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Articles 1 - 30 of 230
Full-Text Articles in Physical Sciences and Mathematics
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
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 …
Retinal Vessel Segmentation Using Modified Symmetrical Local Threshold, Umar Özgünalp
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 …
Time Series Forecasting On Multivariate Solar Radiation Data Using Deep Learning (Lstm), Murat Ci̇han Sorkun, Özlem Durmaz İncel, Christophe Paoli
Time Series Forecasting On Multivariate Solar Radiation Data Using Deep Learning (Lstm), Murat Ci̇han Sorkun, Özlem Durmaz İncel, Christophe Paoli
Turkish Journal of Electrical Engineering and Computer Sciences
Energy management is an emerging problem nowadays and utilization of renewable energy sources is an efficient solution. Solar radiation is an important source for electricity generation. For effective utilization, it is important to know precisely the amount from different sources and at different horizons: minutes, hours, and days. Depending on the horizon, two main classes of methods can be used to forecast the solar radiation: statistical time series forecasting methods for short to midterm horizons and numerical weather prediction methods for medium- to long-term horizons. Although statistical time series forecasting methods are utilized in the literature, there are a limited …
On The Automorphisms And Isomorphisms Of Mds Matrices And Their Efficient Implementations, Muharrem Tolga Sakalli, Sedat Akleylek, Kemal Akkanat, Vincent Rijmen
On The Automorphisms And Isomorphisms Of Mds Matrices And Their Efficient Implementations, Muharrem Tolga Sakalli, Sedat Akleylek, Kemal Akkanat, Vincent Rijmen
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we explicitly define the automorphisms of MDS matrices over the same binary extension field. By extending this idea, we present the isomorphisms between MDS matrices over $\mathbb{F}_{2^{m}}$ and MDS matrices over $\mathbb{F}_{2^{mt}}$, where $t \ge 1$ and $m>1$, which preserves the software implementation properties in view of XOR operations and table lookups of any given MDS matrix over $\mathbb{F}_{2^{m}}$. Then we propose a novel method to obtain distinct functions related to these automorphisms and isomorphisms to be used in generating isomorphic MDS matrices (new MDS matrices in view of implementation properties) using the existing ones. The …
A Compact Wideband Series Linear Dielectric Resonator Array Antenna, Yazeed Qasayneh, Abdullulah Almuhaisen, Talha Yazdani
A Compact Wideband Series Linear Dielectric Resonator Array Antenna, Yazeed Qasayneh, Abdullulah Almuhaisen, Talha Yazdani
Turkish Journal of Electrical Engineering and Computer Sciences
This communication presents a miniaturised series linear wideband array of notched rectangular dielectric resonator antennas that operate in the band IEEE 802.11a. Three dielectric resonators (DRs) were excited through the aperture slots coupled with a microstrip feed. To improve the array gain, the aperture slots were placed based on the attributes related to the standing-wave ratio on a short-ended microstrip feeder to obtain optimal joint power for the DRs, while the bandwidth was improved using the notched rectangular DRs. An equivalent impedance model of the proposed array was postulated to provide physical insight into the array resonance behaviour. The impedance …
A Power And Area Efficient Approximate Carry Skip Adder For Error Resilient Applications, Sujit Patel, Bharat Garg, Shireesh Kumar Rai
A Power And Area Efficient Approximate Carry Skip Adder For Error Resilient Applications, Sujit Patel, Bharat Garg, Shireesh Kumar Rai
Turkish Journal of Electrical Engineering and Computer Sciences
The compute-intensive multimedia applications on portable devices require power and area efficient arithmetic units. The adder is a prime building block of these arithmetic units and limits the overall performance. Therefore, this paper analyzes the logic operations of the state-of-the-art adders and presents a novel low complexity adder segment with new carry prediction logic by removing the redundant logic and sharing the common operations. Further, a new power and area efficient approximate carry skip (PAEA-CSK) adder is proposed using the novel adder segment. The effectiveness of the proposed PAEA-CSK adder is evaluated and compared over the existing adders by implementing …
Performance Improvement Of Induction Motor Drives With Model-Based Predictive Torque Control, Fati̇h Korkmaz
Performance Improvement Of Induction Motor Drives With Model-Based Predictive Torque Control, Fati̇h Korkmaz
