Human-Computer Interaction and Beyond: Advances Towards Smart and Interconnected Environments is a 2-part book set which presents discoveries, innovative ideas, concepts, practical solutions, and novel applications of Human-Computer Interaction (HCI) and related disciplines such as artificial intelligence, machine learning, data mining, computer vision, and natural language processing. The book provides readers with information about HCI trends which are shaping the future of smart, interconnected urban and industrial environments. This is the second of the two volumes of the edited books. The chapters of this volume cover topics like ERP usability in educational settings, the role of AI in enhancing HCI functionality, usability of local mobile healthcare apps, analyzing the usage of social media apps and a review of HCI systems for disaster management and systems for tracking traffic safety violations. Contributions are authored by experts and scientists in the field of HCI and its interrelated disciplines from 9 different countries – Albania, China, India, Indonesia, Nigeria, Pakistan, Spain, the United Kingdom, and the United States. Human-Computer Interaction and Beyond: Advances Towards Smart and Interconnected Environments is an informative reference for scientists, researchers, and developers in both academia and industry who wish to learn, design, implement, and apply these emerging technologies in HCI in different sectors, with the goal of realizing futuristic technology-driven living and functional smart cities and environments.

Machine Learning and Its Application: A Quick Guide for Beginners aims to cover most of the core topics required for study in machine learning curricula included in university and college courses. The textbook introduces readers to central concepts in machine learning and artificial intelligence, which include the types of machine learning algorithms and the statistical knowledge required for devising relevant computer algorithms. The book also covers advanced topics such as deep learning and feature engineering. <p> Key features: <p> - 8 organized chapters on core concepts of machine learning for learners <p> - Accessible text for beginners unfamiliar with complex mathematical concepts <p> - Introductory topics are included, including supervised learning, unsupervised learning, reinforcement learning and predictive statistics <p> - Advanced topics such as deep learning and feature engineering provide additional information <p> - Introduces readers to python programming with examples of code for understanding and practice <p> - Includes a summary of the text and a dedicated section for references <p> Machine Learning and Its Application: A Quick Guide for Beginners is an essential book for students and learners who want to understand the basics of machine learning and equip themselves with the knowledge to write algorithms for intelligent data processing applications.

New technologies and computing methodologies are now used to address the existing issues of urban traffic systems. The development of computational intelligence methods such as machine learning and deep learning, enables engineers to find innovative solutions to guide traffic in order to reduce transportation and mobility problems in urban areas. &lt;p&gt; This volume, Computational Intelligence for Sustainable Transportation and Mobility, presents several computing models for intelligent transportation systems, which may hold the key to achieving sustainable development goals by optimizing traffic flow and minimizing associated risks. The book begins with the basic computational Intelligence techniques for traffic systems and explains its applications in vehicular traffic prediction, model optimization, behavior analysis, traffic density estimation, and more. The main objectives of this book are to present novel techniques developed, new technologies and computational intelligence for sustainable mobility and transportation solutions, as well as giving an understanding of some Industry 4.0 trends. &lt;p&gt; Readers will learn how to apply computational intelligence techniques such as multiagent systems (MAS), whale optimization, artificial Intelligence (AI), deep neural networks (DNNs) so that they can to develop algorithms, models, and approaches for sustainable transportation operations. &lt;p&gt; Key Features: &lt;p&gt; - Provides an overview of machine learning models and their optimization for intelligent transportation systems in urban areas &lt;p&gt; - Covers classification of traffic behavior &lt;p&gt; - Demonstrates the application of artificial immune system algorithms for traffic prediction &lt;p&gt; - Covers traffic density estimation using deep learning models &lt;p&gt; - Covers Fog and edge computing for intelligent transportation systems &lt;p&gt; - Gives an IoT and Industry 4.0 perspective about intelligent transportation systems to readers &lt;p&gt; - Presents a current perspective on an urban hyperloop system for India &lt;p&gt; This volume is essential reading for scholars and professionals involved in courses and training programs in the field of transportation, computer science, data science and applied machine learning.

This book provides an ideal foundation for readers to understand the application of artificial intelligence (AI) and machine learning (ML) techniques to expert systems in the healthcare sector. It starts with an introduction to the topic and presents chapters which progressively explain decision-making theory that helps solve problems which have multiple criteria that can affect the outcome of a decision. Key aspects of the subject such as machine learning in healthcare, prediction techniques, mathematical models and classification of healthcare problems are included along with chapters which delve in to advanced topics on data science (deep-learning, artificial neural networks, etc.) and practical examples (influenza epidemiology and retinoblastoma treatment analysis). Key Features: - Introduces readers to the basics of AI and ML in expert systems for healthcare - Focuses on a problem solving approach to the topic - Provides information on relevant decision-making theory and data science used in the healthcare industry - Includes practical applications of AI and ML for advanced readers - Includes bibliographic references for further reading The reference is an accessible source of knowledge on multi-criteria decision-support systems in healthcare for medical consultants, healthcare policy makers, researchers in the field of medical biotechnology, oncology and pharmaceutical research and development.

