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Articles 511 - 540 of 3020
Full-Text Articles in Physical Sciences and Mathematics
Satire Identification In Turkish News Articles Based On Ensemble Of Classifiers, Aytuğ Onan, Mansur Alp Toçoğlu
Satire Identification In Turkish News Articles Based On Ensemble Of Classifiers, Aytuğ Onan, Mansur Alp Toçoğlu
Turkish Journal of Electrical Engineering and Computer Sciences
Social media and microblogging platforms generally contain elements of figurative and nonliteral language, including satire. The identification of figurative language is a fundamental task for sentiment analysis. It will not be possible to obtain sentiment analysis methods with high classification accuracy if elements of figurative language have not been properly identified. Satirical text is a kind of figurative language, in which irony and humor have been utilized to ridicule or criticize an event or entity. Satirical news is a pervasive issue on social media platforms, which can be deceptive and harmful. This paper presents an ensemble scheme for satirical news …
Convolutional Auto Encoders For Sentence Representation Generation, Ali̇ Mert Ceylan, Vecdi̇ Aytaç
Convolutional Auto Encoders For Sentence Representation Generation, Ali̇ Mert Ceylan, Vecdi̇ Aytaç
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, we have proposed an alternative approach for sentence modeling problem. The difficulty of the choice of answer, the semantically related questions and the lack of syntactic closeness of the answers give rise to the difficulty of selecting the answer. The deep learning field has recently achieved a pivotal success in semantic analysis, machine translation, and text summaries. The essence of this work, inspired by the human orthographic processing mechanism and using multiple convolution filters with pre-rendered 2-Dimension (2D) representations of sentences, input or output size is to learn the basic features of the language without concerns. For …
Crash Course Learning: An Automated Approach To Simulation-Driven Lidar-Basedtraining Of Neural Networks For Obstacle Avoidance In Mobile Robotics, Stanko Kruzic, Josip Music, Mirjana Bonkovic, Frantisek Duchon
Crash Course Learning: An Automated Approach To Simulation-Driven Lidar-Basedtraining Of Neural Networks For Obstacle Avoidance In Mobile Robotics, Stanko Kruzic, Josip Music, Mirjana Bonkovic, Frantisek Duchon
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes and implements a self-supervised simulation-driven approach to data collection used for training of perception-based shallow neural networks for mobile robot obstacle avoidance. In the approach, a 2D LiDAR sensor was used as an information source for training neural networks. The paper analyzes neural network performance in terms of numbers of layers and neurons, as well as the amount of data needed for reliable robot operation. Once the best architecture is identified, it is trained using only data obtained in simulation and then implemented and tested on a real robot (Turtlebot 2) in several simulations and real-world scenarios. …
Measurement Based Threat Aware Drone Base Station Deployment, Alper Akarsu, Tolga Gi̇ri̇ci̇
Measurement Based Threat Aware Drone Base Station Deployment, Alper Akarsu, Tolga Gi̇ri̇ci̇
Turkish Journal of Electrical Engineering and Computer Sciences
Unmanned aerial vehicles are gaining importance with many civilian and military applications. Especially the surveillance, search/rescue, and military operations may have to be carried out in extremely constrained environments. In such scenarios, drone base stations (DBSs) have to provide communication services to the people at the ground. The ground users may have no access to the global positioning system (GPS); therefore, their locations have to be estimated using alternative techniques. Besides there may be threats in the environment, such as shooters. In this work, we address the problem of optimal DBS deployment under the aforementioned constraints. We propose a novel …
Comparisons Of Extreme Learning Machine And Backpropagation-Based I-Vector Approach For Speaker Identification, Musab T S Al-Kaltakchi, Raid Rafi Omar Al-Nima, Mohammed A M Abdullah
Comparisons Of Extreme Learning Machine And Backpropagation-Based I-Vector Approach For Speaker Identification, Musab T S Al-Kaltakchi, Raid Rafi Omar Al-Nima, Mohammed A M Abdullah
