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Articles 1591 - 1620 of 8897

Full-Text Articles in Physical Sciences and Mathematics

Preparations Of Nickel-Iron Hydroxide/Sulfide And Their Electrocatalytic Performances For Overall Water Splitting, Hang-Shuo Lu, Xiao-Bo He, Feng-Xiang Yin, Guo-Ru Li Feb 2020

Preparations Of Nickel-Iron Hydroxide/Sulfide And Their Electrocatalytic Performances For Overall Water Splitting, Hang-Shuo Lu, Xiao-Bo He, Feng-Xiang Yin, Guo-Ru Li

Journal of Electrochemistry

The Ni-Fe/Ti oxygen evolution electrode was prepared by electrodeposition on a titanium mesh substrate. Then, the as prepared Ni-Fe/Ti electrode was used to derive the Ni-Fe-S/Ti hydrogen evolution electrode through solid phase sulfuration. The effects of the molar ratio of Ni2+ to Fe3+ in the electrolyte and the amount of thiourea on the structures and electrochemical performances of Ni-Fe/Ti and Ni-Fe-S/Ti electrodes were investigated. The results show that the oxygen evolution performance of Ni-Fe/Ti electrode was first increased and then decreased with the increase of nickel ion content in the electrolyte. The Ni9Fe1/Ti electrode exhibited the best oxygen …

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Recent Progress In The Mechanistic Understanding Of Co2 Reduction On Copper, Matthew M Sartin, Wei Chen, Fan He, Yan-Xia Chen Feb 2020

Recent Progress In The Mechanistic Understanding Of Co2 Reduction On Copper, Matthew M Sartin, Wei Chen, Fan He, Yan-Xia Chen

Journal of Electrochemistry

In this review, we present the major developments in the understanding of the mechanisms of the electrochemical reduction of CO2 from a historical perspective. Most of the work discussed in this review was carried out at copper electrodes, as this is the only material at which hydrocarbons are produced in reasonable quantities. The emphasis focuses on the differentiation of mechanisms for the generation of C1 and C2 products as well as factors and methods for controlling the product selectivity of CO2 reduction. We have highlighted ambiguities, assumptions, and important methodologies, such as differential electrochemical mass spectrometry and electrochemical …

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Preparation And Electrocatalytic Performance Of Nico2O4/Ni Foam For Hydrogen Peroxide Electrooxidation, Wei-Wei Chen, Fei-Fan Zhang, Jia-Liang Du, Yi Wang, Chun-Lin Zhao, Kai Zhu, Dian-Xue Cao, Gui-Ling Wang Feb 2020

Preparation And Electrocatalytic Performance Of Nico2O4/Ni Foam For Hydrogen Peroxide Electrooxidation, Wei-Wei Chen, Fei-Fan Zhang, Jia-Liang Du, Yi Wang, Chun-Lin Zhao, Kai Zhu, Dian-Xue Cao, Gui-Ling Wang

Journal of Electrochemistry

The electrodes of Ni foam supported NiCo2O4 nanowires were prepared by hydrothermal method, followed by a thermal treatment in air, and were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM) and transmission electron microscopy (TEM). It was found that the NiCo2O4 nanowires had a diameter of about 50 nm with a length up to 3 ~ 5 μm. The catalytic performances of the Ni foam supported NiCo2O4 nanowires for H2O2 electrooxidation were studied by cyclic voltammetry and chronoamperometry. The results show that the Ni foam supported NiCo …

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Challenges In The Activity And Stability Of Pt-Based Catalysts Toward Orr, Tuo Zhao, Er-Gui Luo, Xian Wang, Jun-Jie Ge, Chang-Peng Liu, Wei Xing Feb 2020

Challenges In The Activity And Stability Of Pt-Based Catalysts Toward Orr, Tuo Zhao, Er-Gui Luo, Xian Wang, Jun-Jie Ge, Chang-Peng Liu, Wei Xing

