Content Computing

Welcome to the Advanced Workshop on Content Computing 2004. The focus of this workshop was "Content Computing". It emphasized research areas that facilitate efficient, appropriate dissemination of content to users with the necessary access rights. We use the word "content" instead of "information" or "data" because we want to cover not only raw data but also presentation quality. The fast growth of the Internet has already made it the key infrastructure for information dissemination,education,business and entertainment. While the client-server model has been the most widely adopted paradigm for the WWW, the desire to provide more value-added services in the delivery layer has led to the concept of an active network, where content-driven, intelligent computation will be performed to provide quality-of-service for content presentation and best-?t client demand. These value-added services typically aim to enhance information security, provide pervasive Internet access, and improve application robustness, system/network performance, knowledge extraction,etc. They are realized by incorporating sophisticated mechanisms at the delivery layer,which is transparent to the content providers and Web surfers. Consequently, the notion of "Content Computing" has emerged. Content computing is a new paradigm for coordinating distributed systems and intelligent networks, based on a peer-to-peer model and with value-added processing of the application-specific contents at the - livery layer. This paradigm is especially useful to pervasive lightweight client devices such as mobile and portable end-user terminals with a wide variation of hardware/software configurations. This year, the workshop was held in Zhenjiang, Jiangsu, China. We received 194 high-quality papers from 11 regions, namely PR China, Korea, Singapore, Japan, United States, Canada, Australia, Germany, Taiwan, Italy, and Hong Kong. Totally, 62 papers were accepted and presented in the workshop.

Basic Category Theory for Computer Scientists provides a straightforward presentation of the basic constructions and terminology of category theory, including limits, functors, natural transformations, adjoints, and cartesian closed categories. Category theory is a branch of pure mathematics that is becoming an increasingly important tool in theoretical computer science, especially in programming language semantics, domain theory, and concurrency, where it is already a standard language of discourse. Assuming a minimum of mathematical preparation, Basic Category Theory for Computer Scientists provides a straightforward presentation of the basic constructions and terminology of category theory, including limits, functors, natural transformations, adjoints, and cartesian closed categories. Four case studies illustrate applications of category theory to programming language design, semantics, and the solution of recursive domain equations. A brief literature survey offers suggestions for further study in more advanced texts. Contents Tutorial • Applications • Further Reading

This title gives students an integrated and rigorous picture of applied computer science, as it comes to play in the construction of a simple yet powerful computer system.

An in-depth overview of an emerging field that brings together high-performance computing, big data processing, and deep lLearning. Over the last decade, the exponential explosion of data known as big data has changed the way we understand and harness the power of data. The emerging field of high-performance big data computing, which brings together high-performance computing (HPC), big data processing, and deep learning, aims to meet the challenges posed by large-scale data processing. This book offers an in-depth overview of high-performance big data computing and the associated technical issues, approaches, and solutions. The book covers basic concepts and necessary background knowledge, including data processing frameworks, storage systems, and hardware capabilities; offers a detailed discussion of technical issues in accelerating big data computing in terms of computation, communication, memory and storage, codesign, workload characterization and benchmarking, and system deployment and management; and surveys benchmarks and workloads for evaluating big data middleware systems. It presents a detailed discussion of big data computing systems and applications with high-performance networking, computing, and storage technologies, including state-of-the-art designs for data processing and storage systems. Finally, the book considers some advanced research topics in high-performance big data computing, including designing high-performance deep learning over big data (DLoBD) stacks and HPC cloud technologies.

Faced with a full-blown crisis, a growing number of journalists are engaging in seemingly unjournalistic practices such as creating and maintaining databases, handling algorithms, or designing online applications. “Data journalists” claim that these approaches help the profession demonstrate greater objectivity and fulfill its democratic mission. In their view, computational methods enable journalists to better inform their readers, more closely monitor those in power, and offer deeper analysis. In Computing the News, Sylvain Parasie examines how data journalists and news organizations have navigated the tensions between traditional journalistic values and new technologies. He traces the history of journalistic hopes for computing technology and contextualizes the surge of data journalism in the twenty-first century. By importing computational techniques and ways of knowing new to journalism, news organizations have come to depend on a broader array of human and nonhuman actors. Parasie draws on extensive fieldwork in the United States and France, including interviews with journalists and data scientists as well as a behind-the-scenes look at several acclaimed projects in both countries. Ultimately, he argues, fulfilling the promise of data journalism requires the renewal of journalistic standards and ethics. Offering an in-depth analysis of how computing has become part of the daily practices of journalists, this book proposes ways for journalism to evolve in order to serve democratic societies.

An introduction to computer engineering for babies. Learn basic logic gates with hands on examples of buttons and an output LED.

This book unravels the mystery of Big Data computing and its power to transform business operations. The approach it uses will be helpful to any professional who must present a case for realizing Big Data computing solutions or to those who could be involved in a Big Data computing project. It provides a framework that enables business and technical managers to make optimal decisions necessary for the successful migration to Big Data computing environments and applications within their organizations.

This textbook raises thought-provoking questions regarding our rapidly-evolving computing technologies, highlighting the need for a strong ethical framework in our computer science education. Ethics in Computing offers a concise introduction to this topic, distilled from the more expansive Ethical and Social Issues in the Information Age. Features: introduces the philosophical framework for analyzing computer ethics; describes the impact of computer technology on issues of security, privacy and anonymity; examines intellectual property rights in the context of computing; discusses such issues as the digital divide, employee monitoring in the workplace, and health risks; reviews the history of computer crimes and the threat of cyberbullying; provides coverage of the ethics of AI, virtualization technologies, virtual reality, and the Internet; considers the social, moral and ethical challenges arising from social networks and mobile communication technologies; includes discussion questions and exercises.

The papers in this volume comprise the refereed proceedings of the the First International Conference on Computer and Computing Technologies in Ag- culture (CCTA 2007), in Wuyishan, China, 2007. This conference is organized by China Agricultural University, Chinese Society of Agricultural Engineering and the Beijing Society for Information Technology in Agriculture. The purpose of this conference is to facilitate the communication and cooperation between institutions and researchers on theories, methods and implementation of computer science and information technology. By researching information technology development and the - sources integration in rural areas in China, an innovative and effective approach is expected to be explored to promote the technology application to the development of modern agriculture and contribute to the construction of new countryside. The rapid development of information technology has induced substantial changes and impact on the development of China’s rural areas. Western thoughts have exerted great impact on studies of Chinese information technology devel- ment and it helps more Chinese and western scholars to expand their studies in this academic and application area. Thus, this conference, with works by many prominent scholars, has covered computer science and technology and information development in China’s rural areas; and probed into all the important issues and the newest research topics, such as Agricultural Decision Support System and Expert System, GIS, GPS, RS and Precision Farming, CT applications in Rural Area, Agricultural System Simulation, Evolutionary Computing, etc.