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| computer science areas of research: Assessing and Responding to the Growth of Computer Science Undergraduate Enrollments National Academies of Sciences, Engineering, and Medicine, Division on Engineering and Physical Sciences, Computer Science and Telecommunications Board, Policy and Global Affairs, Board on Higher Education and Workforce, Committee on the Growth of Computer Science Undergraduate Enrollments, 2018-04-28 The field of computer science (CS) is currently experiencing a surge in undergraduate degree production and course enrollments, which is straining program resources at many institutions and causing concern among faculty and administrators about how best to respond to the rapidly growing demand. There is also significant interest about what this growth will mean for the future of CS programs, the role of computer science in academic institutions, the field as a whole, and U.S. society more broadly. Assessing and Responding to the Growth of Computer Science Undergraduate Enrollments seeks to provide a better understanding of the current trends in computing enrollments in the context of past trends. It examines drivers of the current enrollment surge, relationships between the surge and current and potential gains in diversity in the field, and the potential impacts of responses to the increased demand for computing in higher education, and it considers the likely effects of those responses on students, faculty, and institutions. This report provides recommendations for what institutions of higher education, government agencies, and the private sector can do to respond to the surge and plan for a strong and sustainable future for the field of CS in general, the health of the institutions of higher education, and the prosperity of the nation. |
| computer science areas of research: Handbook of Research on Integrating Computer Science and Computational Thinking in K-12 Education Keengwe, Jared, Wachira, Patrick, 2019-12-13 As technology continues to develop and prove its importance in modern society, certain professions are acclimating. Aspects such as computer science and computational thinking are becoming essential areas of study. Implementing these subject areas into teaching practices is necessary for younger generations to adapt to the developing world. There is a critical need to examine the pedagogical implications of these technological skills and implement them into the global curriculum. The Handbook of Research on Integrating Computer Science and Computational Thinking in K-12 Education is a collection of innovative research on the methods and applications of computer science curriculum development within primary and secondary education. While highlighting topics including pedagogical implications, comprehensive techniques, and teacher preparation models, this book is ideally designed for teachers, IT consultants, curriculum developers, instructional designers, educational software developers, higher education faculty, administrators, policymakers, researchers, and graduate students. |
| computer science areas of research: Stuck in the Shallow End, updated edition Jane Margolis, 2017-03-03 Why so few African American and Latino/a students study computer science: updated edition of a book that reveals the dynamics of inequality in American schools. The number of African Americans and Latino/as receiving undergraduate and advanced degrees in computer science is disproportionately low. And relatively few African American and Latino/a high school students receive the kind of institutional encouragement, educational opportunities, and preparation needed for them to choose computer science as a field of study and profession. In Stuck in the Shallow End, Jane Margolis and coauthors look at the daily experiences of students and teachers in three Los Angeles public high schools: an overcrowded urban high school, a math and science magnet school, and a well-funded school in an affluent neighborhood. They find an insidious “virtual segregation” that maintains inequality. The race gap in computer science, Margolis discovers, is one example of the way students of color are denied a wide range of occupational and educational futures. Stuck in the Shallow End is a story of how inequality is reproduced in America—and how students and teachers, given the necessary tools, can change the system. Since the 2008 publication of Stuck in the Shallow End, the book has found an eager audience among teachers, school administrators, and academics. This updated edition offers a new preface detailing the progress in making computer science accessible to all, a new postscript, and discussion questions (coauthored by Jane Margolis and Joanna Goode). |
| computer science areas of research: Computer Science National Research Council, Division on Engineering and Physical Sciences, Computer Science and Telecommunications Board, Committee on the Fundamentals of Computer Science: Challenges and Opportunities, 2004-10-06 Computer Science: Reflections on the Field, Reflections from the Field provides a concise characterization of key ideas that lie at the core of computer science (CS) research. The book offers a description of CS research recognizing the richness and diversity of the field. It brings together two dozen essays on diverse aspects of CS research, their motivation and results. By describing in accessible form computer science's intellectual character, and by conveying a sense of its vibrancy through a set of examples, the book aims to prepare readers for what the future might hold and help to inspire CS researchers in its creation. |
