This book covers a wide range of topics on the role of Artificial Intelligence, Machine Learning, and Big Data for healthcare applications and deals with the ethical issues and concerns associated with it. This book explores the applications in different areas of healthcare and highlights the current research. "Big Data and Artificial Intelligence for Healthcare Applications" covers healthcare big data analytics, mobile health and personalized medicine, clinical trial data management and presents how Artificial Intelligence can be used for early disease diagnosis prediction and prognosis. It also offers some case studies that describes the application of Artificial Intelligence and Machine Learning in healthcare. Researchers, healthcare professionals, data scientists, systems engineers, students, programmers, clinicians, and policymakers will find this book of interest.

Textual Statistics with R comprehensively covers the main multidimensional methods in textual statistics supported by a specially-written package in R. Methods discussed include correspondence analysis, clustering, and multiple factor analysis for contigency tables. Each method is illuminated by applications. The book is aimed at researchers and students in statistics, social sciences, hiistory, literature and linguistics. The book will be of interest to anyone from practitioners needing to extract information from texts to students in the field of massive data, where the ability to process textual data is becoming essential.

It is a major challenge to migrate very large databases from one system, say for example, to transfer critical data from Oracle to SQL Server. One has to consider several issues such as loss of data being transferred, the security of the data, the cost and effort, technical aspects of the software involved, etc. There a very few books that provide practical tools and the methodology to migrate data from one vendor to another. This book introduces the concepts in database migration with large sample databases. It provides step by step guides and screenshots for database migration tools. Many examples are shown for migrating Oracle, SQL Server and MySQL databases.

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.

Healthcare transformation requires us to continually look at new and better ways to manage insights - both within and outside the organization today. Increasingly, the ability to glean and operationalize new insights efficiently as a byproduct of an organization's day-to-day operations is becoming vital to hospitals and health systems ability to survive and prosper. One of the long-standing challenges in healthcare informatics has been the ability to deal with the sheer variety and volume of disparate healthcare data and the increasing need to derive veracity and value out of it. Demystifying Big Data and Machine Learning for Healthcare investigates how healthcare organizations can leverage this tapestry of big data to discover new business value, use cases, and knowledge as well as how big data can be woven into pre-existing business intelligence and analytics efforts. This book focuses on teaching you how to: Develop skills needed to identify and demolish big-data myths Become an expert in separating hype from reality Understand the V's that matter in healthcare and why Harmonize the 4 C's across little and big data Choose data fi delity over data quality Learn how to apply the NRF Framework Master applied machine learning for healthcare Conduct a guided tour of learning algorithms Recognize and be prepared for the future of artificial intelligence in healthcare via best practices, feedback loops, and contextually intelligent agents (CIAs) The variety of data in healthcare spans multiple business workflows, formats (structured, un-, and semi-structured), integration at point of care/need, and integration with existing knowledge. In order to deal with these realities, the authors propose new approaches to creating a knowledge-driven learning organization-based on new and existing strategies, methods and technologies. This book will address the long-standing challenges in healthcare informatics and provide pragmatic recommendations on how to deal with them.

Blockchain technology is poised to revolutionize more than just payment and crypto-currency. Many vertical industries will be reshaped by the new trusted data models enabled and inspired by the blockchain - healthcare is no exception. In fact, healthcare may hold the greatest opportunities for meaningful use of the technology. Early pioneers have explored some of the first use cases for medical payments, electronic health records, HIPAA/data privacy, drug counterfeiting, and credentialing of healthcare professionals. We have only begun to scratch the surface in how to automate the complexities of today's healthcare systems and design new systems which focus on trust, transparency and the alignment of incentives. Metcalf, Bass, Dhillon, and Hooper have curated a collection of examples based on the fundamentals of blockchain that build upon the early successes and examples that point to the future. After a brief introduction to bitcoin, blockchain and the protocols available, a getting-started guide is presented specific to health and healthcare. The authors discuss the complexities and possibilities of smart contracts and some of the early consortia that are exploring the possibilities. Examples and use cases are found throughout the book, with specific sections that cover the more sophisticated and far-reaching examples which have the potential to scale at the industry-level. In addition, a discussion of integrating blockchain technology into other advanced healthcare trends and IT systems - such as telemedicine, artificial intelligence, machine learning, the Internet of Things, value-based payments , patient engagement solutions, big data solutions, medical tourism, and precision medicine/genetic therapies among many others are presented. The final section provides a glimpse into the future using blockchain technology and examples of research projects that are still in labs across the globe. The appendices may prove particularly useful for additional details on how to get started, including resources and organizations specifically focusing on blockchain and distributed ledger solutions.

