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2021

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Articles 27361 - 27390 of 27876

Full-Text Articles in Physical Sciences and Mathematics

Robust Model Reference Adaptive Pi Controller Based Sliding Mode Control Forthree-Phase Grid Connected Photovoltaic Inverter, Mojtaba Moeti, Mehdi Asadi Jan 2021

Robust Model Reference Adaptive Pi Controller Based Sliding Mode Control Forthree-Phase Grid Connected Photovoltaic Inverter, Mojtaba Moeti, Mehdi Asadi

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, the design of a new robust model reference adaptive PI (MRAC-PI) current controller is proposed for a two-stage grid connected photovoltaic (PV) inverter. Perturb & observe (P&O) algorithm is implemented in the boost part in order to extract the maximum power from the PV array. Firstly, the current dynamics with considering the system uncertainties are written in dq frame and are simplified by employing a decoupling system. Then, the MRAC-PI controller is designed based on a sliding mode control (SMC) to improve the robustness of the controller under system uncertainties. The parameters of PI controller are tuned …

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Neurofuzzy Robust Backstepping Based Mppt Control For Photovoltaic System, Kamran Ali, Laiq Khan, Qudrat Khan, Shafaat Ullah, Naghmash Ali Jan 2021

Neurofuzzy Robust Backstepping Based Mppt Control For Photovoltaic System, Kamran Ali, Laiq Khan, Qudrat Khan, Shafaat Ullah, Naghmash Ali

Turkish Journal of Electrical Engineering and Computer Sciences

Linear maximum power point tracking (MPPT) techniques are unable to achieve the desired performance and efficiency under wide variation in atmospheric conditions (temperature and irradiance) and consequently the maximum power point (MPP). Hence, the design and implementation of a nonlinear MPPT controller is essential to address the problems associated with the variations of the MPP. In this research article, a new nonlinear robust backstepping-based MPPT control technique is proposed for a standalone PV array connected to a dynamic load, and its performance comparison with existing backstepping, integral backstepping and conventional proportional integral derivative (PID) and perturb and observe (P&O) based …

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A Counter Based Approach For Reducer Placement With Augmented Hadoop Rackawareness, Mir Wajahat Hussain, K Hemant Reddy, Diptendu Sinha Roy Jan 2021

A Counter Based Approach For Reducer Placement With Augmented Hadoop Rackawareness, Mir Wajahat Hussain, K Hemant Reddy, Diptendu Sinha Roy

Turkish Journal of Electrical Engineering and Computer Sciences

As the data-driven paradigm for intelligent systems design is gaining prominence, performance requirements have become very stringent, leading to numerous fine-tuned versions of Hadoop and its MapReduce programming model. However, very few researchers have investigated the effect of intelligent reducer placement on Hadoop's performance. This paper delves into this much ignored reducer placement phase for improving Hadoop's performance and proposes to spawn reduce phase of Hadoop tasks in an asynchronous fashion across nodes in a Hadoop cluster. The main contributions of this paper are: (i) to track when map phase of tasks are completed, (ii) to count the number of …

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Risk-Averse Optimal Bidding Strategy For A Wind Energy Portfolio Managerincluding Ev Parking Lots For Imbalance Mitigation, Alper Çi̇çek, Ozan Erdi̇nç Jan 2021

Risk-Averse Optimal Bidding Strategy For A Wind Energy Portfolio Managerincluding Ev Parking Lots For Imbalance Mitigation, Alper Çi̇çek, Ozan Erdi̇nç

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, an optimal bidding strategy for a wind energy portfolio manager (WEPM) including electricvehicle parking lots (EVPLs) that aims to maximize profits by trading in the day-ahead (DA) market and balancingmarket (BM) and through bilateral contracts, taking into account line capacities and risk management is proposed. Thementioned structure is modeled in mixed integer linear programming (MILP) framework, and the uncertainties regardingelectric vehicle (EV) behavior, electricity market data, wind power generation are captured via a stochastic approach. Todemonstrate the effectiveness of the model, several case studies are carried out considering Sweden and Turkey electricitymarket prices with different risk aversion …

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Development Of Majority Vote Ensemble Feature Selection Algorithm Augmentedwith Rank Allocation To Enhance Turkish Text Categorization, Emi̇n Borandağ, Akin Özçi̇ft, Yeşi̇m Kaygusuz Jan 2021

Development Of Majority Vote Ensemble Feature Selection Algorithm Augmentedwith Rank Allocation To Enhance Turkish Text Categorization, Emi̇n Borandağ, Akin Özçi̇ft, Yeşi̇m Kaygusuz

