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2018

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Articles 751 - 780 of 1217

Full-Text Articles in Computer Engineering

Bagged Tree Classification Of Arrhythmia Using Wavelets For Denoising, Compression, And Feature Extraction, Özgür Tomak, Temel Kayikçioğlu Jan 2018

Bagged Tree Classification Of Arrhythmia Using Wavelets For Denoising, Compression, And Feature Extraction, Özgür Tomak, Temel Kayikçioğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Arrhythmia, also known as dysrhythmia, is a condition involving an irregular heartbeat. A problem in the heart may cause problems in other organs, and as time passes, this will lead to more severe problems. Arrhythmia must be detected at an early stage to prevent such a problem occurring in the heart. Detection of arrhythmia from an electrocardiogram is an easy method that does not need much equipment and does not harm the patient. The purpose of this research is to find a faster and more accurate system to classify nine classes of arrhythmia. The St. Petersburg Institute of Cardiological Technics …

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Multilabel Learning For The Online Transient Stability Assessment Of Electric Power Systems, Peyman Beyranvand, Veysel Murat İstemi̇han Genç, Zehra Çataltepe Jan 2018

Multilabel Learning For The Online Transient Stability Assessment Of Electric Power Systems, Peyman Beyranvand, Veysel Murat İstemi̇han Genç, Zehra Çataltepe

Turkish Journal of Electrical Engineering and Computer Sciences

Dynamic security assessment of a large power system operating over a wide range of conditions requires an intensive computation for evaluating the system's transient stability against a large number of contingencies. In this study, we investigate the application of multilabel learning for improving training and prediction time, along with the prediction accuracy, of neural networks for online transient stability assessment of power systems. We introduce a new multilabel learning method, which uses a contingency clustering step to learn similar contingencies together in the same multilabel multilayer perceptron. Experimental results on two different power systems demonstrate improved accuracy, as well as …

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Novel Modified Impedance-Based Methods For Fault Location In The Presence Of A Fault Current Limiter, Javad Barati, Aref Doroudi Jan 2018

Novel Modified Impedance-Based Methods For Fault Location In The Presence Of A Fault Current Limiter, Javad Barati, Aref Doroudi

Turkish Journal of Electrical Engineering and Computer Sciences

A fault current limiter (FCL) is promising novel electric equipment to effectively reduce excessive short circuit current in power networks. The presence of a FCL at the time of a fault occurrence makes it necessary to consider new settings for protective relays and fault locators. This paper examines the presence of a FCL in power networks and its effects on single-ended impedance-based fault location methods. It will be shown that FCL deployment in a transmission line makes the traditional fault location method inefficient. Two modified methods are presented to solve the problem. The modified methods locate the fault point using …

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Performance Evaluation Of Alumina Trihydrate And Silica-Filled Silicone Rubber Composites For Outdoor High-Voltage Insulations, Hidayatullah Khan, Muhammad Amin, Ayaz Ahmad Jan 2018

Performance Evaluation Of Alumina Trihydrate And Silica-Filled Silicone Rubber Composites For Outdoor High-Voltage Insulations, Hidayatullah Khan, Muhammad Amin, Ayaz Ahmad

Turkish Journal of Electrical Engineering and Computer Sciences

In recent years, silicone rubber-based composites have been widely investigated for outdoor applications due to their promising insulating properties. However, mechanical, thermal, and tracking properties of pure silicone rubber are very poor, which restrains its application for long-term performance. In this research work, the influence of microsized alumina trihydrate (ATH) and micro/nanosized silica (SiO$_{2})$ fillers on mechanical, thermal, and electrical properties of room temperature vulcanized silicone rubber (RTV-SiR) has been studied. SiR-blends with varying amounts of ATH and SiO$_{2}$ particles were prepared by blending in a two-roll mixing mill, compression molding, and postcuring processes in sequence. In order to evaluate …

