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2019

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Low Leakage Pocket Junction-Less Dgtfet With Biosensing Cavity Region, Suman Lata Tripathi, Raju Patel, Vimal Kumar Agrawal Jan 2019

Low Leakage Pocket Junction-Less Dgtfet With Biosensing Cavity Region, Suman Lata Tripathi, Raju Patel, Vimal Kumar Agrawal

Turkish Journal of Electrical Engineering and Computer Sciences

Low leakage current junction-less double gate tunnel field-effect transistor (JLDGTFET) with narrow band gap material pocket region of $Si_{0.7}Ge_{0.3}$ shows increased band to band tunneling and sharp subthreshold characteristics to meet low power, high speed digital and memory applications. The proposed JLDGTFET exploits the junction-less behavior that supports reasonable values of ON/OFF currents as well as improved subthreshold parameters. First, the performance optimization of the JLDGTFET is carried out with different gate contact and oxide region materials in terms of $I_{ON}/I_{OFF}$ current ratio, subthreshold slope, and drain induced barrier lowering. The ON/OFF performance of the pocket $Si_{0.7}Ge_{0.3}$ JLDGTFET with cavity …

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A Smart Wireless Sensor Network Node For Fire Detection, Wajahat Khalid, Asma Sattar, Muhammad Ali Qureshi, Asjad Amin, Mobeen Ahmed Malik, Kashif Hussain Jan 2019

A Smart Wireless Sensor Network Node For Fire Detection, Wajahat Khalid, Asma Sattar, Muhammad Ali Qureshi, Asjad Amin, Mobeen Ahmed Malik, Kashif Hussain

Turkish Journal of Electrical Engineering and Computer Sciences

Fires generally occur due to human carelessness and the change in environmental conditions. The uncontrolled fire results in death incidents of humans and animals as well as severe threats to the ecosystem. The preservation of the natural environment is important. The wireless sensor networks, widely used in different monitoring applications, is used in this work. For fire detection, we use flame, smoke, temperature, humidity, and light intensity sensors in our proposed network node which is low-cost, reduced-size, and power-efficient. The experiments are performed in a well-controlled real-time environment. The proposed node transmits the sensed data to the central node. The …

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A Hybrid Single-Source Shortest Path Algorithm, Hi̇lal Arslan, Murat Manguoğlu Jan 2019

A Hybrid Single-Source Shortest Path Algorithm, Hi̇lal Arslan, Murat Manguoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

The single-source shortest path problem arises in many applications, such as roads, social applications, and computer networks. Finding the shortest path is challenging, especially for graphs that contain a large number of vertices and edges. In this work, we propose a novel hybrid method that first sparsifies a given graph by removing most edges that cannot form the shortest path tree and then applies a classical shortest path algorithm to the sparser graph. Removing all the edges that cannot form the shortest path tree would be expensive since it is equivalent to solving the original problem. Therefore, we propose an …

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A Comparative Study Of Nonlinear Bayesian Filtering Algorithms For Estimation Ofgene Expression Time Series Data, Nesrine Amor, Asma Meddeb, Sahbi Marrouchi, Souad Chebbi Jan 2019

A Comparative Study Of Nonlinear Bayesian Filtering Algorithms For Estimation Ofgene Expression Time Series Data, Nesrine Amor, Asma Meddeb, Sahbi Marrouchi, Souad Chebbi

Turkish Journal of Electrical Engineering and Computer Sciences

This paper addresses the problem of estimating the time series of a gene expression using nonlinear Bayesian filtering algorithms. The response of gene regulatory networks (GRNs) to functional requirements in the cell and environmental conditions evolves over time. Dynamic biological processes such as cancer progression and treatment recovery depend on the collected genetic profiles. These processes are behind genetic interactions that rewire over the course of time. The GRN was formulated as a nonlinear and non-Gaussian dynamic system defined by the gene measurement model and the unknown state is an evolution of the gene model. However, the GRN has a …

