Artificial Intelligence in Mechanical and Industrial Engineering offers a unified platform for the dissemination of basic and applied knowledge on the integration of artificial intelligence within the realm of mechanical and industrial engineering. The book covers the tools and information needed to build successful careers and a source of knowledge for those working with AI within these domains. The book offers a systematic approach to explicate fundamentals as well as recent advances. It incorporates various case studies for major topics as well as numerous examples. It will also include real-time intelligent automation and associated supporting methodologies and techniques, and cover decision-support systems, as well as applications of Chaos Theory and Fractals. The book will give scientists, researchers, instructors, students, and practitioners the tools and information needed to build successful careers and to be an impetus to advancements in next-generation mechanical and industrial engineering domains.

eWork and eBusiness in Architecture, Engineering and Construction 2021 collects the papers presented at the 13th European Conference on Product and Process Modelling (ECPPM 2021, Moscow, 5-7 May 2021). The contributions cover a wide spectrum of thematic areas that hold great promise towards the advancement of research and technological development targeted at the digitalization of the AEC/FM (Architecture, Engineering, Construction and Facilities Management) domains. High quality contributions are devoted to critically important problems that arise, including: Information and Knowledge Management Semantic Web and Linked Data Communication and Collaboration Technologies Software Interoperability BIM Servers and Product Lifecycle Management Systems Digital Twins and Cyber-Physical Systems Sensors and Internet of Things Big Data Artificial and Augmented Intelligence in AEC Construction Management 5D/nD Modelling and Planning Building Performance Simulation Contract, Cost and Risk Management Safety and Quality Sustainable Buildings and Urban Environments Smart Buildings and Cities BIM Standardization, Implementation and Adoption Regulatory and Legal Aspects BIM Education and Training Industrialized Production, Smart Products and Services Over the past quarter century, the biennial ECPPM conference series, as the oldest BIM conference, has provided researchers and practitioners with a unique platform to present and discuss the latest developments regarding emerging BIM technologies and complementary issues for their adoption in the AEC/FM industry.

This book aims to assess the experience of education during COVID-19 pandemic and explore the future of application of technologies and artificial intelligence in education. Education delivery requires the support of new technologies such as artificial intelligence (AI), the Internet of Things (IoT), big data, and machine learning to fight and aspire to new diseases. The academic community and those interested in education agree that education after the corona pandemic will not be the same as before. The book also questions the role of accreditation bodies (e.g., AACSB, etc.) to ensure the effectiveness and efficiency of technology tools in achieving distinguished education in times of crisis.

The Internet has gone from an Internet of people to an Internet of Things (IoT). This has brought forth strong levels of complexity in handling interoperability that involves the integrating of wireless sensor networks (WSNs) into IoT. This book offers insights into the evolution, usage, challenges, and proposed countermeasures associated with the integration. Focusing on the integration of WSNs into IoT and shedding further light on the subtleties of such integration, this book aims to highlight the encountered problems and provide suitable solutions. It throws light on the various types of threats that can attack both WSNs and IoT along with the recent approaches to counter them. This book is designed to be the first choice of reference at research and development centers, academic institutions, university libraries, and any institution interested in the integration of WSNs into IoT. Undergraduate and postgraduate students, Ph.D. scholars, industry technologists, young entrepreneurs, and researchers working in the field of security and privacy in IoT are the primary audience of this book.

This book covers a wide range of topics on the role of Artificial Intelligence, Machine Learning, and Big Data for healthcare applications and deals with the ethical issues and concerns associated with it. This book explores the applications in different areas of healthcare and highlights the current research. "Big Data and Artificial Intelligence for Healthcare Applications" covers healthcare big data analytics, mobile health and personalized medicine, clinical trial data management and presents how Artificial Intelligence can be used for early disease diagnosis prediction and prognosis. It also offers some case studies that describes the application of Artificial Intelligence and Machine Learning in healthcare. Researchers, healthcare professionals, data scientists, systems engineers, students, programmers, clinicians, and policymakers will find this book of interest.

