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Articles 631 - 660 of 3106
Full-Text Articles in Engineering
Remac: A Novel Hybrid And Reservation-Based Mac Protocol For Vanets, Fi̇kri̇ Ağgün, Musa Çibuk, Shafqat Ur Rehman
Remac: A Novel Hybrid And Reservation-Based Mac Protocol For Vanets, Fi̇kri̇ Ağgün, Musa Çibuk, Shafqat Ur Rehman
Turkish Journal of Electrical Engineering and Computer Sciences
The period in which a roadside unit (RSU) of a vehicle remains in the coverage area is too short in vehicular ad hoc networks (VANETs) in which the vehicles move at high speeds. In this short period, it is necessary for the vehicles to join the network and establish continuous communication with the RSU. To accomplish this, the RSU and vehicles need an efficient and robust media access control (MAC) protocol. In this study, a new reservation-based MAC (ReMAC) protocol in which multiple channels are used is suggested to ensure rapid connection to RSUs, smooth transition between RSUs, and efficient …
A Novel Genome Analysis Method With The Entropy-Based Numerical Techniqueusing Pretrained Convolutional Neural Networks, Bi̇hter Daş, Suat Toraman, İbrahi̇m Türkoğlu
A Novel Genome Analysis Method With The Entropy-Based Numerical Techniqueusing Pretrained Convolutional Neural Networks, Bi̇hter Daş, Suat Toraman, İbrahi̇m Türkoğlu
Turkish Journal of Electrical Engineering and Computer Sciences
The identification of DNA sequences as exon and intron is a common problem in genome analysis. The methods used for feature extraction and mapping techniques for the digitization of sequences affect directly the solution of this problem. The existing mapping techniques are not enough to detect coding and noncoding regions in some genomes because the digital representation of each base in a DNA sequence with an integer does not fully reflect the structure of an original DNA sequence. In the entropy-based mapping technique, we could overcome this problem because the technique deepens distinction rates of exon regions, and better reflects …
Finite-Time Dynamic Surface Approach To Nonlinear Systems With Mismatcheduncertainties, Guofa Sun, Yaming Xu
Finite-Time Dynamic Surface Approach To Nonlinear Systems With Mismatcheduncertainties, Guofa Sun, Yaming Xu
Turkish Journal of Electrical Engineering and Computer Sciences
This paper develops a finite-time dynamic surface control (DSC) scheme for nonlinear systems with mismatched uncertainties via a high-order sliding mode(HOSM) observer. By designing a second-order terminal sliding surface based on the estimated signals, an observer-based sliding mode control (SMC) is designed to counteract the mismatched uncertainties in each step of backstepping. The proposed DSC scheme exhibits the following two attractive features. One is the application of HOSM observer to deal with mismatched system uncertainty functions. This is very different from the traditional approximator-based adaptive methods in dealing with high-order uncertain nonlinear systems. The other is the finite-time convergence of …
Sketic: A Machine Learning-Based Digital Circuit Recognition Platform, Mohamamd Abdel Majeed, Tasneem Almousa, Maysaa Alsalman, Abeer Yosef
Sketic: A Machine Learning-Based Digital Circuit Recognition Platform, Mohamamd Abdel Majeed, Tasneem Almousa, Maysaa Alsalman, Abeer Yosef
Turkish Journal of Electrical Engineering and Computer Sciences
In digital system design, digital logic circuit diagrams are built using interconnects and symbolic representations of the basic logic gates. Constructing such diagrams using free sketches is the first step in the design process. After that the circuit schematic or code has to be generated before being able to simulate the design. While most of the mentioned steps are automated using design automation tools, drafting the schematic circuit and then converting it into a valid format that can be simulated are still done manually due to the lack of robust tools that can recognize the free sketches and incorporate them …
Detection Of Bga Solder Defects From X-Ray Images Using Deep Neural Network, Ceren Türer Akdeni̇z, Zümray Ölmez, Tamer Ölmez
Detection Of Bga Solder Defects From X-Ray Images Using Deep Neural Network, Ceren Türer Akdeni̇z, Zümray Ölmez, Tamer Ölmez
Turkish Journal of Electrical Engineering and Computer Sciences
