Abstract: The main features of virtual organizations are outlined. The mathematical models of functioning of virtual organization are offered on the basis of theory of queuing systems. Characteristics of efficiency are examined.

Keywords: virtual enterprise, virtual laboratory, queuing system.

ACM Classification Keywords: I.6.4 Model Validation and Analysis; K.6.1 Project and People Management - Systems analysis and design.

Link:

BIVIRTUAL ORGANIZATION AS A QUEUING SYSTEM

Tetiana Palonna, Iurii Palonnyi

http://www.foibg.com/ijitk/ijitk-vol02/ijitk02-3-p17.pdf

Abstract: The purpose of the current paper is to present the developed methodology of viable model based enterprise management, which is needed for modern enterprises to survive and growth in the information age century. The approach is based on Beer’s viable system model and uses it as a basis of the information technology implementation and development. The enterprise is viewed as a cybernetic system which functioning is controlled from the same rules as for every living system.

Keywords: enterprise strategy, viable system model, enterprise model, neural network, artificial intelligence, cybernetics, business trends.

ACM Classification Keywords: I.6.3 Simulation and Modeling: Applications; I.2.6 Artificial Intelligence: Neural nets

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VIABLE MODEL OF THE ENTERPRISE – A CYBERNETIC APPROACH FOR IMPLEMENTING THE INFORMATION TECHNOLOGIES IN MANAGEMENT

Todorka Kovacheva

http://www.foibg.com/ijita/vol13/ijita13-4-p06.pdf

Abstract: Enterprises in growing markets with transitional economy nowadays encounter extreme necessity to change their structures and improve business processes. In order to support knowledge processes within organizational change initiative enterprises can use business modeling tools. On one hand software vendors suggest many tools of this kind, but on the other hand growing markets with transitional economy determine quite special requirements for such tools. This article reveals these requirements, assesses existing business modeling tools using these requirements and describes ORG-Master as a tool specially created for support of process improvement initiatives in the growing markets with transitional economy.

Keywords: Business information modeling, business modeling, knowledge process, organizational change, business process improvement, growing markets, transitional economy.

ACM Classification Keywords: I.6.3 Simulation and Modeling: Applications

Link:

USING ORG-MASTER FOR KNOWLEDGE BASED ORGANIZATIONAL CHANGE

Dmitry Kudryavtsev, Lev Grigoriev, Valentina Kislova, Alexey Zablotsky

http://www.foibg.com/ijita/vol13/ijita13-2-p05.pdf

Abstract: Research and development of mathematical model of optimum distribution of resources (basically financial) for maintenance of the new (raised) quality (reliability) of complex system concerning, which the decision on its re-structuring is accepted, is stated. The final model gives answers (algorithm of calculation) to questions: how many elements of system to allocate on modernization, which elements, up to what level of depth modernization of each of allocated is necessary, and optimum answers are by criterion of minimization of financial charges.

Keywords: system, re-structuring, quality, reliability.

ACM Classification Keywords: I.6.3 Simulation and Modeling: Applications

Link:

MATHEMATICAL MODEL OF RE-STRUCTURING COMPLEX TECHNICAL AND ECONOMIC STRUCTURES

May Kornijchuk, Inna Sovtus, Eugeny Tsaregradskyy

http://www.foibg.com/ijita/vol12/ijita12-2-p09.pdf

Abstract: Active monitoring and problem of non-stable of sound signal parameters in the regime of piling up response signal of environment is under consideration. Math model of testing object by set of weak stationary dynamic actions is offered. The response of structures to the set of signals is under processing for getting important information about object condition in high frequency band. Making decision procedure by using researcher’s heuristic and aprioristic knowledge is discussed as well. As an example the result of numerical solution is given.

Keywords: math model, active monitoring, set of weak stationary dynamic actions.

ACM Classification Keywords: I.6.1 Simulation Theory.

Link:

ACTIVE MONITORING AND DECISION MAKING PROBLEM

Sergey Mostovoi, Vasiliy Mostovoi

http://www.foibg.com/ijita/vol12/ijita12-2-p11.pdf

Abstract: This paper describes a method of signal preprocessing under active monitoring. Suppose we want to solve the inverse problem of getting the response of a medium to one powerful signal, which is equivalent to obtaining the transmission function of the medium, but do not have an opportunity to conduct such an experiment (it might be too expensive or harmful for the environment). Practically the problem can be reduced to obtaining the transmission function of the medium. In this case we can conduct a series of experiments of relatively low power and superpose the response signals. However, this method is conjugated with considerable loss of information (especially in the high frequency domain) due to fluctuations of the phase, the frequency and the starting time of each individual experiment. The preprocessing technique presented in this paper allows us to substantially restore the response of the medium and consequently to find a better estimate for the transmission function. This technique is based on expanding the initial signal into the system of orthogonal functions.