Big Data is now highly regarded and accepted as a useful tool to help organizations manage their data and information effectively and efficiently. This new volume, The Emerging Technology of Big Data: Its Impact as a Tool for ICT Development, looks at the new technology that has emerged to meet the growing need and demand and studies the impact of Big Data in several areas of today's society, including social media, business process re-engineering, science, e-learning, higher education, business intelligence, and green computing. In today's modern society, information system (IS) through Big Data contributes to the success of organizations because it provides a solid foundation for increasing both efficiency and productivity. Many business organizations and educational institutions realize that compliance with Big Data will affect their prospects for success. Everyday, the amount of data collected from digital tools grows tremendously. As the amount of data increases, the use of IS becomes more and more essential. The book looks at how large datasets and analytics have slowly crept into the world of education and discusses methods of teaching and learning and the collection of student-learning data. The final chapter of the book considers the environmental impacts of ICT and emphasizes green ICT awareness as a corporate strategy through information systems. The global ICT industry accounts for approximately 2 percent of global carbon dioxide (CO2) emissions, and the manufacture, shipping, and disposal of ICT equipment also contributes environmentally. This chapter addresses these issues. The information provided here will be valuable information for education professionals, businesses, faculty, scientists and researchers, and others.

This volume brings together research and system designs that address the scientific basis and the practical systems design issues that support areas ranging from intelligent business interfaces and predictive analytics to economics modeling. Applications for management science and IT have been of interest areas for business schools and computing experts during recent years. Among the areas that are being treated are modern analytics, heterogeneous computing, business intelligence, ERP (enterprise resource planning), and decision science. Consumers have been pledging their love for data visualizations for a while now, and data is the area being explored, such as B2B and EC (E-commerce), E-business and the Intelligent Web, CRM (customer relationship management), infrastructures, and more. The digitization implications of these many new applications are described and explored in this informative volume. One of BookAuthority's Best New Analytics Books to Read in 2020!

Physically Unclonable Functions (PUFs) translate unavoidable variations in certain parameters of materials, waves, or devices into random and unique signals. They have found many applications in the Internet of Things (IoT), authentication systems, FPGA industry, several other areas in communications and related technologies, and many commercial products. Statistical Trend Analysis of Physically Unclonable Functions first presents a review on cryptographic hardware and hardware-assisted cryptography. The review highlights PUF as a mega trend in research on cryptographic hardware design. Afterwards, the authors present a combined survey and research work on PUFs using a systematic approach. As part of the survey aspect, a state-of-the-art analysis is presented as well as a taxonomy on PUFs, a life cycle, and an established ecosystem for the technology. In another part of the survey, the evolutionary history of PUFs is examined, and strategies for further research in this area are suggested. In the research side, this book presents a novel approach for trend analysis that can be applied to any technology or research area. In this method, a text mining tool is used which extracts 1020 keywords from the titles of the sample papers. Then, a classifying tool classifies the keywords into 295 meaningful research topics. The popularity of each topic is then numerically measured and analyzed over the course of time through a statistical analysis on the number of research papers related to the topic as well as the number of their citations. The authors identify the most popular topics in four different domains; over the history of PUFs, during the recent years, in top conferences, and in top journals. The results are used to present an evolution study as well as a trend analysis and develop a roadmap for future research in this area. This method gives an automatic popularity-based statistical trend analysis which eliminates the need for passing personal judgments about the direction of trends, and provides concrete evidence to the future direction of research on PUFs. Another advantage of this method is the possibility of studying a whole lot of existing research works (more than 700 in this book). This book will appeal to researchers in text mining, cryptography, hardware security, and IoT.

