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Articles 1651 - 1680 of 8897

Full-Text Articles in Physical Sciences and Mathematics

A Preliminary Survey On Software Testing Practices In Khyber Pakhtunkhwa Region Of Pakistan, Bushra Latif, Tauseef Rana Jan 2020

A Preliminary Survey On Software Testing Practices In Khyber Pakhtunkhwa Region Of Pakistan, Bushra Latif, Tauseef Rana

Turkish Journal of Electrical Engineering and Computer Sciences

Conducted to ensure the quality of software products, the software testing process has a great significance in the software development and is the vital step of the verification and validation process. For conforming a software feature to the end user requirements, organizations rely on extensive testing procedures. Despite being the key factor, many of the software development industries/companies do not define/follow a systematic testing process. In this paper, we analyze/learn from the conducted surveys in the past and formulate a questionnaire for a survey in the northern region of Pakistan. To the best of our knowledge, no such survey has …

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Adaptive Blind Equalization For A Mimo Chaotic Communication System, Gökçen Çeti̇nel, Cabi̇r Vural Jan 2020

Adaptive Blind Equalization For A Mimo Chaotic Communication System, Gökçen Çeti̇nel, Cabi̇r Vural

Turkish Journal of Electrical Engineering and Computer Sciences

There exist few blind solutions for chaotic MIMO channel equalization. In this work, a chaotic MIMO channel equalization framework is proposed. The objective function to be minimized in the proposed solution is obtained by adopting the objective function developed for chaotic SISO channel equalization. Furthermore, an optimum filter that minimizes the proposed cost function is designed to recover chaotic input signals assuming that the channel is known. The stationary point of the adaptive solution is equal to the optimal filter if the adaptive filter coefficients change sufficiently slowly. The adaptive solution is contrasted with the optimum filter in terms of …

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Towards Human Activity Recognition For Ubiquitous Health Care Using Data From Awaist-Mounted Smartphone, Umar Zia, Wajeeha Khalil, Salabat Khan, Iftikhar Ahmad, Naeem Khatak Jan 2020

Towards Human Activity Recognition For Ubiquitous Health Care Using Data From Awaist-Mounted Smartphone, Umar Zia, Wajeeha Khalil, Salabat Khan, Iftikhar Ahmad, Naeem Khatak

Turkish Journal of Electrical Engineering and Computer Sciences

Understanding human activities is a newly emerging paradigm that is greatly involved in developing ubiquitous health care (u-Health) systems. The aim of these systems is to seamlessly gather knowledge about the patient?s health and, after collecting knowledge, make suggestions to the patient according to his/her health profile. For this purpose, one of the most important ubiquitous communication trends is the smartphone, which has drawn the attention of both professionals and caregivers for monitoring the aging population, childcare, fall detection, and cognitive impairment. Recognizing human actions in a ubiquitous environment is very challenging and researchers have extensively investigated different methods to …

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A Multibeam Subarrayed Time-Modulated Linear Array, Uğur Yeşi̇lyurt, İhsan Kanbaz, Ertuğrul Aksoy Jan 2020

A Multibeam Subarrayed Time-Modulated Linear Array, Uğur Yeşi̇lyurt, İhsan Kanbaz, Ertuğrul Aksoy

Turkish Journal of Electrical Engineering and Computer Sciences

In conventional time-modulated arrays (TMAs), because of the usage of the RF-switch, harmonics are generated at multiples of the modulation frequency. In this study, the synthesis of time-modulated arrays has been analyzed for cognitive radio (CR) systems, in which these harmonics are suitably exploited for more efficient utilization of the spectrum. In order to accomplish the desired pattern at requested harmonic frequencies, a new excitation strategy with sinusoidal signals is proposed. The use of sinusoidal waveforms creates independent beams, allowing independent steering capability. Moreover, by utilizing the subarray structure, it is possible to have a smaller number of excitation functions …

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Robust Optimal Operation Of Smart Distribution Grids With Renewable Basedgenerators, Omid Zare, Sadjad Galvani, Murtaza Farsadi Jan 2020

