Covers all the aspects of a flapping-wing vehicles needed to design one and understand how/why it flies. Explains related engineering practice including fabrication, materials, and manufacturing. Includes CFD analysis of 3D wing profile. Discusses image-based control of group of Ornithopters. Explores indigenous PCB design for achieving altitude and attitude control.

Addresses real-world challenges in using AI Covers the entire AI process in a holistic manner Explains the technical issues in an easy to use manner Provides real-world examples of AI enablement Addresses the challenges of complex enterprises, coalitions and consortia Avoids the hype, with balanced perspective on benefits and drawbacks of AI

It explore issues of diversity and inclusion in relation to artificial intelligence (AI). The author leads a research group on Digitalization and Robotization of Society at NTNU Norwegian University of Science and Technology.

With businesses becoming ever more competitive, marketing strategies need to be more precise and performance oriented. Companies are investing considerably in analytical infrastructure for marketing. This new volume, Marketing Analytics: A Machine Learning Approach, enlightens readers on the application of analytics in marketing and the process of analytics, providing a foundation on the concepts and algorithms of machine learning and statistics. The book simplifies analytics for businesses and explains its uses in different aspects of marketing in a way that even marketers with no prior analytics experience will find it easy to follow, giving them to tools to make better business decisions. This volume gives a comprehensive overview of marketing analytics, incorporating machine learning methods of data analysis that automates analytical model building. The volume covers the important aspects of marketing analytics, including segmentation and targeting analysis, statistics for marketing, marketing metrics, consumer buying behavior, neuromarketing techniques for consumer analytics, new product development, forecasting sales and price, web and social media analytics, and much more. This well-organized and straight-forward volume will be valuable for marketers, managers, decision makers, and research scholars, and faculty in business marketing and information technology and would also be suitable for classroom use.

Object detection is a basic visual identification problem in computer vision that has been explored extensively over the years. Visual object detection seeks to discover objects of specific target classes in a given image with pinpoint accuracy and apply a class label to each object instance. Object recognition strategies based on deep learning have been intensively investigated in recent years as a result of the remarkable success of deep learning-based image categorization. In this book, we go through in detail detector architectures, feature learning, proposal generation, sampling strategies, and other issues that affect detection performance. The book describes every newly proposed novel solution but skips through the fundamentals so that readers can see the field's cutting edge more rapidly. Moreover, unlike prior object detection publications, this project analyses deep learning-based object identification methods systematically and exhaustively, and also gives the most recent detection solutions and a collection of noteworthy research trends. The book focuses primarily on step-by-step discussion, an extensive literature review, detailed analysis and discussion, and rigorous experimentation results. Furthermore, a practical approach is displayed and encouraged.

The book presents a significant expansion in depth and breadth of the previous edition. It includes substantially more numerical illustrations and copious supporting MATLAB code that the reader can use to replicate illustrations or build his or her own. The code is deliberately written to be as simple as possible and easy to edit. The book is an excellent starting point for any researcher to gain a solid grounding in MPC concepts and algorithms before moving into application or more advanced research topics. Sample problems for readers are embedded throughout the chapters, and in-text questions are designed for readers to demonstrate an understanding of concepts through numerical simulation.

Takes an interdisciplinary approach to contribute to the ongoing development of human-AI interaction. Current debate and development of AI is "algorithm-driven" or technical-oriented in lieu of human-centered. At present, there is no systematic interdisciplinary discussion to effectively deal with issues and challenges arising from AI. This book offers critical analysis of the logic and social implications of algorithmic processes. Reporting from the processes of scientific research, the results can be useful for understanding the relationship between algorithms and humans, allowing AI designers to assess the quality of the meaningful interactions with AI systems.

With the increasing demand of robots for industrial and domestic use, it becomes indispensable to ensure their safety, security, and reliability. Safety, Security and Reliability of Robotic Systems: Algorithms, Applications, and Technologies provides a broad and comprehensive coverage of the evolution of robotic systems, as well as industrial statistics and future forecasts. First, it analyzes the safety-related parameters of these systems. Then, it covers security attacks and related countermeasures, and how to establish reliability in these systems. The later sections of the book then discuss various applications of these systems in modern industrial and domestic settings. By the end of this book, you will be familiarized with the theoretical frameworks, algorithms, applications, technologies, and empirical research findings on the safety, security, and reliability of robotic systems, while the book's modular structure and comprehensive material will keep you interested and involved throughout. This book is an essential resource for students, professionals, and entrepreneurs who wish to understand the safe, secure, and reliable use of robotics in real-world applications. It is edited by two specialists in the field, with chapter contributions from an array of experts on robotics systems and applications.

