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Articles 7081 - 7110 of 25597

Full-Text Articles in Computer Engineering

Power-Based Modelling And Control: Experimental Results On A Cart-Pole Doubleinverted Pendulum, Tuğçe Yaren, Selçuk Ki̇zi̇r Jan 2021

Power-Based Modelling And Control: Experimental Results On A Cart-Pole Doubleinverted Pendulum, Tuğçe Yaren, Selçuk Ki̇zi̇r

Turkish Journal of Electrical Engineering and Computer Sciences

This paper is concerned with the modeling framework based on power and control for a mechanical system that has nonlinear, unstable, and under-actuated characteristic features, based on an analogy, which is developed by using the Brayton and Moser's (BM) equations between mechanical and electrical systems. The analogy is based on a mixed-potential function generalized for BM. The mixed-potential function for a cart - pole double inverted pendulum (CPDIP) system is used as a new building block for modeling, analysis, and controller design. The analogy allows for the exact transfer of results from electrical circuit synthesis and analysis to the mechanical …

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New Hyperchaotic System With Single Nonlinearity, Its Electronic Circuit Andencryption Design Based On Current Conveyor, Anitha Karthikeyan, Serdar Çi̇çek, Karthikeyan Rajagopal, Prakash Duraisamy, Ashokkumar Srinivasan Jan 2021

New Hyperchaotic System With Single Nonlinearity, Its Electronic Circuit Andencryption Design Based On Current Conveyor, Anitha Karthikeyan, Serdar Çi̇çek, Karthikeyan Rajagopal, Prakash Duraisamy, Ashokkumar Srinivasan

Turkish Journal of Electrical Engineering and Computer Sciences

Nowadays, hyperchaotic system (HCSs) have been started to be used in engineering applications because they have complex dynamics, randomness, and high sensitivity. For this purpose, HCSs with different features have been introduced in the literature. In this work, a new HCS with a single discontinuous nonlinearity is introduced and analyzed. The proposed system has one saddle focus equilibrium. When the dynamic properties and bifurcation graphics of the system are analyzed, it is determined that the proposed system exhibits the complex phenomenon of multistability. Moreover, analog electronic circuit design of the proposed system is performed with positive second-generation current conveyor. In …

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Control Synthesis For Parametric Timed Automata Under Reachability, Ebru Aydin Göl Jan 2021

Control Synthesis For Parametric Timed Automata Under Reachability, Ebru Aydin Göl

Turkish Journal of Electrical Engineering and Computer Sciences

Timed automata is a fundamental modeling formalism for real-time systems. During the design of such real-time systems, often the system information is incomplete, and design choices can vary. These uncertainties can be integrated to the model via parameters and labelled transitions. Then, the design can be completed by tuning the parameters and restricting the transitions via controller synthesis. These problems, namely parameter synthesis and controller synthesis, are studied separately in the literature. Herein, these are combined to generate an automaton satisfying the given specification by both parameter tuning and controller synthesis, thus exploring all design choices. First, it is shown …

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A New Approach: Semisupervised Ordinal Classification, Ferda Ünal, Derya Bi̇rant, Özlem Şeker Jan 2021

A New Approach: Semisupervised Ordinal Classification, Ferda Ünal, Derya Bi̇rant, Özlem Şeker

Turkish Journal of Electrical Engineering and Computer Sciences

Semisupervised learning is a type of machine learning technique that constructs a classifier by learning from a small collection of labeled samples and a large collection of unlabeled ones. Although some progress has been made in this research area, the existing semisupervised methods provide a nominal classification task. However, semisupervised learning for ordinal classification is yet to be explored. To bridge the gap, this study combines two concepts ?semisupervised learning? and "ordinal classification" for the categorical class labels for the first time and introduces a new concept of "semisupervised ordinal classification". This paper proposes a new algorithm for semisupervised learning …

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Constrained Discrete-Time Optimal Control Of Uncertain Systems With Adaptivelyapunov Redesign, Oğuz Han Altintaş, Ali̇ Emre Turgut Jan 2021

Constrained Discrete-Time Optimal Control Of Uncertain Systems With Adaptivelyapunov Redesign, Oğuz Han Altintaş, Ali̇ Emre Turgut