| computer science areas of research: Computer Science Education Research Sally Fincher, Marian Petre, 2004-01-01 This book provides an overview of how to approach computer science education research from a pragmatic perspective. It represents the diversity of traditions and approaches inherent in this interdisciplinary area, while also providing a structure within which to make sense of that diversity. It provides multiple 'entry points'- to literature, to methods, to topics Part One, 'The Field and the Endeavor', frames the nature and conduct of research in computer science education. Part Two, 'Perspectives and Approaches', provides a number of grounded chapters on particular topics or themes, written by experts in each domain. These chapters cover the following topics: * design * novice misconceptions * programming environments for novices * algorithm visualisation * a schema theory view on learning to program * critical theory as a theoretical approach to computer science education research Juxtaposed and taken together, these chapters indicate just how varied the perspectives and research approaches can be. These chapters, too, act as entry points, with illustrations drawn from published work. |
| computer science areas of research: Computer Science Kyle Kirkland, 2010 Investigates the research and discoveries of computer scientists whose efforts have expanded knowledge of the rapidly changing field of computer science. |
| computer science areas of research: Trends in Functional Programming Volume 6 Marko Van Eekelen, 2005-06-01 This is Volume 7 of Trends in Functional Programming (TFP). It contains a refereed selection of the papers that were presented at TFP 2006: the Seventh Symposium on Trends in Functional Programming. which took place in Nottingham, 19-21 April, 2006. TFP is an international forum for researchers from all functional programming communities spanning the entire width of topics in the field. Its goal is to provide a broad view of current and future trends in functional programming in a lively and friendly setting, thus promoting new research directions related to the field of functional programming and the relationship between functional programming and other fields of computer science. True to the spirit of TFP, the selection of papers in this volume covers a wide range of topics, including dependently typed programming, generic programming, purely functional data structures, function synthesis, declarative debugging, implementation of functional programming languages, and memory management. A particular emerging trend is that of dependently typed programming, reflected by a number of papers in the present selection and by the co-location of TFP and Types 2006. |
| computer science areas of research: Funding a Revolution National Research Council, Computer Science and Telecommunications Board, Committee on Innovations in Computing and Communications: Lessons from History, 1999-02-11 The past 50 years have witnessed a revolution in computing and related communications technologies. The contributions of industry and university researchers to this revolution are manifest; less widely recognized is the major role the federal government played in launching the computing revolution and sustaining its momentum. Funding a Revolution examines the history of computing since World War II to elucidate the federal government's role in funding computing research, supporting the education of computer scientists and engineers, and equipping university research labs. It reviews the economic rationale for government support of research, characterizes federal support for computing research, and summarizes key historical advances in which government-sponsored research played an important role. Funding a Revolution contains a series of case studies in relational databases, the Internet, theoretical computer science, artificial intelligence, and virtual reality that demonstrate the complex interactions among government, universities, and industry that have driven the field. It offers a series of lessons that identify factors contributing to the success of the nation's computing enterprise and the government's role within it. |
| computer science areas of research: Research Directions in Computer Science Albert R. Meyer, John V. Guttag, Ronald L. Rivest, Peter Szolovits, 1991 Research Directions in Computer Science celebrates the twenty-fifth anniversary of the founding of MIT's Project MAC. It covers the full range of ongoing computer science research at the MIT Laboratory for Computer Science and the MIT Artificial Intelligence Laboratory, both of which grew out of the original Project MAC. Leading researchers from the faculties and staffs of the laboratories highlight current research and future activities in multiprocessors and parallel computer architectures, in languages and systems for distributed computing, in intelligent systems (AI) and robotics, in complexity and learning theory, in software methodology, in programming language theory, in software for engineering research and education, and in the relation between computers and economic productivity. ContributorsAbelson, Arvind, Rodney Brooks, David Clark, Fernando Corbato, William Daily, Michael Dertouzos, John Guttag, Berthold K. P. Horn, Barbara Liskov, Albert Meyer, Nicholas Negroponte, Marc Raibert, Ronald Rivest, Michael Sipser, Gerald Sussman, Peter Szolovits, and John Updike |
