Data-Driven Solutions to Transportation Problems explores the fundamental principle of analyzing different types of transportation-related data using methodologies such as the data fusion model, the big data mining approach, computer vision-enabled traffic sensing data analysis, and machine learning. The book examines the state-of-the-art in data-enabled methodologies, technologies and applications in transportation. Readers will learn how to solve problems relating to energy efficiency under connected vehicle environments, urban travel behavior, trajectory data-based travel pattern identification, public transportation analysis, traffic signal control efficiency, optimizing traffic networks network, and much more.

Industrial internet of things (IIoT) is changing the face of industry by completely redefining the way stakeholders, enterprises, and machines connect and interact with each other in the industrial digital ecosystem. Smart and connected factories, in which all the machinery transmits real-time data, enable industrial data analytics for improving operational efficiency, productivity, and industrial processes, thus creating new business opportunities, asset utilization, and connected services. IIoT leads factories to step out of legacy environments and arcane processes towards open digital industrial ecosystems. Innovations in the Industrial Internet of Things (IIoT) and Smart Factory is a pivotal reference source that discusses the development of models and algorithms for predictive control of industrial operations and focuses on optimization of industrial operational efficiency, rationalization, automation, and maintenance. While highlighting topics such as artificial intelligence, cyber security, and data collection, this book is ideally designed for engineers, manufacturers, industrialists, managers, IT consultants, practitioners, students, researchers, and industrial industry professionals.

There is no doubt that there has been much excitement regarding the pioneering contributions of artificial intelligence (AI), the internet of things (IoT), and blockchain technologies and tools in visualizing and realizing smarter as well as sophisticated systems and services. However, researchers are being bombarded with various machine and deep learning algorithms, which are categorized as a part and parcel of the enigmatic AI discipline. The knowledge discovered gets disseminated to actuators and other concerned systems in order to empower them to intelligently plan and insightfully execute appropriate tasks with clarity and confidence. The IoT processes in conjunction with the AI algorithms and blockchain technology are bound to lay out a stimulating foundation for producing and sustaining smarter systems for society. The Handbook of Research on Smarter and Secure Industrial Applications Using AI, IoT, and Blockchain Technology articulates and accentuates various AI algorithms, fresh innovations in the IoT, and blockchain spaces. The domain of transforming raw data to information and to relevant knowledge is gaining prominence with the availability of data ingestion, processing, mining, analytics algorithms, platforms, frameworks, and other accelerators. Covering topics such as blockchain applications, Industry 4.0, and cryptography, this book serves as a comprehensive guide for AI researchers, faculty members, IT professionals, academicians, students, researchers, and industry professionals.

The idea of this book grew out of a symposium that was held at Stony Brook in September 2012 in celebration of David S.Warren's fundamental contributions to Computer Science and the area of Logic Programming in particular. Logic Programming (LP) is at the nexus of Knowledge Representation, Artificial Intelligence, Mathematical Logic, Databases, and Programming Languages. It is fascinating and intellectually stimulating due to the fundamental interplay among theory, systems, and applications brought about by logic. Logic programs are more declarative in the sense that they strive to be logical specifications of "what" to do rather than "how" to do it, and thus they are high-level and easier to understand and maintain. Yet, without being given an actual algorithm, LP systems implement the logical specifications automatically. Several books cover the basics of LP but focus mostly on the Prolog language with its incomplete control strategy and non-logical features. At the same time, there is generally a lack of accessible yet comprehensive collections of articles covering the key aspects in declarative LP. These aspects include, among others, well-founded vs. stable model semantics for negation, constraints, object-oriented LP, updates, probabilistic LP, and evaluation methods, including top-down vs. bottom-up, and tabling. For systems, the situation is even less satisfactory, lacking accessible literature that can help train the new crop of developers, practitioners, and researchers. There are a few guides onWarren's Abstract Machine (WAM), which underlies most implementations of Prolog, but very little exists on what is needed for constructing a state-of-the-art declarative LP inference engine. Contrast this with the literature on, say, Compilers, where one can first study a book on the general principles and algorithms and then dive in the particulars of a specific compiler. Such resources greatly facilitate the ability to start making meaningful contributions quickly. There is also a dearth of articles about systems that support truly declarative languages, especially those that tie into first-order logic, mathematical programming, and constraint solving. LP helps solve challenging problems in a wide range of application areas, but in-depth analysis of their connection with LP language abstractions and LP implementation methods is lacking. Also, rare are surveys of challenging application areas of LP, such as Bioinformatics, Natural Language Processing, Verification, and Planning. The goal of this book is to help fill in the previously mentioned void in the LP literature. It offers a number of overviews on key aspects of LP that are suitable for researchers and practitioners as well as graduate students. The following chapters in theory, systems, and applications of LP are included.

