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2021

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Articles 26371 - 26400 of 27884

Full-Text Articles in Physical Sciences and Mathematics

Topics In Design And Analysis Of Experiments: Calibration, Sequential Experimentation, And Model Selection, Christine Miller Jan 2021

Topics In Design And Analysis Of Experiments: Calibration, Sequential Experimentation, And Model Selection, Christine Miller

Theses and Dissertations

Experiments are widely used across multiple disciplines to uncover information about a system or processes. Experimental design is a statistical technique devoted to the methodology of selecting the appropriate samples to aid in the subsequent analysis. We research three open problems in experimental designs regarding calibration, sequential experimentation, and model selection. First, we focus on calibration; the impact of experimental design choice on the performance of statistical calibration is largely unknown. We investigate the performance of several experimental designs with regards to inverse prediction via a comprehensive simulation study. Specifically, we compare several design types including traditional response surface designs, …

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Red Drum And Spotted Seatrout Live-Release Tournament Mortality And Dispersal, T. Reid Nelson, Crystal Hightower, Sean P. Powers Jan 2021

Red Drum And Spotted Seatrout Live-Release Tournament Mortality And Dispersal, T. Reid Nelson, Crystal Hightower, Sean P. Powers

University Faculty and Staff Publications

Although catch-and-release fishing tournaments undoubtedly reduce mortality of target species, postrelease mortality and fish stockpiling at release sites remain common concerns related to these tournaments. The impacts of liverelease tournaments on freshwater species have been widely studied. However, research on estuarine sport fishes is lacking even though catch-and-release tournaments targeting these species are prevalent and popular recreational fisheries exist. Therefore, we estimated the post-weigh-in mortality and dispersal of Red Drum Sciaenops ocellatus and Spotted Seatrout Cynoscion nebulosus released from the 2016–2018 Alabama Deep Sea Fishing Rodeo live-weigh-in categories using acoustic telemetry. To concurrently estimate overall post-weigh-in mortality and dispersal, we …

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Improving Space Efficiency Of Deep Neural Networks, Aliakbar Panahi Jan 2021

Improving Space Efficiency Of Deep Neural Networks, Aliakbar Panahi

Theses and Dissertations

Language models employ a very large number of trainable parameters. Despite being highly overparameterized, these networks often achieve good out-of-sample test performance on the original task and easily fine-tune to related tasks. Recent observations involving, for example, intrinsic dimension of the objective landscape and the lottery ticket hypothesis, indicate that often training actively involves only a small fraction of the parameter space. Thus, a question remains how large a parameter space needs to be in the first place — the evidence from recent work on model compression, parameter sharing, factorized representations, and knowledge distillation increasingly shows that models can be …

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Statistical Approaches For Estimation And Comparison Of Brain Functional Connectivity, Jifang Zhao Jan 2021

Statistical Approaches For Estimation And Comparison Of Brain Functional Connectivity, Jifang Zhao

Theses and Dissertations

Drug addiction can lead to many health-related problems and social concerns. Functional connectivity obtained from functional magnetic resonance imaging (fMRI) data promotes a variety of fundamental understandings in such association. Due to its complex correlation structure and large dimensionality, the modeling and analysis of the functional connectivity from neuroimage are challenging. By proposing a spatio-temporal model for multi-subject neuroimage data, we incorporate voxel-level spatio-temporal dependencies of whole-brain measurements to improve the accuracy of statistical inference. To tackle large-scale spatio-temporal neuroimage data, we develop a computationally efficient algorithm to estimate the parameters. Our method is used to identify functional connectivity and …

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The 3d Printing Of Dielectric Elastomer Films Assisted By Electrostatic Force, Yuhao Wang, Yanfen Zhou, Wenyue Li, Zhanxu Liu, Bangzi Zhou, Shipeng Wen, Liang Jiang, Shaojuan Che, Jianwei Ma, Tony Betts, Stephen Jerrams, Fenglei Zhou Jan 2021