| computer science areas of research: Collaborative Software Engineering Ivan Mistrík, John Grundy, André van der Hoek, Jim Whitehead, 2010-03-10 Collaboration among individuals – from users to developers – is central to modern software engineering. It takes many forms: joint activity to solve common problems, negotiation to resolve conflicts, creation of shared definitions, and both social and technical perspectives impacting all software development activity. The difficulties of collaboration are also well documented. The grand challenge is not only to ensure that developers in a team deliver effectively as individuals, but that the whole team delivers more than just the sum of its parts. The editors of this book have assembled an impressive selection of authors, who have contributed to an authoritative body of work tackling a wide range of issues in the field of collaborative software engineering. The resulting volume is divided into four parts, preceded by a general editorial chapter providing a more detailed review of the domain of collaborative software engineering. Part 1 is on Characterizing Collaborative Software Engineering, Part 2 examines various Tools and Techniques, Part 3 addresses organizational issues, and finally Part 4 contains four examples of Emerging Issues in Collaborative Software Engineering. As a result, this book delivers a comprehensive state-of-the-art overview and empirical results for researchers in academia and industry in areas like software process management, empirical software engineering, and global software development. Practitioners working in this area will also appreciate the detailed descriptions and reports which can often be used as guidelines to improve their daily work. |
| computer science areas of research: Computer Science and Artificial Intelligence National Research Council, Commission on Physical Sciences, Mathematics, and Applications, Naval Studies Board, Panel on Computer Science and Artificial Intelligence, 1997-06-10 The focus of this report is on artificial intelligence (AI) and human-computer interface (HCI) technology. Observations, conclusions, and recommendations regarding AI and HCI are presented in terms of six grand challenge areas which serve to identify key scientific and engineering issues and opportunities. Chapter 1 presents the panel's definitions of these and related terms. Chapter 2 presents the panel's general observations and recommendations regarding AI and HCI. Finally, Chapter 3 discusses computer science, AI, and HCI in terms of the six selected grand challenge areas and three time horizons, that is, short term (within the next 2 years), midterm (2 to 6 years), and long term (more than 6 years from now) and presents additional recommendations in these areas. |
| computer science areas of research: Handbook of Research on Equity in Computer Science in P-16 Education Keengwe, Jared, Tran, Yune, 2020-11-13 The growing trend for high-quality computer science in school curricula has drawn recent attention in classrooms. With an increasingly information-based and global society, computer science education coupled with computational thinking has become an integral part of an experience for all students, given that these foundational concepts and skills intersect cross-disciplinarily with a set of mental competencies that are relevant in their daily lives and work. While many agree that these concepts should be taught in schools, there are systematic inequities that exist to prevent students from accessing related computer science skills. The Handbook of Research on Equity in Computer Science in P-16 Education is a comprehensive reference book that highlights relevant issues, perspectives, and challenges in P-16 environments that relate to the inequities that students face in accessing computer science or computational thinking and examines methods for challenging these inequities in hopes of allowing all students equal opportunities for learning these skills. Additionally, it explores the challenges and policies that are created to limit access and thus reinforce systems of power and privilege. The chapters highlight issues, perspectives, and challenges faced in P-16 environments that include gender and racial imbalances, population of growing computer science teachers who are predominantly white and male, teacher preparation or lack of faculty expertise, professional development programs, and more. It is intended for teacher educators, K-12 teachers, high school counselors, college faculty in the computer science department, school administrators, curriculum and instructional designers, directors of teaching and learning centers, policymakers, researchers, and students. |
| computer science areas of research: The Computational Beauty of Nature Gary William Flake, 2000-01-27 Gary William Flake develops in depth the simple idea that recurrent rules can produce rich and complicated behaviors. In this book Gary William Flake develops in depth the simple idea that recurrent rules can produce rich and complicated behaviors. Distinguishing agents (e.g., molecules, cells, animals, and species) from their interactions (e.g., chemical reactions, immune system responses, sexual reproduction, and evolution), Flake argues that it is the computational properties of interactions that account for much of what we think of as beautiful and interesting. From this basic thesis, Flake explores what he considers to be today's four most interesting computational topics: fractals, chaos, complex systems, and adaptation. Each of the book's parts can be read independently, enabling even the casual reader to understand and work with the basic equations and programs. Yet the parts are bound together by the theme of the computer as a laboratory and a metaphor for understanding the universe. The inspired reader will experiment further with the ideas presented to create fractal landscapes, chaotic systems, artificial life forms, genetic algorithms, and artificial neural networks. |
| computer science areas of research: Digital Image Warping George Wolberg, 1990-08-10 This best-selling, original text focuses on image reconstruction, real-time texture mapping, separable algorithms, two-pass transforms, mesh warping, and special effects. The text, containing all original material, begins with the history of the field and continues with a review of common terminology, mathematical preliminaries, and digital image acquisition. Later chapters discuss equations for spatial information, interpolation kernels, filtering problems, and fast-warping techniques based on scanline algorithms. |