Turkish Journal of Electrical Engineering and Computer Sciences
The extreme learning machine (ELM) is one of the machine learning applications used for regression and classification systems. In this paper, an extended comparison between an ELM and the backpropagation neural network (BPNN)-based i-vector is given in terms of a closed-set speaker identification task using 120 speakers from the TIMIT database. The system is composed of the mel frequency cepstal coefficient (MFCC) and power normalized cepstal coefficient (PNCC) approaches to form the feature extraction stage, while the cepstral mean variance normalization (CMVN) and feature warping are applied in order to mitigate the linear channel effect. The system is utilized with …
Analysis Of Acoustic Sensor Placement For Pd Location In Power Transformer, Khairul Nadiah Khalid, Muhammad Nur Khairul Hafizi Rohani, Baharuddin Ismail, Muzamir Isa, Chang Yii Chai, Wan Nurul Auni Wan Muhammad
Analysis Of Acoustic Sensor Placement For Pd Location In Power Transformer, Khairul Nadiah Khalid, Muhammad Nur Khairul Hafizi Rohani, Baharuddin Ismail, Muzamir Isa, Chang Yii Chai, Wan Nurul Auni Wan Muhammad
Turkish Journal of Electrical Engineering and Computer Sciences
Partial discharge (PD) is an abnormal activity that occurs in high-voltage components, such as power cables, switchgear, machines, and power transformers. Such activity needs to be diagnosed for the equipment to last longer as PD could harm the insulation and potentially lead to asset destruction from time to time. Moving one or more externally mounted acoustic sensors to different locations on the transformer tank is commonly used in order to detect and locate PD signal occurring in the power transformer. However, this procedure may lead to less accuracy in PD identification. Therefore, this research paper presents an analysis of acoustic …
Comparative Analysis Of Classification Techniques For Network Fault Management, Mohammed Madi, Fidaa Jarghon, Yousef Fazea, Omar Almomani, Adeeb Saaidah
Comparative Analysis Of Classification Techniques For Network Fault Management, Mohammed Madi, Fidaa Jarghon, Yousef Fazea, Omar Almomani, Adeeb Saaidah
Turkish Journal of Electrical Engineering and Computer Sciences
Network troubleshooting is a significant process. Many studies were conducted about it. The first step in the troubleshooting procedures is represented in collecting information. It's collected in order to identify the problems. Syslog messages which are sent by almost all network devices include a massive amount of data that concern the network problems. Based on several studies, it was found that analyzing syslog data (which) can be a guideline for network problems and their causes. The detection of network problems can become more efficient if the detected problems have been classified based on the network layers. Classifying syslog data requires …
Combining Metadata And Co-Citations For Recommending Related Papers, Shahbaz Ahmad, Muhammad Tanvir Afzal
Combining Metadata And Co-Citations For Recommending Related Papers, Shahbaz Ahmad, Muhammad Tanvir Afzal
Turkish Journal of Electrical Engineering and Computer Sciences
Identification of relevant documents is performed to keep track of the state-of-the-art methods and relies on research paper recommender systems. The proposed approaches for these systems can be classified into categories like content-based, collaborative filtering-based, and bibliographic information-based approaches. The content-based approaches exploit the full text of articles and provide more promising results than other approaches. However, most content is not freely available because of subscription requirements. Therefore, the scope of content-based approaches is limited. In such scenarios, the best possible alternative could be the exploitation of other openly available resources. Therefore, this research explores the possible use of metadata …
Investigating The Efficiency Of Multithreading Application Programming Interfacesfor Parallel Packet Classification In Wireless Sensor Networks, Mahdi Abbasi, Milad Rafiee, Mohammad R. Khosravi
Investigating The Efficiency Of Multithreading Application Programming Interfacesfor Parallel Packet Classification In Wireless Sensor Networks, Mahdi Abbasi, Milad Rafiee, Mohammad R. Khosravi
Turkish Journal of Electrical Engineering and Computer Sciences