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A Selective Frequency Reconfigurable Bandstop Metamaterial Filter For Wlan Applications, Bachir Belkadi, Zoubir Mahdjoub, Mohammed Lamine Seddiki, Mourad Nedil Jan 2018

A Selective Frequency Reconfigurable Bandstop Metamaterial Filter For Wlan Applications, Bachir Belkadi, Zoubir Mahdjoub, Mohammed Lamine Seddiki, Mourad Nedil

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, two designs of bandstop filters are presented and implemented, each one composed of a coplanar waveguide loaded with a resonator. The first design has a structure with circular resonators, and the second design is a frequency reconfigurable filter with a rectangular spiral resonator and PIN diodes. The designs are based on the use of metamaterial to create notch filters for microwave applications. The Nicolson--Ross--Weir method, used to extract the refractive index, is also described to highlight the supernatural electromagnetic characteristic of metamaterials. From the simulation results, the filters exhibit high frequency selectivity via the presence of reflection …

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Application Of Synthetic Informative Minority Over-Sampling (Simo) Algorithm Leveraging Support Vector Machine (Svm) On Small Datasets With Class Imbalance, Akshatha Fakkeriah Kallappanamatt Jan 2018

Application Of Synthetic Informative Minority Over-Sampling (Simo) Algorithm Leveraging Support Vector Machine (Svm) On Small Datasets With Class Imbalance, Akshatha Fakkeriah Kallappanamatt

Dissertations

Developing predictive models for classification problems considering imbalanced datasets is one of the basic difficulties in data mining and decision-analytics. A classifier’s performance will decline dramatically when applied to an imbalanced dataset. Standard classifiers such as logistic regression, Support Vector Machine (SVM) are appropriate for balanced training sets whereas provides suboptimal classification results when used on unbalanced dataset. Performance metric with prediction accuracy encourages a bias towards the majority class, while the rare instances remain unknown though the model contributes a high overall precision. There are chances where minority instances might be treated as noise and vice versa. (Haixiang et …

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Localization Of Microcalcification On The Mammogram Using Deep Convolutional Neural Network, Jieun Jhang Jan 2018

Localization Of Microcalcification On The Mammogram Using Deep Convolutional Neural Network, Jieun Jhang

Electronic Theses and Dissertations

Breast cancer is the most common cancer in women worldwide, and the mammogram is the most widely used screening technique for breast cancer. To make a diagnosis in the early stage of breast cancer, the appearance of masses and microcalcifications on the mammogram are two crucial indicators. Notably, the early detection of malignant microcalcifications can facilitate the diagnosis and the treatment of breast cancer at the appropriate time. Making an accurate evaluation on microcalcifications is a timeconsuming and challenging task for the radiologists due to the small size and the low contrast of microcalcification. Compared to the background and mammogram …

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An Approach To Finding Parking Space Using The Csi-Based Wifi Technology, Yunfan Zhang Jan 2018

An Approach To Finding Parking Space Using The Csi-Based Wifi Technology, Yunfan Zhang

Electronic Theses and Dissertations

With ever-increasing number of vehicles and shortages of parking spaces, parking has always been a very important issue in transportation. It is necessary to use advanced intelligent technologies to help drivers find parking spaces, quickly. In this thesis, an approach to finding empty spaces in parking lots using the CSI-based WiFi technology is presented. First, the channel state information (CSI) of received WiFi signals is analyzed. The features of CSI data that are strongly correlated with the number of empty slots in parking lots are identified and extracted. A machine learning technique to perform multi-class classification that categorizes the input …

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Wi-Fi Finger-Printing Based Indoor Localization Using Nano-Scale Unmanned Aerial Vehicles, Appala Narasimha Raju Chekuri Jan 2018

Wi-Fi Finger-Printing Based Indoor Localization Using Nano-Scale Unmanned Aerial Vehicles, Appala Narasimha Raju Chekuri