Focuses on the Internet of Healthcare Things and innovative solutions developed for use in the application of healthcare services Discusses artificial intelligence applications, experiments, core concepts, and cutting-edge themes Demonstrates new approaches to analysing medical data and identifying ailments using AI to improve overall quality of life Introduces fundamental concepts for designing the Internet of Healthcare Things solutions Includes pertinent case studies and applications

One of the most difficult, yet important, questions regarding projects is "What advantages will this project create for the investors and key stakeholders?" Projects and programs should be treated as investments. This means that the focus of projects shifts from delivering within the triple constraints (time-cost-quality) towards some of the more fundamental questions: What is the purpose of this investment? What are the specific advantages expected? Are these benefits worth the investment? Implementing Project and Program Benefit Management is written for executives and practitioners within the portfolio, program, and project environment. It guides them through the important work that must be addressed as the investment progresses towards the realization of benefits. The processes discussed cover the strategic elements of benefits realization as well as the more detailed requirements, which are the domain of the program delivery teams and the operational users. Using real cases to explain complex situations, operational teams and wider groups of stakeholders, including communities affected by infrastructure projects, will be able to engage in the conversation with the sponsors and delivery teams. Covering an area of program and project management that is rapidly becoming more widely valued, this book blends theory with practical experience to present a clear process flow to managing the benefits life cycle. Best practices are defined, and pitfalls and traps are identified to enable practitioners to apply rigor and structure to this crucial discipline.

Software analysis patterns play an important role in reducing the overall cost and compressing the time of software project lifecycles. However, building reusable and stable software analysis patterns is still considered a major and delicate challenge. This book proposes a novel concept for building analysis patterns based on software stability and is a modern approach for building stable, highly reusable, and widely applicable analysis patterns. The book also aims to promote better understanding of problem spaces and discusses how to focus requirements analysis accurately. It demonstrates a new approach to discovering and creating stable analysis patterns (SAPs). This book presents a pragmatic approach to understanding problem domains, utilizing SAPs for any field of knowledge, and modeling stable software systems, components, and frameworks. It helps readers attain the basic knowledge that is needed to analyze and extract analysis patterns from any domain of interest. Readers also learn to master methods to document patterns in an effective, easy, and comprehensible manner. Bringing significant contributions to the field of computing, this book is a unique and comprehensive reference manual on SAPs. It provides insight on handling the understanding of problem spaces and supplies methods and processes to analyze user requirements accurately as well as ways to use SAPs in building myriad cost-effective and highly maintainable systems. The book also shows how to link SAPs to the design phase thereby ensuring a smooth transition between analysis and design.

The growing complexity of projects today, as well as the uncertainty inherent in innovative projects, is making obsolete traditional project management practices and procedures, which are based on the notion that much about a project is known at its start. The current high level of change and complexity confronting organizational leaders and managers requires a new approach to projects so they can be managed flexibly to embrace and exploit change. What once used to be considered extreme uncertainty is now the norm, and managing planned projects is being replaced by managing projects as they evolve. Successfully managing projects in extreme situations, such as polar and military expeditions, shows how to manage successfully projects in today's turbulent environment. Executed under the harshest and most unpredictable conditions, these projects are great sources for learning about how to manage unexpected and unforeseen situations as they occur. This book presents multiple case studies of managing extreme events as they happened during polar, mountain climbing, military, and rescue expeditions. A boat accident in the Artic is a lesson on how an effective project manager must be ambidextrous: on one hand able to follow plans and on the other hand able to abandon those plans when disaster strikes and improvise new ones in response. Polar expeditions also illustrate how a team can use "weak links" to go beyond its usual information network to acquire strategic information. Fire and rescues operations illustrate how one team member's knowledge can be transferred to the entire team. Military operations provide case material on how teams coordinate and make use of both individual and collective competencies. This groundbreaking work pushes the definitions of a project and project management to reveal new insight that benefits researchers, academics, and the practitioners managing projects in today's challenging and uncertain times.

