1.
Computer
–
A computer is a device that can be instructed to carry out an arbitrary set of arithmetic or logical operations automatically. The ability of computers to follow a sequence of operations, called a program, such computers are used as control systems for a very wide variety of industrial and consumer devices. The Internet is run on computers and it millions of other computers. Since ancient times, simple manual devices like the abacus aided people in doing calculations, early in the Industrial Revolution, some mechanical devices were built to automate long tedious tasks, such as guiding patterns for looms. More sophisticated electrical machines did specialized analog calculations in the early 20th century, the first digital electronic calculating machines were developed during World War II. The speed, power, and versatility of computers has increased continuously and dramatically since then, conventionally, a modern computer consists of at least one processing element, typically a central processing unit, and some form of memory. The processing element carries out arithmetic and logical operations, and a sequencing, peripheral devices include input devices, output devices, and input/output devices that perform both functions. Peripheral devices allow information to be retrieved from an external source and this usage of the term referred to a person who carried out calculations or computations. The word continued with the same meaning until the middle of the 20th century, from the end of the 19th century the word began to take on its more familiar meaning, a machine that carries out computations. The Online Etymology Dictionary gives the first attested use of computer in the 1640s, one who calculates, the Online Etymology Dictionary states that the use of the term to mean calculating machine is from 1897. The Online Etymology Dictionary indicates that the use of the term. 1945 under this name, theoretical from 1937, as Turing machine, devices have been used to aid computation for thousands of years, mostly using one-to-one correspondence with fingers. The earliest counting device was probably a form of tally stick, later record keeping aids throughout the Fertile Crescent included calculi which represented counts of items, probably livestock or grains, sealed in hollow unbaked clay containers. The use of counting rods is one example, the abacus was initially used for arithmetic tasks. The Roman abacus was developed from used in Babylonia as early as 2400 BC. Since then, many forms of reckoning boards or tables have been invented. In a medieval European counting house, a checkered cloth would be placed on a table, the Antikythera mechanism is believed to be the earliest mechanical analog computer, according to Derek J. de Solla Price. It was designed to calculate astronomical positions and it was discovered in 1901 in the Antikythera wreck off the Greek island of Antikythera, between Kythera and Crete, and has been dated to circa 100 BC
2.
Automata theory
–
Automata theory is the study of abstract machines and automata, as well as the computational problems that can be solved using them. It is a theory in computer science and discrete mathematics. The word automata comes from the Greek word αὐτόματα, which means self-acting, the figure at right illustrates a finite-state machine, which belongs to a well-known type of automaton. This automaton consists of states and transitions, as the automaton sees a symbol of input, it makes a transition to another state, according to its transition function, which takes the current state and the recent symbol as its inputs. Automata theory is related to formal language theory. An automaton is a representation of a formal language that may be an infinite set. Automata play a role in theory of computation, compiler construction, artificial intelligence, parsing. Following is a definition of one type of automaton, which attempts to help one grasp the essential concepts involved in automata theory/theories. An automaton is supposed to run on some given sequence of inputs in time steps. An automaton gets one input every step that is picked up from a set of symbols or letters. At any time, the symbols so far fed to the automaton as input, form a sequence of symbols. An automaton contains a set of states. At each instance in time of run, the automaton is in one of its states. At each time step when the automaton reads a symbol, it jumps or transitions to state that is decided by a function that takes the current state. This function is called the transition function, the automaton reads the symbols of the input word one after another and transitions from state to state according to the transition function, until the word is read completely. Once the input word has been read, the automaton is said to have stopped, depending on the final state, its said that the automaton either accepts or rejects an input word. There is a subset of states of the automaton, which is defined as the set of accepting states, if the final state is an accepting state, then the automaton accepts the word. The set of all the words accepted by an automaton is called the language of that automaton, any subset of the language of an automaton is a language recognized by that automaton
3.
Computer science
–
Computer science is the study of the theory, experimentation, and engineering that form the basis for the design and use of computers. An alternate, more succinct definition of science is the study of automating algorithmic processes that scale. A computer scientist specializes in the theory of computation and the design of computational systems and its fields can be divided into a variety of theoretical and practical disciplines. Some fields, such as computational complexity theory, are highly abstract, other fields still focus on challenges in implementing computation. Human–computer interaction considers the challenges in making computers and computations useful, usable, the earliest 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, further, algorithms for performing computations have existed since antiquity, even before the development of sophisticated computing equipment. Wilhelm Schickard designed and constructed the first working mechanical calculator in 1623, in 1673, Gottfried Leibniz demonstrated a digital mechanical calculator, called the Stepped Reckoner. He may be considered the first computer scientist and information theorist, for, among other reasons and he started developing this machine in 1834, and in less than two years, he had sketched out many of the salient features of the modern computer. A crucial step was the adoption of a card system derived from the Jacquard loom making it infinitely programmable. Around 1885, Herman Hollerith invented the tabulator, which used punched cards to process statistical information, when the machine was finished, some hailed it as Babbages dream come true. During the 1940s, as new and more powerful computing machines were developed, 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 an academic discipline in the 1950s. The worlds first computer science program, the Cambridge Diploma in Computer Science. The first computer science program in the United States was formed at Purdue University in 1962. Since practical computers became available, many applications of computing have become distinct areas of study in their own rights and it is the now well-known IBM brand that formed part of the computer science revolution during this time. IBM released the IBM704 and later the IBM709 computers, still, working with the IBM 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. During the late 1950s, the science discipline was very much in its developmental stages. Time has seen significant improvements in the usability and effectiveness of computing technology, modern society has seen a significant shift in the users of computer technology, from usage only by experts and professionals, to a near-ubiquitous user base
4.
