The Internet of Energy (IoE), with the integration of advanced information and communication technologies (ICT), has led to a transformation of traditional networks to smart systems. Internet of Energy Handbook provides updated knowledge in the field of energy management with an Internet of Things (IoT) perspective. Features Explains the technological developments for energy management leading to a reduction in energy consumption through topics like smart energy systems, smart sensors, communication, techniques, and utilization Includes dedicated sections covering varied aspects related to renewable sources of energy, power distribution, and generation Incorporates energy efficiency, optimization, and sensor technologies Covers multidisciplinary aspects in computational intelligence and IoT Discusses building energy management aspects including temperature, humidity, the number of persons involved, and light intensity This handbook is aimed at graduate students, researchers, and professionals interested in power systems, IoT, smart grids, electrical engineering, and transmission.

This book provides emergent knowledge relating to physical, cyber, and human risk mitigation in a practical and readable approach for the corporate environment. It presents and discusses practical applications of risk management techniques along with useable practical policy change options. This practical organizational security management approach examines multiple aspects of security to protect against physical, cyber, and human risk. A practical more tactical focus includes managing vulnerabilities and applying countermeasures. The book guides readers to a greater depth of understanding and action-oriented options.

Cloud computing is an indispensable part of the modern Information and Communication Technology (ICT) systems. Cloud computing services have proven to be of significant importance, and promote quickly deployable and scalable IT solutions with reduced infrastructure costs. However, utilization of cloud also raises concerns such as security, privacy, latency, and governance, that keep it from turning into the predominant option for critical frameworks. As such, there is an urgent need to identify these concerns and to address them. Cloud Security: Concepts, Applications and Perspectives is a comprehensive work with substantial technical details for introducing the state-of-the-art research and development on various approaches for security and privacy of cloud services; novel attacks on cloud services; cloud forensics; novel defenses for cloud service attacks; and cloud security analysis. It discusses the present techniques and methodologies, and provides a wide range of examples and illustrations to effectively show the concepts, applications, and perspectives of security in cloud computing. This highly informative book will prepare readers to exercise better protection by understanding the motivation of attackers and to deal with them to mitigate the situation. In addition, it covers future research directions in the domain. This book is suitable for professionals in the field, researchers, students who are want to carry out research in the field of computer and cloud security, faculty members across universities, and software developers engaged in software development in the field.

This book aims to bring together leading academic scientists, researchers, and research scholars to exchange and share their experiences and research results on all aspects of Artificial Intelligence. The book provides a premier interdisciplinary platform to present practical challenges and adopted solutions. The book addresses the complete functional framework workflow in Artificial Intelligence technology. It explores the basic and high-level concepts and can serve as a manual for the industry for beginners and the more advanced. It covers intelligent and automated systems and its implications to the real-world, and offers data acquisition and case studies related to data-intensive technologies in AI-based applications. The book will be of interest to researchers, professionals, scientists, professors, students of computer science engineering, electronics and communications, as well as information technology.

A staggering 70% of digital transformations have failed as per McKinsey. The key reason why enterprises are failing in their digital transformation journey is because there is no standard framework existing in the industry that enterprises can use to transform themselves to digital. There are several books that speak about technologies such as Cloud, Artificial Intelligence and Data Analytics in silos, but none of these provides a holistic view on how enterprises can embark on a digital transformation journey and be successful using a combination of these technologies. FORMULA 4.0 is a methodology that provides clear guidance for enterprises aspiring to transform their traditional operating model to digital. Enterprises can use this framework as a readymade guide and plan their digital transformation journey. This book is intended for all chief executives, software managers, and leaders who intend to successfully lead this digital transformation journey. An enterprise can achieve success in digital transformation only of it can create an IT Platform that will enable them to adopt any new technology seamlessly into existing IT estate; deliver new products and services to the market in shorter durations; make business decisions with IT as an enabler and utilize automation in all its major business and IT processes. Achieving these goals is what defines a digital enterprise -- Formula 4.0 is a methodology for enterprises to achieve these goals and become digital. Essentially, there is no existing framework in the market that provides a step-by-step guide to enterprises on how to embark on their successful digital transformation journey. This book enables such transformations. Overall, the Formula 4.0 is an enterprise digital transformation framework that enables organizations to become truly digital.