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, the conventional estimation-based receding horizon control paradigm is enhanced by using functional approximation, the adaptive modifications on state estimation and convex projection notion from optimization theory. The mathematical formalism of parameter adaptation and uncertainty estimation procedure are based on the redesign of optimal state estimation in discrete-time. By using Lyapunov stability theory, it is shown that the online approximation of uncertainties acting on both physical system and state estimator can be obtained. Moreover, the convergence criteria for online parameter adaptation with fully matched and partially matched cases are presented and shown. In addition, it is shown that …

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Distributed Denial Of Service Attack Detection In Cloud Computing Using Hybridextreme Learning Machine, Gopal Singh Kushwah, Virender Ranga Jan 2021

Distributed Denial Of Service Attack Detection In Cloud Computing Using Hybridextreme Learning Machine, Gopal Singh Kushwah, Virender Ranga

Turkish Journal of Electrical Engineering and Computer Sciences

One of the major security challenges in cloud computing is distributed denial of service (DDoS) attacks. In these attacks, multiple nodes are used to attack the cloud by sending huge traffic. This results in the unavailability of cloud services to legitimate users. In this research paper, a hybrid machine learning-based technique has been proposed to detect these attacks. The proposed technique is implemented by combining the extreme learning machine (ELM) model and the blackhole optimization algorithm. Various experiments have been performed with the help of four benchmark datasets namely, NSL KDD, ISCX IDS 2012, CICIDS2017, and CICDDoS2019, to evaluate the …

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Design And Planning Of A Distribution System Using Renewable Technologies In Arural Area Of Pakistan, Abdur Rehman Yousaf, Ghulam Mujtaba, Muhammad Amjad, Zeeshan Rashid Jan 2021

Design And Planning Of A Distribution System Using Renewable Technologies In Arural Area Of Pakistan, Abdur Rehman Yousaf, Ghulam Mujtaba, Muhammad Amjad, Zeeshan Rashid

Turkish Journal of Electrical Engineering and Computer Sciences

The inclusion of renewable energy sources in a distribution system to form a dispersed or decentralized generation network has gained tremendous progress in recent years. The architecture of the distribution system has the potential to serve as a microgrid during an islanding operation connected directly to the load center while excited fully by renewable technologies. This paper deals with planning and designing of a medium voltage power distribution system in a rural area of Pakistan affluent with abundant reserves of renewable sources of electricity. Two types of distribution system architectures, namely radial and ring systems, are simulated using a power …

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A Novel Approach For Intrusion Detection Systems: V-Ids, Kenan İnce Jan 2021

A Novel Approach For Intrusion Detection Systems: V-Ids, Kenan İnce

Turkish Journal of Electrical Engineering and Computer Sciences

An intrusion detection system (IDS) is a security mechanism that detects abnormal activities in a network. An ideal IDS must detect intrusion attempts and maybe categorize them for further research and keep false-positive analysis at a very low level. IDSs are used in the analysis of network traffic data at all sizes. Studies on this subject focused on machine learning techniques. Even though the performance rates are high, it is seen that processes such as data understanding, preprocessing, and consistency tests are time-consuming and laborious. For this reason, the use of deep learning (DL) models that automatically perform the mentioned …

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Shapeshifter: A Morphable Microprocessor For Low Power, Nazli Tokatli, İsa Ahmet Güney, Sercan Sari, Merve Güney, Uğur Nezi̇r, Gürhan Küçük Jan 2021

Shapeshifter: A Morphable Microprocessor For Low Power, Nazli Tokatli, İsa Ahmet Güney, Sercan Sari, Merve Güney, Uğur Nezi̇r, Gürhan Küçük

Turkish Journal of Electrical Engineering and Computer Sciences

A composite core contains large and small heterogeneous microengines. The most important property of composite cores is their ability to select the most proper microengine for running applications to save power without sacrificing too much performance. To achieve this, a composite core tries to predict the performance of the passive microengine by collecting various processor statistics from the active microengine at runtime. In the method proposed in the literature, the microengine, which is more ideal for running the rest of the application, is determined by a migrationdecision circuitry that is bound to collected statistics and complex functions, which are run …

