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2020

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Articles 14941 - 14970 of 15205

Full-Text Articles in Physical Sciences and Mathematics

Modelling Silicate - Nitrate - Ammonium Co-Limitation Of Algal Growth And The Importance Of Bacterial Remineralisation Based On An Experimental Arctic Coastal Spring Bloom Culture Study, Tobias R. Vonnahme, Martial Leroy, Silke Thoms, Dick Van Oevelen, H. Rodger Harvey, Svein Kristiansen, Rolf Gradinger, Christoph Voelker Jan 2020

Modelling Silicate - Nitrate - Ammonium Co-Limitation Of Algal Growth And The Importance Of Bacterial Remineralisation Based On An Experimental Arctic Coastal Spring Bloom Culture Study, Tobias R. Vonnahme, Martial Leroy, Silke Thoms, Dick Van Oevelen, H. Rodger Harvey, Svein Kristiansen, Rolf Gradinger, Christoph Voelker

OES Faculty Publications

Arctic coastal ecosystems are rapidly changing due to climate warming, which makes modelling their productivity crucially important to better understand future changes. System primary production in these systems is highest during the pronounced spring bloom, typically dominated by diatoms. Eventually the spring blooms terminate due to silicon or nitrogen limitation. Bacteria can play an important role for extending bloom duration and total CO2 fixation through ammonium regeneration. Current ecosystem models often simplify the effects of nutrient co-limitations on algal physiology and cellular ratios and neglect bacterial driven regeneration, leading to an underestimation of primary production. Detailed biochemistry- and cell-based models …

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A Secure And Energy-Efficient Opportunistic Routing Protocol With Void Avoidancefor Underwater Acoustic Sensor Networks, Varun Menon, Divya Midhunchakkaravarthy, Sonali John, Sunil Jacob, Amrit Mukherjee Jan 2020

A Secure And Energy-Efficient Opportunistic Routing Protocol With Void Avoidancefor Underwater Acoustic Sensor Networks, Varun Menon, Divya Midhunchakkaravarthy, Sonali John, Sunil Jacob, Amrit Mukherjee

Turkish Journal of Electrical Engineering and Computer Sciences

Recently, underwater acoustic sensor networks (UASNs) have gained wide attention due to their numerous applications in underwater surveillance, oil leakage detection, assisted navigation, and disaster prevention. With unique characteristics like increased propagation delay, constant mobility of sensor nodes, high error rate, and limitations in energy and interference, efficient routing of data packets from the source node to the destination is a major challenge in UASNs. Most of the protocols proposed for traditional sensor networks do not work well in UASNs. Although many protocols have been specifically proposed for underwater environments, the aim of most of them is to improve only …

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On A Yearly Basis Prediction Of Soil Water Content Utilizing Sar Data: A Machinelearning And Feature Selection Approach, Emrullah Acar, Mehmet Si̇raç Özerdem Jan 2020

On A Yearly Basis Prediction Of Soil Water Content Utilizing Sar Data: A Machinelearning And Feature Selection Approach, Emrullah Acar, Mehmet Si̇raç Özerdem

Turkish Journal of Electrical Engineering and Computer Sciences

Soil water content (SWC) performs an important role in many areas including agriculture, drought cases, usage of water resources, hydrology, crop diseases and aerology. However, the measurement of the SWC over large terrains with standard computational techniques is very hard. In order to overcome this situation, remote sensing tools are preferred, which can produce much more successful results in less time than standard calculation techniques. Among all remote sensing tools, synthetic aperture radar (SAR) has a significant impact on determining SWC over large terrains. The main objective of this study is to predict SWC on a yearly basis over the …

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The Impact Of Eddies On Nutrient Supply, Diatom Biomass And Carbon Export In The Northern South China Sea, Yung-Yen Shih, Chin-Chang Hung, Sing-How Tuo, Huan-Jie Shao, Chun Hoe Chow, Francois L.L. Muller, Yuan-Hong Cai Jan 2020

The Impact Of Eddies On Nutrient Supply, Diatom Biomass And Carbon Export In The Northern South China Sea, Yung-Yen Shih, Chin-Chang Hung, Sing-How Tuo, Huan-Jie Shao, Chun Hoe Chow, Francois L.L. Muller, Yuan-Hong Cai