Journal of Electrochemistry

The development of highly efficient oxygen reduction reaction (ORR) catalysts is the key to the commercialization of fuel cells, where the sluggish ORR reaction rate needs to be overcome by adjusting the intermediates adsorption energies on the catalytic surfaces. To-date, platinum (Pt)-based materials are the-state-of-the-art catalysts in terms of both activity and stability in ORR, making them the preferred choice for commercial applications. However, the high cost of Pt-based catalysts limits their widespread use, leading to massive effects paid in reducing Pt loading, improving catalyst activity and stability. This article illustrates the challenges in the ORR reaction and introduces the …

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Lithium Storage Performance Of High Capacity Material Si@CPzs In Lithium Ion Batteries, Qing-Nuan Zhang, Fang-Fang Zhang, Hong-Xia Li, Bing-Jun Yang, Xiao-Cheng Li, Juan Yang Feb 2020

Lithium Storage Performance Of High Capacity Material Si@CPzs In Lithium Ion Batteries, Qing-Nuan Zhang, Fang-Fang Zhang, Hong-Xia Li, Bing-Jun Yang, Xiao-Cheng Li, Juan Yang

Journal of Electrochemistry

Carbon layers with different thicknesses were introduced into the surfaces of silicon (Si) nanoparticles by sol-gel method using poly (cyclotriphosphazene-co-4, 4'-sulfonyldiphenol) as the carbon source. Technologies of X-ray diffraction, thermo-gravimetric analysis, Brunauer-Emmett-Teller and transmission electron microscopy were employed to analyze the structures and components of the as-prepared Si@CPZS composites. Electrochemical performance of Si@CPZS with different carbon thicknesses was studied. The results showed that Si@CPZS with carbon thickness of 10 nm possessed the best performance. Its capacity remained 940 mAh·g-1 after 290 cycles under 500 mA·g-1. As the addictive, the graphite-based anode contained 30% of …

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Atomic Force Microscopic Characterization Of Solid Electrolyte Interphase In Lithium Ion Batteries, Qing-Yu Dong, Yan-Li Chu, Yan-Bin Shen, Li-Wei Chen Feb 2020

Atomic Force Microscopic Characterization Of Solid Electrolyte Interphase In Lithium Ion Batteries, Qing-Yu Dong, Yan-Li Chu, Yan-Bin Shen, Li-Wei Chen

Journal of Electrochemistry

In recent years, the rapid growing in the electric vehicle market has raised higher requirement on the lithium-ion batteries (LIBs) performance towards energy density and safety. However, considering the successful development of LIBs techniques in the past 30 years, there is little room left for improving the LIBs performance on the aspects related to the electrode materials, battery structure design and production processes. It is important to pursue more comprehensive fundamental understanding in the entire system and working principle of LIBs. Solid electrolyte interphase (SEI), existing between the electrode material and the electrolyte, has been proved to be an important …

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Effect Of Nitrogen Content In Catalyst Precursor On Activity Of Fen/C Catalyst For Oxygen Reduction Reaction, Zhi Yang, Ya-Yun Shen, E Zhou, Cheng-Ling Wei, Hao-Li Qin, Juan Tian Feb 2020

Effect Of Nitrogen Content In Catalyst Precursor On Activity Of Fen/C Catalyst For Oxygen Reduction Reaction, Zhi Yang, Ya-Yun Shen, E Zhou, Cheng-Ling Wei, Hao-Li Qin, Juan Tian

Journal of Electrochemistry

Non-noble metal catalysts with high activity and low cost have attracted increasing interest as potential catalysts for oxygen reduction reaction (ORR) to replace Pt-based catalysts. In this paper, the effect of nitrogen content in catalyst precursor on ORR activity of FeN/C catalyst was investigated by X-ray diffraction (XRD), Brunauer-Emmet-Teller (BET) surface area and pore size distribution measurements, transmission electron microscope (TEM), thermogravimetric analysis (TGA), and rotating disk electrode (RDE) techniques. The results show that the most active catalyst was obtained by pyrolysis in argon at 1050 °C with a catalyst precursor containing 20wt% 1,10-phenanthroline, 1wt% Fe and Black Pearl 2000. …

