This fully updated study guide covers every topic on the current version of the CompTIA Security+ exam Get complete coverage of all objectives included on the CompTIA Security+ exam SY0-601 from this comprehensive resource. Written by a team of leading information security experts, this authoritative guide fully addresses the skills required to perform essential security functions and to secure hardware, systems, and software. You'll find learning objectives at the beginning of each chapter, exam tips, practice exam questions, and in-depth explanations. Designed to help you pass the exam with ease, this definitive volume also serves as an essential on-the-job reference. Covers all exam domains, including: Threats, Attacks, and Vulnerabilities Architecture and Design Implementation Operations and Incident Response Governance, Risk, and Compliance Online content includes: 250 practice exam questions Test engine that provides full-length practice exams and customizable quizzes by chapter or by exam domain

Stochastic processes have a wide range of applications ranging from image processing, neuroscience, bioinformatics, financial management, and statistics. Mathematical, physical, and engineering systems use stochastic processes for modeling and reasoning phenomena. While comparing AI-stochastic systems with other counterpart systems, we are able to understand their significance, thereby applying new techniques to obtain new real-time results and solutions. Stochastic Processes and Their Applications in Artificial Intelligence opens doors for artificial intelligence experts to use stochastic processes as an effective tool in real-world problems in computational biology, speech recognition, natural language processing, and reinforcement learning. Covering key topics such as social media, big data, and artificial intelligence models, this reference work is ideal for mathematicians, industry professionals, researchers, scholars, academicians, practitioners, instructors, and students.

Digital evolution has become increasingly present in our lives, whether on cellphones, computers, watches, or other appliances. As a result of the wide access we have to the digital world, the amount of data generated daily is vast. This density of information generated at every moment can be the insight needed for the success of an organization. Much is said about data-based decision-making to generate the best results. The new capabilities of data intelligence unleashed by the emergence of cloud computing and artificial intelligence make it one of the most promising areas of digital transformation change management. Enhancing Business Communications and Collaboration Through Data Science Applications provides relevant theoretical frameworks and the latest empirical research findings in the area. It is written for professionals who wish to improve their understanding of the strategic role of trust at different levels of the information and knowledge society. Covering topics such as data science, online business communication, and user-centered design, this premier reference source is an ideal resource for business managers and leaders, entrepreneurs, data scientists, data analysts, sociologists, students and educators of higher education, librarians, researchers, and academicians.

Autonomous Mobile Robots: Planning, Navigation, and Simulation presents detailed coverage of the domain of robotics in motion planning and associated topics in navigation. This book covers numerous base planning methods from diverse schools of learning, including deliberative planning methods, reactive planning methods, task planning methods, fusion of different methods, and cognitive architectures. It is a good resource for doing initial project work in robotics, providing an overview, methods and simulation software in one resource. For more advanced readers, it presents a variety of planning algorithms to choose from, presenting the tradeoffs between the algorithms to ascertain a good choice. Finally, the book presents fusion mechanisms to design hybrid algorithms.

Machine Learning and Artificial Intelligence in Radiation Oncology: A Guide for Clinicians is designed for the application of practical concepts in machine learning to clinical radiation oncology. It addresses the existing void in a resource to educate practicing clinicians about how machine learning can be used to improve clinical and patient-centered outcomes. This book is divided into three sections: the first addresses fundamental concepts of machine learning and radiation oncology, detailing techniques applied in genomics; the second section discusses translational opportunities, such as in radiogenomics and autosegmentation; and the final section encompasses current clinical applications in clinical decision making, how to integrate AI into workflow, use cases, and cross-collaborations with industry. The book is a valuable resource for oncologists, radiologists and several members of biomedical field who need to learn more about machine learning as a support for radiation oncology.

Artificial Intelligence in the Age of Neural Networks and Brain Computing, Second Edition demonstrates that present 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 possible future alternatives. The present success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel, and Amazon, can be interpreted using the perspective presented in this book by viewing the co-existence of a successful synergism among what is referred to as computational intelligence, natural intelligence, brain computing, and neural engineering. The new edition has been updated to include major new advances in the field, including many new chapters.

