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Sunday, 3 July 2011

Computer science

Computer science


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Computer science deals with the theoretical foundations of information and computation, and with practical techniques for their implementation and application.
Utah teapot representing computer graphicsMicrosoft Tastenmaus mouse representing human-computer interactionComputer science or computing science (abbreviated CS) is the study of the theoretical foundations of information and computation and of practical techniques for their implementation and application in computer systems.[1][2] Computer scientists invent algorithmic processes that create, describe, and transform information and formulate suitable abstractions to model complex systems.
Computer science has many sub-fields; some, such as computational complexity theory, study the properties of computational problems, while others, such as computer graphics, emphasize the computation of specific results. Still others focus on the challenges in implementing computations. For example, programming language theory studies approaches to describe computations, while computer programming applies specific programming languages to solve specific computational problems, and human-computer interaction focuses on the challenges in making computers and computations useful, usable, and universally accessible to humans.
The general public sometimes confuses computer science with careers that deal with computers (such as information technology), or think that it relates to their own experience of computers, which typically involves activities such as gaming, web-browsing, and word-processing. However, the focus of computer science is more on understanding the properties of the programs used to implement software such as games and web-browsers, and using that understanding to create new programs or improve existing ones

History

History

The early foundations of what would become computer science predate the invention of the modern digital computer. Machines for calculating fixed numerical tasks, such as the abacus, have existed since antiquity. Wilhelm Schickard designed the first mechanical calculator in 1623, but did not complete its construction.[4] Blaise Pascal designed and constructed the first working mechanical calculator, the Pascaline, in 1642. Charles Babbage designed a difference engine and then a general-purpose Analytical Engine in Victorian times,[5] for which Ada Lovelace wrote a manual. Because of this work she is regarded today as the world's first programmer.[6] Around 1900, punched card machines were introduced.
During the 1940s, as newer and more powerful computing machines were developed, the term computer came to refer to the machines rather than their human predecessors.[7] As it became clear that computers could be used for more than just mathematical calculations, the field of computer science broadened to study computation in general. Computer science began to be established as a distinct academic discipline in the 1950s and early 1960s. The world's first computer science degree program, the Cambridge Diploma in Computer Science, began at the University of Cambridge Computer Laboratory in 1953. The first computer science degree program in the United States was formed at Purdue University in 1962.[10] Since practical computers became available, many applications of computing have become distinct areas of study in their own right.

Major achievements

Major achievements

The German military used the Enigma machine (shown here) during World War II for communication they thought to be secret. The large-scale decryption of Enigma traffic at Bletchley Park was an important factor that contributed to Allied victory in WWII.[12]
Despite its short history as a formal academic discipline, computer science has made a number of fundamental contributions to science and society. These include:
  • The start of the "digital revolution," which includes the current Information Age and the Internet.[13]
  • A formal definition of computation and computability, and proof that there are computationally unsolvable and intractable problems.[14]
  • The concept of a programming language, a tool for the precise expression of methodological information at various levels of abstraction.[15]
  • In cryptography, breaking the Enigma machine was an important factor contributing to the Allied victory in World War II.[12]
  • Scientific computing enabled practical evaluation of processes and situations of great complexity, as well as experimentation entirely by software. It also enabled advanced study of the mind, and mapping of the human genome became possible with the Human Genome Project.[13] Distributed computing projects such as Folding@home explore protein folding.
  • Algorithmic trading has increased the efficiency and liquidity of financial markets by using artificial intelligence, machine learning, and other statistical and numerical techniques on a large scale.[16]
  • Image synthesis, including video by computing individual video frames.[citation needed]
  • Human language processing, including practical speech-to-text conversion and automated translation of languages[citation needed]
  • Simulation of various processes, including computational fluid dynamics, physical, electrical, and electronic systems and circuits, as well as societies and social situations (notably war games) along with their habitats, among many others. Modern computers enable optimization of such designs as complete aircraft. Notable in electrical and electronic circuit design are SPICE as well as software for physical realization of new (or modified) designs. The latter includes essential design software for integrated circuits

Computer security and cryptography

Computer security and cryptography

Computer security is a branch of computer technology, whose objective includes protection of information from unauthorized access, disruption, or modification while maintaining the accessibility and usability of the system for its intended users. Cryptography is the practice and study of hiding (encryption) and therefore deciphering (decryption) information. Modern cryptography is largely related to computer science, for many encryption and decryption algorithms are based on their computational complexity.

