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Articles 4891 - 4920 of 13043

Full-Text Articles in Computer Engineering

A Review On Embedded Field Programmable Gate Array Architectures And Configuration Tools, Khouloud Bouaziz, Abdulfattah M. Obeid, Sonda Chtourou, Mohamed Abid Jan 2020

A Review On Embedded Field Programmable Gate Array Architectures And Configuration Tools, Khouloud Bouaziz, Abdulfattah M. Obeid, Sonda Chtourou, Mohamed Abid

Turkish Journal of Electrical Engineering and Computer Sciences

Nowadays, systems-on-chip have reached a level where nonrecurring engineering costs have become a great challenge due to the increase of design complexity and postfabrication errors. Embedded field programmable gate arrays (eFPGAs) represent a viable alternative to overcome these issues since they provide postmanufacturing flexibility that can reduce the number of chip redesigns and amortize chip fabrication cost. In this paper, we present an overview on eFPGAs and their architectures, computer aided design (CAD) tools, and design challenges. An eFPGA must be well-designed and accompanied by an optimized CAD tool suite to respond to target application's requirements in terms of power …

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Design Of A High Performance Narrowband Low Noise Amplifier Using An On-Chip Orthogonal Series Stacked Differential Fractal Inductor For 5g Applications, Sunil Kumar Tumma, Bheemarao Nistala Jan 2020

Design Of A High Performance Narrowband Low Noise Amplifier Using An On-Chip Orthogonal Series Stacked Differential Fractal Inductor For 5g Applications, Sunil Kumar Tumma, Bheemarao Nistala

Turkish Journal of Electrical Engineering and Computer Sciences

Inductors play a crucial role in the design of radio frequency integrated circuits (RFICs) and they typically consume a considerably large area and have a low-quality factor at high frequencies. The employment of fractal structure in on-chip inductors helps in improving the quality factor and also reduces the overall area besides improving the inductance value. In this paper, an orthogonal series stacked differential fractal inductor is proposed and the same is used to design a low noise amplifier (LNA) for 5G band (27--30 GHz) applications. The proposed inductor is fabricated on a multilayer printed circuit board and the measurement results …

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A Novel Semisupervised Classification Method Via Membership And Polyhedral Conic Functions, Nur Uylaş Sati Jan 2020

A Novel Semisupervised Classification Method Via Membership And Polyhedral Conic Functions, Nur Uylaş Sati

Turkish Journal of Electrical Engineering and Computer Sciences

In real-world problems, finding sufficient labeled data for defining classification rules is very difficult. This paper suggests a new semisupervised multiclass classification method. In the initialization, new membership functions are defined by utilizing the labeled data?Äôs medoids and means. Then the unlabeled points are labeled with the class of the highest membership value. In the supervised learning phase, separation via the polyhedral conic functions (PCFs) approach is improved by using defined membership values in the linear programming problem. The suggested algorithm is tested on real-world datasets and compared with the state-of-the-art semisupervised methods. The results obtained indicate that the suggested …

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Integrated Topic Modeling And Sentiment Analysis: A Review Rating Prediction Approach For Recommender Systems, Anbazhagan Mahadevan, Michael Arock Jan 2020

Integrated Topic Modeling And Sentiment Analysis: A Review Rating Prediction Approach For Recommender Systems, Anbazhagan Mahadevan, Michael Arock

Turkish Journal of Electrical Engineering and Computer Sciences

Recommender systems (RSs) are running behind E-commerce websites to recommend items that are likely to be bought by users. Most of the existing RSs are relying on mere star ratings while making recommendations. However, ratings alone cannot help RSs make accurate recommendations, as they cannot properly capture sentiments expressed towards various aspects of the items. The other rich and expressive source of information available that can help make accurate recommendations is user reviews. Because of their voluminous nature, reviews lead to the information overloading problem. Hence, drawing out the user opinion from reviews is a decisive job. Therefore, this paper …

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Retinal Vessel Segmentation Using Modified Symmetrical Local Threshold, Umar Özgünalp Jan 2020

Retinal Vessel Segmentation Using Modified Symmetrical Local Threshold, Umar Özgünalp

