Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Conference Object Citation - Scopus: 2Resource Allocation Algorithm for a Relational Join Operator in Grid Systems(Association for Computing Machinery (ACM), 2012) Çokuslu, Deniz; Hameurlain, Abdelkader; Erciyeş, Kayhan; Morvan, FranckGrid systems become very popular during the last decade because of their rapidly increasing computational capabilities. On the other hand, the advances on different domains cause enormous increase in the scale of the manipulated data. This issue augments the importance of distributed query processing and causes researchers to port their underlying environment onto the grid systems. However the dynamicity, heterogeneity and large scale characteristics of grid systems pose new problems for the distributed query processing domain. Resource allocation for query processing in grid systems is one of these problems, which attracts many researchers' attention. In this paper, we propose a new resource allocation algorithm for one relational join operator in a query considering characteristics of the grid systems. We provide theoretical analyses of the proposed algorithm and we consolidate analyses with the simulations. Copyright © 2012 ACM.Conference Object Citation - WoS: 7Citation - Scopus: 11Noise Robust Speaker Verification Using Mel-Frequency Discrete Wavelet Coefficients and Parallel Model Compensation(Institute of Electrical and Electronics Engineers Inc., 2005) Tüfekçi, Zekeriya; Gürbüz, SabriInterfering noise severely degrades the performance of a speaker verification system. The Parallel Model Combination (PMC) technique is one of the most efficient techniques for dealing with such noise. Another method is to use features local in the frequency domain. Recently, Mel-Frequency Discrete Wavelet Coefficients (MFDWCs) [1, 2] were proposed as speech features local in frequency domain. In this paper, we discuss using PMC along with MFDWCs features to take advantage of both noise compensation and local features (MFDWCs) to decrease the effect of noise on speaker verification performance. We evaluate the performance of MFDWCs using the NIST 1998 speaker recognition and NOISEX-92 databases for various noise types and noise levels. We also compare the performance of these versus MFCCs and both using PMC for dealing with additive noise. The experimental results show significant performance improvements for MFDWCs versus MFCCs after compensating the Gaussian Mixture Models (GMMs) using the PMC technique. The MFDWCs gave 5.24 and 3.23 points performance improvement on average over MFCCs for -6 dB and 0 dB SNR values, respectively. These correspond to 26.44% and 23.73% relative reductions in equal error rate (EER), respectively.