This handbook covers the essential subject areas of cutaneous biometrics, including acne, aging, genetics, eczema, psoriasis, atopic dermatitis, rosacea, wound healing, and more. Erythema of rosacea and the risk of skin ulceration associated with oral nicorandil therapy are covered in detail. Various areas of acne are addressed, including acne severity grading, the assessment of general health and quality of life in patients with acne, and the effect of automated online counseling on clinical outcomes and quality of life among adolescents with acne vulgaris. Other topics include the development and validation of a clinical scale for the evaluation of forearm skin photoaging and a scoring system for mucosal disease severity. This is an ideal reference for biomedical engineering researchers and clinicians working in the field of dermatology interested in a deeper understanding of cutaneous biometrics and how it can be applied to their work. This book also:  Broadens reader understanding of the importance of creating meaningful dermatological patient outcome measurements and the use of the physician global assessment in a clinical setting to measure and track patient outcomes Details the guidelines on the measurement of ultraviolet radiation levels in ultraviolet phototherapy 

Artificial intelligence is smarter than humans. It can process information at lightning speed and remain focused on specific tasks without distraction. AI can see into the future, predict outcomes and even use sensors to see around physical and virtual corners. So why does AI frequently get it so wrong and cause harm?

The answer is us: the human beings who write the code and teach AI to mimic our behaviour. Scary Smart explains how to fix the current trajectory now, to make sure that the AI of the future can preserve our species. This book offers a blueprint, pointing the way to what we can do to safeguard ourselves, those we love and the planet itself.

Multi Criteria Decision Making (MCDM) is a generic term for all methods that help people making decisions according to their preferences, in situations where there is more than one conflicting criterion. It is a branch of operational research dealing with finding optimal results in complex scenarios including various indicators, conflicting objectives and criteria. The approach of MCDM involves decision making concerning quantitative and qualitative factors. The importance and success of MCDM are due to the fact that they have successfully dealt with different types of problematics for supporting decision makers such as choice, ranking and sorting, description. Even though, each of the different problematics in MCDM is important, Multi-Criteria Decision-Making Sorting Methods will focus on sorting approaches across a wide range of interesting techniques and research disciplines. The applications which have been and can be solved by these techniques are more and more important in current real-world decision-making problems. Therefore, the book provides a clear overview of MCDM sorting methods and the different tools which can be used to solve real-world problems by revising such tools and characterizing them according to their performance and suitability for different types of problems. The book is aimed at a broad audience including computer scientists, engineers, geography and GIS experts, business and financial management experts, environment experts, and all those professional people interested in MCDM and its applications. The book may also be useful for teaching MCDM courses in fields such as industrial management, computer science, and applied mathematics, as new developments in multi-criteria decision making.

Combining clear labelled imagery with easy-to-understand text, this new edition of Simply Artificial Intelligence is the perfect introduction to the latest developments in AI, including ChatGPT and the Internet of Things.

Covering a broad range of fields within AI - from computing and mathematics to politics and philosophy - entries demystify what artificial intelligence is and how it works, how it has dramatically changed how we live, and how it might evolve in the future. Everyone is talking about AI, but this book helps to explain each individual aspect of AI more clearly than ever before.

Artificial intelligence is something that we have yet to understand fully. Explore the beginnings of this life-changing invention. Explore how technology has evolved and how our understanding of AI has developed. Whether you are interested in AI’s advances or are new to the topic, you can find a range of information and facts in this Simply edition.

This AI book:

-Outlines the key building blocks and technological milestones in its history, profiles its most important practical applications - both current and predicted

-Explores the ethical debates around AI and its increasing influence on culture and society.

-Provides an accessible, reader-friendly guide with detailed imagery and annotated illustrations, expert insights and jargon-free text

-Studies and experiments such as The Turing Test and The Chinese Room experiment

This book is part of the Simply Series, which includes books such as Simply Astronomy, Simply Psychology, Simply Maths, and more. Whether you are studying science or AI-related subjects at school or college or simply want a jargon-free overview of this increasingly important subject, this essential guide is packed with everything you need to understand the basics quickly and easily.

