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

Abstract: Image content interpretation is much dependent on segmentations efficiency. Requirements for the image recognition applications lead to a nessesity to create models of new type, which will provide some adaptation between law-level image processing, when images are segmented into disjoint regions and features are extracted from each region, and high-level analysis, using obtained set of all features for making decisions. Such analysis requires some a priori information, measurable region properties, heuristics, and plausibility of computational inference. Sometimes to produce reliable true conclusion simultaneous processing of several partitions is desired. In this paper a set of operations with obtained image segmentation and a nested partitions metric are introduced.

Keywords: image, spatial reasoning, partitions, covers, interpretation.

ACM Classification Keywords: I.4.6 Segmentation: region growing, partitioning

Link:

IMAGE QUOTIENT SET TRANSFORMS IN SEGMENTATION PROBLEMS

Dmitry Kinoshenko, Sergey Mashtalir, Konstantin Shcherbinin, Elena Yegorova

http://www.foibg.com/ijitk/ijitk-vol02/ijitk02-4-p12.pdf

Abstract: Data processing services for Meteosat geostationary satellite are presented. Implemented services correspond to the different levels of remote-sensing data processing, including noise reduction at preprocessing level, cloud mask extraction at low-level and fractal dimension estimation at high-level. Cloud mask obtained as a result of Markovian segmentation of infrared data. To overcome high computation complexity of Markovian segmentation parallel algorithm is developed. Fractal dimension of Meteosat data estimated using fractional Brownian motion models.

Keywords: cloud mask, fractals, Meteosat, Markov Random Fields, fractional Brownian motion, parallel programming, MPI.

ACM Classification Keywords: I.4.6 Image Processing and Computer Vision: Segmentation – Pixel classification, G.1.2 Numerical Analysis: Approximation – Wavelets and fractals, D.1.3 Programming Techniques: Concurrent Programming – Parallel programming, I.4.7 Image Processing and Computer Vision: Feature Measurement – Texture

Link:

SERVICES FOR SATELLITE DATA PROCESSING

Andriy Shelestov, Oleksiy Kravchenko, Michael Korbakov

http://www.foibg.com/ijita/vol12/ijita12-3-p11.pdf

Abstract: We extend our previous work into error-free representations of transform basis functions by presenting a novel error-free encoding scheme for the fast implementation of a Linzer-Feig? Fast Cosine Transform (FCT) and its inverse. We discuss an 8x8 L-F scaled Discrete Cosine Transform where the architecture uses a new algebraic integer quantization of the 1-D radix-8 DCT that allows the separable computation of a 2-D DCT without any intermediate number representation conversions. The resulting architecture is very regular and reduces latency by 50% compared to a previous error-free design, with virtually the same hardware cost.

Keywords: DCT, Image Compression, Algebraic Integers, Error-Free? Computation.

ACM Classification Keywords: I.4.2 Compression (Coding), I.1.2 Algorithms, F.2.1 Numerical Algorithms.

Link:

ON THE ERROR-FREE COMPUTATION OF FAST COSINE TRANSFORM

Vassil Dimitrov, Khan Wahid

http://www.foibg.com/ijita/vol12/ijita12-4-p04.pdf

Abstract: The desire to create unique things and give free rain to one's imagination served as a powerful impetus to the development of digital art and design software. The commoner was the use of computers the wider variety of professional software was developed. Nowadays the creators and computer designers are receiving more and more new and advanced programs that allow their ideas becoming virtual reality. This research paper looks at the history of the development of graphic editors from the simplest to the most modern and advanced. This brief survey includes the history of different graphic editors’ creation, their features and abilities. This paper highlights the two basic branches of graphic editors – these that are in free use and commercial graphic editors design software. The researcher selected the most powerful and influential graphic editors design software brands like Paint.NET and GIMP among free software and commercial Adobe Photoshop. This paper also dwells upon the way digital art transferred from the exclusively professional business into the hobby for ordinary users. This research paper bears implications for those who are interested in features and potentiality of most popular graphic editors design software.

Keywords: Digital Art, Graphic information, DPaint, Image Manipulation Program, Paint Shop Pro, Photopaint, Photoshop.

ACM Classification Keywords: I.4 Image processing and computer vision, !.4.1 Digitization and image capture, I.4.10 Image representation, I.5.2 Design methodology.

Link:

DIGITAL ART AND DESIGN

Khaled Batiha, Safwan Al-Salaimeh?, Khaldoun A.A. Besoul

http://www.foibg.com/ijitk/ijitk-vol01/ijitk01-2-p07.pdf

Abstract: Very often the experimental data are the realization of the process, fully determined by some unknown function, being distorted by hindrances. Treatment and experimental data analysis are substantially facilitated, if these data to represent as analytical expression. The experimental data processing algorithm and the example of using this algorithm for spectrographic analysis of oncologic preparations of blood is represented in this article.

