Abstract: We discuss the problem of connectivity within large-scale dynamic distributed information systems. Ad hoc system can adapt themselves through resource management or reconfiguration to achieve specific goals, such as functions, performance, energy budget and reliability. One of the mostly important goals is to keep a possibility of routing for any two nodes of the distributed system. Structure of the system can be described by a time-graph. In some moments of the time the structure of a network changes: new nodes can be included into the network and old nodes can be deleted. Thus the connectivity property of the time-graph is a logical function of time. A cause of disconnection may be technical (hardware failures, low energy, server overloading etc) or organizational (information secure, regular breaks or random interruptions). To improve the quality of service we have to control the distributed information system structure. The first step of a self-management (autonomic) system design is to describe permissible structures and forbidden structures. We propose to use the well-known method of graph grammars for this purpose. A finite set of graph grammar rules defines an infinite (but countable) set of permissible structures. An inference process allows us to get some permissible graph after doing of a finite sequence of steps. In this work we solve the problem of a set of graph grammar rules description for such property of graphs as connectivity. A detailed description of the rule set is used for rewriting of any graph (connected or disconnected) to a connected graph. Also we discuss a second step of a self-aware system design: including of the graph grammar into a feedback control cycle. An autonomic system has the property of selfawareness, i.e. the system contains its model and manages itself using this model. During a life-time cycle the current model can be compared with the permissible set described by graph grammar. If the current model isn’t belong to the permissible set then the distributed system turns a connectivity renewal process on. Some problems of graph grammar algorithms complexity are discussed.

Keywords: time-graph, grammar, autonomic system, ad hoc system.

ACM Classification Keywords: H. Information Systems: H.3 Information Storage and Retrieval: H.3.4 Systems and Software – Distributed systems. C. Computer Systems Organization: C.2 Computer-Communication? Networks: C.2.4 Distributed Systems – Distributed applications.

Link:

CONNECTIVITY CONTROL IN AD HOC SYSTEMS: A GRAPH GRAMMAR APPROACH

Alexander Mikov, Alexander Borisov

http://www.foibg.com/ijima/vol02/ijima02-01-p04.pdf

Abstract: Connections of detailed Petri N model and its component CN-net on the level of their structural and dynamic properties are investigated.

Keywords: component Petri net, components-places, components-transitions, languages of component net with components-places and component net with components-transitions.

ACM Classification Keywords: Petri net, language of Petri net, homomorphism, epimorphism, model, model verification.

Link:

COMPONENT MODELING: ON CONNECTIONS OF DETAILED PETRI MODEL AND COMPONENT MODEL OF PARALLEL DISTRIBUTED SYSTEM

Elena Lukyanova

http://www.foibg.com/ijima/vol02/ijima02-01-p02.pdf

Abstract: In this paper, we introduce an efficient improved tone mapping algorithm that can be used for displaying wide dynamic range (WDR) images on conventional display devices that are mainly of low dynamic range (LDR). That algorithm, which enhances the exponent-based tone mapping algorithm of Ofili et al., uses both local and global image information for improving the contrast and increasing the brightness of images. It also directly operates on the Bayer domain instead of the luminance/chrominance domain that is used by the vast majority of tone mapping algorithms. Experimental results performed on different WDR images show that we are able to get images that are more pleasant visually when compared to nine other tone mapping algorithms. These observations are also confirmed numerically through the use of the TMQI, an objective image quality measure.

Keywords: Wide dynamic range images, tone mapping, color filter array, contrast enhancement.

ACM Classification Keywords: A.0 General Literature - Conference Proceedings; I.4.3 Image Processing and Computer Vision – Enhancement

Link:

A JOINT GLOBAL AND LOCAL TONE MAPPING ALGORITHM FOR DISPLAYING WIDE DYNAMIC RANGE IMAGES

Alain Horé, Chika A. Ofili, and Orly Yadid-Pecht?, Fellow, IEEE

http://www.foibg.com/ijima/vol02/ijima02-01-p01.pdf

Abstract: Aspects of visual perception mechanism and pattern recognition methods are examined jointly. Latest results from neurophysiology in studying the visual system of living beings are discussed. Another view on coarse-to-fine approach for technical vision tasks is presented. On the basis of systemological analysis of neurophysiology sources a new hypothesis about visual neuron's functioning is proposed. This hypothesis explains the mechanism and takes into account receptive fields excitatory zones resizing during visual act.

