The clinical use of Artificial Intelligence (AI) in radiation oncology is in its infancy. However, it is certain that AI is capable of making radiation oncology more precise and personalized with improved outcomes. Radiation oncology deploys an array of state-of-the-art technologies for imaging, treatment, planning, simulation, targeting, and quality assurance while managing the massive amount of data involving therapists, dosimetrists, physicists, nurses, technologists, and managers. AI consists of many powerful tools which can process a huge amount of inter-related data to improve accuracy, productivity, and automation in complex operations such as radiation oncology.This book offers an array of AI scientific concepts, and AI technology tools with selected examples of current applications to serve as a one-stop AI resource for the radiation oncology community. The clinical adoption, beyond research, will require ethical considerations and a framework for an overall assessment of AI as a set of powerful tools.30 renowned experts contributed to sixteen chapters organized into six sections: Define the Future, Strategy, AI Tools, AI Applications, and Assessment and Outcomes. The future is defined from a clinical and a technical perspective and the strategy discusses lessons learned from radiology experience in AI and the role of open access data to enhance the performance of AI tools. The AI tools include radiomics, segmentation, knowledge representation, and natural language processing. The AI applications discuss knowledge-based treatment planning and automation, AI-based treatment planning, prediction of radiotherapy toxicity, radiomics in cancer prognostication and treatment response, and the use of AI for mitigation of error propagation. The sixth section elucidates two critical issues in the clinical adoption: ethical issues and the evaluation of AI as a transformative technology.

With exponentially increasing amounts of data accumulating in real-time, there is no reason why one should not turn data into a competitive advantage. While machine learning, driven by advancements in artificial intelligence, has made great strides, it has not been able to surpass a number of challenges that still prevail in the way of better success. Such limitations as the lack of better methods, deeper understanding of problems, and advanced tools are hindering progress. Challenges and Applications of Data Analytics in Social Perspectives provides innovative insights into the prevailing challenges in data analytics and its application on social media and focuses on various machine learning and deep learning techniques in improving practice and research. The content within this publication examines topics that include collaborative filtering, data visualization, and edge computing. It provides research ideal for data scientists, data analysts, IT specialists, website designers, e-commerce professionals, government officials, software engineers, social media analysts, industry professionals, academicians, researchers, and students.

In recent years, artificial intelligence (AI) has drawn significant attention with respect to its applications in several scientific fields, varying from big data handling to medical diagnosis. A tremendous transformation has taken place with the emerging application of AI. AI can provide a wide range of solutions to address many challenges in civil engineering. Artificial Intelligence and Machine Learning Techniques for Civil Engineering highlights the latest technologies and applications of AI in structural engineering, transportation engineering, geotechnical engineering, and more. It features a collection of innovative research on the methods and implementation of AI and machine learning in multiple facets of civil engineering. Covering topics such as damage inspection, safety risk management, and information modeling, this premier reference source is an essential resource for engineers, government officials, business leaders and executives, construction managers, students and faculty of higher education, librarians, researchers, and academicians.

The representation of abstract data and ideas can be a difficult and tedious task to handle when learning new concepts; however, the advances in emerging technology have allowed for new methods of representing such conceptual data. Information Visualization Techniques in the Social Sciences and Humanities is a critical scholarly resource that examines the application of information visualization in the social sciences and humanities. Featuring coverage on a broad range of topics such as social network analysis, complex systems, and visualization aesthetics, this book is geared towards professionals, students, and researchers seeking current research on information visualization.

Although the transition between the first three industrial revolutions took more than a century, Industry 4.0 is progressing quickly. The emergence of digitalization has been rapid thanks to the development of cutting-edge technologies. Though we are witnessing this rapid technological decentralization and interconnectivity at present, organizations and researchers are already discussing Industry 5.0 where full integration of the human side of business and intelligent systems is expected. In this scenario, it is essential to look forward to such strategic workplaces that allow a combination of humans and technology to assure a high degree of automation merged with the cognitive skills of business leaders. Managing Technology Integration for Human Resources in Industry 5.0 provides insights into the impact of the Industrial Revolution 4.0 on human resources. It provides insights for both industry and academia to assist them in teaching and training the next generation leaders through universities and corporate training. Covering topics such as business performance, human technology integration, and digitalization, this premier reference source is an essential resource for human resource managers, IT managers, organizational executives and leaders, entrepreneurs, students and educators of higher education, librarians, researchers, and academicians.

First designed to generate personalized recommendations to users in the 90s, recommender systems apply knowledge discovery techniques to users' data to suggest information, products, and services that best match their preferences. In recent decades, we have seen an exponential increase in the volumes of data, which has introduced many new challenges. Divided into two volumes, this comprehensive set covers recent advances, challenges, novel solutions, and applications in big data recommender systems. Volume 1 contains 14 chapters addressing foundations, algorithms and architectures, approaches for big data, and trust and security measures. Volume 2 covers a broad range of application paradigms for recommender systems over 22 chapters.

Modern businesses are on the lookout for ventures that boost their profits and marketability. Certain new and innovative technological advances can help enterprises accomplish their ambitious goals while providing detailed information to assess all aspects of the business. Global Virtual Enterprises in Cloud Computing Environments is a collection of innovative studies on business processes, procedures, methods, strategy, management thinking, and utilization of technology in cloud computing environments. While highlighting topics including international business strategy, virtual reality, and intellectual capital, this book is ideally designed for corporate executives, research scholars, and students pursuing courses in the areas of management and big data applications seeking current research on effective open innovation strategies in global business.