In the literature it is observed that complex image processing operations are used in the classification of Ball Grid Array (BGA) X-ray images, however high classification results were not achieved. In recent years, it has been shown that deep learning methods are very successful especially in classification problems. In this study, a new deep neural network (DNN) model is proposed to classify the BGA X-ray images. The proposed DNN model contains feature extractor layers and a minimum distance classifier. Since the proposed network consists of less number of layers (4 convolution layers and 1 fully connected layer), determination of the …
Transmit Antenna Selection Schemes For Stbc-Sm, Belal Asaati, Ammar Abu Hudrouss
Transmit Antenna Selection Schemes For Stbc-Sm, Belal Asaati, Ammar Abu Hudrouss
Turkish Journal of Electrical Engineering and Computer Sciences
The coupling of space-time block codes (STBCs) with the spatial modulation (SM) scheme can introduce a spatial diversity to the SM systems. This paper presents antenna selection techniques to provide an additional coding gain with the space-time block coded spatial modulation (STBC-SM). Specifically, the selection of optimal transmit antenna elements at the transmitter to send a spatially modulated space-time block code is studied. This paper studies the effects of applying the capacity optimized antenna selection (COAS) algorithm with the STBC-SM. The COAS algorithm has a suboptimal performance with a trade-off between complexity and bit-error-rate (BER) enhancement. Simulation results for STBC-SM …
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 …
Connectivity Considerations For Mission Planning Of A Search And Rescue Drone Team, Evşen Yanmaz Adam
Connectivity Considerations For Mission Planning Of A Search And Rescue Drone Team, Evşen Yanmaz Adam
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we analyze the mission success performance and mission times of centralized, distributed, and hybrid path-planning methods for a drone team whose mission is to find a target and inform the ground control. We propose two methods that integrate connectivity into the search mission path decisions. We observe that even though the coverage path-planning leads to lower search times, when target connectivity is also required, schemes that incorporate end--end connectivity into path planning result in at least 50 % better mission times for small communication ranges and lower number of drones. Our results also indicate that methods to …
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 …
A Secure And Energy-Efficient Opportunistic Routing Protocol With Void Avoidancefor Underwater Acoustic Sensor Networks, Varun Menon, Divya Midhunchakkaravarthy, Sonali John, Sunil Jacob, Amrit Mukherjee
A Secure And Energy-Efficient Opportunistic Routing Protocol With Void Avoidancefor Underwater Acoustic Sensor Networks, Varun Menon, Divya Midhunchakkaravarthy, Sonali John, Sunil Jacob, Amrit Mukherjee
Turkish Journal of Electrical Engineering and Computer Sciences
Recently, underwater acoustic sensor networks (UASNs) have gained wide attention due to their numerous applications in underwater surveillance, oil leakage detection, assisted navigation, and disaster prevention. With unique characteristics like increased propagation delay, constant mobility of sensor nodes, high error rate, and limitations in energy and interference, efficient routing of data packets from the source node to the destination is a major challenge in UASNs. Most of the protocols proposed for traditional sensor networks do not work well in UASNs. Although many protocols have been specifically proposed for underwater environments, the aim of most of them is to improve only …
On A Yearly Basis Prediction Of Soil Water Content Utilizing Sar Data: A Machinelearning And Feature Selection Approach, Emrullah Acar, Mehmet Si̇raç Özerdem
On A Yearly Basis Prediction Of Soil Water Content Utilizing Sar Data: A Machinelearning And Feature Selection Approach, Emrullah Acar, Mehmet Si̇raç Özerdem
Turkish Journal of Electrical Engineering and Computer Sciences
Soil water content (SWC) performs an important role in many areas including agriculture, drought cases, usage of water resources, hydrology, crop diseases and aerology. However, the measurement of the SWC over large terrains with standard computational techniques is very hard. In order to overcome this situation, remote sensing tools are preferred, which can produce much more successful results in less time than standard calculation techniques. Among all remote sensing tools, synthetic aperture radar (SAR) has a significant impact on determining SWC over large terrains. The main objective of this study is to predict SWC on a yearly basis over the …