Computer engineering
–
Computer engineering is a discipline that integrates several fields of electrical engineering and computer science required to develop computer hardware and software. Computer engineers usually have training in engineering, software design. This field of engineering not only focuses on how computer systems themselves work, Computer engineers are also suited for robotics research, which relies heavily on using digital systems to control and monitor electrical systems like motors, communications, and sensors. Other institutions may require engineering students to one or two years of General Engineering before declaring computer engineering as their primary focus. The first computer engineering program in the United States was established at Case Western Reserve University in 1972. As of 2015, there were 238 ABET-accredited computer engineering programs in the US, in Europe, accreditation of computer engineering schools is done by a variety of agencies part of the EQANIE network. Both computer engineering and electronic engineering programs include analog and digital circuit design in their curriculum, as with most engineering disciplines, having a sound knowledge of mathematics and science is necessary for computer engineers. There are two major specialties in computer engineering, software and hardware, Computer software engineers develop, design, and test software. They construct, and maintain computer programs, as well as set up such as intranets for companies. Software engineers can design or code new applications to meet the needs of a business or individual. Some software engineers work independently as freelancers and sell their software products/applications to an enterprise or individual, most computer hardware engineers research, develop, design, and test various computer equipment. This can range from circuit boards and microprocessors to routers, some update existing computer equipment to be more efficient and work with newer software. Most computer hardware engineers work in laboratories and high-tech manufacturing firms. Some also work for the federal government, according to BLS, 95% of computer hardware engineers work in metropolitan areas. Approximately 33% of their work more than 40 hours a week. The median salary for employed qualified computer hardware engineers was $100,920 per year or $48.52 per hour, Computer hardware engineers held 83,300 jobs in 2012 in the USA. There are many specialty areas in the field of computer engineering, examples include work on wireless communications, multi-antenna systems, optical transmission, and digital watermarking. Those focusing on communications and wireless networks, work advancements in telecommunications systems and networks, modulation and error-control coding, high-speed network design, interference suppression and modulation, design and analysis of fault-tolerant system, and storage and transmission schemes are all a part of this specialty
5.
Paradigm
–
Paradigm comes from Greek παράδειγμα, pattern, example, sample from the verb παραδείκνυμι, exhibit, represent, expose and that from παρά, beside, beyond and δείκνυμι, to show, to point out. In rhetoric, paradeigma is known as a type of proof, the purpose of paradeigma is to provide an audience with an illustration of similar occurrences. This illustration is not meant to take the audience to a conclusion, a personal accountant is a good comparison of paradeigma to explain how it is meant to guide the audience. Anaximenes defined paradeigma as, actions that have occurred previously and are similar to, or the opposite of, the original Greek term παράδειγμα was used in Greek texts such as Platos Timaeus as the model or the pattern that the Demiurge used to create the cosmos. In linguistics, Ferdinand de Saussure used paradigm to refer to a class of elements with similarities, normal science proceeds within such a framework or paradigm. A paradigm does not impose a rigid or mechanical approach, the Oxford English Dictionary defines the basic meaning of the term paradigm as a typical example or pattern of something, a pattern or model. e. Firstly, within normal science, the term refers to the set of experiments that are likely to be copied or emulated. Secondly, underpinning this set of exemplars are shared preconceptions, made prior to – and these preconceptions embody both hidden assumptions and elements that he describes as quasi-metaphysical, the interpretations of the paradigm may vary among individual scientists. Kuhn was at pains to point out that the rationale for the choice of exemplars is a way of viewing reality, that view. For well-integrated members of a discipline, its paradigm is so convincing that it normally renders even the possibility of alternatives unconvincing. Such a paradigm is opaque, appearing to be a view of the bedrock of reality itself. The conviction that the current paradigm is reality tends to disqualify evidence that might undermine the paradigm itself and it is the latter that is responsible for the eventual revolutionary overthrow of the incumbent paradigm, and its replacement by a new one. Kuhn used the expression paradigm shift for this process, and likened it to the change that occurs when our interpretation of an ambiguous image flips over from one state to another. This is significant in relation to the issue of incommensurability, an example of a currently accepted paradigm would be the standard model of physics. Mechanisms similar to the original Kuhnian paradigm have been invoked in various disciplines other than the philosophy of science and these include, the idea of major cultural themes, worldviews, ideologies, and mindsets. They have somewhat similar meanings that apply to smaller and larger examples of disciplined thought. In addition, Michel Foucault used the terms episteme and discourse, mathesis and taxinomia, in The Structure of Scientific Revolutions, Kuhn wrote that the successive transition from one paradigm to another via revolution is the usual developmental pattern of mature science. New paradigms tend to be most dramatic in sciences that appear to be stable and mature, at that time, a statement generally attributed to physicist Lord Kelvin famously claimed, There is nothing new to be discovered in physics now
6.