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Between-Host Hiv Model: Stability Analysis And Solution Using Memeticcomputing, Musharif Ahmed, Ijaz Mansoor Qureshi, Muhammad Aamer Saleem, Muhammad Zubair, Saad Zafar Jan 2019

Between-Host Hiv Model: Stability Analysis And Solution Using Memeticcomputing, Musharif Ahmed, Ijaz Mansoor Qureshi, Muhammad Aamer Saleem, Muhammad Zubair, Saad Zafar

Turkish Journal of Electrical Engineering and Computer Sciences

HIV poses a great threat to humanity for two major reasons. First it attacks the immunity system of the body and second, it is epidemic in nature. Mathematical models of HIV have been instrumental in understanding and controlling the infection. In this paper, we solve the between host epidemic model of HIV, described by nonlinear coupled differential equations, by using memetic computing. Under this model, the sexually active population is divided into four classes and we investigate the transfer of individuals from one class to another. The solution consists of Bernstein polynomials whose parameters have been optimized by using differential …

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Toxicity Prediction Of Small Drug Molecules Of Aryl Hydrocarbon Receptor Using Aproposed Ensemble Model, Vishan Kumar Gupta, Prashant Singh Rana Jan 2019

Toxicity Prediction Of Small Drug Molecules Of Aryl Hydrocarbon Receptor Using Aproposed Ensemble Model, Vishan Kumar Gupta, Prashant Singh Rana

Turkish Journal of Electrical Engineering and Computer Sciences

Quantitative structure-activity relationships and quantitative structure?property relationships have proved their usefulness for predicting toxicities of drug molecules regarding their biological activities. In silico toxicity prediction techniques are essential for reducing testing on rodents (in vivo) and for a less time-consuming and more cost-efficient alternative for the identification of toxic effects at an early stage of drug development. The authors aim to build a prediction model for better assessment of toxicity to quickly and efficiently test whether certain chemical compounds have the potential to disrupt the processes in the human body that may adversely affect human health. Here, we have proposed …

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A Heuristic Algorithm To Find Rupture Degree In Graphs, Rafet Durgut, Tufan Turaci, Hakan Kutucu Jan 2019

A Heuristic Algorithm To Find Rupture Degree In Graphs, Rafet Durgut, Tufan Turaci, Hakan Kutucu

Turkish Journal of Electrical Engineering and Computer Sciences

Since the problem of Konigsberg bridge was released in 1735, there have been many applications of graph theory in mathematics, physics, biology, computer science, and several fields of engineering. In particular, all communication networks can be modeled by graphs. The vulnerability is a concept that represents the reluctance of a network to disruptions in communication after a deterioration of some processors or communication links. Furthermore, the vulnerability values can be computed with many graph theoretical parameters. The rupture degree $r(G)$ of a graph $G=(V,E)$ is an important graph vulnerability parameter and defined as $r(G)=max\{\omega(G-S)- S -m(G-S):\omega(G-S)\geq2, S\subset V \}$, where …

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Global Stabilization Of A Class Of Fractional-Order Delayed Bidirectional Associativememory Neural Networks, Zhanying Yang, Xiaoyun Tang, Jie Zhang Jan 2019

Global Stabilization Of A Class Of Fractional-Order Delayed Bidirectional Associativememory Neural Networks, Zhanying Yang, Xiaoyun Tang, Jie Zhang

Turkish Journal of Electrical Engineering and Computer Sciences

This paper focuses on the stabilization problem of a class of fractional-order bidirectional associative memory neural networks with time delays. Based on feedback control, a sufficient condition is derived to achieve the global stabilization of systems by using the fractional inequality, the Lyapunov stability theory, and the comparison principle. In particular, this kind of control scheme is proved to be robust in the presence of external disturbances when the feedback gains are sufficiently large. In addition, a condition is obtained to achieve the global quasi-stabilization of systems with some external disturbances, and the corresponding error bound is estimated. Finally, some …

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Solving Vehicle Routing Problem For Multistorey Buildings Using Iterated Local Search, Osman Gökalp, Aybars Uğur Jan 2019