Reconfiguration-Based Hierarchical Energy Management In Multimicrogrid Systems Considering Power Losses, Reliability Index, And Voltage Enhancement, Farid Hamzeh Aghdam, Navid Taghizadegan Kalantari, Sajad Najafi Ravadanegh
Reconfiguration-Based Hierarchical Energy Management In Multimicrogrid Systems Considering Power Losses, Reliability Index, And Voltage Enhancement, Farid Hamzeh Aghdam, Navid Taghizadegan Kalantari, Sajad Najafi Ravadanegh
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a reconfiguration-based hierarchical energy management for interconnected microgrids known as multimicrogrid system. The goal is to minimize the operational costs of different entities alongside with finding the best topology to minimize the active power loss, enhance reliability index, and improve the voltage level. The distribution network (DN) includes several dispatchable and undispatchable distributed energy resources, energy storage devices, and multiple microgrids (MGs). The first layer of the optimization process is executed by each MG operator and each MG performs local energy management. Each MG operator informs the DN operator about its optimal schedules. Finally, global energy management …
Real-Time Anomaly Detection And Mitigation Using Streaming Telemetry In Sdn, Çağdaş Kurt, Osman Ayhan Erdem
Real-Time Anomaly Detection And Mitigation Using Streaming Telemetry In Sdn, Çağdaş Kurt, Osman Ayhan Erdem
Turkish Journal of Electrical Engineering and Computer Sciences
Measurement and monitoring are crucial for various network tasks such as traffic engineering, anomaly detection, and intrusion prevention. The success of critical capabilities such as anomaly detection and prevention depends on whether the utilized network measurement method is able to provide granular, near real-time, low-overhead measurement data or not. In addition to the measurement method, the anomaly detection and mitigation algorithm is also essential for recognizing normal and abnormal traffic patterns in such a huge amount of measured data with high accuracy and low latency. Software-defined networking is an emerging concept to enable programmable and efficient measurement functions for these …
An Encrypted Speech Authentication Method Based On Uniform Subband Spectrumvariance And Perceptual Hashing, Qiuyu Zhang, Denghai Zhang, Liang Zhou
An Encrypted Speech Authentication Method Based On Uniform Subband Spectrumvariance And Perceptual Hashing, Qiuyu Zhang, Denghai Zhang, Liang Zhou
Turkish Journal of Electrical Engineering and Computer Sciences
In a real-world cloud server, a speech signal is prone to suffer various attacks, such as malicious muting and tampering. In such a context, the privacy security of the speech owner will not be guaranteed. In order to achieve content authentication of encrypted speech in the cloud server, an efficient encrypted speech authentication method based on uniform subband spectrum variance and perceptual hashing is proposed. Firstly, the original speech is scrambled by Henon mapping to construct an encrypted speech library in the cloud, through extracting uniform subband spectrum variance of the encrypted speech and constructing a hashing sequence to generate …
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 …
Mutant Selection By Using Fourier Expansion, Savaş Takan, Tolga Ayav
Mutant Selection By Using Fourier Expansion, Savaş Takan, Tolga Ayav
Turkish Journal of Electrical Engineering and Computer Sciences
Mutation analysis is a widely used technique to evaluate the effectiveness of test cases in both hardware and software testing. The original model is mutated systematically under certain fault assumptions and test cases are checked against the mutants created to see whether the test cases can detect the faults or not. Mutation analysis is usually a computationally intensive task, particularly in finite state machine (FSM) testing due to a possibly huge amount of mutants. Random selection could be a practical reduction method under the assumption that each mutant is identical in terms of the probability of occurrence of its associating …