Theory of computation
–
In theoretical computer science and mathematics, the theory of computation is the branch that deals with how efficiently problems can be solved on a model of computation, using an algorithm. In order to perform a study of computation, computer scientists work with a mathematical abstraction of computers called a model of computation. There are several models in use, but the most commonly examined is the Turing machine and it might seem that the potentially infinite memory capacity is an unrealizable attribute, but any decidable problem solved by a Turing machine will always require only a finite amount of memory. So in principle, any problem that can be solved by a Turing machine can be solved by a computer that has an amount of memory. The theory of computation can be considered the creation of models of all kinds in the field of computer science, therefore, mathematics and logic are used. In the last century it became an independent academic discipline and was separated from mathematics, some pioneers of the theory of computation were Alonzo Church, Kurt Gödel, Alan Turing, Stephen Kleene, John von Neumann and Claude Shannon. Automata theory is the study of abstract machines and the problems that can be solved using these machines. These abstract machines are called automata, Automata comes from the Greek word which means that something is doing something by itself. Automata theory is closely related to formal language theory, as the automata are often classified by the class of formal languages they are able to recognize. An automaton can be a representation of a formal language that may be an infinite set. Automata are used as models for computing machines, and are used for proofs about computability. Language theory is a branch of mathematics concerned with describing languages as a set of operations over an alphabet and it is closely linked with automata theory, as automata are used to generate and recognize formal languages. Because automata are used as models for computation, formal languages are the mode of specification for any problem that must be computed. Computability theory deals primarily with the question of the extent to which a problem is solvable on a computer, much of computability theory builds on the halting problem result. Many mathematicians and computational theorists who study recursion theory will refer to it as computability theory, Complexity theory considers not only whether a problem can be solved at all on a computer, but also how efficiently the problem can be solved. In order to analyze how much time and space a given algorithm requires, for example, finding a particular number in a long list of numbers becomes harder as the list of numbers grows larger. If we say there are n numbers in the list, then if the list is not sorted or indexed in any way we may have to look at every number in order to find the number were seeking. We thus say that in order to solve this problem, the needs to perform a number of steps that grows linearly in the size of the problem
7.
Thought experiment
–
A thought experiment considers some hypothesis, theory, or principle for the purpose of thinking through its consequences. Given the structure of the experiment, it may not be possible to perform it, perhaps the key experiment in the history of modern science is Galileos demonstration that falling objects must fall at the same rate regardless of their masses. The experiment is described by Galileo in Discorsi e dimostrazioni matematiche thus, do you not agree with me in this opinion. Hence the heavier body moves with less speed than the lighter, thus you see how, from your assumption that the heavier body moves more rapidly than the lighter one, I infer that the heavier body moves more slowly. Although the extract does not convey the elegance and power of the demonstration terribly well, it is clear that it is a thought experiment, instead, many philosophers prefer to consider Thought Experiments to be merely the use of a hypothetical scenario to help understand the way things are. Thought experiments have used in a variety of fields, including philosophy, law, physics. In philosophy, they have used at least since classical antiquity. In law, they were well-known to Roman lawyers quoted in the Digest, in physics and other sciences, notable thought experiments date from the 19th and especially the 20th century, but examples can be found at least as early as Galileo. Johann Witt-Hansen established that Hans Christian Ørsted was the first to use the Latin-German mixed term Gedankenexperiment circa 1812, Ørsted was also the first to use its entirely German equivalent, Gedankenversuch, in 1820. The English term thought experiment was coined from Machs Gedankenexperiment, prior to its emergence, the activity of posing hypothetical questions that employed subjunctive reasoning had existed for a very long time. However, people had no way of categorizing it or speaking about it and this helps to explain the extremely wide and diverse range of the application of the term thought experiment once it had been introduced into English. In physics and other sciences many thought experiments date from the 19th and especially the 20th Century, in Galileo’s thought experiment, for example, the rearrangement of empirical experience consists in the original idea of combining bodies of different weight. Thought experiments have used in philosophy, physics, and other fields. In law, the hypothetical is frequently used for such experiments. Regardless of their goal, all thought experiments display a patterned way of thinking that is designed to allow us to explain, predict and control events in a better. However, they may make those theories themselves irrelevant, and could create new problems that are just as difficult. Ensure the avoidance of past failures Scientists tend to use thought experiments as imaginary, in these cases, the result of the proxy experiment will often be so clear that there will be no need to conduct a physical experiment at all. Scientists also use thought experiments when particular physical experiments are impossible to conduct, such as Einsteins thought experiment of chasing a light beam, leading to Special Relativity