Solving Vehicle Routing Problem For Multistorey Buildings Using Iterated Local Search, Osman Gökalp, Aybars Uğur

Turkish Journal of Electrical Engineering and Computer Sciences

Vehicle routing problem (VRP) which is a well-known combinatorial optimisation problem that has many applications used in industry is also a generalised form of the travelling salesman problem. In this study, we defined and formulated the VRP in multistorey buildings (Multistorey VRP) for the first time and proposed a solving method employing iterated local search metaheuristic algorithm. This variant of VRP has a great potential for turning the direction of optimisation research and applications to the vertical cities area as well as the horizontal ones. Routes of part picking or placing vehicles/humans in multistorey plants can be minimised by this …

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An Improved Imperialist Competitive Algorithm For Global Optimization, Ting You, Yueli Hu, Peijiang Li, Yinggan Tang Jan 2019

An Improved Imperialist Competitive Algorithm For Global Optimization, Ting You, Yueli Hu, Peijiang Li, Yinggan Tang

Turkish Journal of Electrical Engineering and Computer Sciences

The imperialist competitive algorithm (ICA), inspired by sociopolitical behavior in the real world, is a new optimization algorithm. The ICA shows great potential to solve complex optimization problems. In order to improve the ICA's exploration ability and speed up its convergence, two improved schemes are proposed in this paper. The first scheme presents a new possession probability in the imperialistic competition phase. Inspired by geopolitics, not only the power of the empire but also the distance between the imperialists are taken into account in calculating the new possession probability. The second scheme introduces the wavelet mutation operator into the original …

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Detection Of Fraud Risks In Retailing Sector Using Mlp And Svm Techniques, Davut Pehli̇vanli, Süleyman Eken, Ebu Beki̇r Ayan Jan 2019

Detection Of Fraud Risks In Retailing Sector Using Mlp And Svm Techniques, Davut Pehli̇vanli, Süleyman Eken, Ebu Beki̇r Ayan

Turkish Journal of Electrical Engineering and Computer Sciences

In today's business conditions, where business activities are spreading over a wide geographical area, fraud auditing processes have crucial importance especially for the retailing sector which has a high branch network. In the retailing sector, especially purchasing processes are subject to high fraud risks. This paper shows that it is possible to detect fraudulent processes by applying data mining techniques on operational data related to purchasing activities. Within this scope, in order to detect the fraudulent purchasing operations, support vector machine (SVM) models with different kernels and artificial neural networks methods have been used and successful results have been achieved. …

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Biometric Person Authentication Framework Using Polynomial Curve Fitting-Based Ecg Feature Extraction, Şahi̇n Işik, Kemal Özkan, Semi̇h Ergi̇n Jan 2019

Biometric Person Authentication Framework Using Polynomial Curve Fitting-Based Ecg Feature Extraction, Şahi̇n Işik, Kemal Özkan, Semi̇h Ergi̇n

Turkish Journal of Electrical Engineering and Computer Sciences

The applications of modern biometric techniques for person identification systems rapidly increase for meeting the rising security demands. The distinctive physiological characteristics are more correctly measurable and trustworthy since previous measurements are not appropriately made for physiological properties. While a variety of strategies have been enabled for identification, the electrocardiogram (ECG)-based approaches are popular and reliable techniques in the senses of measurability, singularity, and universal awareness of heartbeat signals. This paper presents a new ECG-based feature extraction method for person identification using a huge amount of ECG recordings. First of all, 1800 heartbeats for each of the 36 subjects have …

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Adaptive Canonical Correlation Analysis For Harmonic Stimulation Frequencies Recognition In Ssvep-Based Bcis, Sahar Sadeghi, Ali Maleki Jan 2019

Adaptive Canonical Correlation Analysis For Harmonic Stimulation Frequencies Recognition In Ssvep-Based Bcis, Sahar Sadeghi, Ali Maleki