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Cyber-Physical Security With Rf Fingerprint Classification Through Distance Measure Extensions Of Generalized Relevance Learning Vector Quantization, Trevor J. Bihl, Todd J. Paciencia, Kenneth W. Bauer Jr., Michael A. Temple Feb 2020

Cyber-Physical Security With Rf Fingerprint Classification Through Distance Measure Extensions Of Generalized Relevance Learning Vector Quantization, Trevor J. Bihl, Todd J. Paciencia, Kenneth W. Bauer Jr., Michael A. Temple

Faculty Publications

Radio frequency (RF) fingerprinting extracts fingerprint features from RF signals to protect against masquerade attacks by enabling reliable authentication of communication devices at the “serial number” level. Facilitating the reliable authentication of communication devices are machine learning (ML) algorithms which find meaningful statistical differences between measured data. The Generalized Relevance Learning Vector Quantization-Improved (GRLVQI) classifier is one ML algorithm which has shown efficacy for RF fingerprinting device discrimination. GRLVQI extends the Learning Vector Quantization (LVQ) family of “winner take all” classifiers that develop prototype vectors (PVs) which represent data. In LVQ algorithms, distances are computed between exemplars and PVs, and …

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Reliability Analysis Of Power Grids And Its Interdependent Infrastructures: An Interaction Graph-Based Approach, Upama Nakarmi Feb 2020

Reliability Analysis Of Power Grids And Its Interdependent Infrastructures: An Interaction Graph-Based Approach, Upama Nakarmi

USF Tampa Graduate Theses and Dissertations

Large blackouts with significant societal and economic impacts result from cascade of failures in the transmission network of power grids. Understanding and mitigating cascading failures in power grids is challenging due to the large number of components and their complex interactions, wherein, in addition to the physical topology of the system, the physics of power flow and functional dependencies among components largely affect the spatial distribution and propagation of failures. In this dissertation, data-driven interaction graphs, which help in capturing the underlying interactions and influences among the components during cascading failures, are used for capturing the non-local nature of propagation …

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Measuring Localization Confidence For Quantifying Accuracy And Heterogeneity In Single-Molecule Super-Resolution Microscopy, Hesam Mazidi, Tianben Ding, Arye Nehorai, Matthew D. Lew Feb 2020

Measuring Localization Confidence For Quantifying Accuracy And Heterogeneity In Single-Molecule Super-Resolution Microscopy, Hesam Mazidi, Tianben Ding, Arye Nehorai, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

We present a computational method, termed Wasserstein-induced flux (WIF), to robustly quantify the accuracy of individual localizations within a single-molecule localization microscopy (SMLM) dataset without ground- truth knowledge of the sample. WIF relies on the observation that accurate localizations are stable with respect to an arbitrary computational perturbation. Inspired by optimal transport theory, we measure the stability of individual localizations and develop an efficient optimization algorithm to compute WIF. We demonstrate the advantage of WIF in accurately quantifying imaging artifacts in high-density reconstruction of a tubulin network. WIF represents an advance in quantifying systematic errors with unknown and complex distributions, …

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A Computationally-Efficient Bound For The Variance Of Measuring The Orientation Of Single Molecules, Tingting Wu, Tianben Ding, Hesam Mazidi, Oumeng Zhang, Matthew D. Lew Feb 2020

A Computationally-Efficient Bound For The Variance Of Measuring The Orientation Of Single Molecules, Tingting Wu, Tianben Ding, Hesam Mazidi, Oumeng Zhang, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

Modulating the polarization of excitation light, resolving the polarization of emitted fluorescence, and point spread function (PSF) engineering have been widely leveraged for measuring the orientation of single molecules. Typically, the performance of these techniques is optimized and quantified using the Cramér-Rao bound (CRB), which describes the best possible measurement variance of an unbiased estimator. However, CRB is a local measure and requires exhaustive sampling across the measurement space to fully characterize measurement precision. We develop a global variance upper bound (VUB) for fast quantification and comparison of orientation measurement techniques. Our VUB tightly bounds the diagonal elements of the …

