Computer Engineering Commons^™

A Combined Protective Scheme For Fault Classification And Identification Of Faulty Section In Series Compensated Transmission Lines, Resul Çöteli̇

Turkish Journal of Electrical Engineering and Computer Sciences

The fault detection process is very difficult in transmission lines with a fixed series capacitor because of the nonlinear behavior of protection device and series-parallel resonance. This paper proposes a new method based on S-transform (ST) and support vector machines (SVMs) for fault classification and identification of a faulty section in a transmission line with a fixed series capacitor placed at the middle of the line. In the proposed method, the fault detection process is carried out by using distinctive features of 3-line signals (line voltages and currents) and zero sequence current. The relevant features of these signals are obtained …

Adaptive Detection Of Chaotic Oscillations In Ferroresonance Using Modified Extended Kalman Filter, Cengi̇z Polat Uzunoğlu, Mukden Uğur

Turkish Journal of Electrical Engineering and Computer Sciences

Power quality and power disturbances have become an important factor for power systems. Chaotic ferroresonance is one of the disturbances that may cause overvoltages and overcurrents; hence, it can endanger the system reliability and continuous safe operating. A power system that generates chaotic oscillations is a dynamic system, which can be modeled with a Duffing equation. This paper introduces the application of a modified extended Kalman filter for improving the detection of chaotic behavior of power system signals. A modification algorithm is used to increase the estimation performance of the former casual extended Kalman filter. The proposed method is employed …

Survey Of Power Quality In Turkish National Transmission Network, Celal Kocatepe, Bedri̇ Kekezoğlu, Altuğ Bozkurt, Recep Yumurtaci, Aslan İnan, Oktay Arikan, Mustafa Baysal, Yener Akkaya

Turkish Journal of Electrical Engineering and Computer Sciences

Harmonic distortion and flicker severity have become the main concerns in power transmission networks. Different types of harmonic and flicker sources exist in power systems, such as arc furnaces and cycloconverters. A power quality problem found in networks can cause additional temperature rise, losses, noise, and irritation in the lighting equipment. The aim of this study is to identify the level of harmonics and flicker in the 380-kV transmission network of Turkey. The measurement and analysis are performed using a specially developed power quality analyzer. The effects of harmonics and flicker on the network are discussed based on real measurement …

Optimal Iterative Learning Control Design For Generator Voltage Regulation System, Mohsen Rezaei Estakhrouieh, Ali Akbar Gharaveisi

Turkish Journal of Electrical Engineering and Computer Sciences

The purpose of this paper is to design a good tracking controller for the generator automatic voltage regulator (AVR) system. It uses an iterative learning control (ILC) algorithm as a control rule and tries to keep voltage error as low as possible, while replying to set point changes as fast as possible. Two models of ILC are discussed: P-type learning and linear quadratic (LQ) optimal design. The results of designing by LQ optimal method are compared with a Ziegler--Nichols proportional-integral-derivative (PID) controller. The effects of changing different parameters are investigated and illustrated by simulation. In order to provide better robustness …

Simulation Of Discrete Electromagnetic Propagation Model For Atmospheric Effects On Mobile Communication, Şaban Seli̇m Şeker, Fulya Kunter

Turkish Journal of Electrical Engineering and Computer Sciences

Wireless communication has become an important part of our lives, and atmospheric effects are one of the ultimate factors affecting quality of communication and satellite systems. In this study the attenuation in mobile communication due to atmospheric events like snow and rain is simulated using the discrete propagation model. In this work, spherical raindrop and oblate spheroid raindrop modeling are used. To check the validity of simulations, the commonly used and accepted ITU-R rain model is used. Oblate spheroid raindrop modeling produces results that are more compatible with ITU-R results, especially at frequencies higher than 50 GHz. At lower frequencies, …