Turkish Journal of Electrical Engineering and Computer Sciences

Steady-state visual evoked potential (SSVEP) is the brain's response to quickly repetitive visual stimulus with a certain frequency. To increase the information transfer rate (ITR) in SSVEP-based systems, due to the frequency resolution restriction, we are forced to broaden the frequency range, which causes harmonic frequencies to come into the stimulation frequency range. Conventional canonical correlation analysis (CCA) may be associated with error for SSVEP frequency recognition at stimulation frequencies with harmonic relations. The number of harmonics considered to construct reference signals are determined adaptively; for frequencies whose second harmonic exists in the frequency range, two harmonics are used, and …

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Research On The Dynamic Networking Of Smart Meters Based On Characteristics Of The Collected Data, Yaxin Huang, Yunlian Sun, Xiaodi Zhang Jan 2019

Research On The Dynamic Networking Of Smart Meters Based On Characteristics Of The Collected Data, Yaxin Huang, Yunlian Sun, Xiaodi Zhang

Turkish Journal of Electrical Engineering and Computer Sciences

In order to accurately collect the electricity usage information from the smart meter which uses the power line for communication, this paper proposes the method of dynamic networking to enhance the reliability of the smart meter communication. We shall firstly establish a logical topology between the smart meter and the concentrator with reference to their communication paths within the power supply range of the same transformer, and then grade smart meters, and choose the relay for each level network based on the selection methods of relay, and finally use the improved ant colony algorithm to choose the optimal communication path …

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Exploiting Stochastic Petri Nets With Fuzzy Parameters To Predict Efficient Drug Combinations For Spinal Muscular Atrophy, Rza Bashi̇rov, Recep Duranay, Adi̇l Şeytanoğlu, Mani Mehraei, Ni̇met Akçay Jan 2019

Exploiting Stochastic Petri Nets With Fuzzy Parameters To Predict Efficient Drug Combinations For Spinal Muscular Atrophy, Rza Bashi̇rov, Recep Duranay, Adi̇l Şeytanoğlu, Mani Mehraei, Ni̇met Akçay

Turkish Journal of Electrical Engineering and Computer Sciences

Randomness and uncertainty are two major problems one faces while modeling nonlinear dynamics of molecular systems. Stochastic and fuzzy methods are used to cope with these problems, but there is no consensus among researchers regarding which method should be used when. This is because the areas of applications of these methods are overlapping with differences in opinions. In the present work, we demonstrate how to use stochastic Petri nets with fuzzy parameters to manage random timing of biomolecular events and deal with the uncertainty of reaction rates in biological networks. The approach is demonstrated through a case study of simulation-based …

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Application Of Multiscale Fuzzy Entropy Features For Multilevel Subject-Dependent Emotion Recognition, Hamzah Lotfalinezhad, Ali Maleki Jan 2019

Application Of Multiscale Fuzzy Entropy Features For Multilevel Subject-Dependent Emotion Recognition, Hamzah Lotfalinezhad, Ali Maleki

Turkish Journal of Electrical Engineering and Computer Sciences

Emotion recognition can be used in clinical and nonclinical situations. Despite previous works which mostly used time and frequency features of electroencephalogram (EEG) signals in subject-dependent emotion recognition issues, we used multiscale fuzzy entropy as a nonlinear dynamic feature. The EEG signals of the well-known Database for Emotion Analysis Using Physiological signals dataset was used for classification of two and three levels of emotions in arousal and valence space. The compound feature selection with a cost of average accuracy of support vector machine classifier was used to reduce feature dimensions. For subject-dependent systems, the proposed method is superior in comparison …

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Decision-Making For Small Industrial Internet Of Things Using Decision Fusion, Tuğrul Çavdar, Nader Ebrahimpour Jan 2019

Decision-Making For Small Industrial Internet Of Things Using Decision Fusion, Tuğrul Çavdar, Nader Ebrahimpour

Turkish Journal of Electrical Engineering and Computer Sciences

The industrial Internet of Things (IIoT) is a new field of Internet of Things (IoT) that has gained more popularity recently in industrial units and makes it possible to access information anywhere and anytime. In other words, geographic coordinates cannot prevent obtaining equipment and its data. Today, it is possible to manage and control equipment simply without spending time in an operational area and just by using the IIoT. This system collects data from manufacturing and production units by using wireless sensor networks or other networks for classification of fault detection. These data are then used after analysis to allow …