Robust Optimal Operation Of Smart Distribution Grids With Renewable Basedgenerators, Omid Zare, Sadjad Galvani, Murtaza Farsadi

Turkish Journal of Electrical Engineering and Computer Sciences

Modern distribution systems are equipped with various distributed energy resources (DERs) because of the importance of local generation. These distribution systems encounter more and more uncertainties because of the ever-increasing use of renewable energies. Other sources of uncertainty, such as load variation and system components? failure, will intensify the unpredictable nature of modern distribution systems. Integrating energy storage systems into distribution grids can play a role as a flexible bidirectional source to accommodate issues from constantly varying loads and renewable resources. The overall functionality of these modern distribution systems is enhanced using communication and computational abilities in smart grid frameworks. …

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Dynamic Software Rejuvenation In Web Services: A Whale Optimizationalgorithm-Based Approach, Kimia Rezaei Kalantari, Ali Ebrahimnejad, Homayun Motameni Jan 2020

Dynamic Software Rejuvenation In Web Services: A Whale Optimizationalgorithm-Based Approach, Kimia Rezaei Kalantari, Ali Ebrahimnejad, Homayun Motameni

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we suggest a method for determining the restarting time for web services to increase availability, known as rejuvenation. We consider different parameters such as number of users, maximum service request number, response time, and throughput of a web service to determine its restarting time. Software rejuvenation is an effective technique to counteract software aging in continuously running applications such as web service-based systems. In these systems, web services are allocated based on the needs of the receivers and facilities of servers. One of the challenges while assigning web services is selecting the appropriate server to reduce faults. …

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An Automated Eye Disease Recognition System From Visual Content Of Facial Imagesusing Machine Learning Techniques, Ashrafi Akram, Rameswar Debnath Jan 2020

An Automated Eye Disease Recognition System From Visual Content Of Facial Imagesusing Machine Learning Techniques, Ashrafi Akram, Rameswar Debnath

Turkish Journal of Electrical Engineering and Computer Sciences

Many eye diseases like cataracts, trachoma, or corneal ulcer can cause vision problems. Progression of these eye diseases can only be prevented if they are recognized accurately at the early stage. Visually observable symptoms differ a lot among these eye diseases. However, a wide variety of symptoms is necessary to be analyzed for the accurate detection of eye diseases. In this paper, we propose a novel approach to provide an automated eye disease recognition system using visually observable symptoms applying digital image processing techniques and machine learning techniques such as deep convolution neural network (DCNN) and support vector machine (SVM). …

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Correlation Coefficients Of Pythagorean Hesitant Fuzzy Sets And Their Applicationto Radar Lpi Performance Evaluation, Cheng Xiu Yang, Qianzhe Wang, Weidong Peng, Shaoting Pei Jan 2020

Correlation Coefficients Of Pythagorean Hesitant Fuzzy Sets And Their Applicationto Radar Lpi Performance Evaluation, Cheng Xiu Yang, Qianzhe Wang, Weidong Peng, Shaoting Pei

Turkish Journal of Electrical Engineering and Computer Sciences

Evaluating low probability of intercept (LPI) performance is the first step to design parameters and arrange radar resources. In the evaluation process it is hard to rely on the intercept receiver?s working scenarios and operating parameters. On the other hand, indicators that affect the LPI performance of radiating side are difficult to consider comprehensively. Thus, building an effective evaluation system is crucial. This research considers the natural parameters of radar extracted from a radiating scenario. Subsequently, a number of criteria are selected, including spatial, time, frequency domain, polarization status, energy status, and waveform features. A multidomain radar LPI performance evaluation …

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Piezoresistive Disposable Weight Sensor With Increased Sensitivity, Kuter Erdi̇l, Tuğçe Ayraç, Ömer Gökalp Akcan, Yi̇ği̇t Dağhan Gökdel Jan 2020

Piezoresistive Disposable Weight Sensor With Increased Sensitivity, Kuter Erdi̇l, Tuğçe Ayraç, Ömer Gökalp Akcan, Yi̇ği̇t Dağhan Gökdel