Keywords: coarse-to-fine, neurons of visual system, intercellular processes, pattern recognition, image processing, variable resolution

ACM Classification Keywords: I.4.1 Digitization and Image Capture, I.5.1 Models

Link:

JOINT STUDY OF VISUAL PERCEPTION MECHANISM AND COMPUTER VISION SYSTEMS THAT USE COARSE-TO-FINE APPROACH FOR DATA PROCESSING

Anton Sharypanov, Alexandra Antoniouk, Vladimir Kalmykov

http://www.foibg.com/ijicp/vol01/ijicp01-03-p08.pdf

Abstract: During last decades grows the interest of investigators to the methods of using the third level features for increasing identification accuracy in automated fingerprint recognition systems. It was noticed that the poroscopical maps carry important information about fingerprint pores, namely, their number, sizes, coordinates etc. However, at creation of automated identification technique, there arises a problem in connection with impossibility of using directly the pixel-by-pixel comparison methods of corresponding images. In this paper, we propose technique for comparison of poroscopical maps, based on using investigated earlier structural proximity assessment measure, which was determined using the gradient field of images. The poroscopical map is determined using some known algorithms of image processing, namely binarization, segmentation etc. The results of poroscopical maps processing and comparative analysis of some items from the database of Hong Kong Polytechnical Institute are given. It is shown that the proposed technique for poroscopical maps processing can be used in AFRS for increasing the accuracy of fingerprint identification.

Keywords: Fingerprint, third level, pores, poroscopical map, gradient field, image proximity assessment.

ACM Classification Keywords: Image Processing and Computer Vision

Link:

NOVEL METHOD FOR ANALYSIS OF FINGERPRINT POROSCOPICAL MAPS

David Asatryan, Grigor Sazhumyan, Bagrat Sakanyan

http://www.foibg.com/ijicp/vol01/ijicp01-03-p07.pdf

Abstract: The work is devoted to methods and software tools of designing intelligent decision support systems (IDSS), which helps professionals (decision making persons) helping to diagnose complex problem situations on the example of complicated pathologies of view. Unlike traditional Bayesian belief networks, the proposed application of advanced multilevel (difficult-structured) networks, more convenient for complex research of the problem and providing expert data. Integration of Bayesian belief networks and Dempster-Shafer? method allows using at diagnostics both expert data, and numerical (probabilistic) data obtained in the result of measurements. The proposed approach is implemented in the prototype of the intelligent decision support system for diagnostics of difficult diseases of vision.

Keywords: intelligent system, decision support, diagnostics, problem situation, Bayesian belief network, Demster-Shafer? method.

ACM Classification Keywords: H.4.2 Information systems applications: Types of systems – Decision support; I.2.3 Artificial intelligence: Deduction and Theorem Proving – Uncertainty, "fuzzy," and probabilistic reasoning; I.2.4 Artificial intelligence: Knowledge Representation Formalisms and Methods – Bayesian belief network.

Link:

THE INTELLIGENT DECISION SUPPORT SYSTEM FOR DIAGNOSTIC OF DIFFICULT DISEASES OF VISION

Aleksandr Eremeev, Ruslan Khaziev, Irina Tcapenko, Marina Zueva

http://www.foibg.com/ijicp/vol01/ijicp01-03-p06.pdf

Abstract: The paper is devoted to the development of the new online handwritten mathematical expressions recognition system. The paper presents the recognition method to the handwritten symbols using fussy neural network NEFCLASS as a means for classification.

Keywords: online handwriting recognition, mathematical expressions, fuzzy logic, fuzzy neural networks, structural analysis, artificial neural network, genetic algorithm, conjugate gradient algorithm.

ACM Classification Keywords: I.5.2 Computing Methodologies - Pattern Recognition - Design Methodology - Pattern analysis. G.4 Mathematics of Computing – Mathematical Software - Algorithm design and analysis. I.5.1 Computing Methodologies - Pattern Recognition - Models - Structural.

Link:

Online Handwritten Mathematical Expressions Recognition System Using Fussy Neural Network

Edris Naderan

http://www.foibg.com/ijicp/vol01/ijicp01-03-p05.pdf

Abstract: The reasons for emerging OWL as a standard for ontology representation in the Semanic Web are discussed in the paper. OWL structre and possibilities for representing ontologies of transdisciplinary knowledge are outlined. Recommendations for using OWL at the interdisciplinary level are proposed.