The growing presence of social media and computer use has caused significant changes to community engagement. With the ubiquity of these technologies, there is increasing engagement in social and political policies and changes. Online Communities as Agents of Change and Social Movements is a pivotal reference source for the latest research on relevant theoretical and practical frameworks regarding online communities and social media as agents of social and political change. Featuring extensive coverage on relevant areas such as computer use, online engagement, and collective action, this publication is an ideal resource for researchers, academics, practitioners, and students in the fields of social psychology, social network analysis, media studies, information systems, and political science.

This book explains the concepts, history, and implementation of IT infrastructures. Although many of books can be found on each individual infrastructure building block, this is the first book to describe all of them: datacenters, servers, networks, storage, operating systems, and end user devices. The building blocks described in this book provide functionality, but they also provide the non-functional attributes performance, availability, and security. These attributes are explained on a conceptual level in separate chapters, and specific in the chapters about each individual building block. Whether you need an introduction to infrastructure technologies, a refresher course, or a study guide for a computer science class, you will find that the presented building blocks and concepts provide a solid foundation for understanding the complexity of today's IT infrastructures. This book can be used as part of IT architecture courses based on the IS 2010.4 curriculum.

Applications of Computer Vision in Fashion and Textiles provides a systematic and comprehensive discussion of three key areas that are taking advantage of developments in computer vision technology, namely textile defect detection and quality control, fashion recognition and 3D modeling, and 2D and 3D human body modeling for improving clothing fit. It introduces the fundamentals of computer vision techniques for fashion and textile applications, also reviewing computer vision techniques for textile quality control, including chapters on wavelet transforms, Gibor filters, Fourier transforms, and neural network techniques. Final sections cover recognition, modeling, retrieval technologies and advanced human shape modeling techniques. The book is essential reading for scientists and researchers working in the field of fashion production, quality assurance, product development, textiles, fashion supply chain managers, R&D professionals and managers in the textile industry.

Change Detection and Image Time Series Analysis 2 presents supervised machine-learning-based methods for temporal evolution analysis by using image time series associated with Earth observation data. Chapter 1 addresses the fusion of multisensor, multiresolution and multitemporal data. It proposes two supervised solutions that are based on a Markov random field: the first relies on a quad-tree and the second is specifically designed to deal with multimission, multifrequency and multiresolution time series. Chapter 2 provides an overview of pixel based methods for time series classification, from the earliest shallow learning methods to the most recent deep-learning-based approaches. Chapter 3 focuses on very high spatial resolution data time series and on the use of semantic information for modeling spatio-temporal evolution patterns. Chapter 4 centers on the challenges of dense time series analysis, including pre processing aspects and a taxonomy of existing methodologies. Finally, since the evaluation of a learning system can be subject to multiple considerations, Chapters 5 and 6 offer extensive evaluations of the methodologies and learning frameworks used to produce change maps, in the context of multiclass and/or multilabel change classification issues.

This organizational history relates the role of the National Science Foundation (NSF) in the development of modern computing. Drawing upon new and existing oral histories, extensive use of NSF documents, and the experience of two of the authors as senior managers, this book describes how NSF's programmatic activities originated and evolved to become the primary source of funding for fundamental research in computing and information technologies. The book traces how NSF's support has provided facilities and education for computing usage by all scientific disciplines, aided in institution and professional community building, supported fundamental research in computer science and allied disciplines, and led the efforts to broaden participation in computing by all segments of society. Today, the research and infrastructure facilitated by NSF computing programs are significant economic drivers of American society and industry. For example, NSF supported work that led to the first widely-used web browser, Netscape; sponsored the creation of algorithms at the core of the Google search engine; facilitated the growth of the public Internet; and funded research on the scientific basis for countless other applications and technologies. NSF has advanced the development of human capital and ideas for future advances in computing and its applications. This account is the first comprehensive coverage of NSF's role in the extraordinary growth and expansion of modern computing and its use. It will appeal to historians of computing, policy makers and leaders in government and academia, and individuals interested in the history and development of computing and the NSF.

Thanks to the digital revolution, even a traditional discipline like philology has been enjoying a renaissance within academia and beyond. Decades of work have been producing groundbreaking results, raising new research questions and creating innovative educational resources. This book describes the rapidly developing state of the art of digital philology with a focus on Ancient Greek and Latin, the classical languages of Western culture. Contributions cover a wide range of topics about the accessibility and analysis of Greek and Latin sources. The discussion is organized in five sections concerning open data of Greek and Latin texts; catalogs and citations of authors and works; data entry, collection and analysis for classical philology; critical editions and annotations of sources; and finally linguistic annotations and lexical databases. As a whole, the volume provides a comprehensive outline of an emergent research field for a new generation of scholars and students, explaining what is reachable and analyzable that was not before in terms of technology and accessibility.

Digital transformation is a revolutionary technology that will play a vital role in major industries, including global governments. These administrations are taking the initiative to incorporate digital programs with their objective being to provide digital infrastructure as a basic utility for every citizen, provide on demand services with superior governance, and empower their citizens digitally. However, security and privacy are major barriers in adopting these mechanisms, as organizations and individuals are concerned about their private and financial data. Impact of Digital Transformation on Security Policies and Standards is an essential research book that examines the policies, standards, and mechanisms for security in all types of digital applications and focuses on blockchain and its imminent impact on financial services in supporting smart government, along with bitcoin and the future of digital payments. Highlighting topics such as cryptography, privacy management, and e-government, this book is ideal for security analysts, data scientists, academicians, policymakers, security professionals, IT professionals, government officials, finance professionals, researchers, and students.