This paper investigates the most appropriate application programming interface (API) that best accelerates the flow-based applications on the wireless sensor networks (WSNs). Each WSN include many sensor nodes which have limited resources. These sensor nodes are connected together using base stations. The base stations are commonly network systems with conventional processors which are responsible for handling a large amount of communicated data in flows of network packets. For this purpose, classification of the communicated packets is considered the primary process in such systems. With the advent of high-performance multicore processors, developers in the network industry have considered these processors as …
Deep Reinforcement Learning For Acceptance Strategy In Bilateral Negotiations, Yousef Razeghi, Celal Ozan Berk Yavuz, Reyhan Aydoğan
Deep Reinforcement Learning For Acceptance Strategy In Bilateral Negotiations, Yousef Razeghi, Celal Ozan Berk Yavuz, Reyhan Aydoğan
Turkish Journal of Electrical Engineering and Computer Sciences
This paper introduces an acceptance strategy based on reinforcement learning for automated bilateral negotiation, where negotiating agents bargain on multiple issues in a variety of negotiation scenarios. Several acceptance strategies based on predefined rules have been introduced in the automated negotiation literature. Those rules mostly rely on some heuristics, which take time and/or utility into account. For some negotiation settings, an acceptance strategy solely based on a negotiation deadline might perform well; however, it might fail in another setting. Instead of following predefined acceptance rules, this paper presents an acceptance strategy that aims to learn whether to accept its opponent's …
Bases Of Polymatroids And Problems On Graphs, Hakan Kutucu
Bases Of Polymatroids And Problems On Graphs, Hakan Kutucu
Turkish Journal of Electrical Engineering and Computer Sciences
In the paper, we present new theorems to show that a Hamiltonian path and circuit on an undirected graph can be formulated in terms of bases of polymatroids or extended polymatroids associated with submodular functions defined on subsets of the node-set of a given graph. In this way, we give a new formulation of the well-known traveling salesman problem including constraints in these terms. The main result in the paper states that using a special base of the polymatroid, a Hamiltonian path on an undirected graph can be solved effectively. Since the determination of a Hamiltonian circuit can be reduced …
Harmonic Reduction Of Svc With System Integrated Apf, Yan Xuhui, Wang Feng, Mahmood Ul Hassan, Muhammad Humayun
Harmonic Reduction Of Svc With System Integrated Apf, Yan Xuhui, Wang Feng, Mahmood Ul Hassan, Muhammad Humayun
Turkish Journal of Electrical Engineering and Computer Sciences
Static var compensators (svcs) are widely used to compensate for reactive power in a system. The hybrid active power filter (hapf) in combination with svc has extensively been studied in the literature to reduce harmonics generated by the svc. This study proposes a new topology of svc for three-phase systems based on a three-phase thyristor-control reactor (tcr). The harmonics generated by the tcr are minimized by an active power filter (apf), which can be realized by a reduced resonant capacitor size. A control strategy comprising feedback and feedforward control is employed to achieve good harmonic reduction and fast transient response. …
Performance Analysis Of A Fuzzy Disparity Selector For Stereo Matching Of Imagesegments Under Radiometric Variations, Akhil Appu Shetty, Vadakekara Itty George, Chempi Gurudas Nayak, Raviraj Shetty
Performance Analysis Of A Fuzzy Disparity Selector For Stereo Matching Of Imagesegments Under Radiometric Variations, Akhil Appu Shetty, Vadakekara Itty George, Chempi Gurudas Nayak, Raviraj Shetty
Turkish Journal of Electrical Engineering and Computer Sciences
Stereo matching algorithms generate disparity maps, which contain the depth information of the environment, from two or more images of a scene taken from different viewpoints. The process of obtaining dense disparity maps is a problem which is still being actively researched. The presence of radiometric differences in the images only further complicates the stereo matching problem. In the present research work, the images are initially split into small patches of pixels, such that pixels in each patch have similar intensities. The authors attempt to study the effect of the parameters, namely, tuning parameter `?? and the number of segments, …
