Bilgisayar Mühendisliği Bölümü Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12469/45

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Citation - WoS: 57
Citation - Scopus: 65
Beams: Backbone Extraction and Merge Strategy for the Global Many-To Alignment of Multiple Ppi Networks
(Oxford University Press, 2014) Alkan, Ferhat; Erten, Cesim
Motivation: Global many-to-many alignment of biological networks has been a central problem in comparative biological network studies. Given a set of biological interaction networks the informal goal is to group together related nodes. For the case of protein-protein interaction networks such groups are expected to form clusters of functionally orthologous proteins. Construction of such clusters for networks from different species may prove useful in determining evolutionary relationships in predicting the functions of proteins with unknown functions and in verifying those with estimated functions. Results: A central informal objective in constructing clusters of orthologous proteins is to guarantee that each cluster is composed of members with high homological similarity usually determined via sequence similarities and that the interactions of the proteins involved in the same cluster are conserved across the input networks. We provide a formal definition of the global many-to-many alignment of multiple protein-protein interaction networks that captures this informal objective. We show the computational intractability of the suggested definition. We provide a heuristic method based on backbone extraction and merge strategy (BEAMS) for the problem. We finally show through experiments based on biological significance tests that the proposed BEAMS algorithm performs better than the state-of-the-art approaches. Furthermore the computational burden of the BEAMS algorithm in terms of execution speed and memory requirements is more reasonable than the competing algorithms.
Citation - WoS: 15
Citation - Scopus: 19
Campways: Constrained Alignment Framework for the Comparative Analysis of a Pair of Metabolic Pathways
(Oxford University Press, 2013) Abaka, Gamze; Biyikoglu, Turker; Erten, Cesim
Motivation: Given a pair of metabolic pathways an alignment of the pathways corresponds to a mapping between similar substructures of the pair. Successful alignments may provide useful applications in phylogenetic tree reconstruction drug design and overall may enhance our understanding of cellular metabolism. Results: We consider the problem of providing one-to-many alignments of reactions in a pair of metabolic pathways. We first provide a constrained alignment framework applicable to the problem. We show that the constrained alignment problem even in a primitive setting is computationally intractable which justifies efforts for designing efficient heuristics. We present our Constrained Alignment of Metabolic Pathways (CAMPways) algorithm designed for this purpose. Through extensive experiments involving a large pathway database we demonstrate that when compared with a state-of-the-art alternative the CAMPways algorithm provides better alignment results on metabolic networks as far as measures based on same-pathway inclusion and biochemical significance are concerned. The execution speed of our algorithm constitutes yet another important improvement over alternative algorithms.
Citation - WoS: 35
Citation - Scopus: 41
Channel Estimation for Residual Self-Interference in Full-Duplex Amplify-And Two-Way Relays
(IEEE-INST Electrical Electronics Engineers Inc, 2017) Li, Xiaofeng; Tepedelenlioglu, Cihan; Şenol, Habib
Training schemes for full duplex two-way relays are investigated. We propose a novel one-block training scheme with a maximum likelihood estimator to estimate the channels between the nodes as well as the residual self-interference (RSI) channel simultaneously. A quasi-Newton algorithm is used to solve the estimator. As a baseline a multi-block training scheme is also considered. The Cramer-Rao bounds of the one-block and multi-block training schemes are derived. By using the Szego's theorem about Toeplitz matrices we analyze how the channel parameters and transmit powers affect the Fisher information. We show analytically that exploiting the structure arising from the RSI channel increases its Fisher information. Numerical results show the benefits of estimating the RSI channel.