A New Method Based On Sensitivity Analysis To Optimize The Placement Of Ssscs, Hamed Hashemi Dezaki, Masoud Mohammadalizadeh Shabestary, Hossein Askarian Abyaneh, Gevorg Babamalek Gharehpetian, Mehdi Garmrudi

Turkish Journal of Electrical Engineering and Computer Sciences

The flexible altering current transmission system (FACTS) controllers such as static synchronous series compensators (SSSCs) and unified power flow controllers can strongly improve the different parameters of power systems. They can be used to improve the transient stabilities, voltage profiles, lines transmission capabilities, etc. Therefore, the optimized allocation of FACTS devices is an important issue in recent research. The optimal placements of FACTS devices can have a determinant effect on the performance of a system, too. In this paper, the proper allocation of SSSCs is proposed. Sensitivity analysis is used in order to model SSSCs' effects on the power system. …

Comparison Of Speech Parameterization Techniques For The Classification Of Speech Disfluencies, Chong Yen Fook, Hariharan Muthusamy, Lim Sin Chee, Sazali Bin Yaacob, Abdul Hamid Bin Adom

Turkish Journal of Electrical Engineering and Computer Sciences

Stuttering assessment through the manual classification of speech disfluencies is subjective, inconsistent, time-consuming, and prone to error. The aim of this paper is to compare the effectiveness of the 3 speech feature extraction methods, mel-frequency cepstral coefficients, linear predictive coding (LPC)-based cepstral parameters, and perceptual linear predictive (PLP) analysis, for classifying 2 types of speech disfluencies, repetition and prolongation, from recorded disfluent speech samples. Three different classifiers, the k-nearest neighbor classifier, linear discriminant analysis-based classifier, and support vector machine, are employed for the classification of speech disfluencies. Speech samples are taken from the University College London Archive of Stuttered Speech …

Fuzzified Artificial Bee Colony Algorithm For Nonsmooth And Nonconvex Multiobjective Economic Dispatch Problem, Chandrasekaran Koodalsamy, Sishaj Pulikottil Simon

Turkish Journal of Electrical Engineering and Computer Sciences

The economic dispatch (ED) problem is one of the important optimization problems in power system operation. Recently the power system has stressed the need for reliable, nonpolluting, and economic operation. Hence, 3 conflicting functions of reliability, emission, and fuel cost are considered in the objective function of the proposed ED problem. The problem is formulated as a nonsmooth and nonconvex problem when the valve-point effects of thermal units are considered in the proposed reliable emission and economic dispatch (REED) problem. This paper presents a multiobjective optimization methodology for solving the newly developed REED problem using a fuzzified artificial bee colony …

An Efficient Solving Of The Traveling Salesman Problem: The Ant Colony System Having Parameters Optimized By The Taguchi Method, Musa Peker, Baha Şen, Pinar Yildiz Kumru

Turkish Journal of Electrical Engineering and Computer Sciences

Owing to its complexity, the traveling salesman problem (TSP) is one of the most intensively studied problems in computational mathematics. The TSP is defined as the provision of minimization of total distance, cost, and duration by visiting the n number of points only once in order to arrive at the starting point. Various heuristic algorithms used in many fields have been developed to solve this problem. In this study, a solution was proposed for the TSP using the ant colony system and parameter optimization was taken from the Taguchi method. The implementation was tested by various data sets in the …

Detection Of Microcalcification Clusters In Digitized X-Ray Mammograms Using Unsharp Masking And Image Statistics, Peli̇n Kuş, İrfan Karagöz

Turkish Journal of Electrical Engineering and Computer Sciences

A fully automated method for detecting microcalcification (MC) clusters in regions of interest (ROIs) extracted from digitized X-ray mammograms is proposed. In the first stage, an unsharp masking is used to perform the contrast enhancement of the MCs. In the second stage, the ROIs are decomposed into a 2-level contourlet representation and the reconstruction is obtained by eliminating the low-frequency subband in the second level. In the third stage, statistical textural features are extracted from the ROIs and they are classified using support vector machines. To test the performance of the method, 57 ROIs selected from the Mammographic Image Analysis …

