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2018

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Articles 8821 - 8850 of 8951

Full-Text Articles in Engineering

Tunable Class-F High Power Amplifier At X-Band Using Gan Hemt, Osman Ceylan, Hasan Bülent Yağci, Selçuk Paker Jan 2018

Tunable Class-F High Power Amplifier At X-Band Using Gan Hemt, Osman Ceylan, Hasan Bülent Yağci, Selçuk Paker

Turkish Journal of Electrical Engineering and Computer Sciences

Class-F type amplification stands on proper termination of harmonics such as short for even harmonics and open for odd harmonics. Moreover, termination of only the first few harmonics is practical for high-frequency circuits, while obtaining satisfactory short and open terminations at high frequencies is a challenging design issue. In the present study, a topology of harmonics termination for Class-F load network with 2nd and 3rd harmonics and its relative analytical analysis are presented. The proposed output termination structure for Class-F type amplification provides an improved short termination of 2nd harmonic; therefore, the efficiency of the power amplifier increases. In addition, …

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Neuron Modeling: Estimating The Parameters Of A Neuron Model From Neural Spiking Data, Reşat Özgür Doruk Jan 2018

Neuron Modeling: Estimating The Parameters Of A Neuron Model From Neural Spiking Data, Reşat Özgür Doruk

Turkish Journal of Electrical Engineering and Computer Sciences

We present a modeling study aiming at the estimation of the parameters of a single neuron model from neural spiking data. The model receives a stimulus as input and provides the firing rate of the neuron as output. The neural spiking data will be obtained from point process simulation. The resultant data will be used in parameter estimation based on the inhomogeneous Poisson maximum likelihood method. The model will be stimulated by various forms of stimuli, which are modeled by a Fourier series (FS), exponential functions, and radial basis functions (RBFs). Tabulated results presenting cases with different sample sizes (# …

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An Efficient Structure For T-Cntfets With Intrinsic-N-Doped Impurity Distribution Pattern In Drain Region, Ali Naderi, Maryam Ghodrati Jan 2018

An Efficient Structure For T-Cntfets With Intrinsic-N-Doped Impurity Distribution Pattern In Drain Region, Ali Naderi, Maryam Ghodrati

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, by using impurity distribution engineering of drain region, an efficient structure is proposed for tunneling carbon nanotube field-effect transistors (T-CNTFETs). The drain region of the proposed structure consists of two parts. The impurity density of the part close to the channel is intrinsic and the other is n-type with constant density of 1 nm$^{-1}$. In conventional T-CNTFETs, heavily doped drain causes a spiky drop of potential energy around the channel to drain junction resulting in a pathway for carriers in the valence band to tunnel to the conduction band which means ambipolar behavior and large leakage current. …

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Diode Clamped Gate Driver-Based High Voltage Pulse Generator For Electroporation, Krishnaveni Subramani, Rajini Veeraraghavalu Jan 2018

Diode Clamped Gate Driver-Based High Voltage Pulse Generator For Electroporation, Krishnaveni Subramani, Rajini Veeraraghavalu

Turkish Journal of Electrical Engineering and Computer Sciences

Pulsed electric field technology is an emerging nonthermal food processing method. PEF food processing requires a high voltage pulse generator that produces high intensive pulses to be delivered to the food product. Innovation in semiconductor technology motivates researchers to modernize high voltage pulse generators to reduce the cost, size, and complexities in circuit operation and to increase the suitability for food processing since the last few decades. The present study aims to explore a high voltage pulse generator for electroporation study. The implemented high voltage pulse generator develops $\sim $1.62 kV with adjustable pulse widths of 0.62 $\mu $s and …

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Improved Transient Response Capacitor Less Low Dropout Regulator Employing Adaptive Bias And Bulk Modulation, Suresh Alapati, Sreehari Rao Patri Jan 2018