Citation - WoS: 13
Citation - Scopus: 19
Channel Estimation for Tds-Ofdm Systems in Rapidly Time-Varying Mobile Channels
(IEEE-Inst Electrical Electronics Engineers Inc, 2018) Başaran, Mehmet; Şenol, Habib; Erküçük, Serhat; Çırpan, Hakan Ali
This paper explores the performance of time-domain synchronous orthogonal frequency-division multiplexing (TDS-OFDM) systems operated under rapidly time-varying mobile channels. Since a rapidly time-varying channel contains more unknown channel coefficients than the number of observations, the mobile channel can conveniently be modeled with the discrete Legendre polynomial basis expansion model to reduce the number of unknowns. The linear minimum mean square error (LMMSE) estimate can be exploited for channel estimation on inter-block-interference-free received signal samples owing to transmitting pseudo-noise (PN) sequences. In conventional TDS-OFDM systems, the channel estimation performance is limited due to estimating channel responses only from the beginning part of the channel. Therefore, a new system model named "partitioned TDS-OFDM system" is proposed to improve the system performance by inserting multiple PN sequences to the middle and end parts of the channel as well. In addition to providing the reconstruction error performance, Bayesian Cramer-Rao lower hound is derived analytically. Also, the LMMSE-based symbol detection is employed. To alleviate the negative effects of inter-carrier-interference (ICI) occuring in mobile channels, ICI cancellation is applied to enhance the detection performance. The simulation results demonstrate that the proposed TDS-OFDM system is superior to the conventional system and its corresponding performance is able to approach the achievable lower performance bound.
Citation - WoS: 47
Citation - Scopus: 60
A Computerized Recognition System for the Home-Based Physiotherapy Exercises Using an Rgbd Camera
(IEEE, 2014) Ar, İlktan; Akgül, Yusuf Sinan
Computerized recognition of the home based physiotherapy exercises has many benefits and it has attracted considerable interest among the computer vision community. However most methods in the literature view this task as a special case of motion recognition. In contrast we propose to employ the three main components of a physiotherapy exercise (the motion patterns the stance knowledge and the exercise object) as different recognition tasks and embed them separately into the recognition system. The low level information about each component is gathered using machine learning methods. Then we use a generative Bayesian network to recognize the exercise types by combining the information from these sources at an abstract level which takes the advantage of domain knowledge for a more robust system. Finally a novel postprocessing step is employed to estimate the exercise repetitions counts. The performance evaluation of the system is conducted with a new dataset which contains RGB (red green and blue) and depth videos of home-based exercise sessions for commonly applied shoulder and knee exercises. The proposed system works without any body-part segmentation bodypart tracking joint detection and temporal segmentation methods. In the end favorable exercise recognition rates and encouraging results on the estimation of repetition counts are obtained.
Citation - WoS: 2
Citation - Scopus: 3
The Effect of a Bump in an Elastic Tube on Wave Propagation in a Viscous Fluid of Variable Viscosity
(Elsevier Science, 2007) Demiray, Hilmi
In the present work treating the arteries as a thin walled prestressed elastic tube with a bump and the blood as a Newtonian fluid of variable viscosity we have studied the propagation of weakly nonlinear waves in such a medium by employing the reductive perturbation method in the longwave approximation. Korteweg-deVries-Burgers equation with variable coefficients is obtained as the evolution equation. Seeking a progressive wave type of solution to this evolution equation it is observed that the wave speed is variable. The numerical calculations show that the wave speed reaches to its maximum value at the center of the bump but it gets smaller and smaller as we go away from the center of the bump. Such a result seems to be reasonable from physical considerations. © 2006 Elsevier Inc. All rights reserved.
Citation - WoS: 29
Citation - Scopus: 31
Electrochromic Properties of Heat-Treated Thin Films of Ceo2-Tio2 Prepared by Sol-Gel Route
(Elsevier Science Bv, 2008) Ghodsi, Farhad E.; Tepehan, Fatma Zehra; Tepehan, Galip Gültekin
CeO2-TiO2-ZrO2 thin films were prepared using the sol-gel process and deposited on glass and ITO-coated glass substrates via dipcoating technique. The samples were heat treated between 100 and 500 degrees C. The heat treatment effects on the electrochromic performances of the films were determined by means of cyclic voltammetry measurements. The structural behavior of the film was characterized by atomic force microscopy and X-ray diffraction. Refractive index extinction coefficient and thickness of the films were determined in the 350-1000nm wavelength using nkd spectrophotometry analysis. Heat treatment temperature affects the electrochromic optical and structural properties of the film. The charge density of the samples increased from 8.8 to 14.8 mC/cm(2) with increasing heat-treatment temperatures from 100 to 500 degrees C. It was determined that the highest ratio between anodic and cathodic charge takes place with increase of temperature up to 500 degrees C. (c) 2007 Elsevier B.V. All rights reserved.
