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Electrical and Computer Engineering

2020

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Articles 61 - 76 of 76

Full-Text Articles in Physics

Flux Expulsion In Niobium Superconducting Radio-Frequency Cavities Of Different Purity And Essential Contributions To The Flux Sensitivity, P. Dhakal, Gianluigi Ciovati, Alex Gurevich Jan 2020

Flux Expulsion In Niobium Superconducting Radio-Frequency Cavities Of Different Purity And Essential Contributions To The Flux Sensitivity, P. Dhakal, Gianluigi Ciovati, Alex Gurevich

Physics Faculty Publications

Magnetic flux trapped during the cooldown of superconducting radio-frequency cavities through the transition temperature due to incomplete Meissner state is known to be a significant source of radio-frequency losses. The sensitivity of flux trapping depends on the distribution and the type of defects and impurities which pin vortices, as well as the cooldown dynamics when the cavity transitions from a normal to superconducting state. Here we present the results of measurements of the flux trapping sensitivity on 1.3 GHz elliptical cavities made from large-grain niobium with different purity for different cooldown dynamics and surface treatments. The results show that lower …

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High-Fidelity Mini-Led And Micro-Led Displays, Yuge Huang Jan 2020

High-Fidelity Mini-Led And Micro-Led Displays, Yuge Huang

Electronic Theses and Dissertations, 2020-

Mini-LED and micro-LED are emerging disruptive display technologies, because they can work as local dimmable backlight to significantly enhance the dynamic range of conventional LCDs, or as sunlight readable emissive displays. However, there are still unresolved issues impairing their display fidelity: 1) motion blur on high-resolution, large-size and high-luminance devices, 2) limited contrast ratio on mini-LED backlit LCD (mLED-LCD), 3) relatively high power consumption, and 4) compromised ambient contrast ratio. This dissertation tackles with each of these issues for achieving high display fidelity. Motion blur is caused by slow liquid crystal response time and image update delays. Low-duty ratio operation …

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Multi-Parameter Optical Metrology: Quantum And Classical, Walker Larson Jan 2020

Multi-Parameter Optical Metrology: Quantum And Classical, Walker Larson

Electronic Theses and Dissertations, 2020-

The insights offered by quantum mechanics to the field of optical metrology are many-fold, with non-classical states of light themselves used to make sensors that surpass the sensitivity of sensors using classical states of light. Unfortunately, this advantage, referred to often as "super-sensitivity" is notoriously fragile, and even the slightest experimental imperfections may greatly reduce the efficacy of the non-classical sensors, sometimes completely obviating their advantage. In my thesis I have shown that the performance of an otherwise ideal two-photon interferometer, which exploits entanglement between photons to make super-sensitive measurements of phase, is crippled by the slightest introduction of decoherence …

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Fluorescence Microscopy With Tailored Illumination Light, Jialei Tang Jan 2020

Fluorescence Microscopy With Tailored Illumination Light, Jialei Tang

Electronic Theses and Dissertations, 2020-

Fluorescence microscopy has long been a valuable tool for biological and medical imaging. Control of optical parameters such as the amplitude, phase, polarization and propagation angle of light gives fluorescence imaging great capabilities ranging from single molecule imaging to long-term observation of living organisms. While numerous fluorescence imaging techniques have been developed over the past decades, there is always an inevitable tradeoff among the spatial resolution, imaging speed, contrast, photodamage and the total cost when it comes to choose the appropriate microscope. A main goal of my dissertation research is to develop state-of-the-art microscope systems that exhibit unprecedented performance in …

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Transient Mid-Ir Nonlinear Refraction In Air And Nonlinear Optical Properties Of Organometallic Complexes, Salimeh Tofighi Jan 2020

Transient Mid-Ir Nonlinear Refraction In Air And Nonlinear Optical Properties Of Organometallic Complexes, Salimeh Tofighi

Electronic Theses and Dissertations, 2020-

This dissertation explores two main topics: Transient nonlinear refraction of air in Mid-IR spectral range and nonlinear optical properties of organometallic complexes. For seeing a vibrational and rotational Raman response the molecule should be Raman active. The first requirement for being a Raman active molecule is that the polarizability of molecule must be anisotropic. Linear symmetric molecules do have rotational Raman spectra. Not all the vibrational mode can be excited by a femtosecond pulse. The pulsewidth of our excitation beam should be less than the half of the vibration period. In this dissertation my excitation pulsewidth is not short enough …