OES Faculty Publications

We have investigated the effect of eddies (cold and warm eddies, CEs and WEs) on the nutrient supply to the euphotic zone and the organic carbon export from the euphotic zone to deeper parts of the water column in the northern South China Sea. Besides basic hydrographic and biogeochemical parameters, the flux of particulate organic carbon (POC), a critical index of the strength of the oceanic biological pump, was also measured at several locations within two CEs and one WE using floating sediment traps deployed below the euphotic zone. The POC flux associated with the CEs (85 ± 55 mg-C …

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Partial Discharge Detection And Localization On The Medium Voltage Xlpe Cableswith Multiclass Support Vector Machines, Fati̇h Serttaş, Fati̇h Onur Hocaoğlu Jan 2020

Partial Discharge Detection And Localization On The Medium Voltage Xlpe Cableswith Multiclass Support Vector Machines, Fati̇h Serttaş, Fati̇h Onur Hocaoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

In medium voltage cables, partial discharges (PD?s) are the major problems that trigger electrical insulation failures. Therefore, classification of PD source type and failure localization in medium voltage cables are significant issues of medium voltage engineering. Therefore, in this study, both detection and localization of PD are studied. As a first step, 4 different kind of defects are artificially generated at the same length of the same kind of medium voltage cross-linked polyethylene (XLPE) cables. Consequently, an experimental setup is built. During the experiments, different medium voltage levels are applied to the cables, then the PD signals are measured and …

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Optimal Svc Allocation In Power Systems Using Lightning Attachment Procedureoptimization, Ayman Awad, Salah Kamel, Heba Youssef, Francisco Jurado Jan 2020

Optimal Svc Allocation In Power Systems Using Lightning Attachment Procedureoptimization, Ayman Awad, Salah Kamel, Heba Youssef, Francisco Jurado

Turkish Journal of Electrical Engineering and Computer Sciences

Flexible AC transmission systems (FACTS) technology is widely adopted and utilized to maintain the performance of power systems. However, the improvements of power system performance achieved by FACTS devices depend on the right sizing and allocation of such devices. For technical and economic considerations, a FACTS device's location and size should be selected very carefully in order to maximize its benefits to the power system. In this paper, the sizing and location of a static VAR compensator (SVC) are optimally determined using a new optimization technique called lightning attachment procedure optimization (LAPO). The optimal allocation of the SVC is determined …

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Performance Across Worldview-2 And Rapideye For Reproducible Seagrass Mapping, Megan M. Coffer, Blake A. Schaeffer, Richard C. Zimmerman, Victoria Hill, Jiang Li, Kazi A. Islam, Peter J. Whitman Jan 2020

Performance Across Worldview-2 And Rapideye For Reproducible Seagrass Mapping, Megan M. Coffer, Blake A. Schaeffer, Richard C. Zimmerman, Victoria Hill, Jiang Li, Kazi A. Islam, Peter J. Whitman

OES Faculty Publications

Satellite remote sensing offers an effective remedy to challenges in ground-based and aerial mapping that have previously impeded quantitative assessments of global seagrass extent. Commercial satellite platforms offer fine spatial resolution, an important consideration in patchy seagrass ecosystems. Currently, no consistent protocol exists for image processing of commercial data, limiting reproducibility and comparison across space and time. Additionally, the radiometric performance of commercial satellite sensors has not been assessed against the dark and variable targets characteristic of coastal waters. This study compared data products derived from two commercial satellites: DigitalGlobe's WorldView-2 and Planet's RapidEye. A single scene from each platform …

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Field-Of-View Optimization Of Magnetically Actuated 2d Gimballed Scanners, Gökçe Aköz, Yi̇ği̇t Dağhan Gökdel Jan 2020

Field-Of-View Optimization Of Magnetically Actuated 2d Gimballed Scanners, Gökçe Aköz, Yi̇ği̇t Dağhan Gökdel

Turkish Journal of Electrical Engineering and Computer Sciences

This work presents the field of view (FOV) maximization of a magnetically actuated two-dimensional (2D) gimballed scanner. The process of maximization is completed in two steps. (1) Optimization of the electrocoil providing the magnetic force that moves the scanner and (2) precise choice of optimum respective locations of both the scanner and the electrocoil. We first derived a formula relating the generated magnetic flux density, coil design parameters and driving voltage. Subsequently, we discussed the design trade-offs of an actuating electrocoil. We also conducted several experiments on a stainless steel 430 scanner having a footprint of 15 mm × 15 …