Electronic Theses and Dissertations

Explosive growth in the number of mobile devices like smartphones, tablets, and smartwatches has escalated the demand for localization-based services, spurring development of numerous indoor localization techniques. Especially, widespread deployment of wireless LANs prompted ever increasing interests in WiFi-based indoor localization mechanisms. However, a critical shortcoming of such localization schemes is the intensive time and labor requirements for collecting and building the WiFi fingerprinting database, especially when the system needs to cover a large space. In this thesis, we propose to automate the WiFi fingerprint survey process using a group of nano-scale unmanned aerial vehicles (NAVs). The proposed system significantly …

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Review Of The Effectiveness Of Impulse Testing For The Evaluation Of Cable Insulation Quality And Recommendations For Quality Testing, Adrian Coughlan, Joseph Kearney, Tom Looby Jan 2018

Review Of The Effectiveness Of Impulse Testing For The Evaluation Of Cable Insulation Quality And Recommendations For Quality Testing, Adrian Coughlan, Joseph Kearney, Tom Looby

Conference papers

Abstract— This project investigates impulse breakdown testing as a means of determining the as constructed standard of MV power cable. A literature survey is undertaken to elucidate the place of this test in an overall cable test regime and to determine the factors that impact on the performance of the test method. Testing was undertaken on ESB Networks cables to establish if a merit order ranking was feasible based on this test and to determine if the test could detect defects in the inner semiconducting layer. Based on this, conclusions and recommendations are made regarding the overall applicability and usefulness …

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Examining A Hate Speech Corpus For Hate Speech Detection And Popularity Prediction, Filip Klubicka, Raquel Fernandez Jan 2018

Examining A Hate Speech Corpus For Hate Speech Detection And Popularity Prediction, Filip Klubicka, Raquel Fernandez

Other resources

As research on hate speech becomes more and more relevant every day, most of it is still focused on hate speech detection. By attempting to replicate a hate speech detection experiment performed on an existing Twitter corpus annotated for hate speech, we highlight some issues that arise from doing research in the field of hate speech, which is essentially still in its infancy. We take a critical look at the training corpus in order to understand its biases, while also using it to venture beyond hate speech detection and investigate whether it can be used to shed light on other …

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Transformer Incipient Fault Diagnosis On The Basis Of Energy-Weighted Dga Usingan Artificial Neural Network, Md Danish Equbal, Shakeb Ahmad Khan, Tarikul Islam Jan 2018

Transformer Incipient Fault Diagnosis On The Basis Of Energy-Weighted Dga Usingan Artificial Neural Network, Md Danish Equbal, Shakeb Ahmad Khan, Tarikul Islam

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a transformer incipient fault diagnosis model has been developed with the help of an artificial neural network (ANN), taking into account the difference in the energy required to produce the different fault gases. The key fault gases are indicative of the fault type prevailing in the transformer. However, in conventional studies, the energy difference in fault gas formation is not considered while adopting the key gas method for fault diagnosis. In this work, a weighting factor has been used to take into account this relative difference in energy requirement for various fault gas formations. The fault gas …

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Real-Time Chaff Generation For A Biometric Fuzzy Vault, Manvjeet Kaur, Sanjeev Sofat Jan 2018

Real-Time Chaff Generation For A Biometric Fuzzy Vault, Manvjeet Kaur, Sanjeev Sofat

Turkish Journal of Electrical Engineering and Computer Sciences

Biometric technology is rapidly being adopted in wide variety of security applications. However, the system itself is not completely foolproof and is vulnerable to many attacks. Some of the attacks on the biometric system are very severe, one of which is the attack on template security. In spite of the various template security techniques presented in the literature, none of them is able to provide security, diversity, revocability, and good performance simultaneously to the biometric system. Fuzzy vault is one of the most promising bio-cryptographic techniques to prevent the template data from being misused. To make the fuzzy vault practically …