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Image Forgery Detection Based On Fusion Of Lightweight Deep Learning Models, Amit Doegar, Srinidhi Hiriyannaiah, Siddesh Gaddadevara Matt, Srinivasa Krishnarajanagar Gopaliyengar, Maitreyee Dutta Jan 2021

Image Forgery Detection Based On Fusion Of Lightweight Deep Learning Models, Amit Doegar, Srinidhi Hiriyannaiah, Siddesh Gaddadevara Matt, Srinivasa Krishnarajanagar Gopaliyengar, Maitreyee Dutta

Turkish Journal of Electrical Engineering and Computer Sciences

Image forgery detection is one of the key challenges in various real time applications, social media and online information platforms. The conventional methods of detection based on the traces of image manipulations are limited to the scope of predefined assumptions like hand-crafted features, size and contrast. In this paper, we propose a fusion based decision approach for image forgery detection. The fusion of decision is based on the lightweight deep learning models namely SqueezeNet, MobileNetV2 and ShuffleNet. The fusion decision system is implemented in two phases. First, the pretrained weights of the lightweight deep learning models are used to evaluate …

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Performance Improvement Speed Control Of Ipmsm Drive Based On Nonlinearcurrent Control, Muhammad Usama, Jaehong Kim Jan 2021

Performance Improvement Speed Control Of Ipmsm Drive Based On Nonlinearcurrent Control, Muhammad Usama, Jaehong Kim

Turkish Journal of Electrical Engineering and Computer Sciences

Recently model predictive control (MPC) scheme emerges as an efficient current control technique for dynamic performance of motor drives. For excellent dynamic performance, maximum torque per ampere (MTPA) control technique is utilized to achieve maximum torque while using minimum current constrain in contrast to conventional qaxis current control. Model predictive current control (MPCC) scheme alongside MTPA control is employed to replace the traditional constant gain proportional-integral (PI) current control and a nonlinear hysteresis current (HC) control schemes. The PI and hysteresis current controller offers satisfactory performance at ideal conditions but, with variable speed and load conditions, these control schemes cause …

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Area-Delay Efficient Radix-4 8×8 Booth Multiplier For Dsp Applications, Subodh Singhal, Sujit Patel, Anurag Mahajan, Gaurav Saxena Jan 2021

Area-Delay Efficient Radix-4 8×8 Booth Multiplier For Dsp Applications, Subodh Singhal, Sujit Patel, Anurag Mahajan, Gaurav Saxena

Turkish Journal of Electrical Engineering and Computer Sciences

Booth multiplier is the key component in portable very large-scale integration (VSLI) systems enabled with signal and image processing applications. The area, delay, and energy are the major constraints in these systems. Therefore, in this paper, a detailed analysis of the state-of-the-art Booth multiplier architecture and its various internal units are presented to find the scope of optimization. Based on the finding of analysis, optimized new binary to 2's complement (B2C), Booth encoder-cum-selector type-1 and type-2, and partial product addition units are proposed. Furthermore, using these optimized units, an efficient parallel radix-4 8×8 Booth multiplier architecture is proposed. The simulation …

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Comparative Review Of Disk Type And Unconventional Transverse Flux Machines:Performance Analysis, Erhan Tuncel, Emi̇n Yildiriz Jan 2021

Comparative Review Of Disk Type And Unconventional Transverse Flux Machines:Performance Analysis, Erhan Tuncel, Emi̇n Yildiriz

Turkish Journal of Electrical Engineering and Computer Sciences

Transverse flux machines (TFM) can be designed with high pole numbers, so they are very useful in directdrive systems with high torque density. Although many TFM models have been proposed to date, no detailed classification and comparison has been made before. Conventional TFMs have a high power and torque density, but low power factors and high cogging torques have prevented them from being widely used. However, especially with the new disk type TFMs proposed in recent years and the methods developed, these drawbacks have been reduced. In this paper, the TFMs proposed in recent years have been classified and their …

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Zero Knowledge Based Data Deduplication Using In-Line Block Matching Protocolfor Secure Cloud Storage, Vivekrabinson Kanagamani, Muneeswaran Karuppiah Jan 2021