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Exploring The Power Of Supervised Learning Methods For Company Name Disambiguation In Microblog Posts, Nafi̇ye Polat, Ali̇ Çakmak, Rabi̇a Turan Jan 2020

Exploring The Power Of Supervised Learning Methods For Company Name Disambiguation In Microblog Posts, Nafi̇ye Polat, Ali̇ Çakmak, Rabi̇a Turan

Turkish Journal of Electrical Engineering and Computer Sciences

Twitter is an online social networking website where people can post short messages on any subject, and these messages become visible to other users. Users intentionally express their opinions about companies or products via microblogging texts. Analyzing such messages might help explore what customers think about company products, or what the broad feelings of customers are. Identifying tweets referring to products and companies is becoming an important tool recently. However, company names are often vague. Hence, the first step is to locate the messages that are relevant to a company. In this paper, we present a number of supervised learning …

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Low Power And Low Phase Noise Vco With Dual Current Shaping For Iotapplications, Sajad Nejadhasan, Narges Moazenian, Ebrahim Abiri, Mohammah Reza Salehi Jan 2020

Low Power And Low Phase Noise Vco With Dual Current Shaping For Iotapplications, Sajad Nejadhasan, Narges Moazenian, Ebrahim Abiri, Mohammah Reza Salehi

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, two low phase noise and power consumption VCO circuits, which are suitable for Internet of things (IoT) applications, are proposed. In the first structure, in order to have more control of the current consumption, the current shaping technique is used in the PMOS and NMOS biasing circuit. In the second structure, for increasing the oscillation amplitude and reducing the phase noise, independent biasing for the NMOS section is used. In both structures, to increase the frequency tuning range (FTR), without using a capacitor bank, the varactor is used in the biasing structure. In the first structure the …

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Prominent Quality Attributes Of Crisis Software Systems: A Literature Review, Ahmet Ari̇f Aydin Jan 2020

Prominent Quality Attributes Of Crisis Software Systems: A Literature Review, Ahmet Ari̇f Aydin

Turkish Journal of Electrical Engineering and Computer Sciences

Developing software systems to meet user-demanded functionality is critical. Achieving the design goals by providing the needed functionality is a necessary task, and it is about figuring out a proper set of quality attributes and implementing each one by reflecting a complete set of quality attributes. This study presents popular quality attributes of crisis software systems by conducting a literature review. Each crisis software system has been studied by concentrating on crisis management phases where the system is used, design purposes, and the data processing style. The findings of this research shed light on the crisis software development process by …

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Efficient Bandwidth Management Algorithm For Ng-Epon, Ammar Rafiq, Muhammad Faisal Hayat Jan 2020

Efficient Bandwidth Management Algorithm For Ng-Epon, Ammar Rafiq, Muhammad Faisal Hayat

Turkish Journal of Electrical Engineering and Computer Sciences

Next generation ethernet passive optical network (NG-EPON) is a promising technology to cater huge bandwidth and efficient distribution demands of the future Internet services. IEEE working group has been doing efforts for the standardization of NG-EPON. Four wavelength channels of 25Gbps each are supported by NG-EPON for the transmission of optical network unit (ONU) traffic towards optical line terminal (OLT). Dynamic wavelength and bandwidth allocation (DWBA) algorithms are needed for the efficient arbitration of bandwidth resources between subscribers. In this paper, we have proposed a DWBA algorithm named as efficient bandwidth management algorithm (EBMA) for NG-EPON. EBMA has been designed …

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Harmonic Effects Optimization At A System Level Using A Harmonic Power Flowcontroller, Reza Mehri, Hossein Mokhtari Jan 2020

Harmonic Effects Optimization At A System Level Using A Harmonic Power Flowcontroller, Reza Mehri, Hossein Mokhtari

Turkish Journal of Electrical Engineering and Computer Sciences

Increase of nonlinear loads in industries has resulted in high levels of harmonic currents and consequently harmonic voltages in power networks. Harmonics have several negative effects such as higher energy losses and equipment life reduction. To reduce the levels of harmonics in power networks, different methods of harmonic suppression have been employed. The basic idea in all of these methods is to prevent harmonics from flowing into a power network at customer sides and the point of common coupling (PCC). Due to the costs, none of the existing mitigating methods result in a harmonic-free power system. The remaining harmonic currents, …