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Gacnn Sleeptunenet: A Genetic Algorithm Designing The Convolutional Neural Network Architecture For Optimal Classification Of Sleep Stages From A Single Eeg Channel, Shahnawaz Qureshi, Seppo Karilla, Sirirut Vanichayobon Jan 2019

Gacnn Sleeptunenet: A Genetic Algorithm Designing The Convolutional Neural Network Architecture For Optimal Classification Of Sleep Stages From A Single Eeg Channel, Shahnawaz Qureshi, Seppo Karilla, Sirirut Vanichayobon

Turkish Journal of Electrical Engineering and Computer Sciences

This study presents a method for designing--by a genetic algorithm, without manual intervention--the feature learning architecture for classification of sleep stages from a single EEG channel, when using a convolutional neural network called GACNN SleepTuneNet. Two EEG electrode positions were selected, namely FP2-F4 and FPz-Cz, from two available datasets. Twenty-five generations were involved in diagnosis without hand-crafted features, to learn the architecture for classification of sleep stages based on AASM standard. Based on the results, our model not only achieved the highest classification accuracy, but it also distinguished the sleep stages based on either of the two EEG electrode signals, …

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Abc-Based Stacking Method For Multilabel Classification, Weimin Ding, Shengli Wu Jan 2019

Abc-Based Stacking Method For Multilabel Classification, Weimin Ding, Shengli Wu

Turkish Journal of Electrical Engineering and Computer Sciences

Multilabel classification is a supervised learning problem wherein each individual instance is associated with multiple labels. Ensemble methods are effective in managing multilabel classification problems by creating a set of accurate, diverse classifiers and then combining their outputs to produce classifications. This paper presents a novel stacking-based ensemble algorithm, ABC-based stacking, for multilabel classification. The artificial bee colony algorithm, along with a single-layer artificial neural network, is used to find suitable meta-level classifier configurations. The optimization goal of the meta-level classifier is to maximize the average accuracy of classification of all the instances involved. We run an experiment on 10 …

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Rough Fuzzy Cuckoo Search For Triclustering Microarray Gene Expression Data, Swathypriyadharsini Palaniswamy, Premalatha K Jan 2019

Rough Fuzzy Cuckoo Search For Triclustering Microarray Gene Expression Data, Swathypriyadharsini Palaniswamy, Premalatha K

Turkish Journal of Electrical Engineering and Computer Sciences

Analyzing time series microarray gene expression data is a computational challenge due to its three-dimensional characteristics. Triclustering techniques are applied to three-dimensional data for mining similarly expressed genes under a subset of conditions and time points. In this work, a novel rough fuzzy cuckoo search algorithm is proposed for triclustering genes across samples and time points simultaneously. By applying the upper and lower approximation of rough set theory and the objective function of fuzzy k-means, rough fuzzy k-means was incorporated into a cuckoo search to handle the uncertainty of the data. The proposed method was applied to three real-life time …

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A New Technique For The Measurement And Assessment Of Carotid Artery Wall Vibrations Using Ultrasound Rf Echoes, Samrand Sharifi, Hamid Behnam, Zahra Alizadeh Sani Jan 2019

A New Technique For The Measurement And Assessment Of Carotid Artery Wall Vibrations Using Ultrasound Rf Echoes, Samrand Sharifi, Hamid Behnam, Zahra Alizadeh Sani

Turkish Journal of Electrical Engineering and Computer Sciences

Atherosclerosis is known as the leading cause of heart attacks and brain strokes. One of the symptoms of this disease is the reduction of artery wall motion caused by age. This study presents a novel method to extract high frequency components of wall motion, wall vibrations, based on discrete wavelet transform. The fractal dimension, largest Lyapunov exponent, and spectral entropy are then analyzed to indicate the chaotic behavior in wall vibrations. Phase information from demodulated radiofrequency signals is extracted and the entropy of phase-difference is computed as a statistical measure for better characterization of the artery wall tissue. The results …

