Abstract: The problem of finding the optimal join ordering executing a query to a relational database management system is a combinatorial optimization problem, which makes deterministic exhaustive solution search unacceptable for queries with a great number of joined relations. In this work an adaptive genetic algorithm with dynamic population size is proposed for optimizing large join queries. The performance of the algorithm is compared with that of several classical non-deterministic optimization algorithms. Experiments have been performed optimizing several random queries against a randomly generated data dictionary. The proposed adaptive genetic algorithm with probabilistic selection operator outperforms in a number of test runs the canonical genetic algorithm with Elitist selection as well as two common random search strategies and proves to be a viable alternative to existing non-deterministic optimization approaches.

Keywords: genetic algorithms, query optimization, join ordering, randomized algorithms

ACM Classification Keywords: H.2.4. Query processing, H.3.4. Performance evaluation (efficiency and effectiveness)

Link:

AN ADAPTIVE GENETIC ALGORITHM WITH DYNAMIC POPULATION SIZE FOR OPTIMIZING JOIN QUERIES

Stoyan Vellev

http://www.foibg.com/ibs_isc/ibs-02/IBS-02-p11.pdf

Abstract: This paper deals with the classification of news items in ePaper, a prototype system of a future personalized newspaper service on a mobile reading device. The ePaper system aggregates news items from various news providers and delivers to each subscribed user (reader) a personalized electronic newspaper, utilizing content-based and collaborative filtering methods. The ePaper can also provide users "standard" (i.e., not personalized) editions of selected newspapers, as well as browsing capabilities in the repository of news items. This paper concentrates on the automatic classification of incoming news using hierarchical news ontology. Based on this classification on one hand, and on the users' profiles on the other hand, the personalization engine of the system is able to provide a personalized paper to each user onto her mobile reading device.

Keywords: Classification, Electronic newspaper, Information filtering, Mobile device, Ontology, Personalization.

ACM Classification Keywords: H5.2. Information interfaces and presentation, H.3.3. Information Storage and Retrieval; information filtering, H.3.1. Content Analysis and Indexing

Link:

ONTOLOGY-BASED CLASSIFICATION OF NEWS IN AN ELECTRONIC NEWSPAPER

Lena Tenenboim, Bracha Shapira, Peretz Shoval

http://www.foibg.com/ibs_isc/ibs-02/IBS-02-p12.pdf

Abstract: Linguistic theory, cognitive, information, and mathematical modeling are all useful while we attempt to achieve a better understanding of the Language Faculty (LF). This cross-disciplinary approach will eventually lead to the identification of the key principles applicable in the systems of Natural Language Processing. The present work concentrates on the syntax-semantics interface. We start from recursive definitions and application of optimization principles, and gradually develop a formal model of syntactic operations. The result – a Fibonaccilike syntactic tree – is in fact an argument-based variant of the natural language syntax. This representation (argument-centered model, ACM) is derived by a recursive calculus that generates a mode which connects arguments and expresses relations between them. The reiterative operation assigns primary role to entities as the key components of syntactic structure. We provide experimental evidence in support of the argument-based model. We also show that mental computation of syntax is influenced by the inter-conceptual relations between the images of entities in a semantic space. Keywords: natural language, mathematical modeling, cognitive modeling ACM Classification Keywords: I.2 Artificial Intelligence, 1.2.0. Cognitive simulation,1.2.7. Natural language processing - Speech recognition and synthesis.

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EXPERIMENTAL SUPPORT OF ARGUMENT-BASED SYNTACTIC COMPUTATION

Velina Slavova, Alona Soschen

http://www.foibg.com/ibs_isc/ibs-02/IBS-02-p15.pdf

Abstract: In this study, we showed various approachs implemented in Artificial Neural Networks for network resources management and Internet congestion control. Through a training process, Neural Networks can determine nonlinear relationships in a data set by associating the corresponding outputs to input patterns. Therefore, the application of these networks to Traffic Engineering can help achieve its general objective: “intelligent” agents or systems capable of adapting dataflow according to available resources. In this article, we analyze the opportunity and feasibility to apply Artificial Neural Networks to a number of tasks related to Traffic Engineering. In previous sections, we present the basics of each one of these disciplines, which are associated to Artificial Intelligence and Computer Networks respectively.

Keywords: Traffic Engineering, Artificial Neural Networks, Internet Traffic Engineering, Computer Networks.