Computational science

Computational science (or scientific computing) is the field of study concerned with constructing mathematical models and quantitative analysis techniques and using computers to analyse and solve scientific problems. In practical use, it is typically the application of computer simulation and other forms of computation to problems in various scientific disciplines.
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Numerical analysis Computational physics Computational chemistry Bioinformatics

Information science

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Information Retrieval Knowledge Representation Natural Language Processing Human–computer interaction

Computer architecture and engineering




Computer architecture and engineering

Computer architecture, or digital computer organization, is the conceptual design and fundamental operational structure of a computer system. It focuses largely on the way by which the central processing unit performs internally and accesses addresses in memory. The field often involves disciplines of computer engineering and electrical engineering, selecting and interconnection hardware components to create computers that meet functional, performance, and cost goals.
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Digital logic Microarchitecture Multiprocessing
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Operating systems Computer networks Databases Computer security
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Ubiquitous computing Systems architecture Compiler design Programming languages

Computer graphics and visualization

Computer graphics is the study of digital visual contents, and involves syntheses and manipulations of image data. The study is connected to many other fields in computer science, including computer vision, image processing, and computational geometry, and are heavily applied in the fields of special effects and video games.

Artificial intelligence

Artificial intelligence

This branch of computer science aims to create synthetic systems which solve computational problems, reason and/or communicate like animals and humans do. This theoretical and applied subfield requires a very rigorous and integrated expertise in multiple subject areas such as applied mathematics, logic, semiotics, electrical engineering, philosophy of mind, neurophysiology, and social intelligence which can be used to advance the field of intelligence research or be applied to other subject areas which require computational understanding and modelling such as in finance or the physical sciences. This field started in full earnest when Alan Turing, the pioneer of computer science and artificial intelligence, proposed the Turing Test for the purpose of answering the ultimate question... "Can computers think ?".
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Machine Learning Computer vision Image Processing Pattern Recognition
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Cognitive Science Data Mining Evolutionary Computation Information Retrieval
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Knowledge Representation Natural Language Processing Robotics

Applied computer science

Applied computer science

Despite its name, a significant amount of computer science does not involve the study of computers themselves. Because of this, several alternative names have been proposed. Certain departments of major universities prefer the term computing science, to emphasize precisely that difference. Danish scientist Peter Naur suggested the term datalogy, to reflect the fact that the scientific discipline revolves around data and data treatment, while not necessarily involving computers. The first scientific institution to use the term was the Department of Datalogy at the University of Copenhagen, founded in 1969, with Peter Naur being the first professor in datalogy. The term is used mainly in the Scandinavian countries. Also, in the early days of computing, a number of terms for the practitioners of the field of computing were suggested in the Communications of the ACMturingineer, turologist, flow-charts-man, applied meta-mathematician, and applied epistemologist.[22] Three months later in the same journal, comptologist was suggested, followed next year by hypologist.[23] The term computics has also been suggested.[24] In continental Europe, names such as informatique (French), Informatik (German) or informatika (Slavic languages), derived from information and possibly mathematics or automatic, are more common than names derived from computer/computation.
Renowned computer scientist Edsger Dijkstra once stated: "Computer science is no more about computers than astronomy is about telescopes." The design and deployment of computers and computer systems is generally considered the province of disciplines other than computer science. For example, the study of computer hardware is usually considered part of computer engineering, while the study of commercial computer systems and their deployment is often called information technology or information systems. However, there has been much cross-fertilization of ideas between the various computer-related disciplines. Computer science research has also often crossed into other disciplines, such as philosophy, cognitive science, linguistics, mathematics, physics, statistics, and economics.
Computer science is considered by some to have a much closer relationship with mathematics than many scientific disciplines, with some observers saying that computing is a mathematical science.[8] Early computer science was strongly influenced by the work of mathematicians such as Kurt Gödel and Alan Turing, and there continues to be a useful interchange of ideas between the two fields in areas such as mathematical logic, category theory, domain theory, and algebra.
The relationship between computer science and software engineering is a contentious issue, which is further muddied by disputes over what the term "software engineering" means, and how computer science is defined. David Parnas, taking a cue from the relationship between other engineering and science disciplines, has claimed that the principal focus of computer science is studying the properties of computation in general, while the principal focus of software engineering is the design of specific computations to achieve practical goals, making the two separate but complementary disciplines.[25]
The academic, political, and funding aspects of computer science tend to depend on whether a department formed with a mathematical emphasis or with an engineering emphasis. Computer science departments with a mathematics emphasis and with a numerical orientation consider alignment with computational science. Both types of departments tend to make efforts to bridge the field educationally if not across all research.