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2020

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Articles 2251 - 2280 of 2675

Full-Text Articles in Computer Engineering

Energy Efficiency In Cmos Power Amplifier Designs For Ultralow Power Mobile Wireless Communication Systems, Selvakumar Mariappan, Jagadheswaran Rajendran, Norlaili Mohd Noh, Harikrishnan Ramiah, Asrulnizam Abd Manaf Jan 2020

Energy Efficiency In Cmos Power Amplifier Designs For Ultralow Power Mobile Wireless Communication Systems, Selvakumar Mariappan, Jagadheswaran Rajendran, Norlaili Mohd Noh, Harikrishnan Ramiah, Asrulnizam Abd Manaf

Turkish Journal of Electrical Engineering and Computer Sciences

Wireless communication standards keep evolving so that the requirement for high data rate operation can be fulfilled. This leads to the efforts in designing high linearity and low power consumption radio frequency power amplifier (RFPA) to support high data rate signal transmission and preserving battery life. The percentage of the DC power of the transceiver utilized by the power amplifier (PA) depends on the efficiency of the PA, user data rate, propagation conditions, signal modulations, and communication protocols. For example, the PA of a WLAN transceiver consumes 49 % of the overall efficiency from the transmitter. Hence, operating the PA …

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Fuzzy C-Means Directional Clustering (Fcmdc) Algorithm Using Trigonometric Approximation, Orhan Kesemen, Özge Tezel, Eda Özkul, Buğra Kaan Ti̇ryaki̇ Jan 2020

Fuzzy C-Means Directional Clustering (Fcmdc) Algorithm Using Trigonometric Approximation, Orhan Kesemen, Özge Tezel, Eda Özkul, Buğra Kaan Ti̇ryaki̇

Turkish Journal of Electrical Engineering and Computer Sciences

Cluster analysis is widely used in data analysis. Statistical data analysis is generally performed on the linear data. If the data has directional structure, classical statistical methods cannot be applied directly to it. This study aims to improve a new directional clustering algorithm which is based on trigonometric approximation. The trigonometric approximation is used for both descriptive statistics and clustering of directional data. In this paper, the fuzzy clustering algorithms (FCD and FCM4DD) improved for directional data and the proposed method are carried out on some numerical and real data examples, and the simulation results are presented. Consequently, these results …

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Context-Aware System For Glycemic Control In Diabetic Patients Using Neural Networks, Owais Bhat, Dawood A. Khan Jan 2020

Context-Aware System For Glycemic Control In Diabetic Patients Using Neural Networks, Owais Bhat, Dawood A. Khan

Turkish Journal of Electrical Engineering and Computer Sciences

Diabetic patients are quite hesitant in engaging in normal physiological activities due to difficulties associated with diabetes management. Over the last few decades, there have been advancements in the computational power of embedded systems and glucose sensing technologies. These advancements have attracted the attention of researchers around the globe developing automatic insulin delivery systems. In this paper, a method of closed-loop control of diabetes based on neural networks is proposed. These neural networks are used for making predictions based on the clinical data of a patient. A neural network feedback controller is also designed to provide a glycemic response by …

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Automatic Characterization Of Copy Number Polymorphism Using High Throughput Sequencing, Can Alkan Jan 2020

Automatic Characterization Of Copy Number Polymorphism Using High Throughput Sequencing, Can Alkan

Turkish Journal of Electrical Engineering and Computer Sciences

Genome structural variation, broadly defined as alterations longer than 50 bp, are important sources for genetic variation among humans, including those that cause complex diseases such as autism, developmental delay, and schizophrenia. Although there has been considerable progress in characterizing structural variation since the beginnings of the 1000 Genomes Project, one form of structural variation called segmental duplications (SDs) remained largely understudied in large cohorts. This is mostly because SDs cannot be accurately discovered using the alignment files generated with standard read mapping tools. Instead, they can only be found when multiple map locations are considered. There is still a …

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Controlling Waveguide Modes Using $\Mathcal{Pt}$ Transformation Media, Hayretti̇n Odabaşi Jan 2020

