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Fundamenta Informaticae is an international journal publishing original research results in all areas of theoretical computer science. Papers are encouraged contributing:
- solutions by mathematical methods of problems emerging in computer science
- solutions of mathematical problems inspired by computer science.
Topics of interest include (but are not restricted to): theory of computing, complexity theory, algorithms and data structures, computational aspects of combinatorics and graph theory, programming language theory, theoretical aspects of programming languages, computer-aided verification, computer science logic, database theory, logic programming, automated deduction, formal languages and automata theory, concurrency and distributed computing, cryptography and security, theoretical issues in artificial intelligence, machine learning, pattern recognition, algorithmic game theory, bioinformatics and computational biology, quantum computing, probabilistic methods, & algebraic and categorical methods.
Authors: Nowak, Agnieszka | Wakulicz-Deja, Alicja | Bachliński, Sebastian
Article Type: Research Article
Abstract: Optimization of the speech recognition process is aiming at achieving short time of classification (speech to text system), while preserving the content of speech signal description, and all necessary details of speech signal in considered application. The goal of parametrization of the human's speech is to eliminate of those physical features of speech signal, that do not bring any useful information (e.g., frequency of laryngeal tone, timbre of voice). The purpose of the parametrization of a …speech signal is to minimize the volume of information that is to be analyzed. Our experiments suggest that using the cluster analysis method with agglomerative hierarchical technique is very helpful in finding relationships between speech phones. It lets us accelerate the process of speech recognition, simply because it is not necessary to analyze each phone separately and comparing it with an unclassified object. This principle has been carried to hidden Markov models. To organize those models we use the cluster analysis method with hierarchical techniques. Each model represents a single sequence of speech (probably the phone sequence). At the "top" of the structure we have models of phones in the most general context. When we go thru this structure to the bottom, there are models of phones in particular context. By the context we understand the juxtaposition the different phones. Show more
Citation: Fundamenta Informaticae, vol. 72, no. 1-3, pp. 283-293, 2006
Authors: Nguyen, Trung Thanh | Willis, Claire P. | Paddon, Derek J. | Nguyen, Sinh Hoa | Nguyen, Hung Son
Article Type: Research Article
Abstract: Sunspots are the subject of interest to many astronomers and solar physicists. Sunspot observation, analysis and classification form an important part of furthering the knowledge about the Sun. Sunspot classification is a manual and very labor intensive process that could be automated if successfully learned by a machine. This paper presents machine learning approaches to the problem of sunspot classification. The classification scheme attempted was the seven-class Modified Zurich scheme [18]. The data was obtained by …processing NASA SOHO/MDI satellite images to extract individual sunspots and their attributes. A series of experiments were performed on the training dataset with an aim of learning sunspot classification and improving prediction accuracy. The experiments involved using decision trees, rough sets, hierarchical clustering and layered learning methods. Sunspots were characterized by their visual properties like size, shape, positions, and were manually classified by comparing extracted sunspots with corresponding active region maps (ARMaps) from the Mees Observatory at the Institute for Astronomy, University of Hawaii. Show more
Keywords: sunspot classification, layered learning, rough sets, machine learning
Citation: Fundamenta Informaticae, vol. 72, no. 1-3, pp. 295-309, 2006
Authors: Ochmański, Edward | Pieckowska, Joanna
Article Type: Research Article
Abstract: Trace nets are a generalization of elementary nets, proposed by Badouel and Darondeau. They admit phenomena, unknown in traditional nets. For instance, in trace nets does not hold the "diamond property". For this reason, we propose a more precise definition of conflict, applicable to trace nets, and study occurrences of conflicts and existence of conflict-free runs in such nets. Main result of the paper says that any just computation in a trace net, starting from a …conflict state, contains a conflict step. This result allows to construct an algorithm, selecting only conflict-free just computations from among all computations of a given net. All results of the paper hold for elementary nets, as they are a subclass of trace nets. Show more
Keywords: Petri nets, trace nets, conflicts
Citation: Fundamenta Informaticae, vol. 72, no. 1-3, pp. 311-321, 2006
Authors: Ochmański, Edward | Stawikowska, Krystyna
Article Type: Research Article
Abstract: The paper deals with star-free languages in free monoids and trace monoids. We introduce the notion of star-free star, fundamental for this paper, and show that the classes of star-free languages and star-free star languages coincide. Then, using this result, we obtain a general characterization of star-free trace languages, containing a result of Guaiana/Restivo/Salemi (star-free=aperiodic in trace monoids), originally proved in a more involved, combinatorial way.
Keywords: star-free languages, traces languages
Citation: Fundamenta Informaticae, vol. 72, no. 1-3, pp. 323-331, 2006
Authors: Redziejowski, Roman R.
