Informatica

This article presents the ways of identification, selection and transformation of the data into other structures. Relation selection and transformation may change data quantity and order of laying out. As a result the data are aggregated to the structure needed for application problem algorithm. Data aggregation makes possible to adapt data structure presentation order and quantity for any application problem. Naturally, there must be enough necessary data in the relation sets for any application problem.

The paper analyzes the performance of parallel global optimization algorithm, which is used to optimize grillage-type foundations. The parallel algorithm is obtained by using the automatic parallelization tool. We describe briefly the layer structure of the Master–Slave Template library and present a detailed mathematical formulation of the application problem. Experiments are done on the homogeneous computer cluster of 7 IBM machines RS6000. The results of experiments are presented.

A model of the moisture diffusion in wood under isothermal conditions taking into consideration coating of the surface of a specimen is presented in a 2-D-in-space formulation. A reliability of a corresponding 1-D model is investigated for a simulation of moisture movement in 2-D medium. This paper presents a technique to determine the width as well as the degree of edges coating of the specimen making the 1-D model relevant for 2-D medium. This technique bases on the computer simulation of 2-D moisture diffusion to estimate the reliability of the corresponding 1-D model. In the technique, approximate coefficients of the diffusion and surface emission may be employed if accurate values of these coefficients are unknown.

High-quality machine translation between human languages has for a long time been an unattainable dream for many computer scientists involved in this fascinating and interdisciplinary field of the application of computers. The developed quite recently example-based machine translation technique seems to be a serious alternative to the existing automatic translation techniques. In the paper the usage of the example based machine translation technique for the development of system, which would be able to translate an unrestricted German text into Polish is proposed. The new approach to the example-based machine translation technique that takes into account the peculiarity of the Polish grammar is developed. The obtained primary results of the development of proposed system seem to be very promising and appear to be a step made in the right direction towards a fully-automatic high quality German-into-Polish machine translation system for unrestricted text.

The amount of products and services available over the Internet increases significantly and it soon becomes beyond users ability to analyze and compare them. At the same time the number of potential customers available via the Internet also increases dramatically and starts to be beyond the service providers ability to perform efficient targeted marketing. A possible way for relaxing the above-mentioned limitations could be in usage of electronic assistants, both for customers and providers. Such assistants may serve as mediators for commercial Internet-based activity. Software agents could play role of such mediators representing customers and providers in the network. In this paper we present our experience and a solution to using agent technology in customer services management for mobile users. The solution is intended to increase granularity and personalization in targeted advertising while ensuring customer privacy. The proposed solution has been implemented in a prototype system for providing services for users of mobile devices.

Application of knowledge discovery in databases (data mining) for medical decision support is discussed in this work. The aim of the study was to use decision support algorithm for the differential diagnosis of intraocular tumors using parameters from eye images obtained by the ultrasound examination. Application of predictive modeling algorithm for decision tree formation using See5.0/C5.0 data mining system is presented. The decision tree was build using tumor geometry and microstructure parameters. The use of decision tree allows to differentiate tumors from other tumor-like formations. Low percentage of diagnostic errors shows that decision tree is reliable enough to offer it as “second opinion” for physician's decision support.

The presented article is about a research using artificial neural network (ANN) methods for compound (technical and fundamental) analysis and prognosis of Lithuania's National Stock Exchange (LNSE) indices LITIN, LITIN-A and LITIN-VVP. We employed initial pre-processing (analysis for entropy and correlation) for filtering out model input variables (LNSE indices, macroeconomic indicators, Stock Exchange indices of other countries such as the USA – Dow Jones and S&P, EU – Eurex, Russia – RTS). Investigations for the best approximation and forecasting capabilities were performed using different backpropagation ANN learning algorithms, configurations, iteration numbers, data form-factors, etc. A wide spectrum of different results has shown a high sensitivity to ANN parameters. ANN autoregressive, autoregressive causative and causative trend model performances were compared in the approximation and forecasting by a linear discriminant analysis.

This paper presents model-based forecasting of the Lithuanian education system in the period of 2001–2010. In order to obtain satisfactory forecasting results, development of models used for these aims should be grounded on some interactive data mining. The process of the development is usually accompanied by the formulation of some assumptions to background methods or models. The accessibility and reliability of data sources should be verified. Special data mining of data sources may verify the assumptions. Interactive data mining of the data, stored in the system of the Lithuanian teachers' database, and that of other sources representing the state of the education system and demographic changes in Lithuania was used. The models cover the estimation of data quality in the databases, analysis of the flow of teachers and pupils, clustering of schools, the model of dynamics of the pedagogical staff and pupils, and the quality analysis of teachers. The main results of forecasting and integrated analysis of the Lithuanian teachers' database with other data reflecting the state of the education system and demographic changes in Lithuania are presented.

The goal of the paper is to create a model for investigating the character of relationships between the freedom and restrictions in the terrorism context, in order to find out how sensitive is the probability of the population survival to small changes in these two parameters. A model for simulating relationships between access to resources and possibility of termination of the population is presented. The model comprises an agent world, its properties, interactions, and a world life cycle algorithm. As the “right” properties and interactions of the model are a question of experimentation, the model is introduced in two steps: a general model and a specific sub-model. Preliminary analysis of results received on a sub-model implementation demonstrate that in certain cases the relationship between the level of access to information and the overall aggressiveness value implying the end of population may has a stepwise character.