Turkish Journal of Electrical Engineering and Computer Sciences
One of the most important advantages of using modeling and simulation software in design and control engineering is the ability to predict system behavior within specified conditions. This paper presents a novel error vector-based control algorithm that aims to reduce torque ripples predicting flux and torque errors in a conventional vector-controlled induction motor. For this purpose, a new control model has been developed that envisages flux change by applying probabilistic space vectors' torque and flux control. In the proposed predictive control algorithm, flux and torque errors are calculated for each candidate voltage vector. Thus, the optimal output voltage vector that …
A Novel Chaos-Based Modulation Scheme: Adaptive Threshold Level Chaotic On-Offkeying For Increased Ber Performance, Kenan Altun, Eni̇s Günay
A Novel Chaos-Based Modulation Scheme: Adaptive Threshold Level Chaotic On-Offkeying For Increased Ber Performance, Kenan Altun, Eni̇s Günay
Turkish Journal of Electrical Engineering and Computer Sciences
A novel modulation scheme called adaptive threshold level-chaotic on?off keying (ATL-COOK) is proposed. This scheme is applied to direct chaotic communication (DCC) systems where the chaotic signals are used as carrier signals. The objective of the proposed adaptive method is to increase the low BER versus SNR performance caused by the constant threshold voltage level. In the proposed method, the communication signal received by the receiver circuits was defined as a Dirac delta function and a comparison signal was obtained from this signal. Then the BER versus SNR performance was analyzed and compared with that of various chaotic generator structures …
An Inter-Domain Attack Mitigating Solution, Gökhan Akin, Ozan Bük, Erdem Uçar
An Inter-Domain Attack Mitigating Solution, Gökhan Akin, Ozan Bük, Erdem Uçar
Turkish Journal of Electrical Engineering and Computer Sciences
Online services on the Internet are increasing day by day, and in parallel, the number of cyber-attacks is rapidly increasing. These attacks are not always about data theft, but they can cause severe damage by denial of service attacks. Intrusion Prevention System products that many organizations use at the border of their enterprise networks are not strong enough to protect against DoS attacks. The typical way to mitigate such attacks is to get support from a service provider. However, a service provider only provides solutions for the traffic originating from itself. If the source of attack is in another ISP …
Hyperheuristics For Explicit Resource Partitioning In Simultaneous Multithreadedprocessors, İsa Ahmet Güney, Kemal Poyraz, Gürhan Küçük, Ender Özcan
Hyperheuristics For Explicit Resource Partitioning In Simultaneous Multithreadedprocessors, İsa Ahmet Güney, Kemal Poyraz, Gürhan Küçük, Ender Özcan
Turkish Journal of Electrical Engineering and Computer Sciences
In simultaneous multithreaded (SMT) processors, various data path resources are concurrently shared by many threads. A few heuristic approaches that explicitly distribute those resources among threads with the goal of improved overall performance have already been proposed. A selection hyperheuristic is a high-level search methodology that mixes a predetermined set of heuristics in an iterative framework to utilize their strengths for solving a given problem instance. In this study, we propose a set of selection hyperheuristics for selecting and executing the heuristic with the best performance at a given stage. To the best of our knowledge, this is one of …
Piezoresistive Disposable Weight Sensor With Increased Sensitivity, Kuter Erdi̇l, Tuğçe Ayraç, Ömer Gökalp Akcan, Yi̇ği̇t Dağhan Gökdel
Piezoresistive Disposable Weight Sensor With Increased Sensitivity, Kuter Erdi̇l, Tuğçe Ayraç, Ömer Gökalp Akcan, Yi̇ği̇t Dağhan Gökdel
Turkish Journal of Electrical Engineering and Computer Sciences
This study presents the design, simulation, implementation, and experimental characterization of a paperbased perforated disposable weight sensor system with a double piezoresistive layer. The demonstrated system is designed to achieve highly sensitive weight sensing operations with low-cost materials. For that purpose, the main fabrication material of the proposed disposable sensor is selected as a 289 $\mu$m thick Strathmore 400 series Bristol paper. Approximately 48 $\mu$m thick piezoresistive graphite paste is coated onto both sides of the paper-based cantilever beam with the aim of acquiring more sensitive weight-sensing capability. Additionally, the proposed paper-based structure has rows of closely spaced perforations at …
