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Full-Text Articles in Physical Sciences and Mathematics

The Impact Of Text Preprocessing On The Prediction Of Review Ratings, Muhi̇tti̇n Işik, Hasan Dağ Jan 2020

The Impact Of Text Preprocessing On The Prediction Of Review Ratings, Muhi̇tti̇n Işik, Hasan Dağ

Turkish Journal of Electrical Engineering and Computer Sciences

With the increase of e-commerce platforms and online applications, businessmen are looking to have a rating and review system through which they can easily reveal the feelings of customers related to their products and services. It is undeniable from the statistics that online ratings and reviews attract new customers as well as increase sales by means of providing confidence, ratification, opinions, comparisons, merchant credibility, etc. Although considerable research has been devoted to the sentiment analysis for review classification, rather less attention has been paid to the text preprocessing which is a crucial step in opinion mining especially if convenient preprocessing …


Analysis Of Condition Number And Position Estimation Error For Multiangulationposition Estimation System, Sa'id Musa Yarima, Ahmad Zuri Sha'ameri, Abdulmalik Shehu Yaro Jan 2020

Analysis Of Condition Number And Position Estimation Error For Multiangulationposition Estimation System, Sa'id Musa Yarima, Ahmad Zuri Sha'ameri, Abdulmalik Shehu Yaro

Turkish Journal of Electrical Engineering and Computer Sciences

A passive wireless positioning system could be used to detect the location of low-level airborne targets such as drones or unmanned aircraft systems from the electromagnetic emission detected at spatially deployed ground receiving stations (GRSs). The multiangulation system proposed in this paper makes use of the angle of arrival (AOA) of the transmitted signal from the target to estimate its position through a 2-stage process. The AOA is the positiondependent signal parameter (PDSP) obtained from the target emission in the first stage, and using the PDSP and GRSs, the target location is estimated in the second stage by the angulation …


Two Novel Radar Detectors For Spiky Sea Clutter With The Presence Of Thermal Noise And Interfering Targets, Nouh Guidoum, Faouzi Soltani, Amar Mezache Jan 2020

Two Novel Radar Detectors For Spiky Sea Clutter With The Presence Of Thermal Noise And Interfering Targets, Nouh Guidoum, Faouzi Soltani, Amar Mezache

Turkish Journal of Electrical Engineering and Computer Sciences

In the context of noncoherent detection and high-resolution maritime radar system with low grazing angle, new Constant False Alarm Rate (CFAR) decision rules are suggested for two Compound Gaussian (CG) clutters namely: The K distribution and the Compound Inverse Gaussian (CIG) distribution, which are considered among the most appropriate models for sea clutter. The proposed decision rules are then modified to deal with the presence of thermal noise and interfering targets. The proposed detectors are investigated on the basis of synthetic data as well as real data of the IPIX radar database. The obtained results exhibit a high probability of …


Selective Personalization And Group Profiles For Improved Web Search Personalization, Samira Karimi Mansoub, Gönenç Ercan, İlyas Çi̇çekli̇ Jan 2020

Selective Personalization And Group Profiles For Improved Web Search Personalization, Samira Karimi Mansoub, Gönenç Ercan, İlyas Çi̇çekli̇

Turkish Journal of Electrical Engineering and Computer Sciences

Personalization is a common technique used in Web search engines to improve the effectiveness of retrieval. While personalizing some queries yields significant improvements in user experience by providing a ranking in line with the user preferences, it fails to improve or even degrades the effectiveness for less ambiguous queries. A potential personalization metric could improve search engines by selectively applying personalization. One such measure, click entropy uses the query history and the clicked documents for the query, which might be sparse for some queries. In this article, the topic entropy measure is improved by integrating the user distribution into the …


An Optimized Fpga Design Of Inverse Quantization And Transform For Hevcdecoding Blocks And Validation In An Sw/Hw Environment, Ahmed Ben Atitallah, Manel Kammoun, Rabie Ben Atitallah Jan 2020

