Computer Sciences Commons^™

Robust Power System State Estimation By Appropriate Selection Of Tolerance Forthe Least Measurement Rejected Algorithm, Mohammad Shoaib Shahriar, Ibrahim Omar Habiballah

Turkish Journal of Electrical Engineering and Computer Sciences

Modern power systems are highly complicated and nonlinear in nature. Accurate estimation of the power system states (voltage-magnitude and phase-angle) is required for the secure operation of the power system. The presence of bad-data measurements in meters has made this estimation process challenging. An efficient estimator should detect and eliminate the effect of bad data during the estimation process. Least measurement rejected (LMR) is a robust estimator that has been found successful in dealing with various categories of bad data. The performance of LMR depends upon the proper selection of a tolerance for each measurement. This paper presents a novel …

A New Approach For Parameter Estimation Of The Single-Diode Model Forphotovoltaic Cells/Modules, Bi̇lge Kaan Atay, Ulaş Emi̇noğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Solar energy has become a popular renewable energy source, leading to wide use of photovoltaic (PV) cells/modules in energy production. For this reason, realistic modeling of PVs and determining the equivalent circuit parameters is of great importance in terms of planning and operation. Hence, in this study, an analytical model for identifying the single-diode equivalent circuit parameters; series resistance (Rs ), shunt resistance (Rp ), diode ideality factor (a), diode reverse-saturation current (Io ), and photon current (Ipv ) for PV cells/modules is developed without neglecting any term. In order to test the accuracy of the model, a number of …

Effect Of Orientation Of Rf Sources Maintained Within The Enclosures On Electricalshielding Effectiveness Performance, İbrahi̇m Bahadir Başyi̇ği̇t, Abdullah Genç, Selçuk Helhel

Turkish Journal of Electrical Engineering and Computer Sciences

The effect of single aperture metallic enclosures on electrical shielding effectiveness (ESE) has been investigated. Simulations and measurements have been obtained for comparison. The effects of orientation of transmitting antenna (source orientation) with respect to aperture length have been studied at 2.60?9 GHz as a novelty, and this gives details of IC RF source orientation in an enclosure. In the case of square apertures on an enclosure, a higher ESE value is obtained with respect to a rectangular aperture. As a case study, when the aperture width of the enclosure is decreased from 75 to 18.75 mm, the frequency bandwidth …

Adaptive Switching Gain Sliding Mode Control For Speed Regulation In Pmsms, Yanwei Huang, Yuqing Xie, Zheyi Liu

Turkish Journal of Electrical Engineering and Computer Sciences

To suppress uncertainties caused by parametric variations or disturbances, an adaptive switching gain (ASG) is proposed for integral sliding mode control (ISMC) to regulate speed in permanent magnet synchronous motors (PMSMs). According to system uncertainties, the ASG is designed to adjust the switching gain to suppress the chattering. The adaptive law is a positive value resulting in an increment of the switching gain when the tracking trajectory is outside the boundary layer. Conversely, it is negative with a decrement of the gain. Further, it improves a convergent rate by the function of the reciprocal of the tracking error when the …

Particle Swarm Optimization Approach To Optimal Design Of An Afpm Tractionmachine For Different Driving Conditions, Naghi Rostami

Turkish Journal of Electrical Engineering and Computer Sciences

Axial flux permanent magnet (AFPM) machines can be employed as the traction motor of electric vehicles due to their high torque capability, high efficiency, modular and compact construction, and capability of integration with other mechanical components in integrated systems. Besides, the system efficiency can be further improved by optimal design of the selected electric machine. In this paper, an AFPM machine is optimized against two well-known driving cycles called the New European Drive Cycle (NEDC) and US06 and the influence of the driving cycle on the obtained machine parameters is evaluated. US06 is the more demanding driving cycle and thus …

Empirical Single Frequency Network Threshold For Dvb-T2 Based On Laboratory Experiments, Bundit Ruckveratham, Sathaporn Promwong

Turkish Journal of Electrical Engineering and Computer Sciences

DVB-T2 broadcasting with a single frequency network (SFN) allows an efficient management of frequency utilization and extends the coverage area, which will enable more people to view a broadcast. The SFN mode also increases the concentration of the signal in overlap areas. However, some difference of overlap areas in actual use of SFN networks may have some degradation of the received signal due to the effect of the SFN. In this research, we analyze SFN broadcasting in SISO mode. This paper represents the effects of delays on the SFN signal over different delay times within the guard interval (GI) by …

