Wrocław University of Technology

About: Wrocław University of Technology is a education organization based out in Wrocław, Poland. It is known for research contribution in the topics: Laser & Fuzzy logic. The organization has 13115 authors who have published 31279 publications receiving 338694 citations.

Simultaneous measurement of multiparameters using a Sagnac interferometer with polarization maintaining side-hole fiber.

Abstract: A Sagnac interferometer with a section of a polarization maintaining side-hole fiber for multiparameter measurement is proposed The sensor was experimentally demonstrated to be sensitive to torsion, temperature, and longitudinal strain, simultaneously The birefringence in the investigated side-hole fiber is induced simultaneously by the elliptical shape of a germanium-doped core and by field overlap with the air holes surrounding the core The latter effect is purely geometrical and causes high chromatic dispersion of the group birefringence in the long wavelength range, which results in a different period of spectral interference fringes A different wavelength response is obtained for each interference fringe peak when the fiber is subjected to torsion, temperature, or longitudinal strain A matrix equation for simultaneous measurement of the three parameters--torsion, temperature, and longitudinal strain--is also proposed

An ensemble classification approach for melanoma diagnosis

Abstract: Malignant melanoma is the deadliest form of skin cancer, and has, among cancer types, one of the most rapidly increasing incidence rates in the world. Early diagnosis is crucial, since if detected early, its cure is simple. In this paper, we present an effective approach to melanoma identification from dermoscopic images of skin lesions based on ensemble classification. First, we perform automatic border detection to segment the lesion from the background skin. Based on the extracted border, we extract a series of colour, texture and shape features. The derived features are then employed in a pattern classification stage for which we employ a novel, dedicated ensemble learning approach to address the class imbalance in the training data and to yield improved classification performance. Our classifier committee trains individual classifiers on balanced subspaces, removes redundant predictors based on a diversity measure and combines the remaining classifiers using a neural network fuser. Experimental results on a large dataset of dermoscopic skin lesion images show our approach to work well, to provide both high sensitivity and specificity, and our presented classifier ensemble to lead to statistically better recognition performance compared to other dedicated classification algorithms.

Some catalytic properties of hydrothermally synthesised zinc aluminate spinel

Abstract: Two samples of zinc aluminate were hydrothermally synthesised from zinc acetate and different aluminium sources: basic aluminium nitrate or aluminium hydroxide. The textural properties of the prepared ZnAl2O4 samples are different from these one of the zinc aluminate prepared by conventional way. Powder XRD and TEM measurements reveal that samples are single-phase material or mixture of ZnAl2O4 with small amount of γ-Al2O3, with morphology of quasi-spherical shape. Catalytic properties of the hydrothermally obtained zinc aluminate and Pt (Pd) catalysts supported on them were investigated in the reactions of cyclohexene isomerisation and combustion of trichloroethylene, respectively. It was evidenced that activity and selectivity of the investigated materials could be qualitatively correlated with the part of the strong acid centres measured by TPD of NH3.