The Georgia Institute of Technology’s Georgia Electronic Design Center (GEDC) has developed a complementary metal oxide semiconductor (CMOS) chip capable of transmitting 60 GHz digital radio-frequency signals. GEDC researchers say the technology could lead to the rapid transfer of high-definition movies and other large files from a PC to a cell phone, virtually wireless desktop computers and data centers, wireless home DVD systems, in-store kiosks that can download movies to mobile devices, and the ability to move gigabytes of photos or video files from a camera to a PC almost instantly. “We believe this new standard represents a major step forward,” says GEDC director Joy Laskar. “Consumers could see products capable of ultra-fast short-range data transfer within two or three years.” GEDC’s chip provides multi-gigabit wireless transmissions by combining 60 GHz CMOS digital radio capabilities and multi-gigabit signal processing in an ultra-compact device. Laskar says the new technology represents the highest level of integration for 60 GHz wireless single-chip solutions. “Multi-gigabit technology definitely has major promise for new consumer and IT applications,” says Microsoft Research’s Darko Kirovski. GEDC researchers say they have already achieved high data transfer speeds that could lead to unprecedented short-range wireless speeds, including 15 Gbps at 1 meter, 10 Gbps at 2 meters, and 5 Gbps at 5 meters.

Full article here

Math and science must become more popular with young children if they are to take advantage of the employment opportunities as the world becomes smarter, writes Rick R. Qualman, IBM’s senior state executive for Florida. The retirement of Baby Boomers already means that between 250,000 and 500,000 IT jobs could go unfilled over the next five years. Also, fewer students are enrolling in computer science programs, and test scores in math and science at the middle school level are below the national average. Florida schools will not be able to solve the problem on their own, considering the state’s budget woes. “We, as parents, business professionals, and community leaders must also take action, encouraging young people to excel in math and science and supporting those who have expressed an interest in such careers with mentors and resources to help them stay on course and succeed,” Qualman says. He says that starting Transition to Teaching programs would be a way for companies to prepare employees to become math or science teachers when they retire. “Our children can succeed in tomorrow’s smart world–if they are prepared,” Qualman says.

View full article here

For more information please visit: www.cpccci.com

With the competition for tech jobs heating up as a result of the economic downturn, having an effective résumé is almost becoming a prerequisite for finding the right job. Unfortunately, many IT workers fail to optimize their résumés for the way that recruiters sort through potential candidates. In today’s hiring environment, a well-written résumé can make all the difference in standing out in a crowd of other IT professionals. With that in mind, the article provides five essential tips for writing the perfect tech résumé, including advice on everything from which technical details to include, to how to position new certifications, to how to blend a mix of business and technology experiences.

According to recruiters, the primary problem with most technical résumés is that they are too long and too detailed. Résumés should only be two pages maximum and should summarize technical accomplishments, not provide in-depth detail about them. Moreover, too many resumes include an objective at the top or bottom. Companies want to know what you can do for them, not what you want from them. When outlining your accomplishments, try to keep a balance between those related to business and technology. A prior job description should start with a general statement similar to a summary bullet, and then proceed to technical details that show technology’s impact on business.

When deciding what to include on your resume, remember that resumes must reach a number of audiences. Most tech résumés go through a number of filters, from keyword search to a nontechnical hiring manager or a recruiter to a CTO or a tech-savvy CIO who is looking to fill a specific need. The challenge is to write a résumé that speaks to these different readers. To get past the search filter, you’ll need to do a little research on jobs in demand during a recession and related job descriptions. The goal is to find the acronyms and keyword phrases that the software will be looking for, such as names of popular certifications.

View full article here: http://www.cio.com/article/472366/_Tips_for_an_Outstanding_IT_Resume?source=nlt_ciocareers

Given this need to bolster their core businesses, many organizations are experiencing greater demand for systems engineers, application developers, and database pros who can help make that happen. They are placing particular emphasis on individuals who will be able to move innovative projects forward once the economic uncertainty lifts. Potential areas of growth include mobile technology and electronic medical records. Generally speaking, companies will be looking to align themselves with the new priorities of the Obama Administration, especially when it comes to technology policy.

