Blockchain Technology for Emerging Applications: A Comprehensive Approach explores recent theories and applications of the execution of blockchain technology. Chapters look at a wide range of application areas, including healthcare, digital physical frameworks, web of-things, smart transportation frameworks, interruption identification frameworks, ballot-casting, architecture, smart urban communities, and digital rights administration. The book addresses the engineering, plan objectives, difficulties, constraints, and potential answers for blockchain-based frameworks. It also looks at blockchain-based design perspectives of these intelligent architectures for evaluating and interpreting real-world trends. Chapters expand on different models which have shown considerable success in dealing with an extensive range of applications, including their ability to extract complex hidden features and learn efficient representation in unsupervised environments for blockchain security pattern analysis.

Build a solid foundation in data analysis skills and pursue a coveted Data+ certification with this intuitive study guide CompTIA Data+ Study Guide: Exam DA0-001 delivers easily accessible and actionable instruction for achieving data analysis competencies required for the job and on the CompTIA Data+ certification exam. You'll learn to collect, analyze, and report on various types of commonly used data, transforming raw data into usable information for stakeholders and decision makers. With comprehensive coverage of data concepts and environments, data mining, data analysis, visualization, and data governance, quality, and controls, this Study Guide offers: All the information necessary to succeed on the exam for a widely accepted, entry-level credential that unlocks lucrative new data analytics and data science career opportunities 100% coverage of objectives for the NEW CompTIA Data+ exam Access to the Sybex online learning resources, with review questions, full-length practice exam, hundreds of electronic flashcards, and a glossary of key terms Ideal for anyone seeking a new career in data analysis, to improve their current data science skills, or hoping to achieve the coveted CompTIA Data+ certification credential, CompTIA Data+ Study Guide: Exam DA0-001 provides an invaluable head start to beginning or accelerating a career as an in-demand data analyst.

Opinion Mining and Text Analytics on Literary Works and Social Media introduces the use of artificial intelligence and big data analytics techniques which can apply opinion mining and text analytics on literary works and social media. This book focuses on theories, method and approaches in which data analytic techniques can be used to analyze data from social media, literary books, novels, news, texts, and beyond to provide a meaningful pattern. The subject area of this book is multidisciplinary; related to data science, artificial intelligence, social science and humanities, and literature. This is an essential resource for scholars, Students and lecturers from various fields of data science, artificial intelligence, social science and humanities, and literature, university libraries, new agencies, and many more.

The digital transformation of the 21st century has affected all facets of society and has been highly advantageous in many industries, including urban planning and regional development. The practices, strategies, and developments surrounding urban e-planning in particular have been constantly shifting and adapting to new innovations as they arrive. Trends and Innovations in Urban E-Planning provides an updated panorama of the main trends, challenges, and recent innovations in the field of e-planning through the critical perspectives of diverse experts. This book adds new and updated evidence on recent changes in this field and provides critical insights on these innovations. Covering topics such as citizen engagement, land property management, and spatial planning, this book is an essential resource for students and educators of higher education, researchers, urban planners, engineers, public officials, community groups, and academicians.

Machine Learning Algorithms for Signal and Image Processing Enables readers to understand the fundamental concepts of machine and deep learning techniques with interactive, real-life applications within signal and image processing Machine Learning Algorithms for Signal and Image Processing aids the reader in designing and developing real-world applications using advances in machine learning to aid and enhance speech signal processing, image processing, computer vision, biomedical signal processing, adaptive filtering, and text processing. It includes signal processing techniques applied for pre-processing, feature extraction, source separation, or data decompositions to achieve machine learning tasks. Written by well-qualified authors and contributed to by a team of experts within the field, the work covers a wide range of important topics, such as: Speech recognition, image reconstruction, object classification and detection, and text processing Healthcare monitoring, biomedical systems, and green energy How various machine and deep learning techniques can improve accuracy, precision rate recall rate, and processing time Real applications and examples, including smart sign language recognition, fake news detection in social media, structural damage prediction, and epileptic seizure detection Professionals within the field of signal and image processing seeking to adapt their work further will find immense value in this easy-to-understand yet extremely comprehensive reference work. It is also a worthy resource for students and researchers in related fields who are looking to thoroughly understand the historical and recent developments that have been made in the field.

Optimum-Path Forest: Theory, Algorithms, and Applications was first published in 2008 in its supervised and unsupervised versions with applications in medicine and image classification. Since then, it has expanded to a variety of other applications such as remote sensing, electrical and petroleum engineering, and biology. In recent years, multi-label and semi-supervised versions were also developed to handle video classification problems. The book presents the principles, algorithms and applications of Optimum-Path Forest, giving the theory and state-of-the-art as well as insights into future directions.

