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Source Modelling And Stress Transfer Scenarios Of The October 30, 2020 Samos Earthquake: Seismotectonic Implications, Sotiris Sboras, Ilias Lazos, Stylianos Bitharis, Christos Pikridas, Dimitrios Galanakis, Aristeidis Fotiou, Alexandros Chatzipetros, Spyros Pavlides
Source Modelling And Stress Transfer Scenarios Of The October 30, 2020 Samos Earthquake: Seismotectonic Implications, Sotiris Sboras, Ilias Lazos, Stylianos Bitharis, Christos Pikridas, Dimitrios Galanakis, Aristeidis Fotiou, Alexandros Chatzipetros, Spyros Pavlides
Turkish Journal of Earth Sciences
On October 30, 2020, a strong earthquake (Mw6.6-7.0) occurred offshore, just north of Samos Island, causing life losses, injuries and damages, especially on the Turkish side. The broader area is characterized by a complex geodynamic setting with both rich seismic history and numerous active faults of different direction and kinematics. The first aim of this study is to define the seismic source of the mainshock, based on seismological and geodetic data (GPS measurements and originally processed GNSS records), as well as our field observations on Samos Island few days after the mainshock. The integration of this information leads to a …
Evaluation Of Occupational Accidents In Forestry In Europe And Turkey By K-Means Clustering Analysis, Anil Orhan Akay, Mustafa Akgül, Abdullah İlker Esi̇n, Murat Demi̇r, Necmetti̇n Şentürk, Tolga Öztürk
Evaluation Of Occupational Accidents In Forestry In Europe And Turkey By K-Means Clustering Analysis, Anil Orhan Akay, Mustafa Akgül, Abdullah İlker Esi̇n, Murat Demi̇r, Necmetti̇n Şentürk, Tolga Öztürk
Turkish Journal of Agriculture and Forestry
The incidence rate of occupational accidents is an important indicator of occupational safety performance. The aim of this study was to classify the similarities and differences among 23 European Union (EU) countries along with Turkey in terms of various occupational accident evaluation criteria. This was achieved using the k-means clustering method on data from the forestry and logging sector between 2008 and 2017. The occupational accident assessment criteria used in the study include the nonfatal male accident incidence rate, the nonfatal female accident incidence rate, the total (male + female) nonfatal accident incidence rate, and the total (male + female) …
Comparative Efficiency Of Five Mathematical Functions In Modelling The First Lactation Milk Yield Of Kankrej Cattle, Thiruvothur Venkatesan Raja, Achintya Kumar Das, Satish Kumar Rathee, Umesh Singh, Sushil Kumar, Bharat Singh Rathod, Harshad Panchasara
Comparative Efficiency Of Five Mathematical Functions In Modelling The First Lactation Milk Yield Of Kankrej Cattle, Thiruvothur Venkatesan Raja, Achintya Kumar Das, Satish Kumar Rathee, Umesh Singh, Sushil Kumar, Bharat Singh Rathod, Harshad Panchasara
Turkish Journal of Veterinary & Animal Sciences
Modelling of first lactation milk yield of Kankrej cattle was done using five different non-linear mathematical functions viz., exponential decline function (EDF), gamma function (GF), inverse polynomial function (IPF), mixed log function (MLF) and parabolic exponential function (PEF). We compared their efficiency in describing variations in first lactation milk yield of animals maintained under field conditions. A total of 3994 fortnightly daily milk records of 203 Kankrej cattle calved during the years between 2011 and 2017 at farmers? herds in the Banaskantha region of Gujarat State, India were utilized for the study. The PROC NLIN procedure of Statistical Analysis Software …
Cover And Contents
Turkish Journal of Veterinary & Animal Sciences
No abstract provided.