An Optimized Fpga Design Of Inverse Quantization And Transform For Hevcdecoding Blocks And Validation In An Sw/Hw Environment, Ahmed Ben Atitallah, Manel Kammoun, Rabie Ben Atitallah

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents an optimized hardware architecture of the inverse quantization and the inverse transform (IQ/IT) for a high-efficiency video coding (HEVC) decoder. Our highly parallel and pipelined architecture was designed to support all HEVC Transform Unit (TU) sizes: 4 × 4, 8 × 8, 16 × 16, and 32 × 32. The IQ/IT was described in the VHSIC hardware description language and synthesized to Xilinx XC7Z020 field-programmable gate array (FPGA) and to TSMC 180 nm standard-cell library. The throughput of the hardware architecture reached in the worst case a processing rate of up to 1080 p at 33 fps …


Finite-Time Dynamic Surface Approach To Nonlinear Systems With Mismatcheduncertainties, Guofa Sun, Yaming Xu Jan 2020

Finite-Time Dynamic Surface Approach To Nonlinear Systems With Mismatcheduncertainties, Guofa Sun, Yaming Xu

Turkish Journal of Electrical Engineering and Computer Sciences

This paper develops a finite-time dynamic surface control (DSC) scheme for nonlinear systems with mismatched uncertainties via a high-order sliding mode(HOSM) observer. By designing a second-order terminal sliding surface based on the estimated signals, an observer-based sliding mode control (SMC) is designed to counteract the mismatched uncertainties in each step of backstepping. The proposed DSC scheme exhibits the following two attractive features. One is the application of HOSM observer to deal with mismatched system uncertainty functions. This is very different from the traditional approximator-based adaptive methods in dealing with high-order uncertain nonlinear systems. The other is the finite-time convergence of …


Replica Bias Circuit For Common-Source Amplifier, Burak Kelleci̇ Jan 2020

Replica Bias Circuit For Common-Source Amplifier, Burak Kelleci̇

Turkish Journal of Electrical Engineering and Computer Sciences

A replica bias circuit to set the current of common-source amplifier to reduce the gain variations across process, voltage, and temperature (PVT) changes is proposed. The gain of a common-source amplifier is set by the load resistor and transistor transconductance which is set proportional to a resistor using a constant-gm bias circuit. The success of constant-gm biasing depends on the accuracy of copying of generated current to the transistor. The leakage current at the transistor gate due to the electrostatic discharge protection diodes prevents the matching of the common source transistor current to the constant-gm circuit current. A low-power replica …


A New Smart Networking Architecture For Container Network Functions, Gülsüm Atici, Pinar Bölük Jan 2020

A New Smart Networking Architecture For Container Network Functions, Gülsüm Atici, Pinar Bölük

Turkish Journal of Electrical Engineering and Computer Sciences

5G slices have challenging application demands from a wide variety of fields including high bandwidth, low latency and reliability. The requirements of the container network functions which are used in telecommunications are different from any other cloud native IT applications as they are used for data plane packet processing functions, together with control, signalling and media processing which have critical processing requirements. This study aims to discover high performing container networking solution by considering traffic loads and application types. The behaviour of several container cluster networking solutions -- Flannel, Weave, Libnetwork, Open Virtual Networking for Open vSwitch and Calico -- …


An Energy-Efficient Lightweight Security Protocol For Optimal Resource Provenance In Wireless Sensor Networks, Sujesh Lal, Joe Prathap P M Jan 2020

An Energy-Efficient Lightweight Security Protocol For Optimal Resource Provenance In Wireless Sensor Networks, Sujesh Lal, Joe Prathap P M

Turkish Journal of Electrical Engineering and Computer Sciences

Security of resource sharing and provenance is a major concern in wireless sensor networks(WSNs),wherethe intruders can easily inject malicious intermediate nodes for various personal gains. This selective forwarding attack may reduce the flow of resource sharing and throughput in the network. Most of the existing techniques are complex and do not provide sufficient security to sensor nodes with low energy. This paper proposes an energy-efficient and lightweight security protocol for optimal resource provenance in multihop WSNs and the Internet of things (IoT) network. The sharing of the resources between the sensor nodes indicates the strength of the mutual cooperation between …


