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.

Learn how to write R code with fewer bugs. The problem with programming is that you are always one typo away from writing something silly. Likewise with data analysis, a small mistake in your model can lead to a big mistake in your results. Combining the two disciplines means that it is all too easy for a missed minus sign to generate a false prediction that you don't spot until it's too late. Testing is the only way to be sure that your code, and your results, are correct. Testing R Code teaches you how to perform development-time testing using the testthat package, allowing you to ensure that your code works as intended. The book also teaches run-time testing using the assertive package; enabling your users to correctly run your code. After beginning with an introduction to testing in R, the book explores more advanced cases such as integrating tests into R packages; testing code that accesses databases; testing C++ code with Rcpp; and testing graphics. Each topic is explained with real-world examples, and has accompanying exercises for readers to practise their skills - only a small amount of experience with R is needed to get started!

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 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.

Performance of Computer Communication Systems A Model-Based Approach Boudewijn R. Haverkort Rheinisch-WestfAlische Technische Hochschule Aachen, Germany Computer communication systems and distributed systems are now able to provide an increasing range of services. As the timing requirements in the operation of these services are becoming crucial for the global community. performance assessment and selection of communication and distributed systems are, therefore, becoming more important. In this book, the author illustrates the techniques and methods used to evaluate the performance of computer communication systems, thereby covering all aspects of model-based performance evaluation. Unlike other books on this topic, there is no restriction to a particular performance evaluation technique. Notable features in this book include:
* coverage of all major techniques of performance evaluation
* non-mathematical problem solving approach, explaining and illustrating performance evaluation techniques
* assessment techniques for stochastic processes, single server queues, networks of queues and stochastic Petri nets
* numerous application studies, including token ring systems, client-server systems, and wide-area networks
* substantial number of practical exercises and examples.
For computer or electrical engineers who design and implement computer communication systems, this book provides an excellent overview of the methods and techniques used to construct and solve performance models. It is also a valuable source of information for postgraduate students in computer science and related subjects. Visit Our Web Page! http: //www.wiley.com/

Cryptographic applications, such as RSA algorithm, ElGamal cryptography, elliptic curve cryptography, Rabin cryptosystem, Diffie -Hellmann key exchange algorithm, and the Digital Signature Standard, use modular exponentiation extensively. The performance of all these applications strongly depends on the efficient implementation of modular exponentiation and modular multiplication. Since 1984, when Montgomery first introduced a method to evaluate modular multiplications, many algorithmic modifications have been done for improving the efficiency of modular multiplication, but very less work has been done on the modular exponentiation to improve the efficiency. This research monograph addresses the question- how can the performance of modular exponentiation, which is the crucial operation of many public-key cryptographic techniques, be improved? The book focuses on Energy Efficient Modular Exponentiations for Cryptographic hardware. Spread across five chapters, this well-researched text focuses in detail on the Bit Forwarding Techniques and the corresponding hardware realizations. Readers will also discover advanced performance improvement techniques based on high radix multiplication and Cryptographic hardware based on multi-core architectures.

This book covers techniques that can be used to analyze data from IoT sensors and addresses questions regarding the performance of an IoT system. It strikes a balance between practice and theory so one can learn how to apply these tools in practice with a good understanding of their inner workings. This is an introductory book for readers who have no familiarity with these techniques. The techniques presented in An Introduction to IoT Analytics come from the areas of machine learning, statistics, and operations research. Machine learning techniques are described that can be used to analyze IoT data generated from sensors for clustering, classification, and regression. The statistical techniques described can be used to carry out regression and forecasting of IoT sensor data and dimensionality reduction of data sets. Operations research is concerned with the performance of an IoT system by constructing a model of the system under study and then carrying out a what-if analysis. The book also describes simulation techniques. Key Features IoT analytics is not just machine learning but also involves other tools, such as forecasting and simulation techniques. Many diagrams and examples are given throughout the book to fully explain the material presented. Each chapter concludes with a project designed to help readers better understand the techniques described. The material in this book has been class tested over several semesters. Practice exercises are included with solutions provided online at www.routledge.com/9780367686314 Harry G. Perros is a Professor of Computer Science at North Carolina State University, an Alumni Distinguished Graduate Professor, and an IEEE Fellow. He has published extensively in the area of performance modeling of computer and communication systems.

