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Articles 13051 - 13080 of 25595

Full-Text Articles in Computer Engineering

Application Of Domination Integrity Of Graphs In Pmu Placement In Electric Power Networks, Mariappan Saravanan, Ramalingam Sujatha, Raman Sundareswaran, Muthu Selvan Balasubramanian Jan 2018

Application Of Domination Integrity Of Graphs In Pmu Placement In Electric Power Networks, Mariappan Saravanan, Ramalingam Sujatha, Raman Sundareswaran, Muthu Selvan Balasubramanian

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we propose the application of the concept of power domination integrity to an electric power network. A phasor measurement unit (PMU) is used to analyze and control the power system by measuring voltage phase in electrical nodes and transmission lines. Due to the high cost of PMUs, it is necessary to minimize the number of PMUs such that the depth of observability is ensured. Placing PMUs in a network can be formulated as a graph theoretic problem of finding the minimum number of nodes (PMUs) in a graph that has a maximum number of links with other …

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Real-Time Power System Dynamic Security Assessment Based On Advanced Feature Selection For Decision Tree Classifiers, Qusay Al-Gubri, Mohd Aifaa Mohd Ariff Jan 2018

Real-Time Power System Dynamic Security Assessment Based On Advanced Feature Selection For Decision Tree Classifiers, Qusay Al-Gubri, Mohd Aifaa Mohd Ariff

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes a novel algorithm based on an advanced feature selection technique for the decision tree (DT) classifier to assess the dynamic security in a power system. The proposed methodology utilizes symmetrical uncertainty (SU) to reduce the data redundancy in a dataset for DT classifier-based dynamic security assessment (DSA) tools. The results show that SU reduces the dimension of the dataset used for DSA significantly. Subsequently, the approach improves the performance of the DT classifier. The effectiveness of the proposed technique is demonstrated on the modified IEEE 30-bus test system model. The results show that the DT classifier with …

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On The Power Handling Of A High Power Combiner For Industrial, Scientific, And Medical Applications, Arash Ahmadi Jan 2018

On The Power Handling Of A High Power Combiner For Industrial, Scientific, And Medical Applications, Arash Ahmadi

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper a 2-way broadband power combiner that can handle up to 1 kW output power is designed and fabricated. The combiner covers the frequency range of 30 to 500 MHz, which is intended for industrial, scientific, and medical (ISM) applications. The power handling of the power combiner depends on the power handling of the components that constitute the combiner. The combiner is composed of some coaxial transmission lines and a transmission line transformer. The ferrite cores, which are used to suppress the common mode current, are one of the major limiting factors, regarding the power handling of the …

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A Novel Single-Inductor Eight-Channel Light-Emitting Diode Driver For Low Power Display Backlight Applications, Magesh Kannan Parthasarathy, Nagarajan Ganesan Jan 2018

A Novel Single-Inductor Eight-Channel Light-Emitting Diode Driver For Low Power Display Backlight Applications, Magesh Kannan Parthasarathy, Nagarajan Ganesan

Turkish Journal of Electrical Engineering and Computer Sciences

A novel decoder-based single-inductor eight-channel light-emitting diode (LED) driver circuit for low power display backlight applications has been proposed. Uniform brightness in the display provides better picture clarity, which can be achieved by providing uniform DC currents to all channels in the backlight arrangement. Existing systems use individual current regulators for each channel, which fails to provide uniform current to individual channels. Instead, uniform current is provided to all eight channels in the proposed system as the same current is distributed to all channels using time-multiplexing by a 3 $\times $ 8 decoder and a 3-bit binary up-counter. A digital …

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Sf6 Gas-Insulated 50-Kva Distribution Transformer Design, Okan Özgönenel, David Thomas, Ünal Kurt Jan 2018

Sf6 Gas-Insulated 50-Kva Distribution Transformer Design, Okan Özgönenel, David Thomas, Ünal Kurt

Turkish Journal of Electrical Engineering and Computer Sciences

There are increasing environmental concerns such that governments are pressured to cooperate with international concurrences. One of the most harmful contaminants is mineral oil when it infiltrates the soil. Although it is a good material in the act of insulating in distribution/power transformers, it presents some environmental hazards and safety disadvantages. For this reason, gas-insulated transformers are considered particularly for hazardous locations. An oil-insulated distribution transformer of 50 kVA, 34.5/0.4 kV, and 50 Hz is investigated and converted to SF6 gas-insulated transformer in this study. The suggested distribution transformer model with SF6 insulated has many benefits, such as being explosion-proof …

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Modified Acceleration Feedback For Practical Disturbance Rejection In Motor Drives, Ahmet Gürhanli Jan 2018

Modified Acceleration Feedback For Practical Disturbance Rejection In Motor Drives, Ahmet Gürhanli