Controlling Waveguide Modes Using $\Mathcal{Pt}$ Transformation Media, Hayretti̇n Odabaşi

Turkish Journal of Electrical Engineering and Computer Sciences

We study rectangular waveguide modes loaded with parity-time $\left(\mathcal{PT}\right)$ transformation media derived by complex transformation optics (CTO) approach. $\mathcal{PT}$ transformation media are obtained through mirror symmetric complex coordinate transformations resulting in a balanced loss/gain media. It is shown that waveguide modes can be controlled by simply changing the imaginary part of the complex coordinate transformation while not affecting any other characteristic of the waveguide. The field distribution inside the waveguide can either be stretched towards the sides or squeezed at the center of the waveguide by employing different loading configurations. \keywords{Complex transformation optics, waveguides, $\mathcal{PT}$ symmetry}

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A Power And Area Efficient Approximate Carry Skip Adder For Error Resilient Applications, Sujit Patel, Bharat Garg, Shireesh Kumar Rai Jan 2020

A Power And Area Efficient Approximate Carry Skip Adder For Error Resilient Applications, Sujit Patel, Bharat Garg, Shireesh Kumar Rai

Turkish Journal of Electrical Engineering and Computer Sciences

The compute-intensive multimedia applications on portable devices require power and area efficient arithmetic units. The adder is a prime building block of these arithmetic units and limits the overall performance. Therefore, this paper analyzes the logic operations of the state-of-the-art adders and presents a novel low complexity adder segment with new carry prediction logic by removing the redundant logic and sharing the common operations. Further, a new power and area efficient approximate carry skip (PAEA-CSK) adder is proposed using the novel adder segment. The effectiveness of the proposed PAEA-CSK adder is evaluated and compared over the existing adders by implementing …

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Performance Improvement Of Induction Motor Drives With Model-Based Predictive Torque Control, Fati̇h Korkmaz Jan 2020

Performance Improvement Of Induction Motor Drives With Model-Based Predictive Torque Control, Fati̇h Korkmaz

Turkish Journal of Electrical Engineering and Computer Sciences

One of the most important advantages of using modeling and simulation software in design and control engineering is the ability to predict system behavior within specified conditions. This paper presents a novel error vector-based control algorithm that aims to reduce torque ripples predicting flux and torque errors in a conventional vector-controlled induction motor. For this purpose, a new control model has been developed that envisages flux change by applying probabilistic space vectors' torque and flux control. In the proposed predictive control algorithm, flux and torque errors are calculated for each candidate voltage vector. Thus, the optimal output voltage vector that …

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Estimation Of Distribution-Based Multiobjective Design Space Exploration For Energy And Throughput-Optimized Mpsocs, Maryam Murad, Ishfaq Hussain, Ayaz Ahmad, Muhammad Yasir Qadri, Nadia N. Qadri Jan 2020

Estimation Of Distribution-Based Multiobjective Design Space Exploration For Energy And Throughput-Optimized Mpsocs, Maryam Murad, Ishfaq Hussain, Ayaz Ahmad, Muhammad Yasir Qadri, Nadia N. Qadri

Turkish Journal of Electrical Engineering and Computer Sciences

Modern multicore architectures comprise a large set of components and parameters that require being matched to achieve the best balance between power consumption and throughput performance for a particular application domain. The exploration of design space for finding the best power throughput trade-off is a combinatorial optimization problem with a large number of combinations, and. in general, black its solution is prohibitively difficult to be explored exhaustively. However, fortunately, evolutionary algorithms (EAs) have the potential to efficiently solve this problem with reasonable computational complexity. In this paper, we consider a multiobjective design space exploration (DSE) problem with two conflicting objectives. …

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Rule Extraction And Performance Estimation By Using Variable Neighborhoodsearch For Solar Power Plant In Konya, Yusuf Uzun, Muci̇z Özcan Jan 2020

Rule Extraction And Performance Estimation By Using Variable Neighborhoodsearch For Solar Power Plant In Konya, Yusuf Uzun, Muci̇z Özcan

