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Articles 511 - 540 of 3106
Full-Text Articles in Physical Sciences and Mathematics
Comparison Of Metaheuristic Optimization Algorithms With A New Modifieddeb Feasibility Constraint Handling Technique, Murat Erhan Çi̇men, Zeynep Gari̇p, Ali̇ Fuat Boz
Comparison Of Metaheuristic Optimization Algorithms With A New Modifieddeb Feasibility Constraint Handling Technique, Murat Erhan Çi̇men, Zeynep Gari̇p, Ali̇ Fuat Boz
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, the modification of the Deb feasibility method is considered to solve the constrained optimization problems. In the developed modified Deb feasibility constraint method, the third rule in its procedure was revised in order to increase the performance of the Deb feasibility constraint handling method. The innovation in the method is based on generating a new individual by using both possible solutions that violate the constraints in the method used for solving the problem. In detail, discussions were given about the application and usefulness of six constrained handling techniques. Furthermore, genetic algorithm, particle swarm optimization, Harris hawks optimization, …
Medical Image Fusion With Convolutional Neural Network In Multiscaletransform Domain, Asan Abas, Hasan Erdi̇nç Koçer, Nurdan Baykan
Medical Image Fusion With Convolutional Neural Network In Multiscaletransform Domain, Asan Abas, Hasan Erdi̇nç Koçer, Nurdan Baykan
Turkish Journal of Electrical Engineering and Computer Sciences
Multimodal medical image fusion approaches have been commonly used to diagnose diseases and involve merging multiple images of different modes to achieve superior image quality and to reduce uncertainty and redundancy in order to increase the clinical applicability. In this paper, we proposed a new medical image fusion algorithm based on a convolutional neural network (CNN) to obtain a weight map for multiscale transform (curvelet/ non-subsampled shearlet transform) domains that enhance the textual and edge property. The aim of the method is achieving the best visualization and highest details in a single fused image without losing spectral and anatomical details. …
Detection Of Amyotrophic Lateral Sclerosis Disease By Variational Modedecomposition And Convolution Neural Network Methods From Event-Relatedpotential Signals, Fatma Lati̇foğlu, Firat Orhan Bulucu, Rami̇s İleri̇
Detection Of Amyotrophic Lateral Sclerosis Disease By Variational Modedecomposition And Convolution Neural Network Methods From Event-Relatedpotential Signals, Fatma Lati̇foğlu, Firat Orhan Bulucu, Rami̇s İleri̇
Turkish Journal of Electrical Engineering and Computer Sciences
Amyotrophic lateral sclerosis (ALS), also known as motor neuron disease, is a neurological disease that occurs as a result of damage to the nerves in the brain and restriction of muscle movements. Electroencephalography (EEG) is the most common method used in brain imaging to study neurological disorders. Diagnosis of neurological disorders such as ALS, Parkinson's, attention deficit hyperactivity disorder is important in biomedical studies. In recent years, deep learning (DL) models have been started to be applied in the literature for the diagnosis of these diseases. In this study, event-related potentials (ERPs) were obtained from EEG signals obtained as a …
Impact Of Image Segmentation Techniques On Celiac Disease Classification Usingscale Invariant Texture Descriptors For Standard Flexible Endoscopic Systems, Manarbek Saken, Munkhtsetseg Banzragch Yağci, Nejat Yumuşak
Impact Of Image Segmentation Techniques On Celiac Disease Classification Usingscale Invariant Texture Descriptors For Standard Flexible Endoscopic Systems, Manarbek Saken, Munkhtsetseg Banzragch Yağci, Nejat Yumuşak
Turkish Journal of Electrical Engineering and Computer Sciences
Celiac disease (CD) is quite common and is a proximal small bowel disease that develops as a permanentintolerance to gluten and other cereal proteins in cereals. It is considered as one of the most di?icult diseases to diagnose.Histopathological evidence of small bowel biopsies taken during endoscopy remains the gold standard for diagnosis.Therefore, computer-aided detection (CAD) systems in endoscopy are a newly emerging technology to enhance thediagnostic accuracy of the disease and to save time and manpower. For this reason, a hybrid machine learning methodshave been applied for the CAD of celiac disease. Firstly, a context-based optimal multilevel thresholding technique wasemployed …
Ensemble Learning Of Multiview Cnn Models For Survival Time Prediction Of Braintumor Patients Using Multimodal Mri Scans, Abdela Ahmed Mossa, Ulus Çevi̇k