| computer science areas of research: Advances in Computer Science for Engineering and Education Zhengbing Hu, Ivan Dychka, Sergey Petoukhov, Matthew He, 2022-04-27 This book contains high-quality refereed research papers presented at the Fifth International Conference on Computer Science, Engineering, and Education Applications (ICCSEEA2022), which took place in Kyiv, Ukraine, on February 21–22, 2022, and was organized by the National Technical University of Ukraine Igor Sikorsky Kyiv Polytechnic Institute, National Aviation University, and the International Research Association of Modern Education and Computer Science. State-of-the-art studies in computer science, artificial intelligence, engineering methodologies, genetic coding systems, deep learning with medical applications, and knowledge representation with educational applications are among the topics covered in the book. For academics, graduate students, engineers, management practitioners, and undergraduate students interested in computer science and its applications in engineering and education, this book is a valuable resource. |
| computer science areas of research: Computer Science Education Research Taylor & Francis Group, 2020-06-30 This book provides an overview of how to approach computer science education research from a pragmatic perspective. It represents the diversity of traditions and approaches inherent in this interdisciplinary area, while also providing a structure within which to make sense of that diversity. It provides multiple entry points-to literature, to methods, to topics-inviting readers to explore further for themselves those sub-areas that capture their specific interests. The book indicates the range of motivations, traditions, research design, and techniques in an attempt to provide orientation for someone new to research in this area. Part One, The Field and the Endeavor, frames the nature and conduct of research in computer science education. Part Two, Perspectives and Approaches, provides a number of grounded chapters on particular topics or themes, written by experts in each domain. These chapters cover the following topics: Design; Novice misconceptions; Programming environments for novices; Algorithm visualization; A schema theory view on learning to program; Critical enquiry as a theoretical approach to computer science education research. Juxtaposed and taken together, these chapters indicate just how varied the perspectives and research approaches can be. These chapters, too, act as entry points, with illustrations drawn from published work. Book jacket. |
| computer science areas of research: Formalizing Common Sense John McCarthy, 1998 Extending over a period of 30 years, this is a collection of papers written by John McCarthy on artificial intelligence. They range from informal surveys written for a general audience to technical discussions of challenging research problems that should be of interest to specialists. |
| computer science areas of research: Writing for Computer Science Justin Zobel, 2004-06-03 A complete update to a classic, respected resource Invaluable reference, supplying a comprehensive overview on how to undertake and present research |
| computer science areas of research: Computer Science in Sport Arnold Baca, 2014-10-03 Computers are a fundamentally important tool in sport science research, sports performance analysis and, increasingly, in coaching and education programmes in sport. This book defines the field of ‘sport informatics’, explaining how computer science can be used to solve sport-related problems, in both research and applied aspects. Beginning with a clear explanation of the functional principles of hardware and software, the book examines the key functional areas in which computer science is employed in sport, including: knowledge discovery and database development data acquisition, including devices for measuring performance data motion tracking and analysis systems modelling and simulation match analysis systems e-learning and multimedia in sports education Bridging the gap between theory and practice, this book is important reading for any student, researcher or practitioner working in sport science, sport performance analysis, research methods in sport, applied computer science or informatics. |
| computer science areas of research: Advances in Computer Science for Engineering and Education III Zhengbing Hu, Sergey Petoukhov, Ivan Dychka, Matthew He, 2020-08-05 This book comprises high-quality refereed research papers presented at the Third International Conference on Computer Science, Engineering and Education Applications (ICCSEEA2020), held in Kyiv, Ukraine, on 21–22 January 2020, organized jointly by National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, National Aviation University, and the International Research Association of Modern Education and Computer Science. The topics discussed in the book include state-of-the-art papers in computer science, artificial intelligence, engineering techniques, genetic coding systems, deep learning with its medical applications, and knowledge representation with its applications in education. It is an excellent source of references for researchers, graduate students, engineers, management practitioners, and undergraduate students interested in computer science and their applications in engineering and education. |
| computer science areas of research: Deep Learning for Coders with fastai and PyTorch Jeremy Howard, Sylvain Gugger, 2020-06-29 Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala |
| computer science areas of research: Research in Computer Sciences Hans H. Zschirnt, 1965 |
| computer science areas of research: Study and Research Guide in Computer Science Wolfgang Tölle, Jason Yasner, Michael Pieper, 2012-12-06 Computer science departments at universities in the U.S.A. are world renowned. This handy reference guide gives detailed profiles of 40 of the best known among them. The profiles are organized in a uniform layout to present basic information, faculty, curriculum, courses for graduate students, affiilated institutions, facilities, research areas, funding, selected projects, and collaborations. Two full alphabetical listings of professors are included, one giving their universities and the other their research areas. The guide will be indispensible for anyone - student or faculty, not only in the U.S.A. - interested in research and education in computer science in the U.S.A. |
