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Articles 181 - 202 of 202
Full-Text Articles in Physical Sciences and Mathematics
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 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 …
Optimal Coordination Of Directional Overcurrent Relay Based On Combination Ofimproved Particle Swarm Optimization And Linear Programming Consideringmultiple Characteristics Curve, Suzana Pil Ramli, Hazlie Mokhlis, Wei Ru Wong, Munir Azam Muhammad, Nurulafiqah Nadzirah Mansor, Muhamad Hatta Hussain
Optimal Coordination Of Directional Overcurrent Relay Based On Combination Ofimproved Particle Swarm Optimization And Linear Programming Consideringmultiple Characteristics Curve, Suzana Pil Ramli, Hazlie Mokhlis, Wei Ru Wong, Munir Azam Muhammad, Nurulafiqah Nadzirah Mansor, Muhamad Hatta Hussain
Turkish Journal of Electrical Engineering and Computer Sciences
Optimal coordination of directional over-current relays (DOCRs) is a crucial task in ensuring the security and reliability of power system network. In this paper, a hybridization of an improved particle swarm optimization and linear programming (IPSO-LP) is proposed to solve DOCRs coordination problem. The considered decision variables in the optimization are plug setting current, time multiplier setting, type of relay, and type of curve. By considering these parameters in the optimization, the best relay operating time can be determined. Furthermore, the proposed technique also considered the continuous values of pick-up current setting (PSC) and time setting multiplier (TMS). Test on …
Novel Fast Terminal Sliding Mode Controller With Current Constraint Forpermanent-Magnet Synchronous Motor, Yao Fang, Huifang Kong, Daoyuan Ding
Novel Fast Terminal Sliding Mode Controller With Current Constraint Forpermanent-Magnet Synchronous Motor, Yao Fang, Huifang Kong, Daoyuan Ding
Turkish Journal of Electrical Engineering and Computer Sciences
Under the noncascade structure, the balance between q-axis current constraint and dynamic performance in permanent-magnet synchronous motor system has become a critical problem. On the one hand, large transient current is required to provide high torque to achieve fast dynamic performance. On the other hand, current constraint becomes a state constraint problem, instead of governing q-axis reference current in the cascade structure directly. Aiming at this issue, a novel fast terminal sliding mode control (FTSMC)-based controller with current constraint is developed in this paper. The novelty of this scheme is related to the proposed penalty function based on interior point …
Distributed Denial Of Service Attack Detection In Cloud Computing Using Hybridextreme Learning Machine, Gopal Singh Kushwah, Virender Ranga
Distributed Denial Of Service Attack Detection In Cloud Computing Using Hybridextreme Learning Machine, Gopal Singh Kushwah, Virender Ranga
Turkish Journal of Electrical Engineering and Computer Sciences
One of the major security challenges in cloud computing is distributed denial of service (DDoS) attacks. In these attacks, multiple nodes are used to attack the cloud by sending huge traffic. This results in the unavailability of cloud services to legitimate users. In this research paper, a hybrid machine learning-based technique has been proposed to detect these attacks. The proposed technique is implemented by combining the extreme learning machine (ELM) model and the blackhole optimization algorithm. Various experiments have been performed with the help of four benchmark datasets namely, NSL KDD, ISCX IDS 2012, CICIDS2017, and CICDDoS2019, to evaluate the …
A Novel Hybrid Decision-Based Filter And Universal Edge-Based Logical Smoothingadd-On To Remove Impulsive Noise, Rajanbir Singh Ghumaan, Prateek Jeet Singh Sohi, Nikhil Sharma, Bharat Garg
A Novel Hybrid Decision-Based Filter And Universal Edge-Based Logical Smoothingadd-On To Remove Impulsive Noise, Rajanbir Singh Ghumaan, Prateek Jeet Singh Sohi, Nikhil Sharma, Bharat Garg
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a novel hybrid filter along with a universal extension to remove salt and pepper noise even at a very high noise density. The proposed filter initially specifies a threshold and then denoises the image using a combination of linear, nonlinear, and probabilistic techniques. Furthermore, to improve the quality, a universal add-on is presented which uses edge detection and smoothening techniques to brush out fine details from the restored image. To evaluate the efficacy, the proposed and existing filtering techniques are implemented in MATLAB and simulated with benchmark images. The simulation results show that the proposed filter is …
An Enhanced Bandwidth Disturbance Observer Based Control- S-Filter Approach, Mehmet Önder Efe, Coşku Kasnakoğlu