ACM Classification Keywords: D.4.4 Communications Management

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STUDY OF THE APPLICATION OF NEURAL NETWORKS IN INTERNET TRAFFIC ENGINEERING

Nelson Piedra, Janneth Chicaiza, Jorge López, Jesús García

http://www.foibg.com/ibs_isc/ibs-02/IBS-02-p05.pdf

Abstract: This paper presents an extended behavior of networks of evolutionary processors. Usually, such nets are able to solve NP-complete problems working with symbolic information. Information can evolve applying rules and can be communicated though the net provided some constraints are verified. These nets are based on biological behavior of membrane systems, but transformed into a suitable computational model. Only symbolic information is communicated. This paper proposes to communicate evolution rules as well as symbolic information. This idea arises from the DNA structure in living cells, such DNA codes information and operations and it can be sent to other cells. Extended nets could be considered as a superset of networks of evolutionary processors since permitting and forbidden constraints can be written in order to deny rules communication.

Keywords: Networks of Evolutionary Processors, Membrane Systems, and Natural Computation.

ACM Classification Keywords: F.1.2 Modes of Computation, I.6.1 Simulation Theory, H.1.1 Systems and Information Theory

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EXTENDED NETWORKS OF EVOLUTIONARY PROCESSORS

Luis Fernando de Mingo, Nuria Gómez Blas, Francisco Gisbert, Miguel A. Peña

http://www.foibg.com/ibs_isc/ibs-02/IBS-02-p01.pdf

Abstract: In this paper, a new method for offline handwriting recognition is presented. A robust algorithm for handwriting segmentation has been described here with the help of which individual characters can be segmented from a word selected from a paragraph of handwritten text image which is given as input to the module. Then each of the segmented characters are converted into column vectors of 625 values that are later fed into the advanced neural network setup that has been designed in the form of text files. The networks has been designed with quadruple layered neural network with 625 input and 26 output neurons each corresponding to a character from a-z, the outputs of all the four networks is fed into the genetic algorithm which has been developed using the concepts of correlation, with the help of this the overall network is optimized with the help of genetic algorithm thus providing us with recognized outputs with great efficiency of 71%.

Keywords: Handwriting Recognition, Segementation, Artificial Neural Networks, Genetic Algorithm.

ACM Classification Keywords: I.2 Artificial Intelligence, I.4 Image processing and Computer Vision, I.5 Pattern Recognition.

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OFFLINE HANDWRITING RECOGNITION USING GENETIC ALGORITHM

Shashank Mathur, Vaibhav Aggarwal, Himanshu Joshi, Anil Ahlawat

http://www.foibg.com/ibs_isc/ibs-02/IBS-02-p03.pdf

Abstract: The aim of this work is distributed genetic algorithm implementation (so called island algorithm) to accelerate the optimum searching process in space of solutions. Distributed genetic algorithm has also smaller chances to fall in local optimum. This conception depends on mutual cooperation of the clients which realize separate working of genetic algorithms on local machines. As a tool for implementation of distributed genetic algorithm, created to produce net's applications Java technology was chosen. In Java technology, there is a technique of remote methods invocation - Java RMI. By means of invoking remote methods it can send objects between clients and server RMI.

Keywords: Genetic Algorithms and Evolutionary

ACM Classification Keywords: G.1.6 Optimalization – Global optimalization

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DISTRIBUTED GENETIC ALGORITHM IMPLEMENTATION BY MEANS OF REMOTE METHODS INVOCATION TECHNIQUE – JAVA RMI

Lukasz Maciura, Galina Setlak

http://www.foibg.com/ibs_isc/ibs-02/IBS-02-p10.pdf

Abstract: Floods represent the most devastating natural hazards in the world, affecting more people and causing more property damage than any other natural phenomena. One of the important problems associated with flood monitoring is flood extent extraction from satellite imagery, since it is impractical to acquire the flood area through field observations. This paper presents a method to flood extent extraction from synthetic-aperture radar (SAR) images that is based on intelligent computations. In particular, we apply artificial neural networks, self-organizing Kohonen’s maps (SOMs), for SAR image segmentation and classification. We tested our approach to process data from three different satellite sensors: ERS-2/SAR (during flooding on Tisza river, Ukraine and Hungary, 2001), ENVISAT/ASAR WSM (Wide Swath Mode) and RADARSAT-1 (during flooding on Huaihe river, China, 2007). Obtained results showed the efficiency of our approach.

Keywords: flood extent extraction, neural networks, data fusion, SAR images.