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Wireless Underground Communications In Sewer And Stormwater Overflow Monitoring: Radio Waves Through Soil And Asphalt Medium, Usman Raza, Abdul Salam Feb 2020

Wireless Underground Communications In Sewer And Stormwater Overflow Monitoring: Radio Waves Through Soil And Asphalt Medium, Usman Raza, Abdul Salam

Faculty Publications

Storm drains and sanitary sewers are prone to backups and overflows due to extra amount wastewater entering the pipes. To prevent that, it is imperative to efficiently monitor the urban underground infrastructure. The combination of sensors system and wireless underground communication system can be used to realize urban underground IoT applications, e.g., storm water and wastewater overflow monitoring systems. The aim of this article is to establish a feasibility of the use of wireless underground communications techniques, and wave propagation through the subsurface soil and asphalt layers, in an underground pavement system for storm water and sewer overflow monitoring application. …

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In-Situ Gold-Ceria Nanoparticles: Superior Optical Fluorescence Quenching Sensor For Dissolved Oxygen, Nader Shehata, Ishac Kandas, Effat Samir Feb 2020

In-Situ Gold-Ceria Nanoparticles: Superior Optical Fluorescence Quenching Sensor For Dissolved Oxygen, Nader Shehata, Ishac Kandas, Effat Samir

Electrical & Computer Engineering Faculty Publications

Cerium oxide (ceria) nanoparticles (NPs) have been proved to be an efficient optical fluorescent material through generating visible emission (~530 nm) under violet excitation. This feature allowed ceria NPs to be used as an optical sensor via the fluorescence quenching Technique. In this paper, the impact of in-situ embedded gold nanoparticles (Au NPs) inside ceria nanoparticles was studied. Then, gold–ceria NPs were used for sensing dissolved oxygen (DO) in aqueous media. It was observed that both fluorescence intensity and lifetime were changed due to increased concentration of DO. Added gold was found to enhance the sensitivity of ceria to DO …

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Deep Learning For Load Forecasting With Smart Meter Data: Online Adaptive Recurrent Neural Network, Mohammad Navid Fekri, Harsh Patel, Katarina Grolinger, Vinay Sharma Jan 2020

Deep Learning For Load Forecasting With Smart Meter Data: Online Adaptive Recurrent Neural Network, Mohammad Navid Fekri, Harsh Patel, Katarina Grolinger, Vinay Sharma

Electrical and Computer Engineering Publications

No abstract provided.

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Power-Over-Tether Uas Leveraged For Nearly Indefinite Meteorological Data Acquisition In The Platte River Basin, Daniel Rico, Carrick Detweiler, Francisco Munoz-Arriola Jan 2020

Power-Over-Tether Uas Leveraged For Nearly Indefinite Meteorological Data Acquisition In The Platte River Basin, Daniel Rico, Carrick Detweiler, Francisco Munoz-Arriola

CSE Conference and Workshop Papers

The integration of unmanned aerial systems (UASs) has increased in the field of agriculture. These systems can provide data that was previously difficult to obtain to help increase efficiency and production. Typical commercial off the shelf (COTS) UASs have significant limitations in the form of small payloads, and short flight times which inhibit their ability to provide significant quantities of useful data. We present the development of a novel power-over-tether UAS that leverages the physical presence of the tether to integrate sensors at multiple altitudes along the tether. The UAS can acquire data nearly indefinitely to sense atmospheric conditions and …

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Edge-Cloud Computing For Iot Data Analytics: Embedding Intelligence In The Edge With Deep Learning, Ananda Mohon M. Ghosh, Katarina Grolinger Jan 2020

Edge-Cloud Computing For Iot Data Analytics: Embedding Intelligence In The Edge With Deep Learning, Ananda Mohon M. Ghosh, Katarina Grolinger