The complexity and severity of the Distributed Denial of Service (DDoS) attacks are increasing day-by-day. The Internet has a highly inconsistent structure in terms of resource distribution. Numerous technical solutions are available, but those involving economic aspects have not been given much consideration. The book, DDoS Attacks - Classification, Attacks, Challenges, and Countermeasures, provides an overview of both types of defensive solutions proposed so far, exploring different dimensions that would mitigate the DDoS effectively and show the implications associated with them. Features: Covers topics that describe taxonomies of the DDoS attacks in detail, recent trends and classification of defensive mechanisms on the basis of deployment location, the types of defensive action, and the solutions offering economic incentives. Introduces chapters discussing the various types of DDoS attack associated with different layers of security, an attacker's motivations, and the importance of incentives and liabilities in any defensive solution. Illustrates the role of fair resource-allocation schemes, separate payment mechanisms for attackers and legitimate users, negotiation models on cost and types of resources, and risk assessments and transfer mechanisms. DDoS Attacks - Classification, Attacks, Challenges, and Countermeasures is designed for the readers who have an interest in the cybersecurity domain, including students and researchers who are exploring different dimensions associated with the DDoS attack, developers and security professionals who are focusing on developing defensive schemes and applications for detecting or mitigating the DDoS attacks, and faculty members across different universities.

Using the SARS-CoV-2/CoVID-19 pandemic as a giant case study, and following the structure of the domains of information security, this book looks at what the crisis teaches us about security. It points out specific security fundamentals where social, medical, or business responses to the crisis failed or needed to make specific use of those concepts. For the most part, these lessons are simply reminders of factors that get neglected during times of non-crisis. The lessons particularly point out the importance of planning and resilience in systems and business. Those studying cybersecurity and its preventive measures and applications, as well as those involved in risk management studies and assessments, will all benefit greatly from the book. Robert Slade has had an extensive and prolific career in management, security, and telecommunications research, analysis, and consultancy. He has served as an educator visiting universities and delivering lecturers and seminars.

This book covers techniques that can be used to analyze data from IoT sensors and addresses questions regarding the performance of an IoT system. It strikes a balance between practice and theory so one can learn how to apply these tools in practice with a good understanding of their inner workings. This is an introductory book for readers who have no familiarity with these techniques. The techniques presented in An Introduction to IoT Analytics come from the areas of machine learning, statistics, and operations research. Machine learning techniques are described that can be used to analyze IoT data generated from sensors for clustering, classification, and regression. The statistical techniques described can be used to carry out regression and forecasting of IoT sensor data and dimensionality reduction of data sets. Operations research is concerned with the performance of an IoT system by constructing a model of the system under study and then carrying out a what-if analysis. The book also describes simulation techniques. Key Features IoT analytics is not just machine learning but also involves other tools, such as forecasting and simulation techniques. Many diagrams and examples are given throughout the book to fully explain the material presented. Each chapter concludes with a project designed to help readers better understand the techniques described. The material in this book has been class tested over several semesters. Practice exercises are included with solutions provided online at www.routledge.com/9780367686314 Harry G. Perros is a Professor of Computer Science at North Carolina State University, an Alumni Distinguished Graduate Professor, and an IEEE Fellow. He has published extensively in the area of performance modeling of computer and communication systems.

"This book addresses how health apps, in-home measurement devices, telemedicine, data mining, and artificial intelligence and smart medical algorithms are all enabled by the transition to a digital health infrastructure.....it provides a comprehensive background with which to understand what is happening in healthcare informatics and why."-C. William Hanson, III, MD, Chief Medical Information Officer and Vice President, University of Pennsylvania Health System. "This book is dedicated to the frontline healthcare workers, who through their courage and honor to their profession, helped maintain a reliable service to the population at large, during a chaotic time. These individuals withstood fear and engaged massive uncertainty and risk to perform their duties of providing care to those in need at a time of crisis. May the world never forget the COVID-19 pandemic and the courage of our healthcare workers".-Stephan P. Kudyba, Author Healthcare Informatics: Evolving Strategies in the Digital Era focuses on the services, technologies, and processes that are evolving in the healthcare industry. It begins with an introduction to the factors that are driving the digital age as it relates to the healthcare sector and then covers strategic topics such as risk management, project management, and knowledge management that are essential for successful digital initiatives. It delves into facets of the digital economy and how healthcare is adapting to the geographic, demographic, and physical needs of the population and highlights the emergence and importance of apps and telehealth. It also provides a high-level approach to managing pandemics by applying the various elements of the digital ecosystem. The book covers such technologies as: Computerized physician order entry (CPOE) Clinical Information Systems Alerting systems and medical sensors Electronic healthcare records (EHRs) Mobile healthcare and telehealth. Apps Business Intelligence and Decision Support Analytics Digital outreach to the population Artificial Intelligence The book then closes the loop on the efficiency enhancing process with a focus on utilizing analytics for problem solving for a variety of healthcare processes including the pharmaceutical sector. Finally, the book ends with current and futuristic views on evolving applications of AI throughout the industry.