Provides comprehensive coverage of theory and hands-on implementation of computer vision-based sensors for structural health monitoring This book is the first to fill the gap between scientific research of computer vision and its practical applications for structural health monitoring (SHM). It provides a complete, state-of-the-art review of the collective experience that the SHM community has gained in recent years. It also extensively explores the potentials of the vision sensor as a fast and cost-effective tool for solving SHM problems based on both time and frequency domain analytics, broadening the application of emerging computer vision sensor technology in not only scientific research but also engineering practice. Computer Vision for Structural Dynamics and Health Monitoring presents fundamental knowledge, important issues, and practical techniques critical to successful development of vision-based sensors in detail, including robustness of template matching techniques for tracking targets; coordinate conversion methods for determining calibration factors to convert image pixel displacements to physical displacements; sensing by tracking artificial targets vs. natural targets; measurements in real time vs. by post-processing; and field measurement error sources and mitigation methods. The book also features a wide range of tests conducted in both controlled laboratory and complex field environments in order to evaluate the sensor accuracy and demonstrate the unique features and merits of computer vision-based structural displacement measurement. Offers comprehensive understanding of the principles and applications of computer vision for structural dynamics and health monitoring Helps broaden the application of the emerging computer vision sensor technology from scientific research to engineering practice such as field condition assessment of civil engineering structures and infrastructure systems Includes a wide range of laboratory and field testing examples, as well as practical techniques for field application Provides MATLAB code for most of the issues discussed including that of image processing, structural dynamics, and SHM applications Computer Vision for Structural Dynamics and Health Monitoring is ideal for graduate students, researchers, and practicing engineers who are interested in learning about this emerging sensor technology and advancing their applications in SHM and other engineering problems. It will also benefit those in civil and aerospace engineering, energy, and computer science.

In healthcare, a digital twin is a digital representation of a patient or healthcare system using integrated simulations and service data. The digital twin tracks a patient's records, crosschecks them against registered patterns and analyses any diseases or contra indications. The digital twin uses adaptive analytics and algorithms to produce accurate prognoses and suggest appropriate interventions. A digital twin can run various medical scenarios before treatment is initiated on the patient, thus increasing patient safety as well as providing the most appropriate treatments to meet the patient's requirements. Digital Twin Technologies for Healthcare 4.0 discusses how the concept of the digital twin can be merged with other technologies, such as artificial intelligence (AI), machine learning (ML), big data analytics, IoT and cloud data management, for the improvement of healthcare systems and processes. The book also focuses on the various research perspectives and challenges in implementation of digital twin technology in terms of data analysis, cloud management and data privacy issues. With chapters on visualisation techniques, prognostics and health management, this book is a must-have for researchers, engineers and IT professionals in healthcare as well as those involved in using digital twin technology, AI, IoT & big data analytics for novel applications.

A smart, incisive take-down of the bogus claims being made about so-called ‘artificial intelligence’, exposing the real harm these technologies do to our jobs, health, society and environment, who stands to gain from them, and how to fight back.

Is AI going to take over the world? Have scientists created an artificial lifeform that can think on its own? Is it going to replace all our jobs, even creative ones, like doctors, teachers and care-workers? Are we about to enter an age where computers are better than humans at everything?

The answers to these questions, as the expert authors of The AI Con make clear, are 'no', 'they wish', 'LOL', and 'definitely not'. In fact, these fears are all symptoms of the hype being used by tech corporations to justify data theft, motivate surveillance capitalism, and devalue human creativity so they can replace meaningful work with jobs that treat people like machines. Meanwhile, across healthcare, education, media, government and law-enforcement, ‘AI’ products are already being introduced that are unreliable, ineffective, unjust and dangerous.

Packed with real-world examples, pithy arguments and expert insights, The AI Con arms you to spot AI hype in all its guises, expose the exploitation and power-grabs it aims to hide, and push back against it at work and in your daily life.

The advancement in FinTech especially artificial intelligence (AI) and machine learning (ML), has significantly affected the way financial services are offered and adopted today. Important financial decisions such as investment decision making, macroeconomic analysis, and credit evaluation are getting more complex in the field of finance. ML is used in many financial companies which are making a significant impact on financial services. With the increasing complexity of financial transaction processes, ML can reduce operational costs through process automation which can automate repetitive tasks and increase productivity. Among others, ML can analyze large volumes of historical data and make better trading decisions to increase revenue. This book provides an exhaustive overview of the roles of AI and ML algorithms in financial sectors with special reference to complex financial applications such as financial risk management in a big data environment. In addition, it provides a collection of high-quality research works that address broad challenges in both theoretical and application aspects of AI in the field of finance.

Understand microgrids and networked microgrid systems Microgrids are interconnected groups of energy sources that operate together, capable of connecting with a larger grid or operating independently as needed and network conditions require. They can be valuable sources of energy for geographically circumscribed areas with highly targeted energy needs, and for remote or rural areas where continuous connection with a larger grid is difficult. Microgrids' controllability makes them especially effective at incorporating renewable energy sources. Microgrids: Theory and Practice introduces readers to the analysis, design, and operation of microgrids and larger networked systems that integrate them. It brings to bear both cutting-edge research into microgrid technology and years of industry experience in designing and operating microgrids. Its discussions of core subjects such as microgrid modeling, control, and optimization make it an essential short treatment, valuable for both academic and industrial study. Readers will acquire the skills needed to address existing problems and meet new ones as this crucial area of power engineering develops. Microgrids: Theory and Practice also features: Incorporation of new cyber-physical system technologies for enabling microgrids as resiliency resources Theoretical treatment of a wide range of subjects including smart programmable microgrids, distributed and asynchronous optimization for microgrid dispatch, and AI-assisted microgrid protection Practical discussion of real-time microgrids simulations, hybrid microgrid design, transition to renewable microgrid networks, and more Microgrids: Theory and Practice is ideal as a textbook for graduate and advanced undergraduate courses in power engineering programs, and a valuable reference for power industry professionals looking to address the challenges posed by microgrids in their work.

