A Robust Smes Control For Enhancing Stability Of Distribution Systems Fed From Intermittent Wind Power Generation,
2019
TÜBİTAK
A Robust Smes Control For Enhancing Stability Of Distribution Systems Fed From Intermittent Wind Power Generation, Sayed Said, Mokhtar Aly, Balint Hartmann
Turkish Journal of Electrical Engineering and Computer Sciences
The voltage and frequency stability issues of power systems are the main challenges that arise from high penetration levels of wind energy systems. This paper presents an effective solution for voltage and frequency stability problems by using a superconducting magnetic energy storage (SMES) system controlled with a fuzzy logic controller (FLC). The proposed control system can suppress the voltage and frequency fluctuations due to the high variations of wind speed. In addition, the proposed control system is suitable for both balanced and unbalanced distribution systems with high penetration levels of wind turbines (WTs). A squirrel cage induction generator (SCIG) is …
Research On The Dynamic Networking Of Smart Meters Based On Characteristics Of The Collected Data,
2019
TÜBİTAK
Research On The Dynamic Networking Of Smart Meters Based On Characteristics Of The Collected Data, Yaxin Huang, Yunlian Sun, Xiaodi Zhang
Turkish Journal of Electrical Engineering and Computer Sciences
In order to accurately collect the electricity usage information from the smart meter which uses the power line for communication, this paper proposes the method of dynamic networking to enhance the reliability of the smart meter communication. We shall firstly establish a logical topology between the smart meter and the concentrator with reference to their communication paths within the power supply range of the same transformer, and then grade smart meters, and choose the relay for each level network based on the selection methods of relay, and finally use the improved ant colony algorithm to choose the optimal communication path …
Heat Flux Capacity Measurement And Improvement For The Test Of Superconducting Logic Circuits In Closed-Cycle Cryostats,
2019
TÜBİTAK
Heat Flux Capacity Measurement And Improvement For The Test Of Superconducting Logic Circuits In Closed-Cycle Cryostats, Sasan Razmkhah, Ali̇ Bozbey
Turkish Journal of Electrical Engineering and Computer Sciences
With the current progress of superconducting integrated circuits, circuit complexities have reached more than 100,000 Josephson junctions. At the laboratory environment, circuit tests are generally being conducted at liquid Helium environments. With the commercialization of the superconducting integrated circuit-based systems and/or price increase of liquid Helium, utilization of the closed-cycle systems will be inevitable. Even though it is possible to implement closed-cycle systems with quite substantial excess cooling powers after all the wirings and peripheral circuits, one point not to be overlooked is the power density at the superconducting chips. We have observed that the circuits designed for operation at …
Investigation Of The Mechanism Of Transport Across The Poly/Monocrystalline Silicon Interface In Polysilicon-Emitter Bipolar Transistors Based On Variations In The Interface Treatment Process, Shahriar Jamasb
Turkish Journal of Electrical Engineering and Computer Sciences
Electrical transport across the poly/monocrystalline silicon (poly-Si/c-Si) interface has been investigated by introducing variations in the interface treatment process affecting the thickness of the native oxide layer formed on the silicon surface. The I-V relationship characterizing the resistance associated with this interface is extracted using an improved open-collector method, which eliminates the inherent nonlinearity arising from the reverse active characteristics of the bipolar transistor. The nonohmic behavior of the interface at low electric fields is demonstrated to be consistent with direct tunneling through a rectangular barrier presented by an ultrathin interfacial oxide layer. An approximate tunnel junction model is proposed …
Lower Order Controller Design Using Weighted Singular Perturbation Approximation,
2019
TÜBİTAK
Lower Order Controller Design Using Weighted Singular Perturbation Approximation, Muhammad Raees Furquan Azhar, Umair Zulfiqar, Muwahida Liaquat
Turkish Journal of Electrical Engineering and Computer Sciences
Most of the analytical design procedures yield controllers of almost the same order as that of the plant. Resultantly, if the plant is of a high order, the controller obtained from these design procedures is also of a high order. The order of the controller should be practically acceptable for easy implementation. There are two indirect methods for designing a low order controller for high order plants: plant reduction and compensator reduction. In compensator reduction, the order of the controller designed for the original higher order plant is reduced. In plant reduction, the order of the plant is reduced for …