Turkish Journal of Electrical Engineering and Computer Sciences

The increase in the number of texts as digital documents from numerous sources such as customer reviews,news, and social media has made text categorization crucial in order to be able to manage the enormous amount ofdata. The high dimensional nature of these texts requires a preliminary feature selection task to reduce the featurespace with a potential increase in the prediction accuracy. In this study, we developed an ensemble feature selectionmethod, namely majority vote rank allocation, was developed for Turkish text categorization purposes. The methoduses a majority voting ensemble strategy in combination with a rank allocation approach to combine weak filters …

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Mismatch Error Shaping Of Dac Unit Elements In Multibit $\Delta$$\Sigma$ Modulators Using A Novel Unified Adc/Dac, Leila Sharifi, Omid Hashemipour Jan 2021

Mismatch Error Shaping Of Dac Unit Elements In Multibit $\Delta$$\Sigma$ Modulators Using A Novel Unified Adc/Dac, Leila Sharifi, Omid Hashemipour

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a unified analog to digital converter (ADC) and digital to analog converter (DAC) for multibit $\Delta\Sigma$ modulators. The unified ADC/DAC circuit provides error shaping for mismatches between DAC unit elements. Hence, the dynamic element matching (DEM) circuit or digital calibration is not required resulting in the area and power saving as well as the elimination of the excess loop delay introduced by DEM circuit. Incorporating a 6-bit unified ADC/DAC, the $\Delta\Sigma$ modulator achieves 16.15-bit resolution utilizing only a second order loop filter and oversampling ratio of 40. The proposed modulator is simulated in a 65-nm CMOS process. …

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Deep Learning Techniques Of Losses In Data Transmitted In Wirelesssensor Networks, Mevlüt Ersoy, Beki̇r Aksoy Jan 2021

Deep Learning Techniques Of Losses In Data Transmitted In Wirelesssensor Networks, Mevlüt Ersoy, Beki̇r Aksoy

Turkish Journal of Electrical Engineering and Computer Sciences

Wireless sensor network (WSN) systems are frequently used today as a result of rapid technological developments. Wireless sensor networks, which form the basis of the Internet of Things (IoT), have a wide range of use in theworld from education to health, and from military applications to home applications. It enables the data obtained fromthe sensors to be transferred between nodes with the help of end-to-end wireless protocols. In parallel with the increasingnumber of nodes in WSN, data tra?ic density also increases. Due to the limitations of the WSN network, lost packetrates also increase with increasing data tra?ic. In this study, …

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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 Jan 2021

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 …

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Ensemble Learning Of Multiview Cnn Models For Survival Time Prediction Of Braintumor Patients Using Multimodal Mri Scans, Abdela Ahmed Mossa, Ulus Çevi̇k Jan 2021

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 …

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Automated Classification Of Bi-Rads In Textual Mammography Reports, Mostafa Boroumandzadeh, Elham Parvinnia Jan 2021

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 …

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Improvements Of Torque Ripple Reduction In Dtc Im Drive Witharbitrary Number Of Voltage Intensities And Automatic Algorithm Modification, Marko Rosic, Sanja Antic, Milan Bebic Jan 2021

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 …

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An Adversarial Framework For Open-Set Human Action Recognition Usingskeleton Data, Özge Özti̇mur Karadağ Jan 2021

An Adversarial Framework For Open-Set Human Action Recognition Usingskeleton Data, Özge Özti̇mur Karadağ

Turkish Journal of Electrical Engineering and Computer Sciences

Human action recognition is a fundamental problem which is applied in various domains, and it is widelystudied in the literature. Majority of the studies model action recognition as a closed-set problem. However, in real-life applications it usually arises as an open-set problem where a set of actions are not available during training butare introduced to the system during testing. In this study, we propose an open-set action recognition system, humanaction recognition and novel action detection system (HARNAD), which consists of two stages and uses only 3D skeletoninformation. In the first stage, HARNAD recognizes a given action and in the second …

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A Multiple Sensor Fusion Based Drift Compensation Algorithm For Mecanumwheeled Mobile Robots, Abdurrahman Halabi̇, Mert Ezi̇m, Kansu Oğuz Canbek, Abdurrahman Eray Baran Jan 2021

A Multiple Sensor Fusion Based Drift Compensation Algorithm For Mecanumwheeled Mobile Robots, Abdurrahman Halabi̇, Mert Ezi̇m, Kansu Oğuz Canbek, Abdurrahman Eray Baran