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Construction And Performance Analysis Of A New Sac-Ocdma Code Based Onlatin Square Matrix, Amel Aissaoui, Latifa Hacini Jan 2020

Construction And Performance Analysis Of A New Sac-Ocdma Code Based Onlatin Square Matrix, Amel Aissaoui, Latifa Hacini

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper a family of novel spreading code called Latin square code (LSC) is proposed for spectral amplitude coding-optical code division multiple access (SAC-OCDMA) system. The main feature of the proposed code is the zero cross-correlation which eliminates both multiple access interference (MAI) and phase induced intensity noise (PIIN). The code construction can be easily accomplished using Latin square matrix (LSM) for any weight and number of users. The simplicity in the construction code has made it a compelling candidate for future OCDMA applications. SAC-OCDMA system employing direct decoding is mathematically analyzed and then numerically simulated using Matlab and …

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Modelling Sensor Ontology With The Sosa/Ssn Frameworks:A Case Study For Laboratory Parameters, Özlem Aktaş, Mehmet Mi̇lli̇, Sanaz Lakestani̇, Musa Mi̇lli̇ Jan 2020

Modelling Sensor Ontology With The Sosa/Ssn Frameworks:A Case Study For Laboratory Parameters, Özlem Aktaş, Mehmet Mi̇lli̇, Sanaz Lakestani̇, Musa Mi̇lli̇

Turkish Journal of Electrical Engineering and Computer Sciences

Recently, the use of sensor-based systems in many areas has led to an exponential increase in the raw sensor data. However, the lack of neither syntactic nor semantic integrity between these sensor data limited their sharing, reusability, and interpretation. These inabilities can cause some problems. For example, different wireless sensor networks may not work together due to the subtle variations in their sensing methods, operating systems, syntax, and data structure. In recent years, to cope with these inabilities, the semantic sensor web approach, which enables us to enrich the meaning of sensor data, has been seen as the critical technology …

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An Efficient Storage-Optimizing Tick Data Clustering Model, Haleh Amintoosi, Masood Niazi Torshiz, Yahya Forghani, Sara Alinejad Jan 2020

An Efficient Storage-Optimizing Tick Data Clustering Model, Haleh Amintoosi, Masood Niazi Torshiz, Yahya Forghani, Sara Alinejad

Turkish Journal of Electrical Engineering and Computer Sciences

Tick data is a large volume of data, related to a phenomenon such as stock market or weather change, with data values changing rapidly over time. An important issue is to store tick data table in a way that it occupies minimum storage space while at the same time it can provide fast execution of queries. In this paper, a mathematical model is proposed to partition tick data tables into clusters with the aim of minimizing the required storage space. The genetic algorithm is then used to solve the mathematical model which is indeed a clustering model. The proposed method …

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Hydrothermal Activity And Seismicity At Teahitia Seamount: Reactivation Of The Society Islands Hotspot?, Christopher R. German, Joseph A. Resing, Guangyu Xu, Isobel A. Yeo, Sharon L. Walker, Colin W. Devey, James W. Moffett, Gregory A. Cutter, Olivier Hyvernaud, Dominique Reymond Jan 2020

Hydrothermal Activity And Seismicity At Teahitia Seamount: Reactivation Of The Society Islands Hotspot?, Christopher R. German, Joseph A. Resing, Guangyu Xu, Isobel A. Yeo, Sharon L. Walker, Colin W. Devey, James W. Moffett, Gregory A. Cutter, Olivier Hyvernaud, Dominique Reymond

OES Faculty Publications

Along mid-ocean ridges, submarine venting has been found at all spreading rates and in every ocean basin. By contrast, intraplate hydrothermal activity has only been reported from five locations, worldwide. Here we extend the time series at one of those sites, Teahitia Seamount, which was first shown to be hydrothermally active in 1983 but had not been revisited since 1999. Previously, submersible investigations had led to the discovery of low-temperature (≤30°C) venting associated with the summit of Teahitia Seamount at ≤1500 m. In December 2013 we returned to the same site at the culmination of the US GEOTRACES Eastern South …