A variety of computing techniques have been developed in recent times in combination with emerging technologies. Such techniques, coupled with an increase in computing power, has given credence to an information based paradigm in many fields (also termed as informatics). Informatics computing has evolved into complex structures of heterogeneous methods involving multiple data processing applications. Research on new technologies also brings new tools to use along with continuous improvements in existing tools. This reference presents contributions that cover emerging computing techniques and their implementation in computer science, informatics and engineering, as well as other important topics that are often discussed in the modern computing environment. Chapters in this book are contributed by researchers, academicians and industry experts and inform readers about current computer technologies and applications. The topics covered in the book include, online privacy, internet gaming disorder, epidemiological modelling (including COVID-19), computer security and malware detection, document sentiment analysis, and project management. This book is an interesting update on new trends in computing techniques and applications for readers interested in the latest developments in computer science.

How to Design Optimization Algorithms by Applying Natural Behavioral Patterns is a guide book that introduces readers to optimization algorithms based on natural language processing. Readers will learn about the basic concept of optimization, optimization algorithm fundamentals and the methods employed to formulate natural ideas and behaviors into algorithms. Readers will learn how to create their own algorithm from the information provided in the text. The book is a simple reference to students and programming enthusiasts who are interested in learning about optimization and the process of designing algorithms designed to mimic natural phenomena.

Human-Computer Interaction and Beyond: Advances Towards Smart and Interconnected Environments is a 2-part book set which presents discoveries, innovative ideas, concepts, practical solutions, and novel applications of Human-Computer Interaction (HCI) and related disciplines such as artificial intelligence, machine learning, data mining, computer vision, and natural language processing. The book provides readers with information about HCI trends which are shaping the future of smart, interconnected urban and industrial environments. Contributions are authored by experts and scientists in the field of HCI and its interrelated disciplines from 8 different countries – Chile, China, Croatia, India, Iran, Malaysia, Peru, and South Korea. The chapters of this volume present novel and state of the art research works conducted at the intersection of HCI aimed at developing trust, increasing user acceptance, augmenting user performance, and fostering human-technology partnerships. Chapters cover usability testing in digital healthcare systems, user experience testing of handicapped children and assistive technologies for visually impaired users and a gamified user experience design for learning. The volume also presents a review of twitter usability testing among Indian users, along with specific cases of arthritis diagnostic systems, meteorological draught analysis and the role of EUPS in improving GUI design to improve the user experience. Human-Computer Interaction and Beyond: Advances Towards Smart and Interconnected Environments is an informative reference for scientists, researchers, and developers in both academia and industry who wish to learn, design, implement, and apply these emerging technologies in HCI in different sectors, with the goal of realizing futuristic technology-driven living and functional smart cities and environments.

This reference provides the reader with focused information about microstrip antenna design and applications. Readers are first introduced to the basic design of microstrip antennas. Subsequent chapters explain how microstrip antennas are suitable for practical applications. These chapters cover topics such as fractal and defected ground structure antennas, microstrip antenna evaluation, and the use of microstrip antennas in mobile communications and IoT applications. Scholars, researchers, and industrial professionals involved in the fields of electronics and electrical engineering as well as instrumentation will benefit from the information given in this book.

This handbook is a concise yet complete guide to fundamental engineering requirements and quality characteristics that users, developers, and marketers of mobile applications should be aware of. It provides detailed definitions and descriptions of eight key software application features that are integral to the overall design and user experience goals, and which may often overlap with certain functionalities. The book explains the essential aspects of these features clearly to novice developers. Readers will also learn about how to optimize the listed features to tailor their applications to the needs of their users. &lt;/P&gt; Key Features: &lt;/P&gt; - Presents detailed information about eight different features which guide mobile application development: capability, reliability, usability, charisma, security, performance, mobility and compatibility &lt;/P&gt; - Reader-friendly, structured layout of each chapter including relevant illustrations and clear language, designed for quick learning &lt;/P&gt; - Focus on both software function and user perception of applications on mobile devices &lt;/P&gt; - Includes a handy appendix with information about mobile learning projects and related work packages &lt;/P&gt; Handbook of Mobile Application Development: A Guide to Selecting the Right Engineering and Quality Features is the ideal learning tool for novice software developers, computer science students, IT enthusiasts and marketers who want to design or develop mobile apps for an optimal user experience.

The importance of Artificial Intelligence cannot be over-emphasised in current times, where automation is already an integral part of industrial and business processes. </p> A First Course in Artificial Intelligence is a comprehensive textbook for beginners which covers all the fundamentals of Artificial Intelligence. Seven chapters (divided into thirty-three units) introduce the student to key concepts of the discipline in simple language, including expert system, natural language processing, machine learning, machine learning applications, sensory perceptions (computer vision, tactile perception) and robotics. Each chapter provides information in separate units about relevant history, applications, algorithm and programming with relevant case studies and examples. The simplified approach to the subject enables beginners in computer science who have a basic knowledge of Java programming to easily understand the contents. The text also introduces Python programming language basics, with demonstrations of natural language processing. It also introduces readers to the Waikato Environment for Knowledge Analysis (WEKA), as a tool for machine learning. </p> The book is suitable for students and teachers involved in introductory courses in undergraduate and diploma level courses which have appropriate modules on artificial intelligence.