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Developing A Uas-Deployable Methane Sensor Using Low-Cost Modular Open-Source Components, Gavin Demali Jan 2020

Developing A Uas-Deployable Methane Sensor Using Low-Cost Modular Open-Source Components, Gavin Demali

Williams Honors College, Honors Research Projects

This project aimed to develop a methane sensor for deployment on an unmanned aerial system (UAS), or drone, platform. This design is centered around low cost, commercially available modular hardware components and open source software libraries. Once successfully developed, this system was deployed at the Bath Nature Preserve in Bath Township, Summit County Ohio in order to detect any potential on site fugitive methane emissions in the vicinity of the oil and gas infrastructure present. The deliverables of this project (i.e. the data collected at BNP) will be given to the land managers there to better inform future management and …

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Superconducting Phase Transition In Inhomogeneous Chains Of Superconducting Islands, Eduard Ilin, Irina Burkova, Xiangyu Song, Michael Pak, Dmitri S. Golubev, Alexey Bezryadin Jan 2020

Superconducting Phase Transition In Inhomogeneous Chains Of Superconducting Islands, Eduard Ilin, Irina Burkova, Xiangyu Song, Michael Pak, Dmitri S. Golubev, Alexey Bezryadin

Faculty Publications

We study one-dimensional chains of superconducting islands with a particular emphasis on the regime in which every second island is switched into its normal state, thus forming a superconductor-insulator-normal metal (S-I-N) repetition pattern. As is known since Giaever tunneling experiments, tunneling charge transport between a superconductor and a normal metal becomes exponentially suppressed, and zero-bias resistance diverges, as the temperature is reduced and the energy gap of the superconductor grows larger than the thermal energy. Here we demonstrate that this physical phenomenon strongly impacts transport properties of inhomogeneous superconductors made of weakly coupled islands with fluctuating values of the critical …

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Special Section Guest Editorial: Machine Learning In Optics, Jonathan Howe, Travis Axtell, Khan Iftekharuddin Jan 2020

Special Section Guest Editorial: Machine Learning In Optics, Jonathan Howe, Travis Axtell, Khan Iftekharuddin

Electrical & Computer Engineering Faculty Publications

This guest editorial summarizes the Special Section on Machine Learning in Optics.

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Gold/Qds-Embedded-Ceria Nanoparticles: Optical Fluorescence Enhancement As A Quenching Sensor, Nader Shehata, Effat Samir, Ishac Kandas Jan 2020

Gold/Qds-Embedded-Ceria Nanoparticles: Optical Fluorescence Enhancement As A Quenching Sensor, Nader Shehata, Effat Samir, Ishac Kandas

Electrical & Computer Engineering Faculty Publications

This work focuses on improving the fluorescence intensity of cerium oxide (ceria) nanoparticles (NPs) through added plasmonic nanostructures. Ceria nanoparticles are fluorescent nanostructures which can emit visible fluorescence emissions under violet excitation. Here, we investigated different added plasmonic nanostructures, such as gold nanoparticles (Au NPs) and Cadmium sulfide/selenide quantum dots (CdS/CdSe QDs), to check the enhancement of fluorescence intensity emissions caused by ceria NPs. Different plasmonic resonances of both aforementioned nanostructures have been selected to develop optical coupling with both fluorescence excitation and emission wavelengths of ceria. In addition, different additions whether in-situ or post-synthesis have been investigated. We found …

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Thermoelectric Porous Mof Based Hybrid Materials, Engelbert Redel, Helmut Baumgart Jan 2020

Thermoelectric Porous Mof Based Hybrid Materials, Engelbert Redel, Helmut Baumgart

Electrical & Computer Engineering Faculty Publications

Porous hybrid materials and MOF (Metal-Organic-Framework) films represent modern designer materials that exhibit many requirements of a near ideal and tunable future thermoelectric (TE) material. In contrast to traditional semiconducting bulk TE materials, porous hybrid MOF templates can be used to overcome some of the constraints of physics in bulk TE materials. These porous hybrid systems are amenable for simulation and modeling to design novel optimized electron-crystal phonon-glass materials with potentially very high ZT (figure of merit) numbers. Porous MOF and hybrid materials possess an ultra-low thermal conductivity, which can be further modulated by phonon engineering within their complex porous …

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Superconducting Radio-Frequency Cavity Fault Classification Using Machine Learning At Jefferson Laboratory, Chris Tennant, Adam Carpenter, Tom Powers, Anna Shabalina Solopova, Lasitha Vidyaratne, Khan Iftekharuddin Jan 2020