Improved Transient Response Capacitor Less Low Dropout Regulator Employing Adaptive Bias And Bulk Modulation, Suresh Alapati, Sreehari Rao Patri

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a low quiescent current, fast settling time, and adaptively biased capacitor less low-dropout (LDO) regulator. The topology involves a segmented pass transistor with bulk modulation and adaptively biased current control stages to improve the transient performance. The bulk modulation of the pass transistor assists in fast settling of the output voltage. The frequency compensation makes the LDO voltage regulator stable adaptively over load current transitions. In addition, the biasing stage is designed such that it adapts to the load transitions while consuming the quiescent current abstemiously. This arrangement further improves settling time to be within 1 µs …

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Pattern Diversity Antenna For On-Body And Off-Body Wban Links, Sema Dumanli Jan 2018

Pattern Diversity Antenna For On-Body And Off-Body Wban Links, Sema Dumanli

Turkish Journal of Electrical Engineering and Computer Sciences

Maintaining the quality and the reliability of a wireless body area network (WBAN) has a variety of challenges, one of which is the design of the on-body antenna. The on-body antenna often forms both on-body and off-body links and needs to have an application-specific pattern to secure the connection. The antenna should direct its energy in parallel to the human skin while establishing an on-body link, ideally omnidirectionally, while an on-body link would benefit from a directional radiation pattern perpendicular to human skin. Moreover, the lossy body tissue is within the reactive region of the antenna affecting the antenna performance; …

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Design Of An On-Chip Hilbert Fractal Inductor Using An Improved Feed Forward Neural Network For Si Rfics, Akhendra Kumar Padavala, Bheema Rao Nistala Jan 2018

Design Of An On-Chip Hilbert Fractal Inductor Using An Improved Feed Forward Neural Network For Si Rfics, Akhendra Kumar Padavala, Bheema Rao Nistala

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents an efficient modeling of Hilbert fractal inductors by improved feed forward neural network trained hybrid particle swarm optimization and gravitational search algorithm (FNNPSOGSA). The proposed model computes the effective inductance value (L) and quality factor (Q) of Hilbert fractal inductors with metal trace width, effective fractal length, frequency, and oxide thickness as input parameters. In contrast to the traditional feed forward neural network, the proposed FNNPSOGSA has been designed with fewer hidden neurons with much-enhanced learning and generalization capabilities. As a consequence, the proposed model achieves better speed and is as accurate as electromagnetic simulations. From the …

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A Dynamic Channel Assignment Method For Multichannel Multiradio Wireless Mesh Networks, Şafak Durukan Odabaşi, Abdül Hali̇m Zai̇m Jan 2018

A Dynamic Channel Assignment Method For Multichannel Multiradio Wireless Mesh Networks, Şafak Durukan Odabaşi, Abdül Hali̇m Zai̇m

Turkish Journal of Electrical Engineering and Computer Sciences

The popularity of wireless communication accelerates research on new technologies that are required to satisfy users' needs. Wireless mesh networks (WMNs), which are additional access technologies instead of being a renewed one, have an important place among next-generation wireless networks. In particular, the capability of working without any infrastructure is the most outstanding advantage of WMNs. There are many studies aimed at WMNs, particularly channel assignment and routing methods for multichannel multiradio structures that provide higher data capacity. Interference, which has a direct effect on the quality of communication, is still a challenge to be addressed. In this study, multichannel …

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Symbolic Interpretation Of Artificial Neural Networks Using Genetic Algorithms, Dounia Yedjour, Abdelkader Benyettou, Hayat Yedjour Jan 2018

Symbolic Interpretation Of Artificial Neural Networks Using Genetic Algorithms, Dounia Yedjour, Abdelkader Benyettou, Hayat Yedjour