Discovery Of The Connection Among Age-Related Macular Degeneration, Mthfr C677t And Pai 1 4g/5g Gene Polymorphisms, And Body Mass Index By Means Of Bayesian Inference Methods, Aydan Çelebi̇ler, Huseyin Seker, Bora Yüksel, Ahmet Orun, Si̇bel Bi̇lgi̇li̇, Muhammet Baysal Karaca

Turkish Journal of Electrical Engineering and Computer Sciences

Age-related macular degeneration (AMD) is the leading cause of irreversible blindness in the elderly. The aim of this study was therefore to explore the relationship between the presence of multiple gene polymorphisms and 2 distinct advanced `dry and wet' AMD phenotypes, and to assess gene interactions with the influence of personal factors in a Turkish population as a pilot study. For the analysis, the data were collected from 73 unrelated participants, grouped as 29 wet and 26 dry AMD patients, and 18 healthy controls. They were all genotyped for the multiple gene polymorphisms in 12 different genes. The data set …

A New Intelligent Classifier For Breast Cancer Diagnosis Based On A Rough Set And Extreme Learning Machine: Rs + Elm, Yilmaz Kaya

Turkish Journal of Electrical Engineering and Computer Sciences

Breast cancer is one of the leading causes of death among women all around the world. Therefore, true and early diagnosis of breast cancer is an important problem. The rough set (RS) and extreme learning machine (ELM) methods were used collectively in this study for the diagnosis of breast cancer. The unnecessary attributes were discarded from the dataset by means of the RS approach. The classification process by means of ELM was performed using the remaining attributes. The Wisconsin Breast Cancer dataset (WBCD), derived from the University of California Irvine machine learning database, was used for the purpose of testing …

Novel Approaches For Automated Epileptic Diagnosis Using Fcbf Selection And Classification Algorithms, Baha Şen, Musa Peker

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a new application for automated epileptic detection using the fast correlation-based feature (FCBF) selection and classification algorithms. This study consists of 3 stages: feature extraction, feature selection from electroencephalography (EEG) signals, and the classification of these signals. In the feature extraction phase, 16 attribute algorithms are used in 5 categories, and 36 feature parameters are obtained from these algorithms. In the feature selection phase, the FCBF algorithm is chosen to select a set of attributes that best represent the EEG signals. The resulting attributes are used as input parameters for the classification algorithms. In the classification phase, …

Anfis-Based Estimation Of Pv Module Equivalent Parameters: Application To A Stand-Alone Pv System With Mppt Controller, Ahmet Afşi̇n Kulaksiz

Turkish Journal of Electrical Engineering and Computer Sciences

The performance and system cost of photovoltaic (PV) systems can be improved by employing high-efficiency power conditioners with maximum power point tracking (MPPT) methods. Fast implementation and accurate operation of MPPT controllers can be realized by modeling the characteristics of PV modules, obtaining equivalent parameters. In this study, adaptive neuro-fuzzy inference systems (ANFISs) have been used to obtain 3 of the parameters in a single-diode model of PV cells, namely series resistance, shunt resistance, and diode ideality factor. The input parameters of ANFISs are a material-type of PV modules, short circuit current, open circuit voltage, and unit area under the …

Adaptive Control Of A Time-Varying Rotary Servo System Using A Fuzzy Model Reference Learning Controller With Variable Adaptation Gain, Ömer Aydoğdu, Özdemi̇r Alkan

Turkish Journal of Electrical Engineering and Computer Sciences

The constant parameters in a conventional fuzzy controller lead to a poor performance for time-varying systems. In this study, a fuzzy model reference learning controller (FMRLC) with a newly defined variable adaptation gain is designed and implemented in the adaptive fuzzy control of a time-varying rotary servo (TVRS) system. In the design of the FMRLC, a knowledge-base modification algorithm with variable adaptation gain is used instead of a fuzzy relation table. Hence, it is provided that the learning and adaptation mechanism continuously updates the knowledge base of the adaptive fuzzy controller against any parameter variations, such as changing loads. By …