The text covers a wide range of topics such as mathematical modeling of crop pest control management, water resources management, impact of anthropogenic activities on atmospheric carbon dioxide concentrations, impact of climate changes on melting of glaciers and polar bear populations, dynamics of slow-fast predator-prey system and spread and control of HIV epidemic. It emphasizes the use of mathematical modeling to investigate the fluid flow problems including the breaking of viscoelastic jet, instability arising in nanofiber, flow in an annulus channel, and thermal instability in nano-fluids in a comprehensive manner. This book will be a readily accessible source of information for the students, researchers and policymakers interested in the application of mathematical and computational modeling techniques to investigate various biological and engineering phenomena. Features Focuses on the current modeling and computational trends to investigate various ecological, epidemiological, and engineering systems. Presents the mathematical modeling of a wide range of ecological and environmental issues including crop pest control management, water resources management, the effect of anthropogenic activities on atmospheric carbon dioxide concentrations, and impact of climate changes on melting of glaciers and polar bear population. Covers a wide range of topics including the breaking of viscoelastic jet, instability arising in nanofiber, flow in an annulus channel, and thermal instability in nano-fluids. Examines evolutionary models i.e., models of time-varying processes. Highlights the recent developments in the analytical methods to investigate the nonlinear dynamical systems. Showcases diversified applications of computational techniques to solve practical biological and engineering problems. The book focuses on the recent research developments in the mathematical modeling and scientific computing of biological and engineering systems. It will serve as an ideal reference text for senior undergraduate, graduate students, and researchers in diverse fields including ecological engineering, environmental engineering, computer engineering, mechanical engineering, mathematics, and fluid dynamics.

Derived from industry-training classes that the author teaches at the Embedded Systems Institute at Eindhoven, the Netherlands and at Buskerud University College at Kongsberg in Norway, Systems Architecting: A Business Perspective places the processes of systems architecting in a broader context by juxtaposing the relationship of the systems architect with enterprise and management. This practical, scenario-driven guide fills an important gap, providing systems architects insight into the business processes, and especially into the processes to which they actively contribute. The book uses a simple reference model to enable understanding of the inside of a system in relation to its context. It covers the impact of tool selection and brings balance to the application of the intellectual tools versus computer-aided tools. Stressing the importance of a clear strategy, the authors discuss methods and techniques that facilitate the architect's contribution to the strategy process. They also give insight into the needs and complications of harvesting synergy, insight that will help establish an effective synergy-harvesting strategy. The book also explores the often difficult relationship between managers and systems architects. Written in an approachable style, the book discusses the breadth of the human sciences and their relevance to systems architecting. It highlights the relevance of human aspects to systems architects, linking theory to practical experience when developing systems architecting competence.

Cognitive Computing for Internet of Medical Things (IoMT) offers a complete assessment of the present scenario, role, challenges, technologies, and impact of IoMT-enabled smart healthcare systems. It contains chapters discussing various biomedical applications under the umbrella of the IoMT. Key Features Exploits the different prospects of cognitive computing techniques for the IoMT and smart healthcare applications Addresses the significance of IoMT and cognitive computing in the evolution of intelligent medical systems for biomedical applications Describes the different computing techniques of cognitive intelligent systems from a practical point of view: solving common life problems Explores the technologies and tools to utilize IoMT for the transformation and growth of healthcare systems Focuses on the economic, social, and environmental impact of IoMT-enabled smart healthcare systems This book is primarily aimed at graduates, researchers and academicians working in the area of development of the application of the of the application of the IoT in smart healthcare. Industry professionals will also find this book helpful.

Completely revised including six new chapters, this new edition presents a more comprehensive knowledge of issues facing developers of complex products and process management. It includes more tools for implementing a Systems Engineering approach to minimize the risks of delays and cost overruns and helps create the right product for its customers. Designing Complex Products with Systems Engineering Processes and Techniques, Second Edition highlights how to increase customer satisfaction, quality, safety, and usability to meet program timings and budgets using a Systems Engineering approach. It provides decision-making considerations and models for creating sustainable product design and describes many techniques and tools used in product development and the product life-cycle orientation. The book also offers techniques used in Design for Manufacturing, Design for Assembly, and product evaluation methods for verification and validation testing. Many new examples, case studies, six new chapters, and updated program and data charts held on our website are offered. The book targets practicing engineers, engineering management personnel, product designers, product planners, product and program managers in all industrialized and developing countries. In addition the book is also useful to undergraduate, graduate students, and faculty in engineering, product design, and product project and program management.

Covers technologies considered to explore, predict, operation and maintenance of renewable energy sources Aids design and use of renewable energy sources including application of artificial intelligence in a real-time environment Includes IoT, Cloud Computing, Big data, Smart Grid and different optimization techniques for resource forecasting, installation, operation, and optimization of energy generation Discusses the principle of integration/hybridization of renewable energy sources along with their optimization based on energy requirement. Reviews concept and challenges involved in the implementation of smart grid.