| computer science areas of research: Infinite Words Dominique Perrin, Jean-Éric Pin, 2004-02-18 Infinite Words is an important theory in both Mathematics and Computer Sciences. Many new developments have been made in the field, encouraged by its application to problems in computer science. Infinite Words is the first manual devoted to this topic. Infinite Words explores all aspects of the theory, including Automata, Semigroups, Topology, Games, Logic, Bi-infinite Words, Infinite Trees and Finite Words. The book also looks at the early pioneering work of Büchi, McNaughton and Schützenberger. Serves as both an introduction to the field and as a reference book. Contains numerous exercises desgined to aid students and readers. Self-contained chapters provide helpful guidance for lectures. |
| computer science areas of research: INSPEC Thesaurus 1979 Institution of Electrical Engineers, 1978 |
| computer science areas of research: The Cambridge Handbook of Computing Education Research Sally A. Fincher, Anthony V. Robins, 2019-02-21 This Handbook describes the extent and shape of computing education research today. Over fifty leading researchers from academia and industry (including Google and Microsoft) have contributed chapters that together define and expand the evidence base. The foundational chapters set the field in context, articulate expertise from key disciplines, and form a practical guide for new researchers. They address what can be learned empirically, methodologically and theoretically from each area. The topic chapters explore issues that are of current interest, why they matter, and what is already known. They include discussion of motivational context, implications for practice, and open questions which might suggest future research. The authors provide an authoritative introduction to the field which is essential reading for policy makers, as well as both new and established researchers. |
| computer science areas of research: Digital Biology Peter J. Bentley, 2010-05-11 Imagine a future world where computers can create universes -- digital environments made from binary ones and zeros. Imagine that within these universes there exist biological forms that reproduce, grow, and think. Imagine plantlike forms, ant colonies, immune systems, and brains, all adapting, evolving, and getting better at solving problems. Imagine if our computers became greenhouses for a new kind of nature. Just think what digital biology could do for us. Perhaps it could evolve new designs for us, think up ways to detect fraud using digital neurons, or solve scheduling problems with ants. Perhaps it could detect hackers with immune systems or create music from the patterns of growth of digital seashells. Perhaps it would allow our computers to become creative and inventive. Now stop imagining. digital biology is an intriguing glimpse into the future of technology by one of the most creative thinkers working in computer science today. As Peter J. Bentley explains, the next giant step in computing technology is already under way as computer scientists attempt to create digital universes that replicate the natural world. Within these digital universes, we will evolve solutions to problems, construct digital brains that can learn and think, and use immune systems to trap and destroy computer viruses. The biological world is the model for the next generation of computer software. By adapting the principles of biology, computer scientists will make it possible for computers to function as the natural world does. In practical terms, this will mean that we will soon have smart devices, such as houses that will keep the temperature as we like it and automobiles that will start only for drivers they recognize (through voice recognition or other systems) and that will navigate highways safely and with maximum fuel efficiency. Computers will soon be powerful enough and small enough that they can become part of clothing. Digital agents will be able to help us find a bank or restaurant in a city that we have never visited before, even as we walk through the airport. Miniature robots may even be incorporated into our bodies to monitor our health. Digital Biology is also an exploration of biology itself from a new perspective. We must understand how nature works in its most intimate detail before we can use these same biological processes inside our computers. Already scientists engaged in this work have gained new insights into the elegant simplicity of the natural universe. This is a visionary book, written in accessible, nontechnical language, that explains how cutting-edge computer science will shape our world in the coming decades. |
| computer science areas of research: Introduction to High Performance Computing for Scientists and Engineers Georg Hager, Gerhard Wellein, 2010-07-02 Written by high performance computing (HPC) experts, Introduction to High Performance Computing for Scientists and Engineers provides a solid introduction to current mainstream computer architecture, dominant parallel programming models, and useful optimization strategies for scientific HPC. From working in a scientific computing center, the author |
| computer science areas of research: Fundamental Concepts in Computer Science Erol Gelenbe, 2009 This book presents fundamental contributions to computer science as written and recounted by those who made the contributions themselves. As such, it is a highly original approach to a OC living historyOCO of the field of computer science. The scope of the book is broad in that it covers all aspects of computer science, going from the theory of computation, the theory of programming, and the theory of computer system performance, all the way to computer hardware and to major numerical applications of computers. |