Turkish Journal of Electrical Engineering and Computer Sciences

The knowledge acquired during the learning of artificial neural networks (ANNs) is coded as values in synaptic weights, which makes their interpretations difficult, hence the name of the black box. The aim of this work is to provide a comprehensible interpretation of the ANN's decisions by extracting symbolic rules. We improve the performance of our extraction algorithm by combining the ANN with a genetic algorithm. Misleading rules whose support and confidence values are less than fixed thresholds are removed and, as a result, the comprehensibility is improved. The extracted rules are evaluated and compared with other works. The results show …

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Development Of Intelligent Decision Support System Using Fuzzy Cognitive Maps For Migratory Beekeepers, Ahmet Albayrak, Feci̇r Duran, Rai̇f Bayir Jan 2018

Development Of Intelligent Decision Support System Using Fuzzy Cognitive Maps For Migratory Beekeepers, Ahmet Albayrak, Feci̇r Duran, Rai̇f Bayir

Turkish Journal of Electrical Engineering and Computer Sciences

This study presents the development of an intelligent information system using fuzzy cognitive maps that provides information to migratory beekeepers about the nectar flow and climate conditions in the regions they will visit. Beekeeping is an agricultural activity essentially focused on honey production. High honey yields in beekeeping can be achieved through migratory beekeeping. Migratory beekeepers complete the honey production season by carrying their hives to regions with high nectar flow. Beekeepers decide on the regions they will visit based on their previous experiences. In this study, a software-based system that provides information to the beekeepers about the honey yield …

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Optimization In The Catalyst Optimizer Of Spark Sql, Meenu Chawla, Vinita Baniwal Jan 2018

Optimization In The Catalyst Optimizer Of Spark Sql, Meenu Chawla, Vinita Baniwal

Turkish Journal of Electrical Engineering and Computer Sciences

Apache Spark is one of the most technically challenged frameworks for cluster computing in which data are processed in a parallel fashion. The cluster consists of unreliable machines. It processes a large amount of data faster compared to the MapReduce framework. For providing the facility of optimized and fast SQL query processing, a new unit is developed in Apache Spark named Spark SQL. It allows users to use relational processing and functional programming in one place. It provides many optimizations by leveraging the benefits of its core. This is called the catalyst optimizer. This optimizer has many rules to optimize …

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Genetic Programming-Based Pseudorandom Number Generator For Wireless Identification And Sensing Platform, Cem Kösemen, Gökhan Dalkiliç, Ömer Aydin Jan 2018

Genetic Programming-Based Pseudorandom Number Generator For Wireless Identification And Sensing Platform, Cem Kösemen, Gökhan Dalkiliç, Ömer Aydin

Turkish Journal of Electrical Engineering and Computer Sciences

The need for security in lightweight devices such as radio frequency identification tags is increasing and a pseudorandom number generator (PRNG) constitutes an essential part of the authentication protocols that provide security. The main aim of this research is to produce a lightweight PRNG for cryptographic applications in wireless identification and sensing platform family devices, and other related lightweight devices. This PRNG is produced with genetic programming methods using entropy calculation as the fitness function, and it is tested with the NIST statistical test suite. Moreover, it satisfies the requirements of the EPCGen2 standards.

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Dynamic Cpu Scheduling For Load Balancing In Virtualized Environments, Suresh Chandra Moharana, Sibani Samal, Amulya Ratna Swain, Ganga Bishnu Mund Jan 2018

Dynamic Cpu Scheduling For Load Balancing In Virtualized Environments, Suresh Chandra Moharana, Sibani Samal, Amulya Ratna Swain, Ganga Bishnu Mund

Turkish Journal of Electrical Engineering and Computer Sciences

In the modern era of computing, the cloud computing platform became popular with its on-demand resource scalability feature. Virtualization is the key technology to achieve resource scalability in the cloud environment. Virtual machine monitors (VMMs) like Xen and KVM are the enabling tools for virtualizing the resources in the cloud environment. The major role of VMMs is to map virtual CPUs of virtual machines to physical CPUs, popularly known as CPU scheduling. In this study, we analyzed the CPU scheduler of Xen VMM, called Credit CPU scheduler, with respect to CPU utilization. In order to maximize the physical CPU utilization …

