart systems, speech, videos and involves biomedical signal processing: electrocardiogram (ECG), electroencephalogram (EEG), magnetoencephalography (MEG), electromyogram (EMG), etc. This book proves to be a valuable resource for those in academia and industry.

Knowledge-Driven Computing constitutes an emerging area of intensive research located at the intersection of Computational Intelligence and Knowledge Engineering with strong mathematical foundations. It embraces methods and approaches coming from diverse computational paradigms, such as evolutionary computation and nature-inspired algorithms, logic programming and constraint programming, rule-based systems, fuzzy sets and many others. The use of various knowledge representation formalisms and knowledge processing and computing paradigms is oriented towards the efficient resolution of computationally complex and difficult problems.

Scilab is a scientific software package that provides a powerful open computing environment for engineering and scientific applications. Distributed freely via the Internet since 1994, Scilab is currently being used in educational and industrial environments around the world.