Dynamic Optimal Management Of A Hybrid Microgrid Based On Weather Forecasts, Hamadi Bouaicha, Emily Craparo, Habib Dallagi, Samir Nejim
Dynamic Optimal Management Of A Hybrid Microgrid Based On Weather Forecasts, Hamadi Bouaicha, Emily Craparo, Habib Dallagi, Samir Nejim
Turkish Journal of Electrical Engineering and Computer Sciences
Hybrid microgrids containing both renewable and conventional power sources are becoming increasingly attractive for a variety of reasons. However, intermittency of renewable power production and uncertainty in future load prediction increase risks of electric grid instability and, by consequence, restrict the portion of renewable power production in microgrids. In order, to prefigure the upcoming renewable power production, particularly, wind power and photovoltaic power, we suggest using weather forecasts. In addition to illustrating short term renewable power prediction based on ensemble weather forecasts, this paper focuses on optimizing the management of distributed power generation, power storage, and power exchange with the …
The Quantum Version Of The Shifted Power Method And Its Application Inquadratic Binary Optimization, Ammar Daşkin
The Quantum Version Of The Shifted Power Method And Its Application Inquadratic Binary Optimization, Ammar Daşkin
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we present a direct quantum adaptation of the classical shifted power method. The method is very similar to the iterative phase estimation algorithm; however, it does not require any initial estimate of an eigenvector, and as in the classical case its convergence and the required number of iterations are directly related to the eigengap. If the amount of the gap is in the order of $1/poly(n)$, then the algorithm can converge to the dominant eigenvalue in $O(poly(n))$ time. The method can be potentially used for solving any eigenvalue related problem and finding minimum/maximum of a data set …
Image Denoising Using Deep Convolutional Autoencoder With Feature Pyramids, Ekrem Çeti̇nkaya, Mustafa Furkan Kiraç
Image Denoising Using Deep Convolutional Autoencoder With Feature Pyramids, Ekrem Çeti̇nkaya, Mustafa Furkan Kiraç
Turkish Journal of Electrical Engineering and Computer Sciences
Image denoising is 1 of the fundamental problems in the image processing field since it is the preliminary step for many computer vision applications. Various approaches have been used for image denoising throughout the years from spatial filtering to model-based approaches. Having outperformed all traditional methods, neural-network-based discriminative methods have gained popularity in recent years. However, most of these methods still struggle to achieve flexibility against various noise levels and types. In this paper, a deep convolutional autoencoder combined with a variant of feature pyramid network is proposed for image denoising. Simulated data generated by Blender software along with corrupted …
Improving Performance Of Indoor Localization Using Compressive Sensing Andnormal Hedge Algorithm, Saeid Hassanhosseini, Mohammad Reza Taban, Jamshid Abouei, Arash Mohammadi
Improving Performance Of Indoor Localization Using Compressive Sensing Andnormal Hedge Algorithm, Saeid Hassanhosseini, Mohammad Reza Taban, Jamshid Abouei, Arash Mohammadi
Turkish Journal of Electrical Engineering and Computer Sciences
Accurate indoor localization technologies are currently in high demand in wireless sensor networks, which strongly drive the development of various wireless applications including healthcare monitoring, patient tracking and endoscopic capsule localization. The precise position determination requires exact estimation of the time varying characteristics of wireless channels. In this paper, we address this issue and propose a three-phased scheme, which employs an optimal single stage TDOA/FDOA/AOA indoor localization based on spatial sparsity. The first contribution is to formulate the received unknown signals from the emitter as a compressive sensing problem. Then, we solve an $\ell_1$ minimization problem to localize the emitter's …
Controlling A Launch Vehicle At Exoatmospheric Flight Conditions Via Adaptivecontrol Allocation, Yildiray Yildiz
Controlling A Launch Vehicle At Exoatmospheric Flight Conditions Via Adaptivecontrol Allocation, Yildiray Yildiz