The Visceral Adiposity Index, Lipid Accumulation Product, And Plasma Atherogenicindex Are Associated With Subclinical Atherosclerosis In Patients With Newly Diagnosedacromegaly, Mustafa Özbek, Murat Çalapkulu, Sema Hepşen, Muhammed Erkam Sencar, Hayri̇ Bostan, İlknur Öztürk Ünsal, Erman Çakal
The Visceral Adiposity Index, Lipid Accumulation Product, And Plasma Atherogenicindex Are Associated With Subclinical Atherosclerosis In Patients With Newly Diagnosedacromegaly, Mustafa Özbek, Murat Çalapkulu, Sema Hepşen, Muhammed Erkam Sencar, Hayri̇ Bostan, İlknur Öztürk Ünsal, Erman Çakal
Turkish Journal of Medical Sciences
Background /aim: Acromegaly is a rare chronic endocrine disorder, the active form of which is associated with an increased risk of cardiovascular and metabolic disease. Therefore, early diagnosis and treatment of cardiovascular diseases in acromegaly patients are important in terms of morbidity and mortality. The aim of this study was to determine whether the visceral adiposity index (VAI), lipid accumulation product (LAP), and plasma atherogenic index (PAI) are early cardiovascular risk markers in patients with active acromegaly. Materials and methods: The study included 45 patients newly diagnosed with acromegaly and 45 age-sex matched healthy control subjects. The VAI, LAP, and …
Comparison Of Methods Used In Predicting Irrigation Performance Indicators, Si̇nan Kartal, Firat Arslan
Comparison Of Methods Used In Predicting Irrigation Performance Indicators, Si̇nan Kartal, Firat Arslan
Turkish Journal of Agriculture and Forestry
Decreasing availability of water and increasing consumption of it in recent years shows water management plans increase its value. Depending on water consumption in the current and previous years, it is important to predict water consumption in the coming years and make plans accordingly. Evaluation of the performance of water use in agriculture, identifying water resources that are most intensively used and prediction of the potential performance in the coming years have become increasingly important. Irrigation water management is of crucial importance for sustainable food security and needs to plan for saving water due to global warming and climate change …
Evaluation Of Systemic Involvement Of Coronavirus Disease 2019 Through Spleen; Size Andtexture Analysis, Abdussamet Batur, Abi̇di̇n Kilinçer, Fati̇h Ateş, Nazlim Aktuğ Demi̇r, Recai̇ Ergün
Evaluation Of Systemic Involvement Of Coronavirus Disease 2019 Through Spleen; Size Andtexture Analysis, Abdussamet Batur, Abi̇di̇n Kilinçer, Fati̇h Ateş, Nazlim Aktuğ Demi̇r, Recai̇ Ergün
Turkish Journal of Medical Sciences
Background/aim: To investigate the changes in the spleen size, parenchymal heterogeneity, and computed tomography (CT) texture analysis features of patients diagnosed with Coronavirus disease 2019 (COVID-19) Materials and methods: The size and parenchymal structure of the spleen in 91 patients who underwent thoracic CT examination due to COVID-19 were evaluated. For the evaluation of parenchymal heterogeneity, CT texture analysis was performed using dedicated software (Olea Medical, France). The texture analysis of each case consisted of 15 first-order intensity-based features, 17 gray level cooccurrence matrix-based features, and 9 gray level run length matrix-based features. Results: A total of 91 patients (45 …
$\Lambda_C \To \Lambda$ Form Factors In Lattice Qcd, Hüseyi̇n Bahti̇yar
$\Lambda_C \To \Lambda$ Form Factors In Lattice Qcd, Hüseyi̇n Bahti̇yar
Turkish Journal of Physics
Studying the semileptonic decays of charmed particles is prominent in testing the standard model of particle physics. Motivated by recent experimental progress in weak decays of the charm baryon sector, we study the form factors of $\Lambda_c \to \Lambda \ell^+ \nu$ transition on two flavor lattices. We compute two- and three-point functions, extract the dimensionless projected correlators, and combine them to form the Weinberg form factors. In the zero transferred momentum limit $f_1$, $f_2$ and $g_1$ form factors are found to be in agreement with other models, furthermore $f_3$ and $g_3$ form factors are comparable to model determinations. The $g_2$ …