A Robust Ensemble Feature Selector Based On Rank Aggregation For Developing New Vo\Textsubscript{2}Max Prediction Models Using Support Vector Machines, Fatih Abut, Mehmet Fati̇h Akay, James George

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes a new ensemble feature selector, called the majority voting feature selector (MVFS), for developing new maximal oxygen uptake (VO2max) prediction models using a support vector machine (SVM). The approach is based on rank aggregation, which meaningfully utilizes the correlation among the relevance ranks of predictor variables given by three state-of-the-art feature selectors: Relief-F, minimum redundancy maximum relevance (mRMR), and maximum likelihood feature selection (MLFS). By applying the SVM combined with MVFS on a self-created dataset containing maximal and submaximal exercise data from 185 college students, several new hybrid (VO2max) prediction models have been created. To compare the …

A Modified Gravitational Search Algorithm And Its Application In Lifetime Maximization Of Wireless Sensor Networks, Sepehr Ebrahimi Mood, Mohammad Masoud Javidi

Turkish Journal of Electrical Engineering and Computer Sciences

Recently, academic communities and industrial sectors have been affected by significant advancements in wireless sensor networks (WSNs). Employing clustering methods is the dominant method to maximize the WSN's lifetime, which is considered to be a major issue. Metaheuristic algorithms have attracted wide attention in the research area of clustering. In this paper, first a novel nature-inspired optimization algorithm based on the gravitational search algorithm (GSA) is defined. To control the exploitation and exploration capabilities of this algorithm, along with calculating the masses value, the tournament selection method is employed. Tournament size, the parameter of this method, is computed automatically using …

Evaluating The Attributes Of Remote Sensing Image Pixels For Fast K-Means Clustering, Ali̇ Sağlam, Nurdan Baykan

Turkish Journal of Electrical Engineering and Computer Sciences

Clustering process is an important stage for many data mining applications. In this process, data elements are grouped according to their similarities. One of the most known clustering algorithms is the k-means algorithm. The algorithm initially requires the number of clusters as a parameter and runs iteratively. Many remote sensing image processing applications usually need the clustering stage like many image processing applications. Remote sensing images provide more information about the environments with the development of the multispectral sensor and laser technologies. In the dataset used in this paper, the infrared (IR) and the digital surface maps (DSM) are also …

Parallel Algorithms For Computing Sparse Matrix Permanents, Kamer Kaya

Turkish Journal of Electrical Engineering and Computer Sciences

The permanent is an important characteristic of a matrix and it has been used in many applications. Unfortunately, it is a hard to compute and hard to approximate the immanant. For dense/full matrices, the fastest exact algorithm, Ryser, has O($2^{n-1}$n) complexity. In this work, a parallel algorithm, SkipPer, is proposed to exploit the sparsity within the input matrix as much as possible. SkipPer restructures the matrix to reduce the overall work, skips the unnecessary steps, and employs a coarse-grain, shared-memory parallelization with dynamic scheduling. The experiments show that SkipPer increases the performance of exact permanent computation up to 140 compared …

Possible Effects Of Dielectrophoretic Fields In The Brains Of Mri Operators And Ms Patients: A Radiologically Isolated Syndrome Evaluation, Cahi̇t Canbay

Turkish Journal of Electrical Engineering and Computer Sciences

Frequent use of magnetic resonance imaging (MRI) devices, which are major contributors in understanding health problems in the human body, is a subject that needs to be taken into consideration both for patients and for operators who are constantly in the vicinity of devices. In this context, electromagnetic impact assessment of an MRI device was performed at the point where the patient entered the device. Dielectrophoretic fields induced by radio frequency (RF) coils of an MRI scanner on male and female operator brain models were computed by using dispersive electrical medium parameters. The main cause of induced secondary dielectrophoretic fields …

Compact Metal-Plate Slotted Wlan-Wimax Antenna Design With Usb Wi-Fi Adapter Application, Cem Baytöre, Cem Göçen, Meri̇h Palandöken, Adnan Kaya, Emi̇ne Yeşi̇m Zoral

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a compact antenna design, which operates in the 2.4, 5.2, and 5.8 GHz (WLAN) and 3.5 and 5.5 GHz (WiMAX) frequency bands, has been implemented to be compatible with the 802.11.ac/n standards. The proposed metal antenna is made of a copper plate of thickness 0.5 mm with a compact overall physical size of 20 mm $\times$ 30 mm. Although it is low-profile, it can work with high efficiency because it has a cheap planar metal structure and it does not contain any expensive dielectric material. The antenna is investigated in terms of S parameters, input impedance, efficiency, …

