Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Classification (66)
- Deep learning (61)
- Machine learning (60)
- Optimization (60)
- Genetic algorithm (57)
-
- Particle swarm optimization (49)
- Artificial neural network (34)
- Support vector machine (34)
- Feature extraction (32)
- Wireless sensor networks (31)
- Feature selection (28)
- Power quality (27)
- Artificial neural networks (26)
- Fuzzy logic (26)
- Distributed generation (25)
- Induction motor (24)
- Clustering (21)
- Convolutional neural network (20)
- Support vector machines (20)
- Convolutional neural networks (19)
- Image processing (18)
- Neural networks (18)
- Energy efficiency (17)
- Neural network (17)
- Reliability (17)
- Sliding mode control (17)
- Electric vehicle (16)
- Natural language processing (16)
- Renewable energy (16)
- Artificial bee colony (15)
Articles 1081 - 1110 of 3020
Full-Text Articles in Physical Sciences and Mathematics
Volumetric 3d Reconstruction Of Real Objects Using Voxel Mapping Approach In A Multiple-Camera Environment, Tushar Jadhav, Kulbir Singh, Aditya Abhyankar
Volumetric 3d Reconstruction Of Real Objects Using Voxel Mapping Approach In A Multiple-Camera Environment, Tushar Jadhav, Kulbir Singh, Aditya Abhyankar
Turkish Journal of Electrical Engineering and Computer Sciences
Extracting 3D information from 2D images is an inverse estimation problem and a challenging task in itself. The aim of 2D to 3D reconstruction is to generate either a volume or a surface representing the object from multiple views. This paper presents a simple and accurate multiple-view volumetric 3D reconstruction method using an integrated approach based on homography estimation and voxel mapping. The homography-based approaches give accurate estimates but do not provide system dynamics. The voxel-based volumetric reconstruction methods provide system dynamics that are essential for system modeling. However, they face challenges while modeling the concavities. This paper presents a …
Schedulability Test For Ima Systems Based On Mixed Integer Linear Programming Formulation, Yukai Hao, Ming Mu, Xiaodi Dai, Xiangdong Li
Schedulability Test For Ima Systems Based On Mixed Integer Linear Programming Formulation, Yukai Hao, Ming Mu, Xiaodi Dai, Xiangdong Li
Turkish Journal of Electrical Engineering and Computer Sciences
Integrated modular avionics (IMA) architecture is widely adopted for the design of modern aircraft. It simplifies the system development process and improves the system security and reliability. In IMA systems, avionics applications are packed into various partitions, and integrated into a standard computing platform. How to determine the schedulability of systems is one of the key problems. In this paper, using the characters of avionics systems, a partition model with a strict period is built, and constraints in space, time, and communication are analyzed. Based on the mixed integer linear programming formulation, a solution to determine the schedulability of IMA …
Data Clustering Using Ede, An Enhanced Differential Evolution Algorithm With Fuzzy C-Means Technique, Meera Ramadas, Ajith Abraham
Data Clustering Using Ede, An Enhanced Differential Evolution Algorithm With Fuzzy C-Means Technique, Meera Ramadas, Ajith Abraham
Turkish Journal of Electrical Engineering and Computer Sciences
Clustering is the way toward sorting out items into groups whose individuals are comparative somehow. It is a gathering of articles that are intelligent inside, yet unmistakably not at all like the items having a place with different groups. Clustering of data plays a major part in efficient customer segmentation, organization of documents, information retrieval, extraction of topics, classification, collaborative filtering, visualization, and indexing. In the area of information retrieval systems, evolutionary algorithms work in a robust and efficient manner for clustering. To overcome the problem of local maxima, various nature-inspired metaheuristic algorithms like particle swarm optimization, artificial bee colony, …
Investigation On Optimal Parameter Selection For Llc Half-Bridge Resonant Converter Based On Fha, Jianguang Ma, Xueye Wei, Liang Hu, Wenting Jia
Investigation On Optimal Parameter Selection For Llc Half-Bridge Resonant Converter Based On Fha, Jianguang Ma, Xueye Wei, Liang Hu, Wenting Jia
Turkish Journal of Electrical Engineering and Computer Sciences