Article Type: Research Article
Abstract: The notion of an associative omega-product is applied to processes. Processes are one of the ways to represent behavior of Petri nets. They have been studied for some years as an alternative to traces and dependence graphs. One advantage of processes, as compared to traces, is a very simple way to define infinite concatenation. We take a closer look at this operation, and show that it is a free associative omega-product of finite processes. Its associativity …simplifies some arguments about infinite concatenation, as illustrated by the proof of interleaving theorem. Show more
Citation: Fundamenta Informaticae, vol. 72, no. 1-3, pp. 333-345, 2006
Authors: Shilov, N.V. | Garanina, N.O. | Choe, K.-M.
Article Type: Research Article
Abstract: We present (update+abstraction) algorithm for model checking a fusion of Computation Tree Logic and Propositional Logic of Knowledge in systems with the perfect recall synchronous semantics. It has been already known that the problem is decidable with a non-elementary lower bound. The decidability follows from interpretation of the problem in a so-called Chain Logic and then in the Second Order Logic of Monadic Successors. This time we give a direct algorithm for model checking and detailed …time upper bound where a number of different parameters are taken into count (i.e. a number of agents, a number of states, knowledge depth, formula size). We present a toy experiment with this algorithm that encourages our hope that the algorithm can be used in practice. Show more
Citation: Fundamenta Informaticae, vol. 72, no. 1-3, pp. 347-361, 2006
Authors: Skowron, Andrzej | Stepaniuk, Jarosław | Peters, James | Swiniarski, Roman
Article Type: Research Article
Abstract: This paper considers the problem of how to establish calculi of approximation spaces. Approximation spaces considered in the context of rough sets were introduced by Zdzisław Pawlak more than two decades ago. In general, a calculus of approximation spaces is a system for combining, describing, measuring, reasoning about, and performing operations on approximation spaces. An approach to achieving a calculus of approximation spaces that provides a basis for approximating reasoning in distributed systems …of cooperating agents is considered in this paper. Examples of basic concepts are given throughout this paper to illustrate how approximation spaces can be beneficially used in many settings, in particular for complex concept approximation. The contribution of this paper is the presentation of a framework for calculi of approximation spaces useful for approximate reasoning by cooperating agents. Show more
Keywords: rough sets, approximation spaces, concept approximation, learning, approximate reasoning
Citation: Fundamenta Informaticae, vol. 72, no. 1-3, pp. 363-378, 2006
Authors: Stefanowski, Jerzy | Wilk, Szymon
Article Type: Research Article
Abstract: The paper addresses problems of improving performance of rule-based classifiers constructed from imbalanced data sets, i.e., data sets where the minority class of primary importance is under-represented in comparison to majority classes. We introduced two techniques to detect and process inconsistent examples from the majority classes in the boundary between the minority and majority classes. Both these techniques differ in the way of processing inconsistent boundary examples from the majority classes. The first …approach removes them, while the other relabels them as belonging to the minority class. The experiments showed that the best results were obtained for the filtering technique, where inconsistent majority class examples were reassigned to the minority class, combined with a classifier composed of decision rules generated by the MODLEM algorithm. Show more
Keywords: Knowledge Discovery, Data Mining, Rough Sets, Classification, Class Imbalance, Rule Induction
Citation: Fundamenta Informaticae, vol. 72, no. 1-3, pp. 379-391, 2006
Authors: Suraj, Zbigniew | Gayar, Neamat El | Delimata, Pawel
Article Type: Research Article
Abstract: During the past decade methods of multiple classifier systems have been developed as a practical and effective solution for a variety of challenging applications. A wide number of techniques and methodologies for combining classifiers have been proposed in the past years in literature. In our work we present a new approach to multiple classifier systems using rough sets to construct classifier ensembles. Rough set methods provide us with various useful techniques of data classification. …In the paper, we also present a method of reduction of the data set with the use of multiple classifiers. Reduction of the data set is performed on attributes and allows to decrease the number of conditional attributes in the decision table. Our method helps to decrease the number of conditional attributes of the data with a small loss on classification accuracy. Show more
Keywords: multiple classifier systems, k-NN, reduction, feature selection
Citation: Fundamenta Informaticae, vol. 72, no. 1-3, pp. 393-406, 2006
Authors: Winkowski, Józef
Article Type: Research Article
Abstract: The paper is concerned with algebras which can be obtained by endowing sets of processes of Petri nets with a sequential and a parallel composition. The considered algebras are categories with additional structures and special properties. It is shown that all structures which enjoy such properties can be represented as algebras of processes of Petri nets.
Keywords: Petri nets, states, processes, sequential composition, parallel composition, category, partial monoid
Citation: Fundamenta Informaticae, vol. 72, no. 1-3, pp. 407-420, 2006
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