Turkish Journal of Electrical Engineering and Computer Sciences

Retinal vessel segmentation is important for the identification of many diseases including glaucoma, hypertensive retinopathy, diabetes, and hypertension. Moreover, retinal vessel diameter is associated with cardiovascular mortality. Accurate detection of blood vessels improves the detection of exudates in color fundus images, as well as detection of the retinal nerve, optic disc, or fovea. A retinal vessel is a darker stripe on a lighter background. Thus, the objective is very similar to the lane detection task for intelligent vehicles. A lane on a road is a light stripe on a darker background (i.e. asphalt). For lane detection, the symmetrical local threshold …

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Detailed Modeling Of A Thermoelectric Generator For Maximum Power Point Tracking, Hayati̇ Mamur, Yusuf Çoban Jan 2020

Detailed Modeling Of A Thermoelectric Generator For Maximum Power Point Tracking, Hayati̇ Mamur, Yusuf Çoban

Turkish Journal of Electrical Engineering and Computer Sciences

Thermoelectric generators (TEGs) are used in small power applications to generate electrical energy from waste heats. Maximum power is obtained when the connected load to the ends of TEGs matches their internal resistance. However, impedance matching cannot always be ensured. Therefore, TEGs operate at lower efficiency. For this reason, maximum power point tracking (MPPT) algorithms are utilized. In this study, both TEGs and a boost converter with MPPT were modeled together. Detailed modeling, simulation, and verification of TEGs depending on the Seebeck coefficient, the hot/cold side temperatures, and the number of modules in MATLAB/Simulink were carried out. In addition, a …

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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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Consumer Loans' First Payment Default Detection: A Predictive Model, Utku Koç, Türkan Sevgi̇li̇ Jan 2020

Consumer Loans' First Payment Default Detection: A Predictive Model, Utku Koç, Türkan Sevgi̇li̇

Turkish Journal of Electrical Engineering and Computer Sciences

A default loan (also called nonperforming loan) occurs when there is a failure to meet bank conditions and repayment cannot be made in accordance with the terms of the loan which has reached its maturity. In this study, we provide a predictive analysis of the consumer behavior concerning a loan?Äôs first payment default (FPD) using a real dataset of consumer loans with approximately 600,000 records from a bank. We use logistic regression, naive Bayes, support vector machine, and random forest on oversampled and undersampled data to build eight different models to predict FPD loans. A two-class random forest using undersampling …

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Applying Deep Learning Models To Structural Mri For Stage Prediction Of Alzheimer's Disease, Altuğ Yi̇ği̇t, Zerri̇n Işik Jan 2020

Applying Deep Learning Models To Structural Mri For Stage Prediction Of Alzheimer's Disease, Altuğ Yi̇ği̇t, Zerri̇n Işik

Turkish Journal of Electrical Engineering and Computer Sciences

Alzheimer's disease is a brain disease that causes impaired cognitive abilities in memory, concentration, planning, and speaking. Alzheimer's disease is defined as the most common cause of dementia and changes different parts of the brain. Neuroimaging, cerebrospinal fluid, and some protein abnormalities are commonly used as clinical diagnostic biomarkers. In this study, neuroimaging biomarkers were applied for the diagnosis of Alzheimer's disease and dementia as a noninvasive method. Structural magnetic resonance (MR) brain images were used as input of the predictive model. T1 weighted volumetric MR images were reduced to two-dimensional space by several preprocessing methods for three different projections. …

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An Index-Based Joint Multilingual/Cross-Lingual Text Categorization Using Topic Expansion Via Babelnet, Eniafe Festus Ayetiran Jan 2020

An Index-Based Joint Multilingual/Cross-Lingual Text Categorization Using Topic Expansion Via Babelnet, Eniafe Festus Ayetiran

Turkish Journal of Electrical Engineering and Computer Sciences

The majority of the state-of-the-art text categorization algorithms are supervised and therefore require prior training. Besides the rigor involved in developing training datasets and the requirement for repetition of training for different texts, working with multilingual texts poses additional unique challenges. One of these challenges is that the developer is required to have many different languages involved. Term expansion such as query expansion has been applied in numerous applications; however, a major drawback of most of these applications is that the actual meaning of terms is not usually taken into consideration. Considering the semantics of terms is necessary because of …

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A New Biometric Identity Recognition System Based On A Combination Of Superior Features In Finger Knuckle Print Images, Hadis Heidari, Abdolah Chalechale Jan 2020

A New Biometric Identity Recognition System Based On A Combination Of Superior Features In Finger Knuckle Print Images, Hadis Heidari, Abdolah Chalechale