Electrical and Computer Engineering Publications

Rapid growth in numbers of connected devices including sensors, mobile, wearable, and other Internet of Things (IoT) devices, is creating an explosion of data that are moving across the network. To carry out machine learning (ML), IoT data are typically transferred to the cloud or another centralized system for storage and processing; however, this causes latencies and increases network traffic. Edge computing has the potential to remedy those issues by moving computation closer to the network edge and data sources. On the other hand, edge computing is limited in terms of computational power and thus is not well suited for …

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Dual-Axis Solar Tracker, Bryan Kennedy Jan 2020

Dual-Axis Solar Tracker, Bryan Kennedy

All Undergraduate Projects

Renewable energies, and fuels that are not fossil fuel-based, are one of the prolific topics of debate in modern society. With climate change now becoming a primary focus for scientists and innovators of today, one of the areas for the largest amount of potential and growth is that of the capturing and utilization of Solar Energy. This method involves using a mechanical system to track the progression of the sun as it traverses the sky throughout the day. A dual-axis solar tracker such as the one designed and built for this project, can follow the sun both azimuthally and in …

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Improved Contacts And Device Performance In Mos2 Transistors Using 2d Semiconductor Interlayers, Kraig Andrews Jan 2020

Improved Contacts And Device Performance In Mos2 Transistors Using 2d Semiconductor Interlayers, Kraig Andrews

Wayne State University Dissertations

The rapid growth of modern electronics industry over the past half-century has been sustained by the continued miniaturization of silicon-based electronics. However, as fundamental limits approach, there is a need to search for viable alternative materials for next-generation electronics in the post-silicon era. Two-dimensional (2D) semiconductors such as transition metal dichalcogenides (TMDs) have attracted much attention due to their atomic thickness, absence of dangling bonds and moderately high carrier mobility. However, achieving low-resistance contacts has been major impediment in developing high-performance field-effect transistors (FETs) based on 2D semiconductors. A substantial Schottky barrier (SB) is often present at the metal/2D-semicondcutor interface, …

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Coverage Guided Differential Adversarial Testing Of Deep Learning Systems, Jianmin Guo, Houbing Song, Yue Zhao, Yu Jiang Jan 2020

Coverage Guided Differential Adversarial Testing Of Deep Learning Systems, Jianmin Guo, Houbing Song, Yue Zhao, Yu Jiang

Publications

Deep learning is increasingly applied to safety-critical application domains such as autonomous cars and medical devices. It is of significant importance to ensure their reliability and robustness. In this paper, we propose DLFuzz, the coverage guided differential adversarial testing framework to guide deep learing systems exposing incorrect behaviors. DLFuzz keeps minutely mutating the input to maximize the neuron coverage and the prediction difference between the original input and the mutated input, without manual labeling effort or cross-referencing oracles from other systems with the same functionality. We also design multiple novel strategies for neuron selection to improve the neuron coverage. The …

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Photovoltage Enhancement For Stable Perovskite Solar Cells With A Temperature-Controlled Grain Growth Technique, Luis Eduardo Valerio Jan 2020

Photovoltage Enhancement For Stable Perovskite Solar Cells With A Temperature-Controlled Grain Growth Technique, Luis Eduardo Valerio

Open Access Theses & Dissertations

By performing strong characterizations methods, one can begin to fully understand the chemistry and composition behind a great performing perovskite solar cell. Understanding how the interaction between layers inside a solar cell is driven by the temperature and overall environment is a key element to improve the fabrication process and overall efficiency of such cells. This Thesis will present a study of the hybrid organic-inorganic, mixed-cation, mixed-halide, temperature and thickness-controlled perovskite solar cell. A constant power conversion efficiency (PCE) ranging between 15-17% and an open circuit voltage V¬oc above 1.05 V for a wide-band gap perovskite cell is presented.