Turkish Journal of Electrical Engineering and Computer Sciences

Acceleration feedback techniques have been used in control systems for a long time in order to improve the stiffness. Basically, the acceleration of the motor is calculated using speed or position measurements and the current command is adjusted using the acceleration data for avoiding deviations from the commanded speed. This method has to deal with two challenges. The first challenge is calculating the acceleration correctly. If it is calculated by double differentiation of position feedback of a servo motor, it may lead to a high amount of noise. On the other hand, if observer techniques are used, the error and …

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Feature Selection Algorithm For No-Reference Image Quality Assessment Using Natural Scene Statistics, Imran Fareed Nizami, Muhammad Majid, Khawar Khurshid Jan 2018

Feature Selection Algorithm For No-Reference Image Quality Assessment Using Natural Scene Statistics, Imran Fareed Nizami, Muhammad Majid, Khawar Khurshid

Turkish Journal of Electrical Engineering and Computer Sciences

Images play an essential part in our daily lives and the performance of various imaging applications is dependent on the user?s quality of experience. No-reference image quality assessment (NR-IQA) has gained importance to assess the perceived quality, without using any prior information of the nondistorted version of the image. Different NR-IQA techniques that utilize natural scene statistics classify the distortion type based on groups of features and then these features are used for estimating the image quality score. However, every type of distortion has a different impact on certain sets of features. In this paper, a new feature selection algorithm …

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A Comparative Analysis Of 1-Level Multiplier-Free Discrete Wavelet Transform Implementations On Fpgas, Husam Alzaq, Burak Berk Üstündağ Jan 2018

A Comparative Analysis Of 1-Level Multiplier-Free Discrete Wavelet Transform Implementations On Fpgas, Husam Alzaq, Burak Berk Üstündağ

Turkish Journal of Electrical Engineering and Computer Sciences

In this article, we investigated the design and implementation aspects of multilevel discrete wavelet transform (DWT) by employing a finite impulse response filter on field programmable gate array platform. We presented two key multiplication-free architectures, namely, the distributed arithmetic algorithm (DAA) and residue number system (RNS). Our goal is to estimate the performance requirements and hardware resources for each approach, allowing for selection of the proper algorithm and implementation of multilevel DAA- and RNS-based DWT. The design has been implemented and synthesized in Xilinx Virtex 6 ML605, taking advantage of Virtex 6?s embedded block RAMs. The results reveal that the …

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Region Characteristics-Based Fusion Of Spatial And Transform Domain Image Denoising Methods, Rajiv Verma, Rajoo Pandey Jan 2018

Region Characteristics-Based Fusion Of Spatial And Transform Domain Image Denoising Methods, Rajiv Verma, Rajoo Pandey

Turkish Journal of Electrical Engineering and Computer Sciences

Nonlocal means (NLM)- and wavelet-based image denoising methods have drawn much attention in image processing due to their effectiveness and simplicity. The performance of these algorithms varies according to region characteristics in an image. For example, NLM performs well for smooth regions due to deployment of redundancy available in images, whereas wavelet-based approaches may preserve key image features by controlling the degree of threshold for shrinking the noisy coefficients. This paper presents a simple novel approach that estimates an original image by simply taking the weighted average of the denoised images pixel values obtained by NLM and wavelet thresholding schemes …

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Adaptive Bit-Plane Selection-Based Low Complexity Motion Estimation For Screen Content Coding, Ramazan Duvar, Oğuzhan Urhan Jan 2018

Adaptive Bit-Plane Selection-Based Low Complexity Motion Estimation For Screen Content Coding, Ramazan Duvar, Oğuzhan Urhan

Turkish Journal of Electrical Engineering and Computer Sciences

Screen content video coding has become an emerging research topic with the spread of applications such as cloud gaming, screen/desktop virtualization, and mobile or external display interfacing. Screen content videos have different features compared to conventional camcorder-captured scenes. In this work, a novel low bit-depth representation-based motion estimation approach is proposed to exploit screen content specific features to improve coding efficiency. The proposed approach is based on an adaptive selection of Gray-coded bit-planes in order to generate low bit-depth representation of original screen content frames. The experimental results show that the motion estimation performance of the proposed approach is significantly …

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A Low-Complexity Rare-Based 2-D Doa Estimation Algorithm For A Mixture Of Circular And Strictly Noncircular Sources, Kashif Shabir, Tarek Hasan Al Mahmud, Rui Zheng, Zhongfu Ye Jan 2018

A Low-Complexity Rare-Based 2-D Doa Estimation Algorithm For A Mixture Of Circular And Strictly Noncircular Sources, Kashif Shabir, Tarek Hasan Al Mahmud, Rui Zheng, Zhongfu Ye