Measurement Of Sound Velocity In Oil Wells Based On Fast Adaptive Median Filtering, Wei Zhou, Juan Liu, Liqun Gan Jan 2020

Measurement Of Sound Velocity In Oil Wells Based On Fast Adaptive Median Filtering, Wei Zhou, Juan Liu, Liqun Gan

Turkish Journal of Electrical Engineering and Computer Sciences

Measurement of sound velocity in oil wells has long been a challenging industrial issue due to the difficulty in obtaining clear oil pipe coupling waves in strong noise. In this paper, a novel sound velocity measurement method is developed for the dynamic liquid level of oil wells based on fast adaptive median filtering. First, to solve the noise interference problem in the reflected oil pipe coupling wave, a fast adaptive median filtering algorithm is proposed to obtain an accurate oil pipe coupling wave. Then a curve fitting method based on range discrete coefficient is developed to estimate the sound velocity …


A High-Level And Adaptive Metaheuristic Selection Algorithm For Solving Highdimensional Bound-Constrained Continuous Optimization Problems, Osman Gökalp, Aybars Uğur Jan 2020

A High-Level And Adaptive Metaheuristic Selection Algorithm For Solving Highdimensional Bound-Constrained Continuous Optimization Problems, Osman Gökalp, Aybars Uğur

Turkish Journal of Electrical Engineering and Computer Sciences

Metaheuristic algorithms are used to find sufficiently good solutions for the optimization problems that are not solvable in a polynomial time. Although metaheuristics offer a general problem-solving framework and can be applied to various types of optimization problems, their performances depend heavily on the problem to be solved. Thus, hybrid metaheuristics are used to combine strong parts of different algorithms. In this study, a novel adaptive metaheuristic selection algorithm is proposed for solving bound-constrained continuous optimization problems. The developed method hybridizes artificial bee colony, differential evolution, and particle swarm optimization at a high level where each algorithm works independently from …


Experimental And Predicted Xlpe Cable Insulation Properties Under Uvradiation, Abdallah Hedir, Ali Bechouche, Mustapha Moudoud, Madjid Teguar, Omar Lamrous, Sebastien Rondot Jan 2020

Experimental And Predicted Xlpe Cable Insulation Properties Under Uvradiation, Abdallah Hedir, Ali Bechouche, Mustapha Moudoud, Madjid Teguar, Omar Lamrous, Sebastien Rondot

Turkish Journal of Electrical Engineering and Computer Sciences

This paper deals with the behavior of the crosslinked polyethylene (XLPE) used as high-voltage power cable insulation under ultraviolet (UV) radiations. For this, XLPE samples have been irradiated for 240 h using low-pressure vapor fluorescent lamps. Electrical (surface and volume resistivities), mechanical (tensile strength, elongation at break and surface hardness) and physical (weight loss, water absorption, work of water adhesion and contact angle) tests have been first carried out. Experimental results show that the XLPE characteristics are affected by UV radiation. Indeed, a decline in surface resistivity, mechanical properties, and contact angle, and an increase in the water retention amount …


A Novel Genome Analysis Method With The Entropy-Based Numerical Techniqueusing Pretrained Convolutional Neural Networks, Bi̇hter Daş, Suat Toraman, İbrahi̇m Türkoğlu Jan 2020

A Novel Genome Analysis Method With The Entropy-Based Numerical Techniqueusing Pretrained Convolutional Neural Networks, Bi̇hter Daş, Suat Toraman, İbrahi̇m Türkoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

The identification of DNA sequences as exon and intron is a common problem in genome analysis. The methods used for feature extraction and mapping techniques for the digitization of sequences affect directly the solution of this problem. The existing mapping techniques are not enough to detect coding and noncoding regions in some genomes because the digital representation of each base in a DNA sequence with an integer does not fully reflect the structure of an original DNA sequence. In the entropy-based mapping technique, we could overcome this problem because the technique deepens distinction rates of exon regions, and better reflects …