Optimized Operation And Maintenance Costs To Improve System Reliability By Decreasing The Failure Rate Of Distribution Lines, Hamed Hashemi Dezaki, Seyed Hossein Hosseinian, Hossein Askarian Abyaneh, Seyed Mohammad Mousavi Agah

Turkish Journal of Electrical Engineering and Computer Sciences

Improving distribution system reliability has received a great deal of attention in recent years. Because of the limitation in expected budgets, it is desirable to determine the most efficient strategy to improve system reliability. This paper proposes a novel method to determine the optimized operation and maintenance costs in order to decrease the failure of system components. The proposed objective function includes the average system frequency interruption index (ASIFI) value. To achieve the best strategy to decrease failures of system components, it is necessary to find the minimum value of the objective function, considering the constraints of operation and maintenance …

Design Of Information Retrieval Experiments: The Sufficient Topic Set Size For Providing An Adequate Level Of Confidence, Beki̇r Taner Di̇nçer

Turkish Journal of Electrical Engineering and Computer Sciences

In the current design of information retrieval (IR) experiments, a sample of 50 topics is generally agreed to be sufficient in size to perform dependable system evaluations. This article presents the detailed and formal explanation of how the second fundamental theorem of probability, the central limit theorem, can be used for the estimation of the sufficient size of a topic sample. The research performed in this article, using past Text Retrieval Conference data, reveals that, on average, 50 topics will be sufficient to provide a confidence level at or above 95% if the null hypothesis of an equal population mean …

Compact Microstrip Antenna With Metamaterial For Wideband Applications, Han Xiong, Jing-Song Hong, Ming-Tao Tan, Bing Li

Turkish Journal of Electrical Engineering and Computer Sciences

An improved metamaterial antenna, with a compact size of 27.8 x 31.9 x 0.794 mm^3, fed by an offset-microstrip line, is proposed. The total size is slightly reduced and the measured impedance bandwidth is 4.08-7.83 GHz for a return loss of \mid S_{11}\mid < -10 dB. Compared with the original patch antenna, the bandwidth of the proposed antenna is 550 MHz broader and has a lower resonant frequency. The simulated gain of the antenna is more than 2 dB, with a peak of about 6 dB at 6.8 GHz. Moreover, the antenna has strong radiation in the horizontal direction for some specific applications within the entire band.

A Novel Dynamic Bandwidth Selection Method For Thinning Noisy Point Clouds, Mehmet Öztürk, Zeynep Hasirci

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we propose a dynamic bandwidth selection method for thinning noisy point clouds into curves. Due to the nonhomogeneous distribution of noise or varying curvature of the data, the thinning procedure requires a dynamically adjusted bandwidth along the curve. On the other hand, the selected local region must be sorted along a suitable direction vector for local curve fitting purposes. The contribution of this paper to the field is 2-folded: first, a normalized eigenvalue analysis-based method is used to determine the best local bandwidth. The second task is getting a good regression line of the local region for …

Optimal Placement And Sizing Of Distributed Generations In Distribution Systems For Minimizing Losses And Thd_V Using Evolutionary Programming, Aida Fazliana Abdul Kadir, Azah Mohamed, Hussain Shareef, Mohd Zamri Che Wanik

Turkish Journal of Electrical Engineering and Computer Sciences

Growing concerns over environmental impacts, improvement of the overall network conditions, and rebate programs offered by governments have led to an increase in the number of distributed generation (DG) units in commercial and domestic electric power production. However, a large number of DG units in a distribution system may sometimes contribute to high levels of harmonic distortion, even though the emission levels of the individual DG units comply with the harmonic standards. It is known that the nonoptimal size and nonoptimal placement of DG units may lead to high power losses, bad voltage profiles, and harmonic propagations. Therefore, this paper …

