Food is a necessary aspect of human life, and agriculture is crucial to any country's global economy. Because the food business is essential to both a country's economy and global economy, artificial intelligence (AI)-based smart solutions are needed to assure product quality and food safety. The agricultural sector is constantly under pressure to boost crop output as a result of population growth. This necessitates the use of AI applications. Artificial Intelligence Applications in Agriculture and Food Quality Improvement discusses the application of AI, machine learning, and data analytics for the acceleration of the agricultural and food sectors. It presents a comprehensive view of how these technologies and tools are used for agricultural process improvement, food safety, and food quality improvement. Covering topics such as diet assessment research, crop yield prediction, and precision farming, this premier reference source is an essential resource for food safety professionals, quality assurance professionals, agriculture specialists, crop managers, agricultural engineers, food scientists, computer scientists, AI specialists, students, libraries, government officials, researchers, and academicians.

Present day sophisticated, adaptive, and autonomous (to a certain degree) robotic technology is a radically new stimulus for the cognitive system of the human learner from the earliest to the oldest age. It deserves extensive, thorough, and systematic research based on novel frameworks for analysis, modelling, synthesis, and implementation of CPSs for social applications. Cyber-Physical Systems for Social Applications is a critical scholarly book that examines the latest empirical findings for designing cyber-physical systems for social applications and aims at forwarding the symbolic human-robot perspective in areas that include education, social communication, entertainment, and artistic performance. Highlighting topics such as evolinguistics, human-robot interaction, and neuroinformatics, this book is ideally designed for social network developers, cognitive scientists, education science experts, evolutionary linguists, researchers, and academicians.

Artificial intelligence has become an invaluable tool in modern society and can be utilized across fields such as healthcare, travel, education, and construction. There are numerous benefits for companies, industries, and governments when adopting this technology into their daily operations as it continues to evolve to support the needs of society. Further study on the challenges and strategies of implementation is required in order to ensure the technology is employed to its full potential. Artificial Intelligence for Societal Development and Global Well-Being considers the various uses, best practices, and success factors of artificial intelligence across fields and industries and discusses critical ways in which the technology must be developed further for the good of society. Covering a range of topics such as smart devices, artificial neural networks, and natural intelligence, this reference work is crucial for scientists, librarians, business owners, government officials, entrepreneurs, scholars, researchers, practitioners, instructors, and students.

Complex Systems and Clouds: A Self-Organization and Self-Management Perspective provides insights into the intricate world of self-organizing systems. Large scale distributed computer systems have evolved into very complex systems and are at the point where they need to borrow self-adapting organizing concepts from nature. The book explores complexity in big distributed systems and in the natural processes in physics and chemistry, building a platform for understanding how self-organization in big distributed systems can be achieved. It goes beyond the theoretical description of self-organization to present principles for designing self-organizing systems, and concludes by showing the need for a paradigm shift in the development of large-scale systems from strictly deterministic to non-deterministic and adaptive.

4 zettabytes (4 billion terabytes) of data generated in 2013, 44 zettabytes predicted for 2020 and 185 zettabytes for 2025. These figures are staggering and perfectly illustrate this new era of data deluge. Data has become a major economic and social challenge. The speed of processing of these data is the weakest link in a computer system: the storage system. It is therefore crucial to optimize this operation. During the last decade, storage systems have experienced a major revolution: the advent of flash memory. Flash Memory Integration: Performance and Energy Issues contributes to a better understanding of these revolutions. The authors offer us an insight into the integration of flash memory in computer systems, their behavior in performance and in power consumption compared to traditional storage systems. The book also presents, in their entirety, various methods for measuring the performance and energy consumption of storage systems for embedded as well as desktop/server computer systems. We are invited on a journey to the memories of the future.

This book provides a friendly, practical introduction to open source development options for programmers who build applications to run on IBM i computers. The book will help developers get started using open source, giving plenty of specific examples. The author dispenses guidance to help IBM i developers get into open source in a strategic way--for example, helping them to assess and evaluate the tools and platforms based on criteria such as their business needs, capabilities and flexibility of the open source technologies, and career development considerations. Readers will take away a clear understanding of open source on IBM i platforms and tools, how they fit in with IBM i app development, and the next steps they must take in order to start developing with open source technologies.

Due to the continuous technology advancements and customer demands, software systems are getting larger and more complex ever-increasingly. So, software systems may not necessarily be developed within the limited budget and delivered at the expected time. Quality is also another important issue that needs to be addressed in software development. Indeed, failing to meet the expected level of quality may lead to catastrophic consequences, especially for safety-critical systems (e.g., railway systems, airplanes, etc.). To manage the development of large and complex software systems, software engineering has been introduced, which aims at applying the principles of engineering to software development. By doing so, software systems can be developed within budget and delivered at the expected time with the expected level of quality. This Book is a project-oriented software engineering book, in which readers are expected to be involved in a software project. By doing so, it is intended to give readers the chance of having practical experience on the taught material and their programming skills. Moreover, readers can also enhance their skills on working as a team to accomplish a project in a way that meets the requirements of the customers. The aim of this book is to introduce the discipline of Software Engineering, focusing on the knowledge and technology required and how they can be applied in developing software systems in terms of their requirements, analysis, and design. It also aims at introducing the Unified Modeling Language (UML) to let readers have practical experience in specifying software requirements, analysis, and design.