Turkish Journal of Electrical Engineering and Computer Sciences

This paper investigates a multiple sensor fusion based drift compensation technique for a mecanum wheeledmobile robot platform. The mobile robot is equipped with high-precision encoders integrated to the wheels and fouraccelerometers placed on its chassis. The proposed algorithm combines the information from the encoders and theacceleration sensors to estimate the total drift in the acceleration dimension. The inner loop controller is designedutilizing a disturbance-observer-based acceleration control structure which is blind against the slipping motion of thewheels. The estimated drift acceleration from the sensor fusion is then mapped back to the joint space of the robot andused as additional compensation over …

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Energy-Efficient Virtual Infrastructure Based Geo-Nested Routing Protocol Forwireless Sensor Networks, Baranidharan Varadharajan, Sivaradje Gopalakrishnan, Kiruthiga Varadharajan, Karthikeyan Mani, Sathishkumar Kutralingam Jan 2021

Energy-Efficient Virtual Infrastructure Based Geo-Nested Routing Protocol Forwireless Sensor Networks, Baranidharan Varadharajan, Sivaradje Gopalakrishnan, Kiruthiga Varadharajan, Karthikeyan Mani, Sathishkumar Kutralingam

Turkish Journal of Electrical Engineering and Computer Sciences

The wireless sensor networks (WSN) are comprised of hundreds to thousands of compact and battery-operated sensor nodes. The deployed sensor nodes are widely used to sense the physical changes in the environment,which collect, aggregate, and transmit the information as data packets or static sink or monitoring station. Thedata transmission is very challenging under some extreme environments and applications. The efficient way of datatransmission is achieved by designing an energy-efficient routing protocol. The position of the sink nodes is broadcasted periodically to all other sensor nodes to forward the sensed data to the monitoring system or sink. The frequentbroadcasting of the …

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Multidirectional Power Flow In Three-Port Isolated Dc-Dc Converter For Multiplebattery Stacks, Chandra Sekhar Nalamati, Niranjan Kumar, Rajesh Gupta Jan 2021

Multidirectional Power Flow In Three-Port Isolated Dc-Dc Converter For Multiplebattery Stacks, Chandra Sekhar Nalamati, Niranjan Kumar, Rajesh Gupta

Turkish Journal of Electrical Engineering and Computer Sciences

The advances in the field of power electronics have created a superior platform for interfacing clean renewableresources with the ever-growing energy storage technology. In this paper, a multidirectional power flow operation in thethree-port isolated DC-DC converter (TBDC) topology has been demonstrated for interfacing different battery energystorage sections to increase the system reliability. Comparison of multiple battery integration with dual active bridge andTBDC has been presented. Converter analysis has been conducted using the Fourier series harmonic model and converterloss calculation is also presented. Power flow controller has been proposed for closed-loop control of the TBDC. Theperformance of the converter has been …

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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 Jan 2021

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 …

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Dynamic Issue Queue Capping For Simultaneous Multithreaded Processors, Merve Güney, Büşra Kuru, Sercan Sari, İsa Ahmet Güney, Gürhan Küçük Jan 2021

Dynamic Issue Queue Capping For Simultaneous Multithreaded Processors, Merve Güney, Büşra Kuru, Sercan Sari, İsa Ahmet Güney, Gürhan Küçük

Turkish Journal of Electrical Engineering and Computer Sciences

A simultaneous multithreaded (SMT) processor mixes multiple instruction streams in its superscalar out-of-order execution core for higher throughput. To achieve this, a superscalar processor is modified in such a way that someof its resources are duplicated and the rest is shared among multiple threads. The issue queue (IQ), which holds allwaiting instructions until they become ready and scheduled for execution, is among these shared resources. A baselineunmanaged IQ can give an unexpectedly low performance since a hungry thread can tie up most of the IQ entries.This type of scenario is also worse in terms of the fairness metric since some …

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An Evolutionary-Based Image Classification Approach Through Facial Attributes, Seli̇m Yilmaz, Cemi̇l Zalluhoğlu Jan 2021

An Evolutionary-Based Image Classification Approach Through Facial Attributes, Seli̇m Yilmaz, Cemi̇l Zalluhoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

With the recent developments in technology, there has been a significant increase in the studies on analysisof human faces. Through automatic analysis of faces, it is possible to know the gender, emotional state, and even theidentity of people from an image. Of them, identity or face recognition has became the most important task whichhas been studied for a long time now as it is crucial to take measurements for public security, credit card verification,criminal identification, and the like. In this study, we have proposed an evolutionary-based framework that relies ongenetic programming algorithm to evolve a binary- and multilabel image classifier …

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Swft: Subbands Wavelet For Local Features Transform Descriptor For Cornealdiseases Diagnosis, Samer Al-Salihi, Sezgi̇n Aydin, Nebras Hussein Jan 2021