Keywords: graphics, experimental data, Besie's curves

ACM Classification Keywords: I.4 Image processing and computer vision - Approximate methods

Link:

APPROXIMATION OF EXPERIMENTAL DATA BY BEZIER CURVES

Vitaliy Vishnevskey, Vladimir Kalmykov, Tatyana Romanenko

http://www.foibg.com/ijita/vol15/ijita15-3-p06.pdf

Abstract: Computer modeling is a perspective method for optimal design of prosthesis and orthoses. The study is oriented to develop modular ankle foot orthosis (MAFO) to assist the very frequently observed gait abnormalities relating the human ankle-foot complex using CAD modeling. The main goal is to assist the anklefoot flexors and extensors during the gait cycle (stance and swing) using torsion spring. Utilizing 3D modeling and animating open source software (Blender 3D), it is possible to generate artificially different kind of normal and abnormal gaits and investigate and adjust the assistive modular spring driven ankle foot orthosis.

Keywords: biomechanics; 3D computer modeling, ankle-foot orthosis

ACM Classification Keywords: I.3.7 Three-Dimensional? Graphics and Realism, I.6.5 Model Development

Link:

OPEN SOURCE INFORMATION TECHNOLOGIES APPROACH FOR MODDELING OF ANKLE-FOOT ORTHOSIS

Slavyana Milusheva, Stefan Karastanev, Yuli Toshev

http://www.foibg.com/ijita/vol14/ijita14-2-p06.pdf

Abstract: The paper presents the Bulgarian setting in digital preservation of and access to cultural and scientific heritage. It mentions key Bulgarian institutions, which take or should take part in digitisation endeavours. It also presents examples of building and adapting specialised tools in the field, and more specifically SPWC, ACT and XEditMan.

Keywords: digital preservation of and access to cultural and scientific heritage, legislative issues, SPWC, ACT, XEditMan

ACM Classification Keywords: I.3.3. Digitizing and scanning; I.3.6. Standards; D.2.1. Methodologies

Link:

DIGITISATION OF CULTURAL HERITAGE: BETWEEN EU PRIORITIES AND BULGARIAN REALITIES1

Milena Dobreva, Nikola Ikonomov

http://www.foibg.com/ijita/vol12/ijita12-1-p02.pdf

Abstract: Implementation of GEOSS/GMES initiative requires creation and integration of service providers, most of which provide geospatial data output from Grid system to interactive user. In this paper approaches of DOScenters (service providers) integration used in Ukrainian segment of GEOSS/GMES will be considered and template solutions for geospatial data visualization subsystems will be suggested. Developed patterns are implemented in DOS center of Space Research Institute of National Academy of Science of Ukraine and National Space Agency of Ukraine (NASU-NSAU).

Keywords: data visualization.

ACM Classification Keywords: I.3.2 Graphics Systems - Distributed/network graphics, C.5.0 Computer system implementation – General.

Link:

DISTRIBUTED VISUALIZATION SYSTEMS IN REMOTE SENSING DATA PROCESSING GRID

Andrii Shelestov, Oleksiy Kravchenko, Mykola Ilin

http://www.foibg.com/ijitk/ijitk-vol02/ijitk02-1-p14.pdf

Abstract. The purpose of the paper is to explore the possibility of applying existing formal theories of description and design of distributed and concurrent systems to interaction protocols for real-time multi-agent systems. In particular it is shown how the language PRALU, proposed for description of parallel logical control algorithms and rooted in the Petri net formalism, can be used for the modeling of complex concurrent conversations between agents in a multi-agent system. It is demonstrated with a known example of English auction on how to specify an agent interaction protocol using considered means.

Keywords: multi-agent system, interaction protocol, parallel control algorithm

ACM Classification Keywords: I.2.11 Computer Applications; Distributed Artificial Intelligence, Multiagent systems; D.3.3 Programming Languages: Language Constructs and Features – Control structures, Concurrent programming structures

Link:

DEVELOPING AGENT INTERACTION PROTOCOLS WITH PRALU

Dmitry Cheremisinov, Liudmila Cheremisinova

http://www.foibg.com/ijita/vol13/ijita13-3-p07.pdf

Abstract: The principles of adaptive routing and multi-agent control for information flows in IP-networks.

Keywords: telecommunication system, adaptive quality service, multi-agent control, IP-network.

ACM Classification Keywords: I.2.11 Distributed Artificial Intelligence: Multiagent systems; F.1.1 Models of Computation: Neural networks

Link:

ADAPTIVE ROUTING AND MULTI-AGENT CONTROL FOR INFORMATION FLOWS IN IP-NETWORKS

Adil Timofeev

http://www.foibg.com/ijita/vol12/ijita12-3-p15.pdf