The LLC half-bridge resonant converter has attracted extensive research attention due to its advantages of achieving high efficiency and high power density. However, the resonant process is more complicated, where the main difficulty is to precisely calculate resonant parameters. In this paper, the fundamental harmonic approximation (FHA) method is employed to analyze the resonant process of the converter. In particular, the working mode and the mathematical model of the LLC half-bridge resonant converter are established, where a new method is proposed to determine the operating frequency of LLC based on voltage gain and transformer loss. Based on the proposed method, …
Ab Initio Study Of The Structural, Electronic, And Magnetic Properties Of Co$_{2}$Fega And Co$_{2}$Fesi And Their Future Contribution To The Building Of Quantum Devices, Abdallah Oumsalem, Yamina Bourezig, Zakia Nabi, Badra Bouabdallah
Ab Initio Study Of The Structural, Electronic, And Magnetic Properties Of Co$_{2}$Fega And Co$_{2}$Fesi And Their Future Contribution To The Building Of Quantum Devices, Abdallah Oumsalem, Yamina Bourezig, Zakia Nabi, Badra Bouabdallah
Turkish Journal of Electrical Engineering and Computer Sciences
How small can an electronic device be and still function? How many atoms are needed for such device? At what point will the semiconductor fabrication technology be unable to construct anything smaller? These are common questions asked by researchers, and the answers indicate the short-term limitations on the use of semiconductor technology. When we reach these limitations, we can propose two methods to solve these problems: first, we could continue using semiconductor technology, alongside the development of new theories and techniques to counter quantum effects caused by the miniaturization of electronic devices like transistors and microprocessors. Second, we could exploit …
Digital Image Copy-Move Forgery Detection Based On Discrete Fractional Wavelet Transform, Amanjot Kaur Lamba, Neeru Jindal, Sanjay Sharma
Digital Image Copy-Move Forgery Detection Based On Discrete Fractional Wavelet Transform, Amanjot Kaur Lamba, Neeru Jindal, Sanjay Sharma
Turkish Journal of Electrical Engineering and Computer Sciences
With the advancement of sophisticated cameras and image editing software tools, digital image tampering techniques are frequently used without leaving visual cues behind. Digital image copy-move forgery is a kind of image manipulation that involves copying and pasting of a certain section (or sections) within the same digital image. Generally, this is done with false intentions of hiding important information or providing false information in an image. In view of this, the focus of the present paper is to propose a discrete fractional wavelet transform-based scheme for identification of duplicated regions in the image. The test image is split into …
Topological Feature Extraction Of Nonlinear Signals And Trajectories And Its Application In Eeg Signals Classification, Saleh Lashkari, Ali Sheikhani, Mohammad Reza Hashemi Golpayegani, Ali Moghimi, Hamid Reza Kobravi
Topological Feature Extraction Of Nonlinear Signals And Trajectories And Its Application In Eeg Signals Classification, Saleh Lashkari, Ali Sheikhani, Mohammad Reza Hashemi Golpayegani, Ali Moghimi, Hamid Reza Kobravi
Turkish Journal of Electrical Engineering and Computer Sciences
This study introduces seven topological features that characterize attractor dynamic of nonlinear and chaotic trajectories in a phase space. These features quantify volume, occupied space, nonuniformity, and curvature of trajectory. The features are evaluated as initial point invariant measures by a practical approach, which means that a feature is only sensitive to dynamic changes. The Lorenz and Rossler system trajectories are employed in this evaluation. Moreover, the proposed features are used in a real world application, i.e. epileptic seizure electroencephalogram signal classification. As the result shows, these features are efficient in this task in comparison with others studies that used …
Frequency Equivalent Circuits For The On And Off State Of An Optically Triggered Switch Based On A Pin Photodiode, Ivan Olaf Hernandez-Fuentes, Carlos Villa-Angulo, Jose Manuel Ramirez-Zarate, Raul Rascon-Carmona, Rosa Citalli Anguiano-Cota
Frequency Equivalent Circuits For The On And Off State Of An Optically Triggered Switch Based On A Pin Photodiode, Ivan Olaf Hernandez-Fuentes, Carlos Villa-Angulo, Jose Manuel Ramirez-Zarate, Raul Rascon-Carmona, Rosa Citalli Anguiano-Cota
Turkish Journal of Electrical Engineering and Computer Sciences