A Novel Map-Merging Technique For Occupancy Grid-Based Maps Using Multiple Robots: A Semantic Approach,
2019
TÜBİTAK
A Novel Map-Merging Technique For Occupancy Grid-Based Maps Using Multiple Robots: A Semantic Approach, Aki̇f Durdu, Mehmet Korkmaz
Turkish Journal of Electrical Engineering and Computer Sciences
Map merging is a noteworthy phenomenon for cases such as search and rescue and disaster areas in which the duration is quite significant when gathering information about an environment. It is obvious that the total mapping time decreases if the number of agents (robots) increases. However, the use of multiple agents leads to problems such as task allocation schemes and the fusing of local maps. Examining the present methods, it is generally observed that the common features of local maps have been found and the global map is formed by obtaining related transformation between local maps. However, such implementations may …
Exploiting Stochastic Petri Nets With Fuzzy Parameters To Predict Efficient Drug Combinations For Spinal Muscular Atrophy,
2019
TÜBİTAK
Exploiting Stochastic Petri Nets With Fuzzy Parameters To Predict Efficient Drug Combinations For Spinal Muscular Atrophy, Rza Bashi̇rov, Recep Duranay, Adi̇l Şeytanoğlu, Mani Mehraei, Ni̇met Akçay
Turkish Journal of Electrical Engineering and Computer Sciences
Randomness and uncertainty are two major problems one faces while modeling nonlinear dynamics of molecular systems. Stochastic and fuzzy methods are used to cope with these problems, but there is no consensus among researchers regarding which method should be used when. This is because the areas of applications of these methods are overlapping with differences in opinions. In the present work, we demonstrate how to use stochastic Petri nets with fuzzy parameters to manage random timing of biomolecular events and deal with the uncertainty of reaction rates in biological networks. The approach is demonstrated through a case study of simulation-based …
A Distributed Load Balancing Algorithm For Deduplicated Storage,
2019
TÜBİTAK
A Distributed Load Balancing Algorithm For Deduplicated Storage, Prabavathy Balasundaram, Chitra Babu, Pradeep Rengaswamy
Turkish Journal of Electrical Engineering and Computer Sciences
While deduplication brings the advantage of significant space savings in storage, it nevertheless incurs the overhead of maintaining huge metadata. Updating such huge metadata during the data migration that arises due to load balancing activity results in significant overhead. In order to reduce this metadata update overhead, this paper proposes a suitable alternate index that tracks the data blocks even when they migrate across the nodes without explicitly storing the location information. In addition, a virtual server-based load balancing (VSLB) algorithm has been proposed in order to reduce the migration overhead. The experimental results indicate that the proposed index reduces …
Investigation Of Start-Up Conditions On Electric Submersible Pump Driven With Flux Switching Motor,
2019
TÜBİTAK
Investigation Of Start-Up Conditions On Electric Submersible Pump Driven With Flux Switching Motor, Mohammadhossein Barzegari Bafghi, Abolfazl Vahedi
Turkish Journal of Electrical Engineering and Computer Sciences
One of the motor types that is recently considered to be a candidate for electric submersible pumps (ESPs) is the flux switching motor. Therefore, it becomes crucial to verify that this type of motor can stand ESP conditions. The main subject of this paper is to investigate the start-up condition of ESP along with considering the long power supply cable to study the motor performance, where the real aspect of the ESP conditions is investigated. Since there is not any model of pump load that models the dynamic behavior of ESP correctly, first, a model for the pump is developed. …
A New Model To Determine The Hierarchical Structure Of The Wireless Sensor Networks,
2019
TÜBİTAK
A New Model To Determine The Hierarchical Structure Of The Wireless Sensor Networks, Resmi̇ye Nasi̇boğlu, Zülküf Teki̇n Erten
Turkish Journal of Electrical Engineering and Computer Sciences
Wireless sensor networks are one of the rising areas of scientific research. Common purpose of these investigations is usually constructing optimal structure of the network by prolonging its lifetime. In this study, a new model has been proposed to construct a hierarchical structure of wireless sensor networks. Methods used in the model to determine clusters and appropriate cluster heads are k-means clustering and fuzzy inference system (FIS), respectively. The weighted averaging based on levels (WABL) defuzzification method is used to calculate crisp outputs of the FIS. A new theorem for calculation of WABL values has been proved in order to …