Turkish Journal of Electrical Engineering and Computer Sciences

Biometric methods are among the safest and most secure solutions for identity recognition and verification. One of the biometric features with sufficient uniqueness for identity recognition is the finger knuckle print (FKP). This paper presents a new method of identity recognition and verification based on FKP features, where feature extraction is combined with an entropy-based pattern histogram and a set of statistical texture features. The genetic algorithm (GA) is then used to find the superior features among those extracted. After extracting superior features, a support vector machine-based feedback scheme is used to improve the performance of the biometric system. Two …

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Fast Texture Classification Of Denoised Sar Image Patches Using Glcm On Spark, Caner Özcan, Kadri̇ Okan Ersoy, İskender Ülgen Oğul Jan 2020

Fast Texture Classification Of Denoised Sar Image Patches Using Glcm On Spark, Caner Özcan, Kadri̇ Okan Ersoy, İskender Ülgen Oğul

Turkish Journal of Electrical Engineering and Computer Sciences

Classification of a synthetic aperture radar (SAR) image is an essential process for SAR image analysis and interpretation. Recent advances in imaging technologies have allowed data sizes to grow, and a large number of applications in many areas have been generated. However, analysis of high-resolution SAR images, such as classification, is a time-consuming process and high-speed algorithms are needed. In this study, classification of high-speed denoised SAR image patches by using Apache Spark clustering framework is presented. Spark is preferred due to its powerful open-source cluster-computing framework with fast, easy-to-use, and in-memory analytics. Classification of SAR images is realized on …

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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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Lung Cancer Subtype Differentiation From Positron Emission Tomography Images, Oğuzhan Ayyildiz, Zafer Aydin, Bülent Yilmaz, Seyhan Karaçavuş, Kübra Şenkaya, Semra İçer, Erdem Arzu Taşdemi̇r, Eser Kaya Jan 2020

Lung Cancer Subtype Differentiation From Positron Emission Tomography Images, Oğuzhan Ayyildiz, Zafer Aydin, Bülent Yilmaz, Seyhan Karaçavuş, Kübra Şenkaya, Semra İçer, Erdem Arzu Taşdemi̇r, Eser Kaya

Turkish Journal of Electrical Engineering and Computer Sciences

Lung cancer is one of the deadly cancer types, and almost 85 % of lung cancers are nonsmall cell lung cancer (NSCLC). In the present study we investigated classification and feature selection methods for the differentiation of two subtypes of NSCLC, namely adenocarcinoma (ADC) and squamous cell carcinoma (SqCC). The major advances in understanding the effects of therapy agents suggest that future targeted therapies will be increasingly subtype specific. We obtained positron emission tomography (PET) images of 93 patients with NSCLC, 39 of which had ADC while the rest had SqCC. Random walk segmentation was applied to delineate three-dimensional tumor …

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Filter Design For Small Target Detection On Infrared Imagery Using Normalized-Cross-Correlation Layer, Hüseyi̇n Seçki̇n Demi̇r, Erdem Akagündüz Jan 2020

Filter Design For Small Target Detection On Infrared Imagery Using Normalized-Cross-Correlation Layer, Hüseyi̇n Seçki̇n Demi̇r, Erdem Akagündüz

Turkish Journal of Electrical Engineering and Computer Sciences

n this paper, we introduce a machine learning approach to the problem of infrared small target detection filter design. For this purpose, similar to a convolutional layer of a neural network, the normalized-cross-correlational (NCC) layer, which we utilize for designing a target detection/recognition filter bank, is proposed. By employing the NCC layer in a neural network structure, we introduce a framework, in which supervised training is used to calculate the optimal filter shape and the optimum number of filters required for a specific target detection/recognition task on infrared images. We also propose the mean-absolute-deviation NCC (MAD-NCC) layer, an efficient implementation …

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On The Asymptotic Analysis Of The High-Order Statistics Of The Channel Capacity Over Generalized Fading Channels, Ferkan Yilmaz Jan 2020

On The Asymptotic Analysis Of The High-Order Statistics Of The Channel Capacity Over Generalized Fading Channels, Ferkan Yilmaz

Turkish Journal of Electrical Engineering and Computer Sciences

In this article, we provide further asymptotic analysis to the higher-order statistics (HOS) of the channel capacity over generalized fading channels, especially by proposing simple and closed-form expressions each of which can be easily computed as a tight bound revealing the existence of constant gap between the actual and asymptotic HOS of the channel capacity in the limit of both high and low signal-to-noise ratios. As such, we show that these closed-form asymptotic expressions are insightful enough to comprehend the diversity gains. The mathematical formalism we followed in this article is illustrated with some selected numerical examples that validate the …