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.

Healthcare Informatics: Improving Efficiency through Technology, Analytics, and Management supplies an understanding of the different types of healthcare service providers, corresponding information technologies, analytic methods, and data issues that play a vital role in transforming the healthcare industry. All of these elements are reshaping the various activities such as workflow and processes of hospitals, healthcare systems, ACOs, and patient analytics, including hot spotting, risk stratification, and treatment effectiveness. A follow-up to Healthcare Informatics: Improving Efficiency and Productivity, this latest book includes new content that examines the evolution of Big Data and how it is revolutionizing the healthcare industry. It presents strategies for achieving national goals for the meaningful use of health information technology and includes sound project management principles and case illustrations for technology roll-out, such as Computer Physician Order Entry (CPOE) for optimal utilization. The book describes how to enhance process efficiency by linking technologies, data, and analytics with strategic initiatives to achieve success. It explains how to leverage data resources with analytics to enhance decision support for care providers through in-depth descriptions of the array of analytic methods that are used to create actionable information, including Business Intelligence, Six Sigma, Data, and Text Mining.

The recent explosive growth of biological data has lead to a rapid increase in the number of molecular biology databases. Held in many different locations and often using varying interfaces and non-standard data formats, integrating and comparing data from these multiple databases can be difficult and time-consuming. This book provides an overview of the key tools currently available for large-scale comparisons of gene sequences and annotations, focusing on the databases and tools from the University of California, Santa Cruz (UCSC), Ensembl, and the National Centre for Biotechnology Information (NCBI). Written specifically for biology and bioinformatics students and researchers, it aims to give an appreciation for the methods by which the browsers and their databases are constructed, enabling readers to determine which tool is the most appropriate for their requirements. Each chapter contains a summary and exercises to aid understanding and promote effective use of these important tools.

Translational bioinformatics (TBI) involves development of storage, analytics, and advanced computational methods to harvest knowledge from voluminous biomedical and genomic data into 4P healthcare (proactive, predictive, preventive, and participatory). Translational Bioinformatics Applications in Healthcare offers a detailed overview on concepts of TBI, biological and clinical databases, clinical informatics, and pertinent real-case applications. It further illustrates recent advancements, tools, techniques, and applications of TBI in healthcare, including Internet of Things (IoT) potential, toxin databases, medical image analysis and telemedicine applications, analytics of COVID-19 CT images, viroinformatics and viral diseases, and COVID-19-related research. Covers recent technologies such as Blockchain, IoT, and Big data analytics in bioinformatics Presents the role of translational bioinformatic methods in the field of viroinformatics, as well as in drug development and repurposing Includes translational healthcare and NGS for clinical applications Illustrates translational medicine systems and their applications in better healthcare Explores medical image analysis with focus on CT images and novel coronavirus disease detection Aimed at researchers and graduate students in computational biology, data mining and knowledge discovery, algorithms and complexity, and interdisciplinary fields of studies, including bioinformatics, health-informatics, biostatistics, biomedical engineering, and viroinformatics. Khalid Raza is an Assistant Professor, the Department of Computer Science, Jamia Millia Islamia (Central University), New Delhi. His research interests include translational bioinformatics, computational intelligence methods and its applications in bioinformatics, viroinformatics, and health informatics. Nilanjan Dey is an Associate Professor, the Department of Computer Science and Engineering, JIS University, Kolkata, India. His research interests include medical imaging, machine learning, computer-aided diagnosis, and data mining.