Turkish Journal of Electrical Engineering and Computer Sciences
The focus of this paper is the control of a reusable launch vehicle at exoatmospheric flight conditions, in the presence of actuator effectiveness uncertainty. Since during exoatmospheric flight, dynamic pressure is nonexistent, aerodynamic control surfaces cannot be used. Under these conditions, reaction control jet actuators can provide the necessary thrust to control the vehicle. Reaction control jets have only 2 states, namely, on and off, and continuous control inputs can be implemented with the help of pulse width modulation, which is also employed in this paper. A continuous controller is designed in the outer loop and a control allocator is …
Simplified Model Predictive Current Control Of Non-Sinusoidal Low Power Brushlessdc Machines, Alireza Lahooti Eshkevari, Hossein Torkaman
Simplified Model Predictive Current Control Of Non-Sinusoidal Low Power Brushlessdc Machines, Alireza Lahooti Eshkevari, Hossein Torkaman
Turkish Journal of Electrical Engineering and Computer Sciences
Several strategies have been proposed to control nonsinusoidal brushless DC machines (BLDCMs). However, high electromagnetic torque ripple and current overshoots occur in commutation times, which are significant problems of those strategies such as for hysteresis current controllers. This paper proposes a model predictive strategy to solve the above issues. It is simple and straightforward. Moreover, it reduces the motor torque ripple significantly and improves the response rate of the control system to the load torque variation in comparison with the conventional technique. The torque varies smoothly, and the performance of the system at commutation time is improved by eliminating the …
Fiber Optic Chemical Sensors For Water Testing By Using Fiber Loop Ringdown Spectroscopy Technique, Mali̇k Kaya
Fiber Optic Chemical Sensors For Water Testing By Using Fiber Loop Ringdown Spectroscopy Technique, Mali̇k Kaya
Turkish Journal of Electrical Engineering and Computer Sciences
Real-time response, low cost, sensitive and easy setup fiber optic chemical sensors were fabricated by etching a part of single mode fiber in hydrofluoric (HF) acid solution and tested in different water samples such as tap water, DI water, salty and sugar water with different concentrations to record ringdown time (RDT) differences between media due to refractive index differences by employing the fiber loop ringdown (FLRD) spectroscopy technique. Baseline stability of 0.63 % and the minimum detectable RDT of $5.05$ $\mu$s for this kind of fiber optic chemical sensors were obtained. Fabricated sensors were coated with N,N-Diethyl-p-phenylenediamine for the first …
An Electrothermal Current Prediction Method For Overload Protection Of Miniaturecircuit Breakers, Sen Lyu, Ming Zong
An Electrothermal Current Prediction Method For Overload Protection Of Miniaturecircuit Breakers, Sen Lyu, Ming Zong
Turkish Journal of Electrical Engineering and Computer Sciences
Traditional miniature circuit breakers (MCBs) cannot meet the requirement for the intelligence of distributing apparatuses in a smart grid. The intellectualization of MCBs is restricted due to the lack of appropriate current measurement methods. Thus, an electrothermal current prediction method is proposed based on the derived relationship between root-mean-square (RMS) current and steady-state temperature rise. A fast acquisition algorithm is used to obtain the required temperature rise before thermal equilibrium to highly reduce the total time consumption. The presented prediction method is found immunized against the ambient temperature. The theory is validated with experiments using a thermostat. The tested steady-state …
Reducing Computational Complexity In Fingerprint Matching, Mubeen Sabir, Tariq Mahmood Khan, Munazza Arshad, Sana Munawar
Reducing Computational Complexity In Fingerprint Matching, Mubeen Sabir, Tariq Mahmood Khan, Munazza Arshad, Sana Munawar
Turkish Journal of Electrical Engineering and Computer Sciences
The performance of cross-correlation functions can decrease computational complexity under optimal fingerprint feature selection. In this paper, a technique is proposed to perform alignment of fingerprints followed by their matching in fewer computations. Minutiae points are extracted and alignment is performed on the basis of their spatial locations and orientation fields. Unlike traditional cross-correlation based matching algorithms, ridges are not included in the matching process to avoid redundant computations. However, optimal cross-correlation is chosen by correlating feature vectors accompanying x-y locations of minutiae points and their aligned orientation fields. As a result, matching time is significantly reduced with much improved …