Zero Knowledge Based Data Deduplication Using In-Line Block Matching Protocolfor Secure Cloud Storage, Vivekrabinson Kanagamani, Muneeswaran Karuppiah

Turkish Journal of Electrical Engineering and Computer Sciences

In the area of cloud computing, data deduplication enables the cloud server to store a single copy of data by eliminating redundant files to improve storage and network efficiency. Proof-of-ownership (PoW) is a cryptographic function that verifies the user who really owns the data. Most of the existing schemes have tried to solve the deduplication problem by providing the same encryption key for identical data. However, these schemes suffer from dynamic changes in ownership management. In this paper, we propose an in-line block matching (IBM) protocol based on zero-knowledge proof for deduplication with dynamic ownership management, which eliminates the unauthorized …

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Legendre-Wavelet Embedded Neurofuzzy Feedback Linearization Based Controlscheme For Phevs Charging Station In A Microgrid, Muhammad Awais, Laiq Khan, Saghir Ahmad, Sidra Mumtaz, Rabiah Badar, Shafaat Ullah Jan 2021

Legendre-Wavelet Embedded Neurofuzzy Feedback Linearization Based Controlscheme For Phevs Charging Station In A Microgrid, Muhammad Awais, Laiq Khan, Saghir Ahmad, Sidra Mumtaz, Rabiah Badar, Shafaat Ullah

Turkish Journal of Electrical Engineering and Computer Sciences

The immense emergence of plug-in hybrid electric vehicles (PHEVs) is envisioned in the future. The rapid proliferation of PHEVs and their charging triggers intense surges in the load during load peak hours. A sophisticated controlled charging station is developed for PHEVs to alleviate grid load during peak demand hours. A novel feedback linearization embedded full recurrent adaptive NeuroFuzzy Legendre wavelet control (FBL-FRANF-Leg-WC) technique is employed to control the charging of PHEVs. The antecedent part of the NeuroFuzzy framework is based on recurrent Gaussian membership function while the consequent part comprises of recurrent Legendre wavelet. The charging station is integrated into …

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Bagging Ensemble For Deep Learning Based Gender Recognition Using Test-Timeaugmentation On Large-Scale Datasets, Taner Danişman Jan 2021

Bagging Ensemble For Deep Learning Based Gender Recognition Using Test-Timeaugmentation On Large-Scale Datasets, Taner Danişman

Turkish Journal of Electrical Engineering and Computer Sciences

We present a bagging ensemble of convolutional networks in combination with the test-time augmentation technique to improve performance on the cross-dataset gender recognition problem. The bagging ensemble combines the predictions from multiple homogeneous models into the ensemble prediction. Augmentation techniques are often used in the learning phase of the CNNs to improve the generalization ability. On the other hand, test-time augmentation is not a common method used in the testing phase of the learned model. We conducted experiments on models trained using different hyperparameters. We augmented the test data and combine the predictive outputs from these network models. Experiments performed …

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Field-Programmable Gate Array (Fpga) Hardware Design And Implementation Ofa New Area Efficient Elliptic Curve Crypto-Processor, Muhammad Kashif, İhsan Çi̇çek Jan 2021

Field-Programmable Gate Array (Fpga) Hardware Design And Implementation Ofa New Area Efficient Elliptic Curve Crypto-Processor, Muhammad Kashif, İhsan Çi̇çek

Turkish Journal of Electrical Engineering and Computer Sciences

Elliptic curve cryptography provides a widely recognized secure environment for information exchange in resource-constrained embedded system applications, such as Internet-of-Things, wireless sensor networks, and radio frequency identification. As the elliptic-curve cryptography (ECC) arithmetic is computationally very complex, there is a need for dedicated hardware for efficient computation of the ECC algorithm in which scalar point multiplication is the performance bottleneck. In this work, we present an ECC accelerator that computes the scalar point multiplication for the NIST recommended elliptic curves over Galois binary fields by using a polynomial basis. We used the Montgomery algorithm with projective coordinates for the scalar …

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Fast Hardware-Oriented Algorithm For 3d Positioning In Line-Of-Sight And Singlebounced Non-Line-Of-Sight Environments, Cem Yağli, Emre Özen, Ari̇f Akkeleş Jan 2021