Multi-Objective Weighted Sum Approach Model Reduction By Routh-Pade Approximation Using Harmony Search, Hasan Nasiri Soloklo, Malihe Maghfoori Farsangi

Turkish Journal of Electrical Engineering and Computer Sciences

A new weighted-sum multiobjective approach is investigated for order reduction based on Routh--Padé approximation, in which the harmony search algorithm is used to optimize the reduced-order model's parameters. In this method, apart from minimizing the errors between a set of subsequent time moments/Markov parameters of the system and those of the model, the error between the singular values of the reduced-order system and those of the original system is minimized. The Routh criterion is applied for specifying the stability conditions. The stability condition is then considered as a constraint in the optimization problem. To present the ability of the proposed …

Ssr Mitigation With Sssc Thanks To Fuzzy Control, Seyed Mohammad Hassan Hosseini, Hadi Samadzadeh, Javad Olamaei, Murtaza Farsadi

Turkish Journal of Electrical Engineering and Computer Sciences

This paper deals with the capability of a static synchronous series compensator (SSSC) to attenuate the subsynchronous resonance (SSR). Two well-known controllers are designed, namely a conventional damping controller (CDC) and fuzzy logic damping controller (FLDC). These 2 damping controllers are added to a main control loop of a SSSC operating as a SSR damping controller. It should be noted that, to optimize the parameters of the CDC, a versatile optimization technique is implemented, namely particle swarm optimization (PSO). A comprehensive comparison between the 2 control methods is carried out for different operational conditions. To observe the superior performance of …

Minimal Controller Synthesis Algorithms With Output Feedback And Their Generalization, Ata Sevi̇nç

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes several improvements in the minimal controller synthesis algorithms, which were developed for a class of nonlinear systems with uncertainties. The major proposition is that only the output feedback is enough to control some nonlinear systems without an observer while the existing algorithms require the complete state feedback. Next, the extended version and the parameter identification technique of the minimal controller synthesis algorithm are combined in a single method estimating some more parameters for some known forms of nonlinearities. This is applicable with or without the improvement of removing the need for using the complete state feedback. It …

Negative Selection Algorithm For Dengue Outbreak Detection, Maryam Mousavi, Azuraliza Abu Bakar, Suhaila Zainudin, Zalizah Awang Long, Mazrura Sahani, Mohammadmahdi Vakilian

Turkish Journal of Electrical Engineering and Computer Sciences

Dengue is a critical communicable and vector-borne disease and is becoming a serious concern in Malaysia. It is important to have an early detection system that could provide immediate action, such as the control of dengue transmission at a specific location. However, the available strategy and action may give long-term effects to the community since inaccurate decision making or prediction may lead to other circumstances. Moreover, the need to have a system that can detect the outbreak in a reasonable amount of time is critical. In this study, a nature-inspired computing technique, the artificial immune system (AIS), is used for …

A Video-Based Eye Pupil Detection System For Diagnosing Bipolar Disorder, Gökay Akinci, Edi̇z Polat, Orhan Murat Koçak

Turkish Journal of Electrical Engineering and Computer Sciences

Eye pupil detection systems have become increasingly popular in image processing and computer vision applications in medical systems. In this study, a video-based eye pupil detection system is developed for diagnosing bipolar disorder. Bipolar disorder is a condition in which people experience changes in cognitive processes and abilities, including reduced attentional and executive capabilities and impaired memory. In order to detect these abnormal behaviors, a number of neuropsychological tests are also designed to measure attentional and executive abilities. The system acquires the position and radius information of eye pupils in video sequences using an active contour snake model with an …

A Flexible Rule-Based Framework For Pilot Performance Analysis In Air Combat Simulation Systems, Ömer Faruk Arar, Kürşat Ayan