Improving Word Embeddings Projection For Turkish Hypernym Extraction, Savaş Yildirim

Turkish Journal of Electrical Engineering and Computer Sciences

Corpus-driven approaches can automatically explore is-a relations between the word pairs from corpus. This problem is also called hypernym extraction. Formerly, lexico-syntactic patterns have been used to solve hypernym relations. The language-specific syntactic rules have been manually crafted to build the patterns. On the other hand, recent studies have applied distributional approaches to word semantics. They extracted the semantic relations relying on the idea that similar words share similar contexts. Former distributional approaches have applied one-hot bag-of-word (BOW) encoding. The dimensionality problem of BOW has been solved by various neural network approaches, which represent words in very short and dense …

Assessment Of Techno-Economic Benefits For Smart Charging Scheme Of Electric Vehicles In Residential Distribution System, Kumari Kasturi, Manas Ranjan Nayak

Turkish Journal of Electrical Engineering and Computer Sciences

Connecting multiple electric vehicles (EVs) to a power system network for the purpose of charging has major setbacks like decrease in power quality, instability in voltage profile, and increase in power losses and thus electricity price. This paper focuses on devising an optimal charging scheme to reduce the negative impacts of EVs' presence in the distribution network by limiting the charging process to only off-peak demand periods when the electricity price is comparatively lower. The salp swarm algorithm, an efficient, fast, and reliable optimization technique, is used to obtain the optimal locations for the EVs and their charging schedule in …

Tapu: Test And Pick Up-Based $K$-Connectivity Restoration Algorithm For Wireless Sensor Networks, Vahi̇d Khali̇lpour Akram, Orhan Dağdevi̇ren

Turkish Journal of Electrical Engineering and Computer Sciences

A $k$-connected wireless sensor network remains connected if any $k$-1 arbitrary nodes stop working. The aim of movement-assisted $k$-connectivity restoration is to preserve the $k$-connectivity of a network by moving the nodes to the necessary positions after possible failures in nodes. This paper proposes an algorithm named TAPU for $k$-connectivity restoration that guarantees the optimal movement cost. Our algorithm improves the time and space complexities of the previous approach (MCCR) in both best and worst cases. In the proposed algorithm, the nodes are classified into safe and unsafe groups. Failures of safe nodes do not change the $k$ value of …

The Biobjective Multiarmed Bandit: Learning Approximate Lexicographic Optimal Allocations, Cem Teki̇n

Turkish Journal of Electrical Engineering and Computer Sciences

We consider a biobjective sequential decision-making problem where an allocation (arm) is called $\epsilon$ lexicographic optimal if its expected reward in the first objective is at most $\epsilon$ smaller than the highest expected reward, and its expected reward in the second objective is at least the expected reward of a lexicographic optimal arm. The goal of the learner is to select arms that are $\epsilon$ lexicographic optimal as much as possible without knowing the arm reward distributions beforehand. For this problem, we first show that the learner's goal is equivalent to minimizing the $\epsilon$ lexicographic regret, and then, propose a …

Power Quality Improvement Of Smart Microgrids Using Ems-Based Fuzzy Controlled Upqc, Ahmed A. Hossam-Eldin, Ahmed A. Mansour, Mohammed El-Gamal, Karim H. Youssef

Turkish Journal of Electrical Engineering and Computer Sciences

The prevalent power quality problems in smart microgrids and power distribution systems are voltage sag, voltage swell, and harmonic distortion. The achievement of pure sinusoidal waveform with proper magnitude and phase is currently a great research and development concern. The aim of this paper is to evaluate and mitigate the smart microgrid harmonics, voltage sag, and voltage swell throughout a 24-h cycle, taking into consideration the variation in solar power generation due to changes in irradiation received by photovoltaic cells, the variation in wind power generation due to changes in wind speed, and the variation of linear and nonlinear load …

Optimized Bilevel Classifier For Brain Tumor Type And Grade Discrimination Using Evolutionary Fuzzy Computing, Kavitha Srinivasan, Mohanavalli Subramaniam, Bharathi Bhagavathsingh