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Investigating The Occurrence Mechanism Of Cytokine-Like Formations By The Electromagnetic Approach, Cahi̇t Canbay, Özgün Palak, Aydoğa Kallem Jan 2019

Investigating The Occurrence Mechanism Of Cytokine-Like Formations By The Electromagnetic Approach, Cahi̇t Canbay, Özgün Palak, Aydoğa Kallem

Turkish Journal of Electrical Engineering and Computer Sciences

This study aims to elucidate the production mechanism of cytokine-like formations secreted from T cells and similar cells by electromagnetic modeling techniques. Three Hertz dipole antennas polarized in arbitrary directions were placed without touching each other at the center of spherical T-cell models to test the Canbay hypothesis about the formation mechanism of cytokines (CHAFMOC) on T-cell surfaces. A dielectrophoretic force field was created within the gelatin layer of the T-cell model. The prepared control and electromagnetically stimulated T-cell model samples were incubated in water in a glass container in a Faraday cage for the specified period and then photographed. …

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Three-Channel Control Architecture For Multilateral Teleoperation Under Time Delay, Uğur Tümerdem Jan 2019

Three-Channel Control Architecture For Multilateral Teleoperation Under Time Delay, Uğur Tümerdem

Turkish Journal of Electrical Engineering and Computer Sciences

Multilateral teleoperation is an extension of bilateral/haptic teleoperation framework to multiple operators/robots and finds applications in haptic training. As in bilateral teleoperation, time delay is an important problem, and stability and transparency, which quantifies the performance of the teleoperation system, are critical in the design of multilateral control systems. This paper proposes a novel three-channel-based multilateral control architecture with damping injection to guarantee delay-independent L2 stability and high transparency in multilateral teleoperation systems. The theoretical and computational analyses are verified with experiment results.

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Identifying Criminal Organizations From Their Social Network Structures, Muhammet Serkan Çi̇nar, Burkay Genç, Hayri̇ Sever Jan 2019

Identifying Criminal Organizations From Their Social Network Structures, Muhammet Serkan Çi̇nar, Burkay Genç, Hayri̇ Sever

Turkish Journal of Electrical Engineering and Computer Sciences

Identification of criminal structures within very large social networks is an essential security feat. By identifying such structures, it may be possible to track, neutralize, and terminate the corresponding criminal organizations before they act. We evaluate the effectiveness of three different methods for classifying an unknown network as terrorist, cocaine, or noncriminal. We consider three methods for the identification of network types: evaluating common social network analysis metrics, modeling with a decision tree, and network motif frequency analysis. The empirical results show that these three methods can provide significant improvements in distinguishing all three network types. We show that these …

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Local Directional-Structural Pattern For Person-Independent Facial Expression Recognition, Farkhod Makhmudkhujaev, Md Tauhid Bin Iqbal, Byungyong Ryu, Oksam Chae Jan 2019

Local Directional-Structural Pattern For Person-Independent Facial Expression Recognition, Farkhod Makhmudkhujaev, Md Tauhid Bin Iqbal, Byungyong Ryu, Oksam Chae

Turkish Journal of Electrical Engineering and Computer Sciences

Existing popular descriptors for facial expression recognition often suffer from inconsistent feature description, experiencing poor accuracies. We present a new local descriptor, local directional-structural pattern (LDSP), in this work to address this issue. Unlike the existing local descriptors using only the texture or edge information to represent the local structure of a pixel, the proposed LDSP utilizes the positional relationship of the top edge responses of the target pixel to extract more detailed structural information of the local texture. We further exploit such information to characterize expression-affiliated crucial textures while discarding the random noisy patterns. Moreover, we introduce a globally …

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Measurement Of Network-Based And Random Meetings In Social Networks, Pranav Nerurkar, Madhav Chandane, Sunil Bhirud Jan 2019

Measurement Of Network-Based And Random Meetings In Social Networks, Pranav Nerurkar, Madhav Chandane, Sunil Bhirud