Ensemble Learning Of Multiview Cnn Models For Survival Time Prediction Of Braintumor Patients Using Multimodal Mri Scans, Abdela Ahmed Mossa, Ulus Çevi̇k
Turkish Journal of Electrical Engineering and Computer Sciences
Brain tumors have been one of the most common life-threatening diseases for all mankind. There have beenhuge efforts dedicated to the development of medical imaging techniques and radiomics to diagnose tumor patients quicklyand e?iciently. One of the main aims is to ensure that preoperative overall survival time (OS) prediction is accurate.Recently, deep learning (DL) algorithms, and particularly convolutional neural networks (CNNs) achieved promisingperformances in almost all computer vision fields. CNNs demand large training datasets and high computational costs.However, curating large annotated medical datasets are difficult and resource-intensive. The performances of singlelearners are also unsatisfactory for small datasets. Thus, this study …
Automated Classification Of Bi-Rads In Textual Mammography Reports, Mostafa Boroumandzadeh, Elham Parvinnia
Automated Classification Of Bi-Rads In Textual Mammography Reports, Mostafa Boroumandzadeh, Elham Parvinnia
Turkish Journal of Electrical Engineering and Computer Sciences
The main purpose of this paper is to process key information in medical text records and also classifypatients, per different levels of breast imaging-reporting and data system (BI-RADS). The BI-RADS is a scheme for thestandardization of breast imaging reports. Therefore, medical text mining is employed to classify mammography reportssupported BI-RADS. In this research, a new method is proposed for automated BI-RADS classifications extraction fromtextual reports and improves the therapeutic procedures. At first, a mammography lexicon is employed for choosingkeywords from medical text reports. Word2vec and term frequency inverse document frequency (TFIDF) techniques areused for extracting features, finally, they are combined …
Improvements Of Torque Ripple Reduction In Dtc Im Drive Witharbitrary Number Of Voltage Intensities And Automatic Algorithm Modification, Marko Rosic, Sanja Antic, Milan Bebic
Improvements Of Torque Ripple Reduction In Dtc Im Drive Witharbitrary Number Of Voltage Intensities And Automatic Algorithm Modification, Marko Rosic, Sanja Antic, Milan Bebic
Turkish Journal of Electrical Engineering and Computer Sciences
Techniques of direct torque control (DTC) are very common in high-performance electric motor drives.Retaining the good features of the conventional DTC and reducing torque ripple have been the subject of many years ofresearch work on improving these algorithms. This paper presents the DTC algorithm with discretized voltage vectorsbased on the use of conventional switching table (ST-DTC). This algorithm enables a significant torque ripple reductionby defining the corresponding number of the given voltage intensity while retaining calculation simplicity and fast torqueresponse typical of the ST-DTC algorithms. The proposed algorithm has the ability for its automatic modificationdepending on the defined number of …
Optimal Planning Dg And Bes Units In Distribution System Consideringuncertainty Of Power Generation And Time-Varying Load, Mansur Khasanov, Salah Kamel, Ayman Awad, Francisco Jurado
Optimal Planning Dg And Bes Units In Distribution System Consideringuncertainty Of Power Generation And Time-Varying Load, Mansur Khasanov, Salah Kamel, Ayman Awad, Francisco Jurado
Turkish Journal of Electrical Engineering and Computer Sciences
Global environmental problems associated with traditional energy generation have led to a rapid increasein the use of renewable energy sources (RES) in power systems. The integration of renewable energy technologiesis commercially available nowadays, and the most common of such RES technology is photovoltaic (PV). This paperproposes an application of hybrid teaching-learning and artificial bee colony (TLABC) technique for determining theoptimal allocation of PV based distributed generation (DG) and battery energy storage (BES) units in the distributionsystem (DS) with the aim of minimizing the total power losses. Besides, some potential nodes identified by the powerloss sensitivity factor (PLSF). Thereupon TLABC is …
Placement Accuracy Algorithm For Smart Street Lights, Zulkifli Ishak, Wan Siti Halimatul Munirah Wan Ahmad, Nurul Asyikin Mohamed Radzi, Suhaila Sulaiman, Noor Emilia Ramli
Placement Accuracy Algorithm For Smart Street Lights, Zulkifli Ishak, Wan Siti Halimatul Munirah Wan Ahmad, Nurul Asyikin Mohamed Radzi, Suhaila Sulaiman, Noor Emilia Ramli