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An Optimized Multiobjective Cpu Job Scheduling Using Evolutionary Algorithms, Santhi Venkatraman, Dharshikha Selvagopal Jan 2018

An Optimized Multiobjective Cpu Job Scheduling Using Evolutionary Algorithms, Santhi Venkatraman, Dharshikha Selvagopal

Turkish Journal of Electrical Engineering and Computer Sciences

Scheduling in a multiprocessor parallel computing environment is an NP-hard optimization problem. The main objective of this work is to obtain a schedule in a distributed computing system (DCS) environment that minimizes the makespan and maximizes the throughput. We study the use of two of the evolutionary swarm optimization techniques, the firefly algorithm and the artificial bee colony (ABC) algorithm, to optimize the scheduling in a DCS. We also enhance the traditional ABC algorithm by merging the genetic algorithm techniques of crossover and mutation with the employed bee phase and the onlooker phase, respectively. The resulting enhanced ABC algorithm is …

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Blood Glucose Control Using An Abc Algorithm-Based Fuzzy-Pid Controller, Seli̇m Soylu, Kenan Danişman Jan 2018

Blood Glucose Control Using An Abc Algorithm-Based Fuzzy-Pid Controller, Seli̇m Soylu, Kenan Danişman

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a Mamdani-type fuzzy controller is proposed as the controller part of an artificial pancreas. The controller is optimized with the artificial bee colony optimization algorithm. The glucose{insulin regulatory system, based on a nonlinear differential model in the presence of delay, is used both for virtual patient and healthy person data. The main target of the controller is to mimic a blood glucose concentration profile of the healthy person with exogenous insulin infusion. Simulations are performed to assess the control function in terms of tracking the blood glucose concentration profile of the healthy person and minimizing errors. To …

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Two-Area Load Frequency Control With Redox Ow Battery Using Intelligentalgorithms In A Restructured Scenario, Lakshmi Dhandapani, Fathima Peer, Ranganath Muthu Jan 2018

Two-Area Load Frequency Control With Redox Ow Battery Using Intelligentalgorithms In A Restructured Scenario, Lakshmi Dhandapani, Fathima Peer, Ranganath Muthu

Turkish Journal of Electrical Engineering and Computer Sciences

Load frequency control (LFC) is an essential aspect of power system dynamics. This paper focuses on the optimization of LFC for a two-area deregulated power system under different scenarios. A recent nature-inspired ower pollination algorithm (FPA), based on the pollination process of plants, is used to tune the proportional integral (PI) controller parameters of LFC for the global minima solution. FPA is compared with a genetic algorithm, particle swarm optimization, and a conventional PI controller. During large load disturbance in the areas, controllers are incapable of reducing frequency deviations and tie-line power oscillations due to the slow response of the …

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Construction Of A Turkish Proposition Bank, Koray Ak, Cansu Toprak, Volkan Esgel, Olcay Taner Yildiz Jan 2018

Construction Of A Turkish Proposition Bank, Koray Ak, Cansu Toprak, Volkan Esgel, Olcay Taner Yildiz

Turkish Journal of Electrical Engineering and Computer Sciences

This paper describes our approach to developing the Turkish PropBank by adopting the semantic role-labeling guidelines of the original PropBank and using the translation of the English Penn-TreeBank as a resource. We discuss the semantic annotation process of the PropBank and language-specific cases for Turkish, the tools we have developed for annotation, and quality control for multiuser annotation. In the current phase of the project, more than 9500 sentences are semantically analyzed and predicate-argument information is extracted for 1330 verbs and 1914 verb senses. Our plan is to annotate 17,000 sentences by the end of 2017.