Now in its fifth edition, Foundations of Software Testing: ISTQB Certification is the essential guide to software testing and to the ISTQB Foundation qualification written by respected international authorities in software testing who themselves helped develop the ISTQB Syllabus. Completely updated to comprehensively reflect the most recent changes to the ISTQB Foundation Syllabus v 4.0, 2023, this book adopts a practical, hands-on approach, covering the fundamental topics that every system and software tester should know. About ISTQBInternational Software Testing Qualifications Board (ISTQB) is a multinational body overseeing the development of international qualifications in software testing. It offers an internationally recognized qualification that ensures there is an international, common understanding of software and system testing issues.

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

From climate change forecasts and pandemic maps to Lego sets and Ancestry algorithms, models encompass our world and our lives. In her thought-provoking new book, Annabel Wharton begins with a definition drawn from the quantitative sciences and the philosophy of science but holds that history and critical cultural theory are essential to a fuller understanding of modeling. Considering changes in the medical body model and the architectural model, from the Middle Ages to the twenty-first century, Wharton demonstrates the ways in which all models are historical and political. Examining how cadavers have been described, exhibited, and visually rendered, she highlights the historical dimension of the modified body and its depictions. Analyzing the varied reworkings of the Holy Sepulchre in Jerusalem-including by monumental commanderies of the Knights Templar, Alberti's Rucellai Tomb in Florence, Franciscans' olive wood replicas, and video game renderings-she foregrounds the political force of architectural representations. And considering black boxes-instruments whose inputs we control and whose outputs we interpret, but whose inner workings are beyond our comprehension-she surveys the threats posed by such opaque computational models, warning of the dangers that models pose when humans lose control of the means by which they are generated and understood. Engaging and wide-ranging, Models and World Making conjures new ways of seeing and critically evaluating how we make and remake the world in which we live.

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

Ethical Practice of Statistics and Data Science is intended to prepare people to fully assume their responsibilities to practice statistics and data science ethically. Aimed at early career professionals, practitioners, and mentors or supervisors of practitioners, the book supports the ethical practice of statistics and data science, with an emphasis on how to earn the designation of, and recognize, "the ethical practitioner". The book features 47 case studies, each mapped to the Data Science Ethics Checklist (DSEC); Data Ethics Framework (DEFW); the American Statistical Association (ASA) Ethical Guidelines for Statistical Practice; and the Association of Computing Machinery (ACM) Code of Ethics. It is necessary reading for students enrolled in any data intensive program, including undergraduate or graduate degrees in (bio-)statistics, business/analytics, or data science. Managers, leaders, supervisors, and mentors who lead data-intensive teams in government, industry, or academia would also benefit greatly from this book. This is a companion volume to Ethical Reasoning For A Data-Centered World, also published by Ethics International Press (2022). These are the first and only books to be based on, and to provide guidance to, the ASA and ACM Ethical Guidelines/Code of Ethics.

Fractional-order Modelling of Dynamic Systems with Applications in Optimization, Signal Processing and Control introduces applications from a design perspective, helping readers plan and design their own applications. The book includes the different techniques employed to design fractional-order systems/devices comprehensively and straightforwardly. Furthermore, mathematics is available in the literature on how to solve fractional-order calculus for system applications. This book introduces the mathematics that has been employed explicitly for fractional-order systems. It will prove an excellent material for students and scholars who want to quickly understand the field of fractional-order systems and contribute to its different domains and applications. Fractional-order systems are believed to play an essential role in our day-to-day activities. Therefore, several researchers around the globe endeavor to work in the different domains of fractional-order systems. The efforts include developing the mathematics to solve fractional-order calculus/systems and to achieve the feasible designs for various applications of fractional-order systems.

Recent Trends in Computer-aided Diagnostic Systems for Skin Diseases: Theory, Implementation, and Analysis provides comprehensive coverage on the development of computer-aided diagnostic (CAD) systems employing image processing and machine learning tools for improved, uniform evaluation and diagnosis (avoiding subjective judgment) of skin disorders. The methods and tools are described in a general way so that these tools can be applied not only for skin diseases but also for a wide range of analogous problems in the domain of biomedical systems. Moreover, quantification of clinically relevant information that can associate the findings of physicians/experts is the most challenging task of any CAD system. This book gives all the details in a step-by-step form for different modules so that the readers can develop each of the modules like preprocessing, feature extraction/learning, disease classification, as well as an entire expert diagnosis system themselves for their own applications.

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

Data Communications and Networking, 6th Edition, teaches the principles of networking using TCP/IP protocol suite. It employs a bottom-up approach where each layer in the TCP/IP protocol suite is built on the services provided by the layer below. This edition has undergone a major restructuring to reduce the number of chapters and focus on the organization of TCP/IP protocol suite. It concludes with three chapters that explore multimedia, network management, and cryptography/network security. Technologies related to data communications and networking are among the fastest growing in our culture today, and there is no better guide to this rapidly expanding field than Data Communications and Networking.

