ISO/IEC 27001:2005 is an international standard for information security management systems (ISMSs). Closely allied to ISO/IEC 27002:2005 (which used to be known as ISO17799), this standard (sometimes called the ISMS standard) can help organisations meet all their information-related regulatory compliance objectives and can help them prepare and position themselves for new and emerging regulations. Information is the lifeblood of today s organis-ation and, therefore, ensuring that information is simultaneously protected and available to those who need it is essential to modern business operations. Information systems are not usually designed from the outset to be secure. Technical security measures and checklists are limited in their ability to protect a complete information system. Management systems and procedural controls are essential components of any really secure information system and, to be effective, need careful planning and attention to detail. ISO/IEC 27001 provides the specification for an information security management system and, in the related Code of Practice, ISO/IEC 27002, it draws on the knowledge of a group of experienced information security practitioners in a wide range of significant organisations across more than 40 countries to set out best practice in information security. An ISO27001-compliant system will provide a systematic approach to ensuring the availability, confidentiality and integrity of corporate information. The controls of ISO27001 are based on identifying and combating the entire range of potential risks to the organisation s information assets. This helpful, handy ISO27001/ISO27002 pocket guide gives a useful overview of these two important information security standards. Key features include: The ISO/IEC 27000 Family of Information Security Standards Background to the Standards Specification vs Code of Practice Certification process The ISMS and ISO27001 Overview of ISO/IEC 27001:2005 Documentation & Records Management Responsibility Policy & Scope Risk Assessment Implementation

Artificial Intelligence and Machine Learning in Smart City Planning shows the reader practical applications of AIML techniques and describes recent advancements in this area in various sectors. Owing to the multidisciplinary nature, this book primarily focuses on the concepts of AIML and its methodologies such as evolutionary techniques, neural networks, machine learning, deep learning, block chain technology, big data analytics, and image processing in the context of smart cities. The text also discusses possible solutions to different challenges posed by smart cities by presenting cutting edge AIML techniques using different methodologies, as well as future directions for those same techniques.

Integrated Human-Machine Intelligence: Beyond Artificial Intelligence focuses on deep situational awareness in human-computer integration, covering the interaction and integration mechanisms of human intelligence, machine intelligence and environmental systems. The book also details the cognitive, philosophical, social, scientific and technological, and military theories and methods of human-computer division, cooperation and collaborative decision-making to provide basic theoretical support for a development strategy in the field of national intelligence. Sections focus on describing a new form of intelligence produced by the interaction of human, machine and environmental systems which will become the next generation of AI. From the perspective of deep situational awareness in human-computer integration, the book studies the interaction and integration mechanisms of human intelligence, machine intelligence and environmental systems. In addition, it details the cognitive, philosophical, social, scientific and technological, and military theories and methods of human-computer division, cooperation and collaborative decision-making, so as to provide basic theoretical support for a development strategy in the field of national intelligence.

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

The Designer's Guide to the Cortex-M Microcontrollers, Third Edition provides an easy-to-understand introduction to the concepts required to develop programs in C with a Cortex-M based microcontroller. Sections cover architectural descriptions that are supported with practical examples, enabling readers to easily develop basic C programs to run on the Cortex-M0/M0+/M3 and M4 and M7 and examine advanced features of the Cortex architecture, such as memory protection, operating modes and dual stack operation. Final sections examine techniques for software testing and code reuse specific to Cortex-M microcontrollers. Users will learn the key differences between the Cortex-M0/M0+/M3 and M4 and M7; how to write C programs to run on Cortex-M based processors; how to make the best use of the CoreSight debug system; the Cortex-M operating modes and memory protection; advanced software techniques that can be used on Cortex-M microcontrollers, and much more.

Intelligent Nanotechnology: Merging Nanoscience and Artificial Intelligence provides an overview of advances in science and technology made possible by the convergence of nanotechnology and artificial intelligence (AI). Sections focus on AI-enhanced design, characterization and manufacturing and the use of AI to improve important material properties, with an emphasis on mechanical, photonic, electronic and magnetic properties. Designing benign nanomaterials through the prediction of their impact on biology and the environment is also discussed. Other sections cover the use of AI in the acquisition and analysis of data in experiments and AI technologies that have been enhanced through nanotechnology platforms. Final sections review advances in applications enabled by the merging of nanotechnology and artificial intelligence, including examples from biomedicine, chemistry and automated research.

Case Studies in Geospatial Applications to Groundwater Resources provides thorough the most up-to-date techniques in GIS and geostatistics as they relate to groundwater, through detailed case studies that prove real-world applications of remote sensing applications to this subject. Groundwater is the primary source of fresh water in many parts of the world, while come regions are becoming overly dependent on it, consuming groundwater faster than it is naturally replenished and causing water tables to decline unremittingly. India is the largest user of groundwater in the world followed by China and the USA, with developing countries using groundwater at an unsustainable rate. Systematic planning of groundwater usage using modern techniques is essential for the proper utilization, management and modeling of this precious but shrinking natural resource. With the advent of powerful and highspeed personal computers, efficient techniques for water management have evolved, of which remote sensing, GIS (Geographic Information Systems), GPS (Global Positioning Systems) and Geostatistical techniques are of great significance. This book advances the scientific understanding, development, and application of geospatial technologies related to water resource management. Case Studies in Geospatial Applications to Groundwater Resources is a valuable reference for researchers and postgraduate students in Earth and Environmental Sciences, especially GIS, agriculture, hydrology, natural resources, and soil science, who need to be able to apply the latest technologies in groundwater research in a practical manner.