The 3d Printing Of Dielectric Elastomer Films Assisted By Electrostatic Force, Yuhao Wang, Yanfen Zhou, Wenyue Li, Zhanxu Liu, Bangzi Zhou, Shipeng Wen, Liang Jiang, Shaojuan Che, Jianwei Ma, Tony Betts, Stephen Jerrams, Fenglei Zhou

Articles

ompared with traditional methods for preparing dielectric elastomer (DE) films, electrohydrodynamic (EHD) 3D printing displays many advantages, notably full automation, computer control and flexible design. It also confers high printing resolution, high preparation efficiency with minimal probability of nozzle clogging. In this article, EHD 3D printing was employed to fabricate silicone rubber (SR) based DE films. In order to increase their dielectric constant, high dielectric copper phthalocyanine (CuPc) particles were added into the SR ink. Optimal printing conditions were determined by analyzing the effects of printing voltage and ink properties on the formation of liquid cone and the printed line …

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Radium Isotopes As Submarine Groundwater Discharge (Sgd) Tracers: Review And Recommendations, J. Garcia-Orellana, V. Rodellas, Joseph Tamborski, M. Diego-Feliu, P. Van Beek, Y. Weinstein, M. Charette, A. Alorda-Kleinglass, H.A. Michael, T. Stieglitz, J. Scholten Jan 2021

Radium Isotopes As Submarine Groundwater Discharge (Sgd) Tracers: Review And Recommendations, J. Garcia-Orellana, V. Rodellas, Joseph Tamborski, M. Diego-Feliu, P. Van Beek, Y. Weinstein, M. Charette, A. Alorda-Kleinglass, H.A. Michael, T. Stieglitz, J. Scholten

OES Faculty Publications

Submarine groundwater discharge (SGD) is now recognized as an important process of the hydrological cycle worldwide and plays a major role as a conveyor of dissolved compounds to the ocean. Naturally occurring radium isotopes (Ra-223, Ra-224, Ra-226 and Ra-228) are widely employed geochemical tracers in marine environments. Whilst Ra isotopes were initially predominantly applied to study open ocean processes and fluxes across the continental margins, their most common application in the marine environment has undoubtedly become the identification and quantification of SGD. This review focuses on the application of Ra isotopes as tracers of SGD and associated inputs of water …

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A Mathematical Analysis Of The Wind Triangle Problem And An Inquiry Of True Airspeed Calculations In Supersonic Flight, Leonard T. Huang, Lisa I. Cummings Jan 2021

A Mathematical Analysis Of The Wind Triangle Problem And An Inquiry Of True Airspeed Calculations In Supersonic Flight, Leonard T. Huang, Lisa I. Cummings

International Journal of Aviation, Aeronautics, and Aerospace

In the first half of this paper, we present a fresh perspective toward the Wind Triangle Problem in aerial navigation by deriving necessary and sufficient conditions, which we call "go/no-go conditions", for the existence/non-existence of a solution of the problem. Although our derivation is based on simple trigonometry and basic properties of quadratic functions, it is mathematically rigorous. We also offer examples to demonstrate how easy it is to check these conditions graphically. In the second half of this paper, we use function theory to re-examine another problem in aerial navigation, namely, that of computing true airspeed — even in …

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Co2 Reduction Measures In The Aviation Industry: Current Measures And Outlook, Florian Mathys, P. Wild, J. Wang Jan 2021

Co2 Reduction Measures In The Aviation Industry: Current Measures And Outlook, Florian Mathys, P. Wild, J. Wang

International Journal of Aviation, Aeronautics, and Aerospace

This article gives a holistic overview of the current CO2 reduction measures and analyses the effectiveness of measures that are feasible for implementation in the future. To achieve the objectives of the Paris Agreement, the aviation industry needs to implement reduction measures because of its forecasted growth and contribution to global warming. The focus is set on CO2 reduction measures, categorized in technology, operations, infrastructure/air traffic management (ATM), and market-based measures. The most promising long-term technologies to reduce CO2 emissions are hydrogen-powered aircrafts and sustainable aviation fuels (SAF). In terms of operations, CO2 emissions can be …

