Mühendislik ve Doğa Bilimleri Fakültesi
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Browsing Mühendislik ve Doğa Bilimleri Fakültesi by Type "Conference Object"
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Conference Object Citation Count: 0Abstraction in FPGA implementation of neural networks(World Scientific and Engineering Academy and Society, 2008) Öğrenci, Arif SelçukA model for FPGA implementation of multilayer perceptron neural networks is presented. The model tries to incorporate object oriented design principles in the analysis training and design of components using hardware description languages. The synthesis will be based on the tools supplied by the FPGA vendors. The results indicate that the method can be utilized and it can be further improved to create a general methodology that bridges the gap between hardware and software in embedded system design.Conference Object Citation Count: 1Accelerating Brain Simulations on Graphical Processing Units(IEEE, 2015) Kayraklıoğlu, Engin; El-Ghazawi, Tarek A.; Bozkuş, ZekiNEural 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.Conference Object Citation Count: 6Achievable Performance of Bayesian Compressive Sensing Based Spectrum Sensing(IEEE, 2014) Başaran, Mehmet; Erküçük, Serhat; Çırpan, Hakan AliIn wideband spectrum sensing compressive sensing approaches have been used at the receiver side to decrease the sampling rate if the wideband signal can be represented as sparse in a given domain. While most studies consider the reconstruction of primary user's signal accurately it is indeed more important to analyze the presence or absence of the signal correctly. Furthermore these studies do not consider the achievable lower bounds of reconstruction error and how well the selected method performs correspondingly. Motivated by these issues we investigate in detail the primary user detection performance of Bayesian compressive sensing (BCS) approach in this paper. Accordingly we (i) determine the BCS signal reconstruction performance in terms of mean-square error (MSE) compression ratio and signal-to-noise ratio (SNR) and compare it with the conventionally used basis pursuit approach (ii) determine how well BCS performs compared with the Bayesian Cramer-Rao lower bound (BCRLB) of the signal reconstruction error and (iii) assess the probability of detection performance of BCS for various SNR and compression ratio values. The results of this study are important for determining the achievable performance of BCS based spectrum sensing.Conference Object Citation Count: 4Action Recognition Using Random Forest Prediction with Combined Pose-based and Motion-based Features(IEEE, 2013) Ar, İlktan; Akgül, Yusuf SinanIn 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.Conference Object Citation Count: 2Active reconfigurable control of a submarine with indirect adaptive control(2003) Kerestecioğlu, Feza; Kerestecioğlu, FezaAn indirect adaptive controller is designed for submersibles. The design is developed using a linearized MIMO model of a submarine. Standard recursive least squares estimation method is used to estimate the parameters. Depth and pitch angle of the submarine is controlled by means of the well-known indirect self-tuning method. In case of a system fault estimated parameters of the submarine model have been used to update the controller coefficients.Conference Object Citation Count: 0Advanced signal processing algorithms for wireless communications(Springer-Verlag Berlin, 2006) Panayırcı, Erdal; Çırpan, Hakan AliTraditional wireless technologies are not well suited to meet the extremely demanding requirements of providing the very high data rates with the ubiquity mobility and portability characteristic of cellular systems. Some fundamental barriers related to the nature of the radio channel as well as the limited bandwidth availability at the frequencies of interest stand in the way. Unique sets of efficient advanced signal processing algorithms and techniques is the one of the primary enablers that will allow lifting these limits primarily due to the impressive advent of low cost and low power digital signal processors. As an application of advanced signal processing techniques we will consider the solution of blind phase noise estimation and data detection problem via a computationally efficient sequential Monte Carlo (SMC) methodology in this paper.Conference Object Citation Count: 0AHP-BASED APPROACH TO EVALUATE SOLAR POWER PLANT LOCATION ALTERNATIVES(Intl