On The Performance Of Quick Artificial Bee Colony Algorithm For Dynamic Deployment Of Wireless Sensor Networks,
2019
TÜBİTAK
On The Performance Of Quick Artificial Bee Colony Algorithm For Dynamic Deployment Of Wireless Sensor Networks, Beyza Gorkemli, Zahraa Al-Dulaimi
Turkish Journal of Electrical Engineering and Computer Sciences
In recent years, the use of wireless sensor networks (WSNs) has increased and there have been significant improvements in this field. Especially with smarter, cheaper, and smaller sensor nodes, various kinds of information can be detected and collected in different environments and under different conditions. WSNs have thus been used in many applications such as military, surveillance, target tracking, home, medical, and environmental applications. As the popularity of WSNs increases, problems related to these networks are being realized. The dynamic deployment problem is one of the main challenges that have a direct effect on the performance of WSNs. In this …
Application Of Multiscale Fuzzy Entropy Features For Multilevel Subject-Dependent Emotion Recognition,
2019
TÜBİTAK
Application Of Multiscale Fuzzy Entropy Features For Multilevel Subject-Dependent Emotion Recognition, Hamzah Lotfalinezhad, Ali Maleki
Turkish Journal of Electrical Engineering and Computer Sciences
Emotion recognition can be used in clinical and nonclinical situations. Despite previous works which mostly used time and frequency features of electroencephalogram (EEG) signals in subject-dependent emotion recognition issues, we used multiscale fuzzy entropy as a nonlinear dynamic feature. The EEG signals of the well-known Database for Emotion Analysis Using Physiological signals dataset was used for classification of two and three levels of emotions in arousal and valence space. The compound feature selection with a cost of average accuracy of support vector machine classifier was used to reduce feature dimensions. For subject-dependent systems, the proposed method is superior in comparison …
A Hybrid Feature-Selection Approach For Finding The Digital Evidence Of Web Application Attacks,
2019
TÜBİTAK
A Hybrid Feature-Selection Approach For Finding The Digital Evidence Of Web Application Attacks, Mohammed Babiker, Eni̇s Karaarslan, Yaşar Hoşcan
Turkish Journal of Electrical Engineering and Computer Sciences
The most critical challenge of web attack forensic investigations is the sheer amount of data and level of complexity. Machine learning technology might be an efficient solution for web attack analysis and investigation. Consequently, machine learning applications have been applied in various areas of information security and digital forensics, and have improved over time. Moreover, feature selection is a crucial step in machine learning; in fact, selecting an optimal feature subset could enhance the accuracy and performance of the predictive model. To date, there has not been an adequate approach to select optimal features for the evidence of web attack. …
An Automated Snick Detection And Classification Scheme As A Cricket Decision Review System,
2019
TÜBİTAK
An Automated Snick Detection And Classification Scheme As A Cricket Decision Review System, Aftab Khan, Syed Qadir Hussain, Muhammad Waleed, Ashfaq Khan, Umair Khan
Turkish Journal of Electrical Engineering and Computer Sciences
Umpire decisions can greatly affect the outcome of a cricket game. When there is doubt about the umpire?s call for a decision, a decision review system (DRS) may be brought into play by a batsman or bowler to validate the decision. Recently, the latest technologies, including Hotspot, Hawk-eye, and Snickometer, have been employed when there is doubt among the on-field umpire, batsman, or bowlers. This research is a step forward in gaging the true class of a snick generated from the contact of the cricket ball with either (i) the bat, (ii) gloves, (iii) pad, or (iv) a combination of …
Decision-Making For Small Industrial Internet Of Things Using Decision Fusion,
2019
TÜBİTAK
Decision-Making For Small Industrial Internet Of Things Using Decision Fusion, Tuğrul Çavdar, Nader Ebrahimpour
Turkish Journal of Electrical Engineering and Computer Sciences
The industrial Internet of Things (IIoT) is a new field of Internet of Things (IoT) that has gained more popularity recently in industrial units and makes it possible to access information anywhere and anytime. In other words, geographic coordinates cannot prevent obtaining equipment and its data. Today, it is possible to manage and control equipment simply without spending time in an operational area and just by using the IIoT. This system collects data from manufacturing and production units by using wireless sensor networks or other networks for classification of fault detection. These data are then used after analysis to allow …