Swft: Subbands Wavelet For Local Features Transform Descriptor For Cornealdiseases Diagnosis, Samer Al-Salihi, Sezgi̇n Aydin, Nebras Hussein

Turkish Journal of Electrical Engineering and Computer Sciences

Human cornea is the front see-through shield of the eye. It refracts light onto the retina to induce vision.Therefore, any defect in the cornea may lead to vision disturbance. This deficiency is estimated by sets of topographicalimages measured, and assessed by an ophthalmologist. Consequently, an important priority is the early and accuratediagnosis of diseases that may affect corneal integrity through the use of machine learning algorithms. Images producedby a Pentacam device can be subjected to rotation or some distortion during acquisition; therefore, accurate diagnosisrequires the use of local features in the image. Accordingly, a new algorithm called subbands wavelet for …

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Heuristic Based Binary Grasshopper Optimization Algorithm To Solve Unitcommitment Problem, Muhammad Shahid, Tahir Nadeem Malik, Ahsan Said Jan 2021

Heuristic Based Binary Grasshopper Optimization Algorithm To Solve Unitcommitment Problem, Muhammad Shahid, Tahir Nadeem Malik, Ahsan Said

Turkish Journal of Electrical Engineering and Computer Sciences

The unit commitment problem in power system is a highly nonlinear, nonconvex, multiconstrained, complex,highly dimensional, mixed integer and combinatorial generation selection problem. The phenomenon of committing anddecommitting represents a discrete problem that requires binary/discrete optimization techniques to tackle with unitcommitment optimization problem. The key functions of the unit commitment optimization problem involve decidingwhich units to commit and then to decide their optimum power (economic dispatch). This paper confers a binarygrasshopper optimization algorithm to solve the unit commitment optimization problem under multiple constraints.The grasshopper optimization algorithm is a metaheuristic, multiple solutions-based algorithm inspired by the naturalswarming behavior of grasshopper towards food. …

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A Novel Pulse Plethysmograph Signal Analysis Method For Identification Of Myocardial Infarction, Dilated Cardiomyopathy, And Hypertension, Muhammad Umar Khan, Sumair Aziz Jan 2021

A Novel Pulse Plethysmograph Signal Analysis Method For Identification Of Myocardial Infarction, Dilated Cardiomyopathy, And Hypertension, Muhammad Umar Khan, Sumair Aziz

Turkish Journal of Electrical Engineering and Computer Sciences

Cardiac diseases (CDs) are one of the leading causes of the growing global mortality rate. Early detectionof CDs is necessary to avoid a high increase in the mortality rate. Machine learning-based computer-aided diagnosisof CDs using various physiological signals has recently been used by researchers. Since pulse plethysmograph (PuPG)signal contains a wealth of information about cardiac pathologies, therefore, this paper presents an expert system designfor the automatic diagnosis of cardiac disorders like hypertension, dilated cardiomyopathy and myocardial infarctionusing a novel fingertip PuPG signal analysis. The proposed system first performs signal denoising of raw PuPG sensordata using discrete wavelet transform (DWT). After …

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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 Jan 2021

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 …

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Neural Relation Extraction: A Review, Mehmet Aydar, Özge Bozal, Furkan Özbay Jan 2021

Neural Relation Extraction: A Review, Mehmet Aydar, Özge Bozal, Furkan Özbay

Turkish Journal of Electrical Engineering and Computer Sciences

Neural relation extraction discovers semantic relations between entities from unstructured text using deeplearning methods. In this study, we make a clear categorization of the existing relation extraction methods in termsof data expressiveness and data supervision, and present a comprehensive and comparative review. We describe theevaluation methodologies and the datasets used for model assessment. We explicitly state the common challenges inrelation extraction task and point out the potential of the pretrained models to solve them. Accordingly, we investigateadditional research directions and improvement ideas in this field.

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A Novel Approach Of Order Diminution Using Time Moment Concept With Routharray And Salp Swarm Algorithm, Nafees Ahamad, Afzal Sikander Jan 2021

A Novel Approach Of Order Diminution Using Time Moment Concept With Routharray And Salp Swarm Algorithm, Nafees Ahamad, Afzal Sikander

Turkish Journal of Electrical Engineering and Computer Sciences

In control engineering, there may be two systems that have the same input-output characteristic with differentdegrees of complexity. This concept leads to order diminution(OD) of a large scale system. In this article, the authorspropose a new hybrid order diminution technique based on the time moment matching method with the Routh arrayconcept and a recently developed fast and accurate salp swarm optimization (SSO) technique. The proposed methodcombines the advantages of both the classical method of OD and the optimization technique. The unknown coe?icient ofthe divisor of the reduced system is obtained by exploring the time moment matching methodology with the Routh …