Turkish Journal of Electrical Engineering and Computer Sciences

The use of renewable energy sources in the production of electricity has become inevitable in order to reduce the greenhouse gases left in the atmosphere that cause the Earth to warm up. Although countries on a national basis have implemented a number of policies to support electricity generated from renewable energy sources, investments to produce electricity without a license on a local basis are not desirable. Those who want to invest medium and small scale for the most reason expect that this work will be supported by real data. Although the electricity generated by renewable investments is generated by simulation …

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Geographic Variation And Ethnicity In Diabetic Retinopathy Detection Via Deeplearning, Ali Serener, Sertan Serte Jan 2020

Geographic Variation And Ethnicity In Diabetic Retinopathy Detection Via Deeplearning, Ali Serener, Sertan Serte

Turkish Journal of Electrical Engineering and Computer Sciences

The prevalence of diabetes is on the rise steadily around the globe. Diabetic retinopathy (DR) is a result of damage to the blood vessels in the retina due to diabetes and its fast treatment is crucial for preventing possible blindness. The diagnosis of DR is done mostly using a comprehensive eye exam, where the eye is dilated for better inspection. Analysis by an ophthalmologist is prone to human error and thus automatic and highly accurate detection of DR is preferred for an earlier and better diagnosis. It is important, however, that automatic detection be accurate for all data collected from …

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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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Hyperheuristics For Explicit Resource Partitioning In Simultaneous Multithreadedprocessors, İsa Ahmet Güney, Kemal Poyraz, Gürhan Küçük, Ender Özcan Jan 2020

Hyperheuristics For Explicit Resource Partitioning In Simultaneous Multithreadedprocessors, İsa Ahmet Güney, Kemal Poyraz, Gürhan Küçük, Ender Özcan

Turkish Journal of Electrical Engineering and Computer Sciences

In simultaneous multithreaded (SMT) processors, various data path resources are concurrently shared by many threads. A few heuristic approaches that explicitly distribute those resources among threads with the goal of improved overall performance have already been proposed. A selection hyperheuristic is a high-level search methodology that mixes a predetermined set of heuristics in an iterative framework to utilize their strengths for solving a given problem instance. In this study, we propose a set of selection hyperheuristics for selecting and executing the heuristic with the best performance at a given stage. To the best of our knowledge, this is one of …

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Multitask-Based Association Rule Mining, Peli̇n Yildirim Taşer, Kökten Ulaş Bi̇rant, Derya Bi̇rant Jan 2020

Multitask-Based Association Rule Mining, Peli̇n Yildirim Taşer, Kökten Ulaş Bi̇rant, Derya Bi̇rant

Turkish Journal of Electrical Engineering and Computer Sciences

Recently, there has been a growing interest in association rule mining (ARM) in various fields. However, standard ARM algorithms fail to discover rules for multitask problems as they do not consider task-oriented investigation and, therefore, they ignore the correlation among the tasks. Considering this situation, this paper proposes a novel algorithm, named multitask association rule miner (MTARM), that tends to jointly discover rules by considering multiple tasks. This paper also introduces two novel concepts: single-task rule and multiple-task rule. In the first phase of the proposed approach, highly frequent local rules (single-task rules) are explored for each task separately and …

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Adaptive Prescribed Performance Servo Control Of An Automotive Electronicthrottle System With Actuator Constraint, Zitao Sun, Xiaohong Jiao Jan 2020

Adaptive Prescribed Performance Servo Control Of An Automotive Electronicthrottle System With Actuator Constraint, Zitao Sun, Xiaohong Jiao

Turkish Journal of Electrical Engineering and Computer Sciences

To further improve the transient and steady-state performance of automotive electronic throttle position tracking, in this paper an adaptive prescribed performance servo control strategy is designed and applied to a real electronic throttle control system. In view of the possible high gain of the prescribed performance controller in practice, the actuator constraint is also considered in the controller design. The designed servo controller can ensure the transient and steady-state responses of tracking error are limited in the range prescribed by the performance function, and converge with the prescribed convergence rate and have no overshoot. The incorporated adaptive updating law can …

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Estimating Spatiotemporal Focus Of Documents Using Entropy With Pmi, Damla Yaşar, Selma Teki̇r Jan 2020