Energy Saving Scheduling In A Fog-Based Iot Application By Bayesian Task Classification Approach,
2019
TÜBİTAK
Energy Saving Scheduling In A Fog-Based Iot Application By Bayesian Task Classification Approach, Gholamreza Heydari, Dadmehr Rahbari, Mohsen Nickray
Turkish Journal of Electrical Engineering and Computer Sciences
The Internet of things increases information volume in computer networks and the concept of fog will help us to control this volume more efficiently. Scheduling resources in such an environment would be an NP-Hard problem. This article has studied the concept of scheduling in fog with Bayesian classification which could be applied to gain the task requirements like the processing ones. After classification, virtual machines will be created in accordance with the predicted requirements. The ifogsim simulator has been applied to study our fog-based Bayesian classification scheduling (FBCS) method performance in an EEG tractor application. Algorithms have been evaluated on …
Gacnn Sleeptunenet: A Genetic Algorithm Designing The Convolutional Neural Network Architecture For Optimal Classification Of Sleep Stages From A Single Eeg Channel, Shahnawaz Qureshi, Seppo Karilla, Sirirut Vanichayobon
Turkish Journal of Electrical Engineering and Computer Sciences
This study presents a method for designing--by a genetic algorithm, without manual intervention--the feature learning architecture for classification of sleep stages from a single EEG channel, when using a convolutional neural network called GACNN SleepTuneNet. Two EEG electrode positions were selected, namely FP2-F4 and FPz-Cz, from two available datasets. Twenty-five generations were involved in diagnosis without hand-crafted features, to learn the architecture for classification of sleep stages based on AASM standard. Based on the results, our model not only achieved the highest classification accuracy, but it also distinguished the sleep stages based on either of the two EEG electrode signals, …
Defect Detection Of Seals In Multilayer Aseptic Packages Using Deep Learning,
2019
TÜBİTAK
Defect Detection Of Seals In Multilayer Aseptic Packages Using Deep Learning, Kemal Adem, Cemi̇l Közkurt
Turkish Journal of Electrical Engineering and Computer Sciences
Sealing in aseptic packages, one of the healthiest and cheapest technologies to protect food from parasites in the liquid food industry, requires a detailed and careful control process. Since the controls are made manually and visually by expert machine operators, the human factor can lead to the failure to detect defects, resulting in high cost and food safety risks. Therefore, this study aims to perform a leak test in aseptic package seals by a system that makes decisions using independent deep learning methods. The proposed Faster R-CNN and the Updated Faster R-CNN deep learning models were subjected to training and …
Abc-Based Stacking Method For Multilabel Classification,
2019
TÜBİTAK
Abc-Based Stacking Method For Multilabel Classification, Weimin Ding, Shengli Wu
Turkish Journal of Electrical Engineering and Computer Sciences
Multilabel classification is a supervised learning problem wherein each individual instance is associated with multiple labels. Ensemble methods are effective in managing multilabel classification problems by creating a set of accurate, diverse classifiers and then combining their outputs to produce classifications. This paper presents a novel stacking-based ensemble algorithm, ABC-based stacking, for multilabel classification. The artificial bee colony algorithm, along with a single-layer artificial neural network, is used to find suitable meta-level classifier configurations. The optimization goal of the meta-level classifier is to maximize the average accuracy of classification of all the instances involved. We run an experiment on 10 …
Rough Fuzzy Cuckoo Search For Triclustering Microarray Gene Expression Data,
2019
TÜBİTAK
Rough Fuzzy Cuckoo Search For Triclustering Microarray Gene Expression Data, Swathypriyadharsini Palaniswamy, Premalatha K
Turkish Journal of Electrical Engineering and Computer Sciences
Analyzing time series microarray gene expression data is a computational challenge due to its three-dimensional characteristics. Triclustering techniques are applied to three-dimensional data for mining similarly expressed genes under a subset of conditions and time points. In this work, a novel rough fuzzy cuckoo search algorithm is proposed for triclustering genes across samples and time points simultaneously. By applying the upper and lower approximation of rough set theory and the objective function of fuzzy k-means, rough fuzzy k-means was incorporated into a cuckoo search to handle the uncertainty of the data. The proposed method was applied to three real-life time …
