Association for Computing Machinery – förlag

This introductory textbook teaches the simple development of geospatial applications based on the principles and software tools of geospatial data science. It introduces a new generation of geospatial technologies that have emerged from the development of the Semantic Web and the linked data paradigm, and shows how data scientists can use them to build environmental applications easily.

Geospatial data science is the science of collecting, organizing, analyzing, and visualizing geospatial data. Since around 2010, there has been extensive work in the area of geospatial data science using semantic technologies and linked data, from researchers in the areas of the Semantic Web, Geospatial Databases and Geoinformatics. The main results of this research have been the publication of the OGC standard GeoSPARQL and the implementation of a number of linked data tools supporting this standard. Up to now, there has been no textbook that enables someone to teach this material to undergraduate or graduate students.

The material of the book is developed in a tutorial style and it is appropriate for an introductory course on the subject. This can be an advanced undergraduate course or a graduate course offered by Computer Science or GIS faculty. It is a hands-on approach and every chapter contains exercises that help students master the material.

The book is accompanied by a Web site: https://ai.di.uoa.gr/geospatial-data-science-book/index.html where solutions to some of the exercises are given together with supplementary material such as datasets and code. Most of the material in the book has been tried in the “Knowledge Technologies” course taught by the first author in the Department of Informatics and Telecommunications of the National and Kapodistrian University of Athens since 2012.

This introductory textbook teaches the simple development of geospatial applications based on the principles and software tools of geospatial data science. It introduces a new generation of geospatial technologies that have emerged from the development of the Semantic Web and the linked data paradigm, and shows how data scientists can use them to build environmental applications easily.

Geospatial data science is the science of collecting, organizing, analyzing, and visualizing geospatial data. Since around 2010, there has been extensive work in the area of geospatial data science using semantic technologies and linked data, from researchers in the areas of the Semantic Web, Geospatial Databases and Geoinformatics. The main results of this research have been the publication of the OGC standard GeoSPARQL and the implementation of a number of linked data tools supporting this standard. Up to now, there has been no textbook that enables someone to teach this material to undergraduate or graduate students.

The material of the book is developed in a tutorial style and it is appropriate for an introductory course on the subject. This can be an advanced undergraduate course or a graduate course offered by Computer Science or GIS faculty. It is a hands-on approach and every chapter contains exercises that help students master the material.

The book is accompanied by a Web site: https://ai.di.uoa.gr/geospatial-data-science-book/index.html where solutions to some of the exercises are given together with supplementary material such as datasets and code. Most of the material in the book has been tried in the “Knowledge Technologies” course taught by the first author in the Department of Informatics and Telecommunications of the National and Kapodistrian University of Athens since 2012.

Professor Stephen A. Cook is a pioneer of the theory of computational complexity. His work on NP-completeness and the P vs. NP problem remains a central focus of this field. Cook won the 1982 Turing Award for “his advancement of our understanding of the complexity of computation in a significant and profound way.” This volume includes a selection of seminal papers embodying the work that led to this award, exemplifying Cook’s synthesis of ideas and techniques from logic and the theory of computation including NP-completeness, proof complexity, bounded arithmetic, and parallel and space-bounded computation. These papers are accompanied by contributed articles by leading researchers in these areas, which convey to a general reader the importance of Cook’s ideas and their enduring impact on the research community. The book also contains biographical material, Cook’s Turing Award lecture, and an interview. Together these provide a portrait of Cook as a recognized leader and innovator in mathematics and computer science, as well as a gentle mentor and colleague.

Professor Stephen A. Cook is a pioneer of the theory of computational complexity. His work on NP-completeness and the P vs. NP problem remains a central focus of this field. Cook won the 1982 Turing Award for “his advancement of our understanding of the complexity of computation in a significant and profound way.” This volume includes a selection of seminal papers embodying the work that led to this award, exemplifying Cook’s synthesis of ideas and techniques from logic and the theory of computation including NP-completeness, proof complexity, bounded arithmetic, and parallel and space-bounded computation. These papers are accompanied by contributed articles by leading researchers in these areas, which convey to a general reader the importance of Cook’s ideas and their enduring impact on the research community. The book also contains biographical material, Cook’s Turing Award lecture, and an interview. Together these provide a portrait of Cook as a recognized leader and innovator in mathematics and computer science, as well as a gentle mentor and colleague.