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Can Stable Isotopes From Tree Rings Improve Our Understanding Of Past Variability In The Southern Annular Mode?, Zachary Grzywacz Jan 2021

Can Stable Isotopes From Tree Rings Improve Our Understanding Of Past Variability In The Southern Annular Mode?, Zachary Grzywacz

Graduate Theses, Dissertations, and Problem Reports

Few annually dated stable isotope records exist across Oceania. In mid- to high-latitude locations in South America, tree-ring stable isotopes provide information about past climate dynamics such as the Southern Annular Mode (SAM). The SAM drives latitudinal shifts in Southern Hemisphere westerly winds, influencing temperature and moisture delivery across the mid- to high-latitudes, including Tasmania. Combinations of paleoclimate proxies from across the Southern Ocean might provide insight into dynamic processes like the SAM that are difficult to measure with a single proxy. Measuring stable carbon and oxygen isotope ratios from tree rings in Tasmania could provide complementary data to contribute …

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Option Implied Volatility's Predictability On Monthly Stock Returns, Hung T. Dao Jan 2021

Option Implied Volatility's Predictability On Monthly Stock Returns, Hung T. Dao

Senior Independent Study Theses

Since the trading of options is based on underlying stocks, it is reasonable to assume that information from the options market can be used to explain the returns in the stock market. Our independent study investigates the relationship between options implied volatility and stock returns. Previous studies have found significant results in using implied volatility in predicting stock returns. This paper provides a discussion of such studies, the theoretical framework for the research topic, and the Black-Scholes model, which is famous for its application in implied volatility calculation. Monthly returns of 20 large US firms are regressed against implied volatility …

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The Application Of Machine Learning In Analyzing Organic Compounds From Nmr Spectral Data, Nicole Maia Powell Jan 2021

The Application Of Machine Learning In Analyzing Organic Compounds From Nmr Spectral Data, Nicole Maia Powell

Senior Independent Study Theses

Nuclear magnetic resonance (NMR) is used in organic chemistry to identify unknown organic compounds. The data obtained from an NMR spectrometer are typically shown in the form of a spectrum, which is then analyzed by an analytical chemist. The action of analyzing a spectrum, especially one of a large and complex molecule, is a long and tedious process. In this project, Python is used to implement hierarchical clustering on NMR data obtained from an NMR spectrometer at the College of Wooster to explore its application in NMR analysis. MATLAB is used to build a decision tree from the same data, …

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Climate Change Impacts Go Beyond The Surface: Groundwater Recharge Rates And Aquifer Resources Across The Contiguous United States, Kendra R. Devereux Jan 2021

Climate Change Impacts Go Beyond The Surface: Groundwater Recharge Rates And Aquifer Resources Across The Contiguous United States, Kendra R. Devereux

Senior Independent Study Theses

Groundwater is a primary source of potable water for millions and a major source for crop irrigation in the United States. Thus, it is vital to understand current and future rates of recharge to predict and manage groundwater availability. In this study, current groundwater recharge rates across the Contiguous US at 800m resolution are estimated by following methods presented by Reitz et al. (2017), and the reproducibility of the methods are assessed. A water budget approach is implemented where quick flow runoff and evapotranspiration rates are subtracted from precipitation rates. Precipitation was found to be the most reproducible water budget …

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Employing Exoglycosidase And Transferase Enzymes In Capillary Nanogel Electrophoresis For The Determination Of N-Glycan Linkages And Enzyme Michaelis-Menten Constants., Lloyd Bwanali Jan 2021

Employing Exoglycosidase And Transferase Enzymes In Capillary Nanogel Electrophoresis For The Determination Of N-Glycan Linkages And Enzyme Michaelis-Menten Constants., Lloyd Bwanali