Combined Morphology And Svm-Based Fault Feature Extraction Technique Fordetection And Classification Of Transmission Line Faults, Revati Godse, Dr. Sunil Bhat
Combined Morphology And Svm-Based Fault Feature Extraction Technique Fordetection And Classification Of Transmission Line Faults, Revati Godse, Dr. Sunil Bhat
Turkish Journal of Electrical Engineering and Computer Sciences
A transmission line is the main commodity of power transmission network through which power is transmitted to the utility. These lines are often swayed by accidental breakdowns owing to different random origins. Hence, researchers try to detect and track down these failures at the earliest to avoid financial prejudice. This paper offers a new realtime mathematical morphology based approach for fault feature extraction. The morphological open-close-median filter is exploited to wrest unique fault features which are then fed as an input to support vector machine to detect and classify the short circuit faults. The acquired graphical and numerical results of …
A Supervised Learning Approach For Detecting Erroneoussamples In Embeddings, Görkem Saygili
A Supervised Learning Approach For Detecting Erroneoussamples In Embeddings, Görkem Saygili
Turkish Journal of Electrical Engineering and Computer Sciences
Visualizing multidimensional data has been a crucial task in recent years regarding the growing amount of data from various sources. To achieve this, dimensionality reduction algorithms have been used to reduce the number of dimensions for visualization of the data on a screen. However, these algorithms may fail to faithfully represent high dimensional data in lower dimensions and eventually lead to erroneous visualizations. In this work, we propose an error detection algorithm for dimensionality reduction algorithms based on recently developed error prediction algorithms for medical image registration. The proposed algorithm matches the neighborhoods of high and low dimensional data with …
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. …
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. …
A Novel Grouping Proof Authentication Protocol For Lightweight Devices:Gpapxr+, Ömer Aydin, Gökhan Dalkiliç, Cem Kösemen
A Novel Grouping Proof Authentication Protocol For Lightweight Devices:Gpapxr+, Ömer Aydin, Gökhan Dalkiliç, Cem Kösemen
Turkish Journal of Electrical Engineering and Computer Sciences
Radio frequency identification (RFID) tags that meet EPC Gen2 standards are used in many fields such as supply chain operations. The number of the RFID tags, smart cards, wireless sensor nodes, and Internet of things devices is increasing day by day and the areas where they are used are expanding. These devices are very limited in terms of the resources they have. For this reason, many security mechanisms developed for existing computer systems cannot be used for these devices. In order to ensure secure communication, it is necessary to provide authentication process between these lightweight devices and the devices they …
Exhaustive Hard Triplet Mining Loss For Person Re-Identification, Chao Xu, Xiang Sun, Ziliang Chen, Shoubiao Tan
Exhaustive Hard Triplet Mining Loss For Person Re-Identification, Chao Xu, Xiang Sun, Ziliang Chen, Shoubiao Tan
Turkish Journal of Electrical Engineering and Computer Sciences
Person reidentification (Re-ID) is an important task in computer vision and has many applications in videobased surveillance. Recently, the triplet loss has been popular in the deep learning framework for person Re-ID. It is particularly important to note that the selection of hard triplets has significant influence on the performance of the learned deep model. However, the existing triplet losses only focus on some specific forms of hard triplets, thus leading to weaker generalization capability. To address this issue, we propose a novel variant of the triplet loss, named exhaustive hard triplet mining loss (EHTM), which is able to deal …
Exploring The Parameter Space Of Human Activity Recognition With Mobile Devices, Berrenur Saylam, Muhammad Shoaib, Özlem Durmaz İncel
Exploring The Parameter Space Of Human Activity Recognition With Mobile Devices, Berrenur Saylam, Muhammad Shoaib, Özlem Durmaz İncel
Turkish Journal of Electrical Engineering and Computer Sciences