Applied Soft Computing and Embedded System Applications in Solar Energy deals with energy systems and soft computing methods from a wide range of approaches and application perspectives. The authors examine how embedded system applications can deal with the smart monitoring and controlling of stand-alone and grid-connected solar photovoltaic (PV) systems for increased efficiency. Growth in the area of artificial intelligence with embedded system applications has led to a new era in computing, impacting almost all fields of science and engineering. Soft computing methods implemented to energy-related problems regularly face data-driven issues such as problems of optimization, classification, clustering, or prediction. The authors offer real-time implementation of soft computing and embedded system in the area of solar energy to address the issues with microgrid and smart grid projects (both renewable and non-renewable generations), energy management, and power regulation. They also discuss and examine alternative solutions for energy capacity assessment, energy efficiency systems design, as well as other specific smart grid energy system applications. The book is intended for students, professionals, and researchers in electrical and computer engineering fields, working on renewable energy resources, microgrids, and smart grid projects. Examines the integration of hardware with stand-alone PV panels and real-time monitoring of factors affecting the efficiency of the PV panels Offers real-time implementation of soft computing and embedded system in the area of solar energy Discusses how soft computing plays a huge role in the prediction of efficiency of stand-alone and grid-connected solar PV systems Discusses how embedded system applications with smart monitoring can control and enhance the efficiency of stand-alone and grid-connected solar PV systems Explores swarm intelligence techniques for solar PV parameter estimation Dr. Rupendra Kumar Pachauri is Assistant Professor - Selection Grade in the Department of Electrical and Electronics Engineering, University of Petroleum and Energy Studies (UPES), Dehradun, India. Dr. Jitendra Kumar Pandey is Professor & Head of R&D in the University of Petroleum and Energy Studies (UPES), Dehradun, India. Mr. Abhishek Sharma is working as a research scientist in the research and development department (UPES, India). Dr. Om Prakash Nautiyal is working as a scientist in Uttarakhand Science Education & Research Centre (USERC), Department of Information and Science Technology, Govt. of Uttarakhand, Dehradun, India. Prof. Mangey Ram is working as a Research Professor at Graphic Era Deemed to be University, Dehradun, India.

Move into iOS development by getting a firm grasp of its fundamentals, including the Xcode 9 IDE, Cocoa Touch, and the latest version of Apple's acclaimed programming language, Swift 4. With this thoroughly updated guide, you'll learn the Swift language, understand Apple's Xcode development tools, and discover the Cocoa framework. Explore Swift's object-oriented concepts Become familiar with built-in Swift types Dive deep into Swift objects, protocols, and generics Tour the lifecycle of an Xcode project Learn how nibs are loaded Understand Cocoa's event-driven design Communicate with C and Objective-C In this edition, catch up on the latest iOS programming features. Multiline strings and improved dictionaries Object serialization Key paths and key-value observing Expanded git integration Code refactoring And more! Once you master the fundamentals, you'll be ready to tackle the details of iOS app development with author Matt Neuburg's companion guide, Programming iOS 11