| computer science areas of research: How to Solve it by Computer Dromey, 2008 |
| computer science areas of research: Evolving the High Performance Computing and Communications Initiative to Support the Nation's Information Infrastructure National Research Council, Computer Science and Telecommunications Board, Committee to Study High Performance Computing and Communications: Status of a Major Initiative, 1995-03-27 Maintaining the United States' strong lead in information technology will require continued federal support of research in this area, most of which is currently funded under the High Performance Computing and Communications Initiative (HPCCI). The Initiative has already accomplished a great deal and should be continued. This book provides 13 major recommendations for refining both HPCCI and support of information technology research in general. It also provides a good overview of the development of HPCC technologies. |
| computer science areas of research: Java Programming Ralph Bravaco, Shai Simonson, 2009-02-01 Java Programming, From The Ground Up, with its flexible organization, teaches Java in a way that is refreshing, fun, interesting and still has all the appropriate programming pieces for students to learn. The motivation behind this writing is to bring a logical, readable, entertaining approach to keep your students involved. Each chapter has a Bigger Picture section at the end of the chapter to provide a variety of interesting related topics in computer science. The writing style is conversational and not overly technical so it addresses programming concepts appropriately. Because of the flexibile organization of the text, it can be used for a one or two semester introductory Java programming class, as well as using Java as a second language. The text contains a large variety of carefully designed exercises that are more effective than the competition. |
| computer science areas of research: Big Data and Social Science Ian Foster, Rayid Ghani, Ron S. Jarmin, Frauke Kreuter, Julia Lane, 2016-08-10 Both Traditional Students and Working Professionals Acquire the Skills to Analyze Social Problems. Big Data and Social Science: A Practical Guide to Methods and Tools shows how to apply data science to real-world problems in both research and the practice. The book provides practical guidance on combining methods and tools from computer science, statistics, and social science. This concrete approach is illustrated throughout using an important national problem, the quantitative study of innovation. The text draws on the expertise of prominent leaders in statistics, the social sciences, data science, and computer science to teach students how to use modern social science research principles as well as the best analytical and computational tools. It uses a real-world challenge to introduce how these tools are used to identify and capture appropriate data, apply data science models and tools to that data, and recognize and respond to data errors and limitations. For more information, including sample chapters and news, please visit the author's website. |
| computer science areas of research: Research Methods of Computer Science Ehtiram Raza Khan, |
| computer science areas of research: Knowledge Discovery and Data Mining: Challenges and Realities Zhu, Xingquan, Davidson, Ian, 2007-04-30 This book provides a focal point for research and real-world data mining practitioners that advance knowledge discovery from low-quality data; it presents in-depth experiences and methodologies, providing theoretical and empirical guidance to users who have suffered from underlying low-quality data. Contributions also focus on interdisciplinary collaborations among data quality, data processing, data mining, data privacy, and data sharing--Provided by publisher. |
| computer science areas of research: The Future of Computer Science Research in the U.S. United States. Congress. House. Committee on Science, 2005 |
| computer science areas of research: Computer Organization and Microprogramming Yaohan Chu, 1972 Computer design language; Some organizations; Microprogramming; Serial arithmetic units; A fixed-point arithmetic unit; A floating-point arithmetic unit. |
| computer science areas of research: Computing with New Resources Cristian S. Calude, Rūsiņš Freivalds, Iwama Kazuo, 2014-12-09 Professor Jozef Gruska is a well known computer scientist for his many and broad results. He was the father of theoretical computer science research in Czechoslovakia and among the first Slovak programmers in the early 1960s. Jozef Gruska introduced the descriptional complexity of grammars, automata, and languages, and is one of the pioneers of parallel (systolic) automata. His other main research interests include parallel systems and automata, as well as quantum information processing, transmission, and cryptography. He is co-founder of four regular series of conferences in informatics and two in quantum information processing and the Founding Chair (1989-96) of the IFIP Specialist Group on Foundations of Computer Science. |
| computer science areas of research: The Mythical Man-month Frederick P. Brooks (Jr.), 1975 The orderly Sweet-Williams are dismayed at their son's fondness for the messy pastime of gardening. |
| computer science areas of research: Advances in computer science, engineering and applications David C. Wyld, Jan Zizka, Dhinaharan Nagamalai, |
Computer - Wikipedia
A computer is a machine that can be programmed to automatically carry out sequences of arithmetic or logical operations (computation). Modern digital electronic computers can …
Computer | Definition, History, Operating Systems, & Facts
A computer is a programmable device for processing, storing, and displaying information. Learn more in this article about modern digital electronic computers and their design, constituent …
What is a Computer?