Turkish Journal of Electrical Engineering and Computer Sciences

This study presents the design, simulation, implementation, and experimental characterization of a paperbased perforated disposable weight sensor system with a double piezoresistive layer. The demonstrated system is designed to achieve highly sensitive weight sensing operations with low-cost materials. For that purpose, the main fabrication material of the proposed disposable sensor is selected as a 289 $\mu$m thick Strathmore 400 series Bristol paper. Approximately 48 $\mu$m thick piezoresistive graphite paste is coated onto both sides of the paper-based cantilever beam with the aim of acquiring more sensitive weight-sensing capability. Additionally, the proposed paper-based structure has rows of closely spaced perforations at …

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Prediction Of Railway Switch Point Failures By Artificial Intelligence Methods, Burak Arslan, Hasan Ti̇ryaki̇ Jan 2020

Prediction Of Railway Switch Point Failures By Artificial Intelligence Methods, Burak Arslan, Hasan Ti̇ryaki̇

Turkish Journal of Electrical Engineering and Computer Sciences

In recent years, railway transport has been preferred intensively in local and intercity freight and passenger transport. For this reason, it is of utmost importance that railway lines are operated in an uninterrupted and safe manner. In order to carry out continuous operation, all systems must continue to operate with maximum availability. In this study, data were collected from switch motors, which are the important equipment of railways, and the related equipment and these data were evaluated with sector experience and the results related to the failure status of the switch points were revealed. The obtained results were processed with …

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Satire Identification In Turkish News Articles Based On Ensemble Of Classifiers, Aytuğ Onan, Mansur Alp Toçoğlu Jan 2020

Satire Identification In Turkish News Articles Based On Ensemble Of Classifiers, Aytuğ Onan, Mansur Alp Toçoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Social media and microblogging platforms generally contain elements of figurative and nonliteral language, including satire. The identification of figurative language is a fundamental task for sentiment analysis. It will not be possible to obtain sentiment analysis methods with high classification accuracy if elements of figurative language have not been properly identified. Satirical text is a kind of figurative language, in which irony and humor have been utilized to ridicule or criticize an event or entity. Satirical news is a pervasive issue on social media platforms, which can be deceptive and harmful. This paper presents an ensemble scheme for satirical news …

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Convolutional Auto Encoders For Sentence Representation Generation, Ali̇ Mert Ceylan, Vecdi̇ Aytaç Jan 2020

Convolutional Auto Encoders For Sentence Representation Generation, Ali̇ Mert Ceylan, Vecdi̇ Aytaç

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, we have proposed an alternative approach for sentence modeling problem. The difficulty of the choice of answer, the semantically related questions and the lack of syntactic closeness of the answers give rise to the difficulty of selecting the answer. The deep learning field has recently achieved a pivotal success in semantic analysis, machine translation, and text summaries. The essence of this work, inspired by the human orthographic processing mechanism and using multiple convolution filters with pre-rendered 2-Dimension (2D) representations of sentences, input or output size is to learn the basic features of the language without concerns. For …

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Crash Course Learning: An Automated Approach To Simulation-Driven Lidar-Basedtraining Of Neural Networks For Obstacle Avoidance In Mobile Robotics, Stanko Kruzic, Josip Music, Mirjana Bonkovic, Frantisek Duchon Jan 2020

Crash Course Learning: An Automated Approach To Simulation-Driven Lidar-Basedtraining Of Neural Networks For Obstacle Avoidance In Mobile Robotics, Stanko Kruzic, Josip Music, Mirjana Bonkovic, Frantisek Duchon

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes and implements a self-supervised simulation-driven approach to data collection used for training of perception-based shallow neural networks for mobile robot obstacle avoidance. In the approach, a 2D LiDAR sensor was used as an information source for training neural networks. The paper analyzes neural network performance in terms of numbers of layers and neurons, as well as the amount of data needed for reliable robot operation. Once the best architecture is identified, it is trained using only data obtained in simulation and then implemented and tested on a real robot (Turtlebot 2) in several simulations and real-world scenarios. …