How can we recruit out of your program? We have a project - how do we reach out to your students? If we do research together who owns it? We have employees who need to "upskill" in analytics - can you help me with that? How much does all of this cost? Managers and executives are increasingly asking university professors such questions as they deal with a critical shortage of skilled data analysts. At the same time, academics are asking such questions as: How can I bring a "real" analytical project in the classroom? How can I get "real" data to help my students develop the skills necessary to be a "data scientist? Is what I am teaching in the classroom aligned with the demands of the market for analytical talent? After spending several years answering almost daily e-mails and telephone calls from business managers asking for staffing help and aiding fellow academics with their analytics teaching needs, Dr. Jennifer Priestley of Kennesaw State University and Dr. Robert McGrath of the University of New Hampshire wrote Closing the Analytics Talent Gap: An Executive's Guide to Working with Universities. The book builds a bridge between university analytics programs and business organizations. It promotes a dialog that enables executives to learn how universities can help them find strategically important personnel and universities to learn how they can develop and educate this personnel. Organizations are facing previously unforeseen challenges related to the translation of massive amounts of data - structured and unstructured, static and in-motion, voice, text, and image - into information to solve current challenges and anticipate new ones. The advent of analytics and data science also presents universities with unforeseen challenges of providing learning through application. This book helps both organizations with finding "data natives" and universities with educating students to develop the facility to work in a multi-faceted and complex data environment. .

This book focuses primarily on both technical and business aspects needed to select, design, develop and deploy control application (or product) successfully for multiple components in building systems. Designing and deploying a control application require multiple steps such as sensing, system dynamics modelling, algorithms, and testing. This may involve choosing an appropriate methodology and technique at multiple stages during the development process. Understanding the pros and cons of such techniques, most importantly being aware of practically possible approaches in the entire ecosystem, is critical in choosing the best framework and system application for different parts of building systems. Providing a wide overview of the state-of art in controls and building systems, providing guidance on developing an end-to-end system in relation to business fundamentals (distribution channels, stakeholders, marketing, supply-chain and financial management), the book is ideal for fourth-year control/mechanical/electrical engineering undergraduates, graduate students, and practitioners including business leaders concerned with smart building technology.

This book records the author's years of experience in the software industry. In his own practices, the author has found that the distributed work pattern has become increasingly popular in more and more work environments, either between vendors and customers or between different teams inside a company. This means that all practitioners in the software industry need to adapt to this new way of communication and collaboration and get skilled enough to meet the greater challenges in integrating the distributed work pattern with agile software delivery. By centering on the difficulties in communication and collaboration between distributed teams, this book digs into the reasons why so many remote delivery projects end up anticlimactic and provides solutions for readers' reference. It also cites successful cases in promoting agile development in distributed teams, which has been a vexing problem for many software development companies. In addition, readers can find suggestions and measures for building self-managing teams in this book. Remote Delivery: A Guide to Software Delivery through Collaboration between Distributed Teams is a very practical guide for software delivery teams with their members distributed in different places and companies engaged in software customization. Developers, QAs, product managers, and project leaders can also be inspired by this book.

The book is based on the best papers of IEEE IRI 2018 and IEEE FMI 2018, Salt Lake City, July, 2018. They have been enhanced and modified suitably for publication. The book comprises recent works covering several aspects of reuse in intelligent systems - including Scientific Theory and Technology-Based Applications. New data analytic algorithms, technologies, and tools are sought to be able to manage, integrate, and utilize large amounts of data despite hardware, software, and/or bandwidth constraints; to construct models yielding important data insights, and to create visualizations to aid in presenting and understanding the data. Furthermore, it addresses the representation, cleansing, generalization, validation, and reasoning strategies for the scientifically-sound and cost-effective advancement of all kinds of intelligent systems - including all software and hardware aspects. The book addresses problems such as, how to optimally select the information/data sets for reuse and how to optimize the integration of existing information/knowledge with new, developing information/knowledge sources!