Cloud computing is an indispensable part of the modern Information and Communication Technology (ICT) systems. Cloud computing services have proven to be of significant importance, and promote quickly deployable and scalable IT solutions with reduced infrastructure costs. However, utilization of cloud also raises concerns such as security, privacy, latency, and governance, that keep it from turning into the predominant option for critical frameworks. As such, there is an urgent need to identify these concerns and to address them. Cloud Security: Concepts, Applications and Perspectives is a comprehensive work with substantial technical details for introducing the state-of-the-art research and development on various approaches for security and privacy of cloud services; novel attacks on cloud services; cloud forensics; novel defenses for cloud service attacks; and cloud security analysis. It discusses the present techniques and methodologies, and provides a wide range of examples and illustrations to effectively show the concepts, applications, and perspectives of security in cloud computing. This highly informative book will prepare readers to exercise better protection by understanding the motivation of attackers and to deal with them to mitigate the situation. In addition, it covers future research directions in the domain. This book is suitable for professionals in the field, researchers, students who are want to carry out research in the field of computer and cloud security, faculty members across universities, and software developers engaged in software development in the field.

This book aims to bring together leading academic scientists, researchers, and research scholars to exchange and share their experiences and research results on all aspects of Artificial Intelligence. The book provides a premier interdisciplinary platform to present practical challenges and adopted solutions. The book addresses the complete functional framework workflow in Artificial Intelligence technology. It explores the basic and high-level concepts and can serve as a manual for the industry for beginners and the more advanced. It covers intelligent and automated systems and its implications to the real-world, and offers data acquisition and case studies related to data-intensive technologies in AI-based applications. The book will be of interest to researchers, professionals, scientists, professors, students of computer science engineering, electronics and communications, as well as information technology.

The energy cost associated with modern information technologies has been increasing exponentially over time, stimulating the search for alternative information storage and processing devices. Magnetic skyrmions are solitonic nanometer-scale quasiparticles whose unique topological properties can be thought of as that of a Mobius strip. Skyrmions are envisioned as information carriers in novel information processing and storage devices with low power consumption and high information density. As such, they could contribute to solving the energy challenge. In order to be used in applications, isolated skyrmions must be thermally stable at the scale of years. In this work, their stability is studied through two main approaches: the Kramers' method in the form of Langer's theory, and the forward flux sampling method. Good agreement is found between the two methods. We find that small skyrmions possess low internal energy barriers, but are stabilized by a large activation entropy. This is a direct consequence of the existence of stable modes of deformation of the skyrmion. Additionally, frustrated exchange that arises at some transition metal interfaces leads to new collapse paths in the form of the partial nucleation of the corresponding antiparticle, as merons and antimerons.

This book provides the state-of-the-art development on security and privacy for fog/edge computing, together with their system architectural support and applications. This book is organized into five parts with a total of 15 chapters. Each area corresponds to an important snapshot. The first part of this book presents an overview of fog/edge computing, focusing on its relationship with cloud technology and the future with the use of 5G communication. Several applications of edge computing are discussed. The second part of this book considers several security issues in fog/edge computing, including the secure storage and search services, collaborative intrusion detection method on IoT-fog computing, and the feasibility of deploying Byzantine agreement protocols in untrusted environments. The third part of this book studies the privacy issues in fog/edge computing. It first investigates the unique privacy challenges in fog/edge computing, and then discusses a privacy-preserving framework for the edge-based video analysis, a popular machine learning application on fog/edge. This book also covers the security architectural design of fog/edge computing, including a comprehensive overview of vulnerabilities in fog/edge computing within multiple architectural levels, the security and intelligent management, the implementation of network-function-virtualization-enabled multicasting in part four. It explains how to use the blockchain to realize security services. The last part of this book surveys applications of fog/edge computing, including the fog/edge computing in Industrial IoT, edge-based augmented reality, data streaming in fog/edge computing, and the blockchain-based application for edge-IoT. This book is designed for academics, researchers and government officials, working in the field of fog/edge computing and cloud computing. Practitioners, and business organizations (e.g., executives, system designers, and marketing professionals), who conduct teaching, research, decision making, and designing fog/edge technology will also benefit from this book The content of this book will be particularly useful for advanced-level students studying computer science, computer technology, and information systems, but also applies to students in business, education, and economics, who would benefit from the information, models, and case studies therein.

