Global inequality has been a burning issue for years now. As the economies progress, it is expected that the benefits of growth will percolate to the lower sections of society. However, this percolation takes place in a discriminating manner. Inequality can be observed in terms of health, income, education, wealth, gender, availability of opportunities, and other socio-economic parameters. The governing authorities and international agencies have been taking various corrective measures to reduce the widening levels of inequality. However, certain external factors like the pandemic can wash away the efforts taken and deteriorate the progress made on the inequality levels in economies. Emerging Trends and Insights on Economic Inequality in the Wake of Global Crises discusses the impact of global disasters and crises on economic inequality. It provides an overview of the evolution of global inequality over the years, increasing different forms of inequalities amidst crises, the corrective measures taken by the national and international agencies, and the way forward for economies with worsening inequalities. Covering topics such as crisis management, digital agriculture, and economic welfare, this premier reference source is an essential resource for economists, business leaders and executives, government officials, students and educators of higher education, sociologists, researchers, and academicians.

Decision-making is a frequent problem in today's financial, business, and industrial world. Thus, fuzzy expert systems are increasingly being used to solve decision-making problems by attempting to solve a part or whole of a practical problem. These expert systems have proven that they can solve problems in various domains where human expertise is required, including the field of agriculture. Fuzzy Expert Systems and Applications in Agricultural Diagnosis is a crucial source that examines the use of fuzzy expert systems for prediction and problem solving in the agricultural industry. Featuring research on topics such as nutrition management, sustainable agriculture, and defuzzification, this book is ideally designed for farmers, researchers, scientists, academics, students, policymakers, and development practitioners seeking the latest research in technological tools that support crop disease diagnosis.

Processing information and analyzing data efficiently and effectively is crucial for any company that wishes to stay competitive in its respective market. Nonlinear data presents new challenges to organizations, however, due to its complexity and unpredictability. The only technology that can properly handle this form of data is artificial neural networks. These modeling systems present a high level of benefits in analyzing complex data in a proficient manner, yet considerable research on the specific applications of these intelligent components is significantly deficient. Applications of Artificial Neural Networks for Nonlinear Data is a collection of innovative research on the contemporary nature of artificial neural networks and their specific implementations within data analysis. While highlighting topics including propagation functions, optimization techniques, and learning methodologies, this book is ideally designed for researchers, statisticians, academicians, developers, scientists, practitioners, students, and educators seeking current research on the use of artificial neural networks in diagnosing and solving nonparametric problems.

Mobile computing facilitates data transmission without needing to be connected to a fixed physical link. Mobile voice communication is widely established throughout the world and the number of subscribers to various cellular networks has increased considerably over the last few years. An extension of this technology is the ability to send and receive data across these cellular networks. Mobile data communication has become a very important and rapidly evolving technology as it allows users to transmit data from remote locations to other remote or fixed locations. This proves to be the solution to the biggest problem for business people on the move. Mobile Computing Techniques in Emerging Markets: Systems, Applications and Services provides the latest research and best practices in the field of mobile computing. Theoretical and pragmatic viewpoints on mobile computing offer guidance for professionals using this book to inform their practices. A solid foundation on mobile computing and an expansive vision of its possibilities combine to promote understanding and the successful implementation of mobile computing techniques in emerging markets.

Knowledge Discovery Practices and Emerging Applications of Data Mining: Trends and New Domains introduces the reader to recent research activities in the field of data mining. This book covers association mining, classification, mobile marketing, opinion mining, microarray data mining, internet mining and applications of data mining on biological data, telecommunication and distributed databases, among others, while promoting understanding and implementation of data mining techniques in emerging domains.

This book introduces readers to numerous multiplicative inverse functional equations and their stability results in various spaces. This type of functional equation can be of use in solving many physical problems and also has significant relevance in various scientific fields of research and study. In particular, multiplicative inverse functional equations have applications in electric circuit theory, physics, and relations connecting the harmonic mean and arithmetic mean of several values. Providing a wealth of essential insights and new concepts in the field of functional equations, the book is chiefly intended for researchers, graduate schools, graduate students, and educators, and can also used for seminars in analysis covering topics of functional equations.

Digital classrooms have become a common addition to curriculums in higher education; however, such learning systems are only successful if students are properly motivated to learn. Optimizing Student Engagement in Online Learning Environments is a critical scholarly resource that examines the importance of motivation in digital classrooms and outlines methods to reengage learners. Featuring coverage on a broad range of topics such as motivational strategies, learning assessment, and student involvement, this book is geared toward academicians, researchers, and students seeking current research on the importance of maintaining ambition among learners in digital classrooms.