The emergent phenomena of virtual reality, augmented reality, and mixed reality is having an impact on ways people communicate with technology and with each other. Schools and higher education institutions are embracing these emerging technologies and implementing them at a rapid pace. The challenge, however, is to identify well-defined problems where these innovative technologies can support successful solutions and subsequently determine the efficacy of effective virtual learning environments. Emerging Technologies in Virtual Learning Environments is an essential scholarly research publication that provides a deeper look into 3D virtual environments and how they can be developed and applied for the benefit of student learning and teacher training. This book features a wide range of topics in the areas of science, technology, engineering, arts, and math to ensure a blend of both science and humanities research. Therefore, it is ideal for curriculum developers, instructional designers, teachers, school administrators, higher education faculty, professionals, researchers, and students studying across all academic disciplines.

Business approaches in today's society have become technologically-driven and highly-applicable within various professional fields. These business practices have transcended traditional boundaries with the implementation of internet technology, making it challenging for professionals outside of the business world to understand these advancements. Interdisciplinary research on business technology is required to better comprehend its innovations. The Handbook of Research on Interdisciplinary Approaches to Digital Transformation and Innovation provides emerging research exploring the complex interconnections of technological business practices within society. This book will explore the practical and theoretical aspects of e-business technology within the fields of engineering, health, and social sciences. Featuring coverage on a broad range of topics such as data monetization, mobile commerce, and digital marketing, this book is ideally designed for researchers, managers, students, engineers, computer scientists, economists, technology designers, information specialists, and administrators seeking current research on the application of e-business technologies within multiple fields.

Updates the premier textbook for students and librarians needing to know the landscape of current databases and how to search them. Librarians need to know of existing databases, and they must be able to teach search capabilities and strategies to library users. This practical guide introduces librarians to a broad spectrum of fee-based and freely available databases and explains how to teach them. The updated 6th edition of this well-regarded text covers new databases on the market as well as updates to older databases. It also explains underlying information structures and demonstrates how to search most effectively. It introduces readers to several recent changes, such as the move away from metadata-based indexing to full text indexing by vendors covering newspaper content. Business databases receive greater emphasis. As in the previous edition, this book takes a real-world approach, covering topics from basic and advanced search tools to online subject databases. Each chapter includes a thorough discussion, a recap, concrete examples, exercises, and points to consider, making it an ideal text for courses in database searching as well as a trustworthy professional resource. Helps librarians and students understand the latest developments in library databases Looks not only at textual databases but also numerical, image, video, and social media resources Includes changes and trends in database functionality since the 5th edition

Society is continually transforming into a digitally powered reality due to the increased dependence of computing technologies. The landscape of cyber threats is constantly evolving because of this, as hackers are finding improved methods of accessing essential data. Analyzing the historical evolution of cyberattacks can assist practitioners in predicting what future threats could be on the horizon. Real-Time and Retrospective Analyses of Cyber Security is a pivotal reference source that provides vital research on studying the development of cybersecurity practices through historical and sociological analyses. While highlighting topics such as zero trust networks, geopolitical analysis, and cyber warfare, this publication explores the evolution of cyber threats, as well as improving security methods and their socio-technological impact. This book is ideally designed for researchers, policymakers, strategists, officials, developers, educators, sociologists, and students seeking current research on the evolution of cybersecurity methods through historical analysis and future trends.