Keywords: mathematical modelling, active monitoring, frequency and phase fluctuation.

ACM Classification Keywords: I.6.1 Simulation Theory.

Link:

SIGNAL PROCESSING UNDER ACTIVE MONITORING

Oleksii Mostovyi

http://www.foibg.com/ijita/vol12/ijita12-3-p08.pdf

Abstract: In this paper a computational mode is presented base on DNA molecules. This model incorporates the theoretical simulation of the principal operations in genetic algorithms. It defines the way of coding of individuals, crossing and the introduction of the individuals so created into the population. It resolves satisfactorily the problems of fitness coding. It shows also the model projection for the resolution of TSP. This is the basic step that will allow the resolution of larger examples of search problems beyond the scope of exact exponentially sized DNA algorithms like the proposed by Adleman Adleman, 1994 and Lipton Lipton, 1995.

Keywords: Genetic Algorithms, Fitness Function, DNA Computing, Evolutionary Computing.

ACM Classification Keywords: I.6. Simulation and Modelling, F.m. Theory of Computation

Link:

DNA SIMULATION OF GENETIC ALGORITHMS: FITNESS COMPUTATION1

Maria Calvino, Nuria Gomez, Luis F. Mingo

http://www.foibg.com/ijita/vol14/ijita14-3-p03.pdf

Abstract: In this paper it is explained how to solve a fully connected N-City? travelling salesman problem (TSP) using a genetic algorithm. A crossover operator to use in the simulation of a genetic algorithm (GA) with DNA is presented. The aim of the paper is to follow the path of creating a new computational model based on DNA molecules and genetic operations. This paper solves the problem of exponentially size algorithms in DNA computing by using biological methods and techniques. After individual encoding and fitness evaluation, a protocol of the next step in a GA, crossover, is needed. This paper also shows how to make the GA faster via different populations of possible solutions.

Keywords: DNA Computing, Evolutionary Computing, Genetic Algorithms.

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

Link:

SOLVING TRAVELLING SALESMAN PROBLEM IN A SIMULATION OF GENETIC ALGORITHMS WITH DNA

Angel Goñi Moreno

http://www.foibg.com/ijita/vol15/ijita15-4-p08.pdf

Abstract: This paper presents the process of load balancing in simulation system Triad.Net, the architecture of load balancing subsystem. The main features of static and dynamic load balancing are discussed and new approach, controlled dynamic load balancing, needed for regular mapping of simulation model on the network of computers is proposed. The paper considers linguistic constructions of Triad language for different load balancing algorithms description.

Keywords: Distributed calculations, distributed simulation, static load balancing, dynamic load balancing, expert systems

ACM Classification Keywords: I.6 Simulation and Modeling I.6.8 Types of Simulation - Distributed: I.2 Artificial Intelligence I.2.5 Programming Languages and Software - Expert system tools and techniques

Link:

DYNAMIC DISTRIBUTION SIMULATION MODEL OBJECTS BASED ON KNOWLEDGE

Alexander Mikov, Еlena Zamyatina, Кonstantin Osmehin

http://www.foibg.com/ijita/vol15/ijita15-3-p15.pdf

Abstract: Gastroesophageal reflux disease (GERD) is a common cause of chronic cough. For the diagnosis and treatment of GERD, it is desirable to quantify the temporal correlation between cough and reflux events. Cough episodes can be identified on esophageal manometric recordings as short-duration, rapid pressure rises. The present study aims at facilitating the detection of coughs by proposing an algorithm for the classification of cough events using manometric recordings. The algorithm detects cough episodes based on digital filtering, slope and amplitude analysis, and duration of the event. The algorithm has been tested on in vivo data acquired using a single-channel intra-esophageal manometric probe that comprises a miniature white-light interferometric fiber optic pressure sensor. Experimental results demonstrate the feasibility of using the proposed algorithm for identifying cough episodes based on real-time recordings using a single channel pressure catheter. The presented work can be integrated with commercial reflux pH/impedance probes to facilitate simultaneous 24-hour ambulatory monitoring of cough and reflux events, with the ultimate goal of quantifying the temporal correlation between the two types of events.