Citation - WoS: 27
Citation - Scopus: 27
Exploiting Heterogeneous Parallelism With the Heterogeneous Programming Library
(Academic Press Inc Elsevier Science, 2013) Vinas, Moises; Bozkuş, Zeki; Fraguela, Basilio B.
While recognition of the advantages of heterogeneous computing is steadily growing the issues of programmability and portability hinder its exploitation. The introduction of the OpenCL standard was a major step forward in that it provides code portability but its interface is even more complex than that of other approaches. In this paper we present the Heterogeneous Programming Library (HPL) which permits the development of heterogeneous applications addressing both portability and programmability while not sacrificing high performance. This is achieved by means of an embedded language and data types provided by the library with which generic computations to be run in heterogeneous devices can be expressed. A comparison in terms of programmability and performance with OpenCL shows that both approaches offer very similar performance while outlining the programmability advantages of HPL. (C) 2013 Elsevier Inc. All rights reserved.
Citation - WoS: 14
Force-Directed Approaches To Sensor Localization
(Association for Computing Machinery, 2010) Efrat, Alon; Forrester, David; Iyer, Anand; Kobourov, Stephen G.; Erten, Cesim; Kılış, Ozan
As the number of applications of sensor networks increases so does the interest in sensor network localization that is in recovering the correct position of each node in a network of sensors from partial connectivity information such as adjacency range or angle between neighboring nodes. In this article we consider the anchor-free localization problem in sensor networks that report possibly noisy range information and angular information about the relative order of each sensor's neighbors. Previously proposed techniques seem to successfully reconstruct the original positions of the nodes for relatively small networks with nodes distributed in simple regions. However these techniques do not scale well with network size and yield poor results with nonconvex or nonsimple underlying topology. Moreover the distributed nature of the problem makes some of the centralized techniques inapplicable in distributed settings. To address these problems we describe a multiscale dead-reckoning (MSDR) algorithm that scales well for large networks can reconstruct complex underlying topologies and is resilient to noise. The MSDR algorithm takes its roots from classic force-directed graph layout computation techniques. These techniques are augmented with a multiscale extension to handle the scalability issue and with a dead-reckoning extension to overcome the problems arising with nonsimple topologies. Furthermore we show that the distributed version of the MSDR algorithm performs as well as if not better than its centralized counterpart as shown by the quality of the layout measured in terms of the accuracy of the computed pairwise distances between sensors in the network.
Citation - WoS: 9
Citation - Scopus: 9
Growth Kinetics of Mps-Capped Cds Quantum Dots in Self-Assembled Thin Films
(Springer, 2012) Koç, Kenan; Tepehan, Fatma Zehra; Tepehan, Galip Gültekin
For this study we prepared colloidal CdS quantum dots using 3-mercaptopropyltrimethoxysilane as capping agent. Colloidal CdS quantum dots were directly deposited on glass substrates by a spin-coating process. Coated substrates were heat-treated between 225A degrees C and 325A degrees C for various heat treatment time intervals to investigate the growth kinetics of the quantum dots. Results showed that sizes of the CdS quantum dots grew approximately from 2.9 to 4.6 nm and the E (1s1s) energy values shifted approximately from 3.3 to 2.7 eV. Results showed that the average size of quantum dots increase by thermal treatment due to Ostwald ripening. The thermal process used to grow the size of quantum dots was examined according to the Lifshitz-Slyozov-Wagner theory. The activation energy of CdS quantum dots in thin films was calculated at approximately 44 kJ/mol.