In this work we have developed equivalent circuit models for the frequency response of an optically triggered switch based on a positive-intrinsic-negative photodiode (PIN-PD) for the On state (light applied to the PIN-PD) and the Off state (without applying light to the PIN-PD). From measurements it was found the frequency response in Off state behaves as a high-pass filter whereas in the On state as a low-pass filter; this means that depending on the input signal frequency there could be an approach or even an overlap between the output amplitude in the On and in the Off state. The developed …
Probabilistic Dynamic Security Assessment Of Large Power Systems Using Machine Learning Algorithms, Sevda Jafarzadeh, Veysel Murat İstemi̇han Genç
Probabilistic Dynamic Security Assessment Of Large Power Systems Using Machine Learning Algorithms, Sevda Jafarzadeh, Veysel Murat İstemi̇han Genç
Turkish Journal of Electrical Engineering and Computer Sciences
Arrhythmia, also known as dysrhythmia, is a condition involving an irregular heartbeat. A problem in the heart may cause problems in other organs, and as time passes, this will lead to more severe problems. Arrhythmia must be detected at an early stage to prevent such a problem occurring in the heart. Detection of arrhythmia from an electrocardiogram is an easy method that does not need much equipment and does not harm the patient. The purpose of this research is to find a faster and more accurate system to classify nine classes of arrhythmia. The St. Petersburg Institute of Cardiological Technics …
Conception And Control Of A Wtgs System Using A Novel Control Technique Based On Mpc-Dpc-Mvf With A Switch Optimization Process, Mansour Madaci, Djallel Kerdoun
Conception And Control Of A Wtgs System Using A Novel Control Technique Based On Mpc-Dpc-Mvf With A Switch Optimization Process, Mansour Madaci, Djallel Kerdoun
Turkish Journal of Electrical Engineering and Computer Sciences
The work proposed through this paper presents a novel technique applied for the control of a wind turbine generation system (WTGS) prototype. A model predictive control combined with a direct power control technique (MPC-DPC) based on SVM control and a novel switching cycle sequence pattern for thermal switch losses reduction have been adopted. The novel developed direct power control (DPC) scheme based on a multivariable filter (MVF) topology for power estimation process has been illustrated. The control of the converter system is adopted through a predictive control strategy to achieve a complete and an instantaneous control over the active and …
Performance Analysis Of Radial And Axial Flux Pmsm Based On 3d Fem Modeling, Oussama Bouaziz, Imen Jaafar, Faouzi Ben Ammar
Performance Analysis Of Radial And Axial Flux Pmsm Based On 3d Fem Modeling, Oussama Bouaziz, Imen Jaafar, Faouzi Ben Ammar
Turkish Journal of Electrical Engineering and Computer Sciences
The objective of this paper is presenting a comparative performance analysis between axial flux and radial flux permanent magnet synchronous machines (PMSMs) dedicated to a 550-W wind turbine application. The outer diameter is fixed for both structures and the modeling is carried out in 3D by means of the finite element method (FEM) using the Multiphysics program ANSYS. The performances of the axial flux and radial flux machines for the same output power and at the same rotor speed are evaluated by comparing their efficiency regarding the material consumption of the active parts and eventually predicting their costs. The obtained …
Implementing Universal Dependency, Morphology, And Multiword Expression Annotation Standards For Turkish Language Processing, Umut Sulubacak, Gülşen Eryi̇ği̇t
Implementing Universal Dependency, Morphology, And Multiword Expression Annotation Standards For Turkish Language Processing, Umut Sulubacak, Gülşen Eryi̇ği̇t
Turkish Journal of Electrical Engineering and Computer Sciences
Released only a year ago as the outputs of a research project (``Parsing Web 2.0 Sentences'', supported in part by a TÜBİTAK 1001 grant (No. 112E276) and a part of the ICT COST Action PARSEME (IC1207)), IMST and IWT are currently the most comprehensive Turkish dependency treebanks in the literature. This article introduces the final states of our treebanks, as well as a newly integrated hierarchical categorization of the multiheaded dependencies and their organization in an exclusive deep dependency layer in the treebanks. It also presents the adaptation of recent studies on standardizing multiword expression and named entity annotation schemes …
