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Catpac
Catpac is a computer program that analyzes text samples to identify key concepts contained within the sample. It was conceived chiefly by Richard Holmes, a Michigan State computer programmer and Dr. Joseph Woelfel, a University at Albany and University at Buffalo sociologist for the analysis of attitude formation and change in the sociological context. Contributions by Rob Zimmelman, an undergraduate and graduate student at the University of Albany, from 1981 to 1984 on the Univac 1100 mainframe, included the inclusion of the CATPAC software in the Galileo*Telegal system, text-labeling and porting of CATPAC output for the Galileo system of paired-comparison conceptual visualization. CATPAC and the Galileo system are still in commercial use today, and with recent data capture and visualization contributions, continues to grow. Contributions by other students at the university resulted in the software that is still in commercial use today. It uses text files as input and produces ...
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Joseph Woelfel
Joseph Woelfel (born June 3, 1940) is an American sociologist. Born in Buffalo, New York, he is currently professor in the Department of Communication at the University at Buffalo, The State University of New York. Career Woelfel obtained his BA in Sociology from Canisius College in 1962, and an MA in Sociology from the University of Wisconsin–Madison in 1963. He obtained his Ph.D. in Sociology, also from the University of Wisconsin, in 1968. Throughout his studies he minored in philosophy. After acting as an instructor at Canisius College (1965–1966) and as a research associate at University of Wisconsin during his studies, Woelfel began work as an assistant professor at the University of Illinois at Urbana–Champaign in 1968. In 1972 he moved to Michigan State University as an associate professor. Then in 1978 he moved to University at Albany, SUNY as a visiting professor, where he was then hired as an associate professor in 1979. In 1981 he was promoted to professor and in ...
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University At Buffalo
The State University of New York at Buffalo, commonly called the University at Buffalo (UB) and sometimes called SUNY Buffalo, is a public research university with campuses in Buffalo and Amherst, New York. The university was founded in 1846 as a private medical college and merged with the State University of New York system in 1962. It is one of the two flagship institutions of the SUNY system. As of fall 2020, the university enrolled 32,347 students in 13 schools and colleges, making it the largest and most comprehensive public university in the state of New York. Since its founding by a group which included future United States President Millard Fillmore, the university has evolved from a small medical school to a large research university. Today, in addition to the College of Arts and Sciences, the university houses the largest state-operated medical school, dental school, education school, business school, engineering school, and pharmacy school, and is also home ...
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Sociology
Sociology is a social science that focuses on society, human social behavior, patterns of social relationships, social interaction, and aspects of culture associated with everyday life. It uses various methods of empirical investigation and critical analysis to develop a body of knowledge about social order and social change. While some sociologists conduct research that may be applied directly to social policy and welfare, others focus primarily on refining the theoretical understanding of social processes and phenomenological method. Subject matter can range from micro-level analyses of society (i.e. of individual interaction and agency) to macro-level analyses (i.e. of social systems and social structure). Traditional focuses of sociology include social stratification, social class, social mobility, religion, secularization, law, sexuality, gender, and deviance. As all spheres of human activity are affected by the interplay between social structure and individu ...
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Self-organization
Self-organization, also called spontaneous order in the social sciences, is a process where some form of overall order arises from local interactions between parts of an initially disordered system. The process can be spontaneous when sufficient energy is available, not needing control by any external agent. It is often triggered by seemingly random fluctuations, amplified by positive feedback. The resulting organization is wholly decentralized, distributed over all the components of the system. As such, the organization is typically robust and able to survive or self-repair substantial perturbation. Chaos theory discusses self-organization in terms of islands of predictability in a sea of chaotic unpredictability. Self-organization occurs in many physical, chemical, biological, robotic, and cognitive systems. Examples of self-organization include crystallization, thermal convection of fluids, chemical oscillation, animal swarming, neural circuits, and black markets. ...
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Interactive Activation And Competition Networks
Interactive activation and competition (IAC) networks are artificial neural networks used to model memory and intuitive generalizations. They are made up of nodes or artificial neuron An artificial neuron is a mathematical function conceived as a model of biological neurons, a neural network. Artificial neurons are elementary units in an artificial neural network. The artificial neuron receives one or more inputs (representing ...s which are arrayed and activated in ways that emulate the behaviors of human memory. The IAC model is used by the parallel distributed processing (PDP) Group and is associated with James L. McClelland and David E. Rumelhart; it is described in detail in their book ''Explorations in Parallel Distributed Processing: A Handbook of Models, Programs, and Exercises''. This model does not contradict any currently known biological data or theories, and its performance is close enough to human performance as to warrant further investigation. References Ex ...
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Artificial Neural Network
Artificial neural networks (ANNs), usually simply called neural networks (NNs) or neural nets, are computing systems inspired by the biological neural networks that constitute animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons. An artificial neuron receives signals then processes them and can signal neurons connected to it. The "signal" at a connection is a real number, and the output of each neuron is computed by some non-linear function of the sum of its inputs. The connections are called ''edges''. Neurons and edges typically have a ''weight'' that adjusts as learning proceeds. The weight increases or decreases the strength of the signal at a connection. Neurons may have a threshold such that a signal is sent only if the aggregate signal crosses that threshold. Typically, ...
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Scalar (mathematics)
A scalar is an element of a field which is used to define a '' vector space''. In linear algebra, real numbers or generally elements of a field are called scalars and relate to vectors in an associated vector space through the operation of scalar multiplication (defined in the vector space), in which a vector can be multiplied by a scalar in the defined way to produce another vector. Generally speaking, a vector space may be defined by using any field instead of real numbers (such as complex numbers). Then scalars of that vector space will be elements of the associated field (such as complex numbers). A scalar product operation – not to be confused with scalar multiplication – may be defined on a vector space, allowing two vectors to be multiplied in the defined way to produce a scalar. A vector space equipped with a scalar product is called an inner product space. A quantity described by multiple scalars, such as having both direction and magnitude, is calle ...
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Matrix (mathematics)
In mathematics, a matrix (plural matrices) is a rectangular array or table of numbers, symbols, or expressions, arranged in rows and columns, which is used to represent a mathematical object or a property of such an object. For example, \begin1 & 9 & -13 \\20 & 5 & -6 \end is a matrix with two rows and three columns. This is often referred to as a "two by three matrix", a "-matrix", or a matrix of dimension . Without further specifications, matrices represent linear maps, and allow explicit computations in linear algebra. Therefore, the study of matrices is a large part of linear algebra, and most properties and operations of abstract linear algebra can be expressed in terms of matrices. For example, matrix multiplication represents composition of linear maps. Not all matrices are related to linear algebra. This is, in particular, the case in graph theory, of incidence matrices, and adjacency matrices. ''This article focuses on matrices related to linear algebra, an ...
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Eigenvector
In linear algebra, an eigenvector () or characteristic vector of a linear transformation is a nonzero vector that changes at most by a scalar factor when that linear transformation is applied to it. The corresponding eigenvalue, often denoted by \lambda, is the factor by which the eigenvector is scaled. Geometrically, an eigenvector, corresponding to a real nonzero eigenvalue, points in a direction in which it is stretched by the transformation and the eigenvalue is the factor by which it is stretched. If the eigenvalue is negative, the direction is reversed. Loosely speaking, in a multidimensional vector space, the eigenvector is not rotated. Formal definition If is a linear transformation from a vector space over a field into itself and is a nonzero vector in , then is an eigenvector of if is a scalar multiple of . This can be written as T(\mathbf) = \lambda \mathbf, where is a scalar in , known as the eigenvalue, characteristic value, or characteristic root ...
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