Computational Science and Techniques

The amount of information on the internet grows exponentially. It isnot enough anymore just to have a general access to this huge amount of data,instead it is becoming a necessity to be able to use different kinds ofautomatic filters to retrieve just the information you actually want. One solution for the information filtering and retrieval is context analysis in which one of the contexts of interest is the geographic context. This paper studies the problem and methodology of geoparsing – recognition of geographic names in unstructured textual content for the aim of extracting geographic context. A prototype implementation of a geoparsing system, capable of automatically analyzing unstructured text, recognizing geographic information and marking geographic names, is developed. Empirical evaluation of the system using articles from real-world news showed that the average quality of its geographic name recognition varies around 75-100%. Possible applications of the developed prototype include automated grouping of any texts by their geographic contexts (e.g., in news portals) and location-based search. Preliminary results of empirical evaluation showed that the average rate of its geographic name recognition varies around 75-100%.

This work contains Monte–Carlo Markov Chain algorithm for estimation of multi-dimensional rare events frequencies. Logits of rare event likelihood we are modeling with Poisson distribution, which parameters are distributed by multivariate normal law with unknown parameters – mean vector and covariance matrix. The estimations of unknown parameters are calculated by the maximum likelihood method. There are equations derived, those must be satisfied with model’s maximum likelihood parameters estimations. Positive definition of evaluated covariance matrixes are controlled by calculating ratio between matrix maximum and minimum eigenvalues.

In this research, parallel computing capabilities of MATLAB and the capabilities for the finite element method were analyzed. A program for solving a heat transfer problem by the finite element method was implemented. Three different parallel algorithms using CPU and GPU for solving steady state and transient heat transfer problems were proposed and implemented. A maximal speedup of around 2.3 times for steady state and 2 times for transient problem solving time was achieved by using a quad-core CPU.

Computational modeling of a biosensor with allosteric enzyme layer was investigated in this study. The operation of the biosensor is modeled using non-stationary reaction-diffusion equations. The model involves three regions: the allosteric enzyme layer where the allosteric enzyme reactions as well as then mass transport by diffusion take place, the diffusion region where the mass transport by diffusion and non-enzymatic reactions take place and the convective region in which the analyte concentration is maintained constant. The biosensor response on dependency substrate concentration, cooperativity coefficient and the diffusion layer thickness on the same parameters have been studied.

It is important for an organization to know what capability/maturity of the process a chosen methodology could ensure. This paper is focused on DSDM Atern process maturity by CMMI.

A well-known example of global optimization that provides solutions within fixed error limits is optimization of functions with a known Lipschitz constant. In many real-life problems this constant is unknown.

The issue of making contracts between services in Service-Oriented Architecture (SOA) arises naturally, because in real life services are subjects for negotiation and contracting. The notion of contract in SOA is rather misleading, because usually means just technical specification – input and output parameters, pre- and postconditions. However, there are also other aspects of contract. Service Level Agreements (SLAs) often are used together with technical contract. SLAs describes the level of service expected by a customer from a supplier, laying out the metrics by which that service is measured, the remedies or penalties in case the agreed-upon levels are not achieved. The paper aim to clear up the notions of contract and agreement in SOA, discusses the properties of languages that are used to specify contacts and agreements, paying special attention to their legal aspects and comparing contract features in WS-Agreement ir WSLA.

Breast cancer is the most frequent women cancer form and one of the leading mortality causes among women around the world. Patients with pathological mutation of a BRCA gene have 65% lifelong breast cancer probability. It is known that such patients have different cause of illness. In this study, we have proposed a new approach for the prediction of BRCA mutation carriers by methodically applying knowledge discovery steps and utilizing data mining methods. An alternative BRCA risk assessment model has been created utilizing decision tree classifier model. The biggest challenge was a very small size and imbalanced nature of the initial dataset, which have been collected by clinicians during 4 years of clinical trial. Iterative optimization of initial dataset, optimal algorithms selection and their parameterization have resulted in higher classifier model performance, with acceptable prediction accuracy for the clinical usage. In this study, three data mining problems have been analyzed using eleven data mining algorithms.

In this paper, we present a comparative analysis of hierarchical clustering and multidimensional scaling methods for genotype and phenotype data analysis. Fisher's exact test was applied to determinate dependencies between congenital anomalies. In order to determine the relationship between the dependences of congenital anomalies, deformations, these systems’ micro anomalies and congenital anomalies associated with orofacial clefs, the Spearman and Kendall correlation coefficients were applied. It has been detected which methods are better for genetic data visualization.

The purpose of this paper is to describe the computational algorithmic generation of the high-quality digital halftones (grey/colour patterns). At the beginning, the formal model for generation of the digital halftones, the so-called grey pattern problem (GPP) is introduced. Then, the heuristic algorithm for the solution, in particular, of the grey pattern problem is discussed. Although the algorithm employed does not guarantee the optimality of the solutions found, still superior-quality, near-optimal (and in some cases probably optimal) solutions can be achieved within reasonable computation time. Further, we provide the results of the extensive computational experiments with the newly proposed, extra-large size instance (data set) of the GPP — which is the main contribution of this work. As a confirmation of the quality of the solutions produced, we also give the visual representations of several fine-looking halftone patterns and the reader can judge about the perfection of the images obtained.