0000000000239933

AUTHOR

Paulis ĶIkusts

showing 3 related works from this author

Application of Graph Clustering and Visualisation Methods to Analysis of Biomolecular Data

2018

In this paper we present an approach based on integrated use of graph clustering and visualisation methods for semi-supervised discovery of biologically significant features in biomolecular data sets. We describe several clustering algorithms that have been custom designed for analysis of biomolecular data and feature an iterated two step approach involving initial computation of thresholds and other parameters used in clustering algorithms, which is followed by identification of connected graph components, and, if needed, by adjustment of clustering parameters for processing of individual subgraphs.

0301 basic medicineComputer scienceComputationcomputer.software_genreVisualization03 medical and health sciencesIdentification (information)ComputingMethodologies_PATTERNRECOGNITION030104 developmental biology0302 clinical medicineGraph drawingFeature (machine learning)Data miningCluster analysiscomputer030217 neurology & neurosurgeryConnectivityClustering coefficient
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Root cause analysis of large scale application testing results

2015

In this paper we present a new root cause analysis algorithm for discovering the most likely causes of the differences found in testing results of two versions of the same software. The problematic points in test and environment attribute hierarchies are presented to the user in compact way which in turn allows to save time on test result processing. We have proven that for clearly separated problem causes our algorithm gives exact solution. Practical application of described method is discussed.

Scale (ratio)Computer science020209 energyApplied Mathematics0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingSoil scienceRoot cause analysis regression testing hierarchy graphs.02 engineering and technologyRoot cause analysisInformation Systems
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Taisnes nogriežņu telpiskas tīklveida konfigurācijas algoritmiska atpazīšana no stereopāra

2017

Mācību rakstura mēģinājums telpiski atpazīt specifiskus stereopārus, kurus veido telpisku ģeometrisku grafu divas plakanas projekcijas. Aplūkoto ģeometrisko grafu šķautnes ir taisnes nogriežņi, bet virsotnes šo nogriežņu galapunkti. Ar šādiem grafiem, kurus saucam arī par nogriežņu tīkliem, mēs vienkāršoti un abstrakti modelējam gan dabisku, gan mākslīgu telpiskus tīklus veidojošu līniju struktūru fundamentālo uzbūvi. Piemēram, organisma asinsvadu tīklus vai augu lapu dzīslojumus bioloģijā, vai dažādas stieņu konstrukcijas sadzīvē un industrijā. Šādā nostādnē algoritmiskajā apstrādē dominē struktūru kombinatoriskais aspekts, kuru tad arī mēs izvēršam savā darbā. Mūsu mērķis bija pārliecināt…

stereopāris telpisks ģeometrisks grafs telpisks taisnes nogrieznis stereo atbilstība
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