Bilgisayar Mühendisliği Bölümü Koleksiyonu

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

Browse

Now showing 1 - 20 of 35

Citation - WoS: 1
Citation - Scopus: 1
Accelerating Brain Simulations on Graphical Processing Units
(IEEE, 2015) Kayraklıoğlu, Engin; El-Ghazawi, Tarek A.; Bozkuş, Zeki
NEural Simulation Tool(NEST) is a large scale spiking neuronal network simulator of the brain. In this work we present a CUDA(R) implementation of NEST. We were able to gain a speedup of factor 20 for the computational parts of NEST execution using a different data structure than NEST's default. Our partial implementation shows the potential gains and limitations of such possible port. We discuss possible novel approaches to be able to adapt generic spiking neural network simulators such as NEST to run on commodity or high-end GPGPUs.
Citation - WoS: 4
Citation - Scopus: 5
Action Recognition Using Random Forest Prediction With Combined Pose-Based and Motion-Based Features
(IEEE, 2013) Ar, İlktan; Akgül, Yusuf Sinan
In this paper we propose a novel human action recognition system that uses random forest prediction with statistically combined pose-based and motion-based features. Given a set of training and test image sequences (videos) we first adopt recent techniques that extract low-level features: motion and pose features. Motion-based features which represent motion patterns in the consecutive images are formed by 3D Haar-like features. Pose-based features are obtained by the calculation of scale invariant contour-based features. Then using statistical methods we combine these low-level features to a novel compact representation which describes the global motion and the global pose information in the whole image sequence. Finally Random Forest classification is employed to recognize actions in the test sequences by using this novel representation. Our experimental results on KTH and Weizmann datasets have shown that the combination of pose-based and motion-based features increased the system recognition accuracy. The proposed system also achieved classification rates comparable to the state-of-the-art approaches.
Citation - WoS: 1
An Analysis for the Use of Compressed Sensing Method in Microwave Imaging
(IEEE, 2017) Yiğit, Enes; Tekbaş, Mustafa; Ünal, İlhami; Erdoğan, Sercan; Çalışkan, Cafer
One of the most important problems encountered in microwave imaging methods is intensive data processing traffic that occurs when high resolution and real time tracking is desired. Radar signals can be recovered without loss of data with a randomly selected subset of the measurement data by compression sensing (CS) method which has been popular in recent years. For this reason, in this study, the use and capabilities of the CS method were investigated for tracking moving human, and the target information was correctly determined for the data obtained much below the Nyquist sampling criterion. In this study, it was revealed that the CS method can be developed for target detection and tracking
Citation - WoS: 1
Citation - Scopus: 2
Analytical Expense Management System
(IEEE, 2009) Bozkuş, Zeki; Bisson, Christophe; Arsan, Taner
Although the development of communication technologies (e.g: UMTS ADSL) allowed the elaboration of multiple users' web applications (e.g. information storage) there are still many improvements on many applications to be done and uncovered areas. Expense management systems on web application area are still in their infancy. Expense management software is widely spread in companies and most of time supported by their intranet. These solutions are quite simple as they mainly collect the information related to the expenses and may propose a simple aggregation of these figures. The result is close to what an excel sheet provides.
Audience Tracking and Cheering Content Control in Sports Events
(IEEE, 2020) Yeşilyurt, Gözdenur; Dursun, Sefa; Kumas, Osman; Çakir, Nagehan; Arsan, Taner
Swearing cheers encountered in sports competitions do not comply with sports ethics and morals. Even if this kind of cheering is a group, the entire tribune block is penalized in accordance with the current rules. This method is not preventive and individual punishment should be used. The aim of this study is to determine the individuals who cheer with swearing content. In this study, the person detection is made with the multi-task cascaded convolutional neural network. Moreover, facial landmarks representing the facial regions and the regions related to them are determined as a result of this process. The mouth region is also determined by means of these important points removed, and finally the mouth is determined according to the equation. The face recognition is carried out because the person would be in a state of yelling if the mouth opening ratio exceeds the threshold value by determining the rate of opening. Landmarks extracted from the facial regions for the face recognition are transformed into feature vectors by FaceNet, and the model is created by classifying these vectors with classifiers to use in recognition process. When evaluated in terms of industry, face recognition and detection systems find a wide field of study.
