Bartosz Świderski

Detection of ‘Orange Skin’ Type Surface Defects in Furniture Elements with the Use of Textural Features

The accuracy of detecting the orange skin surface defect in lacquered furniture elements was tested. Textural features and an SVM classifier were used. Features were selected from a set of 50 features with the bottom-up feature selection strategy driven by the Fisher measure. The features selected were the Kolmogorow-Smirnow-based features, some of the Hilbert curve-based features, some of the maximum subregions features and also some of the thresholding-based features. The Otsu thresholding and percolation-based features were all rejected. The images of size \(300\,\times \,300\) pixels cut from the original, larger images were treated as objects. There were three quality classes: very good, good and bad. In the cross-validation process where the testing sets consisted of 90 and the training sets of 910 objects the accuracies ranged from 90% to 98% and the average accuracy was 94%. The tests revealed that more research should be done on the choice of features for this problem.

System for automatic heart rate calculation in epileptic seizures

This article presents a comprehensive system for automatic heart rate (HR) detection. The system is robust and resistant to disturbances (noise, interferences, artifacts) occurring mainly during epileptic seizures. ECG signal filtration (IIR) and normalization due to skewness and standard deviation were used as preprocessing steps. A key element of the system is a reference QRS complex pattern calculated individually for each ECG recording. Next, a cross-correlation of the reference QRS pattern with short, normalized ECG windows is calculated and the maxima of the correlation are found (R-wave locations). Determination of the RR intervals makes possible calculation of heart rate changes and also heart rate variability (HRV). The algorithm was tested using a simulation in which a noise of an amplitude several times higher than ECG standard deviation levels was added. The proposed algorithm is characterized by high QRS detection accuracy, and high sensitivity and specificity. The algorithm proved to be useful in clinical practice, where it was used to automatically determine HR for ECG signals recorded before and during 58 focal seizures in 56 adult patients with intractable temporal lobe epilepsy.

Feature Selection for ‘Orange Skin’ Type Surface Defect in Furniture Elements

The surfaces of furniture elements having the orange skin surface defect were investigated in the context of selecting optimum features for surface classification. Features selected from a set of 50 features were considered. Seven feature selection methods were used. The results of these selections were aggregated and found consistently positive for some of the features. Among them were primarily the features based on local adaptive thresholding and on Hilbert curves used to evaluate the image brightness variability. These types of features should be investigated further in order to find the features with more significance in the problem of surface quality inspection. The groups of features which appeared least profitable in the analysis were the two features based on percolation, and the one based on Otsu global thresholding.

Beta Stability Over Bull and Bear Market on the Warsaw Stock Exchange

Abstract Beta parameter is one of the commonly used measures of the investment risk of individual stock or portfolio. It plays a crucial role in modern portfolio theory particularly in management of financial investment portfolios. In the field of beta parameter, numerous studies have been conducted, especially beta properties stability in the context of the stock market cycle phases, measuring frequency of rate of return, and the length of a sample period. There are much fewer studies concerned beta parameter in the countries of Central and Eastern Europe which have undergone systemic transformation at the end of the previous century. From a scientific point of view, it is interesting to know how the beta parameter behaves in these countries. The main goal of this article is to examine the beta parameter stability over bull and bear market conditions on the Warsaw Stock Exchange. The paper presents an analysis of beta stability for 134 stocks of the largest companies listed at the WSE during years 2005–2013. To verify statistically the hypothesis of beta parameter stability, we used monthly returns in the Sharpe’s single-index model. In the first part of the article, we present a brief review of the literature and methodology of the study, while in the second part, the obtained results and conclusions are shown.

Intervalling Effect on Estimating the Beta Parameter for the Largest Companies on the WSE

Abstract In the modern portfolio theory investment risk plays a crucial role. It is the subject of numerous studies and publications, in particular in relation to the management of investment portfolios. Commonly used measure of investment management in equities is a beta parameter, which is used to estimate individual stock risk and portfolio risk. In particular, numerous studies the subject of which are the beta parameter properties such as stability in the context of the stock market cycle phases, intervalling effect, length estimation sample etc. The main objective of this paper is to investigate the intervalling effect on the beta parameter. The empirical analysis is carried out for the 33 largest companies of the Warsaw Stock Exchange (WSE) on a sample from the years 2005 to 2012 on the basis of daily, weekly and monthly rates of return. Statistical verification of the hypothesis of the importance of the frequency measuring the return of shares will be based on the single-index Sharpe’s model.