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Garbage In, Garbage Out
In computer science, garbage in, garbage out (GIGO) is the concept that flawed, biased or poor quality ("garbage") information or input (computer science), input produces a result or input/output, output of similar ("garbage") quality. The adage points to the need to improve data quality in, for example, programming. Rubbish in, rubbish out (RIRO) is an alternate wording. The principle applies to all logical Argumentation theory, argumentation: soundness implies validity (logic), validity, but validity does not imply soundness. History The expression was popular in the early days of computing. The first known use is in a 1957 syndicated newspaper article about US Army mathematicians and their work with early computers, in which an Army Specialist named William D. Mellin explained that computers cannot think for themselves, and that "sloppily programmed" inputs inevitably lead to incorrect outputs. The underlying principle was noted by the inventor of the first programmable comput ...
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Computer Science
Computer science is the study of computation, information, and automation. Computer science spans Theoretical computer science, theoretical disciplines (such as algorithms, theory of computation, and information theory) to Applied science, applied disciplines (including the design and implementation of Computer architecture, hardware and Software engineering, software). Algorithms and data structures are central to computer science. The theory of computation concerns abstract models of computation and general classes of computational problem, problems that can be solved using them. The fields of cryptography and computer security involve studying the means for secure communication and preventing security vulnerabilities. Computer graphics (computer science), Computer graphics and computational geometry address the generation of images. Programming language theory considers different ways to describe computational processes, and database theory concerns the management of re ...
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Superior Olivary Complex
The superior olivary complex (SOC) or superior olive is a collection of brainstem nuclei that is located in pons, functions in multiple aspects of hearing and is an important component of the ascending and descending auditory pathways of the auditory system. The SOC is intimately related to the trapezoid body: most of the cell groups of the SOC are dorsal (posterior in primates) to this axon bundle while a number of cell groups are embedded in the trapezoid body. Overall, the SOC displays a significant interspecies variation, being largest in bats and rodents and smaller in primates. Physiology The superior olivary nucleus plays a number of roles in hearing. The #Medial superior olive (MSO), medial superior olive (MSO) is a specialized nucleus that is believed to measure the time difference of arrival of sounds between the ears (the interaural time difference or ITD). The ITD is a major cue for determining the azimuth of sounds, i.e., localising them on the azimuthal plane – t ...
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Computer Errors
An error message is the information displayed when an unforeseen problem occurs, usually on a Computer science, computer or other device. Modern operating systems with graphical user interfaces, often display error messages using dialog boxes. Error messages are used when user intervention is required, to indicate that a desired operation has failed, or to relay important warnings (such as warning a computer user that they are almost out of hard disk drive, hard disk space). Error messages are seen widely throughout computing, and are part of every operating system or computer hardware device. The proper design of error messages is an important topic in usability and other fields of human–computer interaction. Common error messages The following error messages are commonly seen by modern computer users: ;Access denied :This error occurs if the user does not have privileges to a Computer file, file, or if it has been file locking, locked by some program or user. ;Device not re ...
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Undefined Behavior
In computer programming, a program exhibits undefined behavior (UB) when it contains, or is executing code for which its programming language specification does not mandate any specific requirements. This is different from unspecified behavior, for which the language specification does not prescribe a result, and implementation-defined behavior that defers to the documentation of another component of the platform (such as the ABI or the translator documentation). In the C programming community, undefined behavior may be humorously referred to as "nasal demons", after a comp.std.c post that explained undefined behavior as allowing the compiler to do anything it chooses, even "to make demons fly out of your nose". Overview Some programming languages allow a program to operate differently or even have a different control flow from the source code, as long as it exhibits the same user-visible side effects, ''if undefined behavior never happens during program execution''. Undef ...
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Standard Error
The standard error (SE) of a statistic (usually an estimator of a parameter, like the average or mean) is the standard deviation of its sampling distribution or an estimate of that standard deviation. In other words, it is the standard deviation of statistic values (each value is per sample that is a set of observations made per sampling on the same population). If the statistic is the sample mean, it is called the standard error of the mean (SEM). The standard error is a key ingredient in producing confidence intervals. The sampling distribution of a mean is generated by repeated sampling from the same population and recording the sample mean per sample. This forms a distribution of different means, and this distribution has its own mean and variance. Mathematically, the variance of the sampling mean distribution obtained is equal to the variance of the population divided by the sample size. This is because as the sample size increases, sample means cluster more closely arou ...
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No Free Lunch Theorem
In mathematical folklore, the "no free lunch" (NFL) theorem (sometimes pluralized) of David Wolpert and William Macready, alludes to the saying "no such thing as a free lunch", that is, there are no easy shortcuts to success. It appeared in the 1997 "No Free Lunch Theorems for Optimization". Wolpert had previously derived no free lunch theorems for machine learning (statistical inference).Wolpert, David (1996),The Lack of ''A Priori'' Distinctions between Learning Algorithms, ''Neural Computation'', pp. 1341–1390. In 2005, Wolpert and Macready themselves indicated that the first theorem in their paper "state that any two optimization algorithms are equivalent when their performance is averaged across all possible problems". The "no free lunch" (NFL) theorem is an easily stated and easily understood consequence of theorems Wolpert and Macready actually prove. It is objectively weaker than the proven theorems, and thus does not encapsulate them. Various investigators have exte ...