Graduate Theses, Dissertations, and Problem Reports

As a post translational modification protein glycosylation plays a crucial role in protein signaling, binding, kinetics and folding. In disease diagnosis and prognosis, monitoring glycosylation has been identified as a biomarker. Sialylation and sialic acid linkage in N-glycans are markers of cancers including liver, pancreatic and kidney cancer. Quantification of sialic acid linkage is analytically challenging because of the diverse linkages and the presence of heterogenous branching. A capillary electrophoresis method is reported that integrates a unique combination of enzymes and lectins to modify sialylated asparagine-linked glycans (N-glycans) in real time in the capillary so that N-glycan structures containing α2–6-linked …

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Private Groundwater Management And Risk Awareness: A Cross-Sectional Analysis Of Two Age-Related Subsets In The Republic Of Ireland, Simon Mooney, J. O'Dwyer, Paul Hynds Jan 2021

Private Groundwater Management And Risk Awareness: A Cross-Sectional Analysis Of Two Age-Related Subsets In The Republic Of Ireland, Simon Mooney, J. O'Dwyer, Paul Hynds

Articles

Risk communication represents the optimal instrument for decreasing the incidence of private groundwater contamination and associated waterborne illnesses. However, despite attempts to promote voluntary well maintenance in high groundwater-reliant regions such as the Republic of Ireland, awareness levels of supply status (e.g. structural integrity) have remained low. As investigations of supply awareness are often thematically narrow and homogeneous with respect to sub-population, revised analyses of awareness among both current and future supply owners (i.e. adults of typical well owner and student age) are necessary. Accordingly, the current study utilised a national survey of well users and an age-based comparison of …

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A New Classification Method For Encrypted Internet Traffic Using Machine Learning, Mesut Uğurlu, İbrahi̇m Alper Doğru, Recep Si̇nan Arslan Jan 2021

A New Classification Method For Encrypted Internet Traffic Using Machine Learning, Mesut Uğurlu, İbrahi̇m Alper Doğru, Recep Si̇nan Arslan

Turkish Journal of Electrical Engineering and Computer Sciences

The rate of internet usage in the world is over 62% and this rate is increasing day by day. With this increase, it becomes important to ensure the confidentiality of the information in the traffic flowing over the internet. Encryption algorithms and protocols are used for this purpose. This situation, which is beneficial for normal users, is also used by attackers to hide. Cyber attackers or hackers gain the ability to bypass security precautions such as IDS/IPS and antivirus systems with using encrypted traffic. Since payload analysis cannot be performed without deciphering the encrypted traffic, existing commercial security solutions fall …

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Real-Time Motion Tracking Enhancement Via Data-Fusion Based Particle Filter, Tuğrul Taşci, Numan Çelebi̇ Jan 2021

Real-Time Motion Tracking Enhancement Via Data-Fusion Based Particle Filter, Tuğrul Taşci, Numan Çelebi̇

Turkish Journal of Electrical Engineering and Computer Sciences

Motion tracking is a well-defined yet application-specific problem of computer vision field, mostly entailing real-time constraints. Methods addressing such problems are expected also to ensure achievements such as high accuracy and robustness. A probabilistic estimation-based approach is proposed in this paper, in order to enhance the real-time motion tracking process of an RGB-Depth device, in terms of accuracy. A novel method is presented for tracking handpalm of a moving human subject to this end, under a sequence of assumptions such as indoor environment, single object, smooth movement and stable illumination. Tracking accuracy is improved within a particle filter framework by …

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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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Design And Analysis Of A Truncated Elliptical-Shaped Chipless Rfid Tag, Ameer Taimour Khan, Yassin Abdullah, Sidra Farhat, Wasim Nawaz, Usman Rauf Jan 2021

Design And Analysis Of A Truncated Elliptical-Shaped Chipless Rfid Tag, Ameer Taimour Khan, Yassin Abdullah, Sidra Farhat, Wasim Nawaz, Usman Rauf