Turkish Journal of Electrical Engineering and Computer Sciences
The smart street light (SSL) system is an emerging technology in which a street light is equipped withan advanced control system for dimming and turning the light on or off. SSL also improves the maintenance work byproviding an enhanced inventory, which includes Global Positioning System (GPS) coordinates that can be retrieved froma GPS-enabled SSL. However, GPS coordinates may be inaccurate due to human error and GPS inaccuracy. This workproposes new algorithms for identifying human error and GPS inaccuracy in SSL installation by using distance analysisand the solving point-in-polygon method. The algorithms are important for inventory and maintenance purposes. Faultylight poles …
The Nearest Polyhedral Convex Conic Regions For High-Dimensional Classification, Hakan Çevi̇kalp, Emre Çi̇men, Gürkan Öztürk
The Nearest Polyhedral Convex Conic Regions For High-Dimensional Classification, Hakan Çevi̇kalp, Emre Çi̇men, Gürkan Öztürk
Turkish Journal of Electrical Engineering and Computer Sciences
In the nearest-convex-model type classifiers, each class in the training set is approximated with a convexclass model, and a test sample is assigned to a class based on the shortest distance from the test sample to these classmodels. In this paper, we propose new methods for approximating the distances from test samples to the convex regionsspanned by training samples of classes. To this end, we approximate each class region with a polyhedral convex conicregion by utilizing polyhedral conic functions (PCFs) and its extension, extended PCFs. Then, we derive the necessary formulations for computing the distances from test samples to these …
A Step-Down Isolated Three-Phase Igbt Boost Pfc Rectifier Using A Novel Controlalgorithm With A Novel Start-Up Method, Hüseyi̇n Köse, Mehmet Ti̇mur Aydemi̇r
A Step-Down Isolated Three-Phase Igbt Boost Pfc Rectifier Using A Novel Controlalgorithm With A Novel Start-Up Method, Hüseyi̇n Köse, Mehmet Ti̇mur Aydemi̇r
Turkish Journal of Electrical Engineering and Computer Sciences
For some industrial converter applications such as battery chargers, a DC/DC converter is needed to stepdown the high DC (direct current) voltages generated by PWM (pulse with modulated) rectifiers to lower voltage levelssuch as 110V/220V. These both complicate the design and decrease the efficiency. In this paper, a novel topology thatincludes a step-down transformer and a novel control algorithm is proposed. The proposed current, which is synchronized,look-up table based, sinusoidal PWM control method (CS-LUT-SPWM method) using switching frequency-orientedsynchronization (SWFOS) results in a very fast PWM generation and stable operation. Finally, a new thyristor-basedstart-up circuit providing safe operation when there is …
Subjective Analysis Of Social Distance Monitoring Using Yolo V3 Architecture Andcrowd Tracking System, Muhammed Murat Özbek, Mustafa Syed, İlkay Öksüz
Subjective Analysis Of Social Distance Monitoring Using Yolo V3 Architecture Andcrowd Tracking System, Muhammed Murat Özbek, Mustafa Syed, İlkay Öksüz
Turkish Journal of Electrical Engineering and Computer Sciences
The lethal infection, World Health Organization (WHO) reported coronavirus (COVID-19) as a pandemic.Lack of proper vaccine, low levels of immunity against COVID-19 has led to vulnerability of the human beings. Due tolack of efficient vaccine treatment, the only options left to fight against this pandemic are lockdown and social distance.This work offers an autonomous monitoring system on social distancing using deep learning techniques. The proposedarchitecture tracks the humans on roads and calculates their distance between each other. This surveillance detects thefurore violation of social distance utilizing CCTV cameras. The proposed framework uses YOLO v3 object-detectionmodel built on COCO dataset and …
Design Of The Fractional Order Internal Model Controller Using The Swarmintelligence Techniques For The Coupled Tank System, Sateesh Kumar Vavilala, Vinopraba Thirumavalavan, Radhakrishnan Thota, Sivakumaran Natarajan
Design Of The Fractional Order Internal Model Controller Using The Swarmintelligence Techniques For The Coupled Tank System, Sateesh Kumar Vavilala, Vinopraba Thirumavalavan, Radhakrishnan Thota, Sivakumaran Natarajan
Turkish Journal of Electrical Engineering and Computer Sciences