Citation - WoS: 7
Big Data Platform Development With a Domain Specific Language for Telecom Industries
(IEEE, 2013) Şenbalcı, Cüneyt; Altuntaş, Serkan; Bozkuş, Zeki; Arsan, Taner
This paper introduces a system that offer a special big data analysis platform with Domain Specific Language for telecom industries. This platform has three main parts that suggests a new kind of domain specific system for processing and visualization of large data files for telecom organizations. These parts are Domain Specific Language (DSL) Parallel Processing/Analyzing Platform for Big Data and an Integrated Result Viewer. hi addition to these main parts Distributed File Descriptor (DFD) is designed for passing information between these modules and organizing communication. To find out benefits of this domain specific solution standard framework of big data concept is examined carefully. Big data concept has special infrastructure and tools to perform for data storing processing analyzing operations. This infrastructure can be grouped as four different parts these are infrastructure programming models high performance schema free databases and processing-analyzing. Although there are lots of advantages of Big Data concept it is still very difficult to manage these systems for many enterprises. Therefore this study suggest a new higher level language called as DSL which helps enterprises to process big data without writing any complex low level traditional parallel processing codes a new kind of result viewer and this paper also presents a Big Data solution system that is called Petaminer.
Citation - WoS: 1
Citation - Scopus: 4
Channel Estimation in Underwater Cooperative Ofdm System With Amplify-And Relaying
(IEEE, 2012) Şenol, Habib; Panayırcı, Erdal; Erdoğan, Mustafa; Uysal, Murat
This paper is concerned with a challenging problem of channel estimation for amplify-and-forward cooperative relay based orthogonal frequency division multiplexing (OFDM) systems in the presence of sparse underwater acoustic channels and of the correlative non-Gaussian noise. We exploit the sparse structure of the channel impulse response to improve the performance of the channel estimation algorithm due to the reduced number of taps to be estimated. The resulting novel algorithm initially estimates the overall sparse channel taps from the source to the destination as well as their locations using the matching pursuit (MP) approach. The correlated non-Gaussian effective noise is modeled as a Gaussian mixture. Based on the Gaussian mixture model an efficient and low complexity algorithm is developed based on the combinations of the MP and the space-alternating generalized expectation-maximization (SAGE) technique to improve the estimates of the channel taps and their location as well as the noise distribution parameters in an iterative way. The proposed SAGE algorithm is designed in such a way that by choosing the admissible hidden data properly on which the SAGE algorithm relies a subset of parameters is updated for analytical tractability and the remaining parameters for faster convergence Computer simulations show that underwater acoustic (UWA) channel is estimated very effectively and the proposed algorithm has excellent symbol error rate and channel estimation performance.
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 - Scopus: 1
Connected Navigation of Non-Communicating Mobile Agents
(IEEE, 2012) Kerestecioğlu, Feza; Cezayirli, Ahmet
This article discusses the connectivity of autonomous mobile robots that do not have communication capabilities. We show that if the group members follow the proposed Local Steering Strategy which utilizes information only about the relative positions of neighbor robots they can sustain their connectivity even in the case of bounded position measurement errors and the occultation of robots by other robots in the group. To reduce the computational burden in the implementation of the proposed methodology we used sub-optimal solutions. © 2012 IEEE.
Citation - WoS: 1
Citation - Scopus: 1
Dark Patches in Clustering
(IEEE, 2017) Ishaq, Waqar; Büyükkaya, Eliya
This survey highlights issues in clustering which hinder in achieving optimal solution or generates inconsistent outputs. We called such malignancies as dark patches. We focus on the issues relating to clustering rather than concepts and techniques of clustering. For better insight into the issues of clustering we categorize dark patches into three classes and then compare various clustering methods to analyze distributed datasets with respect to classes of dark patches rather than conventional way of comparison by performance and accuracy criteria because performance and accuracy may provide misleading conclusions due to lack of labeled data in unsupervised learning. To the best of our knowledge this prime feature makes our survey paper unique from other clustering survey papers.
Citation - WoS: 1
Citation - Scopus: 2
Data-Aided Autoregressive Sparse Channel Tracking for Ofdm Systems
(IEEE, 2016) Buyuksar, Ayse Betul; Şenol, Habib; Erküçük, Serhat; Cirpan, Hakan Ali
In order to meet future communication system requirements channel estimation over fast fading and frequency selective channels is crucial. In this paper Space Alternated Generalized Expectation Maximization Maximum a Posteriori (SAGE-MAP) based channel estimation algorithm is proposed for Orthogonal Frequency Division Multiplexing (OFDM) systems for Autoregressive (AR) modeled time-varying sparse channels. Also an initialization algorithm has been developed from the widely used sparse approximation algorithm Orthogonal Matching Pursuit (OMP) since the performance of SAGE algorithm strictly depends on initialization. The results show that multipath delay positions can be tracked successfully for every time instant using the proposed SAGE-MAP based approach.
