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Survey Of Network Embedding Techniques For Social Networks, Pranav Nerurkar, Madhav Chandane, Sunil Bhirud
Survey Of Network Embedding Techniques For Social Networks, Pranav Nerurkar, Madhav Chandane, Sunil Bhirud
Turkish Journal of Electrical Engineering and Computer Sciences
High dimensionality of data is a challenging scenario in the current era as the digital transformation of the society is in process. This problem is particularly complex in social networks as in such systems, it is coupled with other challenges such as interdependency of data points and heterogeneity of data sources. To overcome such disadvantages and aid in creation of downstream applications for social network analysis, network embedding techniques have been proposed. These techniques, in themselves, are not important but are the backbone of various network-based applications. Due to the scientific interest in this domain there has been a mushrooming …
Improving Side Lobe Level Of X-Band Microstrip Rotman Lens Utilizing Nonuniform Distribution Of Output Ports, Ehsan Zareian Jahromi, Raheleh Basiri, Parvin Salehi, Hamidreza Karami
Improving Side Lobe Level Of X-Band Microstrip Rotman Lens Utilizing Nonuniform Distribution Of Output Ports, Ehsan Zareian Jahromi, Raheleh Basiri, Parvin Salehi, Hamidreza Karami
Turkish Journal of Electrical Engineering and Computer Sciences
A new microstrip Rotman lens with enhanced side lobe level (SLL) is proposed for X-band applications. A proper nonuniform distribution of the initial width of output ports is considered to improve the SLL. The benefit of SLL improvement is not based on using additional attenuators or amplifiers at the output ports. Moreover, an analytical background is presented to investigate the resulting SLL of the proposed structure. The advantage of SLL enhancement is obtained at all noncorner scan angles considering 10 GHz operating frequency. As the middle input port is excited, more than 3 dB of SLL enhancement is achieved at …
Iterative Sensitivity Matrix-Based Magnetic Resonance Conductivity Tensor Imaging, Evren Deği̇rmenci̇
Iterative Sensitivity Matrix-Based Magnetic Resonance Conductivity Tensor Imaging, Evren Deği̇rmenci̇
Turkish Journal of Electrical Engineering and Computer Sciences
Magnetic resonance conductivity tensor imaging (MRCTI) reconstructs high-resolution anisotropic conductivity images, which are proved to have critical importance in radio-oncological imaging as well as source localization fields. In the MRCTI technique, linearly independent current injections are applied to the region to be imaged and resulting magnetic flux densities are measured using magnetic resonance imaging techniques. In this study, a novel iterative reconstruction algorithm based on a sensitivity matrix approach is proposed and tested using both simulated and experimental measurements. Obtained results show that the proposed technique can reconstruct anisotropic conductivity images with high and position-independent spatial resolution in addition to …
A Compact Wide-Slot Uwb Antennawith Reconfigurable And Sharp Dual-Band Notches For Underlay Cognitive Radioapplications, Falih Alnahwi, Abdulghafor Abdulhameed, Husham Swadi, Abdulkareem Abdullah
A Compact Wide-Slot Uwb Antennawith Reconfigurable And Sharp Dual-Band Notches For Underlay Cognitive Radioapplications, Falih Alnahwi, Abdulghafor Abdulhameed, Husham Swadi, Abdulkareem Abdullah
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a compact wide-slot ultrawide-band (UWB) antenna with reconfigurable and sharp dual-band notches compatible with the underlay cognitive radio systems. The antenna slot and tuning stub are reshaped in such a way that the proposed antenna operating bandwidth extends along the frequency band specified for UWB applications (3.1-10.6 GHz). In spite of their sharpness, the generated band notches perfectly cancel the interference with the entire 5 GHz wireless local area network (WLAN) frequency band (5.15-5.725 GHz) and that of the military X-band satellite communications downlink (7.25-7.745 GHz). The WLAN band notch is presented by attaching a pair of …
A Novel And Unified Approach For Averaged Channel Capacity And Averagedeffective Capacity Analyses Of Diversity Combining And Multihop Transmissionschemes In Flat Fading Environments, Ferkan Yilmaz, Mohamed-Slim Alouini
A Novel And Unified Approach For Averaged Channel Capacity And Averagedeffective Capacity Analyses Of Diversity Combining And Multihop Transmissionschemes In Flat Fading Environments, Ferkan Yilmaz, Mohamed-Slim Alouini
Turkish Journal of Electrical Engineering and Computer Sciences
n this paper, we introduce an Lp -norm aggregation to present a signal-to-noise ratio expression unified not only for such diversity combining schemes as equal-gain combining, maximal-ratio combining, and selection combining, but also for such transmission techniques as multihop transmission. Accordingly, we propose two moment-generating function-based approaches that both respectively unify the exact analyses of the averaged channel capacity and averaged effective capacity over generalized fading channels with respect to the diversity combining and multihop transmission schemes. Finally, the mathematical formalism is illustrated by numerical special cases and verified by simulations.