Fast Hardware-Oriented Algorithm For 3d Positioning In Line-Of-Sight And Singlebounced Non-Line-Of-Sight Environments, Cem Yağli, Emre Özen, Ari̇f Akkeleş

Turkish Journal of Electrical Engineering and Computer Sciences

The ability to find the location of a mobile object and track it in two-dimensional (2D) and three-dimensional (3D) space is an indispensable feature of wireless communication systems. In particular, the increase in demand for using self-navigation technology in unmanned vehicles is attracting additional attention to this area of research. The methods and techniques developed for these systems compete in terms of simplicity, performance, and accuracy. However, the majority of solutions focus on only one of these performance metrics and are not applicable to the projected systems. In this study, a new location estimation solution that satisfies all three performance …

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A Hybrid Technique Using Modified Icp Algorithm For Faster And Automatic 2d &3d Microscopic Image Stitching In Cytopathologic Examination, Hülya Doğan, Eli̇f Baykal Kablan, Murat Eki̇nci̇, Mustafa Emre Erci̇n, Şafak Ersöz Jan 2021

A Hybrid Technique Using Modified Icp Algorithm For Faster And Automatic 2d &3d Microscopic Image Stitching In Cytopathologic Examination, Hülya Doğan, Eli̇f Baykal Kablan, Murat Eki̇nci̇, Mustafa Emre Erci̇n, Şafak Ersöz

Turkish Journal of Electrical Engineering and Computer Sciences

Due to the limitations of the light microscopic system such as limited depth of field and narrow field of view, entire sample areas are invisible and pathologists move the light microscope stage along the X - Y - Z axes with eye-hand coordination. In order to reduce the dependence on the pathologist and to allow whole sample areas to be examined in a short time without any control (without eye-hand coordination), this study creates 2D & 3D panoramic images with wide-view of sample in the light microscopic systems. According to our literature research, there is no study that creates 2D …

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Clustering Ensemble Selection Based On The Extended Jaccard Measure, Hajar Khalili, Mohsen Rabbani, Ebrahim Akbari Jan 2021

Clustering Ensemble Selection Based On The Extended Jaccard Measure, Hajar Khalili, Mohsen Rabbani, Ebrahim Akbari

Turkish Journal of Electrical Engineering and Computer Sciences

Clustering ensemble selection has shown high efficiency in the improvement of the quality of clustering solutions. This technique comprises two important metrics: diversity and quality. It has been empirically proved that ensembles of higher effectiveness can be achieved through taking into consideration the diversity and quality simultaneously. However, the relationships between these two metrics in base clusterings have remained uncertain. This paper suggests a new hierarchical selection algorithm using a diversity/quality measure based on the Jaccard similarity measure. In the proposed algorithm, the selection of the subsets of the clustering partitions is done based on their diversity measures. The proposed …

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Combined System Identification And Robust Control Of A Gimbal Platform, Mehmet Baskin, Mehmet Kemal Leblebi̇ci̇oğlu Jan 2021

Combined System Identification And Robust Control Of A Gimbal Platform, Mehmet Baskin, Mehmet Kemal Leblebi̇ci̇oğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Gimbaled imaging systems require very high performance inertial stabilization loops to achieve clear image acquisition, precise pointing, and tracking performance. Therefore, higher bandwidths become essential to meet recent increased performance demands. However, such systems often posses flexible dynamics around target bandwidth and time delay of gyroscope sensors which put certain limit to achievable bandwidths. For inertial stabilization loops, widely used design techniques have difficulty in achieving large bandwidth and satisfying required robustness simultaneously. Clearly, high performance control design hinges on accurate control-relevant model set. For that reason, combined system identification and robust control method is preferred. In the system identification …

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Wavelet-Based Super Resolution Using Pansharpened Multispectral Images, Vi̇ldan Atalay Aydin, Hassan Foroosh Jan 2021

Wavelet-Based Super Resolution Using Pansharpened Multispectral Images, Vi̇ldan Atalay Aydin, Hassan Foroosh