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Measurement Based Threat Aware Drone Base Station Deployment, Alper Akarsu, Tolga Gi̇ri̇ci̇ Jan 2020

Measurement Based Threat Aware Drone Base Station Deployment, Alper Akarsu, Tolga Gi̇ri̇ci̇

Turkish Journal of Electrical Engineering and Computer Sciences

Unmanned aerial vehicles are gaining importance with many civilian and military applications. Especially the surveillance, search/rescue, and military operations may have to be carried out in extremely constrained environments. In such scenarios, drone base stations (DBSs) have to provide communication services to the people at the ground. The ground users may have no access to the global positioning system (GPS); therefore, their locations have to be estimated using alternative techniques. Besides there may be threats in the environment, such as shooters. In this work, we address the problem of optimal DBS deployment under the aforementioned constraints. We propose a novel …

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Comparisons Of Extreme Learning Machine And Backpropagation-Based I-Vector Approach For Speaker Identification, Musab T S Al-Kaltakchi, Raid Rafi Omar Al-Nima, Mohammed A M Abdullah Jan 2020

Comparisons Of Extreme Learning Machine And Backpropagation-Based I-Vector Approach For Speaker Identification, Musab T S Al-Kaltakchi, Raid Rafi Omar Al-Nima, Mohammed A M Abdullah

Turkish Journal of Electrical Engineering and Computer Sciences

The extreme learning machine (ELM) is one of the machine learning applications used for regression and classification systems. In this paper, an extended comparison between an ELM and the backpropagation neural network (BPNN)-based i-vector is given in terms of a closed-set speaker identification task using 120 speakers from the TIMIT database. The system is composed of the mel frequency cepstal coefficient (MFCC) and power normalized cepstal coefficient (PNCC) approaches to form the feature extraction stage, while the cepstral mean variance normalization (CMVN) and feature warping are applied in order to mitigate the linear channel effect. The system is utilized with …

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Analysis Of Acoustic Sensor Placement For Pd Location In Power Transformer, Khairul Nadiah Khalid, Muhammad Nur Khairul Hafizi Rohani, Baharuddin Ismail, Muzamir Isa, Chang Yii Chai, Wan Nurul Auni Wan Muhammad Jan 2020

Analysis Of Acoustic Sensor Placement For Pd Location In Power Transformer, Khairul Nadiah Khalid, Muhammad Nur Khairul Hafizi Rohani, Baharuddin Ismail, Muzamir Isa, Chang Yii Chai, Wan Nurul Auni Wan Muhammad

Turkish Journal of Electrical Engineering and Computer Sciences

Partial discharge (PD) is an abnormal activity that occurs in high-voltage components, such as power cables, switchgear, machines, and power transformers. Such activity needs to be diagnosed for the equipment to last longer as PD could harm the insulation and potentially lead to asset destruction from time to time. Moving one or more externally mounted acoustic sensors to different locations on the transformer tank is commonly used in order to detect and locate PD signal occurring in the power transformer. However, this procedure may lead to less accuracy in PD identification. Therefore, this research paper presents an analysis of acoustic …

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Comparative Analysis Of Classification Techniques For Network Fault Management, Mohammed Madi, Fidaa Jarghon, Yousef Fazea, Omar Almomani, Adeeb Saaidah Jan 2020

Comparative Analysis Of Classification Techniques For Network Fault Management, Mohammed Madi, Fidaa Jarghon, Yousef Fazea, Omar Almomani, Adeeb Saaidah

Turkish Journal of Electrical Engineering and Computer Sciences

Network troubleshooting is a significant process. Many studies were conducted about it. The first step in the troubleshooting procedures is represented in collecting information. It's collected in order to identify the problems. Syslog messages which are sent by almost all network devices include a massive amount of data that concern the network problems. Based on several studies, it was found that analyzing syslog data (which) can be a guideline for network problems and their causes. The detection of network problems can become more efficient if the detected problems have been classified based on the network layers. Classifying syslog data requires …