Making Sense of Microsoft Excel provides students with the knowledge, tools, and skillsets they need to fully understand the vast capabilities of Microsoft Excel, learn how the program functions, and apply their newfound knowledge to use the program effectively. The book begins by defining a spreadsheet, explaining the types of information that are input into one, and the maximum capacity of spreadsheets. Over the course of eight chapters, students learn how to create a spreadsheet, make a graph of the data from the sheet, use a spreadsheet to find stats about given numbers, use the monthly payment and present value functions, name cells, and create borders. Additional chapters address cell indentation, protecting spreadsheets, managing lists, creating templates, using pivot tables, using Visual Basic Programming within a spreadsheet, and more. For the second edition, images throughout the text have been replaced and updated to reflect the current appearance of Microsoft programs and interfaces. Since Microsoft programs are now a subscription-based service, the interface of the program may continue to change; however, the instructions in this book are up-to-date, even if coloration and design elements differ slightly. This highly valuable and comprehensive introduction to Microsoft Excel empowers students to use the program confidently and effectively. Making Sense of Microsoft Excel is well suited for courses in business, statistics, economics, finance, or any other course that introduces the use of Microsoft Excel.

Change Detection and Image Time Series Analysis 1 presents a wide range of unsupervised methods for temporal evolution analysis through the use of image time series associated with optical and/or synthetic aperture radar acquisition modalities. Chapter 1 introduces two unsupervised approaches to multiple-change detection in bi-temporal multivariate images, with Chapters 2 and 3 addressing change detection in image time series in the context of the statistical analysis of covariance matrices. Chapter 4 focuses on wavelets and convolutional-neural filters for feature extraction and entropy-based anomaly detection, and Chapter 5 deals with a number of metrics such as cross correlation ratios and the Hausdorff distance for variational analysis of the state of snow. Chapter 6 presents a fractional dynamic stochastic field model for spatio temporal forecasting and for monitoring fast-moving meteorological events such as cyclones. Chapter 7 proposes an analysis based on characteristic points for texture modeling, in the context of graph theory, and Chapter 8 focuses on detecting new land cover types by classification-based change detection or feature/pixel based change detection. Chapter 9 focuses on the modeling of classes in the difference image and derives a multiclass model for this difference image in the context of change vector analysis.

Increased use of artificial intelligence (AI) is being deployed in many hospitals and healthcare settings to help improve health care service delivery. Machine learning (ML) and deep learning (DL) tools can help guide physicians with tasks such as diagnosis and detection of diseases and assisting with medical decision making. This edited book outlines novel applications of AI in e-healthcare. It includes various real-time/offline applications and case studies in the field of e-Healthcare, such as image recognition tools for assisting with tuberculosis diagnosis from x-ray data, ML tools for cancer disease prediction, and visualisation techniques for predicting the outbreak and spread of Covid-19. Heterogenous recurrent convolution neural networks for risk prediction in electronic healthcare record datasets are also reviewed. Suitable for an audience of computer scientists and healthcare engineers, the main objective of this book is to demonstrate effective use of AI in healthcare by describing and promoting innovative case studies and finding the scope for improvement across healthcare services.

The second in the Women Securing the Future with TIPPSS series, this book provides insight and expert advice from seventeen women leaders in technology, healthcare and policy to address the challenges of Trust, Identity, Privacy, Protection, Safety and Security (TIPPSS) for connected healthcare, and the growing Internet of Medical Things (IoMT) ecosystem. The ten chapters in this book delve into trust, security and privacy risks in connected healthcare for patients, medical devices, personal and clinical data, healthcare providers and institutions, and provide practical approaches to manage and protect the data, devices, and humans. Cybersecurity, technology and legal experts discuss risks, from data and device hacks to ransomware, and propose approaches to address the challenges including new frameworks for architecting and evaluating medical device and connected hospital cybersecurity. We all need to be aware of the TIPPSS challenges in connected healthcare, and we call upon engineers, device manufacturers, system developers and healthcare providers to ensure trust and manage the risk. Featuring contributions from prominent female experts and role models in technology, cybersecurity, engineering, computer science, data science, business, healthcare, accessibility, research, law, privacy and policy, this book sets the stage to improve security and safety in our increasingly connected world.

Translation and communication between cultures can sometimes be a difficult process. Image-based assessments can offer a way for large populations to be tested on different subjects without having to create multiple testing programs. Cross-Cultural Analysis of Image-Based Assessments: Emerging Research and Opportunities is an innovative resource that offers insight into the application of visual assessments across a global and intercultural context. Highlighting applicable topics which include visual literacy, psychological assessments, assessment development, and equivalency measurements, this publication is ideal for psychologists, therapists, and researchers who would like to stay current on the most efficient way to test multi-cultural populations in various fields of knowledge.