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Combined Morphology And Svm-Based Fault Feature Extraction Technique Fordetection And Classification Of Transmission Line Faults, Revati Godse, Dr. Sunil Bhat Jan 2020

Combined Morphology And Svm-Based Fault Feature Extraction Technique Fordetection And Classification Of Transmission Line Faults, Revati Godse, Dr. Sunil Bhat

Turkish Journal of Electrical Engineering and Computer Sciences

A transmission line is the main commodity of power transmission network through which power is transmitted to the utility. These lines are often swayed by accidental breakdowns owing to different random origins. Hence, researchers try to detect and track down these failures at the earliest to avoid financial prejudice. This paper offers a new realtime mathematical morphology based approach for fault feature extraction. The morphological open-close-median filter is exploited to wrest unique fault features which are then fed as an input to support vector machine to detect and classify the short circuit faults. The acquired graphical and numerical results of …

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Highly Sensitive Fiber Optic Pressure Sensors For Wind Turbine Applications, Mali̇k Kaya, Okan Esentürk Jan 2020

Highly Sensitive Fiber Optic Pressure Sensors For Wind Turbine Applications, Mali̇k Kaya, Okan Esentürk

Turkish Journal of Electrical Engineering and Computer Sciences

Fiber optic pressure sensors utilizing ultra-high sensitive fiber loop ringdown (FLRD) spectroscopy were fabricated using a bare single mode fiber. The fiber optic pressure sensors were applied to monitor pressure change on a plastic pipe embedded into a sea sand filled container in laboratory conditions to simulate a tower. As the pressure applied to the sensor head was changed from $66.4$ kPa to $331.6$ kPa, changes in the ringdown time (RDT) were recorded. The lowest baseline stability of 0.20 % was obtained in these simple FLRD pressure sensors. The minimum detectable optical loss was $992$ $\mu$dB. The results showed that …

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Improving The Efficiency Of Dnn Hardware Accelerator By Replacing Digitalfeature Extractor With An Imprecise Neuromorphic Hardware, Majid Mohammadi Rad, Omid Sojodishijani Jan 2020

Improving The Efficiency Of Dnn Hardware Accelerator By Replacing Digitalfeature Extractor With An Imprecise Neuromorphic Hardware, Majid Mohammadi Rad, Omid Sojodishijani

Turkish Journal of Electrical Engineering and Computer Sciences

Mixed-signal in-memory computation can drastically improve the efficiency of the hardware implementing machine learning (ML) algorithms by (i) removing the need to fetch neural network parameters from internal or external memory and (ii) performing a large number of multiply-accumulate operations in parallel. However, this boost in efficiency comes with some disadvantages. Among them, the inability to precisely program nonvolatile memory devices (NVM) with neural network parameters and sensitivity to noise prevent the mixed-signal hardware to perform a precise and deterministic computation. Unfortunately, these hardware-specific errors can get magnified while propagating along with the layers of the deep neural network. In …

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Diagnosis Of Speed Sensor Faults In An Induction Machine Based On A Robustadaptive Super-Twisting Observer, Mohammed Zakaria Kari, Abdelkader Mechernene, Sidi Mohammed Meliani, Ibrahim Guenoune Jan 2020

Diagnosis Of Speed Sensor Faults In An Induction Machine Based On A Robustadaptive Super-Twisting Observer, Mohammed Zakaria Kari, Abdelkader Mechernene, Sidi Mohammed Meliani, Ibrahim Guenoune

Turkish Journal of Electrical Engineering and Computer Sciences

The present paper aims to determine a robust sensor fault-tolerant controller based on fuzzy logic using a robust adaptive super-twisting observer for the control of an induction machine and an inverter set by a state estimation method. The speed sensor is considered in the present case. The modular structure of the fault-tolerant control (FTC) scheme allows integrating this sensor within the existing closed-loop system, and the observer can therefore be designed independently. This article presents a new method to develop a fuzzy decision system that provides faulttolerant control. This paper also aims at detecting the mechanical speed sensor faults. The …

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Impulse Noise Removal By K-Means Clustering Identified Fuzzy Filter: A Newapproach, Aritra Bandyopadhyay, Kaustuv Deb, Atanu Das, Rajib Bag Jan 2020

Impulse Noise Removal By K-Means Clustering Identified Fuzzy Filter: A Newapproach, Aritra Bandyopadhyay, Kaustuv Deb, Atanu Das, Rajib Bag