Pipelined Adders For Ultralow-Power Wearables, Mansi Jhamb, Tejaswini Dhall, Tamish Verma, Hinduja Puri
Pipelined Adders For Ultralow-Power Wearables, Mansi Jhamb, Tejaswini Dhall, Tamish Verma, Hinduja Puri
Turkish Journal of Electrical Engineering and Computer Sciences
For continuous real-time monitoring of personal health, wearable devices are indispensable. The constraintsof cost, power consumption, and limited device dimensions are the critical issues which need to be handled carefullywhile designing these battery-powered devices. The wearables employ high-end processors dedicated for complex signalprocessing. The core of every digital signal processor is its data path. The arithmetic units like adders constitute thecore of data path and addressing unit. This work proposes a novel low-complexity asynchronous pipelined adder. Theproposed design guarantees great savings in power and latency, which makes it a suitable candidate for low-power high-speed sophisticated wearables. The proposed design consumes …
Contribution Of Artificial Proprioception On A Dynamic Finger Flexion Task, Mehdi Hojatmadani, Evren Samur
Contribution Of Artificial Proprioception On A Dynamic Finger Flexion Task, Mehdi Hojatmadani, Evren Samur
Turkish Journal of Electrical Engineering and Computer Sciences
There has been a considerable effort to provide sensory feedback for myoelectric prostheses. Among the solutions provided in the literature, sensory substitution is an easy and cost-effective way to provide feedback through different sensory modalities at different locations on the body. In this study, we evaluate the effect of sensory substitution of force and position feedback on a two-degree-of-freedom dynamic finger flexion task. For this purpose, a new methodology and an experimental setup are developed. The experimental methodology is based on the "strength-dexterity test", working on the principle of buckling of compression springs. The experimental setup comprises a haptic interface, …
Power Electronic Controller With Time Sharing Switching Strategy For Grid Connected Pv Systems, Maria Jenisha Charles, Ammasaigounden Nanjappagounder, Binu Ben Jose Dharmaian Retnam
Power Electronic Controller With Time Sharing Switching Strategy For Grid Connected Pv Systems, Maria Jenisha Charles, Ammasaigounden Nanjappagounder, Binu Ben Jose Dharmaian Retnam
Turkish Journal of Electrical Engineering and Computer Sciences
The design and implementation of a high-efficiency two-stage power electronic controller for feeding power from a photovoltaic (PV) array to the load/utility grid is proposed. The PV array is connected to the load/utility grid through a boost converter and an inverter. The boost converter is controlled by sinusoidal pulse width modulation (SPWM) pulses so as to get a clamped quasi-sinusoidal waveform at the DC link. The inverter converts the clamped quasi-DC voltage into AC voltage using the SPWM controller. At any time only one switch operates at high frequency, thus yielding reduction in the switching losses of the converters. The …
Convex Polygon Triangulation Based On Planted Trivalent Binary Tree\\ And Ballot Problem, Muzafer Saracevic, Aybeyan Seli̇mi̇
Convex Polygon Triangulation Based On Planted Trivalent Binary Tree\\ And Ballot Problem, Muzafer Saracevic, Aybeyan Seli̇mi̇
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a new technique of generation of convex polygon triangulation based on planted trivalent binary tree and ballot notation. The properties of the Catalan numbers were examined and their decomposition and application in developing the hierarchy and triangulation trees were analyzed. The method of storage and processing of triangulation was constructed on the basis of movements through the polygon. This method was derived from vertices and leaves of the planted trivalent binary tree. The research subject of the paper is analysis and comparison of a constructed method for solving of convex polygon triangulation problem with other methods and …
Improving Anomaly Detection In Bgp Time-Series Data By New Guide Features And Moderated Feature Selection Algorithm, Mahmoud Hashem, Ahmed Bashandy, Samir Shaheen
Improving Anomaly Detection In Bgp Time-Series Data By New Guide Features And Moderated Feature Selection Algorithm, Mahmoud Hashem, Ahmed Bashandy, Samir Shaheen
Turkish Journal of Electrical Engineering and Computer Sciences