ACM Classification Keywords: I.4.6 Segmentation - Pixel classification

Link:

INTELLIGENT COMPUTATIONS FOR FLOOD MONITORING

Nataliia Kussul, Andrii Shelestov, Serhiy Skakun

http://www.foibg.com/ibs_isc/ibs-02/IBS-02-p06.pdf

Abstract: Mobile messaging is an integral and vital part of the mobile industry and contributes significantly to worldwide total mobile service revenues. In today’s competitive world, differentiation is a significant factor in the success of the business communication. SMS (Short Message Service) provides a powerful vehicle for service differentiation. What is missing, however, is the availability of personalized SMS messages. In particular, the exploitation of user profile information allows a selection and content delivery that meets preferences and interests for the individual. Personalization of mobile messages is important in today’s service-oriented society, and has proven to be crucial for the acceptance of services provided by the mobile telecommunication networks. In this paper we focus on user profile description and the mechanism for delivering the relevant information to the mobile user in accordance with his/her profile. Keywords: mobile text messages, user profile, personalization, question-answering system ACM Classification Keywords: I.2 Artificial intelligence: I.2.7 Natural Language Processing: Text analysis.

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PERSONALIZED QUESTION-ANSWERING MOBILE SYSTEM

Lee Johnston, Vladimir Lovitskii, Ian Price, Michael Thrasher, David Traynor

http://www.foibg.com/ibs_isc/ibs-02/IBS-02-p16.pdf

Abstract: In this paper we propose a model of encoding data into DNA strands so that this data can be used in the simulation of a genetic algorithm based on molecular operations. DNA computing is an impressive computational model that needs algorithms to work properly and efficiently. The first problem when trying to apply an algorithm in DNA computing must be how to codify the data that the algorithm will use. In a genetic algorithm the first objective must be to codify the genes, which are the main data. A concrete encoding of the genes in a single DNA strand is presented and we discuss what this codification is suitable for. Previous work on DNA coding defined bond-free languages which several properties assuring the stability of any DNA word of such a language. We prove that a bond-free language is necessary but not sufficient to codify a gene giving the correct codification

Keywords: DNA Computing, Bond-Free? Languages, Genetic Algorithms.

ACM Classification Keywords: I.6. Simulation and Modelling, B.7.1 Advanced Technologies, J.3 Biology and Genetics

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A DNA CODIFICATION FOR GENETIC ALGORITHMS SIMULATION

Ángel Goñi, Francisco José Cisneros, Paula Cordero, Juan Castellanos

http://www.foibg.com/ibs_isc/ibs-02/IBS-02-p09.pdf

Abstract: We want to make a program which can play any game or in other words we want to make AI. It is impossible to include in this program the rules of all games and that is why our program should be able to find these rules by itself. We cannot solve this problem in the general case. So, our first task will be to make a program which is able to find the rules of the Tic-Tac-Toe? game. Even this task is too complicated. So, first we will try to find these rules manually and this will help us make a program which is able to find these rules automatically.

Keywords: Artificial Intelligence, Games, Automated reasoning.

ACM Classification Keywords: I.2.0 Artificial Intelligence - Philosophical foundations

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SECOND ATTEMPT TO BUILD A MODEL OF THE TIC-TAC-TOE GAME 1

Dimiter Dobrev

http://www.foibg.com/ibs_isc/ibs-02/IBS-02-p19.pdf

Abstract: Formal grammars can used for describing complex repeatable structures such as DNA sequences. In this paper, we describe the structural composition of DNA sequences using a context-free stochastic L-grammar. L-grammars are a special class of parallel grammars that can model the growth of living organisms, e.g. plant development, and model the morphology of a variety of organisms. We believe that parallel grammars also can be used for modeling genetic mechanisms and sequences such as promoters. Promoters are short regulatory DNA sequences located upstream of a gene. Detection of promoters in DNA sequences is important for successful gene prediction. Promoters can be recognized by certain patterns that are conserved within a species, but there are many exceptions which makes the promoter recognition a complex problem. We replace the problem of promoter recognition by induction of context-free stochastic L-grammar rules, which are later used for the structural analysis of promoter sequences. L-grammar rules are derived automatically from the drosophila and vertebrate promoter datasets using a genetic programming technique and their fitness is evaluated using a Support Vector Machine (SVM) classifier. The artificial promoter sequences generated using the derived Lgrammar rules are analyzed and compared with natural promoter sequences.

Keywords: stochastic context-free L-grammar, DNA modeling, machine learning, data mining, bioinformatics.

ACM Classification Keywords: F.4.2 Grammars and Other Rewriting Systems; I.2.6 Knowledge acquisition; I.5 Pattern recognition; J.3 Life and medical sciences.