The coupled tank system (comprising two tanks) is used in the chemical industries, water treatment plantsetc. Level control of the coupled tank system is a common problem in the process control industry. This work proposes afractional order internal model controller (FOIMC) with a higher order fractional filter for the level control of the coupledtank system. A first order plus delay time (FOPDT) model of the system is used in the controller design. FOIMC hasadvantages like robustness to changes in the system gain and extended stability margins. The proposed higher orderfractional filter makes the controller physically realizable and quickly roll off …
New Fail Operational Powernet Methods And Topologies For Automated Drivingwith Electric Vehicle, Ahmet Kiliç
New Fail Operational Powernet Methods And Topologies For Automated Drivingwith Electric Vehicle, Ahmet Kiliç
Turkish Journal of Electrical Engineering and Computer Sciences
Electric mobility and automation are important drivers for the future of the automotive industry. Thisrequires an extremely high level of safety, reliability, and efficiency of the energy supply in the vehicle compared to the stateof the art. It is not possible to fulfill these requirements with today's energy supply. To meet these requirements, a fault-operational, scalable powernet is needed. In this paper, a new methodology is presented for the development of powernetfor automated driving with electric vehicle. The new method enables the development of new fail operational powernettopologies, early detection of failures in powernet components and the fulfillment of automated …
A Deep Neural Network Classifier For P300 Bci Speller Based On Cohen's Classtime-Frequency Distribution, Hamed Ghazikhani, Modjtaba Rouhani
A Deep Neural Network Classifier For P300 Bci Speller Based On Cohen's Classtime-Frequency Distribution, Hamed Ghazikhani, Modjtaba Rouhani
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a new method of predicting the P300 component of an electroencephalography (EEG)signal to recognize the characters in a P300 brain-computer interface (BCI) speller accurately. This method consistsof a deep learning model and the nonlinear time-frequency features. It is believed that the combination of the deepmodel network and extracting the nonlinear features of the EEG led this research to a better prediction of the P300and, therefore, character recognition. Cohen's class distribution is used in order to extract the nonlinear features of theEEG. Evaluating all of the kernels, Butterworth found to be more informative and it produced better results. …
Optimal Directional Overcurrent Relay Coordination Based On Computationalintelligence Technique: A Review, Suzana Pil Ramli, Muhammad Usama, Hazlie Mokhlis, Wei Ru Wong, Muhamad Hatta Hussain, Munir Azam Muhammad, Nurulafiqah Nadzirah Mansor
Optimal Directional Overcurrent Relay Coordination Based On Computationalintelligence Technique: A Review, Suzana Pil Ramli, Muhammad Usama, Hazlie Mokhlis, Wei Ru Wong, Muhamad Hatta Hussain, Munir Azam Muhammad, Nurulafiqah Nadzirah Mansor
Turkish Journal of Electrical Engineering and Computer Sciences
An exponential increase in diverse load demand in the last decade has influenced the integration of more power plants into the power system. This increases the fault current due to the bidirectional flow of current, resulting in unwanted tripping of the relays if not properly coordinated. Therefore, it is imperative to ensure the installation of relays in the grid being able to sense the fault current from any direction (i.e. upstream or downstream). This can be accomplished by introducing an optimal directional overcurrent relay (DOCR) coordination scheme into the system. This paper presents an in-depth review of the applications of …
A Geodesic Deployment And Radial Shaped Clustering (Rsc) Algorithm Withstatistical Aggregation In Sensor Networks, Lalitha Krishnasamy, Thangarajan Ramasamy, Rajesh Kumar Dhanaraj, Poongodi Chinnasamy
A Geodesic Deployment And Radial Shaped Clustering (Rsc) Algorithm Withstatistical Aggregation In Sensor Networks, Lalitha Krishnasamy, Thangarajan Ramasamy, Rajesh Kumar Dhanaraj, Poongodi Chinnasamy
Turkish Journal of Electrical Engineering and Computer Sciences
Wireless sensor networks (WSN) comprise a large number of connected tiny or small sensor devices to sense physical phenomenon. In WSN, prolonging the network's lifetime is a biggest challenge due to absence of power harvesting facility and irreplaceable batteries of the sensor devices. Clustering is one of the widely accepted and standard technique to solve the energy issues faced in WSN. In addition to clustering, the shape of the deployment area also plays the major role especially for large scale sensor deployment. This paper proposes a radial shaped clustering (RSC) algorithm with angular inclination routing. The radial shaped deployed area …