The Internet infrastructure relies on the Border Gateway Protocol (BGP) to provide essential routing information where abnormal routing behavior impairs global Internet connectivity and stability. Hence, employing anomaly detection algorithms is important for improving the performance of BGP routing protocol. In this paper, we propose two algorithms; the first is the guide feature generator (GFG), which generates guide features from traditional features in BGP time-series data using moving regression in combination with smoothed moving average. The second is a modified random forest feature selection algorithm which is employed to automatically select the most dominant features (ASMDF). Our mechanism shows that …
Detection Of Hemorrhage In Retinal Images Using Linear Classifiers And Iterative Thresholding Approaches Based On Firefly And Particle Swarm Optimization Algorithms, Kemal Adem, Mahmut Heki̇m, Seli̇m Demi̇r
Detection Of Hemorrhage In Retinal Images Using Linear Classifiers And Iterative Thresholding Approaches Based On Firefly And Particle Swarm Optimization Algorithms, Kemal Adem, Mahmut Heki̇m, Seli̇m Demi̇r
Turkish Journal of Electrical Engineering and Computer Sciences
We propose a novel iterative thresholding approach based on firefly and particle swarm optimization to be used for the detection of hemorrhages, one of the signs of diabetic retinopathy disease. This approach consists of the enhancement of the image using basic preprocessing methods, the segmentation of vessels with the help of Gabor and Top-hat transformation for the removal of the vessels from the image, the determination of the number of regions with hemorrhages and pixel counts in these regions using firefly algorithm (FFA) and particle swarm optimization algorithm (PSOA)-based iterative thresholding, and the detection of hemorrhages with the help of …
Accurate And Compact Stochastic Computations By Exploiting Correlation, Hamdan Abdellatef, Mohamed Khalil Hani, Nasir Shaikh-Husin
Accurate And Compact Stochastic Computations By Exploiting Correlation, Hamdan Abdellatef, Mohamed Khalil Hani, Nasir Shaikh-Husin
Turkish Journal of Electrical Engineering and Computer Sciences
Recent studies have shown, contrary to what was previously believed, that by exploiting correlation in stochastic computing (SC) designs, more accurate SC circuits with low area cost can be realized. However, if these basic SC circuits or blocks are cascaded in series to form a large complex system, correlation between stochastic numbers (SNs) from one block to the next would be lost; thus, inaccuracies are introduced. In this study, we propose correlating circuits to be used in building complex correlated SC systems. One of the circuits is the correlator that restores lost correlations between two SNs due to previous processing. …
Boltzmann Analysis Of Electron Swarm Parameters In Chf3+Cf4 Mixtures, Hidir Düzkaya, Süleyman Sungur Tezcan
Boltzmann Analysis Of Electron Swarm Parameters In Chf3+Cf4 Mixtures, Hidir Düzkaya, Süleyman Sungur Tezcan
Turkish Journal of Electrical Engineering and Computer Sciences
The electron drift velocity, mean energy, ionization, attachment, effective ionization coefficient, limit electrical field, and synergism of pure CHF3 (fluoroform), pure CF4 (tetrafluoromethane), and CHF3+CF4 gas mixtures are calculated by Boltzmann equation analysis in a wide range of density normalized electrical fields (E/N). The finite difference method is used to solve the two-term approximation of the Boltzmann equation under steady-state Townsend conditions. To our knowledge, no previous electron swarm parameters of these mixtures have been published. At constant E/N values, the electron mean energies and drift velocities increase with decreasing CHF3 content. The addition of CF4 into the mixture increases …
Synchronization And Antisynchronization Protocol Design Of Chaotic Nonlinear Gyros: An Adaptive Integral Sliding Mode Approach, Fazal Ur Rahman, Qudrat Khan, Rini Akmeliawati
Synchronization And Antisynchronization Protocol Design Of Chaotic Nonlinear Gyros: An Adaptive Integral Sliding Mode Approach, Fazal Ur Rahman, Qudrat Khan, Rini Akmeliawati
Turkish Journal of Electrical Engineering and Computer Sciences