In practice, many different people with backgrounds in many different disciplines contribute to the design of an enterprise. Anyone who makes decisions to change the current enterprise to achieve some preferred structure is considered a designer. What is problematic is how to use the knowledge of separate aspects of the enterprise to achieve a globally optimized enterprise. The synthesis of knowledge from many disciplines to design an enterprise defines the field of enterprise engineering. Because enterprise systems are exceedingly complex, encompassing many independent domains of study, students must first be taught how to think about enterprise systems. Specifically written for advanced and intermediate courses and modules, Design of Enterprise Systems: Theory, Architecture, and Methods takes a system-theoretical perspective of the enterprise. It describes a systematic approach, called the enterprise design method, to design the enterprise. The design method demonstrates the principles, models, methods, and tools needed to design enterprise systems. The author uses the enterprise system design methodology to organize the chapters to mimic the completion of an actual project. Thus, the book details the enterprise engineering process from initial conceptualization of an enterprise to its final design. Pedagogical tools available include: For instructors: PowerPoint (R) slides for each chapter Project case studies that can be assigned as long-term projects to accompany the text Quiz questions for each chapter Business Process Analyzer software available for download For students: Templates, checklists, forms, and models to support enterprise engineering activities The book fills a need for greater design content in engineering curricula by describing how to design enterprise systems. Inclusion of design is also critical for business students, since they must realize the import their decisions may have on the long-term design of the enterprises they work with. The book's practical focus and project-based approach coupled with the pedagogical tools gives students the knowledge and skills they need to lead enterprise engineering projects.

This book presents a collection of automated methods that are useful for different aspects of fault analysis in cryptography. The first part focuses on automated analysis of symmetric cipher design specifications, software implementations, and hardware circuits. The second part provides automated deployment of countermeasures. The third part provides automated evaluation of countermeasures against fault attacks. Finally, the fourth part focuses on automating fault attack experiments. The presented methods enable software developers, circuit designers, and cryptographers to test and harden their products.

This textbook teaches students techniques for the design of advanced digital systems using System-on-Chip (SoC) Field Programmable Gate Arrays (FPGAs). The author demonstrates design of custom hardware components for the FPGA fabric using VHDL, with implementation of custom hardware-software interfaces. Readers gain hands-on experience by writing programs and Linux device drivers in C to interact with custom hardware. This textbook enables laboratory experience in the design of custom digital systems using SoC FPGAs, emphasizing computational tasks such as digital signal processing, audio, or video processing.

How can we recruit out of your program? We have a project - how do we reach out to your students? If we do research together who owns it? We have employees who need to "upskill" in analytics - can you help me with that? How much does all of this cost? Managers and executives are increasingly asking university professors such questions as they deal with a critical shortage of skilled data analysts. At the same time, academics are asking such questions as: How can I bring a "real" analytical project in the classroom? How can I get "real" data to help my students develop the skills necessary to be a "data scientist? Is what I am teaching in the classroom aligned with the demands of the market for analytical talent? After spending several years answering almost daily e-mails and telephone calls from business managers asking for staffing help and aiding fellow academics with their analytics teaching needs, Dr. Jennifer Priestley of Kennesaw State University and Dr. Robert McGrath of the University of New Hampshire wrote Closing the Analytics Talent Gap: An Executive's Guide to Working with Universities. The book builds a bridge between university analytics programs and business organizations. It promotes a dialog that enables executives to learn how universities can help them find strategically important personnel and universities to learn how they can develop and educate this personnel. Organizations are facing previously unforeseen challenges related to the translation of massive amounts of data - structured and unstructured, static and in-motion, voice, text, and image - into information to solve current challenges and anticipate new ones. The advent of analytics and data science also presents universities with unforeseen challenges of providing learning through application. This book helps both organizations with finding "data natives" and universities with educating students to develop the facility to work in a multi-faceted and complex data environment. .