Estimating Spatiotemporal Focus Of Documents Using Entropy With Pmi, Damla Yaşar, Selma Teki̇r

Turkish Journal of Electrical Engineering and Computer Sciences

Many text documents are spatiotemporal in nature, i.e. contents of a document can be mapped to a specific time period or location. For example, a news article about the French Revolution can be mapped to year 1789 as time and France as place. Identifying this time period and location associated with the document can be useful for various downstream applications such as document reasoning or spatiotemporal information retrieval. In this paper, temporal entropy with pointwise mutual information (PMI) is proposed to estimate the temporal focus of a document. PMI is used to measure the association of words with time expressions. …

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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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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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Lattice-Reduction Aided Multiple-Symbol Differential Detection In Two-Way Relay Transmission, Chanfei Wang, Minghua Cao Jan 2020

Lattice-Reduction Aided Multiple-Symbol Differential Detection In Two-Way Relay Transmission, Chanfei Wang, Minghua Cao

Turkish Journal of Electrical Engineering and Computer Sciences

Multiple-symbol differential detection (MSDD) algorithms are proposed in two-way relay transmission (TWRT). Firstly, generalized likelihood ratio test based MSDD (GLRT-MSDD) is proposed in TWRT. Unfortunately, as the number of observation windows increases, the computational complexity of GLRT-MSDD increases exponentially. Hence, this detection in TWRT constitutes a challenging problem. Moreover, we find a way to reformulate the GLRTMSDD model and additionally propose a lattice-reduction aided MSDD (LR-MSDD) model. Performance analysis and simulations show that the proposed LR-MSDD provides bit-error rate performance close to that of GLRT-MSDD with lower complexity in TWRT.

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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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Emulation Of Burst-Based Adaptive Link Rates In Netfpga Towards Green Networking, Shahul Hamead H, Mirnalinee Tt, Kavi Priya D Jan 2020

Emulation Of Burst-Based Adaptive Link Rates In Netfpga Towards Green Networking, Shahul Hamead H, Mirnalinee Tt, Kavi Priya D

Turkish Journal of Electrical Engineering and Computer Sciences

In recent times, energy consumption in communication media has been increasing drastically. In the literature, energy-saving techniques that enable network devices to enter sleep state or limit the data rate have been proposed to reduce energy costs. In our earlier work, we proposed an energy-saving technique called burst-based adaptive link rate (BBALR), the simulation of which assures increased energy savings. In this paper, we have emulated the hardware implementation of BBALR and compared its performance with the outputs of other prominent energy-saving policies based on dynamic link rate adaption. The energy savings are mapped from the measured sleep time and …

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A Fully Batteryless Multiinput Single Inductor Single Output Energy Harvesting Architecture, Ridvan Umaz Jan 2020

A Fully Batteryless Multiinput Single Inductor Single Output Energy Harvesting Architecture, Ridvan Umaz

Turkish Journal of Electrical Engineering and Computer Sciences

Conventional energy architectures that utilize multiple ambient energy sources are initiated either by an external power supply or through the addition of an extra power source (e.g., battery) to the architecture. However, these interventions compromise the goal of a self-sustainable energy harvesting system. Moreover, conventional architectures are not effective in situations where space is limited (e.g., an artificial heart) or when access to this space is difficult (e.g., human implantable devices), due to their large battery size. Thus, conventional energy combiner circuits that use multiple energy sources are not well suited for supplying power to most applications. This paper presents …

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An Arbitrary Waveform Magnetic Nanoparticle Relaxometer With An Asymmetricalthree-Section Gradiometric Receive Coil, Can Bariş Top Jan 2020

An Arbitrary Waveform Magnetic Nanoparticle Relaxometer With An Asymmetricalthree-Section Gradiometric Receive Coil, Can Bariş Top