While most companies are focusing on ways to retain experienced tech talent, there also are promising opportunities for new graduates. Among top jobs for new grads are network systems and data communications analysts, who have average beginning pay of approximately $40,000. Another good career option for college grads between the ages of 20 to 24 is computer support specialist, with an average beginning salary of $25,950. In addition, both of these jobs have solid long-term prospects, according to recent U.S. Department of Labor data.

Read full article here: http://www.techcareers.com/articles/i/ad4028/blogs/information-technology/career-experts-predict-2009-should-be-good-for-tech-pros.htm

The U.S. Department of Homeland Security (DHS) plans to quadruple its investment in research dedicated to securing the Border Gateway Protocol (BGP) by adding digital signatures to router communications. DHS says the research initiative, dubbed BGPSEC, will prevent routing hijackings and accidental misconfigurations of routing data. DHS expects BGPSEC to take several years to develop prototypes and standards and at least four years before deployment. Experts have praised the accelerated effort, as BGP is one of the Internet’s most vulnerable faults. “The reason BGP problems are so serious is that they attack the Internet infrastructure, rather than particular hosts,” says Columbia University professor of computer science Steve Bellovin. “This is why it is a DHS-type of problem.” Arbor Networks’ Danny McPherson says BGP is one of the largest threats on the Internet. “There doesn’t exist a formally verifiable source for who owns what address space on the Internet, and absent that you can’t really validate the routing system,” McPherson says. The extra funding should enable the DHS to develop ways of authenticating Internet Protocol (IP) address allocations and router announcements on how to reach blocks of IP addresses. DHS funding for router security will rise to approximately $2.5 million per year beginning this year, up from about $600,000 per year over the last three years, says Douglas Maughan, DHS program manager for cybersecurity research and development.

View full article here: http://www.networkworld.com/news/2009/011509-bgp.html

Today, the term information technology has ballooned to encompass many aspects of computing and technology, and the term has become very recognizable. The information technology umbrella can be quite large, covering many fields. Many people from the different field enjoy the improvement of the ICTs. IT professionals perform a variety of duties that range from installing applications to designing complex computer networks and information databases. A few of the duties that IT professionals perform may include data management, networking, engineering computer hardware, database and software design, as well as the management and administration of entire systems.

When computer and communications technologies are combined, the result is information technology, or “infotech”. Information Technology (IT) is a general term that describes any technology that helps to produce, manipulate, store, communicate, and/or disseminate information. Presumably, when speaking of Information Technology (IT) as a whole, it is noted that the use of computers and information are associated.

The term Information Technology (IT) was coined by Jim Domsic of Michigan in November 1981.[citation needed] Domsic created the term to modernize the outdated phrase “data processing”. Domsic at the time worked as a computer manager for an automotive related industry.

In recent years ABET and the ACM have collaborated to form accreditation and curriculum standards for degrees in Information Technology as a distinct field of study separate from both Computer Science and Information Systems. SIGITE is the ACM working group for defining these standards.

References

* Adelman, C. (2000). A Parallel Postsecondary Universe: The Certification System in Information Technology. Washington, D.C.: U.S. Department of Education.
* Allen, T., and M.S. Morton, eds. 1994. Information Technology and the Corporation of the 1990s. New York: Oxford University Press.
* Shelly, Gary, Cashman, Thomas, Vermaat, Misty, and Walker, Tim. (1999). Discovering Computers 2000: Concepts for a Connected World. Cambridge, Massachusetts: Course Technology.
* Webster, Frank, and Robins, Kevin. (1986). Information Technology—A Luddite Analysis. Norwood, NJ: Ablex.