Nonlocal Means Estimation Of Intrinsic Mode Functions For Speech Enhancement, Sagar Reddy Vumanthala, Bikshalu K Jan 2020

Nonlocal Means Estimation Of Intrinsic Mode Functions For Speech Enhancement, Sagar Reddy Vumanthala, Bikshalu K

Turkish Journal of Electrical Engineering and Computer Sciences

The main aim of this paper is to introduce a new approach to enhance speech signals by exploring the advantages of nonlocal means (NLM) estimation and empirical mode decomposition. NLM, a patch-based denoising method, is extensively used for two-dimensional signals like images. However, its use for one-dimensional signals has been attracting more attention recently. The NLM-based approach is quite useful for removing low-frequency noises based on nonlocal similarities present among samples of the signal. However, there is an issue of under averaging in the high-frequency regions. The temporal and spectral characteristics of the speech signal are changing markedly over time. …


Multiplicative-Additive Despeckling In Sar Images, Gülay Aksoy, Fati̇h Nar Jan 2020

Multiplicative-Additive Despeckling In Sar Images, Gülay Aksoy, Fati̇h Nar

Turkish Journal of Electrical Engineering and Computer Sciences

Visual and automatic analyses using synthetic aperture radar (SAR) images are challenging because of inherently formed speckle noise. Thus, reducing speckle noise in SAR images is an important research area for SAR image analysis. During speckle noise reduction, homogeneous regions should be smoothed while details such as edges and point scatterers need to be preserved. General speckle noise model contains gamma distributed multiplicative part which is dominant and Gaussian distributed additive part which is in low amount and mostly neglected in literature. In this study, a novel sparsity-driven speckle reduction method is proposed that takes both multiplicative noise model and …


Detection Of Bga Solder Defects From X-Ray Images Using Deep Neural Network, Ceren Türer Akdeni̇z, Zümray Ölmez, Tamer Ölmez Jan 2020

Detection Of Bga Solder Defects From X-Ray Images Using Deep Neural Network, Ceren Türer Akdeni̇z, Zümray Ölmez, Tamer Ölmez

Turkish Journal of Electrical Engineering and Computer Sciences

In the literature it is observed that complex image processing operations are used in the classification of Ball Grid Array (BGA) X-ray images, however high classification results were not achieved. In recent years, it has been shown that deep learning methods are very successful especially in classification problems. In this study, a new deep neural network (DNN) model is proposed to classify the BGA X-ray images. The proposed DNN model contains feature extractor layers and a minimum distance classifier. Since the proposed network consists of less number of layers (4 convolution layers and 1 fully connected layer), determination of the …


Connectivity Considerations For Mission Planning Of A Search And Rescue Drone Team, Evşen Yanmaz Adam Jan 2020

Connectivity Considerations For Mission Planning Of A Search And Rescue Drone Team, Evşen Yanmaz Adam

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we analyze the mission success performance and mission times of centralized, distributed, and hybrid path-planning methods for a drone team whose mission is to find a target and inform the ground control. We propose two methods that integrate connectivity into the search mission path decisions. We observe that even though the coverage path-planning leads to lower search times, when target connectivity is also required, schemes that incorporate end--end connectivity into path planning result in at least 50 % better mission times for small communication ranges and lower number of drones. Our results also indicate that methods to …


Fuzzy Genetic Based Dynamic Spectrum Allocation (Fgdsa) Approach For Cognitive Radio Sensor Networks, Ganesan Rajesh, Xavier Mercilin Raajini, Kulandairaj Martin Sagayam, Bharat Bhushan, Utku Kose Jan 2020

Fuzzy Genetic Based Dynamic Spectrum Allocation (Fgdsa) Approach For Cognitive Radio Sensor Networks, Ganesan Rajesh, Xavier Mercilin Raajini, Kulandairaj Martin Sagayam, Bharat Bhushan, Utku Kose