This book is a compendium of peer reviewed papers resulting from the International Symposium on Spatial Data Handling (SDH), held in Ottawa, Canada, July 9-12, 2002. It presents a selection of papers that demonstrate a maturing in geographical information science (GISc). Of the many challenges under the general topic of spatial data handling, a number of key areas provide the focus for this book. They tackle issues such as database design and architecture, interoperability, integration, fusion, spatial reasoning, visualisation and web-based mapping, among a number of other aspects.

How can we recruit out of your program? We have a project - how do we reach out to your students? If we do research together who owns it? We have employees who need to "upskill" in analytics - can you help me with that? How much does all of this cost? Managers and executives are increasingly asking university professors such questions as they deal with a critical shortage of skilled data analysts. At the same time, academics are asking such questions as: How can I bring a "real" analytical project in the classroom? How can I get "real" data to help my students develop the skills necessary to be a "data scientist? Is what I am teaching in the classroom aligned with the demands of the market for analytical talent? After spending several years answering almost daily e-mails and telephone calls from business managers asking for staffing help and aiding fellow academics with their analytics teaching needs, Dr. Jennifer Priestley of Kennesaw State University and Dr. Robert McGrath of the University of New Hampshire wrote Closing the Analytics Talent Gap: An Executive's Guide to Working with Universities. The book builds a bridge between university analytics programs and business organizations. It promotes a dialog that enables executives to learn how universities can help them find strategically important personnel and universities to learn how they can develop and educate this personnel. Organizations are facing previously unforeseen challenges related to the translation of massive amounts of data - structured and unstructured, static and in-motion, voice, text, and image - into information to solve current challenges and anticipate new ones. The advent of analytics and data science also presents universities with unforeseen challenges of providing learning through application. This book helps both organizations with finding "data natives" and universities with educating students to develop the facility to work in a multi-faceted and complex data environment. .

Going beyond performing simple analyses, researchers involved in the highly dynamic field of computational intelligent data analysis design algorithms that solve increasingly complex data problems in changing environments, including economic, environmental, and social data. Computational Intelligent Data Analysis for Sustainable Development presents novel methodologies for automatically processing these types of data to support rational decision making for sustainable development. Through numerous case studies and applications, it illustrates important data analysis methods, including mathematical optimization, machine learning, signal processing, and temporal and spatial analysis, for quantifying and describing sustainable development problems. With a focus on integrated sustainability analysis, the book presents a large-scale quadratic programming algorithm to expand high-resolution input-output tables from the national scale to the multinational scale to measure the carbon footprint of the entire trade supply chain. It also quantifies the error or dispersion between different reclassification and aggregation schemas, revealing that aggregation errors have a high concentration over specific regions and sectors. The book summarizes the latest contributions of the data analysis community to climate change research. A profuse amount of climate data of various types is available, providing a rich and fertile playground for future data mining and machine learning research. The book also pays special attention to several critical challenges in the science of climate extremes that are not handled by the current generation of climate models. It discusses potential conceptual and methodological directions to build a close integration between physical understanding, or physics-based modeling, and data-driven insights. The book then covers the conservation of species and ecologically valuable land. A case study on the Pennsylvania Dirt and Gravel Roads Program demonstrates that multiple-objective linear programming is a more versatile and efficient approach than the widely used benefit targeting selection process. Moving on to renewable energy and the need for smart grids, the book explores how the ongoing transformation to a sustainable energy system of renewable sources leads to a paradigm shift from demand-driven generation to generation-driven demand. It shows how to maximize renewable energy as electricity by building a supergrid or mixing renewable sources with demand management and storage. It also presents intelligent data analysis for real-time detection of disruptive events from power system frequency data collected using an existing Internet-based frequency monitoring network as well as evaluates a set of computationally intelligent techniques for long-term wind resource assessment. In addition, the book gives an example of how temporal and spatial data analysis tools are used to gather knowledge about behavioral data and address important social problems such as criminal offenses. It also applies constraint logic programming to a planning problem: the environmental and social impact assessment of the regional energy plan of the Emilia-Romagna region of Italy. Sustainable development problems, such as global warming, resource shortages, global species loss, and pollution, push researchers to create powerful data analysis approaches that analysts can then use to gain insight into these issues to support rational decision making. This volume shows both the data analysis and sustainable development communities how to use intelligent data analysis tools to address practical problems and encourages researchers to develop better methods.

