As technology spreads globally, researchers and scientists continue to develop and study the strategy behind creating artificial life. This research field is ever expanding, and it is essential to stay current in the contemporary trends in artificial life, artificial intelligence, and machine learning. This an important topic for researchers and scientists in the field as well as industry leaders who may adapt this technology. The Handbook of Research on New Investigations in Artificial Life, AI, and Machine Learning provides concepts, theories, systems, technologies, and procedures that exhibit properties, phenomena, or abilities of any living system or human. This major reference work includes the most up-to-date research on techniques and technologies supporting AI and machine learning. Covering topics such as behavior classification, quality control, and smart medical devices, it serves as an essential resource for graduate students, academicians, stakeholders, practitioners, and researchers and scientists studying artificial life, cognition, AI, biological inspiration, machine learning, and more.

Handbook of Pediatric Brain Imaging: Methods and Applications presents state-of-the-art research on pediatric brain image acquisition and analysis from a broad range of imaging modalities, including MRI, EEG and MEG. With rapidly developing methods and applications of MRI, this book strongly emphasizes pediatric brain MRI, elaborating on the sub-categories of structure MRI, diffusion MRI, functional MRI, perfusion MRI and other MRI methods. It integrates a pediatric brain imaging perspective into imaging acquisition and analysis methods, covering head motion, small brain sizes, small cerebral blood flow of neonates, dynamic cortical gyrification, white matter tract growth, and much more.

Cognitive Models for Sustainable Environment reviews the fundamental concepts of gathering, processing and analyzing data from batch processes, along with a review of intelligent and cognitive tools that can be used. The book is centered on evolving novel intelligent/cognitive models and algorithms to develop sustainable solutions for the mitigation of environmental pollution. It unveils intelligent and cognitive models to address issues related to the effective monitoring of environmental pollution and sustainable environmental design. As such, the book focuses on the overall well-being of the global environment for better sustenance and livelihood. The book covers novel cognitive models for effective environmental pollution data management at par with the standards laid down by the World Health Organization. Every chapter is supported by real-life case studies, illustrative examples and video demonstrations that enlighten readers.

Introduction to BiomedicalImaging A state-of-the-art exploration of the foundations and latest developments in biomedical imaging technology In the newly revised second edition of Introduction to Biomedical Imaging, distinguished researcher Dr. Andrew Webb delivers a comprehensive description of the fundamentals and applications of the most important current medical imaging techniques: X-ray and computed tomography, nuclear medicine, ultrasound, magnetic resonance imaging, and various optical-based methods. Each chapter explains the physical principles, instrument design, data acquisition, image reconstruction, and clinical applications of its respective modality. This latest edition incorporates descriptions of recent developments in photon counting CT, total body PET, superresolution-based ultrasound, phased-array MRI technology, optical coherence tomography, and iterative and model-based image reconstruction techniques. The final chapter discusses the increasing role of artificial intelligence/deep learning in biomedical imaging. The text also includes a thorough introduction to general image characteristics, including discussions of signal-to-noise and contrast-to-noise. Perfect for graduate and senior undergraduate students of biomedical engineering, Introduction to Biomedical Imaging, 2nd Edition will also earn a place in the libraries of medical imaging professionals with an interest in medical imaging techniques.

The artificial intelligence subset machine learning has become a popular technique in professional fields as many are finding new ways to apply this trending technology into their everyday practices. Two fields that have majorly benefited from this are pattern recognition and information security. The ability of these intelligent algorithms to learn complex patterns from data and attain new performance techniques has created a wide variety of uses and applications within the data security industry. There is a need for research on the specific uses machine learning methods have within these fields, along with future perspectives. Machine Learning Techniques for Pattern Recognition and Information Security is a collection of innovative research on the current impact of machine learning methods within data security as well as its various applications and newfound challenges. While highlighting topics including anomaly detection systems, biometrics, and intrusion management, this book is ideally designed for industrial experts, researchers, IT professionals, network developers, policymakers, computer scientists, educators, and students seeking current research on implementing machine learning tactics to enhance the performance of information security.

