DSpace Collection: Volume 12 Number 2
http://hdl.handle.net/10525/717
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Building Data Warehouses Using Numbered Information Spaces
http://hdl.handle.net/10525/801
Title: Building Data Warehouses Using Numbered Information Spaces<br/><br/>Authors: Markov, Krassimir<br/><br/>Abstract: An approach for organizing the information in the data warehouses is presented in the paper. Thepossibilities of the numbered information spaces for building data warehouses are discussed. An application isoutlined in the paper.Sat, 01 Jan 2005 00:00:00 GMTActive Monitoring and Decision Making Problem
http://hdl.handle.net/10525/800
Title: Active Monitoring and Decision Making Problem<br/><br/>Authors: Mostovoi, Sergey; Mostovoi, Vasiliy<br/><br/>Abstract: Active monitoring and problem of non-stable of sound signal parameters in the regime of piling upresponse signal of environment is under consideration. Math model of testing object by set of weak stationarydynamic actions is offered. The response of structures to the set of signals is under processing for gettingimportant information about object condition in high frequency band. Making decision procedure by usingresearcher’s heuristic and aprioristic knowledge is discussed as well. As an example the result of numericalsolution is given.Sat, 01 Jan 2005 00:00:00 GMTDIAGaRa: An Incremental Algorithm for Inferring Implicative Rules from Examples
http://hdl.handle.net/10525/799
Title: DIAGaRa: An Incremental Algorithm for Inferring Implicative Rules from Examples<br/><br/>Authors: Naidenova, Xenia<br/><br/>Abstract: An approach is proposed for inferring implicative logical rules from examples. The concept of a gooddiagnostic test for a given set of positive examples lies in the basis of this approach. The process of inferringgood diagnostic tests is considered as a process of inductive common sense reasoning. The incrementalapproach to learning algorithms is implemented in an algorithm DIAGaRa for inferring implicative rulesfrom examples.Sat, 01 Jan 2005 00:00:00 GMTMathematical Model of Re-Structuring Complex Technical and Economic Structures
http://hdl.handle.net/10525/798
Title: Mathematical Model of Re-Structuring Complex Technical and Economic Structures<br/><br/>Authors: Kornijchuk, May; Sovtus, Inna; Tsaregradskyy, Eugeny<br/><br/>Abstract: Research and development of mathematical model of optimum distribution of resources (basicallyfinancial) for maintenance of the new (raised) quality (reliability) of complex system concerning, which thedecision on its re-structuring is accepted, is stated. The final model gives answers (algorithm of calculation) toquestions: how many elements of system to allocate on modernization, which elements, up to what level of depthmodernization of each of allocated is necessary, and optimum answers are by criterion of minimization offinancial charges.Sat, 01 Jan 2005 00:00:00 GMTInformation Processing in a Cognitive Model of NLP
http://hdl.handle.net/10525/797
Title: Information Processing in a Cognitive Model of NLP<br/><br/>Authors: Slavova, Velina; Soschen, Alona; Immes, Luke<br/><br/>Abstract: A model of the cognitive process of natural language processing has been developed using theformalism of generalized nets. Following this stage-simulating model, the treatment of information inevitablyincludes phases, which require joint operations in two knowledge spaces – language and semantics. In order toexamine and formalize the relations between the language and the semantic levels of treatment, the language ispresented as an information system, conceived on the bases of human cognitive resources, semantic primitives,semantic operators and language rules and data. This approach is applied for modeling a specific grammaticalrule – the secondary predication in Russian. Grammatical rules of the language space are expressed asoperators in the semantic space. Examples from the linguistics domain are treated and several conclusions forthe semantics of the modeled rule are made. The results of applying the information system approach to thelanguage turn up to be consistent with the stages of treatment modeled with the generalized net.Sat, 01 Jan 2005 00:00:00 GMTA Mathematical Apparatus for Domain Ontology Simulation. An Extendable Language of Applied Logic
http://hdl.handle.net/10525/796