When Sir Tim Berners-Lee first proposed the foundations of the World Wide Web at CERN in 1989, his manager called it “vague, but exciting.” How things have changed since then! Twenty-six years later, Berners-Lee won the ACM Turing Award “for inventing the World Wide Web, the first Web browser, and the fundamental protocols and algorithms allowing the Web to scale.” This book is a compilation of articles on the original ideas of a true visionary and the subsequent research and development work he has led, helping to realize the Web’s full potential. It is intended for readers interested in the Web’s original technical development, how it has changed over time, and the social impacts of the Web as steered by Berners-Lee since the very beginning.

The book covers Berners-Lee’s development of the key protocols, naming schemes, and markup languages that led to his “world wide web” program and ultimately to the Web as we know it today. His early efforts were refined as Web technology spread around the world, and he was further guided by the work of the World Wide Web Consortium, which he founded and still directs. He was instrumental in the conceptualization and realization of the Semantic Web, a field that is gaining momentum in the age of big data and knowledge graphs; was a driving force for the field of Web Science, a new and growing research area dedicated to the study of both the engineering and the impacts of the Web; and he continues to innovate through his research work at MIT on open and decentralized information. Berners-Lee is also known for his contributions to keeping the Web open and ubiquitous via his work with the World Wide Web Foundation, the UK’s Open Data Institute and his recent call for a crowdsourced magna carta for the Web. This book will help the reader to understand how Sir Tim’s invention of the World Wide Web has revolutionized not just Computer Science, but global society itself.

When Sir Tim Berners-Lee first proposed the foundations of the World Wide Web at CERN in 1989, his manager called it “vague, but exciting.” How things have changed since then! Twenty-six years later, Berners-Lee won the ACM Turing Award “for inventing the World Wide Web, the first Web browser, and the fundamental protocols and algorithms allowing the Web to scale.” This book is a compilation of articles on the original ideas of a true visionary and the subsequent research and development work he has led, helping to realize the Web’s full potential. It is intended for readers interested in the Web’s original technical development, how it has changed over time, and the social impacts of the Web as steered by Berners-Lee since the very beginning.

The book covers Berners-Lee’s development of the key protocols, naming schemes, and markup languages that led to his “world wide web” program and ultimately to the Web as we know it today. His early efforts were refined as Web technology spread around the world, and he was further guided by the work of the World Wide Web Consortium, which he founded and still directs. He was instrumental in the conceptualization and realization of the Semantic Web, a field that is gaining momentum in the age of big data and knowledge graphs; was a driving force for the field of Web Science, a new and growing research area dedicated to the study of both the engineering and the impacts of the Web; and he continues to innovate through his research work at MIT on open and decentralized information. Berners-Lee is also known for his contributions to keeping the Web open and ubiquitous via his work with the World Wide Web Foundation, the UK’s Open Data Institute and his recent call for a crowdsourced magna carta for the Web. This book will help the reader to understand how Sir Tim’s invention of the World Wide Web has revolutionized not just Computer Science, but global society itself.

This book introduces and provides an analysis of the basic concepts of algorithms, data, and computation and discusses the role of algorithms in ruling and shaping our world. It provides a clear understanding of the power and impact on humanity of the pervasive use of algorithms.

From Algorithms to Thinking Machines combines a layman’s approach with a well-founded scientific description to discuss both principles and applications of algorithms, Big Data, and machine intelligence. The book provides a clear and deep description of algorithms, software systems, data-driven applications, machine learning, and data science concepts, as well as the evolution and impact of artificial intelligence.

After introducing computing concepts, the book examines the relationships between algorithms and human work, discussing how jobs are being affected and how computers and software programs are influencing human life and the labor sphere. Topics such as value alignment, collective intelligence, Big Data impact, automatic decision methods, social control, and political uses of algorithms are illustrated and discussed at length without excessive technical detail. Issues related to how corporations, governments, and autocratic regimes are exploiting algorithms and machine intelligence methods to influence people, laws, and markets are extensively addressed. Ethics principles in software programming and human value insertion into artificial intelligence algorithms are also discussed.