Motion sensors available on smart phones make it possible to recognize human activities. Accelerometer, gyroscope, magnetometer, and their various combinations are used to classify, particularly, locomotion activities, ranging from walking to biking. In most of the studies, the focus is on the collection of data and on the analysis of the impact of different parameters on the recognition performance. The parameter space includes the types of sensors used, features, classification algorithms, and position/orientation of the mobile device. In most of the studies, the impact of some of these parameters is partially analyzed; however, in this work, we investigate the parameter …
Optimization Of Real-Time Wireless Sensor Based Big Data With Deep Autoencoder Network: A Tourism Sector Application With Distributed Computing, Beki̇r Aksoy, Utku Kose
Optimization Of Real-Time Wireless Sensor Based Big Data With Deep Autoencoder Network: A Tourism Sector Application With Distributed Computing, Beki̇r Aksoy, Utku Kose
Turkish Journal of Electrical Engineering and Computer Sciences
Internet usage has increased rapidly with the development of information communication technologies. The increase in internet usage led to the growth of data volumes on the internet and the emergence of the big data concept. Therefore, it has become even more important to analyze the data and make it meaningful. In this study, 690 million queries and approximately 5.9 quadrillion data collected daily from different servers were recorded on the Redis servers by using real-time big data analysis method and load balance structure for a company operating in the tourism sector. Here, wireless networks were used as a triggering factor …
Efficient Turkish Tweet Classification System For Crisis Response, Saed Alqaraleh, Merve Işik
Efficient Turkish Tweet Classification System For Crisis Response, Saed Alqaraleh, Merve Işik
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a convolutional neural networks Turkish tweet classification system for crisis response. This system has the ability to classify the present information before or during any crisis. In addition, a preprocessing model was also implemented and integrated as a part of the developed system. This paper presents the first ever Turkish tweet dataset for crisis response, which can be widely used and improve similar studies. This dataset has been carefully preprocessed, annotated, and well organized. It is suitable to be used by all the well-known natural language processing tools. Extensive experimental work, using our produced Turkish tweet dataset …
Adaptive Fast Sliding Neural Control For Robot Manipulator, Bariş Özyer
Adaptive Fast Sliding Neural Control For Robot Manipulator, Bariş Özyer
Turkish Journal of Electrical Engineering and Computer Sciences
Robotic manipulators are open to external disturbances and actuation failures during performing a task such as trajectory tracking. In this paper, we present a modifed controller consisting of a global fast sliding surface combined with an adaptive neural network which is called adaptive fast sliding neural control (AFSNC) for a robotic manipulator to precise stable trajectory tracking performance under the external disturbances. The adaptive term is employedtoreduce uncertainties due to unmodeled dynamics. Trackingerror asymptoticallyconvergesto zero according to the Lyapunov stability theorem. Numerical examples have been carried on a planar two-links manipulator to verify the control approach efficiency. The experimental results …
Design And Application Of Spwm Based 21-Level Hybrid Inverter For Induction Motor Drive, Sheikh Tanzim Meraj, Kamrul Hasan, Ammar Masaoud
Design And Application Of Spwm Based 21-Level Hybrid Inverter For Induction Motor Drive, Sheikh Tanzim Meraj, Kamrul Hasan, Ammar Masaoud
Turkish Journal of Electrical Engineering and Computer Sciences
Thispaperpresentstheapplicationofanewlydeveloped21-levelhybridmultilevelinverter. Ahighfrequency modulation technique known as sinusoidal pulse width modulation (SPWM) is applied to the hybrid inverter. This modulation methodology operates the switching sequences of the multilevel inverter to produce the desired 21-level output voltage. To validate the proper application of this inverter, it is further utilized to maintain the speed of a single phase induction motor. The velocity control of the motor is established on the principle of V/f control technique. The speed control strategy along with the compatibility of the SPWM modulation technique were verified by means of simulation and experimental results.