Software-Defined Data Infrastructures Essentials provides fundamental coverage of physical, cloud, converged, and virtual server storage I/O networking technologies, trends, tools, techniques, and tradecraft skills. From webscale, software-defined, containers, database, key-value store, cloud, and enterprise to small or medium-size business, the book is filled with techniques, and tips to help develop or refine your server storage I/O hardware, software, and services skills. Whether you are new to data infrastructures or a seasoned pro, you will find this comprehensive reference indispensable for gaining as well as expanding experience with technologies, tools, techniques, and trends. We had a front row seat watching Greg present live in our education workshop seminar sessions for ITC professionals in the Netherlands material that is in this book. We recommend this amazing book to expand your converged and data infrastructure knowledge from beginners to industry veterans. -Gert and Frank Brouwer, Brouwer Storage Consultancy Software-Defined Data Infrastructures Essentials provides the foundational building blocks to improve your craft in serval areas including applications, clouds, legacy, and more. IT professionals, as well as sales professionals and support personnel, stand to gain a great deal by reading this book.-Mark McSherry, Oracle Regional Sales Manager Looking to expand your data infrastructure IQ? From CIOS to operations, sales to engineering, this book is a comprehensive reference, a must read for IT infrastructure professionals, beginners to seasoned experts.-Tom Becchetti, Advisory Systems Engineer Greg Schulz has provided a complete 'toolkit' for storage management along with the background and framework for the storage or data infrastructure professional or those aspiring to become one.-Greg Brunton, Experienced Storage and Data Management Professional

Assisting organizations in improving their project management processes, the Project Management Maturity Model defines the industry standard for measuring project management maturity and agile and adaptive capabilities. Project Management Maturity Model, Fourth Edition provides a roadmap showing organizations how to move to higher levels of organizational behavior, improving project success and organizational performance. It's a comprehensive tool for enhancing project management practices, covering areas critical to organizational improvement, such as the project management office, management oversight, and professional development. It also provides methods for optimizing project management processes and suggestions for deploying the model as a strategic tool in improving business outcomes. New material in each chapter also outlines good practices for implementing adaptive an agile processes. The book also includes the Project Portfolio Management Maturity Model, which covers best practices for determining portfolio maturity, setting short-term priorities, implementing benefits realization management, improving portfolio management processes and tracking progress. The author, J. Kent Crawford, CEO of PM Solutions, describes the basics of project management maturity, including the benefits of assessing maturity, and presents a comprehensive framework for improving organization's processes. Chapters are based on the ten project management knowledge areas specified in the Project Management Institute's standard, the PMBOK (R) Guide. This edition provides new and revised materials based on the PMBOK (R) Guide including a fresh focus on agile and adaptive methods, benefits realization, and organizational change management. Organizations can use this book to: Determine the maturity of your organization's project management processes Gauge readiness for agile transformation Map out a logical path to improve your organization's processes Set priorities for short-term process improvement Track and visualize improvements in project management over time Learn to translate process maturity into business results After an objective assessment, an organization can set its goals for increasing the capability of its processes and develop a plan for reaching those goals. This book is ideal for anyone involved with improving the capability of an organization's project and portfolio management processes.

Cloud Data Center Network Architectures and Technologies has been written with the support of Huawei's vast technical knowledge and experience in the data center network (DCN) field, as well as its understanding of customer service requirements. This book describes in detail the architecture design, technical implementation, planning and design, and deployment suggestions for cloud DCNs based on the service challenges DCNs encounter. It starts by describing the overall architecture and technical evolution of DCNs, with the aim of helping readers understand the development of DCNs. It then proceeds to explain the design and implementation of cloud DCNs, including the service model of a single data center (DC), construction of physical and logical networks of DCs, construction of multiple DCNs, and security solutions of DCs. Next, this book dives deep into practices of cloud DCN deployment based on real-world cases to help readers better understand how to build cloud DCNs. Finally, this book introduces DCN openness and some of the hottest forward-looking technologies. In summary, you can use this book as a reference to help you to build secure, reliable, efficient, and open cloud DCNs. It is intended for technical professionals of enterprises, research institutes, information departments, and DCs, as well as teachers and students of computer network-related majors in colleges and universities. Authors Lei Zhang Mr. Zhang is the Chief Architect of Huawei's DCN solution. He has more than 20 years' experience in network product and solution design, as well as a wealth of expertise in product design and development, network planning and design, and network engineering project implementation. He has led the design and deployment of more than 10 large-scale DCNs for Fortune Global 500 companies worldwide. Le Chen Mr. Chen is a Huawei DCN Solution Documentation Engineer with eight years' experience in developing documents related to DCN products and solutions. He has participated in the design and delivery of multiple large-scale enterprise DCNs. Mr. Chen has written many popular technical document series, such as DCN Handbook and BGP Topic.