Turkish Journal of Electrical Engineering and Computer Sciences

This article presents a novel polarization-insensitive chipless radio frequency identification tag having an encoding capacity of 11 bits. The proposed resonator design comprises discontinuous arc slots forming truncated elliptically shape offering 1:1 slot to bit correspondence with suppressed unwanted harmonic resonances. Electromagnetic performance analysis of the proposed tag design is done over an ungrounded Rogers RT duroid® 5880 laminate. The overall tag design covers a footprint of 15 × 15 × 0.508 mm3 offering convincingly appreciable bit density of 4.88 bits/cm2 . The realized tags are analyzed for real-world electromagnetic performance resulting in an agreement between measured and computed results. …

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An Integrated Optimal Method For Cloud Service Ranking, Mohammad Hossein Nejat, Homayun Motameni, Hamed Vahdat-Nejad Jan 2021

An Integrated Optimal Method For Cloud Service Ranking, Mohammad Hossein Nejat, Homayun Motameni, Hamed Vahdat-Nejad

Turkish Journal of Electrical Engineering and Computer Sciences

Many cloud providers present various services with different attributes. It is a complex, lengthy process to select a cloud service that meets user requirements from an assortment of services. At the same time, user requirements are sometimes defined with imprecision (sets or intervals), whereas it is also important to consider the quality of user feedback (QoU) and quality of service (QoS) attributes for ranking. Besides, each MADM method has a di erent procedure, which causes functional contradictions. These contradictions have led to confusion in choosing the best MADM method. It is necessary to provide a method that harmonizes the results. …

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Scale-Invariant Histogram Of Oriented Gradients: Novel Approach For Pedestriandetection In Multiresolution Image Dataset, Sweta Panigrahi, Surya Narayana Raju Undi Jan 2021

Scale-Invariant Histogram Of Oriented Gradients: Novel Approach For Pedestriandetection In Multiresolution Image Dataset, Sweta Panigrahi, Surya Narayana Raju Undi

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes a scale-invariant histogram of oriented gradients (SI-HOG) for pedestrian detection. Most of the algorithms for pedestrian detection use the HOG as the basic feature and combine other features with the HOG to form the feature set, which is usually applied with a support vector machine (SVM). Hence, the HOG feature is the most efficient and fundamental feature for pedestrian detection. However, the HOG feature produces feature vectors of different lengths for different image resolutions; thus, the feature vectors are incomparable for the SVM. The proposed method forms a scale-space pyramid wherein the histogram bin is calculated. Thus, …

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Gene Expression Data Classification Using Genetic Algorithm-Basedfeature Selection, Öznur Si̇nem Sönmez, Mustafa Dağteki̇n, Tolga Ensari̇ Jan 2021

Gene Expression Data Classification Using Genetic Algorithm-Basedfeature Selection, Öznur Si̇nem Sönmez, Mustafa Dağteki̇n, Tolga Ensari̇

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, hybrid methods are proposed for feature selection and classification of gene expression datasets. In the proposed genetic algorithm/support vector machine (GA-SVM) and genetic algorithm/k nearest neighbor (GA-KNN) hybrid methods, genetic algorithm is improved using Pearson's correlation coefficient, Relief-F, or mutual information. Crossover and selection operations of the genetic algorithm are specialized. Eight different gene expression datasets are used for classification process. The classification performances of the proposed methods are compared with the traditional GA-KNN and GA-SVM wrapper methods and other studies in the literature. Classification results demonstrate that higher accuracy rates are obtained with the proposed methods …

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A Hybrid Approach Based On Transfer And Ensemble Learning For Improvingperformances Of Deep Learning Models On Small Datasets, Tunç Gülteki̇n, Aybars Uğur Jan 2021

A Hybrid Approach Based On Transfer And Ensemble Learning For Improvingperformances Of Deep Learning Models On Small Datasets, Tunç Gülteki̇n, Aybars Uğur