This book is open access under a CC BY NC ND license. It addresses the most recent developments in cloud computing such as HPC in the Cloud, heterogeneous cloud, self-organising and self-management, and discusses the business implications of cloud computing adoption. Establishing the need for a new architecture for cloud computing, it discusses a novel cloud management and delivery architecture based on the principles of self-organisation and self-management. This focus shifts the deployment and optimisation effort from the consumer to the software stack running on the cloud infrastructure. It also outlines validation challenges and introduces a novel generalised extensible simulation framework to illustrate the effectiveness, performance and scalability of self-organising and self-managing delivery models on hyperscale cloud infrastructures. It concludes with a number of potential use cases for self-organising, self-managing clouds and the impact on those businesses.

Enabling Technologies for Next Generation Wireless Communications provides up-to-date information on emerging trends in wireless systems, their enabling technologies and their evolving application paradigms. This book includes the latest trends and developments toward next generation wireless communications. It highlights the requirements of next generation wireless systems, limitations of existing technologies in delivering those requirements and the need to develop radical new technologies. It focuses on bringing together information on various technological developments that are enablers vital to fulfilling the requirements of future wireless communication systems and their applications. Topics discussed include spectrum issues, network planning, signal processing, transmitter, receiver, antenna technologies, channel coding, security and application of machine learning and deep learning for wireless communication systems. The book also provides information on enabling business models for future wireless systems. This book is useful as a resource for researchers and practitioners worldwide, including industry practitioners, technologists, policy decision-makers, academicians, and graduate students.

Knowledge Architectures reviews traditional approaches to managing information and explains why they need to adapt to support 21st-century information management and discovery. Exploring the rapidly changing environment in which information is being managed and accessed, the book considers how to use knowledge architectures, the basic structures and designs that underlie all of the parts of an effective information system, to best advantage. Drawing on 40 years of work with a variety of organizations, Bedford explains that failure to understand the structure behind any given system can be the difference between an effective solution and a significant and costly failure. Demonstrating that the information user environment has shifted significantly in the past 20 years, the book explains that end users now expect designs and behaviors that are much closer to the way they think, work, and act. Acknowledging how important it is that those responsible for developing an information or knowledge management system understand knowledge structures, the book goes beyond a traditional library science perspective and uses case studies to help translate the abstract and theoretical to the practical and concrete. Explaining the structures in a simple and intuitive way and providing examples that clearly illustrate the challenges faced by a range of different organizations, Knowledge Architectures is essential reading for those studying and working in library and information science, data science, systems development, database design, and search system architecture and engineering.

Knowledge Architectures reviews traditional approaches to managing information and explains why they need to adapt to support 21st-century information management and discovery. Exploring the rapidly changing environment in which information is being managed and accessed, the book considers how to use knowledge architectures, the basic structures and designs that underlie all of the parts of an effective information system, to best advantage. Drawing on 40 years of work with a variety of organizations, Bedford explains that failure to understand the structure behind any given system can be the difference between an effective solution and a significant and costly failure. Demonstrating that the information user environment has shifted significantly in the past 20 years, the book explains that end users now expect designs and behaviors that are much closer to the way they think, work, and act. Acknowledging how important it is that those responsible for developing an information or knowledge management system understand knowledge structures, the book goes beyond a traditional library science perspective and uses case studies to help translate the abstract and theoretical to the practical and concrete. Explaining the structures in a simple and intuitive way and providing examples that clearly illustrate the challenges faced by a range of different organizations, Knowledge Architectures is essential reading for those studying and working in library and information science, data science, systems development, database design, and search system architecture and engineering.

Trust and Records in an Open Digital Environment explores issues that arise when digital records are entrusted to the cloud and will help professionals to make informed choices in the context of a rapidly changing digital economy. Showing that records need to ensure public trust, especially in the era of alternative truths, this volume argues that reliable resources, which are openly accessible from governmental institutions, e-services, archival institutions, digital repositories, and cloud-based digital archives, are the key to an open digital environment. The book also demonstrates that current established practices need to be reviewed and amended to include the networked nature of the cloud-based records, to investigate the role of new players, like cloud service providers (CSP), and assess the potential for implementing new, disruptive technologies like blockchain. Stancic and the contributors address these challenges by taking three themes - state, citizens, and documentary form - and discussing their interaction in the context of open government, open access, recordkeeping, and digital preservation. Exploring what is needed to enable the establishment of an open digital environment, Trust and Records in an Open Digital Environment should be essential reading for data, information, document, and records management professionals. It will also be a key text for archivists, librarians, professors, and students working in the information sciences and other related fields.