Major information technology companies
Cellular hardware
Audiovox · Alcatel-Lucent · Apple · Sony Ericsson · HTC · Kyocera · LG · Motorola · Samsung · Nokia · Palm · Qualcomm · RIM
Conglomerates
Bull · GE · HCL · Hitachi · LG · Panasonic (JVC, Matsushita) · NCR · News Corp. · Philips · Samsung · Siemens (Infineon, Qimonda) · Sony · Thomson · Toshiba · Vivendi · Wipro Infotech · Yamaha
3G Networks
3Com · Alcatel-Lucent · Allied Telesis · Avaya · Ericsson · Foundry · Huawei · Nokia Siemens · ZTE
Dot-coms
Amazon · AOL · eBay · Expedia · Google · Monster Worldwide · Yahoo! · Ask
Semiconductors (General)
AMD · Analog Devices · ATI Technologies · Fairchild · Freescale · Infineon · Intel · Micron · National · NVIDIA · NXP · Renesas · Rohm · Skyworks · STMicroelectronics · Texas Instruments · TSMC
Electronics manufacturers
Celestica · Elcoteq · Flextronics · Foxconn · Jabil · Kimball · Plexus · Quanta · Sanmina-SCI · SMTC
IT services
Accenture · ACS · Atos Origin · Avanade · BearingPoint · Booz Allen Hamilton · BT · Bull · Capgemini · CGI · Cognizant · CSC · Deloitte · EDS · First Data · Fujitsu · Getronics · HCL Tech · i-flex · IBM · Indra · Infosys · Keane · Logica · Neusoft · PA · Perot · SAIC · Sapient · Satyam · Steria · Syntel · TCS · ThoughtWorks · Tieto · Titan · Unisys · Virtusa · Wipro · Xansa
Server and Network Hardware
Bull · Cisco Systems · Dell · Juniper Networks · IBM · Hewlett-Packard · Sun Microsystems
Display / DTV
Acer · BenQ · LG · Samsung · Sharp · Sony · Toshiba · Trident Microsystems · ViewSonic
Software
Adobe · Apple · Bull · CA · Compuware · Corel · IBM · Idealab · Intuit · Microsoft · Oracle · PTC · Red Hat · SAP · Sun Microsystems
Gaming
Activision Blizzard · Capcom · EA · Infogrames · Microsoft · Nintendo · Sega · Sony Computer Entertainment · Take-Two Interactive · Valve Corporation
Computer system
Acer · Asus · Apple · Bull · Dell · Hewlett-Packard · Lenovo · NEC · Panasonic · Sony · Toshiba
Security
AVG Technologies · ESET · F-Secure · Kaspersky Lab · McAfee · SOFTWIN · Sophos · Symantec · Trend Micro

Computer science (or computing science) 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][3]. Computer Science is frequently described as the systematic study of algorithmic processes that describe and transform information; the fundamental question underlying computer science is, ‘What can be (efficiently) automated?’^[4]. Computer science has many sub-fields; some, such as computer graphics, emphasize the computation of specific results, while others, such as computational complexity theory, study the properties of computational problems. Still others focus on the challenges in implementing computations. For example, programming language theory studies approaches to describing 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 people.

The general public sometimes confuses computer science with other vocational areas that deal with computers, such as information technology (IT), 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.^[5]

History

Main article: History of computer science

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 built the first mechanical calculator in 1623.^[6] Charles Babbage designed a difference engine in Victorian times (between 1837 and 1901)^[7] helped by Ada Lovelace.^[8] Around 1900, the IBM corporation sold punch-card machines.^[9] However, all of these machines were constrained to perform a single task, or at best some subset of all possible tasks.

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. 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 1960s, with the creation of the first computer science departments and degree programs.^[4] Since practical computers became available, many applications of computing have become distinct areas of study in their own right.

Although many initially believed it impossible that computers themselves could actually be a scientific field of study, in the late fifties it gradually became accepted among the greater academic population.^[10] It is the now well-known IBM brand that formed part of the computer science revolution during this time. IBM (short for International Business Machines) released the IBM 704 and later the IBM 709 computers, which were widely used during the exploration period of such devices. “Still, working with the IBM [computer] was frustrating…if you had misplaced as much as one letter in one instruction, the program would crash, and you would have to start the whole process over again”.^[10] During the late 1950s, the computer science discipline was very much in its developmental stages, and such issues were commonplace.

Time has seen significant improvements in the usability and effectiveness of computer science technology. Modern society has seen a significant shift from computers being used solely by experts or professionals to a more widespread user base.