Title: A Mathematical Apparatus for Domain Ontology Simulation. An Extendable Language of Applied Logic<br/><br/>Authors: Kleshchev, Alexander; Artemjeva, Irene<br/><br/>Abstract: A mathematical apparatus for domain ontology simulation will be described in the series of the articles.This article is the first one of the series. The paper is devoted to means for representation of domain models anddomain ontology models, so here a logical language is used only as a means for formalizing ideas. The chiefrequirement to such a language is that it must have such a semantic basis that would allow us to determine themost exact approximation of a set of intended interpretation functions as often as possible. Another requirementclosely connected with the foregoing one is that the awkwardness of expressing ideas in such a language mustnot considerably exceed the complexity of their expressing in natural language. There are two ways to meetthe requirements. The first one is to define and fix a wide semantic basis of the language. In this case thesemantic basis nonetheless can be insufficient for some applications of the language. Extending applicationsof the language can lead from time to time to the necessity of further extending its semantic basis, i.e. to thenecessity of defining new and new versions of the language. The second way is to make the kernel of thelanguage being as nearer to the semantic basis of the classical language as possible and to allow us to makenecessary extensions of the kernel for particular applications. In this article the second way is used to define theextendable language of applied logic. The goal of this article is to define the kernel of the extendable language ofapplied logic and its standard extension. The standard extension of the language defines elements of thesemantic basis that are supposed to be useful practically in all the applications.<br/><br/>Description: * This paper was made according to the program of fundamental scientific research of the Presidium of the Russian Academy of Sciences «Mathematical simulation and intellectual systems», the project "Theoretical foundation of the intellectual systems based on ontologies for intellectual support of scientific researches".Sat, 01 Jan 2005 00:00:00 GMTExperiments in Detection and Correction of Russian Malapropisms by Means of the WEB
http://hdl.handle.net/10525/795
Title: Experiments in Detection and Correction of Russian Malapropisms by Means of the WEB<br/><br/>Authors: Bolshakova, Elena; Bolshakov, Igor; Kotlyarov, Alexey<br/><br/>Abstract: Malapropism is a semantic error that is hardly detectable because it usually retains syntactical linksbetween words in the sentence but replaces one content word by a similar word with quite different meaning. Amethod of automatic detection of malapropisms is described, based on Web statistics and a specially definedSemantic Compatibility Index (SCI). For correction of the detected errors, special dictionaries and heuristic rulesare proposed, which retains only a few highly SCI-ranked correction candidates for the user’s selection.Experiments on Web-assisted detection and correction of Russian malapropisms are reported, demonstratingefficacy of the described method.Sat, 01 Jan 2005 00:00:00 GMTA Workbench for Document Processing
http://hdl.handle.net/10525/794
Title: A Workbench for Document Processing<br/><br/>Authors: Witschurke, Karola<br/><br/>Abstract: During the MEMORIAL project time an international consortium has developed a software solutioncalled DDW (Digital Document Workbench). It provides a set of tools to support the process of digitisation ofdocuments from the scanning up to the retrievable presentation of the content. The attention is focused tomachine typed archival documents. One of the important features is the evaluation of quality in each step of theprocess. The workbench consists of automatic parts as well as of parts which request human activity. Themeasurable improvement of 20% shows the approach is successful.Sat, 01 Jan 2005 00:00:00 GMTA Geometrical Interpretation to Define Contradiction Degrees between Two Fuzzy Sets
http://hdl.handle.net/10525/793
Title: A Geometrical Interpretation to Define Contradiction Degrees between Two Fuzzy Sets<br/><br/>Authors: Torres, Carmen; Castiñeira, Elena; Cubillo, Susana; Zarzosa, Victoria<br/><br/>Abstract: For inference purposes in both classical and fuzzy logic, neither the information itself should becontradictory, nor should any of the items of available information contradict each other. In order to avoid thesetroubles in fuzzy logic, a study about contradiction was initiated by Trillas et al. in [5] and [6]. They introduced theconcepts of both self-contradictory fuzzy set and contradiction between two fuzzy sets. Moreover, the need tostudy not only contradiction but also the degree of such contradiction is pointed out in [1] and [2], suggestingsome measures for this purpose. Nevertheless, contradiction could have been measured in some other way. Thispaper focuses on the study of contradiction between two fuzzy sets dealing with the problem from a geometricalpoint of view that allow us to find out new ways to measure the contradiction degree. To do this, the two fuzzysets are interpreted as a subset of the unit square, and the so called contradiction region is determined. Speciallywe tackle the case in which both sets represent a curve in [0,1]2. This new geometrical approach allows us toobtain different functions to measure contradiction throughout distances. Moreover, some properties of thesecontradiction measure functions are established and, in some particular case, the relations among these differentfunctions are obtained.Sat, 01 Jan 2005 00:00:00 GMTA New Approach for Eliminating the Spurious States in Recurrent Neural Networks