Forecasting The Baltic Dry Index By Using An Artificial Neural Network Approach, Beki̇r Şahi̇n, Samet Gürgen, Bedi̇r Ünver, İsmai̇l Altin
Forecasting The Baltic Dry Index By Using An Artificial Neural Network Approach, Beki̇r Şahi̇n, Samet Gürgen, Bedi̇r Ünver, İsmai̇l Altin
Turkish Journal of Electrical Engineering and Computer Sciences
The Baltic Dry Index (BDI) is a robust indicator in the shipping sector in terms of global economic activities, future world trade, transport capacity, freight rates, ship demand, ship orders, etc. It is hard to forecast the BDI because of its high volatility and complexity. This paper proposes an artificial neural network (ANN) approach for BDI forecasting. Data from January 2010 to December 2016 are used to forecast the BDI. Three different ANN models are developed: (i) the past weekly observation of the BDI, (ii) the past two weekly observations of the BDI, and (iii) the past weekly observation of …
Optimum, Projected, And Regularized Extreme Learning Machine Methods With Singular Value Decomposition And L$_{2}$-Tikhonov Regularization, Mohanad Abd Shehab, Ni̇han Kahraman
Optimum, Projected, And Regularized Extreme Learning Machine Methods With Singular Value Decomposition And L$_{2}$-Tikhonov Regularization, Mohanad Abd Shehab, Ni̇han Kahraman
Turkish Journal of Electrical Engineering and Computer Sciences
The theory and implementation of an extreme learning machine (ELM) have proved that it is a simple, efficient, and accurate machine learning methodology. In an ELM, the hidden nodes are randomly initiated and fixed without iterative tuning. However, the optimal hidden layer neuron number ($L_{opt})$ is the key to ELM generalization performance where initializing this number by trial and error is not reasonably satisfied. Optimizing the hidden layer size using the leave-one-out cross validation method is a costly approach. In this paper, a fast and reliable statistical approach called optimum ELM (OELM) was developed to determine the minimum hidden layer …
Solving A Combined Economic Emission Dispatch Problem Using Adaptive Wind Driven Optimization, Milena Jevtic, Nenad Jovanovic, Jordan Radosavljevic
Solving A Combined Economic Emission Dispatch Problem Using Adaptive Wind Driven Optimization, Milena Jevtic, Nenad Jovanovic, Jordan Radosavljevic
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, the adaptive wind driven optimization (AWDO) algorithm is applied for solving the combined economic emission dispatch (CEED) problem. AWDO is one of the newest hybrid algorithms, which optimizes the selection of coefficients at each iteration, eliminating the need for tuning the coefficients. The evaluation of AWDO performances is carried out on the standard IEEE 30-bus test system with 6 generating units and with various cost curve natures. The results of AWDO use with the test system are compared against the results of use of 3 algorithms: the moth swarm algorithm, firefly algorithm, and hybrid particle swarm optimization …
Threshold-Based Distributed Ddos Attack Detection In Isp Networks, Karanbir Singh, Kanwalvir Singh Dhindsa, Bharat Bhushan
Threshold-Based Distributed Ddos Attack Detection In Isp Networks, Karanbir Singh, Kanwalvir Singh Dhindsa, Bharat Bhushan
Turkish Journal of Electrical Engineering and Computer Sciences
The purpose of this paper is to propose a more efficient and accurate distributed denial of service (DDoS) attack detection mechanism that detects DDoS attacks by monitoring the incoming traffic on the edge routers of ISP networks. It can be implemented as a module or agent function on the machine that is responsible for processing router traffic. The detection algorithm works by monitoring the traffic passing through the edge routers and identifying the occurrence of DDoS attacks or flash events. The algorithm calculates different values like the normalized router entropy, packet rate, and entropy rate and compares them against the …
Lorenz-Like System Design Using Cellular Neural Networks, Eni̇s Günay, Kenan Altun
Lorenz-Like System Design Using Cellular Neural Networks, Eni̇s Günay, Kenan Altun
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, a Lorenz-like system based on cellular neural networks (CNNs) is proposed. Complex butterfly chaotic attractors of Lorenz-like systems are constructed using a three-cell CNN. The proposed system makes the CNN imitate quadratic system dynamics without altering its output nonlinearity. Experimental and numerical analysis results are presented in order to verify the convenience of the system.