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, an optimized bilevel brain tumor diagnostic system for identifying the tumor type at the first level and grade of the identified tumor at the second level is proposed using genetic algorithm, decision tree, and fuzzy rule-based approach. The dataset is composed of axial MRI of brain tumor types and grades. From the images, various features such as first and second order statistical and textural features are extracted (26 features). In the first level, tumor type classification was done using decision tree constructed with all features. Further evolutionary computing using genetic algorithms (GA) was applied to select the …

Selective Word Encoding For Effective Text Representation, Savaş Özkan, Akin Özkan

Turkish Journal of Electrical Engineering and Computer Sciences

Determining the category of a text document from its semantic content is highly motivated in the literature and it has been extensively studied in various applications. Also, the compact representation of the text is a fundamental step in achieving precise results for the applications and the studies are generously concentrated to improve its performance. In particular, the studies which exploit the aggregation of word-level representations are the mainstream techniques used in the problem. In this paper, we tackle text representation to achieve high performance in different text classification tasks. Throughout the paper, three critical contributions are presented. First, to encode …

Relation Prediction Over Biomedical Knowledge Bases For Drug Repositioning, Mehmet Bakal

Theses and Dissertations--Computer Science

Identifying new potential treatment options for medical conditions that cause human disease burden is a central task of biomedical research. Since all candidate drugs cannot be tested with animal and clinical trials, in vitro approaches are first attempted to identify promising candidates. Likewise, identifying other essential relations (e.g., causation, prevention) between biomedical entities is also critical to understand biomedical processes. Hence, it is crucial to develop automated relation prediction systems that can yield plausible biomedical relations to expedite the discovery process. In this dissertation, we demonstrate three approaches to predict treatment relations between biomedical entities for the drug repositioning task …

Word Sense Disambiguation Using Semantic Kernels With Class-Based Term Values, Ayşe Berna Altinel, Murat Can Gani̇z, Bi̇lge Şi̇pal, Eren Can Erkaya, Onur Can Yücedağ, Muhammed Ali̇ Doğan

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, we propose several semantic kernels for word sense disambiguation (WSD). Our approaches adapt the intuition that class-based term values help in resolving ambiguity of polysemous words in WSD. We evaluate our proposed approaches with experiments, utilizing various sizes of training sets of disambiguated corpora (SensEval). With these experiments we try to answer the following questions: 1.) Do our semantic kernel formulations yield higher classification performance than traditional linear kernel?, 2.) Under which conditions a kernel design performs better than others?, 3.) Does the addition of class labels into standard term-document matrix improve the classification accuracy?, 4.) Is …

Transfer Learning Approach To Multiclass Classification Of Child Facial Expressions, Megan A. Witherow, Manar D. Samad, Khan M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

The classification of facial expression has been extensively studied using adult facial images which are not appropriate ground truths for classifying facial expressions in children. The state-of-the-art deep learning approaches have been successful in the classification of facial expressions in adults. A deep learning model may be better able to learn the subtle but important features underlying child facial expressions and improve upon the performance of traditional machine learning and feature extraction methods. However, unlike adult data, only a limited number of ground truth images exist for training and validating models for child facial expression classification and there is a …

Computer-Aided Classification Of Impulse Oscillometric Measures Of Respiratory Small Airways Function In Children, Nancy Selene Avila

Open Access Theses & Dissertations

Computer-aided classification of respiratory small airways dysfunction is not an easy task. There is a need to develop more robust classifiers, specifically for children as the classification studies performed to date have the following limitations: 1) they include features derived from tests that are not suitable for children and 2) they cannot distinguish between mild and severe small airway dysfunction.

This Dissertation describes the classification algorithms with high discriminative capacity to distinguish different levels of respiratory small airways function in children (Asthma, Small Airways Impairment, Possible Small Airways Impairment, and Normal lung function). This ability came from innovative feature selection, …

A Practitioner Survey Exploring The Value Of Forensic Tools, Ai, Filtering, & Safer Presentation For Investigating Child Sexual Abuse Material, Laura Sanchez, Cinthya Grajeda, Ibrahim Baggili, Cory Hall

Electrical & Computer Engineering and Computer Science Faculty Publications

For those investigating cases of Child Sexual Abuse Material (CSAM), there is the potential harm of experiencing trauma after illicit content exposure over a period of time. Research has shown that those working on such cases can experience psychological distress. As a result, there has been a greater effort to create and implement technologies that reduce exposure to CSAM. However, not much work has explored gathering insight regarding the functionality, effectiveness, accuracy, and importance of digital forensic tools and data science technologies from practitioners who use them. This study focused specifically on examining the value practitioners give to the tools …

