Informatica

Most classification algorithms involve subjective inputs or hyperparameters to be determined prior to performing the classification. When taking different input or hyperparameter values, each classification algorithm will comprise a collection of classifiers. In this work, we propose a data-driven methodology for assessing similarity in consensus agreement within such a collection of classifiers, and between two classification algorithms, conditional on the dataset of interest. The core of our approach lies in considering the variability introduced by different hyperparameter values for each algorithm when performing such comparisons. We address these problems by evaluating the similarity through consensus agreement and by proposing the application of asymmetric similarity indices based on the Jaccard coefficient. We present the proposed methodology on two publicly available datasets.

In this paper, a modified version of the discrete wavelet transform (DWT), distinguishing itself with visibly improved space localization properties and noticeably extended potential capabilities, is proposed. The key point of this proposal is the full decorrelation of wavelet coefficients across the lower scales. This proposal can be applied to any DWT of higher orders (Le Gall, Daubechies D4, CDF 9/7, etc.). To open up new areas of practical applicability of the modified DWT, a novel exceptionally fast algorithm for computing the DWT spectra of the selected signal (image) blocks is presented. In parallel, some considerations and experimental results concerning the energy compaction property of the modified DWT are discussed.

The paper addresses the over-saturated protein spot detection and extraction problem in two-dimensional electrophoresis gel images. The effective technique for detection and reconstruction of over-saturated protein spots is proposed. The paper presents: an algorithm of the median filter mask adaptation for initial filtering of gel image; the models of over-saturation used for gel image analysis; several models of protein spots used for reconstruction; technique of the automatic over-saturated protein spot search and reconstruction. Experimental investigation confirms that proposed search technique lets to find up to 96% of over-saturated protein spots. Moreover the proposed flexible protein spot shape models for reconstruction are faster and more accurate in comparison to the flexible diffusion model.

The paper is devoted to analysis of the software peculiarities of the computer based ultrasonic imaging system for non-destructive) testing (NDT) applications. The developed software enables 1, 2, and 3-dimensional imaging of the intrinsic structure of the materials and measurement of their parameters.