Citation - WoS: 4
Citation - Scopus: 7
Improving Performances of Suboptimal Greedy Iterative Biclustering Heuristics Via Localization
(Oxford University Press, 2010) Erten, Cesim; Sözdinler, Melih
Motivation: Biclustering gene expression data is the problem of extracting submatrices of genes and conditions exhibiting significant correlation across both the rows and the columns of a data matrix of expression values. Even the simplest versions of the problem are computationally hard. Most of the proposed solutions therefore employ greedy iterative heuristics that locally optimize a suitably assigned scoring function. Methods: We provide a fast and simple pre-processing algorithm called localization that reorders the rows and columns of the input data matrix in such a way as to group correlated entries in small local neighborhoods within the matrix. The proposed localization algorithm takes its roots from effective use of graph-theoretical methods applied to problems exhibiting a similar structure to that of biclustering. In order to evaluate the effectivenesss of the localization pre-processing algorithm we focus on three representative greedy iterative heuristic methods. We show how the localization pre-processing can be incorporated into each representative algorithm to improve biclustering performance. Furthermore we propose a simple biclustering algorithm Random Extraction After Localization (REAL) that randomly extracts submatrices from the localization pre-processed data matrix eliminates those with low similarity scores and provides the rest as correlated structures representing biclusters. Results: We compare the proposed localization pre-processing with another pre-processing alternative non-negative matrix factorization. We show that our fast and simple localization procedure provides similar or even better results than the computationally heavy matrix factorization pre-processing with regards to H-value tests. We next demonstrate that the performances of the three representative greedy iterative heuristic methods improve with localization pre-processing when biological correlations in the form of functional enrichment and PPI verification constitute the main performance criteria. The fact that the random extraction method based on localization REAL performs better than the representative greedy heuristic methods under same criteria also confirms the effectiveness of the suggested pre-processing method.
Citation - WoS: 78
Citation - Scopus: 86
Joint Channel Estimation Equalization and Data Detection for Ofdm Systems in the Presence of Very High Mobility
(IEEE-INST Electrical Electronics Engineers Inc, 2010) Panayırcı, Erdal; Şenol, Habib; Poor, H. Vincent
This paper is concerned with the challenging and timely problem of joint channel estimation equalization and data detection for uplink orthogonal frequency division multiplexing (OFDM) systems in the presence of frequency selective and very rapidly time varying channels. The resulting algorithm is based on the space alternating generalized expectation maximization (SAGE) technique which is particularly well suited to multicarrier signal formats leading to a receiver structure that also incorporates interchannel interference (ICI) cancelation. In order to reduce the computational complexity of the algorithm band-limited discrete cosine orthogonal basis functions are employed to represent the rapidly time-varying fading channel by the discrete cosine serial expansion coefficients. It is shown that depending on the normalized Doppler frequency only a small number of expansion coefficients is sufficient to approximate the channel perfectly and there is no need to know the correlation function of the input signal. In this way the resulting reduced dimensional channel coefficients are estimated and the data symbols detected iteratively with tractable complexity. The proposed SAGE joint detection algorithm updates the data sequences serially and the channel parameters are updated in parallel leading to a receiver structure that also incorporates ICI cancelation. Computer simulations show that the cosine transformation represents the time-varying channel very effectively and the proposed algorithm has excellent symbol error rate and channel estimation performance even with a very small number of channel expansion coefficients employed in the algorithm resulting in substantial reduction of the computational complexity.
Citation - WoS: 9
Citation - Scopus: 11
Leveraging Saving-Based Algorithms by Master-Slave Genetic Algorithms
(Pergamon-Elsevier Science Ltd, 2011) Battarra, Maria; Benedettini, Stefano; Roli, Andrea
Saving-based algorithms are commonly used as inner mechanisms of efficient heuristic construction procedures. We present a general mechanism for enhancing the effectiveness of such heuristics based on a two-level genetic algorithm. The higher-level algorithm searches in the space of possible merge lists which are then used by the lower-level saving-based algorithm to build the solution. We describe the general framework and we illustrate its application to three hard combinatorial problems. Experimental results on three hard combinatorial optimization problems show that the approach is very effective and it enables considerable enhancement of the performance of saving-based algorithms. (C) 2011 Elsevier Ltd. All rights reserved.
