High-Performance Cmos Cci In A 0.35 \Mu M Cmos Technology And A New All-Pass Filter Application,
2013
TÜBİTAK
High-Performance Cmos Cci In A 0.35 \Mu M Cmos Technology And A New All-Pass Filter Application, Emre Arslan, Bi̇lgi̇n Meti̇n, Mehmet Oğuzhan Çi̇çekoğlu, Avni̇ Morgül
Turkish Journal of Electrical Engineering and Computer Sciences
A differential pair-based, high-performance, first-generation current conveyor is proposed. The proposed circuit is laid out using the Mentor Graphics IC Station layout editor. The performance characteristics have been determined from HSpice postlayout simulations using the Austria Mikro Systeme 0.35 \mu m, 3.3 V process parameters. During the simulations, \pm 1.65 V supply voltages and a 25 \mu A biasing current are used. The power consumption is about 1.12 mW. The circuit also has very high voltage swings on ports X and Y, a very small impedance value on port X, high impedance values on ports Y and Z, and high-valued …
A New Extension Of Activity Networks For Modeling And Verification Of Timed Systems,
2013
TÜBİTAK
A New Extension Of Activity Networks For Modeling And Verification Of Timed Systems, Hassan Motallebi, Mohammad Abdollahi Azgomi, Mohammad Saber Mirzaei, Ali Movaghar
Turkish Journal of Electrical Engineering and Computer Sciences
Stochastic activity networks (SANs) are a well-known petri net-based formalism used for the performance and dependability modeling of a wide range of systems. On the other hand, the growing complexity of timed systems makes it imperative to apply formal analysis techniques in the early stages of the system's development. Finding a suitable framework for the modeling, evaluation, and verification of these systems is still a great challenge. In this paper, we introduce a new formalism named timed activity networks (TANs), which are based on the activity networks that are the nondeterministic settings of the SANs. The advantages of TANs are …
Outlier Rejection Fuzzy C-Means (Orfcm) Algorithm For Image Segmentation,
2013
TÜBİTAK
Outlier Rejection Fuzzy C-Means (Orfcm) Algorithm For Image Segmentation, Fasahat Ullah Siddiqui, Nor Ashidi Mat Isa, Abid Yahya
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a fuzzy clustering-based technique for image segmentation. Many attempts have been put into practice to increase the conventional fuzzy c-means (FCM) performance. In this paper, the sensitivity of the soft membership function of the FCM algorithm to the outlier is considered and the new exponent operator on the Euclidean distance is implemented in the membership function to improve the outlier rejection characteristics of the FCM. The comparative quantitative and qualitative studies are performed among the conventional k-means (KM), moving KM, and FCM algorithms; the latest state-of-the-art clustering algorithms, namely the adaptive fuzzy moving KM , adaptive fuzzy …
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,
2013
TÜBİTAK
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,
2013
TÜBİTAK
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,
2013
TÜBİTAK
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 …
Multireference Tdoa-Based Source Localization,
2013
TÜBİTAK
Multireference Tdoa-Based Source Localization, Hamid Torbati Fard, Mahmoud Atashbar, Yaser Norouzi, Farrokh Hojjat Kashani
Turkish Journal of Electrical Engineering and Computer Sciences
Time difference of arrival (TDOA)-based methods usually achieve the most accurate source localization in passive systems. In these methods, one of the sensors is assigned as the reference and the TDOA of the others with respect to the reference is measured. The source location is estimated by processing these TDOAs. In this paper, a multireference maximum likelihood (ML)-Taylor algorithm is proposed in order to decrease the source localization error of the TDOA methods. In the proposed algorithm, TDOAs are measured assuming 2 different reference sensors, and then the ML objective function of this multireference TDOA algorithm is derived and solved …
Simulation Of Discrete Electromagnetic Propagation Model For Atmospheric Effects On Mobile Communication,
2013
TÜBİTAK
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,
2013
TÜBİTAK
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. …
A 5-Bit 5 Gs/S Flash Adc Using Multiplexer-Based Decoder,
2013
TÜBİTAK
A 5-Bit 5 Gs/S Flash Adc Using Multiplexer-Based Decoder, Oktay Aytar, Ali̇ Tangel, Kudret Şahi̇n
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a 5-bit flash analog-to-digital converter design using the 0.18-\mu m Taiwan Semiconductor Manufacturing Company's CMOS technology library. The designed system consists of 2 main blocks, a comparator array, and a digital decoder. The digital decoder contains a latch, 1-of-N decoder, and fat-tree encoder units. The 1-of-N decoder is implemented using 2 \times 1 multiplexers. As a result, the active die area and the power consumption are reduced, in addition to an increase in the sampling frequency. The power supply voltage range for the overall system is \pm 0.9 V. For testing purposes, a ramp signal of between …
Comparison Of Speech Parameterization Techniques For The Classification Of Speech Disfluencies,
2013
TÜBİTAK
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,
2013
TÜBİTAK
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,
2013
TÜBİTAK
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,
2013
TÜBİTAK
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,
2013
TÜBİTAK
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,
2013
TÜBİTAK
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 …
