203 resultados para Applyed informatics

em Bulgarian Digital Mathematics Library at IMI-BAS


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In October 1997 we celebrate the fiftieth anniversary of the founding of the Institute for Mathematics and Informatics (IMI) of the Bulgarian Academy of Sciences (BAS).

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How the processes of human perception exert influence on the development of the information science is discussed in the article.

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It is proposed to use one common model of computer for teaching different parts of the informatics course, connected with both hardware and software subjects. Reasoning of such slant is presented; the most suitable themes of the course, where it is practical, are enumerated. The own author's development (including software support) – the educational model of virtual computer "E97" and compiler from Pascal language for it – are described. It is accented, that the discussed ideas are helpful for any other similar model.

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The Faculty of Mathematics and Informatics (FMI) of Sofia University “St. Kliment Ohridski” is briefly presented as an educational and research institution. The possible contribution of FMI to KT-DigiCULT-BG project is analyzed.

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A definition of the concept "business informatics" based on the General Information Theory is discussed in the paper.

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This work acquaints with a program for interactive computer training to students on the subject "Mutual intersecting of pyramids in axonometry ”. Our software is a set of three modules, which we call "student", "teacher" and "autopilot". It gives the final solution of the problem, the traceability of various significant moments in its solution and 3D-image of the finished composition of the two intersecting polyhedra, stripped of the working lines and subjected to rotation and translation.

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Report published in the Proceedings of the National Conference on "Education in the Information Society", Plovdiv, May, 2013

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The digitization practice for retro-converting of the mathematical periodicals, published by the Institute of Mathematics and Informatics, Bulgarian Academy of Sciences (IMI-BAS) and the followed benefits for long-term preserving and assuring open access to these materials is discussed in the article.

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Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2014

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The reasonable choice is a critical success factor for decision- making in the field of software engineering (SE). A case-driven comparative analysis has been introduced and a procedure for its systematic application has been suggested. The paper describes how the proposed method can be built in a general framework for SE activities. Some examples of experimental versions of the framework are brie y presented.

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Fault tree methodology is the most widespread risk assessment tool by which one is able to predict - in principle - the outcome of an event whenever it is reduced to simpler ones by the logic operations conjunction and disjunction according to the basics of Boolean algebra. The object of this work is to present an algorithm by which, using the corresponding computer code, one is able to predict - in practice - the outcome of an event whenever its fault tree is given in the usual form.

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In 1965 Levenshtein introduced the deletion correcting codes and found an asymptotically optimal family of 1-deletion correcting codes. During the years there has been a little or no research on t-deletion correcting codes for larger values of t. In this paper, we consider the problem of finding the maximal cardinality L2(n;t) of a binary t-deletion correcting code of length n. We construct an infinite family of binary t-deletion correcting codes. By computer search, we construct t-deletion codes for t = 2;3;4;5 with lengths n ≤ 30. Some of these codes improve on earlier results by Hirschberg-Fereira and Swart-Fereira. Finally, we prove a recursive upper bound on L2(n;t) which is asymptotically worse than the best known bounds, but gives better estimates for small values of n.

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This paper addresses the task of learning classifiers from streams of labelled data. In this case we can face the problem that the underlying concepts can change over time. The paper studies two mechanisms developed for dealing with changing concepts. Both are based on the time window idea. The first one forgets gradually, by assigning to the examples weight that gradually decreases over time. The second one uses a statistical test to detect changes in concept and then optimizes the size of the time window, aiming to maximise the classification accuracy on the new examples. Both methods are general in nature and can be used with any learning algorithm. The objectives of the conducted experiments were to compare the mechanisms and explore whether they can be combined to achieve a synergetic e ect. Results from experiments with three basic learning algorithms (kNN, ID3 and NBC) using four datasets are reported and discussed.

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In the present paper we investigate the life cycles of formalized theories that appear in decision making instruments and science. In few words mixed theories are build in the following steps: Initially a small collection of facts is the kernel of the theory. To express these facts we make a special formalized language. When the collection grows we add some inference rules and thus some axioms to compress the knowledge. The next step is to generalize these rules to all expressions in the formalized language. For these rules we introduce some conclusion procedure. In such a way we make small theories for restricted fields of the knowledge. The most important procedure is the mixing of these partial knowledge systems. In that step we glue the theories together and eliminate the contradictions. The last operation is the most complicated one and some simplifying procedures are proposed.

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This paper is part of a work in progress whose goal is to construct a fast, practical algorithm for the vertex separation (VS) of cactus graphs. We prove a \main theorem for cacti", a necessary and sufficient condition for the VS of a cactus graph being k. Further, we investigate the ensuing ramifications that prevent the construction of an algorithm based on that theorem only.