A Cross-Space Cascading Failure Hazard Assessment Method Consideringbetweenness Centrality And Power Loss, Ruzhi Xu, Dawei Chen, Qizhuo Zong, Jia Luo
A Cross-Space Cascading Failure Hazard Assessment Method Consideringbetweenness Centrality And Power Loss, Ruzhi Xu, Dawei Chen, Qizhuo Zong, Jia Luo
Turkish Journal of Electrical Engineering and Computer Sciences
In order to accurately assess the hazard caused by cross-space cascading failure in the cyber-physical power system, we propose a quantitative assessment method. This method builds a comprehensive framework of assessment that takes into account the betweenness centrality of attack graph and the consequences of failure. The betweenness centrality of each node in the attack graph is used to characterize the frequency of failure. By calculating the number of all nodes on each attack path, the frequency of a certain fault is calculated. The power loss of physical node caused by each cross-space cascading failure is used to characterize the …
Model-Based Control For Second-Order Piezo Actuator System With Hysteresis Intime-Delay Environment, Saikat Kumar Shome, Sandip Jana, Arpita Mukherjee, Partha Bhattacharjee
Model-Based Control For Second-Order Piezo Actuator System With Hysteresis Intime-Delay Environment, Saikat Kumar Shome, Sandip Jana, Arpita Mukherjee, Partha Bhattacharjee
Turkish Journal of Electrical Engineering and Computer Sciences
Piezo actuated systems are promising solutions for precision positioning applications. In this paper, a piezoelectric actuator is modeled as a second-order system using the Dahl hysteresis model and the system parameters have been identified from experimental data. The modified internal model control (M-IMC) approach is presented, which not only improves control performance but also reduces associated controller hardware resources. System dead time is approximated using first-order Padé expansion and the proposed Smith predictor-based M-IMC for piezoelectric actuators is seen to offer satisfactory stable control response even for plants with large dead time. The control performance of the M-IMC has been …
Obround Trees: Sparsity Enhanced Feedback Motion Planning Of Differential Driverobotic Systems, Mustafa Mert Ankarali
Obround Trees: Sparsity Enhanced Feedback Motion Planning Of Differential Driverobotic Systems, Mustafa Mert Ankarali
Turkish Journal of Electrical Engineering and Computer Sciences
Robot motion planning & control is one of the most critical and prevalent problems in the robotics community. Even though original motion planning algorithms had relied on "open-loop" strategies and policies, researchers and engineers have been focusing on feedback motion planning and control algorithms due to the uncertainties, such as process and sensor noise of autonomous robotic applications. Recently, several studies proposed some robust feedback motion planning strategies based on sparsely connected safe zones. In this class of planning and control policies, local control policy inside a single zone computes and feeds the control actions that can drive the robot …
In Depth Study Of Two Solutions For Common Mode Current Reduction In Six-Phasemachine Drive Inverters, Iman Abdoli, Alireza Lahooti Eshkevari, Ali Mosallanejad
In Depth Study Of Two Solutions For Common Mode Current Reduction In Six-Phasemachine Drive Inverters, Iman Abdoli, Alireza Lahooti Eshkevari, Ali Mosallanejad
Turkish Journal of Electrical Engineering and Computer Sciences
Common mode current (CMC) destroy machine bearings in the long run and increase electromagnetic interference. According to standards, the RMS value of CMC must be lower than 0.3A. Theories show that CMC is originated by applying zero states to the inverter. In this paper, the performance of two solutions in reducing CMC for six-phase machines is investigated. In the first solution, the traditional six-phase inverter is modified by adding two serial power switches on its input terminal. This method is an extended version of a method that has been presented for three-phase inverters, reduces CMC by optimizing the circuit structure. …
A Fuzzy Expert System For Predicting The Mortality Of Covid'19, Monika Mangla, Nonita Sharma, Poonam Mittal
A Fuzzy Expert System For Predicting The Mortality Of Covid'19, Monika Mangla, Nonita Sharma, Poonam Mittal
Turkish Journal of Electrical Engineering and Computer Sciences