Keywords: OWL, interdisciplinary research, ontology

ACM Classification Keywords: 1.2.4. Knowledge Representation Formalisms and Methods

Link:

OWL as a Standard Model for Transdisciplinary Knowledje Representation in Semantic Web

Andrey Mihailyuk

http://www.foibg.com/ijicp/vol01/ijicp01-03-p04.pdf

Abstract: The traditional approach (the comparison with a "reference" result) for evaluating quality of the technology to identify knowledge extracted from text arrays is badly applicable out of a need to create the reference answer for each specific set of electronic documents. In this paper we show that integral quantitative coefficients of recall, precision and F-measure can be used to assess effectiveness of linguistic technologies of knowledge identification in texts. Justifying the possibility of using the test collections method for the experimental validation of obtained efficiency coefficients, we propose the use of the approach based on mathematical statistics methods. The procedures of using sampling fraction of the indicator as a characteristic of evaluating the proportion of relevant documents in the general population are reviewed. The paper shows the argumentation to the fact that, in important practical cases of text collection samples, asymmetry of a confidence interval at the binomial distribution can be overcome by approximated transition to the normal distribution. We also propose the methods of determining the confidence interval for the indicator fraction that are based on Wilson approach, and the method of determining the required size of the relevant sample depending on the specified error and confidence probability as well.

Key worlds: evaluation of effectiveness, semistructured text information, test collections method, size sample

ACM Classification Keywords: H.3.3 .Information Search and Retrieval, I.2.4. Knowledge Representation Formalisms and Methods, G.3. Probability and statistics – Statistical computing

Link:

Solution of the Problem of Formal Evaluation of Effectiveness of the Technology Knowledge Identification in Semistructured Text Information

Nina Khairova, Nataliya Sharonova, Dmytro Uzlov

http://www.foibg.com/ijicp/vol01/ijicp01-03-p03.pdf

Abstract: The survey and analysis of new field in AI -computational intelligence (CI) is performed. The main components of CI- technologies, methods and applications are outlined, their interconnections are determined and analyzed. The interrelations between CI and soft-computing are established and discussed.

Keywords: computational intelligence, soft computing, neural networks, fuzzy logic, evolutionary modeling.

ACM Classification Keywords: I.2 Artificial Intelligence, I.2.11 Distributed Artificial Intelligence

Link:

System Analysis of Computational Intelligence Main Trends

Michael Zgurovsky, Yuriy Zaychenko

http://www.foibg.com/ijicp/vol01/ijicp01-03-p02.pdf

Abstract: This work aims at studying personal data analysis area, when confidentiality property of data is ensured. It is supposed that we are given partially critical social science data and prior to the submission of data to the public it is required to modify them so that confidential information is not disclosed, and that the analysis of these data did not differ from the analysis of raw data. Our work builds improved algorithms of class of classification and regression trees, which provide solution to the problem of generation of the so-called synthetic data. The new solution of generation takes into account the structure of the areas of privacy and is providing optimized tree replacement for synthetic data sets.

Keywords: classification, regression, data disclosure, synthetic data.

ACM Classification Keywords: H.1 Information Systems – Models and principles, I.2.0 Artificial intelligence.

Link:

Enhanced Cart Technologies in Partial Synthetic Data Generation

Levon Aslanyan, Vardan Topchyan

http://www.foibg.com/ijicp/vol01/ijicp01-03-p01.pdf

Abstract: The tissue type classification is presented using the neural networks. The multi-spectral images of uterine cervix were segmented using self-organizing Kohonen maps and k-means algorithm. Then, the classification of tissue types from computed segments was made using the cascade neural network, back propagating neural network, and RBF network. The basics of neural networks were briefly explained. The results were presented and analyzed, based on which, the conclusions were made.

Keywords: neural networks, decision making, intellectual systems, segmentation.

ACM Classification Keywords: I.2.1 Applications and Expert Systems - Medicine and science

Link:

THE ANALYSIS OF NEURAL NETWORKS’ PERFORMANCE FOR MEDICAL IMAGE CLASSIFICATION

Kateryna Malyshevska

http://www.foibg.com/ijicp/vol01/ijicp01-02-p11.pdf

Abstract: The article is devoted to the development of the new Automated Building Extraction system applied on High Resolution Satellite Imagery, which is based on an object-oriented approach and soft computing.