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FINO
In computer science, FINO is a humorous scheduling algorithm. It is an acronym for ''first in, never out'' as opposed to traditional ''first in, first out'' (FIFO) and ''last in, first out'' (LIFO) algorithms. A similar acronym is "FISH", for ''first in, still here''. FINO works by withholding all scheduled tasks permanently. No matter how many tasks are scheduled at any time, no task ever actually takes place. A stateful FINO queue can be used to implement a memory leak. The first mention of FINO appears in the Signetics 25120 write-only memory joke datasheet. (alternate copy) See also * Bit bucket * Black hole (networking) In networking, a black hole refers to a place in the network where incoming or outgoing traffic is discarded (or "dropped" or sinkholed) without informing the source that the data did not reach its intended recipient. When examining the topolo ... * * Write-only memory References Scheduling algorithms Computer humour {{comp-sci-stub ...
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Data Processing Inequality
The data processing inequality is an information theoretic concept that states that the information content of a signal cannot be increased via a local physical operation. This can be expressed concisely as 'post-processing cannot increase information'. Statement Let three random variables form the Markov chain X \rightarrow Y \rightarrow Z, implying that the conditional distribution of Z depends only on Y and is conditionally independent of X. Specifically, we have such a Markov chain if the joint probability mass function can be written as :p(x,y,z) = p(x)p(y, x)p(z, y)=p(y)p(x, y)p(z, y) In this setting, no processing of Y, deterministic or random, can increase the information that Y contains about X. Using the mutual information, this can be written as : : I(X;Y) \geqslant I(X;Z), with the equality I(X;Y) = I(X;Z) if and only if I(X;Y\mid Z)=0 . That is, Z and Y contain the same information about X, and X \rightarrow Z \rightarrow Y also forms a Markov chain. Proof On ...
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Computer Says No
"Computer says no" is a catchphrase widely believed to have been first used in the British sketch comedy television programme '' Little Britain'' in 2004. There are previous instances, most notably in the American TV series ''Hill Street Blues'' in 1981. In British culture, the phrase is used to criticise public-facing organisations and customer service staff who rely on information stored on or generated by a computer to make decisions and respond to customers' requests, often in a manner which goes against common sense. It may also refer to a deliberately unhelpful attitude towards customers and service-users commonly experienced within British society, whereby more could be done to reach a mutually satisfactory outcome, but is not. ''Little Britain'' In ''Little Britain'', "Computer says no" is the catchphrase of Carol Beer (played by David Walliams), a bank worker and later holiday rep and hospital receptionist, who always responds to a customer's enquiry by typing it into ...
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Auditory Neuropathy Spectrum Disorder
Auditory neuropathy spectrum disorder (ANSD) is a specific form of hearing loss defined by the presence of normal or near-normal otoacoustic emissions (OAEs) but the absence of normal middle ear reflexes and severely abnormal or completely absent auditory brainstem response (ABRs). Individuals presenting with this recently recognised hearing loss appear to display sporadic windows of hearing and not. Very few (1 in 14) will go on to develop normal speech and language but with poor speech perception in background noise and in others, no speech perception and therefore language development is possible. The condition was originally termed auditory neuropathy (AN) and in 2001 as Auditory Neuropathy / Auditory Dys-synchrony (AN/AD) (to include those cases where no true neuropathy was apparent). In 2008 at a meeting convened at Lake Como in Italy (Guidelines Development Conference on the Identification and Management of Infants with Auditory Neuropathy, International Newborn Hearing Scre ...
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Algorithmic Bias
Algorithmic bias describes systematic and repeatable harmful tendency in a computerized sociotechnical system to create " unfair" outcomes, such as "privileging" one category over another in ways different from the intended function of the algorithm. Bias can emerge from many factors, including but not limited to the design of the algorithm or the unintended or unanticipated use or decisions relating to the way data is coded, collected, selected or used to train the algorithm. For example, algorithmic bias has been observed in search engine results and social media platforms. This bias can have impacts ranging from inadvertent privacy violations to reinforcing social biases of race, gender, sexuality, and ethnicity. The study of algorithmic bias is most concerned with algorithms that reflect "systematic and unfair" discrimination. This bias has only recently been addressed in legal frameworks, such as the European Union's General Data Protection Regulation (proposed 2018) ...
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Machine Learning
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of Computational statistics, statistical algorithms that can learn from data and generalise to unseen data, and thus perform Task (computing), tasks without explicit Machine code, instructions. Within a subdiscipline in machine learning, advances in the field of deep learning have allowed Neural network (machine learning), neural networks, a class of statistical algorithms, to surpass many previous machine learning approaches in performance. ML finds application in many fields, including natural language processing, computer vision, speech recognition, email filtering, agriculture, and medicine. The application of ML to business problems is known as predictive analytics. Statistics and mathematical optimisation (mathematical programming) methods comprise the foundations of machine learning. Data mining is a related field of study, focusing on exploratory data analysi ...
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