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Reliability Comparisons Of Mobile Network Operators: An Experimental Case Study From A Crowdsourced Dataset, Engi̇n Zeydan, Ahmet Yildirim Jan 2020

Reliability Comparisons Of Mobile Network Operators: An Experimental Case Study From A Crowdsourced Dataset, Engi̇n Zeydan, Ahmet Yildirim

Turkish Journal of Electrical Engineering and Computer Sciences

It is of great interest for Mobile Network Operators (MNOs) to know how well their network infrastructure performance behaves in different geographical regions of their operating country compared to their horizontal competitors. However, traditional network monitoring and measurement methods of network infrastructure use limited numbers of measurement points that are insufficient for detailed analysis and expensive to scale using an internal workforce. On the other hand, the abundance of crowdsourced content can engender various unforeseen opportunities for MNOs to cope with this scaling problem. This paper investigates end-to-end reliability and packet loss (PL) performance comparisons of MNOs using a previously …

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Design And Fabrication Of An Eight-Port Binary Wilkinson Power Splitter, Mohammad Amir Ghasemi Shabankareh Jan 2020

Design And Fabrication Of An Eight-Port Binary Wilkinson Power Splitter, Mohammad Amir Ghasemi Shabankareh

Turkish Journal of Electrical Engineering and Computer Sciences

An eight-port X-band power splitter based on binary Wilkinson power splitter topology is presented in this paper. The proposed power splitter consists of three stages, with one, two, and four equal power splitters in the first, second, and third stages, respectively. The input power is divided equally between the eight outputs to provide an equal-split power splitter. Evaluation of the structure is carried out using even- and odd-mode techniques. An epoxy laminate FR4 substrate with thickness of 0.5 mm is chosen, while the designed power splitter is simulated using Keysight Advanced Design System 2019 and ANSYS High Frequency Structure Simulation. …

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Design And Implementation Of A Bandpass Wilkinson Power Divider With Wide Bandwidth And Harmonic Suppression, Hojatollah Soleymani, Sobhan Roshani Jan 2020

Design And Implementation Of A Bandpass Wilkinson Power Divider With Wide Bandwidth And Harmonic Suppression, Hojatollah Soleymani, Sobhan Roshani

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper a Wilkinson power divider (WPD) is presented with ultrawide-band operation and harmonic suppression. This WPD is designed using coupling lines and meandered open stubs at main branches. The center frequency of the presented WPD is 4.25 GHz, which is fabricated and measured on RT/Duroid substrate with dielectric constant of 2.2. The proposed WPD provides good filtering band with high attenuation level. The 15 dB return loss operational bandwidth (BW) of the WPD is obtained between 3.2 GHz and 5.3 GHz, which shows 50 % operational bandwidth.

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A Wide Angle Multiple Beam Lens For Convex Conformal Arrays, Rasi̇me Uyguroglu, Abdullah Y. Oztoprak Jan 2020

A Wide Angle Multiple Beam Lens For Convex Conformal Arrays, Rasi̇me Uyguroglu, Abdullah Y. Oztoprak

Turkish Journal of Electrical Engineering and Computer Sciences

Multifocal lenses have been widely used as multiple beam forming networks for linear and planar arrays, but are not suitable for large convex conformal arrays as they are not physically realizable for wide angle beams. In this study, a new lens design especially suitable for convex conformal arrays is introduced. The new lens has no perfect focal points, but there are a certain number of correct phases in each of the beam directions. The directional patterns of the radiating elements are also taken into account to improve radiation patterns for desired directions. It has been shown that the new lens …

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Sensor Anomaly Detection In The Industrial Internet Of Things Based On Edge Computing, Dequan Kong, Desheng Liu, Lei Zhang, Lili He, Qingwu Shi, Xiaojun Ma Jan 2020

Sensor Anomaly Detection In The Industrial Internet Of Things Based On Edge Computing, Dequan Kong, Desheng Liu, Lei Zhang, Lili He, Qingwu Shi, Xiaojun Ma