Turkish Journal of Electrical Engineering and Computer Sciences

The need for high-volume data is one of the challenging requirements of the deep learning methods, and it makes it harder to apply deep learning algorithms to domains in which the data sources are limited, in other words, small. These domains may vary from medical diagnosis to satellite imaging. The performances of the deep learning methods on small datasets can be improved by the approaches such as data augmentation, ensembling, and transfer learning. In this study, we propose a new approach that utilizes transfer learning and ensemble methods to increase the accuracy rates of convolutional neural networks for classification tasks …

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A Hybrid Numerical Model For Long-Range Electromagnetic Wave Propagation, Gül Yesa Altun, Özlem Özgün Jan 2021

A Hybrid Numerical Model For Long-Range Electromagnetic Wave Propagation, Gül Yesa Altun, Özlem Özgün

Turkish Journal of Electrical Engineering and Computer Sciences

A hybrid numerical model is presented for solving long range electromagnetic wave propagation problems involving objects on or above the ground surface by hybridizing the two-way split-step parabolic equation (2W-SSPE) method with the method of moments (MoM). The advantages of the proposed model are twofold: (i) It reduces the staircasing error in irregular terrain modeling, which usually occurs when the standard SSPE method is used alone. This is achieved by employing the MoM to more accurately obtain the scattered fields from slanted/curved surfaces. (ii) It enables the SSPE method to handle the problems involving objects above the Earth's surface, which …

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Comparison Of Metaheuristic Optimization Algorithms With A New Modifieddeb Feasibility Constraint Handling Technique, Murat Erhan Çi̇men, Zeynep Gari̇p, Ali̇ Fuat Boz Jan 2021

Comparison Of Metaheuristic Optimization Algorithms With A New Modifieddeb Feasibility Constraint Handling Technique, Murat Erhan Çi̇men, Zeynep Gari̇p, Ali̇ Fuat Boz

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, the modification of the Deb feasibility method is considered to solve the constrained optimization problems. In the developed modified Deb feasibility constraint method, the third rule in its procedure was revised in order to increase the performance of the Deb feasibility constraint handling method. The innovation in the method is based on generating a new individual by using both possible solutions that violate the constraints in the method used for solving the problem. In detail, discussions were given about the application and usefulness of six constrained handling techniques. Furthermore, genetic algorithm, particle swarm optimization, Harris hawks optimization, …

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Leukocyte Classification Based On Feature Selection Using Extra Trees Classifier: Atransfer Learning Approach, Diana Baby, Sujitha Juliet Devaraj, Jude Hemanth, Anishin Raj M M Jan 2021

Leukocyte Classification Based On Feature Selection Using Extra Trees Classifier: Atransfer Learning Approach, Diana Baby, Sujitha Juliet Devaraj, Jude Hemanth, Anishin Raj M M

Turkish Journal of Electrical Engineering and Computer Sciences

The criticality of investigating the white blood cell (WBC) count cannot be underestimated, as white blood cells are an important component of the body's defence system. From helping to diagnose hidden infections to insinuating the presence of comorbidities like immunodeficiency, an accurate white blood cell count can contribute significantly to shape a physician?s assessment. The manual process performed by the pathologists for the classification of WBCs is a time consuming and tedious task, which is further disadvantaged by a lack of accuracy. This study concentrates on the automatic detection and classification of WBC without data augmentation into four subtypes such …

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Evolutionary Neural Networks For Improving The Prediction Performance Ofrecommender Systems, Berna Şeref, Gazi̇ Erkan Bostanci, Mehmet Serdar Güzel Jan 2021

Evolutionary Neural Networks For Improving The Prediction Performance Ofrecommender Systems, Berna Şeref, Gazi̇ Erkan Bostanci, Mehmet Serdar Güzel

Turkish Journal of Electrical Engineering and Computer Sciences

Recommender systems provide recommendations to users using background data such as ratings of users about items and features of items. These systems are used in several areas such as e-commerce, news websites, and article websites. By using recommender systems, customers are provided with relevant data as soon as possible and are able to make good decisions. There are more studies about recommender systems and improving their performance. In this study, prediction performances of neural networks are evaluated and their performances are improved using genetic algorithms. Performances obtained in this study are compared with those of other studies. After that, superiority …