Turkish Journal of Electrical Engineering and Computer Sciences

Removal of impulse noise from corrupted digital images has been a hitch in the field of image processing. Random nature of impulse noise makes the task of noise removal more critical. Different filters have been designed for noise removal purpose and have shown formidable results mostly for low and medium level noise densities. In this paper, a new two-stage technique called k-means clustering identified fuzzy filter (KMCIFF) is proposed for de-noising gray-scale images. KMCIFF consists of a k-Means clustering-based high density impulse noise detection, followed by a fuzzy logic-oriented noise removal mechanism. In the detection process, a 5 $\times$ 5 …

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Optimized Idling Grid-Connection Strategy For Synchronous Condenser, Jianxiang Shi, Heqing Huang, Teng Liu, Wei Mu, Jianfeng Zhao Jan 2020

Optimized Idling Grid-Connection Strategy For Synchronous Condenser, Jianxiang Shi, Heqing Huang, Teng Liu, Wei Mu, Jianfeng Zhao

Turkish Journal of Electrical Engineering and Computer Sciences

The rise of large-scale HVDC transmission technology has introduced new requirements for dynamic reactive power compensation in power systems. The new generation of synchronous condensers is independent of grid voltage and does not need to be dragged by a coaxial prime mover, which can improve the dynamic reactive power compensation of the power grid. This new generation of synchronous condensers is dragged by the static frequency converter to a 105% rated speed, after which the static frequency converter logs out. In the process of idling, the excitation mode switching is completed and the unit is connected to the grid simultaneously. …

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A Supervised Learning Approach For Detecting Erroneoussamples In Embeddings, Görkem Saygili Jan 2020

A Supervised Learning Approach For Detecting Erroneoussamples In Embeddings, Görkem Saygili

Turkish Journal of Electrical Engineering and Computer Sciences

Visualizing multidimensional data has been a crucial task in recent years regarding the growing amount of data from various sources. To achieve this, dimensionality reduction algorithms have been used to reduce the number of dimensions for visualization of the data on a screen. However, these algorithms may fail to faithfully represent high dimensional data in lower dimensions and eventually lead to erroneous visualizations. In this work, we propose an error detection algorithm for dimensionality reduction algorithms based on recently developed error prediction algorithms for medical image registration. The proposed algorithm matches the neighborhoods of high and low dimensional data with …

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Detection Of Hand Osteoarthritis From Hand Radiographs Using Convolutionalneural Networks With Transfer Learning, Kemal Üreten, Hasan Erbay, Hadi̇ Hakan Maraş Jan 2020

Detection Of Hand Osteoarthritis From Hand Radiographs Using Convolutionalneural Networks With Transfer Learning, Kemal Üreten, Hasan Erbay, Hadi̇ Hakan Maraş

Turkish Journal of Electrical Engineering and Computer Sciences

Osteoarthritis is the most common type of arthritis. Hand osteoarthritis leads to specific structural changes in the joints, such as asymmetric joint space narrowing and osteophytes (bone spurs). Conventional radiography has traditionally been the primary method of visualizing these structural changes and diagnosing osteoarthritis. We aimed to develop a computerized method that is capable of determining the structural changes seen in radiography of the hand and to assist practitioners in interpreting radiographic changes and diagnosing the disease. In this retrospective study, transfer-learning-based convolutional neural networks were trained on a randomly selected dataset containing 332 radiography images of hands from an …

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Chronic Obstructive Pulmonary Disease Severity Analysis Using Deep Learning Onmulti-Channel Lung Sounds, Gökhan Altan, Yakup Kutlu, Ahmet Gökçen Jan 2020

Chronic Obstructive Pulmonary Disease Severity Analysis Using Deep Learning Onmulti-Channel Lung Sounds, Gökhan Altan, Yakup Kutlu, Ahmet Gökçen

Turkish Journal of Electrical Engineering and Computer Sciences

Chronic obstructive pulmonary disease (COPD) is one of the deadliest diseases which cannot be treated but can be kept under control in certain stages. COPD has five severities, including at-risk, mild, moderate, severe, and very severe stages. Diagnosis of COPD at early stages needs additional clinical tests for even experienced specialists. The study aims at detecting the severity of the COPD to start treatment for preventing the progression of the disease to the next levels. We analyzed 12-channel lung sounds with different COPD severities from RespiratoryDatabase@TR. The lung sounds were recorded from the clinical auscultation points from 41 patients on …