A Fast Text Similarity Measure For Large Document Collections Using Multireference Cosine And Genetic Algorithm, Hamid Mohammadi, Seyed Hossein Khasteh
A Fast Text Similarity Measure For Large Document Collections Using Multireference Cosine And Genetic Algorithm, Hamid Mohammadi, Seyed Hossein Khasteh
Turkish Journal of Electrical Engineering and Computer Sciences
One of the critical factors that make a search engine fast and accurate is a concise and duplicate free index. In order to remove duplicate and near-duplicate (DND) documents from the index, a search engine needs a swift and reliable DND text document detection system. Traditional approaches to this problem, such as brute force comparisons or simple hash-based algorithms, are not suitable as they are not scalable and are not capable of detecting near-duplicate documents effectively. In this paper, a new signature-based approach to text similarity detection is introduced, which is fast, scalable, and reliable and needs less storage space. …
Development Of A Supervised Classification Method To Construct 2d Mineral Mapson Backscattered Electron Images, Mahmut Camalan, Mahmut Çavur
Development Of A Supervised Classification Method To Construct 2d Mineral Mapson Backscattered Electron Images, Mahmut Camalan, Mahmut Çavur
Turkish Journal of Electrical Engineering and Computer Sciences
The Mineral Liberation Analyzer (MLA) can be used to obtain mineral maps from backscattered electron (BSE) images of particles. This paper proposes an alternative methodology that includes random forest classification, a prospective machine learning algorithm, to develop mineral maps from BSE images. The results show that the overall accuracy and kappa statistic of the proposed method are 97% and 0.94, respectively, proving that random forest classification is accurate. The accuracy indicators also suggest that the proposed method may be applied to classify minerals with similar appearances under BSE imaging. Meanwhile, random forest predicts fewer middling particles with binary and ternary …
A Viable Snore Detection System: Hardware And Software Implementations, Ahmet Turgut Tuncer, Mehmet Bi̇lgen
A Viable Snore Detection System: Hardware And Software Implementations, Ahmet Turgut Tuncer, Mehmet Bi̇lgen
Turkish Journal of Electrical Engineering and Computer Sciences
A stand-alone, custom-made biomedical system was introduced for long-term monitoring of sleep and detection of snoring events. Commercially available electronic components were assembled for recording audio, pulse, and respiration signals. Its software was implemented for off-line processing of the acquired signals in C++ and MATLAB environments. The linear and nonlinear features of the signals were extracted and characterized using spectral energy distribution, entropy, and largest Lyapunov exponent (LLE). The performance of the system was evaluated with real physiological data gathered from 14 chronic snorers. Analysis of the cases indicated that the system identified the snoring events with an accuracy of …
Chemical Disease Relation Extraction Task Using Genetic Algorithm With Two Novelvoting Methods For Classifier Subset Selection, Stanley Chika Onye, Nazi̇fe Di̇mi̇li̇ler, Ari̇f Akkeleş
Chemical Disease Relation Extraction Task Using Genetic Algorithm With Two Novelvoting Methods For Classifier Subset Selection, Stanley Chika Onye, Nazi̇fe Di̇mi̇li̇ler, Ari̇f Akkeleş
Turkish Journal of Electrical Engineering and Computer Sciences
Biomedical relation extraction is an important preliminary step for knowledge discovery in the biomedical domain. This paper proposes a multiple classifier system (MCS) for the extraction of chemical-induced disease relations. A genetic algorithm (GA) is employed to select classifier ensembles from a pool of base classifiers. Moreover, the voting method used for combining the members of each of the ensembles is also selected during evolution in the GA framework. The performances of the MCSs are determined by the algorithms used for selecting the classifiers, the diversity among the selected classifiers, and the voting method used in the classifier combination. The …
Comparisons Of Extreme Learning Machine And Backpropagation-Based I-Vector Approach For Speaker Identification, Musab T S Al-Kaltakchi, Raid Rafi Omar Al-Nima, Mohammed A M Abdullah
Comparisons Of Extreme Learning Machine And Backpropagation-Based I-Vector Approach For Speaker Identification, Musab T S Al-Kaltakchi, Raid Rafi Omar Al-Nima, Mohammed A M Abdullah
Turkish Journal of Electrical Engineering and Computer Sciences