Citation - WoS: 18
Citation - Scopus: 18
Modeling the Optical Properties of Wo(3) and Wo(3)-Sio(2) Thin Films
(Elsevier Science Bv, 2008) Saygin-Hinczewski, Dursen; Hinczewski, Michael; Sorar, İdris; Tepehan, Fatma Zehra; Tepehan, Galip Gültekin
The optical properties and surface morphology of sol-gel spin coated WO(3) and WO(3)-SiO(2) composite films annealed at 250 and 400 degrees C are investigated. For the purpose of extracting the optical parameters of the films a novel form for the dielectric function is introduced consisting of two Tauc-Lorentz oscillators and an Urbach tail component which is suited for amorphous multi-transition materials with substantial subgap absorption. The evolution of the refractive indices transmittances and band gaps with doping is marked by sizable shifts at 2.0-2.5% SiO(2) doping for the 250 degrees C films and 4.0-4.5% doping for the 400 degrees C films. In addition pronounced changes in the surface roughness of the films occur at these doping values. (c) 2008 Elsevier B.V. All rights reserved.
Citation - WoS: 36
Citation - Scopus: 37
Nondata-Aided Joint Channel Estimation and Equalization for Ofdm Systems in Very Rapidly Varying Mobile Channels
(IEEE-INST Electrical Electronics Engineers Inc, 2012) Şenol, Habib; Panayırcı, Erdal; Poor, H. Vincent
This paper is concerned with the challenging and timely problem of joint channel estimation and equalization for orthogonal frequency division multiplexing (OFDM) systems in the presence of frequency selective and very rapidly time varying channels. The resulting algorithm is based on the space alternating generalized expectation maximization-maximum a posteriori probability (SAGE-MAP) technique which is particularly well suited to multicarrier signal formats. The algorithm is implemented in the time-domain which enables one to use the Gaussian approximation of the transmitted OFDM samples. Consequently the averaging process of the nonpilot data symbols becomes analytically possible resulting in a feasible and computationally efficient channel estimation algorithm leading to a receiver structure that yields also an equalized output from which the data symbols are detected with excellent symbol error rate (SER) performance. Based on this Gaussian approximation the exact Bayesian Cramer Rao lower bound (CRLB) as well as the convergence rate of the algorithm are derived analytically. To reduce the computational complexity of the algorithm discrete Legendre orthogonal basis functions are employed to represent the rapidly time-varying fading channel. It is shown that depending on the normalized Doppler frequency only a small number of expansion coefficients is sufficient to approximate the channel very well and there is no need to know the correlation function of the input signal. The computational complexity of the algorithm is shown to be similar to O(NL) per detected data symbol and per SAGE-MAP algorithm cycle where N is the number of OFDM subcarriers and L is the number of multipath components.
Citation - WoS: 12
Citation - Scopus: 12
Optical and Structural Properties of Sol-Gel Made Ce/Ti Mixed Oxide Thin Films as Transparent Counter Electrode for Electrochromic Devices
(Elsevier Science Bv, 2008) Ghodsi, Farhad E.; Tepehan, Fatma Zehra; Tepehan, Galip Gültekin
Ce/Ti/Zr mixed oxide thin films were prepared using sol-gel process with mole ratios from 45/5 to 5/45 of Ti/Zr and 50 of Cc and deposited by dip coating technique. Optical electrochromic and structural properties of such films were investigated. The thickness refractive index and extinction coefficient of the films were calculated through transmission and reflection measurement by an nkd spectrophotometer. The surface morphology and structural behaviors of the films were characterized by atomic force microscopy and X-ray diffraction. Cyclic voltammetry measurements also were used to study electrochromic properties of these films. The best counter electrode Ce/Ti/Zr oxide thin film is achieved for the sample with a mole ratio of 40/10 of Ti/Zr. The ratio between anodic and cathodic charge is about 0.95 for this sample with a surface roughness of 1.8 nm. (C) 2008 Elsevier B.V. All rights reserved.