Turkish Journal of Electrical Engineering and Computer Sciences

Magnetic nanoparticles (MNPs) have a wide range of clinical applications for imaging, therapy, and biosensing. Superparamagnetic MNPs can be directly visualized with high spatiotemporal resolution using the magnetic particle imaging (MPI) modality. The image resolution of MPI depends on the relaxation properties of the MNPs. Therefore, characterization of MNP response under alternating magnetic field excitation is necessary to predict MPI imaging performance and develop optimized MNPs. Biosensing applications also make use of the change in the relaxation response of MNPs after binding to a target agent. As MNP relaxation properties change with temperature and viscosity, noninvasive probing of these microenvironmental …

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On Efficient Computation Of Equilibrium Under Social Coalition Structures, Buğra Çaşkurlu, Özgün Eki̇ci̇, Fati̇h Erdem Kizilkaya Jan 2020

On Efficient Computation Of Equilibrium Under Social Coalition Structures, Buğra Çaşkurlu, Özgün Eki̇ci̇, Fati̇h Erdem Kizilkaya

Turkish Journal of Electrical Engineering and Computer Sciences

In game-theoretic settings the key notion of analysis is an equilibrium, which is a profile of agent strategies such that no viable coalition of agents can improve upon their coalitional welfare by jointly changing their strategies. A Nash equilibrium, where viable coalitions are only singletons, and a super strong equilibrium, where every coalition is deemed viable, are two extreme scenarios in regard to coalition formation. A recent trend in the literature is to consider equilibrium notions that allow for coalition formation in between these two extremes and which are suitable to model social coalition structures that arise in various real-life …

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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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Assessment Of Environmental Factors Affecting Software Reliability: A Survey Study, Alper Özcan, Çağatay Çatal, Cengi̇z Toğay, Bedi̇r Teki̇nerdoğan, Emrah Dönmez Jan 2020

Assessment Of Environmental Factors Affecting Software Reliability: A Survey Study, Alper Özcan, Çağatay Çatal, Cengi̇z Toğay, Bedi̇r Teki̇nerdoğan, Emrah Dönmez

Turkish Journal of Electrical Engineering and Computer Sciences

Currently, many systems depend on software, and software reliability as such has become one of the key challenges. Several studies have been carried out that focus on the impact of external environmental factors that impact software reliability. These studies, however, were all carried out in the same geographical context. Given the rapid developments in software engineering, this study aims to identify and reinvestigate the environmental factors that impact software reliability by also considering a different context. The environmental factors that have an impact on software reliability as reported in earlier studies have been analyzed and synthesized. Subsequently, a survey study …

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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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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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Peri-Net: A Parameter Efficient Residual Inception Network For Medical Imagesegmentation, Fatmatülzehra Uslu, Cher Bass, Anil A. Bharath Jan 2020

Peri-Net: A Parameter Efficient Residual Inception Network For Medical Imagesegmentation, Fatmatülzehra Uslu, Cher Bass, Anil A. Bharath

Turkish Journal of Electrical Engineering and Computer Sciences

Recent developments in deep networks allow us to train networks with more parameters by yielding better performance given sufficient amount of data. However, we are still restricted with the availability of labelled data in medical image segmentation, where the problem is exacerbated with high intra- and intervariability of anatomical structures. In order to bypass this problem without compromising network performance, this study introduces a PERINet, which promises to achieve higher performance while being with smaller parameter count such as on the order of 0.8 million than its counterparts. The network benefits from rich features generated by our versions of inception …

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Optimal Svc Allocation In Power Systems Using Lightning Attachment Procedureoptimization, Ayman Awad, Salah Kamel, Heba Youssef, Francisco Jurado Jan 2020

Optimal Svc Allocation In Power Systems Using Lightning Attachment Procedureoptimization, Ayman Awad, Salah Kamel, Heba Youssef, Francisco Jurado

Turkish Journal of Electrical Engineering and Computer Sciences

Flexible AC transmission systems (FACTS) technology is widely adopted and utilized to maintain the performance of power systems. However, the improvements of power system performance achieved by FACTS devices depend on the right sizing and allocation of such devices. For technical and economic considerations, a FACTS device's location and size should be selected very carefully in order to maximize its benefits to the power system. In this paper, the sizing and location of a static VAR compensator (SVC) are optimally determined using a new optimization technique called lightning attachment procedure optimization (LAPO). The optimal allocation of the SVC is determined …

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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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