Artificial Intelligence in the Age of Neural Networks and Brain Computing demonstrates that existing disruptive implications and applications of AI is a development of the unique attributes of neural networks, mainly machine learning, distributed architectures, massive parallel processing, black-box inference, intrinsic nonlinearity and smart autonomous search engines. The book covers the major basic ideas of brain-like computing behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as future alternatives. The success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel and Amazon can be interpreted using this book.

Over the last two decades, researchers are looking at imbalanced data learning as a prominent research area. Many critical real-world application areas like finance, health, network, news, online advertisement, social network media, and weather have imbalanced data, which emphasizes the research necessity for real-time implications of precise fraud/defaulter detection, rare disease/reaction prediction, network intrusion detection, fake news detection, fraud advertisement detection, cyber bullying identification, disaster events prediction, and more. Machine learning algorithms are based on the heuristic of equally-distributed balanced data and provide the biased result towards the majority data class, which is not acceptable considering imbalanced data is omnipresent in real-life scenarios and is forcing us to learn from imbalanced data for foolproof application design. Imbalanced data is multifaceted and demands a new perception using the novelty at sampling approach of data preprocessing, an active learning approach, and a cost perceptive approach to resolve data imbalance. The Handbook of Research on Data Preprocessing, Active Learning, and Cost Perceptive Approaches for Resolving Data Imbalance offers new aspects for imbalanced data learning by providing the advancements of the traditional methods, with respect to big data, through case studies and research from experts in academia, engineering, and industry. The chapters provide theoretical frameworks and the latest empirical research findings that help to improve the understanding of the impact of imbalanced data and its resolving techniques based on data preprocessing, active learning, and cost perceptive approaches. This book is ideal for data scientists, data analysts, engineers, practitioners, researchers, academicians, and students looking for more information on imbalanced data characteristics and solutions using varied approaches.

Source Separation and Machine Learning presents the fundamentals in adaptive learning algorithms for Blind Source Separation (BSS) and emphasizes the importance of machine learning perspectives. It illustrates how BSS problems are tackled through adaptive learning algorithms and model-based approaches using the latest information on mixture signals to build a BSS model that is seen as a statistical model for a whole system. Looking at different models, including independent component analysis (ICA), nonnegative matrix factorization (NMF), nonnegative tensor factorization (NTF), and deep neural network (DNN), the book addresses how they have evolved to deal with multichannel and single-channel source separation.

This timely book presents a detailed analysis of the role of law and regulation in the utilisation of Artificial Intelligence (AI) in the media sector. As well as contributing to the wider discussion on law and AI, the book also digs deeper by exploring pressing issues at the intersections of AI, media, and the law. Chapters critically re-examine various rights and responsibilities from the perspectives of incentives for accountable utilisation of AI in the industry. Featuring chapters from leading scholars in the field, Artificial Intelligence and the Media provides a timely and in-depth research-based contribution to complex themes - especially at the interface of new technology (including AI) with media and regulation. Analysing both legislative and ethical solutions, chapters explore what "AI" and "accountability" mean in terms of media practices, principles, and power relations, as well as how to address the AI revolution with informed law and policy in order to incentivise accountable utilisation of AI and to reduce negative societal impacts. Offering ideas for further research in the area, this book is key reading for academics and researchers in the fields of information and media law, regulation, and technology law. It may also interest media law practitioners, with research-based guidance for everyday practices and tools to prepare for future developments in the area.

Special Forces are a key component of every modern army, capable of carrying out clandestine operations, reconnaissance, and incisive attacks behind enemy lines. Units such as the British SAS, US Navy SEALs, the US Army’s Delta Force, Polish GROM and the France’s National Gendarmerie Intervention Group are famous for their bravery and formidable record. Aircraft are a key element of their functionality, without which Special Forces would not be able to move quickly to the combat zone. Arranged into chapters divided by transports, gunships, helicopters, and unmanned aerial vehicles, the book includes the AC-130H gunship, which can be armed with weapons such as the M61 Vulcan rotary cannon and can destroy ground targets from a range of 2,000 metres; the CV-22 Osprey tiltrotor aircraft, which can land large numbers of men and material in tight spaces because of its STOL capabilities; the Eurocopter AS365 Dauphin II, used by the British Joint Special Forces Aviation Wing (JSFAW) for the insertion of small units behind enemy lines; and the Mil Mi- 171Sh Storm rotorcraft, used by the Russian Spetsnaz commandos for operations in difficult terrain. Illustrated with 140 photographs and artworks, Aircraft of the Special Forces is a dynamic guide to the specialist aircraft and UAVs deployed by Special Forces throughout the world today.

