Studia Informatica

Volume: 1-2(19)
Year: 2015
Publishing: Publishing House of University of Natural Science
Scientific Editor: Wojciech Penczek,
Review Board: PDF File
ISSN: 1731-2264


Bartyzel K.,
Algorithms optimization for the image processing and analysis by constructing parallel solutions
pp. 5-14
Abstract: This paper presents a concept of parallel programming in the context of image analysis and processing algorithms. It demonstrates an exact implementation of the issue of image filtration using the Microsoft .NET framework and the C# language. All technical aspects were subject to analysis. Presented are both theoretical considerations and nuances of implementation. An experiment was also conducted which consisted in the creation of an appropriate program to demonstrate an example noise filter and the recording of performance time in the case of synchronous and parallel execution. The solution analysis was tested on a typical, average laptop and a server with high computing power. The results unanimously show that applying parallel algorithms can significantly improve the effectiveness of the hardware used.
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Drozdek A., Vujanović D.,
Atomic-key B-trees
pp. 15-26
Abstract: Atomic-key B-trees are B-trees with keys of different sizes. This note presents two versions of an insertion algorithm and a deletion algorithm for atomic-key B-trees.
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Wawrzynczak A., Jaroszynski M., Borysiewicz M.,
Recognition of the atmospheric contamination source localization with the Genetic Algorithm
pp. 27-42
Abstract: We have applied the Genetic Algorithm (GA) to the problem of the atmospheric contaminant source localization. The algorithm input data are concentrations of given substance registered by sensor network. To achieve rapid-response event reconstruction,the fast-running Gaussian plume dispersion model is adopted as the forward model. The proposed GA scans 5-dimensional parametersspace searching for the contaminant source coordinates (x,y), release strength (Q) and the atmospheric transport dispersion coefficients. Based on the synthetic experiment data the GA parameters likepopulation size, number of generations and the genetic operators best suitable for the algorithm performance are identified. We demonstrate that proposed GA configuration can successfully point out the parameters of abrupt contamination source. Results indicate the probability of a source to occur at a particular location with a particular release rate. The shapes of the probability distribution function of searched parameters values reflect the uncertainty in observed data.
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Skaruz J., Niewiadomski A., Penczek W.,
Combining SMT and Simulated Annealing into a Hybrid Planning Method
pp. 43-48
Abstract: We present a new approach to the concrete planning (CP) - a stage of theWeb service composition in the PlanICS framework. A new hybrid algorithm (HSA) based on a combination of Simulated Annealing (SA) with Satisfiability Modulo Theories (SMT) has been designed and implemented. The main idea of our hybrid solution is to use an SMT-based procedure in order to generate an initial individual and then improve it during subsequent iterations of SA. The experimental results show that HSA is superior to the other methods we have applied to the CP problem, including Genetic Algorithm, an SMT-based approach, and our previously developed hybrids.
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