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Choice Of Battery Energy Storage For A Hybrid Renewable Energy System, Kusum Lata Tharani, Ratna Dahiya Jan 2018

Choice Of Battery Energy Storage For A Hybrid Renewable Energy System, Kusum Lata Tharani, Ratna Dahiya

Turkish Journal of Electrical Engineering and Computer Sciences

There are certain unelectrified villages across the Indian subcontinent where providing supply through the grid is difficult due to forest cover or mountainous terrain. The most feasible option is to provide off-grid electrification through renewable energy resources such as solar or wind energy. These intermittent sources do not promise a 24 $\times $ 7 supply system. Thus, along with solar or wind energy systems, it becomes important to use a renewable resource, such as biomass, which is available in abundance in rural areas. The need for battery energy storage becomes mandatory in order to store the surplus energy produced by …

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Volumetric 3d Reconstruction Of Real Objects Using Voxel Mapping Approach In A Multiple-Camera Environment, Tushar Jadhav, Kulbir Singh, Aditya Abhyankar Jan 2018

Volumetric 3d Reconstruction Of Real Objects Using Voxel Mapping Approach In A Multiple-Camera Environment, Tushar Jadhav, Kulbir Singh, Aditya Abhyankar

Turkish Journal of Electrical Engineering and Computer Sciences

Extracting 3D information from 2D images is an inverse estimation problem and a challenging task in itself. The aim of 2D to 3D reconstruction is to generate either a volume or a surface representing the object from multiple views. This paper presents a simple and accurate multiple-view volumetric 3D reconstruction method using an integrated approach based on homography estimation and voxel mapping. The homography-based approaches give accurate estimates but do not provide system dynamics. The voxel-based volumetric reconstruction methods provide system dynamics that are essential for system modeling. However, they face challenges while modeling the concavities. This paper presents a …

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Qrmw: Quantum Representation Of Multi Wavelength Images, Engi̇n Şahi̇n, İhsan Yilmaz Jan 2018

Qrmw: Quantum Representation Of Multi Wavelength Images, Engi̇n Şahi̇n, İhsan Yilmaz

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, we propose quantum representation of multiwavelength images (QRMW) that gives preparation and retrieving procedures of quantum images. The proposed QRMW model represents multichannel and $2^{n}\times 2^{m}$ images. Moreover, we present image comparison and some image operations based on the QRMW model. Comparing our model with the models in the literature, the QRMW model has less time complexity. It also uses fewer qubits than existing models in the literature.

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Nonintrusive Identification Of Residential Appliances Using Harmonic Analysis, Srdjan Djordjevic, Milan Simic Jan 2018

Nonintrusive Identification Of Residential Appliances Using Harmonic Analysis, Srdjan Djordjevic, Milan Simic

Turkish Journal of Electrical Engineering and Computer Sciences

The role of nonintrusive load monitoring (NILM) is to identify the operating schedules of individual appliances and their power consumption from single-point electrical measurements. This paper discusses appliance load monitoring based on the harmonic analysis of the steady-state current, which is specifically suited for identification of nonlinear appliances. The existing harmonic-based NILM methods have limited applicability due to the fact that their complexity increases exponentially with the number of target appliances. In order to overcome this problem, this study suggests the use of the step changes of current harmonic phasors as a feature for appliance detection. The key benefit of …

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Data Clustering Using Ede, An Enhanced Differential Evolution Algorithm With Fuzzy C-Means Technique, Meera Ramadas, Ajith Abraham Jan 2018

Data Clustering Using Ede, An Enhanced Differential Evolution Algorithm With Fuzzy C-Means Technique, Meera Ramadas, Ajith Abraham

Turkish Journal of Electrical Engineering and Computer Sciences

Clustering is the way toward sorting out items into groups whose individuals are comparative somehow. It is a gathering of articles that are intelligent inside, yet unmistakably not at all like the items having a place with different groups. Clustering of data plays a major part in efficient customer segmentation, organization of documents, information retrieval, extraction of topics, classification, collaborative filtering, visualization, and indexing. In the area of information retrieval systems, evolutionary algorithms work in a robust and efficient manner for clustering. To overcome the problem of local maxima, various nature-inspired metaheuristic algorithms like particle swarm optimization, artificial bee colony, …