http://hdl.handle.net/10525/792
Title: A New Approach for Eliminating the Spurious States in Recurrent Neural Networks<br/><br/>Authors: Gimenez-Martinez, Victor; Torres, Carmen; Joaquin Erviti Anaut, Jose; Perez-Castellanos, Mercedes<br/><br/>Abstract: As is well known, the Convergence Theorem for the Recurrent Neural Networks, is based inLyapunov ́s second method, which states that associated to any one given net state, there always exist a realnumber, in other words an element of the one dimensional Euclidean Space R, in such a way that when the stateof the net changes then its associated real number decreases. In this paper we will introduce the two dimensionalEuclidean space R2, as the space associated to the net, and we will define a pair of real numbers ( x, y ) ,associated to any one given state of the net. We will prove that when the net change its state, then the product x ⋅ y will decrease. All the states whose projection over the energy field are placed on the same hyperbolicsurface, will be considered as points with the same energy level. On the other hand we will prove that if the statesare classified attended to their distances to the zero vector, only one pattern in each one of the different classesmay be at the same energy level. The retrieving procedure is analyzed trough the projection of the states on thatplane. The geometrical properties of the synaptic matrix W may be used for classifying the n-dimensional state-vector space in n classes. A pattern to be recognized is seen as a point belonging to one of these classes, anddepending on the class the pattern to be retrieved belongs, different weight parameters are used. The capacity ofthe net is improved and the spurious states are reduced. In order to clarify and corroborate the theoretical results,together with the formal theory, an application is presented.Sat, 01 Jan 2005 00:00:00 GMTBridging the Gap Between Human Language and Computer-Oriented Representations
http://hdl.handle.net/10525/791
Title: Bridging the Gap Between Human Language and Computer-Oriented Representations<br/><br/>Authors: Cardenosa, Jesus; Gallardo, Carolina; Santos, Eugenio<br/><br/>Abstract: Information can be expressed in many ways according to the different capacities of humans to perceiveit. Current systems deals with multimedia, multiformat and multiplatform systems but another « multi » is stillpending to guarantee global access to information, that is, multilinguality. Different languages imply differentreplications of the systems according to the language in question. No solutions appear to represent the bridgebetween the human representation (natural language) and a system-oriented representation. The United NationsUniversity defined in 1997 a language to be the support of effective multilinguism in Internet. In this paper, wedescribe this language and its possible applications beyond multilingual services as the possible future standardfor different language independent applications.Sat, 01 Jan 2005 00:00:00 GMTNeural Control of Chaos and Aplications
http://hdl.handle.net/10525/790
Title: Neural Control of Chaos and Aplications<br/><br/>Authors: Hernandez, Cristina; Castellanos, Juan; Gonzalo, Rafael; Palencia, Valentin<br/><br/>Abstract: Signal processing is an important topic in technological research today. In the areas of nonlineardynamics search, the endeavor to control or order chaos is an issue that has received increasing attention overthe last few years. Increasing interest in neural networks composed of simple processing elements (neurons) hasled to widespread use of such networks to control dynamic systems learning. This paper presentsbackpropagation-based neural network architecture that can be used as a controller to stabilize unsteady periodicorbits. It also presents a neural network-based method for transferring the dynamics among attractors, leading tomore efficient system control. The procedure can be applied to every point of the basin, no matter how far awayfrom the attractor they are. Finally, this paper shows how two mixed chaotic signals can be controlled using abackpropagation neural network as a filter to separate and control both signals at the same time. The neuralnetwork provides more effective control, overcoming the problems that arise with control feedback methods.Control is more effective because it can be applied to the system at any point, even if it is moving away from thetarget state, which prevents waiting times. Also control can be applied even if there is little information about thesystem and remains stable longer even in the presence of random dynamic noise.Sat, 01 Jan 2005 00:00:00 GMT