Turkish Journal of Electrical Engineering and Computer Sciences

Cognitive Radio Sensor Network (CRSN) is known as a distributed network of wireless cognitive radio sensor nodes. Such system senses an event signal and ensures collaborative dynamic communication processes over the spectrum bands. Here, the concept of Dynamic Spectrum Access (DSA) denes the method of reaching progressively to the unused range of spectrum band. As among the essential CRSN user types, the Primary User (PU) has the license to access the spectrum band. On the other hand, the Secondary User (SU) tries to access the unused spectrum eciently, by not disturbing the PU. Considering that issue, this study introduces a …


Wavelength Sensitivity Of Indium Tin Oxide On Surface Plasmon Resonance Angles, Antonio Ruiz, Carlos Villa Angulo, Ivan Olaf Hernandez-Fuentes Jan 2020

Wavelength Sensitivity Of Indium Tin Oxide On Surface Plasmon Resonance Angles, Antonio Ruiz, Carlos Villa Angulo, Ivan Olaf Hernandez-Fuentes

Turkish Journal of Electrical Engineering and Computer Sciences

Surface plasmon resonance (SPR) is a charge-density oscillation that occurs when a beam of p-polarized monochromatic light impinges with a greater angle than the critical angle in a dielectric-metal interface. Because of the high losses related to metals, the generated surface plasmon waves propagate with high attenuation in the visible and near-infrared spectral regions in most of the dielectric-metal interfaces. An alternative to reduce such losses is to use a transparent indium tin oxide (ITO) film. In this paper, we compared theoretical calculations and experimental measurements of the SPR angle $\theta_{SPR}$ on the interfaces of a borosilicate prism (Bp) and …


Mlcocoa: A Machine Learning-Based Congestion Control For Coap, Alper Kami̇l Demi̇r, Fati̇h Abut Jan 2020

Mlcocoa: A Machine Learning-Based Congestion Control For Coap, Alper Kami̇l Demi̇r, Fati̇h Abut

Turkish Journal of Electrical Engineering and Computer Sciences

Internet of Things (IoT) is a technological invention that has the potential to impact on how we live and how we work by connecting any device to the Internet. Consequently, a vast amount of novel applications will enhance our lives. Internet Engineering Task Force (IETF) standardized the Constrained Application Protocol (CoAP) to accommodate the application layer and network congestion needs of such IoT networks. CoAP is designed to be very simple where it employs a genuine congestion control (CC) mechanism, named as default CoAP CC leveraging basic binary exponential backoff. Yet efficient, default CoAP CC does not always utilize the …


Optimization Of Real-Time Wireless Sensor Based Big Data With Deep Autoencoder Network: A Tourism Sector Application With Distributed Computing, Beki̇r Aksoy, Utku Kose Jan 2020

Optimization Of Real-Time Wireless Sensor Based Big Data With Deep Autoencoder Network: A Tourism Sector Application With Distributed Computing, Beki̇r Aksoy, Utku Kose

Turkish Journal of Electrical Engineering and Computer Sciences

Internet usage has increased rapidly with the development of information communication technologies. The increase in internet usage led to the growth of data volumes on the internet and the emergence of the big data concept. Therefore, it has become even more important to analyze the data and make it meaningful. In this study, 690 million queries and approximately 5.9 quadrillion data collected daily from different servers were recorded on the Redis servers by using real-time big data analysis method and load balance structure for a company operating in the tourism sector. Here, wireless networks were used as a triggering factor …


A Review On Embedded Field Programmable Gate Array Architectures And Configuration Tools, Khouloud Bouaziz, Abdulfattah M. Obeid, Sonda Chtourou, Mohamed Abid Jan 2020

A Review On Embedded Field Programmable Gate Array Architectures And Configuration Tools, Khouloud Bouaziz, Abdulfattah M. Obeid, Sonda Chtourou, Mohamed Abid