Translational bioinformatics (TBI) involves development of storage, analytics, and advanced computational methods to harvest knowledge from voluminous biomedical and genomic data into 4P healthcare (proactive, predictive, preventive, and participatory). Translational Bioinformatics Applications in Healthcare offers a detailed overview on concepts of TBI, biological and clinical databases, clinical informatics, and pertinent real-case applications. It further illustrates recent advancements, tools, techniques, and applications of TBI in healthcare, including Internet of Things (IoT) potential, toxin databases, medical image analysis and telemedicine applications, analytics of COVID-19 CT images, viroinformatics and viral diseases, and COVID-19-related research. Covers recent technologies such as Blockchain, IoT, and Big data analytics in bioinformatics Presents the role of translational bioinformatic methods in the field of viroinformatics, as well as in drug development and repurposing Includes translational healthcare and NGS for clinical applications Illustrates translational medicine systems and their applications in better healthcare Explores medical image analysis with focus on CT images and novel coronavirus disease detection Aimed at researchers and graduate students in computational biology, data mining and knowledge discovery, algorithms and complexity, and interdisciplinary fields of studies, including bioinformatics, health-informatics, biostatistics, biomedical engineering, and viroinformatics. Khalid Raza is an Assistant Professor, the Department of Computer Science, Jamia Millia Islamia (Central University), New Delhi. His research interests include translational bioinformatics, computational intelligence methods and its applications in bioinformatics, viroinformatics, and health informatics. Nilanjan Dey is an Associate Professor, the Department of Computer Science and Engineering, JIS University, Kolkata, India. His research interests include medical imaging, machine learning, computer-aided diagnosis, and data mining.

How can we recruit out of your program? We have a project - how do we reach out to your students? If we do research together who owns it? We have employees who need to "upskill" in analytics - can you help me with that? How much does all of this cost? Managers and executives are increasingly asking university professors such questions as they deal with a critical shortage of skilled data analysts. At the same time, academics are asking such questions as: How can I bring a "real" analytical project in the classroom? How can I get "real" data to help my students develop the skills necessary to be a "data scientist? Is what I am teaching in the classroom aligned with the demands of the market for analytical talent? After spending several years answering almost daily e-mails and telephone calls from business managers asking for staffing help and aiding fellow academics with their analytics teaching needs, Dr. Jennifer Priestley of Kennesaw State University and Dr. Robert McGrath of the University of New Hampshire wrote Closing the Analytics Talent Gap: An Executive's Guide to Working with Universities. The book builds a bridge between university analytics programs and business organizations. It promotes a dialog that enables executives to learn how universities can help them find strategically important personnel and universities to learn how they can develop and educate this personnel. Organizations are facing previously unforeseen challenges related to the translation of massive amounts of data - structured and unstructured, static and in-motion, voice, text, and image - into information to solve current challenges and anticipate new ones. The advent of analytics and data science also presents universities with unforeseen challenges of providing learning through application. This book helps both organizations with finding "data natives" and universities with educating students to develop the facility to work in a multi-faceted and complex data environment. .

This book provides readers with a practical guide to the principles of hybrid approaches to natural language processing (NLP) involving a combination of neural methods and knowledge graphs. To this end, it first introduces the main building blocks and then describes how they can be integrated to support the effective implementation of real-world NLP applications. To illustrate the ideas described, the book also includes a comprehensive set of experiments and exercises involving different algorithms over a selection of domains and corpora in various NLP tasks. Throughout, the authors show how to leverage complementary representations stemming from the analysis of unstructured text corpora as well as the entities and relations described explicitly in a knowledge graph, how to integrate such representations, and how to use the resulting features to effectively solve NLP tasks in a range of domains. In addition, the book offers access to executable code with examples, exercises and real-world applications in key domains, like disinformation analysis and machine reading comprehension of scientific literature. All the examples and exercises proposed in the book are available as executable Jupyter notebooks in a GitHub repository. They are all ready to be run on Google Colaboratory or, if preferred, in a local environment. A valuable resource for anyone interested in the interplay between neural and knowledge-based approaches to NLP, this book is a useful guide for readers with a background in structured knowledge representations as well as those whose main approach to AI is fundamentally based on logic. Further, it will appeal to those whose main background is in the areas of machine and deep learning who are looking for ways to leverage structured knowledge bases to optimize results along the NLP downstream.