Low-Profile Folded Dipole Uhf Rfid Tag Antenna With Outer Strip Lines Formetal Mounting Application, Fuad Erman, Effariza Hanafi, Eng-Hock Lim, Wan Amirul Wan Mohd Mahyiddin, Sulaiman Wadi Harun, Mohamad Sofian Abu Talip, Rawan Soboh, Hassan Umair
Low-Profile Folded Dipole Uhf Rfid Tag Antenna With Outer Strip Lines Formetal Mounting Application, Fuad Erman, Effariza Hanafi, Eng-Hock Lim, Wan Amirul Wan Mohd Mahyiddin, Sulaiman Wadi Harun, Mohamad Sofian Abu Talip, Rawan Soboh, Hassan Umair
Turkish Journal of Electrical Engineering and Computer Sciences
A metal mountable UHF RFID tag antenna with a low-profile folded dipole structure is proposed. It is fabricated on a single layer of polytetrafluoroethylene (PTFE) dielectric laminate. It is composed of two symmetrical C-shape resonators integrated with the outer strip lines. The IC chip's terminals are connected directly to the center of the C-shaped resonators. The outer strip lines are integrated with the C-shaped resonators, which function to lower the reflection coefficient so as to match the IC chip impedance. In particular, the outer strip lines increase the inductive reactance of the antenna impedance in order to realize IC chip …
Image Subset Communication For Resource-Constrained Applications In Wirelesssensor Networks, Sajid Nazir, Omar Alzubi, Mohammad Kaleem, Hassan Hamdoun
Image Subset Communication For Resource-Constrained Applications In Wirelesssensor Networks, Sajid Nazir, Omar Alzubi, Mohammad Kaleem, Hassan Hamdoun
Turkish Journal of Electrical Engineering and Computer Sciences
JPEG is the most widely used image compression standard for sensing, medical, and security applications. JPEG provides a high degree of compression but field devices relying on battery power must further economize on data transmissions to prolong deployment duration with particular use cases in wireless sensor networks. Transmitting a subset of image data could potentially enhance the battery life of power-constrained devices and also meet the application requirements to identify the objects within an image. Depending on an application's needs, after the first selected subset is received at the base station, further transmissions of the image data for successive refinements …
Revised Polyhedral Conic Functions Algorithm For Supervised Classification, Gürhan Ceylan, Gürkan Öztürk
Revised Polyhedral Conic Functions Algorithm For Supervised Classification, Gürhan Ceylan, Gürkan Öztürk
Turkish Journal of Electrical Engineering and Computer Sciences
In supervised classification, obtaining nonlinear separating functions from an algorithm is crucial for prediction accuracy. This paper analyzes the polyhedral conic functions (PCF) algorithm that generates nonlinear separating functions by only solving simple subproblems. Then, a revised version of the algorithm is developed that achieves better generalization and fast training while maintaining the simplicity and high prediction accuracy of the original PCF algorithm. This is accomplished by making the following modifications to the subproblem: extension of the objective function with a regularization term, relaxation of a hard constraint set and introduction of a new error term. Experimental results show that …
A Mechanism Of Qos Differentiation Based On Offset Time And Adjusted Burstlength In Obs Networks, Viet Minh Nhat Vo, Trung Duc Pham, Thanh Chuong Dang, Van Hoa Le
A Mechanism Of Qos Differentiation Based On Offset Time And Adjusted Burstlength In Obs Networks, Viet Minh Nhat Vo, Trung Duc Pham, Thanh Chuong Dang, Van Hoa Le
Turkish Journal of Electrical Engineering and Computer Sciences
Quality of service (QoS) differentiation is an integral component of any networking system, particularly, with the current and future great diversity of users? applications and their manifold requirements. In optical burst switching (OBS) networks, there are two approaches for QoS differentiation: one is based on offset time and the other is based on burst length. This paper presents a mechanism of QoS differentiation based on both offset time and burst length, in which the offset times are calculated to achieve a complete isolation of data loss between priority classes and the burst length is adaptively adjusted according to the feedbacked …