The COVID-19 pandemic has had a widespread impact on health and economy across the globe. It is leading to a huge number of deaths per day. Few researchers have been attracted to analyzing the mortality rate of COVID-19 from various perspectives. During the research, it has become evident that these fatalities are not only caused by COVID19, but they are also affected by some other factors. The authors of this paper aim to encompass three important types of factors viz. risk factors, clinical factors, and miscellaneous factors that influence the mortality of COVID-19. This manuscript presents a rule-based model under …
New Hyperchaotic System With Single Nonlinearity, Its Electronic Circuit Andencryption Design Based On Current Conveyor, Anitha Karthikeyan, Serdar Çi̇çek, Karthikeyan Rajagopal, Prakash Duraisamy, Ashokkumar Srinivasan
New Hyperchaotic System With Single Nonlinearity, Its Electronic Circuit Andencryption Design Based On Current Conveyor, Anitha Karthikeyan, Serdar Çi̇çek, Karthikeyan Rajagopal, Prakash Duraisamy, Ashokkumar Srinivasan
Turkish Journal of Electrical Engineering and Computer Sciences
Nowadays, hyperchaotic system (HCSs) have been started to be used in engineering applications because they have complex dynamics, randomness, and high sensitivity. For this purpose, HCSs with different features have been introduced in the literature. In this work, a new HCS with a single discontinuous nonlinearity is introduced and analyzed. The proposed system has one saddle focus equilibrium. When the dynamic properties and bifurcation graphics of the system are analyzed, it is determined that the proposed system exhibits the complex phenomenon of multistability. Moreover, analog electronic circuit design of the proposed system is performed with positive second-generation current conveyor. In …
Constrained Discrete-Time Optimal Control Of Uncertain Systems With Adaptivelyapunov Redesign, Oğuz Han Altintaş, Ali̇ Emre Turgut
Constrained Discrete-Time Optimal Control Of Uncertain Systems With Adaptivelyapunov Redesign, Oğuz Han Altintaş, Ali̇ Emre Turgut
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, the conventional estimation-based receding horizon control paradigm is enhanced by using functional approximation, the adaptive modifications on state estimation and convex projection notion from optimization theory. The mathematical formalism of parameter adaptation and uncertainty estimation procedure are based on the redesign of optimal state estimation in discrete-time. By using Lyapunov stability theory, it is shown that the online approximation of uncertainties acting on both physical system and state estimator can be obtained. Moreover, the convergence criteria for online parameter adaptation with fully matched and partially matched cases are presented and shown. In addition, it is shown that …
Design And Planning Of A Distribution System Using Renewable Technologies In Arural Area Of Pakistan, Abdur Rehman Yousaf, Ghulam Mujtaba, Muhammad Amjad, Zeeshan Rashid
Design And Planning Of A Distribution System Using Renewable Technologies In Arural Area Of Pakistan, Abdur Rehman Yousaf, Ghulam Mujtaba, Muhammad Amjad, Zeeshan Rashid
Turkish Journal of Electrical Engineering and Computer Sciences
The inclusion of renewable energy sources in a distribution system to form a dispersed or decentralized generation network has gained tremendous progress in recent years. The architecture of the distribution system has the potential to serve as a microgrid during an islanding operation connected directly to the load center while excited fully by renewable technologies. This paper deals with planning and designing of a medium voltage power distribution system in a rural area of Pakistan affluent with abundant reserves of renewable sources of electricity. Two types of distribution system architectures, namely radial and ring systems, are simulated using a power …
Image Forgery Detection Based On Fusion Of Lightweight Deep Learning Models, Amit Doegar, Srinidhi Hiriyannaiah, Siddesh Gaddadevara Matt, Srinivasa Krishnarajanagar Gopaliyengar, Maitreyee Dutta
Image Forgery Detection Based On Fusion Of Lightweight Deep Learning Models, Amit Doegar, Srinidhi Hiriyannaiah, Siddesh Gaddadevara Matt, Srinivasa Krishnarajanagar Gopaliyengar, Maitreyee Dutta
Turkish Journal of Electrical Engineering and Computer Sciences
Image forgery detection is one of the key challenges in various real time applications, social media and online information platforms. The conventional methods of detection based on the traces of image manipulations are limited to the scope of predefined assumptions like hand-crafted features, size and contrast. In this paper, we propose a fusion based decision approach for image forgery detection. The fusion of decision is based on the lightweight deep learning models namely SqueezeNet, MobileNetV2 and ShuffleNet. The fusion decision system is implemented in two phases. First, the pretrained weights of the lightweight deep learning models are used to evaluate …