The aims of these proceedings are to provide a complete coverage of the areas outlined, and to bring together researchers from academic and industry to share ideas, challenges, and solutions relating to the multifaceted aspects of this field. New multimedia standards (for example, MPEG-21) facilitate the seamless integration of multiple modalities into interoperable multimedia frameworks, transforming the way people work and interact with multimedia data. These key technologies and multimedia solutions interact and collaborate with each other in increasingly effective ways, contributing to the multimedia revolution and having a significant impact across a wide spectrum of consumer, business, healthcare, education, and governmental domains.

This book introduces to blockchain and deep learning and explores and illustrates the current and new trends that integrate them. The pace and speeds for connectivity are certain on the ascend. Blockchain and deep learning are twin technologies that are integral to integrity and relevance of network contents. Since they are data-driven technologies, rapidly growing interests exist to incorporate them in efficient and secure data sharing and analysis applications. Blockchain and deep learning are sentinel contemporary research technologies. This book provides a comprehensive reference for blockchain and deep learning by covering all important topics. It identifies the bedrock principles and forward projecting methodologies that illuminate the trajectory of developments for the decades ahead.

This book explores the phenomenon of data - big and small - in the contemporary digital, informatic and legal-bureaucratic context. Challenging the way in which legal interest in data has focused on rights and privacy concerns, this book examines the contestable, multivocal and multifaceted figure of the contemporary data subject. The book analyses "data" and "personal data" as contemporary phenomena, addressing the data realms, such as stores, institutions, systems and networks, out of which they emerge. It interrogates the role of law, regulation and governance in structuring both formal and informal definitions of the data subject, and disciplining data subjects through compliance with normative standards of conduct. Focusing on the 'personal' in and of data, the book pursues a re-evaluation of the nature, role and place of the data subject qua legal subject in on and offline societies: one that does not begin and end with the inviolability of individual rights but returns to more fundamental legal principles suited to considerations of personhood, such as stewardship, trust, property and contract. The book's concern with the production, use, abuse and alienation of personal data within the context of contemporary communicative capitalism will appeal to scholars and students of law, science and technology studies, and sociology; as well as those with broader political interests in this area.

Social networking has increased drastically in recent years, resulting in an increased amount of data being created daily. Furthermore, diversity of issues and complexity of the social networks pose a challenge in social network mining. Traditional algorithm software cannot deal with such complex and vast amounts of data, necessitating the development of novel analytic approaches and tools. This reference work deals with social network aspects of big data analytics. It covers theory, practices and challenges in social networking. The book spans numerous disciplines like neural networking, deep learning, artificial intelligence, visualization, e-learning in higher education, e-healthcare, security and intrusion detection.

The book aims to showcase the basics of both IoT and Blockchain for beginners as well as their integration and challenge discussions for existing practitioner. It aims to develop understanding of the role of blockchain in fostering security. The objective of this book is to initiate conversations among technologists, engineers, scientists, and clinicians to synergize their efforts in producing low-cost, high-performance, highly efficient, deployable IoT systems. It presents a stepwise discussion, exhaustive literature survey, rigorous experimental analysis and discussions to demonstrate the usage of blockchain technology for securing communications. The book evaluates, investigate, analyze and outline a set of security challenges that needs to be addressed in the near future. The book is designed to be the first reference choice at research and development centers, academic institutions, university libraries and any institutions interested in exploring blockchain. UG/PG students, PhD Scholars of this fields, industry technologists, young entrepreneurs and researchers working in the field of blockchain technology are the primary audience of this book.