Citation - WoS: 1
Citation - Scopus: 4
Distributed Estimation Over Parallel Fading Channels With Channel Estimation Error
(IEEE, 2008) Şenol, Habib; Tepedelenlioğlu, Cihan
We consider distributed estimation of a source observed by sensors in additive Gaussian noise where the sensors are connected to a fusion center with unknown orthogonal (parallel) flat Rayleigh fading channels. We adopt a two-phase approach of (i) channel estimation with training and (ii) source estimation given the channel estimates where the total power is fixed. We prove that allocating half the total power into training is optimal and show that compared to the perfect channel case a performance loss of at least 6 dB is incurred. In addition we show that unlike the perfect channel case increasing the number of sensors will lead to an eventual degradation in performance. We characterize the optimum number of sensors as a function of the total power and noise statistics. Simulations corroborate our analytical findings.
Citation - WoS: 1
Citation - Scopus: 3
Distributed Estimation With Channel Estimation Error Over Orthogonal Fading Channels
(IEEE, 2007) Şenol, Habib; Tepedelenlioğlu, Cihan
We study distributed estimation of a source corrupted by an additive Gaussian noise and observed by sensors which are connected to a fusion center with unknown orthogonal (parallel) flat Rayleigh fading channels. The fading communication channels are estimated with training. Subsequently source estimation given the channel estimates and transmitted sensor observations is performed. We consider a setting where the estimated channels are fed-back to the sensors for optimal power allocation which leads to a threshold behavior of sensors with bad channels being unused (inactive). We also show that at least half of the total power should be used for training. Simulation results corroborate our analytical findings.
Effect of Inter-Block Region on Compressed Sensing Based Channel Estimation in Tds-Ofdm Systems
(IEEE, 2016) Başaran, Mehmet; Erküçük, Serhat; Şenol, Habib; Cirpan, Hakan Ali
Time domain synchronous orthogonal frequency division multiplexing (TDS-OFDM) is the basis technology for digital television standard (DTV) employed in some countries thanks to its high spectral efficiency when compared to traditional cyclic prefix OFDM. Moreover it does not require pilot usage in frequency domain channel estimation. Instead of data usage as cyclic prefix pseudo-noise (PN) sequences are transmitted in guard intervals. Due to interference from the previous OFDM data symbol the received signal in guard interval can be decomposed into a small-sized signal that contains only PN sequences utilizing the inter-block-interference (IBI)-free region in the convolution matrix. Due to sparsity multipath fading channel can be obtained by the application of compressed sensing (CS) technique to reconstruct the high-dimensional sparse channel from the decreased-size of received signal through the known PN sequence matrix. In this study the effect of the size of IBI-free region on CS and Bayesian CS (BCS) based channel estimation is investigated. Accordingly reconstruction error performances of basis pursuit (BP) and BCS are compared. Simulation results show that the channel estimation can be improved by trading-off the length of the IBI-free region. However an increase in IBI-free region leads to decreased energy efficiency at both the transmitter and receiver side.
Effect of the Channel Estimation Error on the Performance of the Source Estimator in a Wireless Sensor Network With Orthogonal Channels
(IEEE, 2008) Şenol, Habib; Tepedelenlioğlu, Cihan
In this work effect of the channel estimation error on the MSE performance of the source estimator in a wireless sensor network with orthogonal flat fading channels is studied. A two-phase approach was employed where in the first phase the orthogonal fading channel coefficients are estimated and in the second phase channel estimates and sensor observations transmitted to fusion center are used for the source estimation. We consider a sensor network in which the channel estimates are fed-back to the sensors for optimal power allocation which leads to switch off the sensors with bad channels in the second phase. We also show that training power should be at least half of the total power. Our analytical findings are corroborated by simulation results.
Citation - WoS: 64
Citation - Scopus: 88
Energy Aware Multi-Hop Routing Protocol for Wsns
(IEEE, 2018) Cengiz, Korhan; Dağ, Tamer
In this paper we propose an energy-efficient multi-hop routing protocol for wireless sensor networks (WSNs). The nature of sensor nodes with limited batteries and inefficient protocols are the key limiting factors of the sensor network lifetime. We aim to provide for a green routing protocol that can be implemented in a wireless sensor network. Our proposed protocol's most significant achievement is the reduction of the excessive overhead typically seen in most of the routing protocols by employing fixed clustering and reducing the number of cluster head changes. The performance analysis indicates that overhead reduction significantly improves the lifetime as energy consumption in the sensor nodes can be reduced through an energy-efficient protocol. In addition the implementation of the relay nodes allows the transmission of collected cluster data through inter cluster transmissions. As a result the scalability of a wireless sensor network can be increased. The usage of relay nodes also has a positive impact on the energy dissipation in the network.