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Design, Construction, And Characterization Of A Combined Mini-Co₂/Voc Sensor And Gas Chromatograph For Field Research, Rishi Basdeo, Michael Hampton Jan 2020

Design, Construction, And Characterization Of A Combined Mini-Co₂/Voc Sensor And Gas Chromatograph For Field Research, Rishi Basdeo, Michael Hampton

Digital Repository: Showcase of Undergraduate Research Excellence

No abstract provided.

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Independent And Simultaneous Control Of Electromagnetic Wave Properties In Self-Collimating Photonic Crystals Using Spatial Variance, Jesus Javier Gutierrez Jan 2020

Independent And Simultaneous Control Of Electromagnetic Wave Properties In Self-Collimating Photonic Crystals Using Spatial Variance, Jesus Javier Gutierrez

Open Access Theses & Dissertations

Photonic crystals are engineered periodic structures that provide great control over electromagnetic waves. One of these mechanisms is self-collimation, in which the electromagnetic wave travels through the photonic crystal along an axis of the lattice without diffracting or spreading. This mechanism of self-collimation is a dispersion phenomenon, which is dependent on the unit cell's physical and geometrical characteristics. An algorithm for generating spatially variant lattices (SVL) was developed that can change geometrical properties in photonic crystals as a function of position, like unit cell orientation, fill fraction, symmetry, and others in a manner that is smooth, continuous, and virtually free …

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Fault Identification On Electrical Transmission Lines Using Artificial Neural Networks, Christopher W. Asbery Jan 2020

Fault Identification On Electrical Transmission Lines Using Artificial Neural Networks, Christopher W. Asbery

Theses and Dissertations--Electrical and Computer Engineering

Transmission lines are designed to transport large amounts of electrical power from the point of generation to the point of consumption. Since transmission lines are built to span over long distances, they are frequently exposed to many different situations that can cause abnormal conditions known as electrical faults. Electrical faults, when isolated, can cripple the transmission system as power flows are directed around these faults therefore leading to other numerous potential issues such as thermal and voltage violations, customer interruptions, or cascading events. When faults occur, protection systems installed near the faulted transmission lines will isolate these faults from the …

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Optimizing Cluster Sets For The Scan Statistic Using Local Search, James Shulgan Jan 2020

Optimizing Cluster Sets For The Scan Statistic Using Local Search, James Shulgan

Graduate Research Theses & Dissertations

In recent years, scattering sensors to produce wireless sensor networks (WSN) has been proposed for detecting localized events in large areas. Because sensor measurements are noisy, the WSN needs to use statistical methods such as the scan statistic. The scan statistic groups measurements into various clusters, computes a cluster statistic for each cluster, and decides that an event has happened if any of the statistics exceeds a threshold. Previous researchers have investigated the performance of the scan statistic to detect events; however, little attention was given to the optimization of which clusters the scan statistic should use. Using the scan …

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Dynamic Allocation/Reallocation Of Dark Cores In Many-Core Systems For Improved System Performance, Xingxing Huang, Xiaohang Wang, Yingtao Jiang, Amit Kumar Singh, Mei Yang Jan 2020

Dynamic Allocation/Reallocation Of Dark Cores In Many-Core Systems For Improved System Performance, Xingxing Huang, Xiaohang Wang, Yingtao Jiang, Amit Kumar Singh, Mei Yang

Electrical & Computer Engineering Faculty Research

A significant number of processing cores in any many-core systems nowadays and likely in the future have to be switched off or forced to be idle to become dark cores, in light of ever increasing power density and chip temperature. Although these dark cores cannot make direct contributions to the chip's throughput, they can still be allocated to applications currently running in the system for the sole purpose of heat dissipation enabled by the temperature gradient between the active and dark cores. However, allocating dark cores to applications tends to add extra waiting time to applications yet to be launched, …

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Optimal Design Of A Flux Reversal Permanent Magnet Machine As A Wind Turbinegenerator, Majid Ghasemian, Farzad Tahami, Zahra Nasiri-Gheidari Jan 2020