"Writing Effective Business Rules" moves beyond the fundamental dilemma of system design: defining business rules either in natural language, intelligible but often ambiguous, or program code (or rule engine instructions), unambiguous but unintelligible to stakeholders. Designed to meet the needs of business analysts, this book provides an exhaustive analysis of rule types and a set of syntactic templates from which unambiguous natural language rule statements of each type can be generated. A user guide to the SBVR specification, it explains how to develop an appropriate business vocabulary and generate quality rule statements using the appropriate templates and terms from the vocabulary. The resulting rule statements can be reviewed by business stakeholders for relevance and correctness, providing for a high level of confidence in their successful implementation.
A complete set of standard templates for rule statements and their component syntactic elementsA rigorous approach to rule statement construction to avoid ambiguity and ensure consistencyA clear explanation of the way in which a fact model provides and constrains the rule statement vocabularyA practical reader-friendly user guide to the those parts of the SBVR specification that are relevant to rule authoring

Information security is receiving a great deal of attention as computers increasingly process more and more sensitive information. A multilevel secure database management system (MLS DBMS) is designed to store, retrieve and process information in compliance with certain mandatory security requirements, essential for protecting sensitive information from unauthorized access, modification and abuse. Such systems are characterized by data objects labeled at different security levels and accessed by users cleared to those levels. Unless transaction processing modules for these systems are designed carefully, they can be exploited to leak sensitive information to unauthorized users. In recent years, considerable research has been devoted to the area of multilevel secure transactions that has impacted the design and development of trusted MLS DBMS products. Multilevel Secure Transaction Processing presents the progress and achievements made in this area. The book covers state-of-the-art research in developing secure transaction processing for popular MLS DBMS architectures, such as kernelized, replicated, and distributed architectures, and advanced transaction models such as workflows, long duration and nested models. Further, it explores the technical challenges that require future attention. Multilevel Secure Transaction Processing is an excellent reference for researchers and developers in the area of multilevel secure database systems and may be used in advanced level courses in database security, information security, advanced database systems, and transaction processing.

This book is about cooperative work and the coordinative practices through which order in cooperative work is accomplished. Information technology has been used in organisational settings and for organisational purposes such as accounting, for a half century, but IT is now also and increasingly being used for the purposes of mediating and regulating complex activities in which multiple professional actors are involved, in factories and hospitals, in pharmaceutical laboratories and architectural offices, and so on. The economic importance of such coordination systems is enormous but their design often inadequate. The problem is that our understanding of the coordinative practices for which these systems are developed is deficient, leaving systems developers and software engineers to base their designs on commonsensical requirements analyses. The research reflected in this book addresses these very problems. It is a collection of articles which establish a conceptual foundation for the research area of Computer-Supported Cooperative Work.

This book, the second volume, highlights 7 out of a total of about 36 megacities in the World which by definition have 10 million inhabitants. The cities/chapters presented in this book are based on recent advance such as the wide use of ICT, IOT, e-Governance, e-Democracy, smart economy and flattening and acceleration of the world that is taking place in recent times as reported by 3 times Pulitzer Prize Winner Thomas Friedman. It therefor departs from other ideologies where only a certain megacity qualifies for the title of smart global megacities while in reality every megacity can, and presents how smart global megacities can be created.

New technologies mean that sports clubs and governing bodies are generating more data than ever to help manage their relationship with fans, their performance, and their income streams. This new edition of Winning with Data in the Business of Sports explains how to acquire, store, maintain, and use data in the most effective ways. The key developments are three-fold: new technology, new understanding of how to apply that technology, and the new laws informing and controlling the data that can be generated from the technology. Important developments that have occurred since the publication of the first edition include the General Data Protection Regulations (GDPR) and the COVID-19 pandemic. With a focus on these unique challenges coupled with the opportunities the use of data creates, this book is essential reading for professionals within the sports industry. This second edition includes: - An introduction to new technologies, the data they generate, and the supporting processes we need to have in place to use them. - Brand new case studies with recent examples of creative applications from clubs, teams, leagues, and governing bodies, including Arsenal, AS Roma, ICC Cricket World Cup, LA Kings, Portland Trail Blazers, and UEFA. - The sports industry's response to tighter data legislation introduced primarily though the GDPR. - The role of data and direct engagement during the COVID-19 pandemic. The book provides clear guidance and knowledge that sports industry professionals need to understand the role of data for the business side of sports. It is essential reading for sports clubs, governing bodies and those working in sports marketing, media and communications, sponsorship, merchandise, ticketing, events, and participation development. The book will also be of interest to students of sports management.