An Enhanced Bandwidth Disturbance Observer Based Control- S-Filter Approach, Mehmet Önder Efe, Coşku Kasnakoğlu
Turkish Journal of Electrical Engineering and Computer Sciences
A continuous time enhanced bandwidth disturbance observer based control (DOBC) scheme is proposed in this paper. The classical Q -filter is implemented in feedback form and a signum function is inserted into the loop. The loop with this modification becomes capable of detecting small magnitude matched disturbances and we present an in depth discussion of the stability and performance issues comparatively. The proposed approach is called S-filter approach and the results outperform the classical approach under certain conditions. The contribution of the current paper is to advance the subject area to nonlinear filters for DOBC loops with guaranteed stability and …
Clustering Ensemble Selection Based On The Extended Jaccard Measure, Hajar Khalili, Mohsen Rabbani, Ebrahim Akbari
Clustering Ensemble Selection Based On The Extended Jaccard Measure, Hajar Khalili, Mohsen Rabbani, Ebrahim Akbari
Turkish Journal of Electrical Engineering and Computer Sciences
Clustering ensemble selection has shown high efficiency in the improvement of the quality of clustering solutions. This technique comprises two important metrics: diversity and quality. It has been empirically proved that ensembles of higher effectiveness can be achieved through taking into consideration the diversity and quality simultaneously. However, the relationships between these two metrics in base clusterings have remained uncertain. This paper suggests a new hierarchical selection algorithm using a diversity/quality measure based on the Jaccard similarity measure. In the proposed algorithm, the selection of the subsets of the clustering partitions is done based on their diversity measures. The proposed …
Radar-Based Microwave Breast Cancer Detection System With A High-Performanceultrawide Band Antipodal Vivaldi Antenna, Hüseyi̇n Özmen, Muhammed Bahaddi̇n Kurt
Radar-Based Microwave Breast Cancer Detection System With A High-Performanceultrawide Band Antipodal Vivaldi Antenna, Hüseyi̇n Özmen, Muhammed Bahaddi̇n Kurt
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, a novel ultrawide band (UWB) antipodal Vivaldi antenna with three pairs of slots was designed to be used as a sensor in microwave imaging systems for breast cancer detection. The proposed antenna operates in UWB frequency range of 3.05-12.2 GHz. FR4 was used as a dielectric material and as a substrate for forming the antenna that has a compact size of 36 mm x 36 mm x 1.6 mm. Frequency and time domain performance of the proposed antenna have been investigated and results show that it meets the requirements for UWB radar applications with linear phase response, …
Scale-Invariant Histogram Of Oriented Gradients: Novel Approach For Pedestriandetection In Multiresolution Image Dataset, Sweta Panigrahi, Surya Narayana Raju Undi
Scale-Invariant Histogram Of Oriented Gradients: Novel Approach For Pedestriandetection In Multiresolution Image Dataset, Sweta Panigrahi, Surya Narayana Raju Undi
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes a scale-invariant histogram of oriented gradients (SI-HOG) for pedestrian detection. Most of the algorithms for pedestrian detection use the HOG as the basic feature and combine other features with the HOG to form the feature set, which is usually applied with a support vector machine (SVM). Hence, the HOG feature is the most efficient and fundamental feature for pedestrian detection. However, the HOG feature produces feature vectors of different lengths for different image resolutions; thus, the feature vectors are incomparable for the SVM. The proposed method forms a scale-space pyramid wherein the histogram bin is calculated. Thus, …
Robust And Efficient Ebg-Backed Wearable Antenna For Ism Applications, Ayesha Saeed, Asma Ejaz, Humayun Shahid, Yasar Amin, Hannu Tenhunen
Robust And Efficient Ebg-Backed Wearable Antenna For Ism Applications, Ayesha Saeed, Asma Ejaz, Humayun Shahid, Yasar Amin, Hannu Tenhunen
Turkish Journal of Electrical Engineering and Computer Sciences
A structurally compact, semiflexible wearable antenna composed of a distinctively miniaturized electromagnetic band gap (EBG) structure is presented in this work. Designed for body-centric applications in the 5.8 GHz band, the design draws heavily from a novel planar geometry realized on Rogers RT/duroid 5880 laminate with a compact physical footprint spanning lateral dimensions of $0.6$$\lambda$$_0$$\times$$0.06$$\lambda$$_0$. Incorporating a 2$\times$2 EBG structure at the rear of the proposed design ensures sufficient isolation between the body and the antenna, doing away with the performance degradation associated with high permittivity of the tissue layer. The peculiar antenna geometry allows for reduced backward radiation and …