Turkish Journal of Electrical Engineering and Computer Sciences

Air combat simulation systems (ACSSs) are developed to train fighter pilots (trainees) in a virtual combat environment. In general, an ACSS consists of the following stages: planning the scenario, training, flight analysis, and performance evaluation. In this paper, the details of the framework, which is developed to analyze and evaluate the performance of the trainees, is introduced. First, the evaluation criteria for the pilot performance are defined. Next, a dynamic pilot performance evaluation system is developed that can be controlled and modified by experienced instructor pilots (instructors/trainers) to define the performance criteria details using predefined evaluation parameters. The evaluation of …

Online State Of Charge And Electrical Impedance Estimation For Multicell Lithium-Ion Batteries, Taesic Kim, Wei Qiao, Liyan Qu

Department of Electrical and Computer Engineering: Faculty Publications

This paper proposes a hybrid battery model-based high-fidelity state of charge (SOC) and electrical impedance estimation method for multicell lithium-ion batteries. The hybrid battery model consists of an enhanced Coulomb counting algorithm for SOC estimation and an electrical circuit battery model. A particle swarm optimization (PSO)-based online parameter identification algorithm is designed to estimate the electrical parameters of the cells sequentially. An SOC compensator is designed to correct the errors of the enhanced Coulomb counting SOC estimations for the cells sequentially. This leads to an accurate, robust online SOC estimation for individual cells of a battery pack. The proposed method …

Thin 3d Multiplication Regions In Plasmonically Enhanced Nanopillar Avalanche Detectors, Pradeep Senanayake, Chung-Hong Hung, Alan C. Farrell, David A. Ramirez, Joshua Shapiro, Chi-Kang Li, Yuh-Renn Wu, Majeed M. Hayat, Diana L. Huffaker

Electrical and Computer Engineering Faculty Research and Publications

We demonstrate a nanopillar (NP) device structure for implementing plasmonically enhanced avalanche photodetector arrays with thin avalanche volumes (∼ 310 nm × 150 nm × 150 nm). A localized 3D electric field due to a core–shell PN junction in a NP acts as a multiplication region, while efficient light absorption takes place via surface plasmon polariton Bloch wave (SPP-BW) modes due to a self-aligned metal nanohole lattice. Avalanche gains of ∼216 at 730 nm at −12 V are obtained. We show through capacitance–voltage characterization, temperature-dependent breakdown measurements, and detailed device modeling that the avalanche region is on the order of …

Hardware Implementation Of Processor Allocator For Mesh Connected Chip Multiprocessors, Rana Sangram Reddy Marri

UNLV Theses, Dissertations, Professional Papers, and Capstones

The advancements in the semiconductor process technology and the current demand for highly parallel computing has led to the advent of Chip Multiprocessors (CMPs). CMP is the integration of two or more independent processor cores, which can read and execute program instructions, on to a single integrated circuit die. CMPs are the main computing platforms for research and development in parallel and high performance computing environments. They offer minimum inter-core communication latencies as the processor cores are present on a single chip.

The Operating System (OS) plays a key role in using a CMP effectively. The OS should support a …

Image Segmentation For Quantification Of Air-Water Interface In Micro-Ct Soil Images, Kranthi Kumar Potteti

UNLV Theses, Dissertations, Professional Papers, and Capstones

Soils are complex environments comprising various biological (roots, water, air etc) and physical constituents (minerals, aggregates, etc). Synchrotron radiation based X-ray microtomography (XMT) is widely used in extracting qualitative and quantitative information regarding spatial distribution of biological and physical soil constituents. Segmentation of these micro-CT soil images is of interest to geologists, hydrologists, civil and petroleum engineers and soil scientists. In this present work, we study and implement segmentation algorithms for microhydrology studies, specifically for soil water conductivity. Three well-known image segmentation algorithms are studied for evaluating their performance for the task. We demonstrate the problems and ways to segment …