Study Of The Average Transverse Sphericity In $Pp$ Collisions At Large Hadron Collider (Lhc) Energies, Uzma Tabassam, Safdar Abbas, Muhammad Anns Saif, Zain Ul Abidin, Yasir Ali
Study Of The Average Transverse Sphericity In $Pp$ Collisions At Large Hadron Collider (Lhc) Energies, Uzma Tabassam, Safdar Abbas, Muhammad Anns Saif, Zain Ul Abidin, Yasir Ali
Turkish Journal of Physics
In the current analysis we have reported the spectra of average transverse-sphericity as a function of multiplicity ($N_ch$) in $pp$ collisions for primary charged particles ($\pi^{+}, \pi^{-}, K^+, K^-, p$ and $\bar{p}$) in mid pseudo-rapidity of $ \eta < 0.8$ and in the kinematic transverse momentum range of $p_T > 0.5 \; GeV/c$ at $\sqrt{s_{NN}}$ = 0.9 and $7 \,TeV$. Two Monte Carlo event generators have been used for current analysis and the predictions of the model are compared to the results coming from the ALICE experiment based at the LHC. A detailed analysis has been carried out for three types of events (soft events, hard events and bulk events) categorized by …
Joint Carrier Frequency And Phase Offset Estimation Algorithm For Cpm-Dsssbased Secure Point-To-Point Communication, Saima Shehzadi, Farzana Kulsoom, Muhammad Zeeshan, Qasim Umar Khan, Shahzad Amin Sheikh
Joint Carrier Frequency And Phase Offset Estimation Algorithm For Cpm-Dsssbased Secure Point-To-Point Communication, Saima Shehzadi, Farzana Kulsoom, Muhammad Zeeshan, Qasim Umar Khan, Shahzad Amin Sheikh
Turkish Journal of Electrical Engineering and Computer Sciences
A point-to-point (P2P) communication system based on the CPM-DSSS scheme ensures reliability, security, and antijamming capabilities. However, for reliable detection of data carrier synchronization of CPM-DSSS based system is one of the requirements. This paper presents a joint algorithm for carrier frequency offset (CFO) and carrier phase offset (CPO) estimation for CPM-DSSS based P2P system. The results indicate that the proposed CFO estimator is unbiased and can accurately estimate a wide range of offsets. Moreover, the proposed algorithm is compared with another research work. The results show that the proposed CFO and CPO estimation algorithm outperforms its counterpart with a …
A Hybrid Numerical Model For Long-Range Electromagnetic Wave Propagation, Gül Yesa Altun, Özlem Özgün
A Hybrid Numerical Model For Long-Range Electromagnetic Wave Propagation, Gül Yesa Altun, Özlem Özgün
Turkish Journal of Electrical Engineering and Computer Sciences
A hybrid numerical model is presented for solving long range electromagnetic wave propagation problems involving objects on or above the ground surface by hybridizing the two-way split-step parabolic equation (2W-SSPE) method with the method of moments (MoM). The advantages of the proposed model are twofold: (i) It reduces the staircasing error in irregular terrain modeling, which usually occurs when the standard SSPE method is used alone. This is achieved by employing the MoM to more accurately obtain the scattered fields from slanted/curved surfaces. (ii) It enables the SSPE method to handle the problems involving objects above the Earth's surface, which …
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 …
Combination Of Classical And Statistical Approaches To Enhance The Fermentation Conditions And Increase The Yield Of Lipopeptide(S) By Pseudomonas Sp. Oxdc12: Its Partial Purification And Determining Antifungal Property, Vivek Chauhan, Vivek Dhiman, Shamsher S. Kanwar
Combination Of Classical And Statistical Approaches To Enhance The Fermentation Conditions And Increase The Yield Of Lipopeptide(S) By Pseudomonas Sp. Oxdc12: Its Partial Purification And Determining Antifungal Property, Vivek Chauhan, Vivek Dhiman, Shamsher S. Kanwar
Turkish Journal of Biology