Turkish Journal of Electrical Engineering and Computer Sciences

Several remote sensing applications require high-spatial-high-spectral resolution multispectral (MS) images. However, most MS sensors provide low-spatial-high-spectral resolution MS images together with high-spatial-low-spectral resolution panchromatic (PAN) bands. In order to increase the spatial resolution of MS bands to the resolution of PAN images and to obtain high-spatial/spectral resolution MS bands, either MS and PAN images are fused (i.e., pansharpening) or super resolution (SR) is performed using MS bands only. Nevertheless, existing methods do not utilize the available temporal and spatial information together. In this paper, we propose a multiframe SR algorithm using high-spatial/spectral resolution MS images (i.e., pansharpened), taking advantage of …

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Evaluation Of Mother Wavelets On Steady-State Visually-Evoked Potentials Fortriple-Command Brain-Computer Interfaces, Ebru Sayilgan, Yilmaz Kemal Yüce, Yalçin İşler Jan 2021

Evaluation Of Mother Wavelets On Steady-State Visually-Evoked Potentials Fortriple-Command Brain-Computer Interfaces, Ebru Sayilgan, Yilmaz Kemal Yüce, Yalçin İşler

Turkish Journal of Electrical Engineering and Computer Sciences

Wavelet transform (WT) is an important tool to analyze the time-frequency structure of a signal. The WT relies on a prototype signal that is called the mother wavelet. However, there is no single universal wavelet that fits all signals. Thus, the selection of mother wavelet function might be challenging to represent the signal to achieve the optimum performance. There are some studies to determine the optimal mother wavelet for other biomedical signals; however, there exists no evaluation for steady-state visually-evoked potentials (SSVEP) signals that becomes very popular among signals manipulated for brain-computer interfaces (BCIs) recently. This study aims to explore, …

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Analyzing Students' Experience In Programming With Computational Thinkingthrough Competitive, Physical, And Tactile Games: The Quadrilateral Methodapproach, M Ahsan Habib, Raja Jamilah Raja Yusof, Siti Salwah Salim, Asmiza Abdul Sani, Hazrina Sofian, Aishah Abu Bakar Jan 2021

Analyzing Students' Experience In Programming With Computational Thinkingthrough Competitive, Physical, And Tactile Games: The Quadrilateral Methodapproach, M Ahsan Habib, Raja Jamilah Raja Yusof, Siti Salwah Salim, Asmiza Abdul Sani, Hazrina Sofian, Aishah Abu Bakar

Turkish Journal of Electrical Engineering and Computer Sciences

The lack of computational thinking (CT) skills can be one of the reasons why students find themselves having difficulties in writing a good program. Therefore, understanding how CT skills can be developed is essential. This research explores how CT skills can be developed for programming through competitive, physical, and tactile games. The CT elements in this research focus on four major programming concepts, which are decomposition, pattern recognition, abstraction, and algorithmic thinking. We have conducted game activities through several algorithms that include sorting, swapping, and graph algorithms and analyzed how the game affects the student experience (SX) in understanding the …

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Deep Q-Network-Based Noise Suppression For Robust Speech Recognition, Tae-Jun Park, Joon-Hyuk Chang Jan 2021

Deep Q-Network-Based Noise Suppression For Robust Speech Recognition, Tae-Jun Park, Joon-Hyuk Chang

Turkish Journal of Electrical Engineering and Computer Sciences

This study develops the deep Q-network (DQN)-based noise suppression for robust speech recognition purposes under ambient noise. We thus design a reinforcement algorithm that combines DQN training with a deep neural networks (DNN) to let reinforcement learning (RL) work for complex and high dimensional environments like speech recognition. For this, we elaborate on the DQN training to choose the best action that is the quantized noise suppression gain by the observation of noisy speech signal with the rewards of DQN including both the word error rate (WER) and objective speech quality measure. Experiments demonstrate that the proposed algorithm improves speech …

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Radar-Based Microwave Breast Cancer Detection System With A High-Performanceultrawide Band Antipodal Vivaldi Antenna, Hüseyi̇n Özmen, Muhammed Bahaddi̇n Kurt Jan 2021

Radar-Based Microwave Breast Cancer Detection System With A High-Performanceultrawide Band Antipodal Vivaldi Antenna, Hüseyi̇n Özmen, Muhammed Bahaddi̇n Kurt