Citation - WoS: 1
Joint Channel Estimation and Equalization for Ofdm Based Broadband Communications in Rapidly Varying Mobile Channels
(IEEE, 2010) Şenol, Habib; Poor, H. Vincent
This paper is concerned with the challenging and timely problem of channel estimation for orthogonal frequency division multiplexing (OFDM) systems in the presence of frequency selective and very rapidly time varying channels. In OFDM systems operating over rapidly time-varying channels the orthogonality between subcarriers is destroyed leading to inter-carrier interference (ICI) and resulting in an irreducible error floor. The band-limited discrete cosine serial expansion of low-dimensionality is employed to represent the time-varying channel. In this way the resulting reduced dimensional channel coefficients are estimated iteratively with tractable complexity and independently of the channel statistics. The algorithm is based on the expectation maximization-maximum a posteriori probability (EM-MAP) technique leading to a receiver structure that also yields the equalized output using the channel estimates. The pilot symbols are employed to estimate the initial coefficients effectively and unknown data symbols are averaged out in the algorithm in a non-data-aided fashion. It is shown that the computational complexity of the proposed algorithm to estimate the channel coefficients and to generate the equalized output as a by-product is similar to O(N) per detected symbol N being the number of OFDM subcarriers. Computational complexity as well as computer simulations carried out for the systems described in WiMAX and LTE standards indicate that it has significant performance and complexity advantages over existing suboptimal channel estimation and equalization algorithms proposed earlier in the literature.
Citation - Scopus: 2
Joint Data Detection and Channel Estimation for Ofdm Systems in the Presence of Very High Mobility
(IEEE, 2009) Panayırcı, Erdal; Şenol, Habib; Poor, H. Vincent
This paper is concerned with the challenging and timely problem of joint channel estimation and data detection for orthogonal frequency division multiplexing (OFDM) systems in the presence of frequency selective and very rapidly time varying channels. The detection and estimation algorithm is based on the space alternating generalized expectation maximization (SAGE) technique which is particularly well-suited to multicarrier signal formats. In order to reduce the computational complexity of the algorithm we apply the cosine orthogonal basis functions to describe the time-varying channel. 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. The proposed SAGE joint detection algorithm updates the data sequences in serial and the channel parameters are updated in parallel leading to a receiver structure that also incorporates a partial interference cancelation of the interchannel interference. 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 reduction of the computational complexity substantially.
Citation - WoS: 13
Citation - Scopus: 17
Low Energy Fixed Clustering Algorithm (lefca) for Wireless Sensor Networks
(IEEE, 2015) Cengiz, Korhan; Dağ, Tamer
Wireless sensor networks (WSNs) have become an important part of our lives as they can be used in vast application areas from disaster relief to health care. As a consequence the life span and the energy consumption of a WSN has become a challenging research area. According to the existing studies instead of using direct transmission or multi-hop routing clustering can significantly reduce the energy consumption of sensor nodes and can prolong the lifetime of a WSN. In this paper we propose a low energy fixed clustering algorithm (LEFCA) for WSNs. With LEFCA the clusters are constructed during the set-up phase. A sensor node which becomes a member of a cluster stays in the same cluster throughout the life span of the network. LEFCA not only improves the lifetime of the network but also decreases the energy dissipation and increases the throughput significantly.
Multi-State Video Transmission With Network Coding
(IEEE, 2018) Şengel, Öznur; Ekmekçi Flierl, Sıla
The goal of this work is to send video packets to all nodes in the network by enveloping Multi-State Video Coding (MSVC) at the same time network coding to maximize the throughput and video quality. This work has two main parts: 1) Multi-State Video Coding and 2) Network Coding. The main purpose of this work is to maximize not only the video quality but also the network throughput. We used Multi-State Video Coding to achieve robustness and we used network coding to increase throughput over the network. After generating the two subsequences using MSVC, we apply network coding to support transmission of packets. In this manner, we aim to increase the throughput as well as robustness and quality of the video transmission.

Browse

Browsing Bilgisayar Mühendisliği Bölümü Koleksiyonu by browse.metadata.publisher "IEEE"