Around 200 different lipopeptides (LPs) have been identified to date, most of which are produced via Bacillus and Pseudomonas species. The clinical nature of the lipopeptide (LP) has led to a big surge in its research. They show antimicrobial and antitumor activities due to which mass-scale production and purification of LPs are beneficial. Response surface methodology (RSM) approach has emerged as an alternative in the field of computational biology for optimizing the reaction parameters using statistical models. In the present study, Pseudomonas sp. strain OXDC12 was used for production and partial purification of LPs using Thin Layer Chromatography (TLC). The …
The Effect Of Weekend Curfews On Epidemics: A Monte Carlo Simulation, Hakan Kaygusuz, Ahmet Ni̇hat Berker
The Effect Of Weekend Curfews On Epidemics: A Monte Carlo Simulation, Hakan Kaygusuz, Ahmet Ni̇hat Berker
Turkish Journal of Biology
The ongoing COVID-19 pandemic is being responded with various methods, applying vaccines, experimental treatment options, total lockdowns or partial curfews. Weekend curfews are among the methods for reducing the number of infected persons, and this method is practically applied in some countries such as Turkey. In this study, the effect of weekend curfews on reducing the spread of a contagious disease, such as COVID-19, is modeled using a Monte Carlo algorithm with a hybrid lattice model. In the simulation setup, a fictional country with three towns and 26,610 citizens were used as a model. Results indicate that applying a weekend …
Detection Of Grain Yield Qtls In The Durum Population Lahn/Cham1 Tested Incontrasting Environments, Issame Farouk, Ahmad Alsaleh, Jihan Motowaj, Fatima Gaboun, Bouchra Belkadi, Abdelkarim Filali Maltouf, Zakaria Kehel, Ismahane Elouafi, Nasserelhaq Nsarellah, M. Miloudi Nachit
Detection Of Grain Yield Qtls In The Durum Population Lahn/Cham1 Tested Incontrasting Environments, Issame Farouk, Ahmad Alsaleh, Jihan Motowaj, Fatima Gaboun, Bouchra Belkadi, Abdelkarim Filali Maltouf, Zakaria Kehel, Ismahane Elouafi, Nasserelhaq Nsarellah, M. Miloudi Nachit
Turkish Journal of Biology
Durum wheat (Triticum turgidum L. var durum) is tetraploid wheat (AABB); it is the main source of semolina and other pasta products. Grain yield in wheat is quantitatively inherited and influenced by the environment. The genetic map construction constitutes the essential step in identifying quantitative trait loci (QTLs) linked to complex traits, such as grain yield. The study aimed to construct a genetic linkage map of two parents that are widely grown durum cultivars (Lahn and Cham1) in the Mediterranean basin, which is characterized by varying climate changes. The genetic linkage map of Lahn/Cham1 population consisted of 112 recombinant inbred …
Transcriptome Profiles Associated With Selenium-Deficiency-Dependent Oxidative Stress Identify Potential Diagnostic And Therapeutic Targets In Liver Cancer Cells, Damla Gözen, Deni̇z Cansen Kahraman, Kübra Narci, Huma Shehwana, Özlen Konu, Rengül Çeti̇n Atalay
Transcriptome Profiles Associated With Selenium-Deficiency-Dependent Oxidative Stress Identify Potential Diagnostic And Therapeutic Targets In Liver Cancer Cells, Damla Gözen, Deni̇z Cansen Kahraman, Kübra Narci, Huma Shehwana, Özlen Konu, Rengül Çeti̇n Atalay
Turkish Journal of Biology
Hepatocellular carcinoma (HCC) is one of the most common cancer types with high mortality rates and displays increased resistance to various stress conditions such as oxidative stress. Conventional therapies have low efficacies due to resistance and off-target effects in HCC. Here we aimed to analyze oxidative stress-related gene expression profiles of HCC cells and identify genes that could be crucial for novel diagnostic and therapeutic strategies. To identify important genes that cause resistance to reactive oxygen species (ROS), a model of oxidative stress upon selenium (Se) deficiency was utilized. The results of transcriptome-wide gene expression data were analyzed in which …
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 …