Keywords: building recognition, satellite imagery, neuro-fuzzy classifier NEFCLASS, genetic algorithm.

ACM Classification Keywords: 1.4.7 Computing Methodologies - Image Processing and Computer Vision – Feature Measurement - Size and shape. G.1.6 Mathematics of Computing – Numerical Analysis – OptimizationGradient? methods. I.4.8 Computing Methodologies - Image Processing and Computer Vision – Scene Analysis - Object recognition. I.5.1 Computing Methodologies - Pattern Recognition - Models - Neural nets.

Link:

Automated Building Extraction System Applied On High Resolution Satellite Imagery Using Fuzzy Neural Network

Svetlana Naderan

http://www.foibg.com/ijicp/vol01/ijicp01-02-p10.pdf

Abstract: New class of preconditioners for iterative algorithms of sparse linear systems solution built using basis matrix method and incomplete decomposition methodology has been proposed. Algorithms with static and dynamic restriction set along with additional refinement procedures have been presented. Results of developed algorithms' testing carried out on matrices from Tim Davis Matrix Collection have been given. Basing on received results, matrix classes, applying proposed preconditioners on which resulted in iterative algorithms speed-up and/or accuracy increase, have been identified

Keywords: linear systems, sparse matrices, poor conditioned matrices, preconditioners, basis matrix method.

ACM Classification Keywords: H.4.2 Information Systems Applications: Types of Systems: Decision Support.

Link:

BUILDING PRECONDITIONERS USING BASIS MATRIX METHOD

Volodymyr Kudin, Vsevolod Bohaienko

http://www.foibg.com/ijicp/vol01/ijicp01-02-p09.pdf

Abstract: The work proposes a method for estimating the stability index of alpha-stable distributions by using moments of fractional order. Provided numerical modeling has fully justified all of the results. Comparative analysis of the efficiency among the proposed method of estimating the stability index and widely used methods was performed. Proposal method is much simpler, far faster and substantially less memory required. Estimation of generalized Hurst exponent from time series of the ordinary Lévy process was performed. Multifractal fluctuation analysis method and evaluation based on stability index estimation were compared. The results of numerical modeling showed that proposed method for estimating the fractal properties of the ordinary Lévy process, based on stability index estimation via fractional order moments is a much more accurate.

Keywords: alpha-stable variables, stability index estimation, fractional order moments, multifractal stochastic processes, Hurst exponent, generalized Hurst exponent, ordinary Levy motion.

ACM Classification Keywords: G.3 Probability and statistics - Time series analysis, Stochastic processes, G.1 Numerical analysis, G.1.2 Approximation - Wavelets and fractals

Link:

ANALYSIS OF THE PROPERTIES OF ORDINARY LEVY MOTION BASED ON THE ESTIMATION OF STABILITY INDEX

Lyudmyla Kirichenko, Vadim Shergin

http://www.foibg.com/ijicp/vol01/ijicp01-02-p08.pdf

Abstract: The idea of subpixel feature detection is widely used in image processing area in these days and it has a high significance in many practical applications. This paper deals with impact of subpixel paradigm on accuracy of 3D coordinates determination using information related to corresponding 2D image pairs. In the other worlds, there is a study how the subpixel corner points detection could influence the accuracy of 3D reconstruction. For that reason our work contains this comparison for image pairs having various mutual position and resolution using data from given datasets. This contribution could answer the question if the paradigm of subpixel detection could be useful in VSLAM methods and other practical tasks where the precision is a key.

Keywords: subpixel corner detection, 3D scene reconstruction, accuracy comparison

ACM Classification Keywords: I.4.8 Scene Analysis - stereo

Link:

IMPACT OF SUBPIXEL PARADIGM ON DETERMINATION OF 3D POSITION FROM 2D IMAGE PAIR

Lukas Sroba, Rudolf Ravas

http://www.foibg.com/ijicp/vol01/ijicp01-02-p07.pdf

Abstract: The current state and trends in the area of dynamic intelligent systems are analyzed. The first experimental results obtained in the development of certain provisions and components of the task-oriented methodology for the integrated expert systems construction during the transition to unformalized problems in dynamic areas of concern solving are considered. State and tendencies of evolution of modern development tools for static and dynamic expert systems development are being analyzed. New facilities of unique Russian instruments for support of integrated expert systems development – the AT-TECHNOLOGY workbench – connected with dynamic integrated expert systems development are in question.