The extreme learning machine (ELM) is one of the machine learning applications used for regression and classification systems. In this paper, an extended comparison between an ELM and the backpropagation neural network (BPNN)-based i-vector is given in terms of a closed-set speaker identification task using 120 speakers from the TIMIT database. The system is composed of the mel frequency cepstal coefficient (MFCC) and power normalized cepstal coefficient (PNCC) approaches to form the feature extraction stage, while the cepstral mean variance normalization (CMVN) and feature warping are applied in order to mitigate the linear channel effect. The system is utilized with …
Peak Shaving And Technical Loss Minimization In Distribution Grids: Atime-Of-Use-Based Pricing Approach For Distribution Service Tariffs, Osman Bülent Tör, Mahmut Erkut Cebeci̇, Mehmet Koç, Saaed Teimourzadeh, Deren Atli, Simona Vasilica Oprea, Adela Bara
Peak Shaving And Technical Loss Minimization In Distribution Grids: Atime-Of-Use-Based Pricing Approach For Distribution Service Tariffs, Osman Bülent Tör, Mahmut Erkut Cebeci̇, Mehmet Koç, Saaed Teimourzadeh, Deren Atli, Simona Vasilica Oprea, Adela Bara
Turkish Journal of Electrical Engineering and Computer Sciences
Deployment of time-of-use (ToU)-based retail energy tariffs (i.e. tariff for energy consumption- not the tariff for distribution service) is a common practice to incentivize consumers to use more energy at off-peak times. Distribution service tariffs (DSTs) are usually time-independent, which results in insensitivity of load to the distribution service cost. However, DST can also be time-dependent, which is studied in this paper. This study presents a methodology to address the effect of ToU pricing (i.e. time-dependent) of DSTs on peak shaving and technical loss minimization in power distribution grids. Here, the main focus is to assess the level of consumers' …
Deep Neural Network Based M-Learning Model For Predicting Mobile Learners'performance, Muhammad Adnan, Asad Habib, Jawad Ashraf, Shafaq Mussadiq, Arsalan Ali
Deep Neural Network Based M-Learning Model For Predicting Mobile Learners'performance, Muhammad Adnan, Asad Habib, Jawad Ashraf, Shafaq Mussadiq, Arsalan Ali
Turkish Journal of Electrical Engineering and Computer Sciences
The use of deep learning (DL) techniques for mobile learning is an emerging field aimed at developing methods for finding mobile learners' learning behavior and exploring important learning features. The learning features (learning time, learning location, repetition rate, content types, learning performance, learning time duration, and so on) act as fuel to DL algorithms based on which DL algorithms can classify mobile learners into different learning groups. In this study, a powerful and efficient m-learning model is proposed based on DL techniques to model the learning process of m-learners. The proposed m-learning model determines the impact of independent learning features …
A High-Level And Adaptive Metaheuristic Selection Algorithm For Solving Highdimensional Bound-Constrained Continuous Optimization Problems, Osman Gökalp, Aybars Uğur
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 …
User Profiling For Tv Program Recommendation Based On Hybrid Televisionstandards Using Controlled Clustering With Genetic Algorithms And Artificial Neuralnetworks, İhsan Topalli, Selçuk Kilinç
User Profiling For Tv Program Recommendation Based On Hybrid Televisionstandards Using Controlled Clustering With Genetic Algorithms And Artificial Neuralnetworks, İhsan Topalli, Selçuk Kilinç
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, an earlier method proposed by the authors to make smart recommendations utilizing artificial intelligence and the latest technologies developed for the television area is expanded further using controlled clustering with genetic algorithms (CCGA). For this purpose, genetic algorithms (GAs), artificial neural networks (ANNs), and hybrid broadcast broadband television (HbbTV) are combined to get the users' television viewing habits and to create profiles. Then television programs are recommended to the users based on that profiling. The data gathered by the developed HbbTV application for previous studies are reused in this study. These data are employed to cluster users. …
A Spreadsheet-Based Decision Support System For Examination Timetabling, Mehmet Güray Güler, Ebru Geçi̇ci̇
A Spreadsheet-Based Decision Support System For Examination Timetabling, Mehmet Güray Güler, Ebru Geçi̇ci̇
Turkish Journal of Electrical Engineering and Computer Sciences