Inst Social & Economic Sci, 2016) Ayağ, ZekiSolar energy is the most readily available source of energy, and one of the most important sources of the renewable energy, because it is non-polluting and helps in lessening the greenhouse effect. Main problem of establishing a solar power plant is to determine its location. In the presence of many location alternatives and evaluation criteria, a multiple-criteria decision making problem arises. In this work, the location problem will be solved by using analytic hierarchy process (AHP) to figure out the most satisfying alternative. A numerical example is also included to show the proposed methodology in Turkey. . . . .Conference Object Citation Count: 0Alternative Transducer Power Gain Expression in Broadband Matching Network Designs(IEEE, 2016) Şengül, Metin Y.In this paper a reflection coefficient based transducer power gain expression has been derived which is an alternative to the impedance based expression exists in the literature. A broadband double matching problem is solved by using the derived gain expression and the obtained performance has been compared with the performance obtained via the existing expression.Conference Object Citation Count: 1An Analysis for the Use of Compressed Sensing Method in Microwave Imaging(IEEE, 2017) Yiğit, Enes; Tekbaş, Mustafa; Ünal, İlhami; Erdoğan, Sercan; Çalışkan, CaferOne 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 trackingConference Object Citation Count: 1An analysis for the use of compressed sensing method in microwave imaging [Mikrodalga Görüntülemede Sıkıştırılmış Algılama Yönteminin Kullanımına Yönelik Bir Analiz](Institute of Electrical and Electronics Engineers Inc., 2017) Yiğit, Enes; Tekbaş, Mustafa; Ünal, İlhami; Erdogan, Sercan; Çalışkan, CaferOne 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. © 2017 IEEE.Conference Object Citation Count: 4Analysis of Extended Busy Tone Performance for Coexistence between WRAN and WLAN TVWS Networks(IEEE, 2015) Baykaş, Tunçer; Erküçük, Serhat; Baykaş, TunçerTV White Spaces indicate spectrum bands which were reserved for licensed terrestrial TV broadcasting and opened to unlicensed use under regulatory conditions. One important regulation which is common in all regulatory domains is no harmful interference is created to licensed devices. On the other hand interference between unlicensed devices is not regulated. As a result system designers developed new methods to improve coexistence between TVWS networks. Extended busy tone one of such methods is designed for coexistence between wireless regional area and wireless local area networks based on IEEE 802.22 and 802.11af standards respectively. In this paper we analyse the performance of extended busy tone at different range conditions and verify via simulations under realistic conditions. Our results indicate that the method can reduce interference considerably at intermediate distances and enable networks to operate without a significant reduction in throughput.Conference Object Citation Count: 3Analytic Network Process (ANP) for solar power plant location problem(Institute of Industrial Engineers, 2010) Samanlıoğlu, Funda; Samanlıoğlu, FundaSolar energy is the most readily available source of energy and one of the most important sources of the renewable energy because it is non-polluting and helps in lessening the greenhouse effect. Main problem of establishing a solar power plant is to determine its location. In the presence of many location alternatives and evaluation criteria a multiple-criteria decision making problem arises. In this work the location problem will be solved by using Analytic Network Process (ANP) to figure out the most satisfying alternative. A numerical example is also included to show the proposed methodology in Turkey.Conference Object Citation Count: 1Analytical Expense Management System(IEEE, 2009) Arsan, Taner; Bisson, Christophe; Arsan, TanerAlthough 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.Conference Object Citation Count: 1Anomaly Detection in Walking Trajectory(IEEE, 2018) Öğrenci, Arif SelçukAnalysis of the walking trajectory and the detection of anomalies in this trajectory, provide important benefits in the fields of health and security. In this work, two methods to detect anomalies in trajectories, are compared. Firstly, an unsupervised method is used where the conformance among trajectories are taken into consideration. Trajectories that deviate from others are qualified