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Pfecc: A Precise Feedback-Based Explicit Congestion Control Algorithm In Nameddata Networking, Hui Li Jan 2021

Pfecc: A Precise Feedback-Based Explicit Congestion Control Algorithm In Nameddata Networking, Hui Li

Turkish Journal of Electrical Engineering and Computer Sciences

Named data networking (NDN), as a future Internet architecture that is a promising alternative to TCP/IPnetworks, has the new features of connectionless, in-network cache, and hop-by-hop forwarding, which makes thecongestion control algorithms of traditional TCP/IP networks unable to be directly applied to NDN. In addition, sincethe optimal size of the sending window cannot be determined, the existing window-based congestion control algorithmsgenerally use the AIMD-like window adjustment algorithm, which cannot achieve the optimal throughput. In thispaper, we propose a precise feedback-based, multipath-aware congestion control algorithm PFECC, which is inspiredby Accel-Brake Control algorithm. PFECC considers the influence of Interest flows, uses a …

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On The Outage Performance Of Swipt-Noma-Crs With Imperfect Sic And Csi, Ferdi̇ Kara Jan 2021

On The Outage Performance Of Swipt-Noma-Crs With Imperfect Sic And Csi, Ferdi̇ Kara

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a nonorthogonal multiple access based cooperative relaying system (NOMA-CRS) is consideredto increase spectral efficiency. Besides, the simultaneous wireless information and power transfer (SWIPT) is proposedfor the relay in NOMA-CRS. In SWIPT-NOMA-CRS, three different energy harvesting (EH) protocols, power sharing(PS), time sharing (TS) and ideal protocols are implemented. The outage performances of the SWIPT-NOMA-CRSare studied for all three EH protocols. In the analysis, to represent practical/reasonable scenarios, imperfect successiveinterference canceler (SIC) and imperfect channel state information (CSI) are taken into consideration. The derivedoutage probability (OP) expressions are validated via computer simulations. Besides, the OP for the benchmark scheme,NOMA-CRS …

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Subjective Analysis Of Social Distance Monitoring Using Yolo V3 Architecture Andcrowd Tracking System, Muhammed Murat Özbek, Mustafa Syed, İlkay Öksüz Jan 2021

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 …

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An Adaptive Element Division Algorithm For Accurate Evaluation Of Singular Andnear Singular Integrals In 3d, Hakan Bayindir, Besi̇m Baranoğlu, Ali̇ Yazici Jan 2021

An Adaptive Element Division Algorithm For Accurate Evaluation Of Singular Andnear Singular Integrals In 3d, Hakan Bayindir, Besi̇m Baranoğlu, Ali̇ Yazici

Turkish Journal of Electrical Engineering and Computer Sciences

An adaptive algorithm for evaluation of singular and near singular integrals in 3D is presented. The algorithmis based on successive adaptive/selective subdivisions of the element until a prescribed error criteria is met. For evaluatingthe integrals in each subdivision, Gauss quadrature is applied. The method is computationally simple, memory efficientand can be applied for both triangular and quadrilateral elements, including the elements with nonplanar and/or curvedsurfaces. To assess the method, several examples are discussed. It has shown that the algorithm performs well forsingular and near-singular integral examples presented in the paper and evaluates the integrals with very high accuracy.

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A Deep Neural Network Classifier For P300 Bci Speller Based On Cohen's Classtime-Frequency Distribution, Hamed Ghazikhani, Modjtaba Rouhani Jan 2021

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. …

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Relational-Grid-World: A Novel Relational Reasoning Environment And An Agentmodel For Relational Information Extraction, Faruk Küçüksubaşi, Eli̇f Sürer Jan 2021

Relational-Grid-World: A Novel Relational Reasoning Environment And An Agentmodel For Relational Information Extraction, Faruk Küçüksubaşi, Eli̇f Sürer

Turkish Journal of Electrical Engineering and Computer Sciences

Reinforcement learning (RL) agents are often designed specifically for a particular problem and they generallyhave uninterpretable working processes. Statistical methods-based agent algorithms can be improved in terms ofgeneralizability and interpretability using symbolic artificial intelligence (AI) tools such as logic programming. Inthis study, we present a model-free RL architecture that is supported with explicit relational representations of theenvironmental objects. For the first time, we use the PrediNet network architecture in a dynamic decision-making problemrather than image-based tasks, and multi-head dot-product attention network (MHDPA) as a baseline for performancecomparisons. We tested two networks in two environments -i.e., the baseline box-world environment and …

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