Mobile Edge Artificial Intelligence: Opportunities and Challenges presents recent advances in wireless technologies and nonconvex optimization techniques for designing efficient edge AI systems. The book includes comprehensive coverage on modeling, algorithm design and theoretical analysis. Through typical examples, the powerfulness of this set of systems and algorithms is demonstrated, along with their abilities to make low-latency, reliable and private intelligent decisions at network edge. With the availability of massive datasets, high performance computing platforms, sophisticated algorithms and software toolkits, AI has achieved remarkable success in many application domains. As such, intelligent wireless networks will be designed to leverage advanced wireless communications and mobile computing technologies to support AI-enabled applications at various edge mobile devices with limited communication, computation, hardware and energy resources.

The field of computational intelligence has grown tremendously over that past five years, thanks to evolving soft computing and artificial intelligent methodologies, tools and techniques for envisaging the essence of intelligence embedded in real life observations. Consequently, scientists have been able to explain and understand real life processes and practices which previously often remain unexplored by virtue of their underlying imprecision, uncertainties and redundancies, and the unavailability of appropriate methods for describing the incompleteness and vagueness of information represented. With the advent of the field of computational intelligence, researchers are now able to explore and unearth the intelligence, otherwise insurmountable, embedded in the systems under consideration. Computational Intelligence is now not limited to only specific computational fields, it has made inroads in signal processing, smart manufacturing, predictive control, robot navigation, smart cities, and sensor design to name a few. Recent Trends in Computational Intelligence Enabled Research: Theoretical Foundations and Applications explores the use of this computational paradigm across a wide range of applied domains which handle meaningful information. Chapters investigate a broad spectrum of the applications of computational intelligence across different platforms and disciplines, expanding our knowledge base of various research initiatives in this direction. This volume aims to bring together researchers, engineers, developers and practitioners from academia and industry working in all major areas and interdisciplinary areas of computational intelligence, communication systems, computer networks, and soft computing.

The digital world is characterized by its immediacy, its density of information and its omnipresence, in contrast to the concrete world. Significant changes will occur in our society as AI becomes integrated into many aspects of our lives. This book focuses on this vision of universalization by dealing with the development and framework of AI applicable to all. It develops a moral framework based on a neo-Darwinian approach - the concept of Ethics by Evolution - to accompany AI by observing a certain number of requirements, recommendations and rules at each stage of design, implementation and use. The societal responsibility of artificial intelligence is an essential step towards ethical, eco-responsible and trustworthy AI, aiming to protect and serve people and the common good in a beneficial way.

State of the Art in Neural Networks and Their Applications presents the latest advances in artificial neural networks and their applications across a wide range of clinical diagnoses. Advances in the role of machine learning, artificial intelligence, deep learning, cognitive image processing and suitable data analytics useful for clinical diagnosis and research applications are covered, including relevant case studies. The application of Neural Network, Artificial Intelligence, and Machine Learning methods in biomedical image analysis have resulted in the development of computer-aided diagnostic (CAD) systems that aim towards the automatic early detection of several severe diseases. State of the Art in Neural Networks and Their Applications is presented in two volumes. Volume 1 covers the state-of-the-art deep learning approaches for the detection of renal, retinal, breast, skin, and dental abnormalities and more.