as anomalies. Secondly, the points in the trajectories are considered as a time series. Artifical neural networks performing supervised learning based on the backpropagation algorithm are used. The results are compared, and the points to be enhanced are highlighted.Conference Object Citation Count: 2Anomaly detection in walking trajectory [Yürüyüş yörüngesinde anormallik algılama](Institute of Electrical and Electronics Engineers Inc., 2018) Öğrenci, Arif SelçukAnalysis of the walking trajectory and the detection of anomalies in this trajectory provide important benefits in the fields of health and security. In this work two methods to detect anomalies in trajectories are compared. Firstly an unsupervised method is used where the conformance among trajectories are taken into consideration. Trajectories that deviate from others are qualified as anomalies. Secondly the points in the trajectories are considered as a time series. Artifical neural networks performing supervised learning based on the backpropagation algorithm are used. The results are compared and the points to be enhanced are highlighted.Conference Object Citation Count: 1Ask me: A Question Answering System via Dynamic Memory Networks(Institute of Electrical and Electronics Engineers Inc., 2019) Yiğit, Gülsüm; Amasyalı, Mehmet FatihMost of the natural language processing problems can be reduced into a question answering problem. Dynamic Memory Networks (DMNs) are one of the solution approaches for question answering problems. Based on the analysis of a question answering system built by DMNs described in [1], this study proposes a model named DMN∗ which contains several improvements on its input and attention modules. DMN∗ architecture is distinguished by a multi-layer bidirectional LSTM (Long Short Term Memory) architecture on input module and several changes in computation of attention score in attention module. Experiments are conducted on Facebook bAbi dataset [2]. We also introduce Turkish bAbi dataset, and produce increased vocabulary sized tasks for each dataset. The experiments are performed on English and Turkish datasets and the accuracy performance results are compared by the work described in [1]. Our evaluation shows that the proposed model DMN∗ obtains improved accuracy performance results on various tasks for both Turkish and English.Conference Object Citation Count: 0The Association of Gvhd With Hla Dr Alleles, Ifn-Gamma, Tgf-Beta, And Mbl2 Gene Polymorphism(Wiley, 2019) Oğuz, Rusdu; Çiftçi, Hayriye Şentürk; Gökçe, Muge; Öğret, Yeliz; Karadeniz, Sedat Tanju; Pehlivan, Sacide; Aydın, Filiz[Abstract Not Available]Conference Object Citation Count: 0Atomic collisions and free lepton pair production(2005) Güçlü, Mehmet Cem; Yılmaz, MelekIn this work we have calculated the total cross sections of electron-positron pair production for the collisions of fully stripped gold ions for various energies. We have also compared our calculation with other methods.Conference Object Citation Count: 0Audience Tracking and Cheering Content Control in Sports Events(IEEE, 2020) Arsan, Taner; Dursun, Sefa; Kumas, Osman; Çakir, Nagehan; Arsan, TanerSwearing 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.Conference Object Citation Count: 6Bayesian compressive sensing for ultra-wideband channel models(IEEE, 2012) Ozgor, Mehmet; Erküçük, Serhat; Cirpan, Hakan AliConsidering the sparse structure of ultra-wideband (UWB) channels compressive sensing (CS) is suitable for UWB channel estimation. Among various implementations of CS the inclusion of Bayesian framework has shown potential to improve signal recovery as statistical information related to signal parameters is considered. In this paper we study the channel estimation performance of Bayesian CS (BCS) for various UWB channel models and noise conditions. Specifically we investigate the effects of (i) sparse structure of standardized IEEE 802.15.4a channel models (ii) signal-to-noise ratio (SNR) regions and (iii) number of measurements on the BCS channel estimation performance and compare them to the results of l(1)-norm minimization based estimation which is widely used for sparse channel estimation. The study shows that BCS exhibits superior performance at higher SNR regions only for adequate number of measurements and sparser channel models (e. g. CM1 and CM2). Based on the results of this study BCS method or the l(1)-norm minimization method can be preferred over the other for different system implementation conditions.