There is no doubt that there has been much excitement regarding the pioneering contributions of artificial intelligence (AI), the internet of things (IoT), and blockchain technologies and tools in visualizing and realizing smarter as well as sophisticated systems and services. However, researchers are being bombarded with various machine and deep learning algorithms, which are categorized as a part and parcel of the enigmatic AI discipline. The knowledge discovered gets disseminated to actuators and other concerned systems in order to empower them to intelligently plan and insightfully execute appropriate tasks with clarity and confidence. The IoT processes in conjunction with the AI algorithms and blockchain technology are bound to lay out a stimulating foundation for producing and sustaining smarter systems for society. The Handbook of Research on Smarter and Secure Industrial Applications Using AI, IoT, and Blockchain Technology articulates and accentuates various AI algorithms, fresh innovations in the IoT, and blockchain spaces. The domain of transforming raw data to information and to relevant knowledge is gaining prominence with the availability of data ingestion, processing, mining, analytics algorithms, platforms, frameworks, and other accelerators. Covering topics such as blockchain applications, Industry 4.0, and cryptography, this book serves as a comprehensive guide for AI researchers, faculty members, IT professionals, academicians, students, researchers, and industry professionals.

Artificial intelligence (AI) describes machines/computers that mimic cognitive functions that humans associate with other human minds, such as learning and problem solving. As businesses have evolved to include more automation of processes, it has become more vital to understand AI and its various applications. Additionally, it is important for workers in the marketing industry to understand how to coincide with and utilize these techniques to enhance and make their work more efficient. The Handbook of Research on Applied AI for International Business and Marketing Applications is a critical scholarly publication that provides comprehensive research on artificial intelligence applications within the context of international business. Highlighting a wide range of topics such as diversification, risk management, and artificial intelligence, this book is ideal for marketers, business professionals, academicians, practitioners, researchers, and students.

Research on artificial life is critical to solving various dynamic obstacles individuals face on a daily basis. From electric wheelchairs to navigation, artificial life can play a role in improving both the simple and complex aspects of civilian life. The Handbook of Research on Investigations in Artificial Life Research and Development is a vital scholarly reference source that examines emergent research in handling real-world problems through the application of various computation technologies and techniques. Examining topics such as computational intelligence, multi-agent systems, and fuzzy logic, this publication is a valuable resource for academicians, scientists, researchers, and individuals interested in artificial intelligence developments.

Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications covers timely topics, including the neural network (NN), particle swarm optimization (PSO), evolutionary algorithm (GA), fuzzy sets (FS) and rough sets (RS), etc. Furthermore, the book highlights recent research on representative techniques to elaborate how a data-centric system formed a powerful platform for the processing of cloud hosted multimedia big data and how it could be analyzed, processed and characterized by CI. The book also provides a view on how techniques in CI can offer solutions in modeling, relationship pattern recognition, clustering and other problems in bioengineering. It is written for domain experts and developers who want to understand and explore the application of computational intelligence aspects (opportunities and challenges) for design and development of a data-centric system in the context of multimedia cloud, big data era and its related applications, such as smarter healthcare, homeland security, traffic control trading analysis and telecom, etc. Researchers and PhD students exploring the significance of data centric systems in the next paradigm of computing will find this book extremely useful.

In today's modernized world, the field of healthcare has seen significant practical innovations with the implementation of computational intelligence approaches and soft computing methods. These two concepts present various solutions to complex scientific problems and imperfect data issues. This has made both very popular in the medical profession. There are still various areas to be studied and improved by these two schemes as healthcare practices continue to develop. Computational Intelligence and Soft Computing Applications in Healthcare Management Science is an essential reference source that discusses the implementation of soft computing techniques and computational methods in the various components of healthcare, telemedicine, and public health. Featuring research on topics such as analytical modeling, neural networks, and fuzzy logic, this book is ideally designed for software engineers, information scientists, medical professionals, researchers, developers, educators, academicians, and students.

The application of artificial intelligence technology to 5G wireless communications is now appropriate to address the design of optimized physical layers, complicated decision-making, network management, and resource optimization tasks within networks. In exploring 5G wireless technologies and communication systems, artificial intelligence is a powerful tool and a research topic with numerous potential fields of application that require further study. Applications of Artificial Intelligence in Wireless Communication Systems explores the applications of artificial intelligence for the optimization of wireless communication systems, including channel models, channel state estimation, beamforming, codebook design, signal processing, and more. Covering key topics such as neural networks, deep learning, and wireless systems, this reference work is ideal for computer scientists, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.

Fractional Order Systems: Optimization, Control, Circuit Realizations and Applications consists of 21 contributed chapters by subject experts. Chapters offer practical solutions and novel methods for recent research problems in the multidisciplinary applications of fractional order systems, such as FPGA, circuits, memristors, control algorithms, photovoltaic systems, robot manipulators, oscillators, etc. This book is ideal for researchers working in the modeling and applications of both continuous-time and discrete-time dynamics and chaotic systems. Researchers from academia and industry who are working in research areas such as control engineering, electrical engineering, mechanical engineering, computer science, and information technology will find the book most informative.

