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Eskisehir, Turkey

Eskisehir Osmangazi University , abbreviated as ESOGU, is located in Eskişehir, in the Eskişehir Province of Turkey. Wikipedia.


Tamyurek B.,Eskiehir Osmangazi University
IEEE Transactions on Power Electronics | Year: 2013

This paper presents the design of a high-performance sinusoidal pulsewidth modulation (SPWM) controller for three-phase uninterruptible power supply (UPS) systems that are operating under highly nonlinear loads. The classical SPWM method is quite effective in controlling the RMS magnitude of the UPS output voltages. However, it is not good enough in compensating the harmonics and the distortion caused specifically by the nonlinear currents drawn by the rectifier loads. The distortion becomes more severe at high power where the switching frequency has to be reduced due to the efficiency concerns. This study proposes a new design strategy that overcomes the limitations of the classical RMS control. It adds inner loops to the closed-loop control system effectively that enables successful reduction of harmonics and compensation of distortion at the outputs. Simulink is used to analyze, develop, and design the controller using the state-space model of the inverter. The controller is implemented in the TMS320F2808 DSP by Texas Instruments, and the performance is evaluated experimentally using a three-phase 10 kVA transformer isolated UPS under all types of load conditions. In conclusion, the experimental results demonstrate that the controller successfully achieves the steady-state RMS voltage regulation specifications as well as the total harmonic distortion and the dynamic response requirements of major UPS standards. © 1986-2012 IEEE.


Cevikalp H.,Eskiehir Osmangazi University
Pattern Recognition Letters | Year: 2010

This study presents two new clustering algorithms for partition of data samples for the support vector machine (SVM) based hierarchical classification. A divisive (top-down) approach is considered in which a set of classes is automatically separated into two smaller groups at each node of the hierarchy. The first algorithm splits the data samples based on a variation of the normalized cuts (NCuts) clustering algorithm wherein the weights of adjacency matrix are modified to utilize class membership in the process. The second algorithm also uses the NCuts clustering; however, it considers the involved classes rather than the individual data samples. It uses the minimum distances between the convex hulls of classes as a distance measure for determining the weights of the graph. Splits are determined for both algorithms based on the eigenvector corresponding to the second smallest eigenvalue of a Laplacian matrix, and it is observed that the proposed algorithms generate well-separated and well-balanced clusters. Unlike other clustering methods used for this purpose, the methods in the present study are found to be more suitable when SVMs are used as base classifiers. As demonstrated in the experiments, the proposed clustering algorithms are integrated into the hierarchical SVM classifiers, which results in significantly improved testing times with a negligible decrease in classification accuracies as compared to the traditional multi-class SVMs. © 2010 Elsevier B.V. All rights reserved.


Gorenek B.,Eskiehir Osmangazi University
Minerva Medica | Year: 2013

Atrial fibrillation and sustained ventricular arrhythmias are the most common arrhythmias accompanying acute coronary syndromes. Arrhythmias are associated with worse clinical course and increased risk of in-hospital, short-term and long-term mortality in patients with ST-elevation myocardial infarction. This review summarizes the current knowledge on most prevalent arrhythmias in patients with ACS and their management in intensive coronary care unit.


Anik M.,Eskiehir Osmangazi University
Journal of Alloys and Compounds | Year: 2010

Mg2Ni and MgNi alloys were synthesized by the mechanical alloying and their electrochemical hydrogen storage characteristics were investigated. The XRD peaks indicated that MgNi alloy was mainly in the amorphous characteristics while Mg2Ni alloy was composed of mixture of amorphous and nano-crystalline structures. The development of the amorphous structure in MgNi alloy was very fast and the maximum storage capacity was reached at 15 h ball milling. The maximum storage capacity of Mg2Ni alloy was observable after at least 40 h ball milling. Both the initial discharge capacity and capacity retention rate of MgNi alloy were much greater than those of Mg2Ni alloy. This observation was mainly attributed to the relatively reversible charge/discharge behavior of MgNi alloy. The charge transfer resistance of Mg2Ni alloy was greater than that of MgNi alloy especially at the higher depths of discharges. The presence of free electro-catalytically active Ni particles on MgNi alloy surface was thought as the main reason for the facilitated hydrogen charge transfer reactions on this alloy. © 2009 Elsevier B.V. All rights reserved.


Eroglu S.,Eskiehir Osmangazi University
Physica A: Statistical Mechanics and its Applications | Year: 2013

The empirical law uncovered by Menzerath and formulated by Altmann, known as the Menzerath-Altmann law (henceforth the MA law), reveals the statistical distribution behavior of human language in various organizational levels. Building on previous studies relating organizational regularities in a language, we propose that the distribution of distinct (or different) words in a large text can effectively be described by the MA law. The validity of the proposition is demonstrated by examining two text corpora written in different languages not belonging to the same language family (English and Turkish). The results show not only that distinct word distribution behavior can accurately be predicted by the MA law, but that this result appears to be language- independent. This result is important not only for quantitative linguistic studies, but also may have significance for other naturally occurring organizations that display analogous organizational behavior. We also deliberately demonstrate that the MA law is a special case of the probability function of the generalized gamma distribution. © 2013 Elsevier B.V. All rights reserved.

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