Major achievements

Please help improve this section by expanding it. Further information might be found on the talk page. (June 2008)

German military used the Enigma machine 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.^[11]

Despite its relatively short history as a formal academic discipline, computer science has made a number of fundamental contributions to science and society. These include:

• Started the Digital Revolution, which led to the current Information Age and the Internet.^[12]
• A formal definition of computation and computability, and proof that there are computationally unsolvable and intractable problems.^[13]
• The concept of a programming language, a tool for the precise expression of methodological information at various levels of abstraction.^[14]
• In cryptography, breaking the Enigma machine was an important factor contributing to the Allied victory in World War II.^[11]
• Scientific computing enabled advanced study of the mind, and mapping the human genome became possible with Human Genome Project.^[12] 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.^[15]

Fields of computer science

As a discipline, computer science spans a range of topics from theoretical studies of algorithms and the limits of computation to the practical issues of implementing computing systems in hardware and software.^[16][17] The Computer Sciences Accreditation Board (CSAB) – which is made up of representatives of the Association for Computing Machinery (ACM), the Institute of Electrical and Electronics Engineers Computer Society, and the Association for Information Systems – identifies four areas that it considers crucial to the discipline of computer science: theory of computation, algorithms and data structures, programming methodology and languages, and computer elements and architecture. In addition to these four areas, CSAB also identifies fields such as software engineering, artificial intelligence, computer networking and communication, database systems, parallel computation, distributed computation, computer-human interaction, computer graphics, operating systems, and numerical and symbolic computation as being important areas of computer science.^[16]

Theory of computation

The study of the theory of computation is focused on answering fundamental questions about what can be computed, and what amount of resources are required to perform those computations. In an effort to answer the first question, computability theory examines which computational problems are solvable on various theoretical models of computation. The second question is addressed by computational complexity theory, which studies the time and space costs associated with different approaches to solving a computational problem.

The famous “P=NP?” problem, one of the Millennium Prize Problems,^[18] is an open problem in the theory of computation.

	P = NP ?
Computability theory	Computational complexity theory

Theoretical computer science

The broader field of theoretical computer science encompasses both the classical theory of computation, and a wide range of other topics that focus on the more abstract, logical and mathematical aspects of computing.

Mathematical logic	Automata theory	Number theory	Graph theory	Type theory	Category theory	Computational geometry	Quantum computing theory

Algorithms and data structures

O(n2)
Analysis of algorithms	Algorithms	Data structures

Programming methodology and languages

Compilers	Programming languages

Computer elements and architecture

Digital logic	Microarchitecture	Multiprocessing

Numerical and symbolic computation

						y = sin(x) + c
Bioinformatics	Cognitive Science	Computational chemistry	Computational neuroscience	Computational physics	Numerical algorithms	Symbolic mathematics

Relationship with other fields

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 ACM – turingineer, turologist, flow-charts-man, applied meta-mathematician, and applied epistemologist.^[19] Three months later in the same journal, comptologist was suggested, followed next year by hypologist.^[20] The term computics has also been suggested.^[21] Informatik was a term used in Europe with more frequency.

The renowned computer scientist Edsger Dijkstra 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 cognitive science, economics, mathematics, physics (see quantum computing), and linguistics.

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.^[4] 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.^[22]

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 computational science. Both types of departments tend to make efforts to bridge the field educationally if not across all research.

Computer science education

Some universities teach computer science as a theoretical study of computation and algorithmic reasoning. These programs often feature the theory of computation, analysis of algorithms, formal methods, concurrency theory, databases, computer graphics and systems analysis, among others. They typically also teach computer programming, but treat it as a vessel for the support of other fields of computer science rather than a central focus of high-level study.

Other colleges and universities, as well as secondary schools and vocational programs that teach computer science, emphasize the practice of advanced computer programming rather than the theory of algorithms and computation in their computer science curricula. Such curricula tend to focus on those skills that are important to workers entering the software industry. The practical aspects of computer programming are often referred to as software engineering. However, there is a lot of disagreement over the meaning of the term, and whether or not it is the same thing as programming.