Examination timetabling is an inevitable problem of educational institutions. Each institution has its own particular limitations; however, the main structure is the same: assigning exams to time slots and classrooms. Several institutions solve the problem manually, but it becomes more difficult every year with increasing numbers of students and limited resources. There are many studies in the literature addressing the examination timetabling problem (ETP) and providing high quality solutions within reasonable amounts of time. Nevertheless, almost none of them can be used in practice since they are not converted into a decision support system (DSS). Commercial DSSs, on the other …
Two Novel Radar Detectors For Spiky Sea Clutter With The Presence Of Thermal Noise And Interfering Targets, Nouh Guidoum, Faouzi Soltani, Amar Mezache
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 …
On Efficient Computation Of Equilibrium Under Social Coalition Structures, Buğra Çaşkurlu, Özgün Eki̇ci̇, Fati̇h Erdem Kizilkaya
On Efficient Computation Of Equilibrium Under Social Coalition Structures, Buğra Çaşkurlu, Özgün Eki̇ci̇, Fati̇h Erdem Kizilkaya
Turkish Journal of Electrical Engineering and Computer Sciences
In game-theoretic settings the key notion of analysis is an equilibrium, which is a profile of agent strategies such that no viable coalition of agents can improve upon their coalitional welfare by jointly changing their strategies. A Nash equilibrium, where viable coalitions are only singletons, and a super strong equilibrium, where every coalition is deemed viable, are two extreme scenarios in regard to coalition formation. A recent trend in the literature is to consider equilibrium notions that allow for coalition formation in between these two extremes and which are suitable to model social coalition structures that arise in various real-life …
A New Semiempirical Model Determining The Dielectric Characteristics Of Citrusleaves For The Remote Sensing At C Band, Abdullah Genç, Habi̇b Doğan, İbrahi̇m Bahadir Başyi̇ği̇t
A New Semiempirical Model Determining The Dielectric Characteristics Of Citrusleaves For The Remote Sensing At C Band, Abdullah Genç, Habi̇b Doğan, İbrahi̇m Bahadir Başyi̇ği̇t
Turkish Journal of Electrical Engineering and Computer Sciences
Dielectric parameters (i.e. permittivity) are fundamental to the simulation, design, modeling, and developing of microwave applications. For targeted objects, the complex permittivity is an essential parameter that affects its characteristics of scattering and microwave radiation. Thus, in microwave remote sensing applications, the knowledge of the dielectric property of vegetable materials is used not only to detect planting areas for monitoring and to able to specify the growth stage of them in seasonal variations, but also to determine the water requirement of the plant for controlling (water stress). This paper focuses on determining the dielectric parameters of orange and lemon leaves, …
A Ga-Based Adaptive Mechanism For Sensorless Vector Control Of Induction Motor Drives For Urban Electric Vehicles, Asma Boulmane, Youssef Zidani, Driss Belkhayat, Marouane Bouchouirbat
A Ga-Based Adaptive Mechanism For Sensorless Vector Control Of Induction Motor Drives For Urban Electric Vehicles, Asma Boulmane, Youssef Zidani, Driss Belkhayat, Marouane Bouchouirbat
Turkish Journal of Electrical Engineering and Computer Sciences
Induction motors are more attractive to car manufacturers because they are more robust and more cost effective to maintain in comparison with other types of electric machines. The evolution of their control makes them more efficient and less expensive. However, a new control technique known as sensorless control is being used to simplify the implementation of electric machines in electric vehicles. This technique involves replacing the flux and speed sensors with an observer. The estimation of these elements is based on the measurement of currents and voltages. The main purpose of the present study is to design a novel robust …
Plane Wave Diffraction By Strip With An Integral Boundary Condition, Kami̇l Karaçuha, Vasil Tabatadze, Eldar Ismailovich Veliev
Plane Wave Diffraction By Strip With An Integral Boundary Condition, Kami̇l Karaçuha, Vasil Tabatadze, Eldar Ismailovich Veliev
Turkish Journal of Electrical Engineering and Computer Sciences
In this article, a new solution method is proposed for plane wave diffraction by a strip. On the surface of the strip, an integral boundary condition is used. The impedance of the strip is investigated. The theoretical and numerical analyses show that there is a relation between the complex-valued fractional order of the integral boundary condition and properties of the material such as the impedance. As a further study, the total radar cross-section is investigated using the proposed method.