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DERIVATION OF CONTEXT-FREE STOCHASTIC L-GRAMMAR RULES FOR PROMOTER SEQUENCE MODELING USING SUPPORT VECTOR MACHINE

Robertas Damaševičius

http://www.foibg.com/ibs_isc/ibs-02/IBS-02-p13.pdf

Abstract: Chaos control is a concept that recently acquiring more attention among the research community, concerning the fields of engineering, physics, chemistry, biology and mathematic. This paper presents a method to simultaneous control of deterministic chaos in several nonlinear dynamical systems. A radial basis function networks (RBFNs) has been used to control chaotic trajectories in the equilibrium points. Such neural network improves results, avoiding those problems that appear in other control methods, being also efficient dealing with a relatively small random dynamical noise.

Keywords: Neural Network, Radial basis function, Backpropagation, Chaotic Dynamic Systems, Control Feedback Methods.

ACM Classification Keywords: F.1.1 Models of Computation: Self-modifying machines (neural networks); F.1.2 Modes of Computation: Alternation and nondeterminism; G.1.7 Ordinary Differential Equations: Chaotic systems;

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SIMULTANEOUS CONTROL OF CHAOTIC SYSTEMS USING RBF NETWORKS

Angel Castellanos, Rafael Gonzalo, Ana Martinez

http://www.foibg.com/ibs_isc/ibs-02/IBS-02-p04.pdf

Abstract: This paper describes the followed methodology to automatically generate titles for a corpus of questions that belong to sociological opinion polls. Titles for questions have a twofold function: (1) they are the input of user searches and (2) they inform about the whole contents of the question and possible answer options. Thus, generation of titles can be considered as a case of automatic summarization. However, the fact that summarization had to be performed over very short texts together with the aforementioned quality conditions imposed on new generated titles led the authors to follow knowledge-rich and domain-dependent strategies for summarization, disregarding the more frequent extractive techniques for summarization.

Keywords: Summarization, text processing, subjective clustering.

ACM Classification Keywords: H.3.1 Content Analysis and Indexing

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AUTOMATIC GENERATION OF TITLES FOR A CORPUS OF QUESTIONS

Jesús Cardeñosa, Carolina Gallardo

http://www.foibg.com/ibs_isc/ibs-02/IBS-02-p14.pdf

Abstract: The best results in the application of computer science systems to automatic translation are obtained in word processing when texts pertain to specific thematic areas, with structures well defined and a concise and limited lexicon. In this article we present a plan of systematic work for the analysis and generation of language applied to the field of pharmaceutical leaflet, a type of document characterized by format rigidity and precision in the use of lexicon. We propose a solution based in the use of one interlingua as language pivot between source and target languages; we are considering Spanish and Arab languages in this case of application.

Keywords: Controlled languages; Interlingua-based Machine Translation

ACM Classification Keywords: I.2.7 Natural Language Processing

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METHODOLOGY FOR LANGUAGE ANALYSIS AND GENERATION IN CLOSED DOMAINS: PHARMACEUTICAL LEAFLET

Jesús Cardeñosa, Carolina Gallardo, Adriana Toni

http://www.foibg.com/ibs_isc/ibs-02/IBS-02-p17.pdf

Abstract: in the paper new non-conventional growing neural network is proposed. It coincides with the Cascade- Correlation Learning Architecture structurally, but uses ortho-neurons as basic structure units, which can be adjusted using linear tuning procedures. As compared with conventional approximating neural networks proposed approach allows significantly to reduce time required for weight coefficients adjustment and the training dataset size.

Keywords: orthogonal activation functions, ortho-synapse, ortho-neuron, cascade orthogonal neural network.

ACM Classification Keywords: I.2.6 Learning – Connectionism and neural nets

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THE CASCADE ORTHOGONAL NEURAL NETWORK

Yevgeniy Bodyanskiy, Artem Dolotov, Iryna Pliss, Yevgen Viktorov

http://www.foibg.com/ibs_isc/ibs-02/IBS-02-p02.pdf

Abstract: In this paper an outliers resistant learning algorithm for the radial-basis-fuzzy-wavelet-neural network based on R. Welsh criterion is proposed. Suggested learning algorithm under consideration allows the signals processing in presence of significant noise level and outliers. The robust learning algorithm efficiency is investigated and confirmed by the number of experiments including medical applications.

Keywords: computational intelligence, hybrid architecture, wavelet, fuzzy-wavelet neural network, robust learning algorithm, outliers resistant.