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.

Artificial Neural Networks for Renewable Energy Systems and Real-World Applications presents current trends for the solution of complex engineering problems in the application, modeling, analysis, and optimization of different energy systems and manufacturing processes. With growing research catering to the applications of neural networks in specific industrial applications, this reference provides a single resource catering to a broader perspective of ANN in renewable energy systems and manufacturing processes. ANN-based methods have attracted the attention of scientists and researchers in different engineering and industrial disciplines, making this book a useful reference for all researchers and engineers interested in artificial networks, renewable energy systems, and manufacturing process analysis.

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.

Adversarial Robustness for Machine Learning summarizes the recent progress on this topic and introduces popular algorithms on adversarial attack, defense and veri?cation. Sections cover adversarial attack, veri?cation and defense, mainly focusing on image classi?cation applications which are the standard benchmark considered in the adversarial robustness community. Other sections discuss adversarial examples beyond image classification, other threat models beyond testing time attack, and applications on adversarial robustness. For researchers, this book provides a thorough literature review that summarizes latest progress in the area, which can be a good reference for conducting future research. In addition, the book can also be used as a textbook for graduate courses on adversarial robustness or trustworthy machine learning. While machine learning (ML) algorithms have achieved remarkable performance in many applications, recent studies have demonstrated their lack of robustness against adversarial disturbance. The lack of robustness brings security concerns in ML models for real applications such as self-driving cars, robotics controls and healthcare systems.

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.

The Definitive Guide to Arm (R) Cortex (R)-M23 and Cortex-M33 Processors focuses on the Armv8-M architecture and the features that are available in the Cortex-M23 and Cortex- M33 processors. This book covers a range of topics, including the instruction set, the programmer's model, interrupt handling, OS support, and debug features. It demonstrates how to create software for the Cortex-M23 and Cortex-M33 processors by way of a range of examples, which will enable embedded software developers to understand the Armv8-M architecture. This book also covers the TrustZone (R) technology in detail, including how it benefits security in IoT applications, its operations, how the technology affects the processor's hardware (e.g., memory architecture, interrupt handling, etc.), and various other considerations in creating secure software.

The User Experience Team of One prescribes a range of approaches that have big impact and take less time and fewer resources than the standard lineup of UX deliverables. Whether you want to cross over into user experience or you're a seasoned practitioner trying to drag your organization forward, this book gives you tools and insight for doing more with less.

Contemporary Management of Metastatic Colorectal Cancer: A Precision Medicine Approach summarizes current knowledge and provides evidenced-based practice recommendations on how to treat patients with metastatic colorectal cancer. The book presents topics such as pre-operating imaging, the use of molecular markers in treatment decisions, neoadjuvant therapy, synchronous colorectal liver metastasis, and minimally invasive approaches. In addition, it discusses immunotherapy, targeted therapies and survivorship. This is a valuable resource for practitioners, cancer researchers, oncologists, graduate students and members of biomedical research who need to understand more about novel treatments for colorectal cancer metastasis.

Application of Machine Learning in Smart Agriculture is the first book to present a multidisciplinary look at how technology can not only improve agricultural output, but the economic efficiency of that output as well. Through a global lens, the book approaches the subject from a technical perspective, providing important knowledge and insights for effective and efficient implementation and utilization of machine learning. As artificial intelligence techniques are being used to increase yield through optimal planting, fertilizing, irrigation, and harvesting, these are only part of the complex picture which must also take into account the economic investment and its optimized return. The performance of machine learning models improves over time as the various mathematical and statistical models are proven. Presented in three parts, Application of Machine Learning in Smart Agriculture looks at the fundamentals of smart agriculture; the economics of the technology in the agricultural marketplace; and a diverse representation of the tools and techniques currently available, and in development. This book is an important resource for advanced level students and professionals working with artificial intelligence, internet of things, technology and agricultural economics.

Tactile Sensing, Skill Learning and Robotic Dexterous Manipulation focuses on cross-disciplinary lines of research and groundbreaking research ideas in three research lines: tactile sensing, skill learning and dexterous control. The book introduces recent work about human dexterous skill representation and learning, along with discussions of tactile sensing and its applications on unknown objects' property recognition and reconstruction. Sections also introduce the adaptive control schema and its learning by imitation and exploration. Other chapters describe the fundamental part of relevant research, paying attention to the connection among different fields and showing the state-of-the-art in related branches. The book summarizes the different approaches and discusses the pros and cons of each. Chapters not only describe the research but also include basic knowledge that can help readers understand the proposed work, making it an excellent resource for researchers and professionals who work in the robotics industry, haptics and in machine learning.

5G IoT and Edge Computing for Smart Healthcare addresses the importance of a 5G IoT and Edge-Cognitive-Computing-based system for the successful implementation and realization of a smart-healthcare system. The book provides insights on 5G technologies, along with intelligent processing algorithms/processors that have been adopted for processing the medical data that would assist in addressing the challenges in computer-aided diagnosis and clinical risk analysis on a real-time basis. Each chapter is self-sufficient, solving real-time problems through novel approaches that help the audience acquire the right knowledge. With the progressive development of medical and communication - computer technologies, the healthcare system has seen a tremendous opportunity to support the demand of today's new requirements.