Keywords: dynamic intelligent system, dynamic integrated expert systems, task-oriented methodology, ATTECHNOLOGY workbench, development tools real time, simulation modeling, temporal reasoning, temporal reasoner.

ACM Classification Keywords: I.2.1 Applications and Expert Systems; I.2.5 Programming Languages and Software

Link:

DYNAMIC INTEGRATED EXPERT SYSTEMS: THE EVOLUTION OF AT-TECHNOLOGY WORKBENCH

Galina Rybina, Victor Rybin

http://www.foibg.com/ijicp/vol01/ijicp01-02-p06.pdf

Abstract: The article reveals an approach to modelling of the cognitive ability managing the focus of attention (an ability to switch one's attention) which is based on the reflexive mechanisms developed in “OntoIntegrator” system. There were considered basic experiments to classify the mathematical texts, and demonstrated the reflection mechanisms for the solution of a set task.

Keywords: ontology, reflection, attention switch, ontological mark-up of the text

ACM Classification Keywords: H.3 INFORMATION STORAGE AND RETRIEVAL H.3.1 Content Analysis and Indexing - Linguistic processing

Link:

AN APPROACH TO THE MODELING OF THE COGNITIVE ABILITY MANAGING THE FOCUS OF ATTENTION ON THE BASIS OF THE REFLEXIVE MECHANISM OF THE SYSTEM

Olga Nevzorova, Vladimir Nevzorov

http://www.foibg.com/ijicp/vol01/ijicp01-02-p05.pdf

Abstract: Let ܥ be a collection of objects, characterized by the set ܣ = {ܽଵ,⋯,ܽ௡} of binary attributes. We consider problems of the following type: given an object-characterization table, it is to check if there exists a subset ܯ in ܥ of a given size, such that each attribute of A is satisfied by a given number of objects in ܯ. Additional restriction may be applied such as - the number of matches of each object in ܯ is limited. In this paper we investigate particular cases of the general problem, and consider approximation solutions by means of binary classification trees.

Keywords: Classification tree, covering, greedy algorithm.

ACM Classification Keywords: F.2.2 Nonnumerical Algorithms and Problems

Link:

CONSTRAINED OBJECT-CHARACTERIZATION TABLES AND ALGORITHMS1

Hasmik Sahakyan

http://www.foibg.com/ijicp/vol01/ijicp01-02-p04.pdf

Abstract: The tasks that encloses the Semantic Web often requires semantic comparisons between classes, properties, relations and instances, that mainly consist in semantic similarity. As a consequence, the number of similarity functions used in this field has greatly increased in the last years. However, the selection of the best similarity functions to use in each case is a difficult task usually guided by heuristics and intuition. To overcome this problem, in this paper we propose a taxonomy of similarity functions as a first step to a semantic catalog of similarity functions. This taxonomy is induced by another taxonomy of data types. Our taxonomy allows selecting the similarity functions applicable to a pair of entities based on the data type used to represent them. It also eases the composition of functions according the composition of data types, and supports the inheritance of applicable functions from the more abstract to the more specific data types. As a consequence, it facilitates the application of similarity functions in an automated way. Finally, we also populate this taxonomy with some of the most popular similarity functions used in Semantic Web.

Keywords: Semantic Web, semantic comparison, similarity measures

ACM Classification Keywords: 1.5.4 Pattern recognition applications. I.2.4 Knowledge Representation Formalisms and Methods.

Link:

TOWARDS A SEMANTIC CATALOG OF SIMILARITY MEASURES

Alfredo Sánchez-Alberca?, Rafael Lahoz-Beltra? and Juan Castellanos-Peñuela?

http://www.foibg.com/ijicp/vol01/ijicp01-02-p03.pdf

Abstract: In the paper the development of operating technique for matrices Euclidean spaces is represented. Particularly, within such development transfer of linear operators’ technique with preserving properties of closely correspondence to natural subspaces is represented. Also - spectral results, SVD – and Moore – Penrose Pseudo Inverse – technique, theory of orthogonal projectors and grouping operators. Besides, solution of the linear discrimination problem in Euclidean spaces of matrices is represented in the paper. Realization the program of empowering the operating technique in matrices Euclidean space made possible on the basis of putting in circulation of so-called "cortege operators” and, correspondingly - "cortege operations”.