This book demonstrates the need for and the value of interdisciplinary research in addressing important societal challenges associated with the widespread use of algorithmic decision-making. Algorithms are increasingly being used to make decisions in various domains such as criminal justice, medicine, and employment. While algorithmic tools have the potential to make decision-making more accurate, consistent, and transparent, they pose serious challenges to societal interests. For example, they can perpetuate discrimination, cause representational harm, and deny opportunities.

The Societal Impacts of Algorithmic Decision-Making presents several contributions to the growing body of literature that seeks to respond to these challenges, drawing on techniques and insights from computer science, economics, and law. The author develops tools and frameworks to characterize the impacts of decision-making and incorporates models of behavior to reason about decision-making in complex environments. These technical insights are leveraged to deepen the qualitative understanding of the impacts of algorithms on problem domains including employment and lending.

The social harms of algorithmic decision-making are far from being solved. While easy solutions are not presented here, there are actionable insights for those who seek to deploy algorithms responsibly. The research presented within this book will hopefully contribute to broader efforts to safeguard societal values while still taking advantage of the promise of algorithmic decision-making.

This book demonstrates the need for and the value of interdisciplinary research in addressing important societal challenges associated with the widespread use of algorithmic decision-making. Algorithms are increasingly being used to make decisions in various domains such as criminal justice, medicine, and employment. While algorithmic tools have the potential to make decision-making more accurate, consistent, and transparent, they pose serious challenges to societal interests. For example, they can perpetuate discrimination, cause representational harm, and deny opportunities.

The Societal Impacts of Algorithmic Decision-Making presents several contributions to the growing body of literature that seeks to respond to these challenges, drawing on techniques and insights from computer science, economics, and law. The author develops tools and frameworks to characterize the impacts of decision-making and incorporates models of behavior to reason about decision-making in complex environments. These technical insights are leveraged to deepen the qualitative understanding of the impacts of algorithms on problem domains including employment and lending.

The social harms of algorithmic decision-making are far from being solved. While easy solutions are not presented here, there are actionable insights for those who seek to deploy algorithms responsibly. The research presented within this book will hopefully contribute to broader efforts to safeguard societal values while still taking advantage of the promise of algorithmic decision-making.

There are significant financial and legal implications for ensuring design correctness and safety in autonomous systems. This book introduces new verification and synthesis algorithms to provide certifiable trusts for real-world autonomous systems. On the theoretical front, the techniques are armed with soundness, precision, and relative completeness guarantees. On the experimental side, this book shows that techniques can be successfully applied on a sequence of real-world problems, including a suite of Toyota engine control modules verified for the first time, satellite control systems, and autonomous driving and ADAS-based maneuvers.

Insights throughout the book provide a level of assurance that can be provided by formal methods for today’s autonomous systems. Verification and synthesis for typical models of real-world autonomous systems are challenging due to their high dimensionality, nonlinearities, and nondeterministic and hybrid nature. In addressing these challenges, several chapters present data-driven algorithmic verification via reachability analysis of complex hybrid systems as well as controller synthesis for dynamic systems under disturbance.

The book includes the first algorithm for over-approximating reach sets of general nonlinear models with locally optimal tightness guarantees as well as algorithms to find correct-by-construction controllers for nonlinear dynamical systems. It is written for researchers in the corporate world, academia, government, and practitioners in autonomous systems.

Spatial gems are computational techniques for processing spatial data. This book, a follow-up to the first Spatial Gems volume, is a further collection of techniques contributed by leading research experts. Although these approaches were developed by their authors as part of larger research projects, the gems represent fundamental solutions that are generically applicable to many different problems. Our goal is to expose these useful techniques that are not yet in textbooks and often buried inside technical research papers to share them with software developers, graduate students, professors, and professional researchers.

This book provides a comprehensive study of the many ways to interact with computers and computerized devices. An “interaction technique” starts when the user performs an action that causes an electronic device to respond, and includes the direct feedback from the device to the user. Examples include physical buttons and switches, on-screen menus and scrollbars operated by a mouse, touchscreen widgets, gestures such as flick-to-scroll, text entry on computers and touchscreens, interactions with conversational agents such as Apple Siri, Google Assistant, Amazon Alexa, and Microsoft Cortana, and adaptations of all of these for people with disabilities.