See also

Computer science portal

Computer networking portal

Information technology portal

References

Further reading

• Association for Computing Machinery. 1998 ACM Computing Classification System. 1998.
• IEEE Computer Society and the Association for Computing Machinery. Computing Curricula 2001: Computer Science. December 15, 2001.
• Peter J. Denning. Is computer science science?, Communications of the ACM, April 2005.
• Donald E. Knuth. Selected Papers on Computer Science, CSLI Publications, Cambridge Univ. Press, 1996.
• Peter J. Denning, Great principles in computing curricula, Technical Symposium on Computer Science Education, 2004.

External links

Wikibooks has more on the topic of Computer science

At Wikiversity, you can learn about: Portal:Computer Science

• Computer science at the Open Directory Project
• Directory of free university lectures in Computer Science
• bibliography/ Collection of Computer Science Bibliographies
• CS Directory and resources
• Photographs of computer scientists (Bertrand Meyer‘s gallery)

Webcasts

• UCLA Computer Science 1 Freshman Computer Science Seminar Section 1
• Berkeley Introduction to Computers

Carnegie Mellon University neuroscientist Marcel Just and colleague Tom Mitchell have combined functional MRI’s (fMRI’s) ability to observe a brain in action with computer science’s ability to process massive amounts of data to see if it is possible to identify what occurs in the brain when people think specific thoughts. The researchers asked subjects to think about 10 objects, five tools, and five dwellings. The subjects’ brain activity was recorded and analyzed for each object. The researchers were able to identify what object they were thinking about from their brain activation patterns. Similarly, researchers at the Bernstein Center in Berlin are working to use brain scans to identify people’s intentions. Bernstein Center research subjects were asked to make a simple decision, whether to add or subtract two numbers, which they would be shown later. Researcher John Dylan-Haynes says he could read directly from the activity in a small part of the brain that controls intentions what the subjects intended to do. Haynes also is working on a system that would be able to tell where people have been. One experiment involves having subjects navigate through a virtual world, and then showing them images of places they have seen and places they have not seen. FMRI scanning already is being used to try to understand what consumers want to buy and how to best sell those products as part of a new field called neuromarketing.

View full article here: http://www.cbsnews.com/stories/2008/12/31/60minutes/main4694713.shtml

Inventor Takanori Shibata, from Japan’s National Institute of Advanced Industrial Science and Technology, demonstrated Paro, a therapeutic robot that looks like a baby seal, at the annual Consumer Electronics Show in Las Vegas. “His whole body is covered by tactile senses so Paro feels your touch and your stroking,” Shibata says. Paro also features artificial intelligence technology, which enables the robot to remember how it was treated, encourage caressing, and respond to mistreatment with a sad cry. “Paro changes his character depending on the interaction with the owner,” Shibata says. Designed for use in animal therapy and social rehabilitation for people who cannot take care of real animals and in institutions that do not allow them, Paro also is being used as a substitute pet in Japan.

View article here: http://www.google.com/hostednews/canadianpress/article/ALeqM5hTQhd4evOkhhJww1S1bmzmAubNBQ

Shawn Henry, cyber division assistant director at the U.S. Federal Bureau of Investigation (FBI), says that beyond weapons of mass destruction, cyberattacks pose the greatest threat to the United States. U.S. experts warn of a “cybergeddon” in which an advanced society that has most of its major infrastructure systems linked to or completely controlled by computers is sabotaged by hackers. Henry says terrorist groups are working to create a virtual 9/11 that would inflict the same kind of damage to the U.S. as the 9/11 attacks did. Last year, Russian hackers allegedly launched a major offensive against Internet networks in Estonia and Georgia, and Palestinian sympathizers have coordinated attacks against hundreds of Israeli Web sites over the past few days. “We’re seeing that the folks on the cutting edge of this tend to be the bad guys,” says the FBI’s Donald Codling. “It’s extraordinarily difficult for us to catch them.” The FBI’s Christopher Painter says cyberattacks are particularly dangerous because the threat is largely invisible and not always taken seriously as a result. “It’s hard to get your head around the threat,” Painter says. “We often discover a company has been attacked and we tell them that and they don’t know.”

View full article here: http://www.abc.net.au/news/stories/2009/01/07/2460906.htm