On Spectral Analysis Of The Internet Delay Space And Detecting Anomalous Routing Paths, Gonca Gürsun

Turkish Journal of Electrical Engineering and Computer Sciences

Latency is one of the most critical performance metrics for a wide range of applications. Therefore, it is important to understand the underlying mechanisms that give rise to the observed latency values and diagnose the ones that are unexpectedly high. In this paper, we study the Internet delay space via robust principal component analysis (RPCA). Using RPCA, we show that the delay space, i.e. the matrix of measured round trip times between end hosts, can be decomposed into two components: the estimated latency between end hosts with respect to the current state of the Internet and the inflation on the …

Classification Of Generic System Dynamics Model Outputs Via Supervised Time Series Pattern Discovery, Mert Edali, Mustafa Gökçe Baydoğan, Gönenç Yücel

Turkish Journal of Electrical Engineering and Computer Sciences

System dynamics (SD) is a simulation-based approach for analyzing feedback-rich systems. An ideal SD modeling cycle requires evaluating the qualitative pattern characteristics of a large set of time series model output for testing, validation, scenario analysis, and policy analysis purposes. This traditionally requires expert judgement, which limits the extent of experimentation due to time constraints. Although time series recognition approaches can help to automate such an evaluation, utilization of them has been limited to a hidden Markov model classifier, namely the Indirect Structure Testing Software (ISTS) algorithm. Despite being used within several automated model-analysis tools, ISTS has several shortcomings. In …

Graph Analysis Of Network Flow Connectivity Behaviors, Hangyu Hu, Xuemeng Zhai, Mingda Wang, Guangmin Hu

Turkish Journal of Electrical Engineering and Computer Sciences

Graph-based approaches have been widely employed to facilitate in analyzing network flow connectivity behaviors, which aim to understand the impacts and patterns of network events. However, existing approaches suffer from lack of connectivity-behavior information and loss of network event identification. In this paper, we propose network flow connectivity graphs (NFCGs) to capture network flow behavior for modeling social behaviors from network entities. Given a set of flows, edges of a NFCG are generated by connecting pairwise hosts who communicate with each other. To preserve more information about network flows, we also embed node-ranking values and edge-weight vectors into the original …

A Comparative Study Of Author Gender Identification, Tuğba Yildiz

Turkish Journal of Electrical Engineering and Computer Sciences

In recent years, author gender identification has gained considerable attention in the fields of information retrieval and computational linguistics. In this paper, we employ and evaluate different learning approaches based on machine learning (ML) and neural network language models to address the problem of author gender identification. First, several ML classifiers are applied to the features obtained by bag-of-words. Secondly, datasets are represented by a low-dimensional real-valued vector using Word2vec, GloVe, and Doc2vec, which are on par with ML classifiers in terms of accuracy. Lastly, neural networks architectures, the convolution neural network and recurrent neural network, are trained and their …

Multiscanning Mode Laser Scanning Confocal Microscopy System, Mert Aktürk, Gökhan Gümüş, Baykal Sarioğlu, Yi̇ği̇t Dağhan Gökdel

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a table-top, reflective mode, laser scanning confocal microscopy system that is capable of scanning the target specimen alternately through various scanning devices and methods is proposed. We have developed a laser scanning confocal microscopy system to utilize combinations of various scanning devices and methods and to be able to characterize the optical performance of different scanners and micromirrors that are frequently used in scanning microscopy systems such as multiphoton microscopy, optical coherence tomography, or confocal microscopy. By integrating the scanner to be characterized on the same optical path with a galvanometric scan mirror, which is the conventional …

Hybrid Self-Controlled Precharge-Free Cam Design For Low Power And High Performance, V V Satyanarayana Satti, Sridevi Sriadibhatla

Turkish Journal of Electrical Engineering and Computer Sciences

Content-addressable memory (CAM) is a prominent hardware for high-speed lookup search, but consumes larger power. Traditional NOR and NAND match-line (ML) architectures suffer from a short circuit current path sharing and charge sharing respectively during precharge. The recently proposed precharge-free CAM suffers from high search delay and the subsequently proposed self-controlled precharge-free CAM suffers from high power consumption. This paper presents a hybrid self-controlled precharge-free (HSCPF) CAM architecture, which uses a novel charge control circuitry to reduce search delay as well as power consumption. The proposed and existing CAM ML architectures were developed using CMOS 45nm technology node with a …