The development of fuzzy expert systems has provided new opportunities for problem solving amidst uncertainties. The medical field, in particular, has benefitted tremendously from advancing fuzzy system technologies. Fuzzy Expert Systems for Disease Diagnosis highlights the latest research and developments in fuzzy rule-based methods used in the detection of medical complications and illness. Offering emerging solutions and practical applications, this timely publication is designed for use by researchers, academicians, and students, as well as practitioners in the medical field.

Student assessment in online learning is submitted remotely without any face-to-face interaction, and therefore, student authentication is widely seen as one of the major challenges in online examination. Authentication is the process of determining whether someone or something is, in fact, who or what it is declared to be. As the dependence upon computers and computer networks grows, especially within education, the need for authentication has increased. Biometric Authentication in Online Learning Environments provides innovative insights into biometrics as a strategy to mitigate risk and provide authentication, while introducing a framework that provides security to improve e-learning and on-line examination by utilizing biometric-based authentication techniques. This book examines e-learning, security, threats in online exams, security considerations, and biometric technologies, and is designed for IT professionals, higher education administrators, professors, researchers, business professionals, academicians, and libraries seeking topics centered on biometrics as an authentication strategy within educational environments.

Electrodeionization: Fundamentals, Methods and Applications explains the latest developments in research on ion exchange membranes, wastewater zero discharge based on ion exchange membranes, membrane capacitive deionization, membrane free and resin wafer electrodeionization cells. Electrodeionization is a fully advanced ion exchange method that combines ion exchange, electrodialysis, and elusion procedures for metal particle removal from wastewater. Gaining popularity due to the lack of chemicals required for resin regeneration and the production of high purity water, this cost-effective method efficiently assists in ion removal and recovery. The technology is suitable for a wide range of applications including desalination, water and wastewater treatment, extraction of high-value products, concentrating and purifying operations, and energy savings, and as such will be of interest to researchers and students working on these areas as well as those in chemicals manufacture, energy generation and storage.

This volume provides readers with a comprehensive review of various gene silencing methodologies and its applications. It provides a historical overview of gene silencing mechanisms in plants, vectors, and strategies available for plant gene silencing, practical applications of gene silencing, bioinformatics tools, and other resources. In addition to these review chapters, this book includes methodology for virus-induced gene silencing (VIGS) in various different plant species, understanding plant stress responses using VIGS, miRNA identification, DNA interference, host-induced gene silencing, use of artificial miRNAs for gene silencing, high throughput RNAi, and more. Written in the highly successful Methods of Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and key tips on troubleshooting and avoiding known pitfalls. Thorough and practical, Plant Gene Silencing: Methods and Protocols seeks to aid scientists to further understand functional relevance of target genes using gene silencing methods and use these technologies in commercial plant varieties.

Computer application systems are helpful for society to turn into a digital era of computing and interaction made more accessible and consistent. Further study in this field is required in order to ensure the applications are utilized appropriately. Perspectives on Social Welfare Applications' Optimization and Enhanced Computer Applications discusses new computer applications and analyzes the existing ones to introduce a subsystem of the current system to make the social interactions towards digital world initiatives. This book provides a platform for scholars, researchers, scientists, and working professionals to exchange and share their computer application creation experiences and research results about all aspects of application software system development within computer science with emerging and advanced technologies. Covering topics such as applied computing, data science, and mobile computing, this premier reference source is ideal for industry professionals, computer scientists, academicians, engineers, researchers, scholars, practitioners, librarians, instructors, and students.

Web usage mining is defined as the application of data mining technologies to online usage patterns as a way to better understand and serve the needs of web-based applications. Because the internet has become a central component in information sharing and commerce, having the ability to analyze user behavior on the web has become a critical component to a variety of industries. Web Usage Mining Techniques and Applications Across Industries addresses the systems and methodologies that enable organizations to predict web user behavior as a way to support website design and personalization of web-based services and commerce. Featuring perspectives from a variety of sectors, this publication is designed for use by IT specialists, business professionals, researchers, and graduate-level students interested in learning more about the latest concepts related to web-based information retrieval and mining.

Machine learning allows for non-conventional and productive answers for issues within various fields, including problems related to visually perceptive computers. Applying these strategies and algorithms to the area of computer vision allows for higher achievement in tasks such as spatial recognition, big data collection, and image processing. There is a need for research that seeks to understand the development and efficiency of current methods that enable machines to see. Challenges and Applications for Implementing Machine Learning in Computer Vision is a collection of innovative research that combines theory and practice on adopting the latest deep learning advancements for machines capable of visual processing. Highlighting a wide range of topics such as video segmentation, object recognition, and 3D modelling, this publication is ideally designed for computer scientists, medical professionals, computer engineers, information technology practitioners, industry experts, scholars, researchers, and students seeking current research on the utilization of evolving computer vision techniques.

