This textbook bridges the gap between introductory and advanced numerical methods for engineering students. The book initially introduces readers to numerical methods before progressing to linear and nonlinear equations. Next, the book covers the topics of interpolation, curve fitting and approximation, integration, differentiation and differential equations. The book concludes with a chapter on advanced mathematical analysis which explains methods for finite difference, method of moments and finite elements. The book introduces readers to key concepts in engineering such as error analysis, algorithms, applied mathematics with the goal of giving an understanding of how to solve engineering problems using computational methods. Each of the featured topics is explained with sufficient detail while retaining the usual introductory nuance. This blend of beginner-friendly and applied information, along with reference listings makes the textbook useful to students of undergraduate and introductory graduate courses in mathematics and engineering.

A smart city uses technology to provide services and solve problems to improve urban policy efficiency, reduce waste, improve quality of life, and maximize social inclusion. By 2050, 66% of the world's population is expected to be urban, which is a key driver of a global trend toward the creation of smart cities. This trend creates many opportunities for urban planning committees to learn how to design, modernize, and operate smart cities intelligently and effectively. Facets of a Smart City: Computational and Experimental Techniques for Sustainable Urban Development is a collection of topics that are relevant to the design of a smart city. This book aims to complement technical journal articles that require advanced knowledge of the subject of smart cities and applications for readers. It aims to bridge knowledge gaps in sustainable urban design by providing background information via case studies to facilitate students, recent graduates and new practitioners in urban design and planning. Key Features: - This book features 9 chapters that cover 6 major domains, which include (i) information modelling, (ii) internet of things, (iii) intelligent transportation systems, (iv) water supply, (v) waste management and (vi) sustainable environment - Computational techniques are included in the book. These include artificial neural networks, stochastic models, particle swarm optimization, machine learning, and adaptive neuro-fuzzy Inference systems. - Goals of case studies presented in this book use computational techniques to offer readers examples of supervised, unsupervised and reinforcement learning strategies in the context of smart city applications - References are provided for further reading

Soft robotics is a subfield of robotics that encompasses the design and fabrication of robots with soft and compliant materials. Soft robots represent components like human prosthetics or biomimicking systems. Soft robotics relies on technically astute designs based on the correct choice of materials to enable a level of dexterity not possible with rigid components alone. The basic prime movers (actuators) and perception (sensors) require control systems capable of accommodating imprecise feedback data and often unpredictable reaction times. Mobility in such robots is more akin to entomological or marine systems than conventional guided vehicles. This reference is a guide to materials and systems used in soft robotics. If features 6 chapters contributed by robotics experts that review fundamental and applied topics that are important for understanding the requirements of soft robotics design projects and the physics of the polymers involved. Chapters are organized for easy reading and include references. The topics include: - Aspects of materials processing and engineering for the development of soft robotic devices - A review on biological gripping principles and their application to robotics - Information about self-sensing electroadhesive polymer grippers with magnetically controllable surface geometry - Theoretical and experimental investigations of magnetic hybrid materials - Modeling and dynamic analysis of a novel rotary soft robotic arm by transfer matrix method - Design and control of a portable continuum robot for pipe inspection assisted by a rigid manipulator This book is a suitable reference for scholars and engineers who are seeking knowledge about materials and design principles in soft robotics with its practical applications.

This reference presents a collection of studies which highlight new developments in improving manufacturing processes and performance. The book includes 11 chapters which cover unique topics of interest to production engineers. These topics include the production of advanced composite materials and alloys to the use of sensors to evaluate production processes, product testing and evaluation (in production and storage environments), and the development and testing of an unmanned aerial vehicle. Chapters have been contributed by several scholars, who give a unique perspective on specific aspects of manufacturing and industrial production. The book also covers recent technologies such as additive manufacturing. Each chapter presents the study in an experimental manner highlighting the theory, methods, and results, where applicable. References for further reading are also provided. This book is intended to provide researchers and engineers with new data and cases for industrial manufacturing processes which may be applied in different industrial sectors.

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.

Additive manufacturing or 3D printing is the construction of an object using CAD models. The technology for additive manufacturing s gaining traction in recent times due to its accessibility for both personal and industrial use, as well as its usefulness in quick prototyping (either of a whole object or its components) and meeting the needs of small commercial workloads. Advances in Additive Manufacturing Processes informs readers about the breadth of 3D printing processes. Chapters cover the basic knowledge of additive techniques and their industrial applications with relevant examples. The improvements in each method and their recent technical achievements with practical experimental data are highlighted. The book presents eight types of 3D printing processes, covering a diverse range of technologies which represent the industry. The contents also cover selected topics of relevance to additive manufacturing which include the formation of defects and factors that affect the mechanical properties of the additively manufactured components. Chapters also provide recent guidelines for adapting additive manufacturing processes to increase productivity and reduce manufacturing cost. Advances in Additive Manufacturing Processes is a handy reference for scholars and professionals involved in manufacturing industries and process engineering as well as hobbyists who are interested in the current state-of-the-art in 3D printing.

Lean Management Solutions for Contemporary Manufacturing Operations: Applications in the automotive industry covers recent techniques aimed at improving manufacturing activities in automotive factories in the time of the fourth industrial revolution. The book informs the reader about some improvements in hard skills (such as technical concepts, new tools, processes, and applied designs), as well as soft skills (strategic planning and the psychology of motivating human resources in manufacturing setups). The book also presents insight for managers who are working with a niche of employees with disabilities with respect to the automotive industry. Topics in the book include: Application of Graph Theory in Workplace Design Applied Design Disability and the 4th Industrial Revolution People Development, Motivation & Results Low Cost Logistics Solutions Agile Methodologies in Manufacturing Projects This book is a concise, informative reference which updates the reader on recent strategies to maximize productivity in the auto manufacturing sector.

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.