Informatica

The purpose of the research described in this paper is to propose a framework and supporting tools that will help software companies to establish formalised methods that will be technically and socially sound with their needs. Following the framework the companies can asses and improve their existing ways of working, capture them into formalised methods and continuously enrich them based on the past development experiences. Furthermore, the formalised methods that are designed based on the suggested framework are flexible and can be automatically adjusted by the supporting tools to suite circumstances of a particular project or team. This paper describes the framework philosophy and its tool support.

In this paper, we present a method for describing the syntax and semantics of viewcharts. Viewcharts is a visual formalism for describing the dynamic behavior of system components. We define the syntax of viewcharts as attributed graphs and, based on this graph, describe dynamic semantics of viewcharts by object mapping automata. This approach covers many important constructs of viewcharts, including hierarchy of views, ownership of elements, scope, and composition of views in SEPARATE, OR and AND ways. It also covers completion and interlevel transitions as well as history transitions without violating the independence of views. Viewcharts was originally based on statecharts; in this paper we also change the basis of viewcharts to an extended version of Finite State Machine (EFSM).

This paper is concerned with the problem of image analysis based detection of local defects embedded in particleboard surfaces. Though simple, but efficient technique developed is based on the analysis of the discrete probability distribution of the image intensity values and the 2D discrete Walsh transform. Robust global features characterizing a surface texture are extracted and then analyzed by a pattern classifier. The classifier not only assigns the pattern into the quality or detective class, but also provides the certainty value attributed to the decision. A 100% correct classification accuracy was obtained when testing the technique proposed on a set of 200 images.

We investigate applicability of quantitative methods to discover the most fundamental structural properties of the most reliable political data in Lithuania. Namely, we analyze voting data of the Lithuanian Parliament. Two most widely used techniques of structural data analysis (clustering and multidimensional scaling) are compared. We draw some technical conclusions which can serve as recommendations in more purposeful application of these methods.

Non-invasive physiological monitors are important subsystems of intensive care informatic systems. New innovative information methods and technology are presented for non-invasive human brain volumetric pulse wave physiological monitoring.

New information technologies provide a possibility of collecting a large amount of fundus images into databases. It allows us to use automated processing and classification of images for clinical decisions. Automated localization and parameterization of the optic nerve disc is particularly important in making a diagnosis of glaucoma, because the main symptoms in these cases are relations between the optic nerve and cupping parameters. This article describes the automated algorithm for the optic nerve disc localization and parameterization by an ellipse within colour retinal images. The testing results are discussed as well.

It is well known that a formal framework for the schema matching problem (SMP) is important because it facilitates the building of algorithm model and the evaluation of algorithms. An algebraic framework for schema matching is developed in this paper. First, based on universal algebra, we propose a meta-meta structure for schema, which is named multi-labeled schema. This definition has a distinctive feature: it is able to formally describe any particular style of schemas, and transforms a schema and other available information into a finite structure over specific signature. Later, we introduce a formal definition of schema matching that is called multivalent matching. Then, we formulize SMP as a schema homomorphism problem, and prove that SMP is equivalent to finding a semantic homomorphism from one schema to another. These results lead to the main contribution of this paper: an algebraic framework for SMP. This framework builds the algorithm model for SMP. Thirdly, we show a classification of schema matching based on the algebraic framework. Finally, we discuss the relations between matching cardinality and subclasses of schema homomorphism.

Multidimensional scaling is a technique for exploratory analysis of multidimensional data widely usable in different applications. By means of this technique the image points in a low-dimensional embedding space can be found whose inter-point distances fit the given dissimilarities between the considered objects. In this paper dependence of relative visualization error on the dimensionality of embedding space is investigated. Both artificial and practical data sets have been used. The images in three-dimensional embedding space normally show the structural properties of sets of considered objects with acceptable accuracy, and widening of applications of stereo screens makes three-dimensional visualization very attractive.

Mammalian brains consisting of up to 10¹¹ neurons belong to group of the most complex systems in the Universe. For years they have been one of the hardest objects of simulation. There are many different approaches to modelling of neurons, but one of the most biologically correct is Hodgkin-Huxley (HH) model. Simulations that require solving a large number of nonlinear differential equations (fundamental in HH model) are always time and power consuming. The structures discussed in this article simulate a part of the rat somatosensory cortex. We use a modular architecture of the network divided into layers and sub-regions. Because of a high degree of complexity effective parallelisation of algorithms is required. We propose method of parallelisation for the network and the results of simulations using GENESIS parallelised for MPI environment are presented. An occurrence of nonlinear behaviour is demonstrated. Most notably, in large biological neural networks consisting of the HH neurons, nonlinearity is shown to manifest itself in the Poincaré sections generated for the varying value of neural membrane's potential.