Hardware Implementation And Comparison Of Displacement Retrieval Algorithms For A Laser Diode-Based Optical Feedback Interferometric Sensor, Ghazi Rehman, Usman Zabit, Muhammad Obaid Ullah
Hardware Implementation And Comparison Of Displacement Retrieval Algorithms For A Laser Diode-Based Optical Feedback Interferometric Sensor, Ghazi Rehman, Usman Zabit, Muhammad Obaid Ullah
Turkish Journal of Electrical Engineering and Computer Sciences
Optical feedback interferometer (OFI) lasers, also called self-mixing (SM) lasers, have been widely explored over the last couple of decades due to their low cost, compactness, and self-aligned nature and they provide a very good solution for measurements of displacement, vibration, distance, velocity, etc. The SM effect takes place when a part of the laser beam is fed back to the active laser cavity after reflecting from the target. The reflected beam interferes with the emitted beam and hence the optical and spectral characteristics of the laser get changed. To retrieve the vibration or displacement signal of the target from …
Novel Modified Impedance-Based Methods For Fault Location In The Presence Of A Fault Current Limiter, Javad Barati, Aref Doroudi
Novel Modified Impedance-Based Methods For Fault Location In The Presence Of A Fault Current Limiter, Javad Barati, Aref Doroudi
Turkish Journal of Electrical Engineering and Computer Sciences
A fault current limiter (FCL) is promising novel electric equipment to effectively reduce excessive short circuit current in power networks. The presence of a FCL at the time of a fault occurrence makes it necessary to consider new settings for protective relays and fault locators. This paper examines the presence of a FCL in power networks and its effects on single-ended impedance-based fault location methods. It will be shown that FCL deployment in a transmission line makes the traditional fault location method inefficient. Two modified methods are presented to solve the problem. The modified methods locate the fault point using …
A Novel Efficient Tsv Built-In Test For Stacked 3d Ics, Badi Guibane, Belgacem Hamdi, Brahim Ben Salem, Abdellatif Mtibaa
A Novel Efficient Tsv Built-In Test For Stacked 3d Ics, Badi Guibane, Belgacem Hamdi, Brahim Ben Salem, Abdellatif Mtibaa
Turkish Journal of Electrical Engineering and Computer Sciences
A through-silicon via (TSV) is established as the main enabler for a three-dimensional integrated circuit (3D IC) that increases system density and compactness. The exponential increase in TSV density led to TSV-induced catastrophic and parametric faults. We propose an original architecture that detects errors caused by TSV manufacturing defects. The proposed design for testability is a built-in technique that detects errors in an early manufacturing stage and is hence very economically attractive. The proposal is capable of testing each and every TSV in the network. The technique achieves high fault coverage and high observability.