Turkish Journal of Electrical Engineering and Computer Sciences

A new rank reduction (RARE)-based two-dimensional (2-D) direction of arrival (DOA) estimation algorithm is proposed considering a mixture of circular and strictly noncircular sources. To enhance array aperture, a geometry of three uniform linear arrays is considered and then treated as displaced arrays from a virtual array using a simple linear transformation. The received data and the conjugated counterpart are combined together, exploiting the noncircular property. Both sources can be estimated separately by designing and exploiting the distinctive nature of circular and noncircular steering vectors. However, a 2-D spectrum search would lead to a high computational complexity burden. To reduce …

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Long-Term Multiobject Tracking Using Alternative Correlation Filters, Kemal Batuhan Başkurt, Refi̇k Samet Jan 2018

Long-Term Multiobject Tracking Using Alternative Correlation Filters, Kemal Batuhan Başkurt, Refi̇k Samet

Turkish Journal of Electrical Engineering and Computer Sciences

We propose a real-time multiobject-tracking approach that is minimally affected by environmental conditions and target appearance change. The aim of the proposed approach is to track any object in a scene, regardless of object type, since tracking all of the objects in a scene is critical and widely used in surveillance applications. Thus, motion detection results are used to initialize the trackers. The proposed object-tracking approach is realized with two types of independent correlation filters estimating location and scale. Alternative correlation filters representing different appearances of the target are also proposed in order to increase the robustness of the approach …

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A Noninvasive Time-Frequency-Based Approach To Estimate Cuffless Arterial Blood Pressure, Ömer Faruk Ertuğrul, Necmetti̇n Sezgi̇n Jan 2018

A Noninvasive Time-Frequency-Based Approach To Estimate Cuffless Arterial Blood Pressure, Ömer Faruk Ertuğrul, Necmetti̇n Sezgi̇n

Turkish Journal of Electrical Engineering and Computer Sciences

Arterial blood pressure (ABP) is one of the most vital signs in the prophylaxis and treatment of blood pressure-related diseases because raised blood pressure is the most significant cause of death and the second major cause of disability in the world. Higher ABP yields greater strain on arteries and these extra strains turn arteries into thicker, less flexible, and more narrow structures. This increases the possibility of having an artery busting or artery occlusion, which are the primary reasons for heart attacks, kidney disease, or strokes. In addition to its importance in monitoring cardiovascular homeostasis, measurement of ABP is imperative …

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Deep Learning Based Brain Tumor Classification And Detection System, Ali̇ Ari, Davut Hanbay Jan 2018

Deep Learning Based Brain Tumor Classification And Detection System, Ali̇ Ari, Davut Hanbay

Turkish Journal of Electrical Engineering and Computer Sciences

The brain cancer treatment process depends on the physician's experience and knowledge. For this reason, using an automated tumor detection system is extremely important to aid radiologists and physicians to detect brain tumors. The proposed method has three stages, which are preprocessing, the extreme learning machine local receptive fields (ELM-LRF) based tumor classification, and image processing based tumor region extraction. At first, nonlocal means and local smoothing methods were used to remove possible noises. In the second stage, cranial magnetic resonance (MR) images were classified as benign or malignant by using ELM-LRF. In the third stage, the tumors were segmented. …

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Image Reconstruction For Frequency-Domain Diffuse Optical Tomography, Vicky Mudeng, Yun Priyanto, Andhika Giyantara Jan 2018

Image Reconstruction For Frequency-Domain Diffuse Optical Tomography, Vicky Mudeng, Yun Priyanto, Andhika Giyantara

Turkish Journal of Electrical Engineering and Computer Sciences

The image reconstruction algorithm of diffuse optical tomography (DOT) is based on the diffusion equation and involves both the forward problem and inverse solution. The forward problem solves the diffusion equation using the finite element method for calculating the transmitted light distribution under the condition of presumed light source and optical coefficient. The inverse solution reconstructs the optical property coefficient distribution using Newton's method. The work within this study develops an image reconstruction algorithm for frequency-domain DOT. A numerical simulations approach to light propagation in the tissue is conducted, while the optical property is reconstructed employing data around the boundary. …

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Improving The Sensitivity And Accuracy Of Microcantilever Biosensors By A Truss Structure Within Air Medium, Soheyla Elmi, Zahra Elmi Jan 2018

Improving The Sensitivity And Accuracy Of Microcantilever Biosensors By A Truss Structure Within Air Medium, Soheyla Elmi, Zahra Elmi

Turkish Journal of Electrical Engineering and Computer Sciences

Early diagnosis is a very fundamental issue in treating most diseases and for this purpose microcantilevers are very effective and reliable devices. In this work, four models of biosensor-based microcantilever are compared and a novel design with high sensitivity, quality factor, and accuracy is proposed. A truss structure is designed near the anchored end of the microcantilever, which improves the sensitivity in order to increase detection accuracy. A linear relationship between resonance frequency shift and masses has been estimated for all the designs. High quality factor, which increases the accuracy of measurement, is taken into account as the other benefit …

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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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