Turkish Journal of Electrical Engineering and Computer Sciences

Nowadays, systems-on-chip have reached a level where nonrecurring engineering costs have become a great challenge due to the increase of design complexity and postfabrication errors. Embedded field programmable gate arrays (eFPGAs) represent a viable alternative to overcome these issues since they provide postmanufacturing flexibility that can reduce the number of chip redesigns and amortize chip fabrication cost. In this paper, we present an overview on eFPGAs and their architectures, computer aided design (CAD) tools, and design challenges. An eFPGA must be well-designed and accompanied by an optimized CAD tool suite to respond to target application's requirements in terms of power …


Simulation And Analysis Of Wind Turbine Radar Echo Based On 3-D Scattering Point Model, Jiangong Zhang, Bin Hao, Bo Tang, Li Huang, Jiawei Yang Jan 2020

Simulation And Analysis Of Wind Turbine Radar Echo Based On 3-D Scattering Point Model, Jiangong Zhang, Bin Hao, Bo Tang, Li Huang, Jiawei Yang

Turkish Journal of Electrical Engineering and Computer Sciences

Wind turbine (WT) arrays in wind farms can cause serious interference on nearby radar stations. This interference could be filtered out if wind turbine radar echo (WTRE) can be obtained accurately. Considering the singleness of in-field experiments, numerical simulation became the majority among such works, but few of them reached necessary accuracy. Therefore, we propose a solution method of WTRE based on three-dimensional (3-D) scattering point model. Firstly, we use the nonuniform rational B-spline to build the 3-D model of WT. Secondly, based on the method of moments (MoM), the Rao-Wilton-Gisson (RWG) basis function is adopted to discretize the integral …


Design Of A High Performance Narrowband Low Noise Amplifier Using An On-Chip Orthogonal Series Stacked Differential Fractal Inductor For 5g Applications, Sunil Kumar Tumma, Bheemarao Nistala Jan 2020

Design Of A High Performance Narrowband Low Noise Amplifier Using An On-Chip Orthogonal Series Stacked Differential Fractal Inductor For 5g Applications, Sunil Kumar Tumma, Bheemarao Nistala

Turkish Journal of Electrical Engineering and Computer Sciences

Inductors play a crucial role in the design of radio frequency integrated circuits (RFICs) and they typically consume a considerably large area and have a low-quality factor at high frequencies. The employment of fractal structure in on-chip inductors helps in improving the quality factor and also reduces the overall area besides improving the inductance value. In this paper, an orthogonal series stacked differential fractal inductor is proposed and the same is used to design a low noise amplifier (LNA) for 5G band (27--30 GHz) applications. The proposed inductor is fabricated on a multilayer printed circuit board and the measurement results …


A Novel Semisupervised Classification Method Via Membership And Polyhedral Conic Functions, Nur Uylaş Sati Jan 2020

A Novel Semisupervised Classification Method Via Membership And Polyhedral Conic Functions, Nur Uylaş Sati

Turkish Journal of Electrical Engineering and Computer Sciences

In real-world problems, finding sufficient labeled data for defining classification rules is very difficult. This paper suggests a new semisupervised multiclass classification method. In the initialization, new membership functions are defined by utilizing the labeled data?Äôs medoids and means. Then the unlabeled points are labeled with the class of the highest membership value. In the supervised learning phase, separation via the polyhedral conic functions (PCFs) approach is improved by using defined membership values in the linear programming problem. The suggested algorithm is tested on real-world datasets and compared with the state-of-the-art semisupervised methods. The results obtained indicate that the suggested …


Retinal Vessel Segmentation Using Modified Symmetrical Local Threshold, Umar Özgünalp Jan 2020

Retinal Vessel Segmentation Using Modified Symmetrical Local Threshold, Umar Özgünalp

Turkish Journal of Electrical Engineering and Computer Sciences

Retinal vessel segmentation is important for the identification of many diseases including glaucoma, hypertensive retinopathy, diabetes, and hypertension. Moreover, retinal vessel diameter is associated with cardiovascular mortality. Accurate detection of blood vessels improves the detection of exudates in color fundus images, as well as detection of the retinal nerve, optic disc, or fovea. A retinal vessel is a darker stripe on a lighter background. Thus, the objective is very similar to the lane detection task for intelligent vehicles. A lane on a road is a light stripe on a darker background (i.e. asphalt). For lane detection, the symmetrical local threshold …