This second edition provides a comprehensive review of various gene silencing methodologies and applications. Chapters detail a historical overview of gene silencing mechanisms in plants, vectors, and strategies available for plant gene silencing, practical applications of gene silencing, bioinformatics tools, and other resources. In addition to these review chapters, this book includes methodology for virus-induced gene silencing (VIGS), understanding plant stress responses using VIGS, miRNA identification, DNA interference, host-induced gene silencing, artificial miRNAs for gene silencing, and high throughput RNAi. Written in the format of the highly successful Methods in Molecular Biology series, each chapter includes an introduction to the topic, lists necessary materials and reagents, includes tips on troubleshooting and known pitfalls, and step-by-step, readily reproducible protocols. Authoritative and cutting-edge, Plant Gene Silencing: Methods and Protocols, Second Edition aims to further the understanding of functional relevance of target genes using gene silencing methods and technologies in commercial plant varieties.

Modern Treatment Strategies for Marine Pollution provides an overview of assessment tools that identify contaminants in marine water, also discussing the latest technologies for removing these contaminants. Through templated and consistently structured chapters, the author explores the importance of seawater to our marine ecosystems and the devastating effects pollutants are causing. Sections cover the emission of toxic pollutants from industries, wastewater discharge, oil spills from boarding ships, ballast water emission, abnormal growth of algal blooms, and more. Techniques explored include huge diameter pipelines erected for removing floating debris from seawater, which is denoted as a primary idea for cleaning contaminants. The book includes numerous case studies that demonstrate how these tools can be successfully used. It is an essential read for marine ecologists and oceanographers at the graduate level and above, but is also ideal for those looking to incorporate these techniques into their own work.

This book covers the state-of-art image classification methods for discrimination of earth objects from remote sensing satellite data with an emphasis on fuzzy machine learning and deep learning algorithms. Both types of algorithms are described in such details that these can be implemented directly for thematic mapping of multiple-class or specific-class landcover from multispectral optical remote sensing data. These algorithms along with multi-date, multi-sensor remote sensing are capable to monitor specific stage (for e.g., phenology of growing crop) of a particular class also included. With these capabilities fuzzy machine learning algorithms have strong applications in areas like crop insurance, forest fire mapping, stubble burning, post disaster damage mapping etc. It also provides details about the temporal indices database using proposed Class Based Sensor Independent (CBSI) approach supported by practical examples. As well, this book addresses other related algorithms based on distance, kernel based as well as spatial information through Markov Random Field (MRF)/Local convolution methods to handle mixed pixels, non-linearity and noisy pixels. Further, this book covers about techniques for quantiative assessment of soft classified fraction outputs from soft classification and supported by in-house developed tool called sub-pixel multi-spectral image classifier (SMIC). It is aimed at graduate, postgraduate, research scholars and working professionals of different branches such as Geoinformation sciences, Geography, Electrical, Electronics and Computer Sciences etc., working in the fields of earth observation and satellite image processing. Learning algorithms discussed in this book may also be useful in other related fields, for example, in medical imaging. Overall, this book aims to: exclusive focus on using large range of fuzzy classification algorithms for remote sensing images; discuss ANN, CNN, RNN, and hybrid learning classifiers application on remote sensing images; describe sub-pixel multi-spectral image classifier tool (SMIC) to support discussed fuzzy and learning algorithms; explain how to assess soft classified outputs as fraction images using fuzzy error matrix (FERM) and its advance versions with FERM tool, Entropy, Correlation Coefficient, Root Mean Square Error and Receiver Operating Characteristic (ROC) methods and; combines explanation of the algorithms with case studies and practical applications.

This book contains fundamental concepts on discrete mathematical structures in an easy to understand style so that the reader can grasp the contents and explanation easily. The concepts of discrete mathematical structures have application to computer science, engineering and information technology including in coding techniques, switching circuits, pointers and linked allocation, error corrections, as well as in data networking, Chemistry, Biology and many other scientific areas. The book is for undergraduate and graduate levels learners and educators associated with various courses and progammes in Mathematics, Computer Science, Engineering and Information Technology. The book should serve as a text and reference guide to many undergraduate and graduate programmes offered by many institutions including colleges and universities. Readers will find solved examples and end of chapter exercises to enhance reader comprehension. Features Offers comprehensive coverage of basic ideas of Logic, Mathematical Induction, Graph Theory, Algebraic Structures and Lattices and Boolean Algebra Provides end of chapter solved examples and practice problems Delivers materials on valid arguments and rules of inference with illustrations Focuses on algebraic structures to enable the reader to work with discrete structures

This volume covers the topic in functional equations in a broad sense and is written by authors who are in this field for the past 50 years. It contains the basic notions of functional equations, the methods of solving functional equations, the growth of functional equations in the last four decades and an extensive reference list on fundamental research papers that investigate the stability results of different types of functional equations and functional inequalities. This volume starts by taking the reader from the fundamental ideas to higher levels of results that appear in recent research papers. Its step-by-step expositions are easy for the reader to understand and admire the elegant results and findings on the stability of functional equations.