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Extended Correlated Principal Component Analysis With Svm-Puk In Opinion Mining, Kollimarla Anusha Devi, Deepak Chowdary Edara, Venkatrama Phani Kumar Sistla, Venkata Krishna Kishore Kolli Jan 2018

Extended Correlated Principal Component Analysis With Svm-Puk In Opinion Mining, Kollimarla Anusha Devi, Deepak Chowdary Edara, Venkatrama Phani Kumar Sistla, Venkata Krishna Kishore Kolli

Turkish Journal of Electrical Engineering and Computer Sciences

With the rapid growth of microblogs and online sites, an inordinate number of product reviews are available on the Internet. They not only help in analyzing, but also assist in making informed decisions about product quality. In the proposed work, an extended correlated principal component analysis (ECPCA) is used for dimensionality reduction. A comparative analysis is conducted on movie reviews (DB-1) and Twitter datasets (DB-2 and DB-3) in opinion mining extraction. The performance of naive Bayes, CHIRP, and support vector machine (SVM) with kernel methods such as radial basis function (RBF), polynomial, and Pearson (PUK) are compared and analyzed on …

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Enlarging Multiword Expression Dataset By Co-Training, Senem Kumova Meti̇n Jan 2018

Enlarging Multiword Expression Dataset By Co-Training, Senem Kumova Meti̇n

Turkish Journal of Electrical Engineering and Computer Sciences

In multiword expressions (MWEs), multiple words unite to build a new unit in language. When MWE identification is accepted as a binary classification task, one of the most important factors in performance is to train the classifier with enough number of labelled samples. Since manual labelling is a time-consuming task, the performances of MWE recognition studies are limited with the size of the training sets. In this study, we propose the comparison-based and common-decision co-training approaches in order to enlarge the MWE dataset. In the experiments, the performances of the proposed approaches were compared to those of the standard co-training …

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Forecasting Of Short-Term Wind Speed At Different Heights Using A Comparative Forecasting Approach, Emrah Korkmaz, Ercan İzgi̇, Sali̇h Tutun Jan 2018

Forecasting Of Short-Term Wind Speed At Different Heights Using A Comparative Forecasting Approach, Emrah Korkmaz, Ercan İzgi̇, Sali̇h Tutun

Turkish Journal of Electrical Engineering and Computer Sciences

The forecasting of wind speed with high accuracy has been a very significant obstacle to the enhancement of wind power quality, for the volatile behavior of wind speed makes forecasting difficult. In order to generate more reliable wind power and to determine the best model for different heights, wind speed needs to be predicted accurately. Recent studies show that soft computing approaches are preferred over physical methods because they can provide fast and reliable techniques to forecast short-term wind speed. In this study, a multilayer perceptron neural network and an adaptive neural fuzzy inference system are utilized to both forecast …

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Incremental Banerjee Test Conditions Committing For Robust Parallelization Framework, Aimad Eddine Debbi, Haddi Bakhti Jan 2018

Incremental Banerjee Test Conditions Committing For Robust Parallelization Framework, Aimad Eddine Debbi, Haddi Bakhti

Turkish Journal of Electrical Engineering and Computer Sciences

This paper describes the design of an automatic parallelization framework. The kernel supplied at its front end was suggested as an instrument for parallel potential assessment. It was used to measure the maximum achievable speedups in the major set of the CHStone benchmark suite programs. In such framework, we suggested the liberation of parallelism incrementally. We proposed a data dependency heuristic-based transformation method to make true dependences dissociation. We generated an internal representation ($ IR^{2} $), where the Banerjee test conditions are met. Two among three of Banerjee test conditions came to be committed. In shared memory many/multicore platforms, the …

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An Enhanced Grey Wolf Optimization Algorithm With Improved Exploration Ability For Analog Circuit Design Automation, M A Mushahhid Majeed, Sreehari Rao Patri Jan 2018