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Analysis And Design Of A Converter Based On Noncascading Structure, Sunil Kumar, Kanwar Pal Singh Rana, Vineet Kumar Jan 2018

Analysis And Design Of A Converter Based On Noncascading Structure, Sunil Kumar, Kanwar Pal Singh Rana, Vineet Kumar

Turkish Journal of Electrical Engineering and Computer Sciences

In the present work, a converter employing two noncascading structures, combined in a single circuit, is presented. The power stored by the storage element is transferred to two subconverters by means of two storage capacitors that complement each other. The stress on the main power switch is of interest as it reduces as the load falls, which in turn reduces the power loss. By means of the storage elements, the input power factor as well as the load transient response can be improved simultaneously. The overall efficiency is high because the amount of power processed twice decreases. There is no …

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Mutatedsocioagentsim (Msas): Semisupervised Modelling Of Multiagent Simulation To Predict And Detect The Mutation In A Camouflaged Social Network, Karthika Subbaraj, Bose Sundan Jan 2018

Mutatedsocioagentsim (Msas): Semisupervised Modelling Of Multiagent Simulation To Predict And Detect The Mutation In A Camouflaged Social Network, Karthika Subbaraj, Bose Sundan

Turkish Journal of Electrical Engineering and Computer Sciences

A social network is a networked structure formed by a set of agents/actors. It describes their interrelationships that facilitate the exchange and flow of resources and information. A camouflaged social network is one such community that influences the underlying structure and the profile of the agents, to cause mutation. The proposed MSAM is a novel system that simulates a multiagent network whose community structure is analyzed to identify the critical agents by studying the mutations caused due to attachment and detachment of agents. The isolation of the tagged agents will demonstrate disruption of information flow, which leads to the dismantling …

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Effect Of Intuitionistic Fuzzy Normalization In Microarray Gene Selection, Prema Ramasamy, Premalatha Kandhasamy Jan 2018

Effect Of Intuitionistic Fuzzy Normalization In Microarray Gene Selection, Prema Ramasamy, Premalatha Kandhasamy

Turkish Journal of Electrical Engineering and Computer Sciences

Analysis of gene expression data is essential in microarray gene expression in order to retrieve the required information. Gene expression data generally contain a large number of genes but a small number of samples. The complicated relations among the different genes make analysis more difficult, and removing irrelevant genes improves the quality of results. This paper presents two fuzzy preprocessing techniques, using a fuzzy set (FS) and intuitionistic fuzzy set (IFS), to normalize datasets. In the feature selection part, four statistical methods were used. Using three publicly available gene expression datasets, the fuzzy normalization techniques were compared with two standard …

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Improvement Of Air Pollution Prediction In A Smart City And Its Correlation With Weather Conditions Using Metrological Big Data, Talat Zaree, Ali Reza Honarvar Jan 2018

Improvement Of Air Pollution Prediction In A Smart City And Its Correlation With Weather Conditions Using Metrological Big Data, Talat Zaree, Ali Reza Honarvar

Turkish Journal of Electrical Engineering and Computer Sciences

Smart cities are an important concept for urban development. This concept addresses many current critical urban problems including traffic and environmental pollution. As utilization of the Internet of things and technology in smart cities increases, large volumes of big data are generated and collected by sensors embedded at different places in the city, which present a real-time display of what is happening throughout the city at all times. Such data should be processed and analyzed as a response to ensure effectiveness and improvement in quality of provided services; correct use and analysis of such data is valuable. Big data mining …

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Topological Feature Extraction Of Nonlinear Signals And Trajectories And Its Application In Eeg Signals Classification, Saleh Lashkari, Ali Sheikhani, Mohammad Reza Hashemi Golpayegani, Ali Moghimi, Hamid Reza Kobravi Jan 2018