Discusses the efficiency measurement of online education Presents the environmental impact of online education Offers a parametric evaluation and categorization of online learning systems Covers big data ecosystems in cloud computing Provides analytical methods to find solutions for big data challenges

Graph Theory and Its Applications, Third Edition is the latest edition of the international, bestselling textbook for undergraduate courses in graph theory, yet it is expansive enough to be used for graduate courses as well. The textbook takes a comprehensive, accessible approach to graph theory, integrating careful exposition of classical developments with emerging methods, models, and practical needs. The authors' unparalleled treatment is an ideal text for a two-semester course and a variety of one-semester classes, from an introductory one-semester course to courses slanted toward classical graph theory, operations research, data structures and algorithms, or algebra and topology. Features of the Third Edition Expanded coverage on several topics (e.g., applications of graph coloring and tree-decompositions) Provides better coverage of algorithms and algebraic and topological graph theory than any other text Incorporates several levels of carefully designed exercises that promote student retention and develop and sharpen problem-solving skills Includes supplementary exercises to develop problem-solving skills, solutions and hints, and a detailed appendix, which reviews the textbook's topics About the Authors Jonathan L. Gross is a professor of computer science at Columbia University. His research interests include topology and graph theory. Jay Yellen is a professor of mathematics at Rollins College. His current areas of research include graph theory, combinatorics, and algorithms. Mark Anderson is also a mathematics professor at Rollins College. His research interest in graph theory centers on the topological or algebraic side.

Machine Learning (ML) is a sub field of artificial intelligence that uses soft computing and algorithms to enable computers to learn on their own and identify patterns in observed data, build models that explain the world, and predict things without having explicit pre-programmed rules and models. This book discusses various applications of ML in engineering fields and the use of ML algorithms in solving challenging engineering problems ranging from biomedical, transport, supply chain and logistics, to manufacturing and industrial. Through numerous case studies, it will assist researchers and practitioners in selecting the correct options and strategies for managing organizational tasks.

Smart shipping is a future method for transporting ocean cargo and exploring the resources of oceans for medical drugs, food, energy resources, and other products. A smart ship is an integration of shipping with many fields such as fishing, manufacturing, navigation, communication, computing, control, sensing, etc., to provide better shipping and services. The purpose of this edited book is to provide state-of-the-art approaches and novel technologies for smart ships, covering a range of topics in these areas so that it will be an excellent reference book for the researchers, students, and professionals in these areas. It presents the fundamental technologies needed to build smart ships, and gives a clear explanation of them. This book will serve as a good reference for researchers to know the state of the art and to discover uncovered territory and develop new applications, as well as being a guideline for building future smart ships. Yang Xiao is a Full Professor in the Department of Computer Science at the University of Alabama, Tuscaloosa, Alabama, USA. Tieshan Li is a Full Professor in the School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China.

This book is an attempt to establish in the readers the importance of creating interoperable data stores and writing rules for handling this data. It also covers extracts from a few project dissertations and a research funded project that the author had supervised.• Describes the power of ontologies for better data management• Provides an overview of knowledge engineering including ontology engineering, tools and techniques• Provides sample development procedures for creating two domain ontologies.• Depicts the utility of ontological representation in situation awareness• Demonstrates recommendation engine for unconventional emergencies using a hybrid reasoning approach.• The text explains how to make better utilization of resources when emergency strikesGraduates and undergraduates doing courses in artificial intelligence, semantic web and knowledge engineering will find this book beneficial.

In recent years, drones have been integrated with the Internet of Things to offer a variety of exciting new applications. Here is a detailed exploration of adapting and implementing Internet of Drones technologies in real-world applications, emphasizing solutions to architectural challenges and providing a clear overview of standardization and regulation, implementation plans, and privacy concerns. The book discusses the architectures and protocols for drone communications, implementing and deploying of 5G-drone setups, security issues, deep learning techniques applied on real-time footage, and more. It also explores some of the varied applications, such as for monitoring and analysis of troposphere pollutants, providing services and communications in smart cities (such as for weather forecasting, communications, transport, safety and protection), for disaster relief management, for agricultural crop monitoring, and more.

Predictive analytics refers to making predictions about the future based on different parameters which are historical data, machine learning, and artificial intelligence. This book provides the most recent advances in the field along with case studies and real-world examples. It discusses predictive modeling and analytics in reliability engineering and introduces current achievements and applications of artificial intelligence, data mining, and other techniques in supply chain management. It covers applications to reliability engineering practice, presents numerous examples to illustrate the theoretical results, and considers and analyses case studies and real-word examples. The book is written for researchers and practitioners in the field of system reliability, quality, supply chain management, and logistics management. Students taking courses in these areas will also find this book of interest.