Turkish Journal of Electrical Engineering and Computer Sciences

Social networks are created by the underlying behavior of the actors involved in them. Each actor has interactions with other actors in the network and these interactions decide whether a social relationship should develop between them. Such interactions may occur due to meeting processes such as chance-based meetings or network-based (choice) meetings. Depending upon which of these two types of interactions plays a greater role in creation of links, a social network shall evolve accordingly. This evolution shall result in the social network obtaining a suitable structure and certain unique features. The aim of this work is to determine the …

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Automated Elimination Of Eog Artifacts In Sleep Eeg Using Regression Method, Mehmet Dursun, Seral Özşen, Sali̇h Güneş, Bayram Akdemi̇r, Şebnem Yosunkaya Jan 2019

Automated Elimination Of Eog Artifacts In Sleep Eeg Using Regression Method, Mehmet Dursun, Seral Özşen, Sali̇h Güneş, Bayram Akdemi̇r, Şebnem Yosunkaya

Turkish Journal of Electrical Engineering and Computer Sciences

Sleep electroencephalogram (EEG) signal is an important clinical tool for automatic sleep staging process. Sleep EEG signal is effected by artifacts and other biological signal sources, such as electrooculogram (EOG) and electromyogram (EMG), and since it is effected, its clinical utility reduces. Therefore, eliminating EOG artifacts from sleep EEG signal is a major challenge for automatic sleep staging. We have studied the effects of EOG signals on sleep EEG and tried to remove them from the EEG signals by using regression method. The EEG and EOG recordings of seven subjects were obtained from the Sleep Research Laboratory of Meram Medicine …

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Polyhedral Conic Kernel-Like Functions For Svms, Gürkan Öztürk, Emre Çi̇men Jan 2019

Polyhedral Conic Kernel-Like Functions For Svms, Gürkan Öztürk, Emre Çi̇men

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, we propose a new approach that can be used as a kernel-like function for support vector machines (SVMs) in order to get nonlinear classification surfaces. We combined polyhedral conic functions (PCFs) with the SVM method. To get nonlinear classification surfaces, kernel functions are used with SVMs. However, the parameter selection of the kernel function affects the classification accuracy. Generally, in order to get successful classifiers which can predict unknown data accurately, best parameters are explored with the grid search method which is computationally expensive. We solved this problem with the proposed method. There is no need to …

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Understanding Attribute And Social Circle Correlation In Social Networks, Pranav Nerurkar, Madhav Chandane, Sunil Bhirud Jan 2019

Understanding Attribute And Social Circle Correlation In Social Networks, Pranav Nerurkar, Madhav Chandane, Sunil Bhirud

Turkish Journal of Electrical Engineering and Computer Sciences

Social circles, groups, lists, etc. are functionalities that allow users of online social network (OSN) platforms to manually organize their social media contacts. However, this facility provided by OSNs has not received appreciation from users due to the tedious nature of the task of organizing the ones that are only contacted periodically. In view of the numerous benefits of this functionality, it may be advantageous to investigate measures that lead to enhancements in its efficacy by allowing for automatic creation of customized groups of users (social circles, groups, lists, etc). The field of study for this purpose, i.e. creating coarse-grained …

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A Novel Accuracy Assessment Model For Video Stabilization Approaches Based On Background Motion, Md Alamgir Hossain, Tien-Dung Nguyen, Eui Nam Huh Jan 2019

A Novel Accuracy Assessment Model For Video Stabilization Approaches Based On Background Motion, Md Alamgir Hossain, Tien-Dung Nguyen, Eui Nam Huh

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we propose a new accuracy measurement model for the video stabilization method based on background motion that can accurately measure the performance of the video stabilization algorithm. Undesired residual motion present in the video can quantitatively be measured by the pixel by pixel background motion displacement between two consecutive background frames. First of all, foregrounds are removed from a stabilized video, and then we find the two-dimensional flow vectors for each pixel separately between two consecutive background frames. After that, we calculate a Euclidean distance between these two flow vectors for each pixel one by one, which …

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