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A Novel Grouping Proof Authentication Protocol For Lightweight Devices:Gpapxr+, Ömer Aydin, Gökhan Dalkiliç, Cem Kösemen Jan 2020

A Novel Grouping Proof Authentication Protocol For Lightweight Devices:Gpapxr+, Ömer Aydin, Gökhan Dalkiliç, Cem Kösemen

Turkish Journal of Electrical Engineering and Computer Sciences

Radio frequency identification (RFID) tags that meet EPC Gen2 standards are used in many fields such as supply chain operations. The number of the RFID tags, smart cards, wireless sensor nodes, and Internet of things devices is increasing day by day and the areas where they are used are expanding. These devices are very limited in terms of the resources they have. For this reason, many security mechanisms developed for existing computer systems cannot be used for these devices. In order to ensure secure communication, it is necessary to provide authentication process between these lightweight devices and the devices they …

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Modeling Compaction Parameters Using Support Vector And Decision Treeregression Algorithms, Abdurrahman Özbeyaz, Mehmet Söylemez Jan 2020

Modeling Compaction Parameters Using Support Vector And Decision Treeregression Algorithms, Abdurrahman Özbeyaz, Mehmet Söylemez

Turkish Journal of Electrical Engineering and Computer Sciences

Shortening the periods of compaction tests can be possible by analyzing the data obtained from previous laboratory tests with regression methods. The regression analysis applied to current data reduces the cost of experiments, saves time, and gives estimated outputs. In this study, the MLS-SVR, KB-SVR, and DTR algorithms were employed for the first time for the estimation of soil compaction parameters. The performances of these regression algorithms in estimating maximum dry unit weight (MDD) and optimum water content (OMC) were compared. Furthermore, the soil properties (fine-grained soil, sand, gravel, specific gravity, liquid limit, and plastic limit) were employed as inputs …

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Optimum Reference Distance Based Path Loss Exponent Determination Forvehicle-To-Vehicle Communication, Kenan Kuzulugi̇l, Zeynep Hasirci, İsmai̇l Hakki Çavdar Jan 2020

Optimum Reference Distance Based Path Loss Exponent Determination Forvehicle-To-Vehicle Communication, Kenan Kuzulugi̇l, Zeynep Hasirci, İsmai̇l Hakki Çavdar

Turkish Journal of Electrical Engineering and Computer Sciences

Vehicle-to-vehicle (V2V) communication environment differs from classical wireless communication with respect to low antenna heights and high mobility. Therefore, V2V channel modeling based on real measurements is still crucial to get the channel parameters for the various road environments. One of the most extracted parameters from measurements is path loss exponent and selecting a fixed reference distance value in obtaining this parameter may also cause remarkable fitting errors. Thus, in this study, least square method-based approach for the best-fitted path loss exponent calculation was proposed by determining the optimum reference distance value from the V2V channel measurements. First, V2V channel …

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Microplastic Fragment And Fiber Contamination Of Beach Sediments From Selected Sites In Virginia And North Carolina, Usa, Gabrielle Z. Dodson, A. Katrina Shotorban, Patrick G. Hatcher, Derek Waggoner, Sutapa Ghosal, Nora Noffke Jan 2020

Microplastic Fragment And Fiber Contamination Of Beach Sediments From Selected Sites In Virginia And North Carolina, Usa, Gabrielle Z. Dodson, A. Katrina Shotorban, Patrick G. Hatcher, Derek Waggoner, Sutapa Ghosal, Nora Noffke

OES Faculty Publications

Microplastic particles (<5 >mm) constitute a growing pollution problem within coastal environments. This study investigated the microplastic presence of estuarine and barrier island beaches in the states of Virginia and North Carolina, USA. Seventeen sediment cores were collected at four study sites and initially tested for microplastic presence by pyrolysis-gas chromatography–mass spectrometry. For the extraction, microplastic particles were first separated from the sediment using a high-density cesium chloride solution (1.88 g/mL). In a second step, an oil extraction collected the remaining microplastic particles of higher densities. Under the light microscope, the extracted microplastic particles were classified based on their morphologies …

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