ACM Classification Keywords: I.2.6 Learning – Connectionism and neural nets.

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OUTLIERS RESISTANT LEARNING ALGORITHM FOR RADIAL-BASIS-FUZZY-WAVELET-NEURAL NETWORK IN STOMACH ACUTE INJURY DIAGNOSIS TASKS

Yevgeniy Bodyanskiy, Oleksandr Pavlov, Olena Vynokurova

http://www.foibg.com/ibs_isc/ibs-02/IBS-02-p07.pdf

Abstract: An original heuristic algorithm of sequential two-block decomposition of partial Boolean functions is researched. The key combinatorial task is considered: finding of suitable partition on the set of arguments, i. e. such one, on which the function is separable. The search for suitable partition is essentially accelerated by preliminary detection of its traces. Within the framework of the experimental system the efficiency of the algorithm is evaluated, the boundaries of its practical application are determined.

Keywords: Partial Boolean Functions, Heuristic Method of Decomposition

ACM Classification Keywords: B.6. Combinational logic, switching theory, automatic synthesis, optimization.

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IMPLEMENTATION OF A HEURISTIC METHOD OF DECOMPOSITION OF PARTIAL BOOLEAN FUNCTIONS

Arkadij Zakrevskij, Nikolai Toropov

http://www.foibg.com/ibs_isc/ibs-01/IBS-01-p08.pdf

Abstract: We consider an uncertain version of the scheduling problem to sequence set of jobs J on a single machine with minimizing the weighted total flow time, provided that processing time of a job can take on any real value from the given closed interval. It is assumed that job processing time is unknown random variable before the actual occurrence of this time, where probability distribution of such a variable between the given lower and upper bounds is unknown before scheduling. We develop the dominance relations on a set of jobs J. The necessary and sufficient conditions for a job domination may be tested in polynomial time of the number n = |J| of jobs. If there is no a domination within some subset of set J, heuristic procedure to minimize the weighted total flow time is used for sequencing the jobs from such a subset. The computational experiments for randomly generated single-machine scheduling problems with n ≤ 700 show that the developed dominance relations are quite helpful in minimizing the weighted total flow time of n jobs with uncertain processing times.

Keywords: Scheduling, robustness and sensitivity analysis.

ACM Classification Keywords: F.2.2 Nonnumerical algorithms and problems: Sequencing and scheduling.

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SEQUENCING JOBS WITH UNCERTAIN PROCESSING TIMES AND MINIMIZING THE WEIGHTED TOTAL FLOW TIME

Yuri Sotskov, Natalja Egorova

http://www.foibg.com/ibs_isc/ibs-01/IBS-01-p12.pdf

Abstract: The problem of finite automata minimization is important for software and hardware designing. Different types of automata are used for modeling systems or machines with finite number of states. The limitation of number of states gives savings in resources and time. In this article we show specific type of probabilistic automata: the reactive probabilistic finite automata with accepting states (in brief the reactive probabilistic automata), and definitions of languages accepted by it. We present definition of bisimulation relation for automata's states and define relation of indistinguishableness of automata states, on base of which we could effectuate automata minimization. Next we present detailed algorithm reactive probabilistic automata’s minimization with determination of its complexity and analyse example solved with help of this algorithm.

Keywords: minimization algorithm, reactive probabilistic automata, equivalence of states of automata, bisimulation relation.

ACM Classification Keywords: F. Theory of Computation, F.1 Computation by Abstract Devices, F.1.1 Models of Computation, Automata; F.4 Mathematical logic and formal languages, F.4.3 Formal Languages

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MINIMIZATION OF REACTIVE PROBABILISTIC AUTOMATA

Olga Siedlecka

http://www.foibg.com/ibs_isc/ibs-01/IBS-01-p10.pdf

Abstract: A model of an overall telecommunication network with virtual circuits switching, in stationary state, with Bernoulli-Poisson-Pascal? (BPP) input flow, repeated calls, limited number of homogeneous terminals and 8 types of losses is considered. One of the main problems of network redimensioning is estimation of the traffic offered in the network because it reflects on finding of necessary number of equivalent switching lines on the basis of the consideration of detailed users behavior and target Quality of Service (QoS). The aim of this paper is to find a new solution of Network Redimensioning Task (NRDT) 4, taking into account the inconvenience of necessary measurements, not considered in the previous research 5. The results are applicable for redimensioning of every (virtual) circuit switching telecommunication system, both for wireline and wireless systems (GSM, PSTN, ISDN and BISDN). For packet - switching networks proposed approach may be used as a comparison basis and when they work in circuit switching mode (e.g. VoIP).