Trust and Records in an Open Digital Environment explores issues that arise when digital records are entrusted to the cloud and will help professionals to make informed choices in the context of a rapidly changing digital economy. Showing that records need to ensure public trust, especially in the era of alternative truths, this volume argues that reliable resources, which are openly accessible from governmental institutions, e-services, archival institutions, digital repositories, and cloud-based digital archives, are the key to an open digital environment. The book also demonstrates that current established practices need to be reviewed and amended to include the networked nature of the cloud-based records, to investigate the role of new players, like cloud service providers (CSP), and assess the potential for implementing new, disruptive technologies like blockchain. Stancic and the contributors address these challenges by taking three themes - state, citizens, and documentary form - and discussing their interaction in the context of open government, open access, recordkeeping, and digital preservation. Exploring what is needed to enable the establishment of an open digital environment, Trust and Records in an Open Digital Environment should be essential reading for data, information, document, and records management professionals. It will also be a key text for archivists, librarians, professors, and students working in the information sciences and other related fields.

Artificial Intelligence Techniques in IoT Sensor Networks is a technical book which can be read by researchers, academicians, students and professionals interested in artificial intelligence (AI), sensor networks and Internet of Things (IoT). This book is intended to develop a shared understanding of applications of AI techniques in the present and near term. The book maps the technical impacts of AI technologies, applications and their implications on the design of solutions for sensor networks. This text introduces researchers and aspiring academicians to the latest developments and trends in AI applications for sensor networks in a clear and well-organized manner. It is mainly useful for research scholars in sensor networks and AI techniques. In addition, professionals and practitioners working on the design of real-time applications for sensor networks may benefit directly from this book. Moreover, graduate and master's students of any departments related to AI, IoT and sensor networks can find this book fascinating for developing expert systems or real-time applications. This book is written in a simple and easy language, discussing the fundamentals, which relieves the requirement of having early backgrounds in the field. From this expectation and experience, many libraries will be interested in owning copies of this work.

Sustainable Entrepreneurship is nowadays considered as a discipline at the cross-roads of many others. This book describes recent cases, techniques and tools proposed for leaders, entrepreneurs, and practitioners who are involved and responsible for making strategic decisions in their companies and aiming at sustainable development. This book highlights the use of new business models/methods that can be employed by organizations and researchers to save millions of dollars, to enhance the economic growth, as well as to resolve environmental and social issues, via sustainable networks, renewal energy distribution, and social/green entrepreneurship. It will provide a comprehensive discussion of practical techniques, like Machine Learning, Robotics, Photovoltaic solar energy, in the field of renewable energy, and other digital tools, such as digital marketing, crowdsourcing platforms, and digital currency. Meanwhile, it will enlighten the way for entrepreneurs and decision makers by helping them to learn how to grow their business. The focus will be on how to benefit from these techniques to develop sustainable and renewable energy-based projects, as well as digitalized new ventures. The book walks the reader through the latest emerging trends in digitalization that can support practitioners, managers, entrepreneurs, and researchers to help them appreciate the application of sustainable solutions in various functional domains.

This book covers theory and practical knowledge of Probabilistic data structures (PDS) and Blockchain (BC) concepts. It introduces the applicability of PDS in BC to technology practitioners and explains each PDS through code snippets and illustrative examples. Further, it provides references for the applications of PDS to BC along with implementation codes in python language for various PDS so that the readers can gain confidence using hands on experience. Organized into five sections, the book covers IoT technology, fundamental concepts of BC, PDS and algorithms used to estimate membership query, cardinality, similarity and frequency, usage of PDS in BC based IoT and so forth.

IoT is empowered by various technologies used to detect, gather, store, act, process, transmit, oversee, and examine information. The combination of emergent technologies for information processing and distributed security, such as Cloud computing, Artificial intelligence, and Blockchain, brings new challenges in addressing distributed security methods that form the foundation of improved and eventually entirely new products and services. As systems interact with each other, it is essential to have an agreed interoperability standard, which is safe and valid. This book aims at providing an introduction by illustrating state-of-the-art security challenges and threats in IoT and the latest developments in IoT with Cloud, AI, and Blockchain security challenges. Various application case studies from domains such as science, engineering, and healthcare are introduced, along with their architecture and how they leverage various technologies Cloud, AI, and Blockchain. This book provides a comprehensive guide to researchers and students to design IoT integrated AI, Cloud, and Blockchain projects and to have an overview of the next generation challenges that may arise in the coming years.

Computing systems are becoming highly complex, harder to understand, and therefore more prone to failure. Where such systems control aircraft for example, system failure could have disastrous consequences. It is important therefore that we are able to employ mathematical techniques to specify the behavior of critical systems. This thesis uses the theory of Communicating Sequential Processes to show how a real-time system (a system that maintains a continuous interaction with its environment) may be specified. Included is a case study in which a local area network protocol is described at two levels of abstraction, and a general method for structuring CSP descriptions of layered protocols is given. The research contained here represents the very latest work on the specification and verification of real-time systems.