Example-Based Super Resolution provides a thorough introduction and overview of example-based super resolution, covering the most successful algorithmic approaches and theories behind them with implementation insights. It also describes current challenges and explores future trends. Readers of this book will be able to understand the latest natural image patch statistical models and the performance limits of example-based super resolution algorithms, select the best state-of-the-art algorithmic alternative and tune it for specific use cases, and quickly put into practice implementations of the latest and most successful example-based super-resolution methods.

Advances in Computers, the latest volume in the series published since 1960, presents detailed coverage of innovations in computer hardware, software, theory, design, and applications. In addition, it provides contributors with a medium in which they can explore their subjects in greater depth and breadth than journal articles usually allow. As a result, many articles have become standard references that continue to be of significant, lasting value in this rapidly expanding field.

It is known that trust is of the utmost importance in human interactions, and blockchain technology establishes a new type of foundation for financial and political confidence. This new kind of trust is based on cryptographic techniques and distributed in digital networks. In an uncertain world where it is difficult to tell what is real or fake, decentralized organizational networks may prove to be particularly competitive given that this new ""distributed trust"" endows them with an unusual functional autonomy, namely guaranteeing the authenticity, confidentiality, and integrity of the processed data. Besides the direct sharing of information enabled by blockchain, transactions can now also take place with newfound trust and ways to safely manage personal data. It is important to look at these implications, particularly in sectors such as business and healthcare. Political and Economic Implications of Blockchain Technology in Business and Healthcare provides relevant theoretical frameworks on the political and economic impact of blockchain technology, which is thought to be able to redesign human interactions concerning transactions. Specifically, it will give ideas, concepts, and instruments considered relevant to advance the knowledge about ""cryptoeconomics"" and decentralized governance. The chapters will also provide several insights on business applications of this digital innovation, particularly in the healthcare sector, and will explore the ethical impact of the new ""distributed trust"" paradigm resulting from the surge of such a disruptive technology. This book is essential for students and researchers in social and life sciences, professionals and policymakers working in the fields of public and business administration, healthcare workers and researchers, academicians, and students interested in blockchain technology and the political and economic impacts in the industry.

Emerging technologies continue to affect a variety of industries, making processes more effective and efficient. However, they also impact society by promoting opportunities to encourage social change and socioeconomic advancement. Blockchain is one that is already influencing third world countries and disrupting the globe. Blockchain Technology for Global Social Change is an essential research publication that provides insight into advancements being made in blockchain and some potential applications of the technology that can improve the lives of individuals in emerging markets. This publication covers a range of topics such as digital government, health systems, and urbanization and is ideal for policymakers, academicians, researchers, sociologists, government officials, economists, and financial experts seeking current and relevant research on evolving blockchain technologies.

Based on current literature and cutting-edge advances in the machine learning field, there are four algorithms whose usage in new application domains must be explored: neural networks, rule induction algorithms, tree-based algorithms, and density-based algorithms. A number of machine learning related algorithms have been derived from these four algorithms. Consequently, they represent excellent underlying methods for extracting hidden knowledge from unstructured data, as essential data mining tasks. Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms presents widely used data-mining algorithms and explains their advantages and disadvantages, their mathematical treatment, applications, energy efficient implementations, and more. It presents research of energy efficient accelerators for machine learning algorithms. Covering topics such as control-flow implementation, approximate computing, and decision tree algorithms, this book is an essential resource for computer scientists, engineers, students and educators of higher education, researchers, and academicians.

Information systems development underwent many changes as systems transitioned onto web-based forums. Complemented by advancements in security and technology, internet-based systems have become an information mainstay. The Handbook of Research on Contemporary Perspectives on Web-Based Systems is a critical scholarly resource that examines relevant theoretical frameworks, current practice guidelines, industry standards, and the latest empirical research findings in web-based systems. Featuring coverage on a wide range of topics such as data integration, mobile applications, and semantic web, this publication is geared toward computer engineers, IT specialists, software designers, professionals, researchers, and upper-level students seeking current and relevant research on the prevalence of these systems and advancements made to them.

Computing and Visualization for Intravascular Imaging and Computer-Assisted Stenting presents imaging, treatment, and computed assisted technological techniques for diagnostic and intraoperative vascular imaging and stenting. These techniques offer increasingly useful information on vascular anatomy and function, and are poised to have a dramatic impact on the diagnosis, analysis, modeling, and treatment of vascular diseases. After setting out the technical and clinical challenges of vascular imaging and stenting, the book gives a concise overview of the basics before presenting state-of-the-art methods for solving these challenges. Readers will learn about the main challenges in endovascular procedures, along with new applications of intravascular imaging and the latest advances in computer assisted stenting.