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Combining Metadata And Co-Citations For Recommending Related Papers, Shahbaz Ahmad, Muhammad Tanvir Afzal Jan 2020

Combining Metadata And Co-Citations For Recommending Related Papers, Shahbaz Ahmad, Muhammad Tanvir Afzal

Turkish Journal of Electrical Engineering and Computer Sciences

Identification of relevant documents is performed to keep track of the state-of-the-art methods and relies on research paper recommender systems. The proposed approaches for these systems can be classified into categories like content-based, collaborative filtering-based, and bibliographic information-based approaches. The content-based approaches exploit the full text of articles and provide more promising results than other approaches. However, most content is not freely available because of subscription requirements. Therefore, the scope of content-based approaches is limited. In such scenarios, the best possible alternative could be the exploitation of other openly available resources. Therefore, this research explores the possible use of metadata …

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Investigating The Efficiency Of Multithreading Application Programming Interfacesfor Parallel Packet Classification In Wireless Sensor Networks, Mahdi Abbasi, Milad Rafiee, Mohammad R. Khosravi Jan 2020

Investigating The Efficiency Of Multithreading Application Programming Interfacesfor Parallel Packet Classification In Wireless Sensor Networks, Mahdi Abbasi, Milad Rafiee, Mohammad R. Khosravi

Turkish Journal of Electrical Engineering and Computer Sciences

This paper investigates the most appropriate application programming interface (API) that best accelerates the flow-based applications on the wireless sensor networks (WSNs). Each WSN include many sensor nodes which have limited resources. These sensor nodes are connected together using base stations. The base stations are commonly network systems with conventional processors which are responsible for handling a large amount of communicated data in flows of network packets. For this purpose, classification of the communicated packets is considered the primary process in such systems. With the advent of high-performance multicore processors, developers in the network industry have considered these processors as …

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Deep Reinforcement Learning For Acceptance Strategy In Bilateral Negotiations, Yousef Razeghi, Celal Ozan Berk Yavuz, Reyhan Aydoğan Jan 2020

Deep Reinforcement Learning For Acceptance Strategy In Bilateral Negotiations, Yousef Razeghi, Celal Ozan Berk Yavuz, Reyhan Aydoğan

Turkish Journal of Electrical Engineering and Computer Sciences

This paper introduces an acceptance strategy based on reinforcement learning for automated bilateral negotiation, where negotiating agents bargain on multiple issues in a variety of negotiation scenarios. Several acceptance strategies based on predefined rules have been introduced in the automated negotiation literature. Those rules mostly rely on some heuristics, which take time and/or utility into account. For some negotiation settings, an acceptance strategy solely based on a negotiation deadline might perform well; however, it might fail in another setting. Instead of following predefined acceptance rules, this paper presents an acceptance strategy that aims to learn whether to accept its opponent's …

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Bases Of Polymatroids And Problems On Graphs, Hakan Kutucu Jan 2020

Bases Of Polymatroids And Problems On Graphs, Hakan Kutucu

Turkish Journal of Electrical Engineering and Computer Sciences

In the paper, we present new theorems to show that a Hamiltonian path and circuit on an undirected graph can be formulated in terms of bases of polymatroids or extended polymatroids associated with submodular functions defined on subsets of the node-set of a given graph. In this way, we give a new formulation of the well-known traveling salesman problem including constraints in these terms. The main result in the paper states that using a special base of the polymatroid, a Hamiltonian path on an undirected graph can be solved effectively. Since the determination of a Hamiltonian circuit can be reduced …

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Harmonic Reduction Of Svc With System Integrated Apf, Yan Xuhui, Wang Feng, Mahmood Ul Hassan, Muhammad Humayun Jan 2020

Harmonic Reduction Of Svc With System Integrated Apf, Yan Xuhui, Wang Feng, Mahmood Ul Hassan, Muhammad Humayun