Feb 6, 2025 · What is a Computer? A computer is a programmable device that stores, retrieves, and processes data. The term "computer" was originally given to humans (human computers) …
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What is a Computer? - GeeksforGeeks
Apr 7, 2025 · A computer is an electronic device that processes, stores, and executes instructions to perform tasks. It includes key components such as the CPU (Central Processing Unit), RAM …
Computer Basics: What is a Computer? - GCFGlobal.org
What is a computer? A computer is an electronic device that manipulates information, or data. It has the ability to store, retrieve, and process data. You may already know that you can use a …
What is a Computer? (Definition & Meaning) - Webopedia
Oct 9, 2024 · A computer is a programmable machine that responds to specific instructions and uses hardware and software to perform tasks. Different types of computers, including …
Computer - Simple English Wikipedia, the free encyclopedia
A computer is a machine that uses electronics to input, process, store, and output data. Data is information such as numbers, words, and lists. Input of data means to read information from a …
Laptop & Desktop Computers - Staples
Buy the computer that fits your exact needs. Choose from laptops, desktops PCs, notebooks, and accessories. Invest in a quality computer for work or personal use.
What is Computer? Definition, Characteristics and Classification
Aug 7, 2024 · A computer is an electronic device wherein we need to input raw data to be processed with a set of programs to produce a desirable output. Computers have the ability to …
Computer - Wikipedia
A computer is a machine that can be programmed to automatically carry out sequences of arithmetic or logical operations (computation). Modern digital electronic computers can …
Computer | Definition, History, Operating Systems, & Facts
A computer is a programmable device for processing, storing, and displaying information. Learn more in this article about modern digital electronic computers and their design, constituent …
What is a Computer?
Feb 6, 2025 · What is a Computer? A computer is a programmable device that stores, retrieves, and processes data. The term "computer" was originally given to humans (human computers) …
Micro Center - Computer & Electronics Retailer - Shop Now
Shop Micro Center for electronics, PCs, laptops, Apple products, and much more. Enjoy in-store pickup, top deals, and expert same-day tech support.
What is a Computer? - GeeksforGeeks
Apr 7, 2025 · A computer is an electronic device that processes, stores, and executes instructions to perform tasks. It includes key components such as the CPU (Central Processing Unit), RAM …
Computer Basics: What is a Computer? - GCFGlobal.org
What is a computer? A computer is an electronic device that manipulates information, or data. It has the ability to store, retrieve, and process data. You may already know that you can use a …
What is a Computer? (Definition & Meaning) - Webopedia
Oct 9, 2024 · A computer is a programmable machine that responds to specific instructions and uses hardware and software to perform tasks. Different types of computers, including …
Computer - Simple English Wikipedia, the free encyclopedia
A computer is a machine that uses electronics to input, process, store, and output data. Data is information such as numbers, words, and lists. Input of data means to read information from a …
Laptop & Desktop Computers - Staples
Buy the computer that fits your exact needs. Choose from laptops, desktops PCs, notebooks, and accessories. Invest in a quality computer for work or personal use.
What is Computer? Definition, Characteristics and Classification
Aug 7, 2024 · A computer is an electronic device wherein we need to input raw data to be processed with a set of programs to produce a desirable output. Computers have the ability to …
