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Fuzzy Logic
The Fuzzy Logic tool was introduced in 1965, by Lotfi Zadeh, and is a mathematical tool for dealing with uncertainty. It offers to a soft computing partnership the important concept of computing with words. It provides a technique to deal with imprecision and information granularity. The fuzzy theory provides a mechanism for representing linguistic constructs such as "many, low, medium, often, few". In general, the fuzzy logic provides an inference structure that enables appropriate human reasoning capabilities.
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The goal of UML is to provide a standard notation that can be used by all object-oriented methods and to select and integrate the best elements of precursor notations. For example, UML includes the use case diagrams introduced by OOSE and uses many features of the OMT class diagrams. UML also includes new concepts that were not present in other major methods at the time, such as extension mechanisms and a constraint language. UML has been designed for a broad range of applications. Hence, it provides constructs for a broad range of systems and activities (e.g., distributed systems, analysis, system design, deployment).

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Algorithms are well defined procedures for solving problems. In computing, algorithms are essential because they serve as the systematic procedures that computers require. A good algorithm is like using the right tool in a workshop. It does the job with the right amount of effort. Using the wrong algorithm or one that is not clearly defined is like cutting a piece of paper with a table saw, or trying to cut a piece of plywood with a pair of scissors: although the job may get done, you have to wonder how effective you were in completing it. As with data structures, three reasons for using formal algorithms are efficiency, abstraction, and reusability.
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What is Artificial Intelligence?
The Industrial Revolution, which started in England around 1760, has replaced human muscle power with the machine. Artificial intelligence (AI) aims at replacing human intelligence with the machine. The work on artificial intelligence started in the early 1950s, and the term it self was coined in 1956.
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Classification is a type of data analysis which can help people predict the class labels of the samples to be classified. A wide variety of classification techniques have been proposed in fields such as machine learning, expert systems and statistics. Normally, classification models are trained first on a historical dataset (i.e., the training set) with their class labels already known. Then, these trained classifiers are applied to predict the class labels of new samples.
Among the most popular classification models (methods), we could mention, although they are used, obviously, for other purposes too: Classification Trees, Naive Bayes Classifiers, Neural Networks, Genetic Algorithms, k-Nearest Neighbor Classifier.
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Data mining
Data mining is the process of discovering meaningful new correlations, patterns and trends by sifting through large amounts of data stored in repositories, using pattern recognition technologies as well as statistical and mathematical techniques. (Gartner Group)
However, before attempting a definition of data mining (sometimes called data or knowledge discovery), let us emphasize some aspects of its genesis.Data mining, also known as "knowledge-discovery in databases" (KDD), has three generic roots, from which it borrowed the techniques and terminology.
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Decision Support System
A decision support system (DSS) is an interactive computer-based application that combines data and mathematical models to help decision makers solve complex problems faced in managing the public and private enterprises and organizations. To some extent they show connections with the information systems of an organization. Hence, it is worth describing in this section a time-line for the evolution of information systems, since this highlights how data processing has developed and has been used within companies.
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Information Retrieval
An Information Retrieval System is the hardware and software that facilitates a user in finding the information the user needs. Hardware is included in the definition because specialized hardware is needed to transform certain modalities into digital processing format (e.g., encoders that translate composite video to digital video). As the detailed processing of items is described it will become clear that an information retrieval system is not a single application but is composed of many different applications that work together to provide the tools and functions needed to assist the users in answering their questions.
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Software Development Life Cycle
The software development life-cycle consists of several phases and these phases need to be identified along with defining the entry and exit criteria for every phase. A phase can begin only when the corresponding phase-entry criteria aresatisfied. Similarly, a phase can be considered to be complete only when the corresponding exit criteria are satisfied. If there is no clear indication of the entry and exit for every phase, it becomes very difficult to track the progress of the project.
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The Open Group Architecture Framework (TOGAF) is a framework for developing an enterprise architecture for use within that organisation. TOGAF provides the methods and tools for assisting in the acceptance, production, use, and maintenance of an enterprise architecture. It is based on an iterative process model supported by best practices and a re-usable set of existing architecture assets.
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