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A Novel Optimum Pi Controller Design Based On Stability Boundary Locussupported Particle Swarm Optimization In Avr System, Mahmut Temel Özdemi̇r Jan 2021

A Novel Optimum Pi Controller Design Based On Stability Boundary Locussupported Particle Swarm Optimization In Avr System, Mahmut Temel Özdemi̇r

Turkish Journal of Electrical Engineering and Computer Sciences

This study proposes a new approach that combines stability and optimization in the design of proportional? integral (PI) controller of automatic voltage regulators (AVR) of synchronous generators with variable system parameters. Thanks to this approach, a PI controller, providing the desired performance and the stability of the AVR system, has been designed. The approach follows a method investigating the PI gain values to achieve the desired goals. In the first step of the study, a new stability boundary locus is calculated for the case in which AVR system?s parameters have changed. The stability boundary locus (SBL) method is a graphic-based …

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A Software Availability Model Based On Multilevel Software Rejuvenation Andmarkov Chain, Zahra Rahmani Ghobadi, Hassan Rashidi Jan 2021

A Software Availability Model Based On Multilevel Software Rejuvenation Andmarkov Chain, Zahra Rahmani Ghobadi, Hassan Rashidi

Turkish Journal of Electrical Engineering and Computer Sciences

Increasing use of software, rapid and unavoidable changes in the operational environment bring many problemsfor software engineers. One of these problems is the aging and degradation of software performance. Software rejuvenationis a proactive and preventive approach to counteract software aging. Generally, when software is initiated, amounts ofmemory are allocated. Then, the body of software is executed for providing a service and when the software is terminated,the allocated memory is released. In this paper, a rejuvenation model based on multilevel software rejuvenation andMarkov chain presented. In this model, the system performance as a result of degraded physical memory and memoryusage is …

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Placement Accuracy Algorithm For Smart Street Lights, Zulkifli Ishak, Wan Siti Halimatul Munirah Wan Ahmad, Nurul Asyikin Mohamed Radzi, Suhaila Sulaiman, Noor Emilia Ramli Jan 2021

Placement Accuracy Algorithm For Smart Street Lights, Zulkifli Ishak, Wan Siti Halimatul Munirah Wan Ahmad, Nurul Asyikin Mohamed Radzi, Suhaila Sulaiman, Noor Emilia Ramli

Turkish Journal of Electrical Engineering and Computer Sciences

The smart street light (SSL) system is an emerging technology in which a street light is equipped withan advanced control system for dimming and turning the light on or off. SSL also improves the maintenance work byproviding an enhanced inventory, which includes Global Positioning System (GPS) coordinates that can be retrieved froma GPS-enabled SSL. However, GPS coordinates may be inaccurate due to human error and GPS inaccuracy. This workproposes new algorithms for identifying human error and GPS inaccuracy in SSL installation by using distance analysisand the solving point-in-polygon method. The algorithms are important for inventory and maintenance purposes. Faultylight poles …

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Maritime Automatic Target Recognition For Ground-Based Scanning Radars By Usingsequential Range Profiles, Baki̇ Bati, Nevci̇han Duru Jan 2021

Maritime Automatic Target Recognition For Ground-Based Scanning Radars By Usingsequential Range Profiles, Baki̇ Bati, Nevci̇han Duru

Turkish Journal of Electrical Engineering and Computer Sciences

Classification of marine targets using radar data products has become an important area for modern researchsociety. However, due to several reasons such as the similarity between ship structures and spatial specifications,classification of marine targets constitutes a challenging problem. In almost all of the studies, this problem has beenhandled by focusing on a single instance of range profiles or synthetic aperture radar data. However, this approachis seen to achieve only a particular success. This study introduces a novel classification approach that is shown toprovide additional classification enhancements by exploiting the extra information extracted from sequential rangeprofiles generated by ground-based marine surveillance …

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