Optimal Design Of A Flux Reversal Permanent Magnet Machine As A Wind Turbinegenerator, Majid Ghasemian, Farzad Tahami, Zahra Nasiri-Gheidari

Turkish Journal of Electrical Engineering and Computer Sciences

Flux reversal permanent magnet generators are well suited for use as wind turbine generators owing to their high torque generation ability and magnetic gear. However, they suffer from poor voltage regulation due to their high winding inductance. In this paper, a design optimization method is proposed for flux reversal generators in wind turbine applications. The proposed method includes a new multiobjective function. Cost, volume of the generator, and mass of the permanent magnet are considered in it independently and simultaneously. Besides the new objective function, the main superiority of this paper compared with published papers is considering winding inductance in …

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Nonlocal Means Estimation Of Intrinsic Mode Functions For Speech Enhancement, Sagar Reddy Vumanthala, Bikshalu K Jan 2020

Nonlocal Means Estimation Of Intrinsic Mode Functions For Speech Enhancement, Sagar Reddy Vumanthala, Bikshalu K

Turkish Journal of Electrical Engineering and Computer Sciences

The main aim of this paper is to introduce a new approach to enhance speech signals by exploring the advantages of nonlocal means (NLM) estimation and empirical mode decomposition. NLM, a patch-based denoising method, is extensively used for two-dimensional signals like images. However, its use for one-dimensional signals has been attracting more attention recently. The NLM-based approach is quite useful for removing low-frequency noises based on nonlocal similarities present among samples of the signal. However, there is an issue of under averaging in the high-frequency regions. The temporal and spectral characteristics of the speech signal are changing markedly over time. …

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Multiplicative-Additive Despeckling In Sar Images, Gülay Aksoy, Fati̇h Nar Jan 2020

Multiplicative-Additive Despeckling In Sar Images, Gülay Aksoy, Fati̇h Nar

Turkish Journal of Electrical Engineering and Computer Sciences

Visual and automatic analyses using synthetic aperture radar (SAR) images are challenging because of inherently formed speckle noise. Thus, reducing speckle noise in SAR images is an important research area for SAR image analysis. During speckle noise reduction, homogeneous regions should be smoothed while details such as edges and point scatterers need to be preserved. General speckle noise model contains gamma distributed multiplicative part which is dominant and Gaussian distributed additive part which is in low amount and mostly neglected in literature. In this study, a novel sparsity-driven speckle reduction method is proposed that takes both multiplicative noise model and …

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Detection Of Bga Solder Defects From X-Ray Images Using Deep Neural Network, Ceren Türer Akdeni̇z, Zümray Ölmez, Tamer Ölmez Jan 2020

Detection Of Bga Solder Defects From X-Ray Images Using Deep Neural Network, Ceren Türer Akdeni̇z, Zümray Ölmez, Tamer Ölmez

Turkish Journal of Electrical Engineering and Computer Sciences

In the literature it is observed that complex image processing operations are used in the classification of Ball Grid Array (BGA) X-ray images, however high classification results were not achieved. In recent years, it has been shown that deep learning methods are very successful especially in classification problems. In this study, a new deep neural network (DNN) model is proposed to classify the BGA X-ray images. The proposed DNN model contains feature extractor layers and a minimum distance classifier. Since the proposed network consists of less number of layers (4 convolution layers and 1 fully connected layer), determination of the …

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Connectivity Considerations For Mission Planning Of A Search And Rescue Drone Team, Evşen Yanmaz Adam Jan 2020

Connectivity Considerations For Mission Planning Of A Search And Rescue Drone Team, Evşen Yanmaz Adam

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we analyze the mission success performance and mission times of centralized, distributed, and hybrid path-planning methods for a drone team whose mission is to find a target and inform the ground control. We propose two methods that integrate connectivity into the search mission path decisions. We observe that even though the coverage path-planning leads to lower search times, when target connectivity is also required, schemes that incorporate end--end connectivity into path planning result in at least 50 % better mission times for small communication ranges and lower number of drones. Our results also indicate that methods to …

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