Improved Online Sequential Extreme Learning Machine: Os-Celm, Olcay Tosun, Recep Eryi̇ği̇t
Improved Online Sequential Extreme Learning Machine: Os-Celm, Olcay Tosun, Recep Eryi̇ği̇t
Turkish Journal of Electrical Engineering and Computer Sciences
Online learning methods (OLM) have been gaining traction as a solution to classification problems because of rapid renewal and fast growth in volume of available data. ELM-based sequential learning (OS-ELM) is one of the most frequently used online learning methodologies partly due to fast training algorithm but suffers from inefficient use of its hidden layers due to the random assignment of the parameters of those layers. In this study, we propose an improved online learning model called online sequential constrained extreme learning machine (OS-CELM), which replaces the random assignment of those parameters with better generalization performance using the CELM method …
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, …
A Hybrid Convolutional Neural Network Approach For Feature Selection Anddisease Classification, Prajna Paramita Debata, Puspanjali Mohapatra
A Hybrid Convolutional Neural Network Approach For Feature Selection Anddisease Classification, Prajna Paramita Debata, Puspanjali Mohapatra
Turkish Journal of Electrical Engineering and Computer Sciences
: Many researchers have analyzed the high dimensional gene expression data for disease classification using several conventional and machine learning-based approaches, but still there exists some issues which make this task nontrivial. Due to the growing complexities of the unstructured data, the researchers focus on the deep learning approach, which is the latest form of machine learning algorithm. In the presented work, a kernel-based Fisher score (KFS) approach is implemented to extract the notable genes, and an improvised chaotic Jaya (CJaya) algorithm optimized convolutional neural network (CJaya-CNN) model is applied to classify high dimensional gene expression or microarray data. This …
Attention-Based End-To-End Cnn Framework For Content-Based X-Ray Imageretrieval, Şaban Öztürk, Adi Alhudhaif, Kemal Polat
Attention-Based End-To-End Cnn Framework For Content-Based X-Ray Imageretrieval, Şaban Öztürk, Adi Alhudhaif, Kemal Polat
Turkish Journal of Electrical Engineering and Computer Sciences
The widespread use of medical imaging devices allows deep analysis of diseases. However, the task of examining medical images increases the burden of specialist doctors. Computer-assisted systems provide an effective management tool that enables these images to be analyzed automatically. Although these tools are used for various purposes, today, they are moving towards retrieval systems to access increasing data quickly. In hospitals, the need for content-based image retrieval systems is seriously evident in order to store all images effectively and access them quickly when necessary. In this study, an attention-based end-to-end convolutional neural network (CNN)framework that can provide effective access …
Deep Learning-Based Covid-19 Detection System Using Pulmonary Ct Scans, Rajit Nair, Adi Alhudhaif, Deepika Koundal, Rumi Iqbal Doewes, Preeti Sharma
Deep Learning-Based Covid-19 Detection System Using Pulmonary Ct Scans, Rajit Nair, Adi Alhudhaif, Deepika Koundal, Rumi Iqbal Doewes, Preeti Sharma
Turkish Journal of Electrical Engineering and Computer Sciences
One of the most significant pandemics has been raised in the form of Coronavirus disease 2019 (COVID19). Many researchers have faced various types of challenges for finding the accurate model, which can automatically detect the COVID-19 using computed pulmonary tomography (CT) scans of the chest. This paper has also focused on the same area, and a fully automatic model has been developed, which can predict the COVID-19 using the chest CT scans. The performance of the proposed method has been evaluated by classifying the CT scans of community-acquired pneumonia (CAP) and other non-pneumonia. The proposed deep learning model is based …
Mri Based Genomic Analysis Of Glioma Using Three Pathway Deep Convolutionalneural Network For Idh Classification, Sonal Gore, Jayant Jagtap
Mri Based Genomic Analysis Of Glioma Using Three Pathway Deep Convolutionalneural Network For Idh Classification, Sonal Gore, Jayant Jagtap
Turkish Journal of Electrical Engineering and Computer Sciences