Keywords: Biomedical signal processing, cough detection, gastroesophageal reflux disease.

ACM Classification Keywords: I.5.4 Pattern Recognition: Applications – Signal processing; J.3 Life and Medical Sciences

Link:

MANOMETRY-BASED COUGH IDENTIFICATION ALGORITHM

Jennifer A. Hogan, Martin P. Mintchev

http://www.foibg.com/ijita/vol14/ijita14-2-p03.pdf

Abstract: Two jamming cancellation algorithms are developed based on a stable solution of least squares problem (LSP) provided by regularization. They are based on filtered singular value decomposition (SVD) and modifications of the Greville formula. Both algorithms allow an efficient hardware implementation. Testing results on artificial data modeling difficult real-world situations are also provided

Keywords: jamming cancellation, approximation, least squares problem, stable solution, recurrent solution, neural networks, incremental training, filtered SVD, Greville formula

ACM Classification Keywords: I.5.4 Signal processing, G.1.2 Least squares approximation, I.5.1 Neural nets

Link:

TRAINING A LINEAR NEURAL NETWORK WITH A STABLE LSP SOLUTION FOR JAMMING CANCELLATION

Elena Revunova, Dmitri Rachkovskij

http://www.foibg.com/ijita/vol12/ijita12-3-p04.pdf

Abstract: Accurate and efficient analysis of biomedical signals can be facilitated by proper identification based on their dominant dynamic characteristics (deterministic, chaotic or random). Specific analysis techniques exist to study the dynamics of each of these three categories of signals. However, comprehensive and yet adequately simple screening tools to appropriately classify an unknown incoming biomedical signal are still lacking. This study is aimed at presenting an efficient and simple method to classify model signals into the three categories of deterministic, random or chaotic, using the dynamics of the False Nearest Neighbours (DFNN) algorithm, and then to utilize the developed classification method to assess how some specific biomedical signals position with respect to these categories. Model deterministic, chaotic and random signals were subjected to state space decomposition, followed by specific wavelet and statistical analysis aiming at deriving a comprehensive plot representing the three signal categories in clearly defined clusters. Previously recorded electrogastrographic (EGG) signals subjected to controlled, surgically-invoked uncoupling were submitted to the proposed algorithm, and were classified as chaotic. Although computationally intensive, the developed methodology was found to be extremely useful and convenient to use.

Keywords: Biomedical signals, classification, chaos, multivariate signal analysis, electrogastrography, gastric electrical uncoupling

ACM Classification Keywords: I.5.4 Pattern Recognition: Applications – Signal processing; J.3 Life and Medical Sciences

Link:

CLASSIFICATION OF BIOMEDICAL SIGNALS USING THE DYNAMICS OF THE FALSE NEAREST NEIGHBOURS (DFNN) ALGORITHM1

Charles Newton Price, Renato J. de Sobral Cintra, David T. Westwick, Martin Mintchev

http://www.foibg.com/ijita/vol12/ijita12-1-p03.pdf

Abstract: A new distance function to compare arbitrary partitions is proposed. Clustering of image collections and image segmentation give objects to be matched. Offered metric intends for combination of visual features and metadata analysis to solve a semantic gap between low-level visual features and high-level human concept.

Keywords: partition, metric, clustering, image segmentation.

ACM Classification Keywords: I.5.3 Clustering - Similarity measures

Link:

PARTITION METRIC FOR CLUSTERING FEATURES ANALYSIS

Dmitry Kinoshenko, Vladimir Mashtalir, Vladislav Shlyakhov

http://www.foibg.com/ijita/vol14/ijita14-3-p06.pdf

Abstract: In a paper the method of complex systems and processes clustering based use of genetic algorithm is offered. The aspects of its realization and shaping of fitness-function are considered. The solution of clustering task of Ukraine areas on socio-economic indexes is represented and comparative analysis with outcomes of classical methods is realized.

Keywords: Clustering, Genetic algorithm.