An Enhanced Grey Wolf Optimization Algorithm With Improved Exploration Ability For Analog Circuit Design Automation, M A Mushahhid Majeed, Sreehari Rao Patri

Turkish Journal of Electrical Engineering and Computer Sciences

A novel circuit sizing technique with improved accuracy and efficiency is proposed to resolve the sizing issues in the analog circuit design. The grey wolf optimization (GWO) algorithm has the total number of iterations divided equally for exploration and exploitation, overlooking the impact of balance between these two phases, aimed for the convergence at a globally optimal solution. An enhanced version of a typical GWO algorithm termed as enhanced grey wolf optimization (EGWO) algorithm is presented with improved exploration ability and is successfully applied in analog circuit design. A set of 23 classical benchmark functions is evaluated and the outcomes …

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Path Planning And Energy Flow Control Of Wireless Power Transfer For Sensor Nodes In Wireless Sensor Networks, Chenyang Xia, Yang Zhang, Yuling Liu, Kezhang Lin, Jun Chen Jan 2018

Path Planning And Energy Flow Control Of Wireless Power Transfer For Sensor Nodes In Wireless Sensor Networks, Chenyang Xia, Yang Zhang, Yuling Liu, Kezhang Lin, Jun Chen

Turkish Journal of Electrical Engineering and Computer Sciences

In wireless sensor networks (WSNs), limited-capacity batteries are generally used for powering sensor nodes, where unbalanced electricity is the primary cause of premature death of WSNs. In this paper, wireless power transfer networks are used to power batteries in WSNs to avoid the problem of limited lifetime of traditional limited-capacity batteries. Furthermore, path planning based on the Dijkstra algorithm, which aims at minimizing the overall energy consumption in the network to improve system efficiency, is discussed in detail. Finally, three power transfer models with low contention level (LCL) topology for energy flow control are experimentally validated from the optimal path.

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Robust Restoration Of Distribution Systems Considering Dg Units And Direct Load Control Programs, Abolfazl Asadi, Mahmud Fotuhi Firuzabad Jan 2018

Robust Restoration Of Distribution Systems Considering Dg Units And Direct Load Control Programs, Abolfazl Asadi, Mahmud Fotuhi Firuzabad

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a new method for restoration of distribution networks after a fault occurrence. This problem is solved from the viewpoint of the distribution system operator with the main goal of minimizing the operating cost during the fault clearance period. The effects of distributed generation (DG) units and direct load control (DLC) programs are considered in designing the proposed restoration procedure. Moreover, the uncertainties associated with the predicted loads of different nodes and the availability of DG are modeled here. Robust optimization is used to model the uncertainties of restoration problems and manage their associated risks. Finally, a robust …

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Design Of A Multiagent-Based Smart Microgrid System For Building Energy And Comfort Management, Batyrkhan Omarov, Aigerim Altayeva Jan 2018

Design Of A Multiagent-Based Smart Microgrid System For Building Energy And Comfort Management, Batyrkhan Omarov, Aigerim Altayeva

Turkish Journal of Electrical Engineering and Computer Sciences

Modern intelligent control system design methodology in the electric power industry and their features are considered when providing the required comfort in multizone buildings with the use of multiagent power consumption and comfort management systems. Such a control system covers all the monitored zones of a building and, if necessary, can provide the greatest possible overall comfort in the building while reducing the required electric power. The purpose of this study was to develop a comfort management system in a multizoned building that can provide comfort while reducing the required electric power.