Keywords: Overall Network Traffic, Offered Traffic, Virtual Circuits Switching.

ACM Classification Keywords: C.2.1 Network Architecture and Design; C.2.3 Network Operations; C.4 Performance of Systems.

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PRIMARY AND SECONDARY EMPIRICAL VALUES IN NETWORK REDIMENSIONING

Emiliya Saranova

http://www.foibg.com/ibs_isc/ibs-01/IBS-01-p07.pdf

Abstract: The finding that Pareto distributions are adequate to model Internet packet interarrival times has motivated the proposal of methods to evaluate steady-state performance measures of Pareto/D/1/k queues. Some limited analytical derivation for queue models has been proposed in the literature, but their solutions are often of a great mathematical challenge. To overcome such limitations, simulation tools that can deal with general queueing system must be developed. Despite certain limitations, simulation algorithms provide a mechanism to obtain insight and good numerical approximation to parameters of queues. In this work, we give an overview of some of these methods and compare them with our simulation approach, which are suited to solve queues with Generalized-Pareto? interarrival time distributions. The paper discusses the properties and use of the Pareto distribution. We propose a real time trace simulation model for estimating the steady-state probability showing the tail-raising effect, loss probability, delay of the Pareto/D/1/k queue and make a comparison with M/D/1/k. The background on Internet traffic will help to do the evaluation correctly. This model can be used to study the longtailed queueing systems. We close the paper with some general comments and offer thoughts about future work.

Keywords: Pareto distribution, delay system, queueing analyses, simulation model, peak traffic modelling;

ACM Classification Keywords: G.3 Probability and statistics: queueing theory, I.6.5 Model development

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EVALUATION OF PARETO/D/1/K QUEUE BY SIMULATION

Seferin Mirtchev, Rossitza Goleva

http://www.foibg.com/ibs_isc/ibs-01/IBS-01-p06.pdf

Abstract: In the works 1, 2 we proposed an approach of forming a consensus of experts’ statements for the case of forecasting of qualitative and quantitative variable. In this paper, we present a method of aggregating sets of individual statements into a collective one for the general case of forecasting of multidimensional heterogeneous variable.

Keywords: multidimensional variable, expert statements, coordination.

ACM Classification Keywords: I.2.6. Artificial Intelligence - knowledge acquisition.

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MULTIDIMENSIONAL HETEROGENEOUS VARIABLE PREDICTION BASED ON EXPERTS’ STATEMENTS∗

Gennadiy Lbov, Maxim Gerasimov

http://www.foibg.com/ibs_isc/ibs-01/IBS-01-p13.pdf

Abstract: The article presents an algorithm for translation the system, described by MSC document into Petri Net modulo strong bisimulation. Obtained net can be later used for determining various systems' properties. Example of correction error in original system with using if described algorithm presented.

Keywords: MSC, Petri Net, model checking, verification, RAD.

ACM Classification Keywords: D.2.4 Software/Program Verification - Formal methods, Model checking

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EXTENDED ALGORITHM FOR TRANSLATION OF MSC-DIAGRAMS INTO PETRI NETS

Sergii Kryvyy, Oleksiy Chugayenko

http://www.foibg.com/ibs_isc/ibs-01/IBS-01-p09.pdf

Abstract: Transition P systems are computational models based on basic features of biological membranes and the observation of biochemical processes. In these models, membrane contains objects multisets, which evolve according to given evolution rules. In the field of Transition P systems implementation, it has been detected the necessity to determine whichever time are going to take active evolution rules application in membranes. In addition, to have time estimations of rules application makes possible to take important decisions related to the hardware / software architectures design. In this paper we propose a new evolution rules application algorithm oriented towards the implementation of Transition P systems. The developed algorithm is sequential and, it has a linear order complexity in the number of evolution rules. Moreover, it obtains the smaller execution times, compared with the preceding algorithms. Therefore the algorithm is very appropriate for the implementation of Transition P systems in sequential devices.

Keywords: Natural Computing, Membrane computing, Transition P System, Rules Application Algorithms

ACM Classification Keywords: D.1.m Miscellaneous – Natural Computing

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FAST LINEAR ALGORITHM FOR ACTIVE RULES APPLICATION IN TRANSITION P SYSTEMS

Francisco Javier Gil, Jorge Tejedor, Luis Fernández

http://www.foibg.com/ibs_isc/ibs-01/IBS-01-p05.pdf