Citation - WoS: 19
Citation - Scopus: 21
Optical and Structural Properties of Ta2o5-Ceo2 Thin Films
(Elsevier Science Bv, 2007) Saygın-Hinczewski, Dursen; Koç, Kenan; Sorar, İdris; Hinczewski, Michael; Tepehan, Fatma Zehra; Tepehan, Galip Gültekin
In this study the sol-gel spin-coating method has been used to make Ta2O5-CeO2 thin films. These films have been prepared in various composition ratios to observe changes in their optical and structural properties. Reflectance and transmittance spectra were collected in the spectral range of 300-1000 nm and were accurately fit using the Tauc-Lorentz model. Film thicknesses refractive indices absorption coefficients and optical band gaps were extracted from the theoretical fit. The highest refractive index value was found at 5% CeO2 doping. The structure of the films was characterized by X-ray diffractometry and Fourier transform infrared spectrometry while the surface morphology was examined through atomic force microscopy. (C) 2007 Elsevier B.V. All rights reserved.
Citation - WoS: 12
Citation - Scopus: 14
Optimal Input Design for the Detection of Changes Towards Unknown Hypotheses
(Taylor & Francis Ltd, 2004) Kerestecioğlu, Feza; Cetin, I
The effects of auxiliary input signals on detecting changes in ARMAX processes via statistical tests are discussed. Two extensions to the Cumulative Sum Test are considered. The first is applicable when the direction of the change in the parameter space is known but its magnitude is unknown. The second is applicable when neither is known. The performance criteria for the design of stationary stochastic inputs are based on the asymptotic properties of the tests. It is shown that power-constrained optimal inputs have discrete spectra and a suitably chosen input can greatly improve the detection performance.
Citation - WoS: 7
Citation - Scopus: 7
Optimal Training for Residual Self-Interference for Full-Duplex One-Way Relays
(IEEE-INST Electrical Electronics Engineers Inc, 2018) Li, Xiaofeng; Tepedelenlioglu, Cihan; Şenol, Habib
Channel estimation and optimal training sequence design for full-duplex one-way relays are investigated. We propose a training scheme to estimate the residual self-interference (RSI) channel and the channels between nodes simultaneously. A maximum likelihood estimator is implemented with the Broyden-Fletcher-Goldfarb-Shanno algorithm. In the presence of RSI the overall source-to-destination channel becomes an inter-symbol-interference (ISI) channel. With the help of estimates of the RSI channel the destination is able to cancel the ISI through equalization. We derive and analyze the Cramer-Rao bound (CRB) in closed-form by using the asymptotic properties of Toeplitz matrices. The optimal training sequence is obtained by minimizing the CRB. Extensions for the fundamental one-way relay model to the frequency-selective fading channels and the multiple relays case are also considered. For the former we propose a training scheme to estimate the overall channel and for the latter the CRB and the optimal number of relays are derived when the distance between the source and the destination is fixed. Simulations using LTE parameters corroborate our theoretical results.
Optimizing Neuron Simulation Environment Using Remote Memory Access With Recursive Doubling on Distributed Memory Systems
(Hindawi Ltd, 2016) Shehzad, Danish; Bozkuş, Zeki
Increase in complexity of neuronal network models escalated the efforts to make NEURON simulation environment efficient. The computational neuroscientists divided the equations into subnets amongst multiple processors for achieving better hardware performance. On parallel machines for neuronal networks interprocessor spikes exchange consumes large section of overall simulation time. In NEURON for communication between processors Message Passing Interface (MPI) is used. MPI Allgather collective is exercised for spikes exchange after each interval across distributed memory systems. The increase in number of processors though results in achieving concurrency and better performance but it inversely affects MPI Allgather which increases communication time between processors. This necessitates improving communication methodology to decrease the spikes exchange time over distributed memory systems. This work has improved MPI Allgather method using Remote Memory Access (RMA) by moving two-sided communication to one-sided communication and use of recursive doubling mechanism facilitates achieving efficient communication between the processors in precise steps. This approach enhanced communication concurrency and has improved overall runtime making NEURON more efficient for simulation of large neuronal network models.

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