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Full Bridge Converter Based Independent Phase Control Of A Permanent Magnet Reluctance Generator For Wind Power Conversion Systems, Erkan Sunan, Fuat Küçük Jan 2018

Full Bridge Converter Based Independent Phase Control Of A Permanent Magnet Reluctance Generator For Wind Power Conversion Systems, Erkan Sunan, Fuat Küçük

Turkish Journal of Electrical Engineering and Computer Sciences

A Permanent Magnet Reluctance Generator (PMRG) possesses important features such as simplicity and low cost. Absence of rotor winding allows the generator to run in a wide speed range. The PMRG may have potential to be used in wind power conversion systems. An asymmetric half bridge (AHB) converter may be acceptable as a classical converter topology for PMRGs and offers independent phase control. The AHB converter with a torque ripple minimization-assisted maximum power point tracking algorithm not only provides significant torque ripple reduction on the mechanical side but also allows conversion of maximum wind energy to electrical energy. The major …

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An Analysis Of Centennial Wind Power Targets Of Turkey, Egemen Sulukan Jan 2018

An Analysis Of Centennial Wind Power Targets Of Turkey, Egemen Sulukan

Turkish Journal of Electrical Engineering and Computer Sciences

Wind power has become one of the cost-effective options for improving the energy mix, while the wind farm installations reach higher shares by new capacity additions in Turkey, similar to many other countries, in order to support the sustainable development targets. Various methodologies are implemented and applied for planning and optimizing energy systems of countries, taking into consideration the energy, economy, and ecology aspects as a whole. The objective of this paper is to demonstrate the implications of "2023 energy targets" policy in terms of wind power. A futuristic scenario was tailored and applied to a comprehensive energy model for …

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A Novel Frt Strategy Based On An Analytical Approach For Pmsg-Based Wind Turbines With Ess Power Rating Reduction, Farid Atashbahar, Ali Ajami, Hossein Mokhtari, Hossein Hojabri Jan 2018

A Novel Frt Strategy Based On An Analytical Approach For Pmsg-Based Wind Turbines With Ess Power Rating Reduction, Farid Atashbahar, Ali Ajami, Hossein Mokhtari, Hossein Hojabri

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper an analytical approach is proposed to formulate the proper set of phase currents reference to ride the permanent magnet synchronous generator (PMSG)-based wind turbine (WT) through faults properly, regardless of fault type. Hence, the WT is forced to inject required reactive current by grid codes together with active power injection, to help support grid frequency during faults and reduce the energy storage system (ESS) power rating. Moreover, it prevents pulsating active power injection to the grid. During grid faults, the DC-link voltage is controlled by the ESS instead of the grid-side converter (GSC) and the GSC controller …

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A New Technique For Optimum Excitation Of Switched Reluctance Motor Drives Over A Wide Speed Range, Mahmoud Hamouda, László Számel Jan 2018

A New Technique For Optimum Excitation Of Switched Reluctance Motor Drives Over A Wide Speed Range, Mahmoud Hamouda, László Számel

Turkish Journal of Electrical Engineering and Computer Sciences

Optimum performance of switched reluctance motors (SRMs) over a wide range of speed control is an essential approach for many industrial applications. However, the doubly salient structure and deep magnetic saturation make magnetization characteristics of SRMs a highly nonlinear function of rotor position and current magnitude. This, in turn, makes the control of SRM drives a challenging task. As the control of SRMs depends on the inductance profile, it requires an adaptive control technique for optimum operation over a wide range of operating speeds. This paper presents an adaptive control technique for optimum excitation of SRM drives. The proposed control …

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Design Of A Fractional Order Pid Controller With Application To An Induction Motor Drive, Ashraf Saleem, Hisham Soliman, Serein Al-Ratrout, Mostefa Mesbah Jan 2018

Design Of A Fractional Order Pid Controller With Application To An Induction Motor Drive, Ashraf Saleem, Hisham Soliman, Serein Al-Ratrout, Mostefa Mesbah

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a new method for designing a fractional-order proportional-integral-derivative (FO-PID) controller with an application to an induction motor drive is proposed. In the proposed method, the motor drive is modeled using an autoregressive with exogenous input (ARX) model whose parameters are experimentally identified using real I/O data. A genetic algorithm is then used to find the FO-PID parameters. To guarantee the robustness of the controller against load variations, minimax optimization is adopted. To validate the results, the proposed controller is applied to a real-life motor drive using a hardware-in-the-loop (HIL) simulator. The experimental results show that the proposed …