Turkish Journal of Electrical Engineering and Computer Sciences

Static var compensators (svcs) are widely used to compensate for reactive power in a system. The hybrid active power filter (hapf) in combination with svc has extensively been studied in the literature to reduce harmonics generated by the svc. This study proposes a new topology of svc for three-phase systems based on a three-phase thyristor-control reactor (tcr). The harmonics generated by the tcr are minimized by an active power filter (apf), which can be realized by a reduced resonant capacitor size. A control strategy comprising feedback and feedforward control is employed to achieve good harmonic reduction and fast transient response. …

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Performance Analysis Of A Fuzzy Disparity Selector For Stereo Matching Of Imagesegments Under Radiometric Variations, Akhil Appu Shetty, Vadakekara Itty George, Chempi Gurudas Nayak, Raviraj Shetty Jan 2020

Performance Analysis Of A Fuzzy Disparity Selector For Stereo Matching Of Imagesegments Under Radiometric Variations, Akhil Appu Shetty, Vadakekara Itty George, Chempi Gurudas Nayak, Raviraj Shetty

Turkish Journal of Electrical Engineering and Computer Sciences

Stereo matching algorithms generate disparity maps, which contain the depth information of the environment, from two or more images of a scene taken from different viewpoints. The process of obtaining dense disparity maps is a problem which is still being actively researched. The presence of radiometric differences in the images only further complicates the stereo matching problem. In the present research work, the images are initially split into small patches of pixels, such that pixels in each patch have similar intensities. The authors attempt to study the effect of the parameters, namely, tuning parameter `?? and the number of segments, …

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Dynamic Optimal Management Of A Hybrid Microgrid Based On Weather Forecasts, Hamadi Bouaicha, Emily Craparo, Habib Dallagi, Samir Nejim Jan 2020

Dynamic Optimal Management Of A Hybrid Microgrid Based On Weather Forecasts, Hamadi Bouaicha, Emily Craparo, Habib Dallagi, Samir Nejim

Turkish Journal of Electrical Engineering and Computer Sciences

Hybrid microgrids containing both renewable and conventional power sources are becoming increasingly attractive for a variety of reasons. However, intermittency of renewable power production and uncertainty in future load prediction increase risks of electric grid instability and, by consequence, restrict the portion of renewable power production in microgrids. In order, to prefigure the upcoming renewable power production, particularly, wind power and photovoltaic power, we suggest using weather forecasts. In addition to illustrating short term renewable power prediction based on ensemble weather forecasts, this paper focuses on optimizing the management of distributed power generation, power storage, and power exchange with the …

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The Quantum Version Of The Shifted Power Method And Its Application Inquadratic Binary Optimization, Ammar Daşkin Jan 2020

The Quantum Version Of The Shifted Power Method And Its Application Inquadratic Binary Optimization, Ammar Daşkin

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we present a direct quantum adaptation of the classical shifted power method. The method is very similar to the iterative phase estimation algorithm; however, it does not require any initial estimate of an eigenvector, and as in the classical case its convergence and the required number of iterations are directly related to the eigengap. If the amount of the gap is in the order of $1/poly(n)$, then the algorithm can converge to the dominant eigenvalue in $O(poly(n))$ time. The method can be potentially used for solving any eigenvalue related problem and finding minimum/maximum of a data set …

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Image Denoising Using Deep Convolutional Autoencoder With Feature Pyramids, Ekrem Çeti̇nkaya, Mustafa Furkan Kiraç Jan 2020

Image Denoising Using Deep Convolutional Autoencoder With Feature Pyramids, Ekrem Çeti̇nkaya, Mustafa Furkan Kiraç

Turkish Journal of Electrical Engineering and Computer Sciences

Image denoising is 1 of the fundamental problems in the image processing field since it is the preliminary step for many computer vision applications. Various approaches have been used for image denoising throughout the years from spatial filtering to model-based approaches. Having outperformed all traditional methods, neural-network-based discriminative methods have gained popularity in recent years. However, most of these methods still struggle to achieve flexibility against various noise levels and types. In this paper, a deep convolutional autoencoder combined with a variant of feature pyramid network is proposed for image denoising. Simulated data generated by Blender software along with corrupted …