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

Cyber-Physical Systems: AI and COVID-19 highlights original research which addresses current data challenges in terms of the development of mathematical models, cyber-physical systems-based tools and techniques, and the design and development of algorithmic solutions, etc. It reviews the technical concepts of gathering, processing and analyzing data from cyber-physical systems (CPS) and reviews tools and techniques that can be used. This book will act as a resource to guide COVID researchers as they move forward with clinical and epidemiological studies on this outbreak, including the technical concepts of gathering, processing and analyzing data from cyber-physical systems (CPS). The major problem in the identification of COVID-19 is detection and diagnosis due to non-availability of medicine. In this situation, only one method, Reverse Transcription Polymerase Chain Reaction (RT-PCR) has been widely adopted and used for diagnosis. With the evolution of COVID-19, the global research community has implemented many machine learning and deep learning-based approaches with incremental datasets. However, finding more accurate identification and prediction methods are crucial at this juncture.

Tensors for Data Processing: Theory, Methods and Applications presents both classical and state-of-the-art methods on tensor computation for data processing, covering computation theories, processing methods, computing and engineering applications, with an emphasis on techniques for data processing. This reference is ideal for students, researchers and industry developers who want to understand and use tensor-based data processing theories and methods. As a higher-order generalization of a matrix, tensor-based processing can avoid multi-linear data structure loss that occurs in classical matrix-based data processing methods. This move from matrix to tensors is beneficial for many diverse application areas, including signal processing, computer science, acoustics, neuroscience, communication, medical engineering, seismology, psychometric, chemometrics, biometric, quantum physics and quantum chemistry.

The topic of creativity has only been on the fringes of pedagogy as it has been deemed either abstract or not measurable and therefore non-standardizable for educational purposes. However, most progressive educators from around the world used creativity as a means for cultural reformation and as a means of social justice. The focus of this edited book will be on culture and creativity. Chapters will consider various topics related to creativity such as - Is creativity cultural? How can creativity and culturally relevant pedagogy go together? Given the current state of education all over the world due to the Pandemic, topics related to creativity and teaching remotely will also be featured. Teachers often say one of two things - they are not creative or that they don't have the time to be creative given the curricular, administrative directions they are required to follow. However, each day, teachers find exceptionally creative ways to engage their students. Especially in the current situation of remote learning, teachers are relying on their creativity to not only create impactful lessons but also teach them creative lessons. While the focus of this book will be around the topic of culture and creativity, asking how it may be cultural; it will also cover a wide range of topics related to creativity and pedagogy as noted in the list of topics. Essentially, this book will ask if creativity is cultural, what implications does this have in terms of cultivating or teaching/learning creativity?

Deep Reinforcement Learning for Wireless Communications and Networking Comprehensive guide to Deep Reinforcement Learning (DRL) as applied to wireless communication systems Deep Reinforcement Learning for Wireless Communications and Networking presents an overview of the development of DRL while providing fundamental knowledge about theories, formulation, design, learning models, algorithms and implementation of DRL together with a particular case study to practice. The book also covers diverse applications of DRL to address various problems in wireless networks, such as caching, offloading, resource sharing, and security. The authors discuss open issues by introducing some advanced DRL approaches to address emerging issues in wireless communications and networking. Covering new advanced models of DRL, e.g., deep dueling architecture and generative adversarial networks, as well as emerging problems considered in wireless networks, e.g., ambient backscatter communication, intelligent reflecting surfaces and edge intelligence, this is the first comprehensive book studying applications of DRL for wireless networks that presents the state-of-the-art research in architecture, protocol, and application design. Deep Reinforcement Learning for Wireless Communications and Networking covers specific topics such as: Deep reinforcement learning models, covering deep learning, deep reinforcement learning, and models of deep reinforcement learning Physical layer applications covering signal detection, decoding, and beamforming, power and rate control, and physical-layer security Medium access control (MAC) layer applications, covering resource allocation, channel access, and user/cell association Network layer applications, covering traffic routing, network classification, and network slicing With comprehensive coverage of an exciting and noteworthy new technology, Deep Reinforcement Learning for Wireless Communications and Networking is an essential learning resource for researchers and communications engineers, along with developers and entrepreneurs in autonomous systems, who wish to harness this technology in practical applications.

Fractional Order Systems: An Overview of Mathematics, Design, and Applications for Engineers introduces applications from a design perspective, helping readers plan and design their own applications. The book includes the different techniques employed to design fractional-order systems/devices comprehensively and straightforwardly. Furthermore, mathematics is available in the literature on how to solve fractional-order calculus for system applications. This book introduces the mathematics that has been employed explicitly for fractional-order systems. It will prove an excellent material for students and scholars who want to quickly understand the field of fractional-order systems and contribute to its different domains and applications. Fractional-order systems are believed to play an essential role in our day-to-day activities. Therefore, several researchers around the globe endeavor to work in the different domains of fractional-order systems. The efforts include developing the mathematics to solve fractional-order calculus/systems and to achieve the feasible designs for various applications of fractional-order systems.