Keywords: Feature vectors, matrix corteges operators, Single Valued Decomposition for cortege linear operators, linear discrimination.

ACM Classification Keywords: G.2.m. Discrete mathematics: miscellaneous, G.2.1 Combinatorics; G.3 Probability and statistics, G.1.6. Numerical analysis, I.5.1.Pattern Recognition; H.1.m. Models and Principles: miscellaneous.

Link:

SPREADING THE MOORE - PENROSE PSEUDO INVERSE ON MATRICES EUCLIDEAN SPACES: THEORY AND APPLICATIONS

Volodymyr Donchenko, Fedir Skotarenko

http://www.foibg.com/ijicp/vol01/ijicp01-02-p02.pdf

Abstract: Social behavior is mainly based on swarm colonies, in which each individual shares its knowledge about the environment with other individuals to get optimal solutions. Such co-operative model differs from competitive models in the way that individuals die and are born by combining information of alive ones. This paper presents the particle swarm optimization with differential evolution algorithm in order to train a neural network instead the classic back propagation algorithm. The performance of a neural network for particular problems is critically dependant on the choice of the processing elements, the net architecture and the learning algorithm. This work is focused in the development of methods for the evolutionary design of artificial neural networks. This paper focuses in optimizing the topology and structure of connectivity for these networks.

Keywords: Social Intelligence, Neural Networks, Grammatical Swarm, Particle Swarm Optimization, Learning Algorithm.

ACM Classification Keywords: F.1.1 Theory of Computation - Models of Computation, I.2.6 Artificial Intelligence - Learning.

Link:

Polynomial Regression using a Perceptron with Axo-axonic Connections

Nuria Gómez Blas, Luis F. de Mingo, Alberto Arteta

http://www.foibg.com/ijicp/vol01/ijicp01-02-p01.pdf

Abstract: Many artificial intelligence problems are NP-complete ones. To increase the needed time of such a problem solving a method of extraction of sub-formulas characterizing the common features of objects under consideration is suggested. Repeated application of this procedure allows forming a level description of an object and of classes of objects. A model example of such a level description and the degree of steps number increasing is presented in the paper.

Keywords: artificial intelligence, pattern recognition, predicate calculus, complexity of an algorithm, level description of a class.

ACM Classification Keywords: I.2.4 Artificial Intelligence Knowledge Representation Formalisms and Methods – Predicate logic, I.5.1 Pattern Recognition Models – Deterministic, F.2.2 Non numerical Algorithms and Problems – Complexity of proof procedures.

Link:

CONSTRUCTION OF CLASS LEVEL DESCRIPTION FOR EFFICIENT RECOGNITION OF A COMPLEX OBJECT

Tatiana Kosovskaya

http://www.foibg.com/ijicp/vol01/ijicp01-01-p11.pdf

Abstract: We present results of a study of the information about the medieval maps and travellers’ geographic descriptions of Turkey. It is based on Ian Manners’ monograph “European Cartographers and the Ottoman World 1500-1750” (University of Chicago, 2007). The obtained chronological distributions show some peculiarities; we discuss one of them.

Keywords: chronological distribution of information, ottoman world 1500-1750, maps, Little Ice Age

ACM Classification Keywords: I.6 SIMULATION AND MODELLING, I.6.3 Applications

Link:

CHRONOLOGICAL MODELLING OF THE WEST – EUROPEAN INFORMATION ABOUT THE MEDIEVAL MAPS OF THE OTTOMAN WORLD 16TH-18TH CENTURIES

Jordan Tabov, Galina Panayotova

http://www.foibg.com/ijicp/vol01/ijicp01-01-p10.pdf

Abstract: The article describes three different approaches to verification of one of the most frequently used UMLdiagrams – the sequence diagram. It indicates that these methods allow estimating its correctness only in certain aspects, and complex application of these approaches is the most effective way.

Keywords: verification, digital machine, driver, UML-diagram, record, correctness, sequence diagram.

Link:

FORMAL VERIFICATION OF THE SEQUENCE DIAGRAM

Vitaliy Lytvynov, Irina Bogdan

http://www.foibg.com/ijicp/vol01/ijicp01-01-p09.pdf