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Improving Performance Of Indoor Localization Using Compressive Sensing Andnormal Hedge Algorithm, Saeid Hassanhosseini, Mohammad Reza Taban, Jamshid Abouei, Arash Mohammadi Jan 2020

Improving Performance Of Indoor Localization Using Compressive Sensing Andnormal Hedge Algorithm, Saeid Hassanhosseini, Mohammad Reza Taban, Jamshid Abouei, Arash Mohammadi

Turkish Journal of Electrical Engineering and Computer Sciences

Accurate indoor localization technologies are currently in high demand in wireless sensor networks, which strongly drive the development of various wireless applications including healthcare monitoring, patient tracking and endoscopic capsule localization. The precise position determination requires exact estimation of the time varying characteristics of wireless channels. In this paper, we address this issue and propose a three-phased scheme, which employs an optimal single stage TDOA/FDOA/AOA indoor localization based on spatial sparsity. The first contribution is to formulate the received unknown signals from the emitter as a compressive sensing problem. Then, we solve an $\ell_1$ minimization problem to localize the emitter's …

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Controlling A Launch Vehicle At Exoatmospheric Flight Conditions Via Adaptivecontrol Allocation, Yildiray Yildiz Jan 2020

Controlling A Launch Vehicle At Exoatmospheric Flight Conditions Via Adaptivecontrol Allocation, Yildiray Yildiz

Turkish Journal of Electrical Engineering and Computer Sciences

The focus of this paper is the control of a reusable launch vehicle at exoatmospheric flight conditions, in the presence of actuator effectiveness uncertainty. Since during exoatmospheric flight, dynamic pressure is nonexistent, aerodynamic control surfaces cannot be used. Under these conditions, reaction control jet actuators can provide the necessary thrust to control the vehicle. Reaction control jets have only 2 states, namely, on and off, and continuous control inputs can be implemented with the help of pulse width modulation, which is also employed in this paper. A continuous controller is designed in the outer loop and a control allocator is …

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Simplified Model Predictive Current Control Of Non-Sinusoidal Low Power Brushlessdc Machines, Alireza Lahooti Eshkevari, Hossein Torkaman Jan 2020

Simplified Model Predictive Current Control Of Non-Sinusoidal Low Power Brushlessdc Machines, Alireza Lahooti Eshkevari, Hossein Torkaman

Turkish Journal of Electrical Engineering and Computer Sciences

Several strategies have been proposed to control nonsinusoidal brushless DC machines (BLDCMs). However, high electromagnetic torque ripple and current overshoots occur in commutation times, which are significant problems of those strategies such as for hysteresis current controllers. This paper proposes a model predictive strategy to solve the above issues. It is simple and straightforward. Moreover, it reduces the motor torque ripple significantly and improves the response rate of the control system to the load torque variation in comparison with the conventional technique. The torque varies smoothly, and the performance of the system at commutation time is improved by eliminating the …

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Fiber Optic Chemical Sensors For Water Testing By Using Fiber Loop Ringdown Spectroscopy Technique, Mali̇k Kaya Jan 2020

Fiber Optic Chemical Sensors For Water Testing By Using Fiber Loop Ringdown Spectroscopy Technique, Mali̇k Kaya

Turkish Journal of Electrical Engineering and Computer Sciences

Real-time response, low cost, sensitive and easy setup fiber optic chemical sensors were fabricated by etching a part of single mode fiber in hydrofluoric (HF) acid solution and tested in different water samples such as tap water, DI water, salty and sugar water with different concentrations to record ringdown time (RDT) differences between media due to refractive index differences by employing the fiber loop ringdown (FLRD) spectroscopy technique. Baseline stability of 0.63 % and the minimum detectable RDT of $5.05$ $\mu$s for this kind of fiber optic chemical sensors were obtained. Fabricated sensors were coated with N,N-Diethyl-p-phenylenediamine for the first …

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