While human capabilities can withstand broad levels of strain, they cannot hope to compete with the advanced abilities of automated technologies. Developing advanced robotic systems will provide a better, faster means to produce goods and deliver a level of seamless communication and synchronization that exceeds human skill. Advanced Robotics and Intelligent Automation in Manufacturing is a pivotal reference source that provides vital research on the application of advanced manufacturing technologies in regards to production speed, quality, and innovation. While highlighting topics such as human-machine interaction, quality management, and sensor integration, this publication explores state-of-the-art technologies in the field of robotics engineering as well as human-robot interaction. This book is ideally designed for researchers, students, engineers, manufacturers, managers, industry professionals, and academicians seeking to enhance their innovative design capabilities.

Internet of things (IoT) is an emerging research field that is rapidly becoming an important part of our everyday lives including home automation, smart buildings, smart things, and more. This is due to cheap, efficient, and wirelessly-enabled circuit boards that are enabling the functions of remote sensing/actuating, decentralization, autonomy, and other essential functions. Moreover, with the advancements in embedded artificial intelligence, these devices are becoming more self-aware and autonomous, hence making decisions themselves. Current research is devoted to the understanding of how decision support systems are integrated into industrial IoT. Decision Support Systems and Industrial IoT in Smart Grid, Factories, and Cities presents the internet of things and its place during the technological revolution, which is taking place now to bring us a better, sustainable, automated, and safer world. This book also covers the challenges being faced such as relations and implications of IoT with existing communication and networking technologies; applications like practical use-case scenarios from the real world including smart cities, buildings, and grids; and topics such as cyber security, user privacy, data ownership, and information handling related to IoT networks. Additionally, this book focuses on the future applications, trends, and potential benefits of this new discipline. This book is essential for electrical engineers, computer engineers, researchers in IoT, security, and smart cities, along with practitioners, researchers, academicians, and students interested in all aspects of industrial IoT and its applications.

Competition in today's global market offers strong motivation for the development of sophisticated tools within computer science. The neuron multi-functional technology platform is a developing field of study that regards the various interactive approaches that can be applied within this subject matter. As advancing technologies continue to emerge, managers and researchers need a compilation of research that discusses the advancements and specific implementations of these intelligent approaches with this platform. Avatar-Based Control, Estimation, Communications, and Development of Neuron Multi-Functional Technology Platforms is a pivotal reference source that provides vital research on the application of artificial and natural approaches towards neuron-based programs. While highlighting topics such as natural intelligence, neurolinguistics, and smart data storage, this publication presents techniques, case studies, and methodologies that combine the use of intelligent artificial and natural approaches with optimization techniques for facing problems and combines many types of hardware and software with a variety of communication technologies to enable the development of innovative applications. This book is ideally designed for researchers, practitioners, scientists, field experts, professors, and students seeking current research on the optimization of avatar-based advancements in multifaceted technology systems.

It is crucial that forensic science meets challenges such as identifying hidden patterns in data, validating results for accuracy, and understanding varying criminal activities in order to be authoritative so as to hold up justice and public safety. Artificial intelligence, with its potential subsets of machine learning and deep learning, has the potential to transform the domain of forensic science by handling diverse data, recognizing patterns, and analyzing, interpreting, and presenting results. Machine Learning and deep learning frameworks, with developed mathematical and computational tools, facilitate the investigators to provide reliable results. Further study on the potential uses of these technologies is required to better understand their benefits. Aiding Forensic Investigation Through Deep Learning and Machine Learning Frameworks provides an outline of deep learning and machine learning frameworks and methods for use in forensic science to produce accurate and reliable results to aid investigation processes. The book also considers the challenges, developments, advancements, and emerging approaches of deep learning and machine learning. Covering key topics such as biometrics, augmented reality, and fraud investigation, this reference work is crucial for forensic scientists, law enforcement, computer scientists, researchers, scholars, academicians, practitioners, instructors, and students.

Communication based on the internet of things (IoT) generates huge amounts of data from sensors over time, which opens a wide range of applications and areas for researchers. The application of analytics, machine learning, and deep learning techniques over such a large volume of data is a very challenging task. Therefore, it is essential to find patterns, retrieve novel insights, and predict future behavior using this large amount of sensory data. Artificial intelligence (AI) has an important role in facilitating analytics and learning in the IoT devices. Applying AI-Based IoT Systems to Simulation-Based Information Retrieval provides relevant frameworks and the latest empirical research findings in the area. It is ideal for professionals who wish to improve their understanding of the strategic role of trust at different levels of the information and knowledge society and trust at the levels of the global economy, networks and organizations, teams and work groups, information systems, and individuals as actors in the networked environments. Covering topics such as blockchain visualization, computer-aided drug discovery, and health monitoring, this premier reference source is an excellent resource for business leaders and executives, IT managers, security professionals, data scientists, students and faculty of higher education, librarians, hospital administrators, researchers, and academicians.