An Efficient Recurrent Fuzzy Cmac Model Based On A Dynamic-Group--Based Hybrid Evolutionary Algorithm For Identification And Prediction Applications, Chin-Ling Lee, Chengjian Lin
An Efficient Recurrent Fuzzy Cmac Model Based On A Dynamic-Group--Based Hybrid Evolutionary Algorithm For Identification And Prediction Applications, Chin-Ling Lee, Chengjian Lin
Turkish Journal of Electrical Engineering and Computer Sciences
This article presents an efficient TSK-type recurrent fuzzy cerebellar model articulation controller (T-RFCMAC) model based on a dynamic-group--based hybrid evolutionary algorithm (DGHEA) for solving identification and prediction problems. The proposed T-RFCMAC model is based on the traditional CMAC model and the Takagi--Sugeno--Kang (TSK) parametric fuzzy inference system. Otherwise, the recurrent network, which imports feedback links with a receptive field cell, is embedded in the T-RFCMAC model, and the feedback units are used as memory elements. The DGHEA, which is a hybrid of the dynamic-group quantum particle swarm optimization (QPSO) and the Nelder--Mead method, is proposed for adjusting the parameters of …
Real-Time Implementation Of Three-Level Inverter-Based D-Statcom Using Neuro-Fuzzy Controller, Resul Çöteli̇, Hakan Açikgöz, Beşi̇r Dandil, Servet Tuncer
Real-Time Implementation Of Three-Level Inverter-Based D-Statcom Using Neuro-Fuzzy Controller, Resul Çöteli̇, Hakan Açikgöz, Beşi̇r Dandil, Servet Tuncer
Turkish Journal of Electrical Engineering and Computer Sciences
A distribution static compensator (D-STATCOM) is a custom power device connected in parallel to a power system to address electric power quality problems caused by reactive power and harmonics. To obtain high performance from a D-STATCOM, the D-STATCOM's \textit{dq}-axis currents must be controlled in an internal control loop. However, control of the D-STATCOM's currents is difficult because of its nonlinear structure, cross-coupling effect between the \textit{d}- and \textit{q}-axis, undefined dynamics, and fast changing load. Therefore, the controller to be preferred for a D-STATCOM should have a nonlinear and robust structure. In this study, a neuro-fuzzy controller (NFC), which is a …
On The Power Handling Of A High Power Combiner For Industrial, Scientific, And Medical Applications, Arash Ahmadi
On The Power Handling Of A High Power Combiner For Industrial, Scientific, And Medical Applications, Arash Ahmadi
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper a 2-way broadband power combiner that can handle up to 1 kW output power is designed and fabricated. The combiner covers the frequency range of 30 to 500 MHz, which is intended for industrial, scientific, and medical (ISM) applications. The power handling of the power combiner depends on the power handling of the components that constitute the combiner. The combiner is composed of some coaxial transmission lines and a transmission line transformer. The ferrite cores, which are used to suppress the common mode current, are one of the major limiting factors, regarding the power handling of the …
Modified Acceleration Feedback For Practical Disturbance Rejection In Motor Drives, Ahmet Gürhanli
Modified Acceleration Feedback For Practical Disturbance Rejection In Motor Drives, Ahmet Gürhanli
Turkish Journal of Electrical Engineering and Computer Sciences
Acceleration feedback techniques have been used in control systems for a long time in order to improve the stiffness. Basically, the acceleration of the motor is calculated using speed or position measurements and the current command is adjusted using the acceleration data for avoiding deviations from the commanded speed. This method has to deal with two challenges. The first challenge is calculating the acceleration correctly. If it is calculated by double differentiation of position feedback of a servo motor, it may lead to a high amount of noise. On the other hand, if observer techniques are used, the error and …
Neuron Modeling: Estimating The Parameters Of A Neuron Model From Neural Spiking Data, Reşat Özgür Doruk
Neuron Modeling: Estimating The Parameters Of A Neuron Model From Neural Spiking Data, Reşat Özgür Doruk
Turkish Journal of Electrical Engineering and Computer Sciences
We present a modeling study aiming at the estimation of the parameters of a single neuron model from neural spiking data. The model receives a stimulus as input and provides the firing rate of the neuron as output. The neural spiking data will be obtained from point process simulation. The resultant data will be used in parameter estimation based on the inhomogeneous Poisson maximum likelihood method. The model will be stimulated by various forms of stimuli, which are modeled by a Fourier series (FS), exponential functions, and radial basis functions (RBFs). Tabulated results presenting cases with different sample sizes (# …
Method Of Singular Integral Equations In Diffraction By Semiinfinite Grating E-Polarization Case, Mstislav Kaliberda, Leonid Lytvynenko, Sergey Pogarsky
