Abstract: The influence of used norm and corresponding Lipschitz constant to the speed of branch and bound algorithm for multidimensional global optimization has been investigated. Lipschitz constants of different test functions for global optimization corresponding to different norms have been estimated. The test functions have been optimized using branch and bound algorithm for Lipschitz optimization with different norms. Experiments have shown that the best results are achieved when the combination of extreme (infinite and first) and Euclidean norms is used.

Abstract: This paper deals with a method, called locally linear embedding. It is a nonlinear dimensionality reduc- tion technique that computes low-dimensional, neighbourhood preserving embeddings of high dimensional data and attempts to discover nonlinear structure in high dimensional data. The implementation of the algorithm is fairly straightforward, as the algorithm has only two control parameters: the number of neighbours of each data point and the regularisation parameter. The mapping quality is quite sensitive to these parameters. In this paper, we propose a new way for selecting the number of the nearest neighbours of each data point. Our approach is experimentally verified on two data sets: artificial data and real world pictures.

Abstract: Currently digital library of educational resources and services (DLE) for general education and vocatio-nal training systems is under active implementation in Lithuania. Its design is based on the idea of partition of digital learning resources to two separate parts (learning objects (content) and units of learning (learning methods/scenarios/ designs)) which have clear different functions, and investigation of reusability and interoperability of these two sepa-rate parts within the system and DLE as a whole on European level. The article aims to analyse several aspects of interoperability of these main DLE components.

Abstract: Eye tracking devices generate enormous amount of data, which requires a well-balanced approach to selective visualization of the data. This approach involves employing some data clustering algorithm. Most of the tradi-tional algorithms, however, are too slow as well as inadequately deterministic to be applied to eye gaze data. This paper describes our software implementation of two modifications of the clustering algorithm suitable for visualization of eye gaze data. Such a visualization greatly facilitates data analysis by grouping the individual samples into more meaningful units referred to as gaze fixations.

Abstract: Credits granting are very important parts of banks' activities, as they may give big profits, but there is a big risk connected with making decisions in this area and mistakes may be very costly for financial institutions. The main idea in credit risk evaluation investigations consists of building classification rules that assign properly bank customers as good or bad payers. In the paper, the system based on combination of unsupervised and supervised clas- sification is proposed. In the first step, by using clustering algorithm, clients are segmented into groups with similar features. In the second step, decision trees are built and classification rules, for each group of clients, are defined. To avoid redundancy, different attributes are taken into account during each kind of classification. The proposed approach allows for using different rules within the same data set, and for defining more accurately clients with high risk. The system was tested on the real credit-risk data sets. Some exemplary results concerning different groups of clients are presented.

Abstract: This paper presents a novel technique of optimization of parameters of the UPQC using Genetic Algorithm (GA) method that takes curves of bode as a basis. The choice of the parameters of the shunt active filter is determined by the ratio of its generated current to the harmonic current, while the choice of the parameters of the series active filter is determined by the ratio of its generated voltage to the harmonic voltage. The total impedance of the whole system without load shows that a phenomenon of resonance could appear. To overcome the problem of reso-nance and widen the pass band, the Genetic Algorithm method was used. Simulation results are presented to validate the proposed method.

Abstract: Copper Institute, Industrial Informatics department, is developing and applying network real time process monitoring and control systems. The kernel of those systems is the microprocessor measuring station - MMS. In hardware and software point of view, MMS is a type of PLC (programmable logic controller) with some of local and remote functional possibilities. In monitoring and control of technological processes in many production plants, occurs a necessity for transfer of information and interaction with the process from remote distances (from control center, for example). It is obvious that for these requirements there should be available monitoring and control systems for operation in network environment. Special attention is paid to communication sub-systems, i.e. development of cost viable and in practice easily applied solution. Some of these systems are already in use. The paper presents hardware and software characteristics and performances, with special regard to network operation and possibilities.

Abstract: There are many tools suitable to model systems and to generate software code from system models, but these tools do not support data validation. Available data validation tools are domain specific and require manual definition of data validation rules. Thus, the lack of the tool supporting both system modelling and automated gene-ration of data validation rules from system models is obvious. The paper discusses the use of system models repre-sented by UML in automation of data validation. The method to derive rules from UML models is presented. A fragment of UML model and derivation of rules represented in the model is demonstrated. The tool supporting proposed method is introduced and the process of automated data validation rules generation from UML models is presented.

Abstract: The possibility to perform correct and automatic model transformation during reasonable short time is vital in the development of software applications. We analyse transformation of ontology axioms into rule model, which is an important and integral part of each conceptual data model. Therefore, the main aim of this research is to adopt the appropriate model based transformation approach for the transformation of ontology axioms into a rule model.

Abstract: In this paper, the diagonal majorization algorithm (DMA) has been investigated. The research focuses on the possibilities to increase the efficiency of the algorithm by disclosing its properties. The diagonal majorization algorithm is oriented at the multidimensional data visualization. The experiments have proved that, when visualizing large data set with DMA, it is possible to save the computing time taking into account several factors: the strategy of numbering of multidimensional vectors in the analysed data set and the neighbourhood order parameter.

Abstract: The test can be developed at the functional level of the circuit. Such an approach allows developing the test at the early stages of the design process in parallel with other activities of this process. The main problem is the achievement of the high quality of the functional test that would be applicable at the gate level implementation of the circuit. The paper presents an algorithm of the functional delay test generation and results of its application to the benchmark circuits. The algorithm is based on the criteria of the quality assessment of the functional test consisting of the pairs of patterns with multiple signal transitions. The criteria are based solely on the primary input values and the primary output values of the software prototype. The criteria allow evaluating the robust and the non-robust test patterns. The presented experimental results demonstrate that the non-robust test patterns enable to increase the transition fault coverage. The use in the pair of test patterns with multiple input transitions enables to decrease the size of test set without loss of transition fault coverage.