The book aims to showcase the basics of both IoT and Blockchain for beginners as well as their integration and challenge discussions for existing practitioner. It aims to develop understanding of the role of blockchain in fostering security. The objective of this book is to initiate conversations among technologists, engineers, scientists, and clinicians to synergize their efforts in producing low-cost, high-performance, highly efficient, deployable IoT systems. It presents a stepwise discussion, exhaustive literature survey, rigorous experimental analysis and discussions to demonstrate the usage of blockchain technology for securing communications. The book evaluates, investigate, analyze and outline a set of security challenges that needs to be addressed in the near future. The book is designed to be the first reference choice at research and development centers, academic institutions, university libraries and any institutions interested in exploring blockchain. UG/PG students, PhD Scholars of this fields, industry technologists, young entrepreneurs and researchers working in the field of blockchain technology are the primary audience of this book.

This multi-contributed handbook focuses on the latest workings of IoT (internet of Things) and Big Data. As the resources are limited, it's the endeavor of the authors to support and bring the information into one resource. The book is divided into 4 sections that covers IoT and technologies, the future of Big Data, algorithms, and case studies showing IoT and Big Data in various fields such as health care, manufacturing and automation. Features Focuses on the latest workings of IoT and Big Data Discusses the emerging role of technologies and the fast-growing market of Big Data Covers the movement toward automation with hardware, software, and sensors, and trying to save on energy resources Offers the latest technology on IoT Presents the future horizons on Big Data

Social networking has increased drastically in recent years, resulting in an increased amount of data being created daily. Furthermore, diversity of issues and complexity of the social networks pose a challenge in social network mining. Traditional algorithm software cannot deal with such complex and vast amounts of data, necessitating the development of novel analytic approaches and tools. This reference work deals with social network aspects of big data analytics. It covers theory, practices and challenges in social networking. The book spans numerous disciplines like neural networking, deep learning, artificial intelligence, visualization, e-learning in higher education, e-healthcare, security and intrusion detection.

Manufacturing, like other industries, is rising to the challenges imposed by aggressive consumer demands and the need for cost-effective processing that delivers quality in the fastest possible time. Fierce competition means that keeping abreast of new developments and applications in technology is essential if companies are to meet demands profitably and keep ahead of competitors. This book investigates the design and management of digital manufacturing and assembly systems for an efficient, flexible, and modular production of customized products using the I40 (industry 4.0)-enabling technologies. This book will also provide case studies covering modeling, simulation, and optimization. eBook includes color figures. Discusses how the advancement of data communication and storage through the Internet of Things (IoT) opens the possibilities of connecting sensors, robots, and devices Sheds light on how the human role in industry is decreasing due to the development of connected manufacturing floors, allowing them to take more control over the manufacturing processes, decisions, and even maintenance Covers the benefits from exploiting digital manufacturing, manufacturing enterprises, and what they expect to achieve Explains the important roles that modeling, simulation, and optimization play Investigates the design and management of digital manufacturing and assembly systems for an efficient, flexible, and modular production of customized products exploiting the I40 (industry 4.0)-enabling technologies

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.

This new volume looks at the electrifying world of blockchain technology and how it has been revolutionizing the Internet of Things and cyber-physical systems. Aimed primarily at business users and developers who are considering blockchain-based projects, the volume provides a comprehensive introduction to the theoretical and practical aspects of blockchain technology. It presents a selection of chapters on topics that cover new information on blockchain and bitcoin security, IoT security threats and attacks, privacy issues, fault-tolerance mechanisms, and more. Some major software packages are discussed, and it also addresses the legal issues currently affecting the field. The information presented here is relevant to current and future problems relating to blockchain technology and will provide the tools to build efficient decentralized applications. Blockchain technology and the IoT can profoundly change how the world-and businesses-work, and this book provides a window into the current world of blockchain. No longer limited to just Bitcoin, blockchain technology has spread into many sectors and into a significant number of different technologies.