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Human Sleep Scoring Based On K-Nearest Neighbors, Shahnawaz Qureshi, Seppo Karrila, Sirirut Vanichayobon Jan 2018

Human Sleep Scoring Based On K-Nearest Neighbors, Shahnawaz Qureshi, Seppo Karrila, Sirirut Vanichayobon

Turkish Journal of Electrical Engineering and Computer Sciences

Human sleep is one of the essential indicators that gauge the overall health and well-being. Presently, it is common for people to face issues related to sleep. Various biomedical signals including electroencephalogram (EEG), electrooculography (EMG), and electrooculography (EOG) are utilized in the diagnosis and during the treatment of sleep disorder cases. An automatic classification to diagnose sleep problems can help in the analysis of sleep EEG data. In this current study, an effort is made to classify the sleep stages from a single EEG channel (C4-A1) based on K-nearest neighbors (K-NN) with three alternative distance metrics. The Euclidean distance is …

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Comparative Analysis Of Mabc With Knn, Som, And Aco Algorithms For Ecg Heartbeat Classification, Seli̇m Di̇lmaç, Zümray Ölmez, Tamer Ölmez Jan 2018

Comparative Analysis Of Mabc With Knn, Som, And Aco Algorithms For Ecg Heartbeat Classification, Seli̇m Di̇lmaç, Zümray Ölmez, Tamer Ölmez

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we proposed a classification method based on a nature-inspired algorithm, i.e., modified artificial bee colony (MABC). This method was applied to electrocardiogram (ECG) heartbeat classification. ECG data was obtained from MITBIH database. Eight different types of heartbeats (N, j, V, F, f, A, a, and R) were analyzed. For a better classification result, both time domain and frequency domain features were used. Feature selection was done by divergence analysis. MABC classification accuracy and heartbeat sensitivity values were compared with the results of other methods. Among other classifiers, k-nearest neighbor (KNN), Kohonen's self-organizing map (SOM), and ant colony …

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An Algorithm For Image Restoration With Mixed Noise Using Total Variation Regularization, Cong Thang Pham, Guilhem Gamard, Andrei Kopylov, Thi Thu Thao Tran Jan 2018

An Algorithm For Image Restoration With Mixed Noise Using Total Variation Regularization, Cong Thang Pham, Guilhem Gamard, Andrei Kopylov, Thi Thu Thao Tran

Turkish Journal of Electrical Engineering and Computer Sciences

We present here an effective scheme for image denoising based on total variation regularization. The proposed scheme allows to efficiently remove Poisson noise as well as Gaussian noise simultaneously with the help of a new kind of data fidelity term, suitable for the mixed Poisson - Gaussian noise model. The results show that the algorithm corresponding to our new scheme outperforms the existing methods for mixed Poisson - Gaussian noise removal.

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Reconstruction Of Geometrical And Reflection Properties Of Surfaces By Using Structured Light Imaging Technique, Şükrü Ozan, Şevket Gümüşteki̇n Jan 2018

Reconstruction Of Geometrical And Reflection Properties Of Surfaces By Using Structured Light Imaging Technique, Şükrü Ozan, Şevket Gümüşteki̇n

Turkish Journal of Electrical Engineering and Computer Sciences

When a robust and dense surface reconstruction is aimed, structured light imaging techniques are usually much appreciated. In this paper we propose a method to reconstruct both geometrical and reflective properties of surfaces by using structured light imaging. We use a technique where a camera and a projector are both treated as viewing devices. They are calibrated in the same manner. Each visible point can be correctly located on both image planes without solving a correspondence problem; hence, a dense reconstruction can be obtained. Since both the camera and the projector are explicitly calibrated, lighting and viewing directions can be …

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