Beginning with a history of the invention and development of interaction techniques, the author goes on to describe the various approaches in use today, continuing with a discussion of the state-of-the-art research that is driving the development of novel approaches for the future. The book features summaries of interviews with some of the original inventors of interaction techniques, including David Canfield Smith (the desktop and icons), Larry Tesler (copy/paste), Ted Selker (IBM TrackPoint), Loren Brichter (Pull-to-Refresh), and many others. The author also describes how to use, model, implement, and evaluate new interaction techniques.

Pick, Click, Flick! is written for anyone interested in interaction techniques, including computer scientists and designers working on human-computer interaction, as well as implementers and consumers who want to understand and get the most out of their digital devices.

In the last decade, deep learning and word embeddings have made significant impacts on information retrieval (IR) by adding techniques based in neural networks and language models. At the same time, certain search modalities such as neural IR and conversational search have become more popular. This book, written by international academic and industry experts, brings the field up to date with detailed discussions of these new approaches and techniques. The book is organized in three sections: Foundations, Adaptations and Concerns, and Verticals.

Under Foundations, we address topics that form the basic structure of any modern IR system, including recommender systems. These new techniques are developed to augment indexing, retrieval, and ranking. Neural IR, recommender systems, evaluation, query-driven functionality, and knowledge graphs are covered in this section.

IR systems need to adapt to specific user characteristics and preferences, and techniques that were considered too niche a few years ago are now a matter of system design consideration. The Adaptations and Concerns section covers the following topics: conversational search, cross-language retrieval, temporal extraction and retrieval, bias in retrieval systems, and privacy in search.

While web search engines are the most popular information access point, there are cases where specific verticals provide a better experience in terms of content and relevance. The Verticals section describes eCommerce, professional search, personal collections, music retrieval, and biomedicine as examples.

This is a comprehensive history of computer graphics in Hollywood cinema. As the first such work of its kind, it is an essential reference for anyone interested in the history of cinema, visual effects, or computer graphics, and the industries of which they are a part.

The book begins with a look at the history behind the calculation of images, from weaving to screen imaging, and the faux computer graphics used in movies before real computer graphics were available or affordable. Next, the author examines the rise of computer graphics and computer-animated films, and the gradual introduction of computer-generated imagery into the cinema. The narrative moves chronologically through the development of computer-generated animation and its use both for cartoonlike imagery and for photorealistic imagery. The author discusses behind-the-scenes uses of computer graphics in the film industry, and how these uses have impacted the kinds of imagery made and the technologies by which they are made. The book also looks at how computer animation is combined with approaches such as procedural generation and simulation, and the ways in which computers automate imagery.

Throughout the book, the histories of individuals, companies, films, and computer graphics techniques are explored in detail, as well as changes in the visual effects (VFX) industry itself over time.

Calculated Imagery: A History of Computer Graphics in Hollywood Cinema is for anyone interested in how CG changed the VFX industry, film history, and filmmaking overall, and the people, companies, and techniques that made it happen.

This is a comprehensive history of computer graphics in Hollywood cinema. As the first such work of its kind, it is an essential reference for anyone interested in the history of cinema, visual effects, or computer graphics, and the industries of which they are a part.

The book begins with a look at the history behind the calculation of images, from weaving to screen imaging, and the faux computer graphics used in movies before real computer graphics were available or affordable. Next, the author examines the rise of computer graphics and computer-animated films, and the gradual introduction of computer-generated imagery into the cinema. The narrative moves chronologically through the development of computer-generated animation and its use both for cartoonlike imagery and for photorealistic imagery. The author discusses behind-the-scenes uses of computer graphics in the film industry, and how these uses have impacted the kinds of imagery made and the technologies by which they are made. The book also looks at how computer animation is combined with approaches such as procedural generation and simulation, and the ways in which computers automate imagery.

Throughout the book, the histories of individuals, companies, films, and computer graphics techniques are explored in detail, as well as changes in the visual effects (VFX) industry itself over time.