Integrated Topic Modeling And Sentiment Analysis: A Review Rating Prediction Approach For Recommender Systems, Anbazhagan Mahadevan, Michael Arock Jan 2020

Integrated Topic Modeling And Sentiment Analysis: A Review Rating Prediction Approach For Recommender Systems, Anbazhagan Mahadevan, Michael Arock

Turkish Journal of Electrical Engineering and Computer Sciences

Recommender systems (RSs) are running behind E-commerce websites to recommend items that are likely to be bought by users. Most of the existing RSs are relying on mere star ratings while making recommendations. However, ratings alone cannot help RSs make accurate recommendations, as they cannot properly capture sentiments expressed towards various aspects of the items. The other rich and expressive source of information available that can help make accurate recommendations is user reviews. Because of their voluminous nature, reviews lead to the information overloading problem. Hence, drawing out the user opinion from reviews is a decisive job. Therefore, this paper …


Detailed Modeling Of A Thermoelectric Generator For Maximum Power Point Tracking, Hayati̇ Mamur, Yusuf Çoban Jan 2020

Detailed Modeling Of A Thermoelectric Generator For Maximum Power Point Tracking, Hayati̇ Mamur, Yusuf Çoban

Turkish Journal of Electrical Engineering and Computer Sciences

Thermoelectric generators (TEGs) are used in small power applications to generate electrical energy from waste heats. Maximum power is obtained when the connected load to the ends of TEGs matches their internal resistance. However, impedance matching cannot always be ensured. Therefore, TEGs operate at lower efficiency. For this reason, maximum power point tracking (MPPT) algorithms are utilized. In this study, both TEGs and a boost converter with MPPT were modeled together. Detailed modeling, simulation, and verification of TEGs depending on the Seebeck coefficient, the hot/cold side temperatures, and the number of modules in MATLAB/Simulink were carried out. In addition, a …


Fuzzy C-Means Directional Clustering (Fcmdc) Algorithm Using Trigonometric Approximation, Orhan Kesemen, Özge Tezel, Eda Özkul, Buğra Kaan Ti̇ryaki̇ Jan 2020

Fuzzy C-Means Directional Clustering (Fcmdc) Algorithm Using Trigonometric Approximation, Orhan Kesemen, Özge Tezel, Eda Özkul, Buğra Kaan Ti̇ryaki̇

Turkish Journal of Electrical Engineering and Computer Sciences

Cluster analysis is widely used in data analysis. Statistical data analysis is generally performed on the linear data. If the data has directional structure, classical statistical methods cannot be applied directly to it. This study aims to improve a new directional clustering algorithm which is based on trigonometric approximation. The trigonometric approximation is used for both descriptive statistics and clustering of directional data. In this paper, the fuzzy clustering algorithms (FCD and FCM4DD) improved for directional data and the proposed method are carried out on some numerical and real data examples, and the simulation results are presented. Consequently, these results …


Consumer Loans' First Payment Default Detection: A Predictive Model, Utku Koç, Türkan Sevgi̇li̇ Jan 2020

Consumer Loans' First Payment Default Detection: A Predictive Model, Utku Koç, Türkan Sevgi̇li̇

Turkish Journal of Electrical Engineering and Computer Sciences

A default loan (also called nonperforming loan) occurs when there is a failure to meet bank conditions and repayment cannot be made in accordance with the terms of the loan which has reached its maturity. In this study, we provide a predictive analysis of the consumer behavior concerning a loan?Äôs first payment default (FPD) using a real dataset of consumer loans with approximately 600,000 records from a bank. We use logistic regression, naive Bayes, support vector machine, and random forest on oversampled and undersampled data to build eight different models to predict FPD loans. A two-class random forest using undersampling …