University of Tabriz

About: University of Tabriz is a education organization based out in Tabriz, Iran. It is known for research contribution in the topics: Population & Nanocomposite. The organization has 12141 authors who have published 20976 publications receiving 313982 citations.

GIS-multicriteria decision analysis for landslide susceptibility mapping: comparing three methods for the Urmia lake basin, Iran

Abstract: The GIS-multicriteria decision analysis (GIS-MCDA) technique is increasingly used for landslide hazard mapping and zonation. It enables the integration of different data layers with different levels of uncertainty. In this study, three different GIS-MCDA methods were applied to landslide susceptibility mapping for the Urmia lake basin in northwest Iran. Nine landslide causal factors were used, whereby parameters were extracted from an associated spatial database. These factors were evaluated, and then, the respective factor weight and class weight were assigned to each of the associated factors. The landslide susceptibility maps were produced based on weighted overly techniques including analytic hierarchy process (AHP), weighted linear combination (WLC) and ordered weighted average (OWA). An existing inventory of known landslides within the case study area was compared with the resulting susceptibility maps. Respectively, Dempster-Shafer Theory was used to carry out uncertainty analysis of GIS-MCDA results. Result of research indicated the AHP performed best in the landslide susceptibility mapping closely followed by the OWA method while the WLC method delivered significantly poorer results. The resulting figures are generally very high for this area, but it could be proved that the choice of method significantly influences the results.

Optimization of C.I. Acid Red 14 azo dye removal by electrocoagulation batch process with response surface methodology

Abstract: The decolorization of C.I. Acid Red 14 (AR14) azo dye by electrocoagulation (EC) process was studied in a batch reactor. Response surface methodology (RSM) was applied to evaluate the simple and combined effects of the three main independent parameters, current density, time of electrolysis and initial pH of the dye solution on the color removal efficiency and optimising the operating conditions of the treatment process. A 2 3 full factorial central composite face centred (CCF) experimental design was employed. Analysis of variance (ANOVA) showed a high coefficient of determination value ( R 2 = 0.928) and satisfactory prediction second-order regression model was derived. Maximum color removal efficiency was predicted and experimentally validated. The optimum current density, time of electrolysis and initial pH of the dye solution were found to be 102 A m −2 , 4.47 min and 7.27, respectively. Under optimal value of process parameters, high removal (>91%) was obtained for Acid Red 14. This study clearly showed that response surface methodology was one of the suitable methods to optimize the operating conditions and maximize the dye removal. Graphical response surface and contour plots were used to locate the optimum point.

Cascaded Multilevel Inverter With Series Connection of Novel H-Bridge Basic Units

Abstract: In this paper, a new single-phase cascaded multilevel inverter based on novel H-bridge units is proposed. In order to generate all voltage levels (even and odd) at the output, nine different algorithms are proposed to determine the magnitudes of dc voltage sources. Then, the proposed algorithms are compared to investigate their advantages and disadvantages. This topology is able to increase the number of output voltage levels by using a lower number of power electronic devices such as switches, power diodes, driver circuits, and dc voltage sources that lead to reduction in installation space and cost of the inverter. In addition, in the proposed cascaded multilevel inverter, not only the number of required power electronic devices is reduced, but also the amount of the blocked voltage by switches, and the number of different voltage amplitudes of the used sources is decreased. These features are some of the most important advantages of the proposed topology. These features are obtained via the comparison of the proposed topology and its proposed algorithms with the conventional cascaded multilevel inverters that have been presented in the literatures. The operation and performances of the proposed topology with its presented algorithms in generating all voltage levels have been verified by using the experimental results of a 49-level single-phase inverter.

Wavelet-based emotion recognition system using EEG signal

Abstract: In this research, emotional states in arousal/valence dimensions have been classified using minimum number of channels and frequency bands of EEG signal. Using the discrete wavelet transforms, EEG signals have been decomposed to corresponding frequency bands and then several features have been extracted. The support vector machine and K-nearest neighbor classifiers have been used to detect the emotional states from the extracted features. For the recorded 10-channel EEG signal, results illustrate the classification accuracy of 86.75 % for arousal level and 84.05 % for valence level. Moreover, using the high-frequency bands, specifically gamma band, yields higher accuracy compared to using low-frequency bands of EEG signal. All of these support to the development of a real-time emotion classification system.