Abstract: Knowing website traffic flow and structure is essential in order to make website successful and better target visitors. In this article website traffic and structure analysis models in combination of intelligent methods are proposed and theoretical predictions are made on how and what factor changes in website structure will affect visitor click paths and overall website activity.

Abstract: The problem of automation of syntactic analysis of the Lithuanian simple sentences is investigated. The features of Lithuanian language – great inflexion and free word order in a sentence – which raise the specific claims for solving the problem of syntactic analysis of Lithuanian sentences are highlighted. The formalized procedure of syntactic analysis is based on the Backus and Naur formalism. The possibilities of extension of the boundaries of the procedure for syntactic analysis are shown. The article presents an algorithm and software for syntactic analysis of Lithuanian simple sentences. The accuracy of performance of the system was evaluated.

Abstract: This work describes an investigation of spectral properties of the voiceless velar stop consonant [k] of Lithuanian. Investigations are based on two Lithuanian corpora: the isolated word corpus VDU-ISO4 and the corpus of short connected phrases VDU-TRI4. Investigations showed that spectra of a plosive [k] exhibit maxima at a frequency corresponding to the second formant of the vowel following plosive [k] and a context independent maximum at 4000 Hz. Properties of these maxima were investigated separately for male and female speech, and for long and short vowel contexts. Results are useful for automatic speech recognition.

Abstract: Business rules approach is quite new and oriented at software systems in which the rules are separated, logically and physically, from other aspects of the system In this paper some of the methods for description of the business are discussed Business rules activation from database triggers is presented Implemented prototype and algorithms are discussed

Abstract: In the paper, a new original procedure for the evaluation of discrete Haar spectra for separate fragments (blocks) of a digital image is proposed. The procedure explores specific properties of Haar wavelets, refers to the assumption that Haar spectrum of the whole image is known, and is much faster than direct evaluation of Haar spectral coefficients for the respective image blocks. It is shown that the developed procedure can be successively applied to implementing of a locally progressive image encoding idea. The essence of the latter – selected blocks of the image under processing are compressed into a bit stream with increasing accuracy. To translate the idea into action, direct employment of hyperbolic image filters is proposed. Preliminary experimental results show that the developed approach leads to reasonable image compression ratios and sufficiently high quality of restored image blocks.

Abstract: Internet- technology is nowadays commonly used in the financial sector, mainly in the field of customerrelations. Electronic finance covers the full system of the customer relationship management, a.k.a. phone, fax, e-mail, mobile and web-channels. This study covers only the usage, advantages and disadvantages of internet-based channels. Transferring information and carrying out transactions via the electronic channels is beneficial for the financial institutions as well as the clients. The role of the traditional infrastructure, the branch-system has to be adapted to the needs of the future. This study summarizes the experiences of the Hungarian digital banking industry based on personal interviews and public statistical and academic resources. It covers the description of solutions, services and clientele in the modern on-line banking systems and shows a perspective of how the financial institutions should step forward towards the maximal fulfillment of the digital needs.

Abstract: The aim of this paper is a computer study of the system for simulation and optimization of interbank settlements. The system is based on the Poisson-lognormal model of settlement flow and performs iterative simulation and optimization of expected transaction costs using randomly generated samples of transaction flows. The results of study by Monte-Carlo simulation are given, based on data of the payment and settlement system of the Bank of Lithuania.

Abstract: A nonrecursive and recursive algorithms are proposed for estimation of the linear periodically time- varying (LPTV) system parameters. Using a block approach, the parameter estimation problem is transformed into one-dimensional minimization problem for L set parameters of the LPTV system. The algorithm can be performed in parallel at L time moments for each set of parameters to reduce the computation time.

Abstract: The purpose of this research in the queueing theory is the theorem about the law of the iterated logarithm in multiphase queueing systems and its application to the mathematical model of the message switching system. First we proof the law of the iterated logarithm for the cumulative idle time of a customer. Then we present an application of the proved theoremfor the model of the message switching system.

Abstract: It was proved that genetic algorithms are the most powerful unbiased optimization techniques for sampling a large solution space. Because of unbiased stochastic sampling, they were quickly adapted in image processing. They were applied for the image enhancement, segmentation, feature extraction and classification as well as the image generation. This article gives a brief overview of the canonical genetic algorithm and it also reviews the tasks of image pre-processing. The survey of publications of this topic leads to the conclusion that the field of genetic algorithms applications is growing fast. The constant improvement of genetic algorithms will definitely help to solve various complex image processing tasks in the future.

Abstract: The subject of this paper is the improving of local search for the traveling salesman problem (TSP). In particular, a so-called fast descent-random ascent (FDRA) strategy is proposed. The FDRA approach is based on the fast-modified 2-opt algorithm combined with certain perturbation (random ascent) procedures. The results obtained from the experiments demonstrate that the new improved local search strategy is better than the other local search algorithms. This approach may also be applied to other combinatorial optimization problems.

Abstract: This paper presents an approach to cash management for automatic teller machine (ATM) network. This approach is based on an artificial neural network to forecast a daily cash demand for every ATM in the network and on the optimization procedure to estimate the optimal cash load for every ATM. During the optimization procedure, the most important factors for ATMs maintenance were considered: cost of cash, cost of cash uploading and cost of daily services. Simulation studies show, that in case of higher cost of cash (interest rate) and lower cost for money uploa-ding, the optimization procedure allows to decrease the ATMs maintenance costs around 15-20 %. For practical imple-mentation of the proposed ATMs’ cash management procedure, further experimental investigations are necessary.