Computer Engineering Commons^™

Estimation Of Multi-Directional Ankle Impedance As A Function Of Lower Extremity Muscle Activation, Lauren Knop

Dissertations, Master's Theses and Master's Reports

The purpose of this research is to investigate the relationship between the mechanical impedance of the human ankle and the corresponding lower extremity muscle activity. Three experimental studies were performed to measure the ankle impedance about multiple degrees of freedom (DOF), while the ankle was subjected to different loading conditions and different levels of muscle activity. The first study determined the non-loaded ankle impedance in the sagittal, frontal, and transverse anatomical planes while the ankle was suspended above the ground. The subjects actively co-contracted their agonist and antagonistic muscles to various levels, measured using electromyography (EMG). An Artificial Neural Network …

Channel And Carrier Frequency Offset Estimation Based On Projection Onto Abidimensional Basis, Roberto Carrasco Alvarez, Ramon Parra Michel, Aldo Gustavo Orozco Lugo, Marco Antonio Gurrola Navarro

Turkish Journal of Electrical Engineering and Computer Sciences

Two of the most counterproductive effects that must be dealt with in communication systems in realistic environments are carrier frequency offset (CFO) and time-varying channels. These problems are usually addressed by using independent approaches for each one. This paper introduces an algorithm that attacks both of these effects in a joint fashion. It is based on a rough compensation of CFO, and after considering that the remaining CFO uncertainty can be seen as part of the time-varying channel a channel estimation that includes that composite channel is performed. Particularly, the channel estimation based on projection onto a bidimensional basis is …

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 …

Novel Applications Of Machine Learning In Bioinformatics, Yi Zhang

Theses and Dissertations--Computer Science

Technological advances in next-generation sequencing and biomedical imaging have led to a rapid increase in biomedical data dimension and acquisition rate, which is challenging the conventional data analysis strategies. Modern machine learning techniques promise to leverage large data sets for finding hidden patterns within them, and for making accurate predictions. This dissertation aims to design novel machine learning-based models to transform biomedical big data into valuable biological insights. The research presented in this dissertation focuses on three bioinformatics domains: splice junction classification, gene regulatory network reconstruction, and lesion detection in mammograms.

A critical step in defining gene structures and mRNA …

Automated Network Security With Exceptions Using Sdn, Sergio A. Rivera Polanco

Theses and Dissertations--Computer Science

Campus networks have recently experienced a proliferation of devices ranging from personal use devices (e.g. smartphones, laptops, tablets), to special-purpose network equipment (e.g. firewalls, network address translation boxes, network caches, load balancers, virtual private network servers, and authentication servers), as well as special-purpose systems (badge readers, IP phones, cameras, location trackers, etc.). To establish directives and regulations regarding the ways in which these heterogeneous systems are allowed to interact with each other and the network infrastructure, organizations typically appoint policy writing committees (PWCs) to create acceptable use policy (AUP) documents describing the rules and behavioral guidelines that all campus network …

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 …

Effects Of Correlation Of Channel Gains On The Secrecy Capacity In The Gaussian Wiretap Channel, Abhishek Lokur

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Secrecy capacity is one of the most important characteristic of a wireless communication channel. Therefore, the study of this characteristic wherein the system has correlated channel gains and study them for different line-of-sight (LOS) propagation scenarios is of ultimate importance.

The primary objective of this thesis from the mathematical side is to determine the secrecy capacity (SC) for correlated channel gains for the main and eavesdropper channels in a Gaussian Wiretap channel as a function from main parameters (μ, Σ, ρ). f(h₁, h₂) is the joint distribution of the two channel gains at channel use (h …

Exploring Critical Success Factors For Data Integration And Decision-Making In Law Enforcement, Marquay Edmondson, Walter R. Mccollum, Mary-Margaret Chantre, Gregory Campbell

International Journal of Applied Management and Technology

Agencies from various disciplines supporting law enforcement functions and processes have integrated, shared, and communicated data through ad hoc methods to address crime, terrorism, and many other threats in the United States. Data integration in law enforcement plays a critical role in the technical, business, and intelligence processes created by users to combine data from various sources and domains to transform them into valuable information. The purpose of this qualitative phenomenological study was to explore the current conditions of data integration frameworks through user and system interactions among law enforcement organizational processes. Further exploration of critical success factors used to …

Recurrent Residual U-Net For Medical Image Segmentation, Md Zahangir Alom, Christopher Yakopcic, Mahmudul Hasan, Tarek M. Taha, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

Deep learning (DL)-based semantic segmentation methods have been providing state-of-the-art performance in the past few years. More specifically, these techniques have been successfully applied in medical image classification, segmentation, and detection tasks. One DL technique, U-Net, has become one of the most popular for these applications. We propose a recurrent U-Net model and a recurrent residual U-Net model, which are named RU-Net and R2U-Net, respectively. The proposed models utilize the power of U-Net, residual networks, and recurrent convolutional neural networks. There are several advantages to using these proposed architectures for segmentation tasks. First, a residual unit helps when training deep …

A Survey Of Techniques For Mobile Service Encrypted Traffic Classification Using Deep Learning, Pan Wang, Xuejiao Chen, Feng Ye, Zhixin Sun

Electrical and Computer Engineering Faculty Publications

The rapid adoption of mobile devices has dramatically changed the access to various net- working services and led to the explosion of mobile service traffic. Mobile service traffic classification has been a crucial task that attracts strong interest in mobile network management and security as well as machine learning communities for past decades. However, with more and more adoptions of encryption over mobile services, it brings a lot of challenges about mobile traffic classification. Although classical machine learning approaches can solve many issues that port and payload-based methods cannot solve, it still has some limitations, such as time-consuming, costly handcrafted …

Estimation And Prediction Of The Human Gait Dynamics For The Control Of An Ankle-Foot Prosthesis, Guilherme Aramizo Ribeiro

Dissertations, Master's Theses and Master's Reports

With the growing population of amputees, powered prostheses can be a solution to improve the quality of life for many people. Powered ankle-foot prostheses can be made to behave similar to the lost limb via controllers that emulate the mechanical impedance of the human ankle. Therefore, the understanding of human ankle dynamics is of major significance. First, this work reports the modulation of the mechanical impedance via two mechanisms: the co-contraction of the calf muscles and a change of mean ankle torque and angle. Then, the mechanical impedance of the ankle was determined, for the first time, as a multivariable …

Mesh Node Communication System For Fire Figthers, Eric E. Hamke, Trace Norris, Jessica E. Ladd, Jeffrey K. Eaton, Jicard J. Malveaux, Manish Bhattarai, Ramiro Jordan, Manel Martinez-Ramon

Electrical & Computer Engineering Technical Reports

This report describes the prototype and demonstration of a reliable local area network (LAN) of devices able to interconnect a crew of fire fighters with a communications node. The data consists of images for thermal cameras at a given rate and other low bandwith data taken from the different sensors of the fire fighter gear, that are connected to the transmitter using a Bluetooth personal area network (PAN). The physical environment is indoors and it is expected that all nodes of the communication networks are distributed in different positions into a building.