This volume covers the topic in functional equations in a broad sense and is written by authors who are in this field for the past 50 years. It contains the basic notions of functional equations, the methods of solving functional equations, the growth of functional equations in the last four decades and an extensive reference list on fundamental research papers that investigate the stability results of different types of functional equations and functional inequalities. This volume starts by taking the reader from the fundamental ideas to higher levels of results that appear in recent research papers. Its step-by-step expositions are easy for the reader to understand and admire the elegant results and findings on the stability of functional equations.

This book introduces readers to numerous multiplicative inverse functional equations and their stability results in various spaces. This type of functional equation can be of use in solving many physical problems and also has significant relevance in various scientific fields of research and study. In particular, multiplicative inverse functional equations have applications in electric circuit theory, physics, and relations connecting the harmonic mean and arithmetic mean of several values. Providing a wealth of essential insights and new concepts in the field of functional equations, the book is chiefly intended for researchers, graduate schools, graduate students, and educators, and can also used for seminars in analysis covering topics of functional equations.

This book covers the state-of-art image classification methods for discrimination of earth objects from remote sensing satellite data with an emphasis on fuzzy machine learning and deep learning algorithms. Both types of algorithms are described in such details that these can be implemented directly for thematic mapping of multiple-class or specific-class landcover from multispectral optical remote sensing data. These algorithms along with multi-date, multi-sensor remote sensing are capable to monitor specific stage (for e.g., phenology of growing crop) of a particular class also included. With these capabilities fuzzy machine learning algorithms have strong applications in areas like crop insurance, forest fire mapping, stubble burning, post disaster damage mapping etc. It also provides details about the temporal indices database using proposed Class Based Sensor Independent (CBSI) approach supported by practical examples. As well, this book addresses other related algorithms based on distance, kernel based as well as spatial information through Markov Random Field (MRF)/Local convolution methods to handle mixed pixels, non-linearity and noisy pixels. Further, this book covers about techniques for quantiative assessment of soft classified fraction outputs from soft classification and supported by in-house developed tool called sub-pixel multi-spectral image classifier (SMIC). It is aimed at graduate, postgraduate, research scholars and working professionals of different branches such as Geoinformation sciences, Geography, Electrical, Electronics and Computer Sciences etc., working in the fields of earth observation and satellite image processing. Learning algorithms discussed in this book may also be useful in other related fields, for example, in medical imaging. Overall, this book aims to: exclusive focus on using large range of fuzzy classification algorithms for remote sensing images; discuss ANN, CNN, RNN, and hybrid learning classifiers application on remote sensing images; describe sub-pixel multi-spectral image classifier tool (SMIC) to support discussed fuzzy and learning algorithms; explain how to assess soft classified outputs as fraction images using fuzzy error matrix (FERM) and its advance versions with FERM tool, Entropy, Correlation Coefficient, Root Mean Square Error and Receiver Operating Characteristic (ROC) methods and; combines explanation of the algorithms with case studies and practical applications.

This book is a practical guide to solving the everyday problems encountered when building apps for Windows 10 devices, including desktops, laptops, tablets, and phones, using HTML5, CSS3 and JavaScript. Each recipe includes a concise statement of the problem and the approach you should take in order to solve it. A full code solution is also given, along with an in-depth explanation, so you can build on your development knowledge while you work on your application. The majority of recipes can be used with the Universal Windows app template, designed to help you build one consistent user experience across devices. These are supplemented with recipes for adapting your app to different devices, screen sizes and sensor availability. You'll also find out how to deploy and publish your apps in the Windows Store. Learn how to: Make use of the latest Universal Windows app features, alongside customizations for specific platforms and screen sizes. Bring your apps to life with live tiles, notifications, and sharing. Prepare your app to adapt to your users' different cultural and business environments using globalization and localization APIs and best practices. Understand the certification process and publish your app to the Windows Store, with the option to pay once, install anywhere. This book is suitable for anyone developing for Windows and Windows Mobile. Readers should be comfortable working with HTML and JavaScript. No previous experience with Microsoft technologies or languages is needed in order to use this book.

Fixtures are crucial to new manufacturing techniques and largely dictate the level of flexibility a manufacturing system can achieve. Advanced Fixture Design for FMS provides a systematic basis for the selection and design of fixturing systems. It gives a review of the current state of the art of flexible and reconfigurable fixturing systems. Recent developments in design methodology using CAD are analysed in depth. Fixture design is seen as an inseparable part of process planning. The primary objective of a fixture system is to ensure that the part being manufactured can be made consistently within the tolerance specified in the design. A new method of tolerance analysis is used to check the suitability of location surfaces and the sequence of operations and is explained in detail.