Deep Learning for Chest Radiographs enumerates different strategies implemented by the authors for designing an efficient convolution neural network-based computer-aided classification (CAC) system for binary classification of chest radiographs into "Normal" and "Pneumonia." Pneumonia is an infectious disease mostly caused by a bacteria or a virus. The prime targets of this infectious disease are children below the age of 5 and adults above the age of 65, mostly due to their poor immunity and lower rates of recovery. Globally, pneumonia has prevalent footprints and kills more children as compared to any other immunity-based disease, causing up to 15% of child deaths per year, especially in developing countries. Out of all the available imaging modalities, such as computed tomography, radiography or X-ray, magnetic resonance imaging, ultrasound, and so on, chest radiographs are most widely used for differential diagnosis between Normal and Pneumonia. In the CAC system designs implemented in this book, a total of 200 chest radiograph images consisting of 100 Normal images and 100 Pneumonia images have been used. These chest radiographs are augmented using geometric transformations, such as rotation, translation, and flipping, to increase the size of the dataset for efficient training of the Convolutional Neural Networks (CNNs). A total of 12 experiments were conducted for the binary classification of chest radiographs into Normal and Pneumonia. It also includes in-depth implementation strategies of exhaustive experimentation carried out using transfer learning-based approaches with decision fusion, deep feature extraction, feature selection, feature dimensionality reduction, and machine learning-based classifiers for implementation of end-to-end CNN-based CAC system designs, lightweight CNN-based CAC system designs, and hybrid CAC system designs for chest radiographs. This book is a valuable resource for academicians, researchers, clinicians, postgraduate and graduate students in medical imaging, CAC, computer-aided diagnosis, computer science and engineering, electrical and electronics engineering, biomedical engineering, bioinformatics, bioengineering, and professionals from the IT industry.

Artificial Intelligence for Future Generation Robotics offers a vision for potential future robotics applications for AI technologies. Each chapter includes theory and mathematics to stimulate novel research directions based on the state-of-the-art in AI and smart robotics. Organized by application into ten chapters, this book offers a practical tool for researchers and engineers looking for new avenues and use-cases that combine AI with smart robotics. As we witness exponential growth in automation and the rapid advancement of underpinning technologies, such as ubiquitous computing, sensing, intelligent data processing, mobile computing and context aware applications, this book is an ideal resource for future innovation.

Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications illustrates recent advances in the field of mem-elements (memristor, memcapacitor, meminductor) and their applications in nonlinear dynamical systems, computer science, analog and digital systems, and in neuromorphic circuits and artificial intelligence. The book is mainly devoted to recent results, critical aspects and perspectives of ongoing research on relevant topics, all involving networks of mem-elements devices in diverse applications. Sections contribute to the discussion of memristive materials and transport mechanisms, presenting various types of physical structures that can be fabricated to realize mem-elements in integrated circuits and device modeling. As the last decade has seen an increasing interest in recent advances in mem-elements and their applications in neuromorphic circuits and artificial intelligence, this book will attract researchers in various fields.

Computer-Aided Oral and Maxillofacial Surgery: Developments, Applications, and Future Perspectives is an ideal resource for biomedical engineers and computer scientists, clinicians and clinical researchers looking for an understanding on the latest technologies applied to oral and maxillofacial surgery. In facial surgery, computer-aided decisions supplement all kind of treatment stages, from a diagnosis to follow-up examinations. This book gives an in-depth overview of state-of-the-art technologies, such as deep learning, augmented reality, virtual reality and intraoperative navigation, as applied to oral and maxillofacial surgery. It covers applications of facial surgery that are at the interface between medicine and computer science. Examples include the automatic segmentation and registration of anatomical and pathological structures, like tumors in the facial area, intraoperative navigation in facial surgery and its recent developments and challenges for treatments like zygomatic implant placement.

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.

Intelligence Science: Leading the Age of Intelligence covers the emerging scientific research on the theory and technology of intelligence, bringing together disciplines such as neuroscience, cognitive science, and artificial intelligence to study the nature of intelligence, the functional simulation of intelligent behavior, and the development of new intelligent technologies. The book presents this complex, interdisciplinary area of study in an accessible volume, introducing foundational concepts and methods, and presenting the latest trends and developments. Chapters cover the Foundations of neurophysiology, Neural computing, Mind models, Perceptual intelligence, Language cognition, Learning, Memory, Thought, Intellectual development and cognitive structure, Emotion and affect, and more. This volume synthesizes a very rich and complex area of research, with an aim of stimulating new lines of enquiry.

Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Volume 122 delves into arti?cial Intelligence and the growth it has seen with the advent of Deep Neural Networks (DNNs) and Machine Learning. Updates in this release include chapters on Hardware accelerator systems for artificial intelligence and machine learning, Introduction to Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Deep Learning with GPUs, Edge Computing Optimization of Deep Learning Models for Specialized Tensor Processing Architectures, Architecture of NPU for DNN, Hardware Architecture for Convolutional Neural Network for Image Processing, FPGA based Neural Network Accelerators, and much more.

Machine reading comprehension (MRC) is a cutting-edge technology in natural language processing (NLP). MRC has recently advanced significantly, surpassing human parity in several public datasets. It has also been widely deployed by industry in search engine and quality assurance systems. Machine Reading Comprehension: Algorithms and Practice performs a deep-dive into MRC, offering a resource on the complex tasks this technology involves. The title presents the fundamentals of NLP and deep learning, before introducing the task, models, and applications of MRC. This volume gives theoretical treatment to solutions and gives detailed analysis of code, and considers applications in real-world industry. The book includes basic concepts, tasks, datasets, NLP tools, deep learning models and architecture, and insight from hands-on experience. In addition, the title presents the latest advances from the past two years of research. Structured into three sections and eight chapters, this book presents the basis of MRC; MRC models; and hands-on issues in application. This book offers a comprehensive solution for researchers in industry and academia who are looking to understand and deploy machine reading comprehension within natural language processing.

INTELLIGENT SECURITY SYSTEMS Dramatically improve your cybersecurity using AI and machine learning In Intelligent Security Systems, distinguished professor and computer scientist Dr. Leon Reznik delivers an expert synthesis of artificial intelligence, machine learning and data science techniques, applied to computer security to assist readers in hardening their computer systems against threats. Emphasizing practical and actionable strategies that can be immediately implemented by industry professionals and computer device's owners, the author explains how to install and harden firewalls, intrusion detection systems, attack recognition tools, and malware protection systems. He also explains how to recognize and counter common hacking activities. This book bridges the gap between cybersecurity education and new data science programs, discussing how cutting-edge artificial intelligence and machine learning techniques can work for and against cybersecurity efforts. Intelligent Security Systems includes supplementary resources on an author-hosted website, such as classroom presentation slides, sample review, test and exam questions, and practice exercises to make the material contained practical and useful. The book also offers: A thorough introduction to computer security, artificial intelligence, and machine learning, including basic definitions and concepts like threats, vulnerabilities, risks, attacks, protection, and tools An exploration of firewall design and implementation, including firewall types and models, typical designs and configurations, and their limitations and problems Discussions of intrusion detection systems (IDS), including architecture topologies, components, and operational ranges, classification approaches, and machine learning techniques in IDS design A treatment of malware and vulnerabilities detection and protection, including malware classes, history, and development trends Perfect for undergraduate and graduate students in computer security, computer science and engineering, Intelligent Security Systems will also earn a place in the libraries of students and educators in information technology and data science, as well as professionals working in those fields.

Developing new approaches and reliable enabling technologies in the healthcare industry is needed to enhance our overall quality of life and lead to a healthier, innovative, and secure society. Further study is required to ensure these current technologies, such as big data analytics and artificial intelligence, are utilized to their utmost potential and are appropriately applied to advance society. Big Data Analytics and Artificial Intelligence in the Healthcare Industry discusses technologies and emerging topics regarding reliable and innovative solutions applied to the healthcare industry and considers various applications, challenges, and issues of big data and artificial intelligence for enhancing our quality of life. Covering a range of topics such as electronic health records, machine learning, and e-health, this reference work is ideal for healthcare professionals, computer scientists, data analysts, researchers, practitioners, scholars, academicians, instructors, and students.