Diagnostic Biomedical Signal and Image Processing Applications: With Deep Learning Methods presents comprehensive research on both medical imaging and medical signals analysis. The book discusses classification, segmentation, detection, tracking and retrieval applications of non-invasive methods such as EEG, ECG, EMG, MRI, fMRI, CT and X-RAY, amongst others. These image and signal modalities include real challenges, which are the main themes that medical imaging and medical signal processing researchers focus on today. The book also emphasizes removing noise and specifying dataset key properties, with each chapter containing details of one of the medical imaging or medical signal modalities. Focusing on solving real medical problems using new deep learning and CNN approaches, this book will appeal to research scholars, graduate students, faculty members, R&D engineers, and biomedical engineers who want to learn how medical signals and images play an important role in the early diagnosis and treatment of diseases.

On November 21, 1990, the Super Nintendo was officially introduced to the Japanese public as the Super Famicom - a date that would forever be engraved in the hearts and souls of gamers worldwide. Following in the footsteps of the NES, whose universal success had definitively shaped the fate of the gaming industry, the Super Nintendo was a technological masterpiece teeming with power and potential, and that still fascinates us to this very day. Across more than 510+ pages richly illustrated with photographs and documents from the period, this perfect fusion of our two previous Super Nintendo Anthology volumes recounts the life story of the Kyoto-based giant's wondrous 16-bit console and delves deep into its huge international games library. A true work of reference, allowing those who missed out on our Super Nintendo/Super Famicom Deluxe Edition the chance to own even more content than before. This new version of our SNES Anthology meshes together both the Software and Hardware books from our out-of-print Ultimate Edition. It covers the console's genesis through to the end of its life cycle (including a deep-dive into its many components, and its graphic/audio capabilities), as well as its accessories (official or otherwise), secrets behind the hardware, and a total of 1770+ official, unofficial and cancelled games - with a specific amount of page space dedicated to each one based on its quality and reputation, including their release date, developer, publisher, genre, and a rating out of five.

Authoritative reference on the state of the art in the field with additional coverage of important foundational concepts Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning presents cutting-edge research advances in the rapidly growing areas in optical and RF electromagnetic device modeling, simulation, and inverse-design. The text provides a comprehensive treatment of the field on subjects ranging from fundamental theoretical principles and new technological developments to state-of-the-art device design, as well as examples encompassing a wide range of related sub-areas. The content of the book covers all-dielectric and metallodielectric optical metasurface deep learning-accelerated inverse-design, deep neural networks for inverse scattering, applications of deep learning for advanced antenna design, and other related topics. To aid in reader comprehension, each chapter contains 10-15 illustrations, including prototype photos, line graphs, and electric field plots. Contributed to by leading research groups in the field, sample topics covered in Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning include: Optical and photonic design, including generative machine learning for photonic design and inverse design of electromagnetic systems RF and antenna design, including artificial neural networks for parametric electromagnetic modeling and optimization and analysis of uniform and non-uniform antenna arrays Inverse scattering, target classification, and other applications, including deep learning for high contrast inverse scattering of electrically large structures Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning is a must-have resource on the topic for university faculty, graduate students, and engineers within the fields of electromagnetics, wireless communications, antenna/RF design, and photonics, as well as researchers at large defense contractors and government laboratories.

Today, computation is an essential component of every technology. However, there has not been much research on quantum computing, even though it has the capability to solve complex problems in an efficient way. Further study is required to fully understand the uses and benefits of this technology. The Handbook of Research on Quantum Computing for Smart Environments presents investigating physical realizations of quantum computers, encoders, and decoders, including photonic quantum realization, cavity quantum electrodynamics, and many more topics on Bits to Qubits. Covering key topics such as machine learning, software, quantum algorithms, and neural networks, this major reference work is ideal for engineers, computer scientists, physicists, mathematicians, researchers, academicians, scholars, practitioners, instructors, and students.