ACM Classification Keywords: I.5.3. Clustering

Link:

EVOLUTIONARY CLUSTERING OF COMPLEX SYSTEMS AND PROCESSES

Vitaliy Snytyuk

http://www.foibg.com/ijita/vol13/ijita13-4-p08.pdf

Abstract: The purpose of this paper is to explain the notion of clustering and a concrete clustering methodagglomerative hierarchical clustering algorithm. It shows how a data mining method like clustering can be applied to the analysis of stocks, traded on the Bulgarian Stock Exchange in order to identify similar temporal behavior of the traded stocks. This problem is solved with the aid of a data mining tool that is called XLMiner™ for Microsoft Excel Office.

Keywords: Data Mining, Knowledge Discovery, Agglomerative Hierarchical Clustering.

ACM Classification Keywords: I.5.3 Clustering

Link:

USING THE AGGLOMERATIVE METHOD OF HIERARCHICAL CLUSTERING AS A DATA MINING TOOL IN CAPITAL MARKET1

Vera Marinova–Boncheva?

http://www.foibg.com/ijita/vol15/ijita15-4-p12.pdf

Abstract: The problem of decision functions quality in pattern recognition is considered. An overview of the approaches to the solution of this problem is given. Within the Bayesian framework, we suggest an approach based on the Bayesian interval estimates of quality on a finite set of events.

Keywords: Bayesian learning theory, decision function quality.

ACM Classification Keywords: I.5.2 Pattern recognition: classifier design and evaluation

Link:

ON THE QUALITY OF DECISION FUNCTIONS IN PATTERN RECOGNITION

Vladimir Berikov

http://www.foibg.com/ijita/vol14/ijita14-1-p14.pdf

Abstract: The problem of recognition on finite set of events is considered. The generalization ability of classifiers for this problem is studied within the Bayesian approach. The method for non-uniform prior distribution specification on recognition tasks is suggested. It takes into account the assumed degree of intersection between classes. The results of the analysis are applied for pruning of classification trees.

Keywords: classifier generalization ability, Bayesian learning, classification tree pruning.

ACM Classification Keywords: I.5.2 Pattern recognition: classifier design and evaluation

Link:

RECOGNITION ON FINITE SET OF EVENTS: BAYESIAN ANALYSIS OF GENERALIZATION ABILITY AND CLASSIFICATION TREE PRUNING

Vladimir Berikov

http://www.foibg.com/ijita/vol13/ijita13-3-p13.pdf

Abstract: Technology of classification of electronic documents based on the theory of disturbance of pseudoinverse matrices was proposed.

Keywords: classification, training sample, a pseudoinverse matrix, Web Data Mining.

ACM Classification Keywords: I.5.2 Design Methodology, I.5.4 Applications, G.1.3 Numerical Linear Algebra

Link:

TECHNOLOGY OF CLASSIFICATION OF ELECTRONIC DOCUMENTS BASED ON THE THEORY OF DISTURBANCE OF PSEUDOINVERSE MATRICES

Volodymyr Donchenko, Viktoria Omardibirova

http://www.foibg.com/ijita/vol13/ijita13-4-p07.pdf

Abstract: The so called “Plural Uncertainty Model” is considered, in which statistical, maxmin, interval and Fuzzy model of uncertainty are embedded. For the last case external and internal contradictions of the theory are investigated and the modified definition of the Fuzzy Sets is proposed to overcome the troubles of the classical variant of Fuzzy Subsets by L. Zadeh. The general variants of logit- and probit- regression are the model of the modified Fuzzy Sets. It is possible to say about observations within the modification of the theory. The conception of the “situation” is proposed within modified Fuzzy Theory and the classifying problem is considered. The algorithm of the classification for the situation is proposed being the analogue of the statistical MLM(maximum likelihood method). The example related possible observing the distribution from the collection of distribution is considered

Keywords: Uncertainty, Fuzzy subset, membership function, classification, clusterization.

ACM Classification keywords: I.5.1.Pattern Recognition: Models Fuzzy sets; G.3. Probability and Statistics: Stochastic processes; H.1.m. Models and Principles: miscellaneous

Link:

UNCERTAINTY AND FUZZY SETS: CLASSIFYING THE SITUATION

Volodymyr Donchenko

http://www.foibg.com/ijita/vol14/ijita14-1-p08.pdf

Abstract: Pattern recognition (classification) algorithmic models and related structures were considered and discussed since 70s: – one, which is formally related to the similarity treatment and so - to the discrete isoperimetric property, and the second, - logic based and introduced in terms of Reduced Disjunctive Normal Forms of Boolean Functions. A series of properties of structures appearing in Logical Models are listed and interpreted. This brings new knowledge on formalisms and ontology when a logic based hypothesis is the model base for Pattern Recognition (classification).