This book presents, in an integrated form, both the analysis and synthesis of three different types of hidden Markov models. Unlike other books on the subject, it is generic and does not focus on a specific theme, e.g. speech processing. Moreover, it presents the translation of hidden Markov models' concepts from the domain of formal mathematics into computer codes using MATLAB (R). The unique feature of this book is that the theoretical concepts are first presented using an intuition-based approach followed by the description of the fundamental algorithms behind hidden Markov models using MATLAB (R). This approach, by means of analysis followed by synthesis, is suitable for those who want to study the subject using a more empirical approach. Key Selling Points: Presents a broad range of concepts related to Hidden Markov Models (HMM), from simple problems to advanced theory Covers the analysis of both continuous and discrete Markov chains Discusses the translation of HMM concepts from the realm of formal mathematics into computer code Offers many examples to supplement mathematical notation when explaining new concepts

Originally published in 1995, Large Deviations for Performance Analysis consists of two synergistic parts. The first half develops the theory of large deviations from the beginning, through recent results on the theory for processes with boundaries, keeping to a very narrow path: continuous-time, discrete-state processes. By developing only what is needed for the applications, the theory is kept to a manageable level, both in terms of length and in terms of difficulty. Within its scope, the treatment is detailed, comprehensive and self-contained. As the book shows, there are sufficiently many interesting applications of jump Markov processes to warrant a special treatment. The second half is a collection of applications developed at Bell Laboratories. The applications cover large areas of the theory of communication networks: circuit switched transmission, packet transmission, multiple access channels, and the M/M/1 queue. Aspects of parallel computation are covered as well including, basics of job allocation, rollback-based parallel simulation, assorted priority queueing models that might be used in performance models of various computer architectures, and asymptotic coupling of processors. These applications are thoroughly analysed using the tools developed in the first half of the book.

A staggering 70% of digital transformations have failed as per McKinsey. The key reason why enterprises are failing in their digital transformation journey is because there is no standard framework existing in the industry that enterprises can use to transform themselves to digital. There are several books that speak about technologies such as Cloud, Artificial Intelligence and Data Analytics in silos, but none of these provides a holistic view on how enterprises can embark on a digital transformation journey and be successful using a combination of these technologies. FORMULA 4.0 is a methodology that provides clear guidance for enterprises aspiring to transform their traditional operating model to digital. Enterprises can use this framework as a readymade guide and plan their digital transformation journey. This book is intended for all chief executives, software managers, and leaders who intend to successfully lead this digital transformation journey. An enterprise can achieve success in digital transformation only of it can create an IT Platform that will enable them to adopt any new technology seamlessly into existing IT estate; deliver new products and services to the market in shorter durations; make business decisions with IT as an enabler and utilize automation in all its major business and IT processes. Achieving these goals is what defines a digital enterprise -- Formula 4.0 is a methodology for enterprises to achieve these goals and become digital. Essentially, there is no existing framework in the market that provides a step-by-step guide to enterprises on how to embark on their successful digital transformation journey. This book enables such transformations. Overall, the Formula 4.0 is an enterprise digital transformation framework that enables organizations to become truly digital.