Technologies in today's society are rapidly developing at a pace that is challenging to stay up to date with. As an increasing number of global regions are implementing smart methods and strategies for sustainable development, they are continually searching for modern advancements within computer science, sensor networks, software engineering, and smart technologies. A compilation of research is needed that displays current applications of computing methodologies in the progression of global cities and how smart technologies are being utilized. Sensor Network Methodologies for Smart Applications is a collection of innovative research on the methods of intelligent systems and technologies and their various applications within sustainable development practices. While highlighting topics including machine learning, network security, and optimization algorithms, this book is ideally designed for researchers, scientists, developers, programmers, engineers, educators, policymakers, geographers, planners, and students seeking current research on smart technologies and sensor networks.

CCNP and CCIE Enterprise Core ENCOR 350-401 Exam Cram is the perfect study guide to help you pass the updated ENCOR 350-401 exam, a core requirement for your CCNP Enterprise, CCIE Enterprise Infrastructure, or CCIE Enterprise Wireless certification. It delivers expert coverage and practice questions for every exam topic, including implementation of core enterprise network technologies involving dual stack (IPv4 and IPv6) architecture, virtualization, infrastructure, network assurance, security, and automation. This guide's extensive preparation tools includes topic overviews, exam alerts, CramSavers, CramQuizzes, chapter-ending review questions, author notes and tips, an extensive glossary, and the handy CramSheet tear-out: key facts in an easy-to-review format. Powerful Pearson Test Prep practice test software offers hundreds of exam-realistic practice questions, with many customization and reporting features: test yourself in study mode, practice exam mode, or flash card mode. Covers the critical information you'll need to score higher on your ENCOR 350-401 exam! Understand Cisco infrastructure, including Layer 2, Layer 3 (IGPs and BGP), IP services, and enterprise wireless Secure enterprise networks by safeguarding device access, network access, infrastructure, REST APIs, wireless systems, and designing network security Automate networks with Python, JSON, YANG data models, DNA Center, vManage, REST APIs, EEM applets, configuration management, and orchestration Master enterprise network design/architecture, deploy WLANs, compare on-premises and cloud infrastructure; and implement SD-WAN, SD-Access, QoS, and switching Use basic virtualization, virtual pathing, and virtual network extensions

The development of information technology in supply chains has shown that this digital revolution can be a source of performance for enterprises and governments. Among these technologies is blockchain. The application of blockchains in cryptocurrency reduces information security risks and eliminates several processing and transaction fees and allows countries with volatile currencies to have a more stable currency. Blockchain Applications in Cryptocurrency for Technological Evolution features a collection of contributions related to the application of blockchain technology in cryptocurrency. It further explains the ways in which these applications have affected the industry. Covering topics such as crypto mining attacks, data processing architecture, and purchase power, this premier reference source is an excellent resource for business leaders and executives, IT managers, logistics specialists, students and faculty of higher education, librarians, researchers, and academicians.

Artificial intelligence has been utilized in a diverse range of industries as more people and businesses discover its many uses and applications. A current field of study that requires more attention, as there is much opportunity for improvement, is the use of artificial intelligence within literary works and social media analysis. Artificial Intelligence Applications in Literary Works and Social Media presents contemporary developments in the adoption of artificial intelligence in textual analysis of literary works and social media and introduces current approaches, techniques, and practices in data science that are implemented to scrap and analyze text data. This book initiates a new multidisciplinary field that is the combination of artificial intelligence, data science, social science, literature, and social media study. Covering key topics such as opinion mining, sentiment analysis, and machine learning, this reference work is ideal for computer scientists, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.