An Improved Memetic Genetic Algorithm Based On A Complex Network As Asolution To The Traveling Salesman Problem, Hadi Mohammadi, Kamal Mirzaie, Mohammad Reza Mollakhalili Meybodi
An Improved Memetic Genetic Algorithm Based On A Complex Network As Asolution To The Traveling Salesman Problem, Hadi Mohammadi, Kamal Mirzaie, Mohammad Reza Mollakhalili Meybodi
Turkish Journal of Electrical Engineering and Computer Sciences
A genetic algorithm (GA) is not a good option for finding solutions around in neighborhoods. The current study applies a memetic algorithm (MA) with a proposed local search to the mutation operator of a genetic algorithm in order to solve the traveling salesman problem (TSP). The proposed memetic algorithm uses swap, reversion and insertion operations to make changes in the solution. In the basic GA, unlike in the real world, the relationship between generations has not been considered. This gap is resolved using the proposed complex network to allow selection among possible solutions. The degree measure has been used for …
Comparative Study Between Measured And Estimated Wind Energy Yield, Ayman Alquraan, Mohammed Al-Mahmodi, Ashraf Radaideh, Hussein Al-Masri
Comparative Study Between Measured And Estimated Wind Energy Yield, Ayman Alquraan, Mohammed Al-Mahmodi, Ashraf Radaideh, Hussein Al-Masri
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes a power-speed (P-V) model of the wind turbine by assuming three different functions for the first performance region; cubic, quadratic and uncorrected cubic. These three functions have been compared with the manufacturer models of five different wind turbines which were installed in five different locations in Jordan; Tafila, Hofa, Fujeij, Al Rajef, and Deahan. The wind turbine of these wind farms are considered as large scale HAWT in the range of Mw. The generated P-V models are developed by applying a new method described in this paper which is basically based on generating a multiplier factor x. …
Gabor Filter-Based Localization Of Straight And Curved Needlesin 2d Ultrasound Images, Mert Kaya, Abdurrahman Enes Şenel, Özkan Bebek
Gabor Filter-Based Localization Of Straight And Curved Needlesin 2d Ultrasound Images, Mert Kaya, Abdurrahman Enes Şenel, Özkan Bebek
Turkish Journal of Electrical Engineering and Computer Sciences
2D ultrasound (US) is one of the most commonly used medical imaging devices for needle localization in biopsies. However, the produced images are low-resolution and contain an excessive number of artifacts, which makes the needle localization challenging. Image processing techniques can help resolve this issue. This paper presents a novel Gabor filter-based method for needle localization in 2D US images, which enhances the needle outline in the images while suppressing other structures. The scheme works in two stages: First, the Gabor filter is applied to the image, the needle insertion angle is estimated, and the needle trajectory is found using …
Distribution Network Reconfiguration Based On Artificial Networkreconfiguration For Variable Load Profile, Hesham Hanie Youssef, Hazlie Bin Mokhlis, Mohamad Sofian Abu Talip, Mohammad Alsamman, Munir Azam Muhammad, Nurulafiqah Nadzirah Mansor
Distribution Network Reconfiguration Based On Artificial Networkreconfiguration For Variable Load Profile, Hesham Hanie Youssef, Hazlie Bin Mokhlis, Mohamad Sofian Abu Talip, Mohammad Alsamman, Munir Azam Muhammad, Nurulafiqah Nadzirah Mansor
Turkish Journal of Electrical Engineering and Computer Sciences
Network reconfiguration is a process to change the open-switches in distribution system for a minimum power loss. In the past, metaheuristic techniques were applied widely for network reconfiguration with consideration of a fixed loading profile. When the loading changes, the current configuration may not be the optimal one. Thus, the technique needs to be executed to find a new optimal configuration based on the latest loading. The process is time-consuming since metaheuristic techniques commonly require high computational times and produces inconsistent results. Therefore, this paper proposes a network reconfiguration technique based on artificial neural network (ANN) for variable loading conditions. …