As the 2020 global lockdown became a universal strategy to control the COVID-19 pandemic, social distancing triggered a massive reliance on online and cyberspace alternatives and switched the world to the digital economy. Despite their effectiveness for remote work and online interactions, cyberspace alternatives ignited several Cybersecurity challenges. Malicious hackers capitalized on global anxiety and launched cyberattacks against unsuspecting victims. Internet fraudsters exploited human and system vulnerabilities and impacted data integrity, privacy, and digital behaviour. Cybersecurity in the COVID-19 Pandemic demystifies Cybersecurity concepts using real-world cybercrime incidents from the pandemic to illustrate how threat actors perpetrated computer fraud against valuable information assets particularly healthcare, financial, commercial, travel, academic, and social networking data. The book simplifies the socio-technical aspects of Cybersecurity and draws valuable lessons from the impacts COVID-19 cyberattacks exerted on computer networks, online portals, and databases. The book also predicts the fusion of Cybersecurity into Artificial Intelligence and Big Data Analytics, the two emerging domains that will potentially dominate and redefine post-pandemic Cybersecurity research and innovations between 2021 and 2025. The book's primary audience is individual and corporate cyberspace consumers across all professions intending to update their Cybersecurity knowledge for detecting, preventing, responding to, and recovering from computer crimes. Cybersecurity in the COVID-19 Pandemic is ideal for information officers, data managers, business and risk administrators, technology scholars, Cybersecurity experts and researchers, and information technology practitioners. Readers will draw lessons for protecting their digital assets from email phishing fraud, social engineering scams, malware campaigns, and website hijacks.

With the advent of the IT revolution, the volume of data produced has increased exponentially and is still showing an upward trend. This data may be abundant and enormous, but it's a precious resource and should be managed properly. Cloud technology plays an important role in data management. Storing data in the cloud rather than on local storage has many benefits, but apart from these benefits, there are privacy concerns in storing sensitive data over third-party servers. These concerns can be addressed by storing data in an encrypted form; however, while encryption solves the problem of privacy, it engenders other serious issues, including the infeasibility of the fundamental search operation and a reduction in flexibility when sharing data with other users, amongst others. The concept of searchable encryption addresses these issues. This book provides every necessary detail required to develop a secure, searchable encryption scheme using both symmetric and asymmetric cryptographic primitives along with the appropriate security models to ensure the minimum security requirements for real-world applications.

The book comprises a new method of solving the integral equation of Leontovich, the most rigorous and most effective equation for the current in thin linear antennas. The book describes the features of the new method in its application in various types of antennas. It considers new ways of analyzing antennas, in particular in the calculation of an antenna gain based on main radiation patterns and the calculation of the directional characteristics of radiators with known distribution of current amplitude. The method of electrostatic analogy proposed by the author, provides the base for comparison of electromagnetic fields of high-frequency currents and electrostatic charges located on linear conductors to improve the directional characteristics of log-periodic and director-type antennas. A new approach to the analysis of the electrical characteristics of a microstrip antenna, which allows expansion of its operation range, is substantiated and developed. New results of antenna synthesis are obtained. The second part of the book is devoted to specific types of antennas (the author had a significant role in their creation). Particular attention is given to ship antennas for different frequency ranges. The book is intended for professionals, working in electrodynamics and those working on development, placement and exploitation of antennas. It will be useful for lecturers (university-level professors), teachers, students of radio engineering and researchers working in various fields of radio electronics and interested in an in-depth study of theoretical problems and designs f antennas. It can also be used for short university courses.

The Healthcare industry is one of the largest and rapidly developing industries. Over the last few years, healthcare management is changing from disease centered to patient centered. While on one side the analysis of healthcare data plays an important role in healthcare management, but on the other side the privacy of a patient's record must be of equal concern. This book uses a research-oriented approach and focuses on privacy-based healthcare tools and technologies. It offers details on privacy laws with real-life case studies and examples, and addresses privacy issues in newer technologies such as Cloud, Big Data, and IoT. It discusses the e-health system and preserving its privacy, and the use of wearable technologies for patient monitoring, data streaming and sharing, and use of data analysis to provide various health services. This book is written for research scholars, academicians working in healthcare and data privacy domains, as well as researchers involved with healthcare law, and those working at facilities in security and privacy domains. Students and industry professionals, as well as medical practitioners might also find this book of interest.