A novel control protocol design, via integral sliding mode control with parameter update laws, for synchronization and desynchronization of a chaotic nonlinear gyro with unknown parameters is the focus of this work. The error dynamics of the actual system are substructured into nominal and uncertain parts to employ adaptive integral sliding mode (AISM) control. The uncertain parameters are estimated via devised adaptive laws. Then the disagreement dynamics are guided to origin via AISM control. The stabilizing controller is also designed in terms of nominal control along with a compensating component. The control and the parameter update laws are constructed to …
Interactive Process Miner: A New Approach For Process Mining, İsmai̇l Yürek, Derya Bi̇rant, Kökten Ulaş Bi̇rant
Interactive Process Miner: A New Approach For Process Mining, İsmai̇l Yürek, Derya Bi̇rant, Kökten Ulaş Bi̇rant
Turkish Journal of Electrical Engineering and Computer Sciences
Process mining is a technique for extracting knowledge from event logs recorded by an information system. In the process discovery phase of process mining, a process model is constructed to represent the business processes systematically and to give a general opinion about the progressive of processes in the event log. The constructed process model can be very complex as a result of structured and unstructured processes recorded in real life. Previous studies proposed different approaches to filter or eliminate some processes from the model to simplify it by implementing some statistical or mathematical formulas rather than user interactions. The main …
An Integrated Approach For The Development Of An Electric Vehicle Powertrain: Design, Analysis, And Implementation, Özgür Üstün, Ramazan Nejat Tuncay, Mert Safa Mökükcü, Ömer Ci̇han Kivanç, Gürkan Tosun, Can Gökce, Murat Çakan
An Integrated Approach For The Development Of An Electric Vehicle Powertrain: Design, Analysis, And Implementation, Özgür Üstün, Ramazan Nejat Tuncay, Mert Safa Mökükcü, Ömer Ci̇han Kivanç, Gürkan Tosun, Can Gökce, Murat Çakan
Turkish Journal of Electrical Engineering and Computer Sciences
Electric motor and power electronic systems are essential elements for the performance and efficiency of electric vehicles (EVs) and hybrid electric vehicles. The inadequacy of the range due to battery limitations is compensated by powertrain solutions and innovative control algorithms. Future targets of electric powertrains are mostly based on weight, space, and efficiency issues. Highly efficient low-volume and light-weight propulsion systems increase the performance of EVs and also enhance their importance as an alternative to internal combustion engine vehicles. In this paper, a detailed propulsion system design study is presented by considering all of the important constraints of the electric …
Real-Time Implementation Of Three-Level Inverter-Based D-Statcom Using Neuro-Fuzzy Controller, Resul Çöteli̇, Hakan Açikgöz, Beşi̇r Dandil, Servet Tuncer
Real-Time Implementation Of Three-Level Inverter-Based D-Statcom Using Neuro-Fuzzy Controller, Resul Çöteli̇, Hakan Açikgöz, Beşi̇r Dandil, Servet Tuncer
Turkish Journal of Electrical Engineering and Computer Sciences
A distribution static compensator (D-STATCOM) is a custom power device connected in parallel to a power system to address electric power quality problems caused by reactive power and harmonics. To obtain high performance from a D-STATCOM, the D-STATCOM's \textit{dq}-axis currents must be controlled in an internal control loop. However, control of the D-STATCOM's currents is difficult because of its nonlinear structure, cross-coupling effect between the \textit{d}- and \textit{q}-axis, undefined dynamics, and fast changing load. Therefore, the controller to be preferred for a D-STATCOM should have a nonlinear and robust structure. In this study, a neuro-fuzzy controller (NFC), which is a …
Multilabel Learning For The Online Transient Stability Assessment Of Electric Power Systems, Peyman Beyranvand, Veysel Murat İstemi̇han Genç, Zehra Çataltepe
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 …
Novel Modified Impedance-Based Methods For Fault Location In The Presence Of A Fault Current Limiter, Javad Barati, Aref Doroudi
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 …
Transformer Incipient Fault Diagnosis On The Basis Of Energy-Weighted Dga Usingan Artificial Neural Network, Md Danish Equbal, Shakeb Ahmad Khan, Tarikul Islam
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 …
Real-Time Chaff Generation For A Biometric Fuzzy Vault, Manvjeet Kaur, Sanjeev Sofat
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 …
Construction Of A Turkish Proposition Bank, Koray Ak, Cansu Toprak, Volkan Esgel, Olcay Taner Yildiz
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.