ACM Classification Keywords: I.5.1 Pattern Recognition: Models

Link:

LOGIC BASED PATTERN RECOGNITION - ONTOLOGY CONTENT (1) 1

Levon Aslanyan, Juan Castellanos

http://www.foibg.com/ijita/vol14/ijita14-3-p02.pdf

Abstract: The goal of the paper is to estimate misclassification probability for decision function by training sample. Here are presented results of investigation an empirical risk bias for nearest neighbours, linear and decision tree classifier in comparison with exact bias estimations for a discrete (multinomial) case. This allows to find out how far Vapnik–Chervonenkis? risk estimations are off for considered decision function classes and to choose optimal complexity parameters for constructed decision functions. Comparison of linear classifier and decision trees capacities is also performed.

Keywords: pattern recognition, classification, statistical robustness, deciding functions, complexity, capacity, overtraining problem.

ACM Classification Keywords:I.5.1 Pattern Recognition: Statistical Models

Link:

EVALUATING MISCLASSIFICATION PROBABILITY USING EMPIRICAL RISK1

Victor Nedel’ko

http://www.foibg.com/ijita/vol13/ijita13-3-p15.pdf

Abstract: The issues relating fuzzy sets definition are under consideration including the analogue for separation axiom, statistical interpretation and membership function representation by the conditional Probabilities.

Keywords: fuzzy sets, membership function, conditional distribution

ACM Classification Keywords: I.5.1. Pattern Recognition: Models - Fuzzy set

Link:

FUZZY SETS: ABSTRACTION AXIOM, STATISTICAL INTERPRETATION, OBSERVATIONS OF FUZZY SETS

Volodymyr Donchenko

http://www.foibg.com/ijita/vol13/ijita13-3-p06.pdf

Abstract: Recommender systems are now widely used in e-commerce applications to assist customers to find relevant products from the many that are frequently available. Collaborative filtering (CF) is a key component of many of these systems, in which recommendations are made to users based on the opinions of similar users in a system. This paper presents a model-based approach to CF by using supervised ARTMAP neural networks (NN). This approach deploys formation of reference vectors, which makes a CF recommendation system able to classify user profile patterns into classes of similar profiles. Empirical results reported show that the proposed approach performs better than similar CF systems based on unsupervised ART2 NN or neighbourhood-based algorithm.

Keywords: neural networks, ARTMAP, collaborative filtering

ACM Classification Keywords: I.5.1 Neural Nets

Link:

AN APPROACH TO COLLABORATIVE FILTERING BY ARTMAP NEURAL NETWORKS

Anatoli Nachev

http://www.foibg.com/ijita/vol12/ijita12-3-p06.pdf

Abstract: This paper proposes a new method using radial basis neural networks in order to find the classification and the recognition of trees species for forest inventories. This method computes the wood volume using a set of data easily obtained. The results that are obtained improve the used classic and statistical models.

Keywords: Neural Networks, clustering, Radial Basis Functions, Forest Inventory.

ACM Classification Keywords: I.5. Pattern Recognition – I.5.1. Neural Nets; I.5.3. Clustering

Link:

APPLICATIONS OF RADIAL BASIS NEURAL NETWORKS FOR AREA FOREST

Angel Castellanos, Ana Martinez Blanco, Valentin Palencia

http://www.foibg.com/ijita/vol14/ijita14-3-p04.pdf

Abstract: the ontological approach to structuring knowledge and the description of data domain of knowledge is considered. It is described tool ontology-controlled complex for research and developments of sensor systems. Some approaches to solution most frequently meeting tasks are considered for creation of the recognition procedures.

Keywords: the tool complex, methods of recognition, ontology.

ACM Classification Keywords: I.4.8 Scene Analysis – Object recognition; I.2.9 Robotics – Sensors

Link:

DEVELOPMENT OF PROCEDURES OF RECOGNITION OF OBJECTS WITH USAGE MULTISENSOR ONTOLOGY CONTROLLED INSTRUMENTAL COMPLEX

Alexander Palagin, Victor Peretyatko

http://www.foibg.com/ijita/vol13/ijita13-4-p02.pdf