Turkish Journal of Electrical Engineering and Computer Sciences

In the industrial internet of things (IIoT), because thousands of pieces of hardware, instruments, and various controllers are involved, the core problem is the sensors. Detection using sensors is the bottom line of the IIoT, directly affecting the detection accuracy and control indicators of the IIoT system. However, when a large number of real-time data generated by IIoT devices are transferred to cloud computing centers, large-scale data will inevitably bring computing load, which will affect the computing speed of cloud computing centers and increase the computing load of cloud computing data centers. These factors directly lead to instability and delay …

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Rms Frequency Error Performance And Spurious Signals In Two-Point Modulators Due To Path Imbalances, Gökhun Selçuk, Kaan Üçel Jan 2020

Rms Frequency Error Performance And Spurious Signals In Two-Point Modulators Due To Path Imbalances, Gökhun Selçuk, Kaan Üçel

Turkish Journal of Electrical Engineering and Computer Sciences

In this study the authors introduce an analysis of rms frequency error performance and spurious signals generated by two-point modulators. The analysis is not limited to a constant delay and magnitude imbalance between modulation paths but allows frequency-dependent group delay and amplitude variations as well. Moreover, a discrete time phase frequency detector model is incorporated in Laplace domain analysis that takes into account the sampling nature of a phase-locked loop (PLL). Using the spectrum of pulse width modulated charge pump pulses, the spurious signals at the output of the PLL are evaluated. The proposed formulae are tested on a practical …

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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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Operation Scheme For Mmc-Based Statcom Using Modified Instantaneous Symmetrical Components, Qing Duan, Wanxing Sheng, Guanglin Sha, Zhen Li, Caihong Zhao, Penghua Li, Chunyan Ma Jan 2020

Operation Scheme For Mmc-Based Statcom Using Modified Instantaneous Symmetrical Components, Qing Duan, Wanxing Sheng, Guanglin Sha, Zhen Li, Caihong Zhao, Penghua Li, Chunyan Ma

Turkish Journal of Electrical Engineering and Computer Sciences

Modular multilevel converters (MMCs) are characterized by modularization and multielectric equality, and the application of this structure to a high-voltage large-capacity static synchronous compensator (STATCOM) shows good potential. In this paper, a modified instantaneous symmetrical component method is proposed for positive- and negative-sequence decomposition, i.e. the critical part of the control device, which can accurately detect the instantaneous value of each sequence component in three-phase asymmetrical phasors in real time. Then, based on this method, the paper proposes a control method for MMC-based STATCOMs that solves the problems of multi-DC (direct current) voltage balance, grid-connected current control, and circulation suppression. …

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Optimal Fractional-Order Pid Controller Of Inverter-Based Power Plants For Power Systems Lfo Damping, Mahdi Saadatmand, Babak Mozafari, Gevork Babamalek Gharehpetian, Soodabeh Soleymani Jan 2020

Optimal Fractional-Order Pid Controller Of Inverter-Based Power Plants For Power Systems Lfo Damping, Mahdi Saadatmand, Babak Mozafari, Gevork Babamalek Gharehpetian, Soodabeh Soleymani

Turkish Journal of Electrical Engineering and Computer Sciences

The penetration of inverter-based power plants (IBPPs), such as large-scale photovoltaic (PV) power plants (LPPPs), is ever increasing considering the merits of renewable energy power plants (REPPs). Given that IBPPs are added to power systems or replaced by conventional power plants, they should undertake the most common tasks of synchronous generators. The low-frequency oscillation (LFO) damping through the power system stabilizers (PSSs) of synchronous generators is regarded as one of the common tasks in power plants. This paper proposes an optimal fractional-order proportional-integral-derivative (FOPID) controller implemented in the control loop of IBPPs for LFO damping in power systems. For this …

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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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Dynamically Updated Diversified Ensemble-Based Approach For Handling Concept Drift, Kanu Goel, Shalini Batra Jan 2020

Dynamically Updated Diversified Ensemble-Based Approach For Handling Concept Drift, Kanu Goel, Shalini Batra

Turkish Journal of Electrical Engineering and Computer Sciences

Concept drift is the phenomenon where underlying data distribution changes over time unexpectedly. Examining such drifts and getting insight into the executing processes at that instance of time is a big challenge. Prediction models should be capable of handling drifts in scenarios where statistical properties show abrupt changes. Various strategies exist in the literature to deal with such challenging scenarios but the majority of them are limited to the identification of a particular kind of drift pattern. The proposed approach uses online drift detection in a diversified adaptive setting with pruning techniques to formulate a concept drift handling approach, named …

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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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