Now showing items 1-13 of 13

    • CiSE: a circular spring embedder layout algorithm 

      Dogrusoz, U.; Belviranli, M. E.; Dilek, A. (Institute of Electrical and Electronics Engineers, 2013)
      We present a new algorithm for automatic layout of clustered graphs using a circular style. The algorithm tries to determine optimal location and orientation of individual clusters intrinsically within a modified spring ...
    • Computational analysis of complicated metamaterial structures using MLFMA and nested preconditioners 

      Ergul Ö.; Malas, T.; Yavuz Ç.; Ünal, A.; Gürel, L. (2007)
      We consider accurate solution of scattering problems involving complicated metamaterial (MM) structures consisting of thin wires and split-ring resonators. The scattering problems are formulated by the electric-field ...
    • EHPBS: Energy harvesting prediction based scheduling in wireless sensor networks 

      Akgun, B.; Aykın, Irmak (IEEE, 2013)
      The clustering algorithms designed for traditional sensor networks have been adapted for energy harvesting sensor networks (EHWSN). However, in these algorithms, the intra-cluster MAC protocols to be used were either not ...
    • Maximum likelihood estimation of Gaussian mixture models using particle swarm optimization 

      Arı, Ç.; Aksoy, S. (IEEE, 2010)
      We present solutions to two problems that prevent the effective use of population-based algorithms in clustering problems. The first solution presents a new representation for arbitrary covariance matrices that allows ...
    • Motion based clustering of model animations using PCA 

      Köse, K.; Çetin, A.E. (2009)
      In the last few years, there is great increase in capture and representation of real 3-Dimensonal scenes using 3D animation models. The 3D signals are then compressed, transmitted to the client side and reconstructed for ...
    • Multirelational k-anonymity 

      Nergiz, M. E.; Clifton, C.; Nergiz, A. E. (2007)
      k-Anonymity protects privacy by ensuring that data cannot be linked to a single individual. In a k-anonymous dataset, any identifying information occurs in at least k tuples. Much research has been done to modify a single ...
    • Multirelational k-anonymity 

      Nergiz, M.E.; Clifton, C.; Nergiz, A.E. (2009)
      k-Anonymity protects privacy by ensuring that data cannot be linked to a single individual. In a k-anonymous data set, any identifying information occurs in at least k tuples. Much research has been done to modify a ...
    • A new approach to search result clustering and labeling 

      Türel, Anıl; Can, Fazlı (Springer, Berlin, Heidelberg, 2011)
      Search engines present query results as a long ordered list of web snippets divided into several pages. Post-processing of retrieval results for easier access of desired information is an important research problem. In ...
    • Online balancing two independent criteria 

      Tse, Savio S.H. (Springer, 2008-10)
      We study the online bicriteria load balancing problem in this paper. We choose a system of distributed homogeneous file servers located in a cluster as the scenario and propose two online approximate algorithms for balancing ...
    • Parallel pruning for k-means clustering on shared memory architectures 

      Gürsoy, A.; Cengiz İ. (Springer Verlag, 2001)
      We have developed and evaluated two parallelization schemes for a tree-based k-means clustering method on shared memory machines. One scheme is to partition the pattern space across processors. We have determined that ...
    • Scene classification using bag-of-regions representations 

      Gökalp, D.; Aksoy, S. (2007)
      This paper describes our work on classification of outdoor scenes. First, images are partitioned into regions using one-class classification and patch-based clustering algorithms where one-class classifiers model the regions ...
    • Unsupervised classification of remotely sensed images using Gaussian mixture models and particle swarm optimization 

      Ari, C.; Aksoy, S. (2010)
      Gaussian mixture models (GMM) are widely used for un-supervised classification applications in remote sensing. Expectation-Maximization (EM) is the standard algorithm employed to estimate the parameters of these models. ...
    • A web-site-based partitioning technique for reducing preprocessing overhead of parallel PageRank computation 

      Cevahir, A.; Aykanat, C.; Turk, A.; Cambazoglu, B.B. (2007)
      A power method formulation, which efficiently handles the problem of dangling pages, is investigated for parallelization of PageRank computation. Hypergraph-partitioning-based sparse matrix partitioning methods can be ...