As per 2016 updates by World Health Organization (WHO) on cancer disease, gliomas are categorized and further treated based on genomic mutations. The imaging modalities support a complimentary but immediate noninvasive diagnosis of cancer based on genetic mutations. Our aim is to train a deep convolutional neural network for isocitrate dehydrogenase (IDH) genotyping of glioma by auto-extracting the most discriminative features from magnetic resonance imaging (MRI) volumes. MR imaging data of total 217 patients were obtained from The Cancer Imaging Archives (TCIA) of high and low-grade gliomas. A 3-pathway convolutional neural network was trained for IDH classification. The multipath neural …
Leukocyte Classification Based On Feature Selection Using Extra Trees Classifier: Atransfer Learning Approach, Diana Baby, Sujitha Juliet Devaraj, Jude Hemanth, Anishin Raj M M
Leukocyte Classification Based On Feature Selection Using Extra Trees Classifier: Atransfer Learning Approach, Diana Baby, Sujitha Juliet Devaraj, Jude Hemanth, Anishin Raj M M
Turkish Journal of Electrical Engineering and Computer Sciences
The criticality of investigating the white blood cell (WBC) count cannot be underestimated, as white blood cells are an important component of the body's defence system. From helping to diagnose hidden infections to insinuating the presence of comorbidities like immunodeficiency, an accurate white blood cell count can contribute significantly to shape a physician?s assessment. The manual process performed by the pathologists for the classification of WBCs is a time consuming and tedious task, which is further disadvantaged by a lack of accuracy. This study concentrates on the automatic detection and classification of WBC without data augmentation into four subtypes such …
Employing Deep Learning Architectures For Image-Based Automatic Cataractdiagnosis, Emrullah Acar, Ömer Türk, Ömer Faruk Ertuğrul, Erdoğan Aldemi̇r
Employing Deep Learning Architectures For Image-Based Automatic Cataractdiagnosis, Emrullah Acar, Ömer Türk, Ömer Faruk Ertuğrul, Erdoğan Aldemi̇r
Turkish Journal of Electrical Engineering and Computer Sciences
Various eye diseases affect the quality of human life severely and ultimately may result in complete vision loss. Ocular diseases manifest themselves through mostly visual indicators in the early or mature stages of the disease by showing abnormalities in optics disc, fovea, or other descriptive anatomical structures of the eye. Cataract is among the most harmful diseases that affects millions of people and the leading cause of public vision impairment. It shows major visual symptoms that can be employed for early detection before the hypermature stage. Automatic diagnosis systems intend to assist ophthalmological experts by mitigating the burden of manual …
New Normal: Cooperative Paradigm For Covid-19 Timely Detection Andcontainment Using Internet Of Things And Deep Learning, Farooque Hassan Kumbhar, Ali Hassan Syed, Soo Young Shin
New Normal: Cooperative Paradigm For Covid-19 Timely Detection Andcontainment Using Internet Of Things And Deep Learning, Farooque Hassan Kumbhar, Ali Hassan Syed, Soo Young Shin
Turkish Journal of Electrical Engineering and Computer Sciences
The spread of the novel coronavirus (COVID-19) has caused trillions of dollars of damages to the governments and health authorities by affecting the global economies. It is essential to identify, track and trace COVID-19 spread at its earliest detection. Timely action can not only reduce further spread but also help in providing an efficient medical response. Existing schemes rely on volunteer participation, and/or mobile traceability, which leads to delays in containing the spread. There is a need for an autonomous, connected, and centralized paradigm that can identify, trace and inform connected personals. We propose a novel connected Internet of Things …
Improved Cell Segmentation Using Deep Learning In Label-Free Optical Microscopyimages, Aydin Ayanzadeh, Özden Yalçin Özuysal, Devri̇m Pesen Okvur, Sevgi̇ Önal, Behçet Uğur Töreyi̇n, Devri̇m Ünay
Improved Cell Segmentation Using Deep Learning In Label-Free Optical Microscopyimages, Aydin Ayanzadeh, Özden Yalçin Özuysal, Devri̇m Pesen Okvur, Sevgi̇ Önal, Behçet Uğur Töreyi̇n, Devri̇m Ünay
Turkish Journal of Electrical Engineering and Computer Sciences
The recently popular deep neural networks (DNNs) have a significant effect on the improvement of segmentation accuracy from various perspectives, including robustness and completeness in comparison to conventional methods. We determined that the naive U-Net has some lacks in specific perspectives and there is high potential for further enhancements on the model. Therefore, we employed some modifications in different folds of the U-Net to overcome this problem. Based on the probable opportunity for improvement, we develop a novel architecture by using an alternative feature extractor in the encoder of U-Net and replacing the plain blocks with residual blocks in the …