The study and application of spatial information systems have been developed primarily from the use of computers in the geosciences. These systems have the principle functions of capturing, storing, representing, manipulating, and displaying data in 2-D and 3-D worlds. This book approaches its subject from the perspectives of informatics and geography, presenting methods of conceptual modeling developed in computer science that provide valuable aids for resolving spatial problems. This book is an essential textbook for both students and practitioners. It is indispensable for academic geographers, computer scientists, and the GIS professional.
Key Features
* Serves as the first comprehensive textbook on the field of Spatial Information Systems (also known as Geographic Information Systems)
* Contains extensive illustrations
* Presents numerous detailed examples

Data-Oriented Programming teaches you to design and implement software using the data-oriented programming paradigm. In it, you'll learn author Yehonathan Sharvit's unique approach to DOP that he has developed over a decade of experience. Every chapter contains a new light bulb moment that will change the way you think about programming. As you read, you'll build a library management system using the DOP paradigm. You'll design data models for business entities, manipulate immutable data collections, and write unit tests for data-oriented systems. About the Technology Data-oriented programming is an exciting new paradigm that eliminates the usual complexity caused by combining data and code into objects and classes. In DOP, you maintain application data in persistent generic data structures separated from the program's code. You use general-purpose functions to manipulate the data without mutating it. This approach rids your applications of state-related bugs and makes your code much easier to understand and maintain.

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.

Data Science for Wind Energy provides an in-depth discussion on how data science methods can improve decision making for wind energy applications, near-ground wind field analysis and forecast, turbine power curve fitting and performance analysis, turbine reliability assessment, and maintenance optimization for wind turbines and wind farms. A broad set of data science methods covered, including time series models, spatio-temporal analysis, kernel regression, decision trees, kNN, splines, Bayesian inference, and importance sampling. More importantly, the data science methods are described in the context of wind energy applications, with specific wind energy examples and case studies. Please also visit the author's book site at https://aml.engr.tamu.edu/book-dswe. Features Provides an integral treatment of data science methods and wind energy applications Includes specific demonstration of particular data science methods and their use in the context of addressing wind energy needs Presents real data, case studies and computer codes from wind energy research and industrial practice Covers material based on the author's ten plus years of academic research and insights

Good data analytics is the basis for effective decisions. Whoever has the data, has the ability to extract information promptly and effectively to make pertinent decisions. The premise of this handbook is to empower users and tool developers with the appropriate collection of formulas and techniques for data analytics and to serve as a quick reference to keep pertinent formulas within fingertip reach of readers. This handbook includes formulas that will appeal to mathematically inclined readers. It discusses how to use data analytics to improve decision-making and is ideal for those new to using data analytics to show how to expand their usage horizon. It provides quantitative techniques for modeling pandemics, such as COVID-19. It also adds to the suite of mathematical tools for emerging technical areas. This handbook is a handy reference for researchers, practitioners, educators, and students in areas such as industrial engineering, production engineering, project management, civil engineering, mechanical engineering, technology management, and business management worldwide.

New technologies mean that sports clubs and governing bodies are generating more data than ever to help manage their relationship with fans, their performance, and their income streams. This new edition of Winning with Data in the Business of Sports explains how to acquire, store, maintain, and use data in the most effective ways. The key developments are three-fold: new technology, new understanding of how to apply that technology, and the new laws informing and controlling the data that can be generated from the technology. Important developments that have occurred since the publication of the first edition include the General Data Protection Regulations (GDPR) and the COVID-19 pandemic. With a focus on these unique challenges coupled with the opportunities the use of data creates, this book is essential reading for professionals within the sports industry. This second edition includes: - An introduction to new technologies, the data they generate, and the supporting processes we need to have in place to use them. - Brand new case studies with recent examples of creative applications from clubs, teams, leagues, and governing bodies, including Arsenal, AS Roma, ICC Cricket World Cup, LA Kings, Portland Trail Blazers, and UEFA. - The sports industry's response to tighter data legislation introduced primarily though the GDPR. - The role of data and direct engagement during the COVID-19 pandemic. The book provides clear guidance and knowledge that sports industry professionals need to understand the role of data for the business side of sports. It is essential reading for sports clubs, governing bodies and those working in sports marketing, media and communications, sponsorship, merchandise, ticketing, events, and participation development. The book will also be of interest to students of sports management.