Calculated Imagery: A History of Computer Graphics in Hollywood Cinema is for anyone interested in how CG changed the VFX industry, film history, and filmmaking overall, and the people, companies, and techniques that made it happen.

This book outlines a methodology to develop formally verified Just-in-Time compilers. Just-in-Time compilation is a technique to execute programs, where execution is interleaved with optimizations of the program itself. These compilers often produce fast executions, so much so that their use has grown greatly for dynamic programming languages. Most modern web browsers today use Just-in-Time compilation to speed up the execution of the JavaScript programs they execute.

However, the techniques used in Just-in-Time compilers can be particularly complex. This complexity can be a source of bugs and vulnerabilities. How can you make sure that your Just-in-Time compiler is bug-free? For traditional ahead-of-time compilers, many techniques have been developed to prevent compilation bugs. One such technique is formally verified compilation, where the compiler itself comes with proof that the semantics of the compiled program correspond to the semantics of the source program. But Just-in-Time compilers are more recent, less understood, and have been the target of far fewer verification efforts.

To bring formal verification to Just-in-Time compilation, the book identifies a set of specific verification challenges and presents novel solutions for each of them. Such challenges include dynamic optimizations, speculative optimizations, deoptimizations, and the interleaving of interpretation and machine code generation. The author repurposes proof techniques from formally verified ahead-of-time compilers like CompCert. Following this methodology, readers can develop Just-in-Time compilers and formally prove that they behave as prescribed by the semantics of the program they execute. All proofs within the book have been mechanized in the Coq proof assistant.

This book outlines a methodology to develop formally verified Just-in-Time compilers. Just-in-Time compilation is a technique to execute programs, where execution is interleaved with optimizations of the program itself. These compilers often produce fast executions, so much so that their use has grown greatly for dynamic programming languages. Most modern web browsers today use Just-in-Time compilation to speed up the execution of the JavaScript programs they execute.

However, the techniques used in Just-in-Time compilers can be particularly complex. This complexity can be a source of bugs and vulnerabilities. How can you make sure that your Just-in-Time compiler is bug-free? For traditional ahead-of-time compilers, many techniques have been developed to prevent compilation bugs. One such technique is formally verified compilation, where the compiler itself comes with proof that the semantics of the compiled program correspond to the semantics of the source program. But Just-in-Time compilers are more recent, less understood, and have been the target of far fewer verification efforts.

To bring formal verification to Just-in-Time compilation, the book identifies a set of specific verification challenges and presents novel solutions for each of them. Such challenges include dynamic optimizations, speculative optimizations, deoptimizations, and the interleaving of interpretation and machine code generation. The author repurposes proof techniques from formally verified ahead-of-time compilers like CompCert. Following this methodology, readers can develop Just-in-Time compilers and formally prove that they behave as prescribed by the semantics of the program they execute. All proofs within the book have been mechanized in the Coq proof assistant.

This book offers a compelling discussion of the digital dreams that have come true, their often unintended side effects (nightmares), and what must be done to counteract the nightmares. It is intended as an impetus to further conversation not only in homes and workplaces, but in academic courses and even legislative debates. Equally importantly, the book is a presentation of what digital technology professionals need to know about these topics and the actions they should undertake individually and in support of other citizens, societal initiatives, and government. The author begins by introducing the amazing progress made in digital technologies over the past 80 years. Pioneering engineers dreamed of potential uses of technology through their writing and technical achievements, further inspiring thousands of researchers to bring the dreams to life, and to dream new dreams as well. The second part of the book describes the myriad adverse side effects and unanticipated challenges that arose as those dreams were pursued and achieved. Examples include rampant misinformation on social media, ransomware, autonomous weapons, and the premature use of AI before it is reliable and safe.

The book closes with a positive call to action, outlining ways to address the challenges through ethical career choices, careful analysis, thoughtful design, research, citizen engagement, legislation/regulation, and careful consideration of how bad actors may use technology. Readers of Digital Dreams Have Become Nightmares should become more knowledgeable, wiser, and also cautiously optimistic, determined to affect positive changes through their design, creation, and use of technology.