Area-Delay Efficient Radix-4 8×8 Booth Multiplier For Dsp Applications, Subodh Singhal, Sujit Patel, Anurag Mahajan, Gaurav Saxena
Area-Delay Efficient Radix-4 8×8 Booth Multiplier For Dsp Applications, Subodh Singhal, Sujit Patel, Anurag Mahajan, Gaurav Saxena
Turkish Journal of Electrical Engineering and Computer Sciences
Booth multiplier is the key component in portable very large-scale integration (VSLI) systems enabled with signal and image processing applications. The area, delay, and energy are the major constraints in these systems. Therefore, in this paper, a detailed analysis of the state-of-the-art Booth multiplier architecture and its various internal units are presented to find the scope of optimization. Based on the finding of analysis, optimized new binary to 2's complement (B2C), Booth encoder-cum-selector type-1 and type-2, and partial product addition units are proposed. Furthermore, using these optimized units, an efficient parallel radix-4 8×8 Booth multiplier architecture is proposed. The simulation …
Comparative Review Of Disk Type And Unconventional Transverse Flux Machines:Performance Analysis, Erhan Tuncel, Emi̇n Yildiriz
Comparative Review Of Disk Type And Unconventional Transverse Flux Machines:Performance Analysis, Erhan Tuncel, Emi̇n Yildiriz
Turkish Journal of Electrical Engineering and Computer Sciences
Transverse flux machines (TFM) can be designed with high pole numbers, so they are very useful in directdrive systems with high torque density. Although many TFM models have been proposed to date, no detailed classification and comparison has been made before. Conventional TFMs have a high power and torque density, but low power factors and high cogging torques have prevented them from being widely used. However, especially with the new disk type TFMs proposed in recent years and the methods developed, these drawbacks have been reduced. In this paper, the TFMs proposed in recent years have been classified and their …
Legendre-Wavelet Embedded Neurofuzzy Feedback Linearization Based Controlscheme For Phevs Charging Station In A Microgrid, Muhammad Awais, Laiq Khan, Saghir Ahmad, Sidra Mumtaz, Rabiah Badar, Shafaat Ullah
Legendre-Wavelet Embedded Neurofuzzy Feedback Linearization Based Controlscheme For Phevs Charging Station In A Microgrid, Muhammad Awais, Laiq Khan, Saghir Ahmad, Sidra Mumtaz, Rabiah Badar, Shafaat Ullah
Turkish Journal of Electrical Engineering and Computer Sciences
The immense emergence of plug-in hybrid electric vehicles (PHEVs) is envisioned in the future. The rapid proliferation of PHEVs and their charging triggers intense surges in the load during load peak hours. A sophisticated controlled charging station is developed for PHEVs to alleviate grid load during peak demand hours. A novel feedback linearization embedded full recurrent adaptive NeuroFuzzy Legendre wavelet control (FBL-FRANF-Leg-WC) technique is employed to control the charging of PHEVs. The antecedent part of the NeuroFuzzy framework is based on recurrent Gaussian membership function while the consequent part comprises of recurrent Legendre wavelet. The charging station is integrated into …
Analyzing Students' Experience In Programming With Computational Thinkingthrough Competitive, Physical, And Tactile Games: The Quadrilateral Methodapproach, M Ahsan Habib, Raja Jamilah Raja Yusof, Siti Salwah Salim, Asmiza Abdul Sani, Hazrina Sofian, Aishah Abu Bakar
Analyzing Students' Experience In Programming With Computational Thinkingthrough Competitive, Physical, And Tactile Games: The Quadrilateral Methodapproach, M Ahsan Habib, Raja Jamilah Raja Yusof, Siti Salwah Salim, Asmiza Abdul Sani, Hazrina Sofian, Aishah Abu Bakar
Turkish Journal of Electrical Engineering and Computer Sciences
The lack of computational thinking (CT) skills can be one of the reasons why students find themselves having difficulties in writing a good program. Therefore, understanding how CT skills can be developed is essential. This research explores how CT skills can be developed for programming through competitive, physical, and tactile games. The CT elements in this research focus on four major programming concepts, which are decomposition, pattern recognition, abstraction, and algorithmic thinking. We have conducted game activities through several algorithms that include sorting, swapping, and graph algorithms and analyzed how the game affects the student experience (SX) in understanding the …