Analysis And Design Of A Converter Based On Noncascading Structure, Sunil Kumar, Kanwar Pal Singh Rana, Vineet Kumar
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 …
Mutatedsocioagentsim (Msas): Semisupervised Modelling Of Multiagent Simulation To Predict And Detect The Mutation In A Camouflaged Social Network, Karthika Subbaraj, Bose Sundan
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 …
Improvement Of Air Pollution Prediction In A Smart City And Its Correlation With Weather Conditions Using Metrological Big Data, Talat Zaree, Ali Reza Honarvar
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 …
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
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 …
Optimum, Projected, And Regularized Extreme Learning Machine Methods With Singular Value Decomposition And L$_{2}$-Tikhonov Regularization, Mohanad Abd Shehab, Ni̇han Kahraman
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 …
Novel Low-Loss Microstrip Triplexer Using Coupled Lines And Step Impedance Cells For 4g And Wimax Applications, Abbas Rezaei, Leila Noori
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, …
Secure Access Control In Multidomain Environments And Formal Analysis Of Model Specifications, Fatemeh Nazerian, Homayun Motameni, Hossein Nematzadeh
Secure Access Control In Multidomain Environments And Formal Analysis Of Model Specifications, Fatemeh Nazerian, Homayun Motameni, Hossein Nematzadeh
Turkish Journal of Electrical Engineering and Computer Sciences
Distributed multiple organizations interact with each other. If the domains employ role-based access control, one method for interaction between domains is role-mapping. However, it may violate constraints in the domains such as role hierarchy, separation of duty, and cardinality. Therefore, autonomy of the domains is lost. This paper proposes secure interoperation in multidomain environments. For this purpose, a cross-domain is created by foreign permission assignment. In an effort to maintain the autonomy of every domain, several rules are defined formally. Then, a decentralized scheme is used to provide permission mapping between domains. At the next stage, the proposed cross-domain is …
Prediction Of Gross Calorific Value Of Coal Based On Proximate Analysis Using Multiple Linear Regression And Artificial Neural Networks, Mustafa Açikkar, Osman Si̇vri̇kaya
Prediction Of Gross Calorific Value Of Coal Based On Proximate Analysis Using Multiple Linear Regression And Artificial Neural Networks, Mustafa Açikkar, Osman Si̇vri̇kaya
Turkish Journal of Electrical Engineering and Computer Sciences
Gross calorific value (GCV) of coal was predicted by using as-received basis proximate analysis data. Two main objectives of the study were to develop prediction models for GCV using proximate analysis variables and to reveal the distinct predictors of GCV. Multiple linear regression (MLR) and artifcial neural network (ANN) (multilayer perceptron MLP, general regression neural network GRNN, and radial basis function neural network RBFNN) methods were applied to the developed 11 models created by different combinations of the predictor variables. By conducting 10-fold cross-validation, the prediction accuracy of the models has been tested by using $ R^2 $, $ RMSE …