Topological Feature Extraction Of Nonlinear Signals And Trajectories And Its Application In Eeg Signals Classification, Saleh Lashkari, Ali Sheikhani, Mohammad Reza Hashemi Golpayegani, Ali Moghimi, Hamid Reza Kobravi

Turkish Journal of Electrical Engineering and Computer Sciences

This study introduces seven topological features that characterize attractor dynamic of nonlinear and chaotic trajectories in a phase space. These features quantify volume, occupied space, nonuniformity, and curvature of trajectory. The features are evaluated as initial point invariant measures by a practical approach, which means that a feature is only sensitive to dynamic changes. The Lorenz and Rossler system trajectories are employed in this evaluation. Moreover, the proposed features are used in a real world application, i.e. epileptic seizure electroencephalogram signal classification. As the result shows, these features are efficient in this task in comparison with others studies that used …

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Optimum, Projected, And Regularized Extreme Learning Machine Methods With Singular Value Decomposition And L$_{2}$-Tikhonov Regularization, Mohanad Abd Shehab, Ni̇han Kahraman Jan 2018

Optimum, Projected, And Regularized Extreme Learning Machine Methods With Singular Value Decomposition And L$_{2}$-Tikhonov Regularization, Mohanad Abd Shehab, Ni̇han Kahraman

Turkish Journal of Electrical Engineering and Computer Sciences

The theory and implementation of an extreme learning machine (ELM) have proved that it is a simple, efficient, and accurate machine learning methodology. In an ELM, the hidden nodes are randomly initiated and fixed without iterative tuning. However, the optimal hidden layer neuron number ($L_{opt})$ is the key to ELM generalization performance where initializing this number by trial and error is not reasonably satisfied. Optimizing the hidden layer size using the leave-one-out cross validation method is a costly approach. In this paper, a fast and reliable statistical approach called optimum ELM (OELM) was developed to determine the minimum hidden layer …

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A Model Of Qos Differentiation Burst Assembly With Padding For Improving The Performance Of Obs Networks, Viet Minh Nhat Vo, Van Hoa Le, Hoang Son Nguyen, Manh Thanh Le Jan 2018

A Model Of Qos Differentiation Burst Assembly With Padding For Improving The Performance Of Obs Networks, Viet Minh Nhat Vo, Van Hoa Le, Hoang Son Nguyen, Manh Thanh Le

Turkish Journal of Electrical Engineering and Computer Sciences

Burst assembly is an operation at the ingress node of optical burst switching (OBS) networks that aggregates incoming packets from various access networks into larger carriers, called bursts. Depending on the density of incoming packets and the preset time or length thresholds, the completed bursts may have various lengths, but they must be at least equal to a minimum value ($B_{\min})$ to facilitate the switching in existing physical optical switches. If a completed burst is smaller than $B_{\min}$, it should be padded by padded bytes and it results in bandwidth utilization inefficiency. One solution to the problem is increasing the …

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Novel Low-Loss Microstrip Triplexer Using Coupled Lines And Step Impedance Cells For 4g And Wimax Applications, Abbas Rezaei, Leila Noori Jan 2018

Novel Low-Loss Microstrip Triplexer Using Coupled Lines And Step Impedance Cells For 4g And Wimax Applications, Abbas Rezaei, Leila Noori

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a new microstrip triplexer with flexible resonance frequencies is designed based on the properties of coupled lines, steps, and spiral cells. It operates at 2.67 GHz for 4G LTE and at 3.1 GHz and 3.43 GHz for IEEE 802.16 WiMAX. The close resonance frequencies make it suitable for frequency division duplex applications. In order to improve insertion loss, the LC equivalent circuit of the proposed resonator is analyzed. Moreover, careful alignment of the coupled lines and step impedance structures is performed to improve the insertion and return losses so that they are 0.72/0.63/0.81 dB and 24.5/24/24.7 dB, …

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