Deep Reinforcement Learning For Acceptance Strategy In Bilateral Negotiations, Yousef Razeghi, Celal Ozan Berk Yavuz, Reyhan Aydoğan
Deep Reinforcement Learning For Acceptance Strategy In Bilateral Negotiations, Yousef Razeghi, Celal Ozan Berk Yavuz, Reyhan Aydoğan
Turkish Journal of Electrical Engineering and Computer Sciences
This paper introduces an acceptance strategy based on reinforcement learning for automated bilateral negotiation, where negotiating agents bargain on multiple issues in a variety of negotiation scenarios. Several acceptance strategies based on predefined rules have been introduced in the automated negotiation literature. Those rules mostly rely on some heuristics, which take time and/or utility into account. For some negotiation settings, an acceptance strategy solely based on a negotiation deadline might perform well; however, it might fail in another setting. Instead of following predefined acceptance rules, this paper presents an acceptance strategy that aims to learn whether to accept its opponent's …
Multiplicative-Additive Despeckling In Sar Images, Gülay Aksoy, Fati̇h Nar
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 …
Asymmetric Slope Compensation For Digital Hybrid Current Mode Control Of Athree-Level Flying Capacitor Buck Converter, Abdulkeri̇m Uğur, Murat Yilmaz
Asymmetric Slope Compensation For Digital Hybrid Current Mode Control Of Athree-Level Flying Capacitor Buck Converter, Abdulkeri̇m Uğur, Murat Yilmaz
Turkish Journal of Electrical Engineering and Computer Sciences
The three-level flying capacitor (3LFC) buck converter has the potential to provide better efficiency and higher power density as compared to the traditional buck converter. However, due to the flying capacitor?s instability issues, control is challenging. In this paper, the digital hybrid current mode (DHCM) control method, which combines the average and peak current mode control techniques, is modified and implemented to a 3LFC buck converter. For flying capacitor (FC) voltage balancing, a novel asymmetric slope compensation (ASC) technique is presented. The proposed ASC technique achieves FC voltage balancing by adjusting the slope compensation of the two switching pairs asymmetrically, …
Exploring The Power Of Supervised Learning Methods For Company Name Disambiguation In Microblog Posts, Nafi̇ye Polat, Ali̇ Çakmak, Rabi̇a Turan
Exploring The Power Of Supervised Learning Methods For Company Name Disambiguation In Microblog Posts, Nafi̇ye Polat, Ali̇ Çakmak, Rabi̇a Turan
Turkish Journal of Electrical Engineering and Computer Sciences
Twitter is an online social networking website where people can post short messages on any subject, and these messages become visible to other users. Users intentionally express their opinions about companies or products via microblogging texts. Analyzing such messages might help explore what customers think about company products, or what the broad feelings of customers are. Identifying tweets referring to products and companies is becoming an important tool recently. However, company names are often vague. Hence, the first step is to locate the messages that are relevant to a company. In this paper, we present a number of supervised learning …