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a novel ultrawide band (UWB) antipodal Vivaldi antenna with three pairs of slots was designed to be used as a sensor in microwave imaging systems for breast cancer detection. The proposed antenna operates in UWB frequency range of 3.05-12.2 GHz. FR4 was used as a dielectric material and as a substrate for forming the antenna that has a compact size of 36 mm x 36 mm x 1.6 mm. Frequency and time domain performance of the proposed antenna have been investigated and results show that it meets the requirements for UWB radar applications with linear phase response, …

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An Admm-Based Incentive Approach For Cooperative Data Analysis In Edgecomputing, Weiwei Fang, Xue Wang, Qingli Wang, Yi Ding Jan 2021

An Admm-Based Incentive Approach For Cooperative Data Analysis In Edgecomputing, Weiwei Fang, Xue Wang, Qingli Wang, Yi Ding

Turkish Journal of Electrical Engineering and Computer Sciences

Edge computing is a new paradigm that provides data processing capabilities at the network edge. In view of the uneven data distribution and the constrained onboard resource, an edge device often needs to call for a number of neighboring devices as followers to cooperate on data analysis tasks. However, these followers may be rational and selfish, having their private optimization objectives such as energy efficiency. Therefore, the leader device needs to incentivize the followers to achieve a certain global objective, e.g., maximizing task accomplishment, rather than their own objectives. In this paper, we model the aforementioned challenges in edge computing …

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Privacy Preserving Hybrid Recommender System Based On Deep Learning, Sangeetha Selvaraj, Sudha Sadasivam Gangadharan Jan 2021

Privacy Preserving Hybrid Recommender System Based On Deep Learning, Sangeetha Selvaraj, Sudha Sadasivam Gangadharan

Turkish Journal of Electrical Engineering and Computer Sciences

Deep learning models are widely being used to provide relevant recommendations in hybrid recommender systems. These hybrid systems combine the advantages of both content based and collaborative filtering approaches. However, these learning systems hamper the user privacy and disclose sensitive information. This paper proposes a privacy preserving deep learning based hybrid recommender system. In hybrid deep neural network, user?s side information such as age, location, occupation, zip code along with user rating is embedded and provided as input. These embedding?s pose a severe threat to individual privacy. In order to eliminate this breach of privacy, we have proposed a private …

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Performance Evaluation Of Hht And Wt For Detection Of Hif And Ct Saturationin Smart Grids, Saeid Heidari, Saeed Asgharigovar, Pouya Pourghasem, Heresh Seyedi, Ömer Usta Jan 2021

Performance Evaluation Of Hht And Wt For Detection Of Hif And Ct Saturationin Smart Grids, Saeid Heidari, Saeed Asgharigovar, Pouya Pourghasem, Heresh Seyedi, Ömer Usta

Turkish Journal of Electrical Engineering and Computer Sciences

Hilbert-Huang transform (HHT), continuous wavelet transform (CWT) and discrete wavelet transform (DWT) are well-known signal processing methods that are widely utilized for feature extraction and fault detection by protection systems in smart grids. In this paper, we assess the performances of these methods encountering challenging situations in distribution networks, i.e. high impedance arcing fault (HIF) and current transformer (CT) saturation. Low fault current amplitude in HIF case causes the overcurrent protection, which is the predominant protection method in distribution grids, to fail. Furthermore, some faults may lead to CT saturation, which may result in delayed operation of the relay. To …

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Ordered Physical Human Activity Recognition Based On Ordinal Classification, Duygu Bağci Daş, Derya Bi̇rant Jan 2021

Ordered Physical Human Activity Recognition Based On Ordinal Classification, Duygu Bağci Daş, Derya Bi̇rant

Turkish Journal of Electrical Engineering and Computer Sciences

Human activity recognition (HAR) is a critical process for applications that focus on the classification of human physical activities such as jogging, walking, downstairs, and upstairs. Ordinal classification (OC) is a special type of supervised multi-class classification in which an inherent ordering among the classes exists, such as low, medium, and high. This study combines these two concepts and introduces an approach to ?human activity recognition based on ordinal classification? (HAROC). In the proposed approach, ordinal classification is applied to human activity recognition where the physical activities can be ordered by using their signals? band power values. This is the …

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