Method Of Singular Integral Equations In Diffraction By Semiinfinite Grating E-Polarization Case, Mstislav Kaliberda, Leonid Lytvynenko, Sergey Pogarsky
Turkish Journal of Electrical Engineering and Computer Sciences
Diffraction of the E-polarized electromagnetic wave by a semiinfinite strip grating is considered. The scattered field is represented as a superposition of the field induced by the currents on the strips of an infinite periodic grating and the field induced by the correction current excited due to end of the grating. A singular integral equation with additional conditions for correction current density is obtained. A solution for the infinite periodic grating in the E-polarization case is obtained from the corresponding solution for the H-polarization case using the duality principle. Numerical results for the current density and far fields distribution are …
Mn-Zn Ferrite Line Emi Suppressor For Power Switching Noise In The Impulse/High Current Bias Regime, Dragana Petrovic, Miroslav Lazic, Obrad Aleksic, Maria Nikolic, Vedran Ibrahimovic, Milan Pajnic
Mn-Zn Ferrite Line Emi Suppressor For Power Switching Noise In The Impulse/High Current Bias Regime, Dragana Petrovic, Miroslav Lazic, Obrad Aleksic, Maria Nikolic, Vedran Ibrahimovic, Milan Pajnic
Turkish Journal of Electrical Engineering and Computer Sciences
Ferrite cores 50 mm long were formed from large ferrite tubes obtained using fine Mn-Zn ferrite powder (M-30-IHIS) extruded and sintered at 1280 $^{\circ}$C for 2 h. Core impedance was measured in the HF range (0.1--100 MHz), varying the number of coil turns and DC bias. Characteristic parameters such as maximum of impedance Z$_m$, frequency of maximum impedance F$_m$, and suppressing range f around F$_m$ were determined for each configuration. The analyzed ferrite cores were tested as round cable suppressors in the impulse regime. Impulses were generated by MOSFET transistor switching of high currents (1--10 A). The number of turns, …
Design Of An On-Chip Hilbert Fractal Inductor Using An Improved Feed Forward Neural Network For Si Rfics, Akhendra Kumar Padavala, Bheema Rao Nistala
Design Of An On-Chip Hilbert Fractal Inductor Using An Improved Feed Forward Neural Network For Si Rfics, Akhendra Kumar Padavala, Bheema Rao Nistala
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents an efficient modeling of Hilbert fractal inductors by improved feed forward neural network trained hybrid particle swarm optimization and gravitational search algorithm (FNNPSOGSA). The proposed model computes the effective inductance value (L) and quality factor (Q) of Hilbert fractal inductors with metal trace width, effective fractal length, frequency, and oxide thickness as input parameters. In contrast to the traditional feed forward neural network, the proposed FNNPSOGSA has been designed with fewer hidden neurons with much-enhanced learning and generalization capabilities. As a consequence, the proposed model achieves better speed and is as accurate as electromagnetic simulations. From the …
Dynamic Cpu Scheduling For Load Balancing In Virtualized Environments, Suresh Chandra Moharana, Sibani Samal, Amulya Ratna Swain, Ganga Bishnu Mund
Dynamic Cpu Scheduling For Load Balancing In Virtualized Environments, Suresh Chandra Moharana, Sibani Samal, Amulya Ratna Swain, Ganga Bishnu Mund
Turkish Journal of Electrical Engineering and Computer Sciences
In the modern era of computing, the cloud computing platform became popular with its on-demand resource scalability feature. Virtualization is the key technology to achieve resource scalability in the cloud environment. Virtual machine monitors (VMMs) like Xen and KVM are the enabling tools for virtualizing the resources in the cloud environment. The major role of VMMs is to map virtual CPUs of virtual machines to physical CPUs, popularly known as CPU scheduling. In this study, we analyzed the CPU scheduler of Xen VMM, called Credit CPU scheduler, with respect to CPU utilization. In order to maximize the physical CPU utilization …
Multilabel Learning For The Online Transient Stability Assessment Of Electric Power Systems, Peyman Beyranvand, Veysel Murat İstemi̇han Genç, Zehra Çataltepe
Multilabel Learning For The Online Transient Stability Assessment Of Electric Power Systems, Peyman Beyranvand, Veysel Murat İstemi̇han Genç, Zehra Çataltepe
Turkish Journal of Electrical Engineering and Computer Sciences
Dynamic security assessment of a large power system operating over a wide range of conditions requires an intensive computation for evaluating the system's transient stability against a large number of contingencies. In this study, we investigate the application of multilabel learning for improving training and prediction time, along with the prediction accuracy, of neural networks for online transient stability assessment of power systems. We introduce a new multilabel learning method, which uses a contingency clustering step to learn similar contingencies together in the same multilabel multilayer perceptron. Experimental results on two different power systems demonstrate improved accuracy, as well as …