Superconducting Radio-Frequency Cavity Fault Classification Using Machine Learning At Jefferson Laboratory, Chris Tennant, Adam Carpenter, Tom Powers, Anna Shabalina Solopova, Lasitha Vidyaratne, Khan Iftekharuddin

Electrical & Computer Engineering Faculty Publications

We report on the development of machine learning models for classifying C100 superconducting radio-frequency (SRF) cavity faults in the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. CEBAF is a continuous-wave recirculating linac utilizing 418 SRF cavities to accelerate electrons up to 12 GeV through five passes. Of these, 96 cavities (12 cryomodules) are designed with a digital low-level rf system configured such that a cavity fault triggers waveform recordings of 17 rf signals for each of the eight cavities in the cryomodule. Subject matter experts are able to analyze the collected time-series data and identify which of the …

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Ensemble Lung Segmentation System Using Deep Neural Networks, Redha A. Ali, Russell C. Hardie, Hussin K. Ragb Jan 2020

Ensemble Lung Segmentation System Using Deep Neural Networks, Redha A. Ali, Russell C. Hardie, Hussin K. Ragb

Electrical and Computer Engineering Faculty Publications

Lung segmentation is a significant step in developing computer-aided diagnosis (CAD) using Chest Radiographs (CRs). CRs are used for diagnosis of the 2019 novel coronavirus disease (COVID-19), lung cancer, tuberculosis, and pneumonia. Hence, developing a Computer-Aided Detection (CAD) system would provide a second opinion to help radiologists in the reading process, increase objectivity, and reduce the workload. In this paper, we present the implementation of our ensemble deep learning model for lung segmentation. This model is based on the original DeepLabV3+, which is the extended model of DeepLabV3. Our model utilizes various architectures as a backbone of DeepLabV3+, such as …

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Corrections To ‘‘Glaciernet: A Deep-Learning Approach For Debris-Covered Glacier Mapping’’, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Brennan W. Young, Michael P. Bishop, Jeffrey S. Kargel Jan 2020

Corrections To ‘‘Glaciernet: A Deep-Learning Approach For Debris-Covered Glacier Mapping’’, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Brennan W. Young, Michael P. Bishop, Jeffrey S. Kargel

Electrical and Computer Engineering Faculty Publications

In the above article [1], Figure 2 was incorrect. Unfortunately, we mixed the color label of "CONV $\to $ BN $\to $ ReLu" and "Unpooling" in the CNN structure section of Figure 2. The color label of "CONV $\to $ BN $\to $ ReLu" should be orange while the color label of "Unpooling" should be green. Also, the word "Decoder" is misspelled. That same figure with the same error is also used for the graphic abstract. The corrected figure is given here. None of the sections in the figure is modified. The only change is in the color label of …

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Mitosisnet: End-To-End Mitotic Cell Detection By Multi-Task Learning, Md Zahangir Alom, Theus Aspiras, Tarek M. Taha, Tj Bowen, Vijayan K. Asari Jan 2020

Mitosisnet: End-To-End Mitotic Cell Detection By Multi-Task Learning, Md Zahangir Alom, Theus Aspiras, Tarek M. Taha, Tj Bowen, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

Mitotic cell detection is one of the challenging problems in the field of computational pathology. Currently, mitotic cell detection and counting are one of the strongest prognostic markers for breast cancer diagnosis. The clinical visual inspection on histology slides is tedious, error prone, and time consuming for the pathologist. Thus, automatic mitotic cell detection approaches are highly demanded in clinical practice. In this paper, we propose an end-to-end multi-task learning system for mitosis detection from pathological images which is named"MitosisNet". MitosisNet consist of segmentation, detection, and classification models where the segmentation, and detection models are used for mitosis reference region …

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Glaciernet: A Deep-Learning Approach For Debris-Covered Glacier Mapping, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Brennan W. Young, Michael P. Bishop, Jeffrey S. Kargel Jan 2020

Glaciernet: A Deep-Learning Approach For Debris-Covered Glacier Mapping, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Brennan W. Young, Michael P. Bishop, Jeffrey S. Kargel

Electrical and Computer Engineering Faculty Publications

Rising global temperatures over the past decades is directly affecting glacier dynamics. To understand glacier fluctuations and document regional glacier-state trends, glacier-boundary detection is necessary. Debris-covered glacier (DCG) mapping, however, is notoriously difficult using conventional geospatial technology methods. Therefore, in this research for automated DCG mapping, we evaluate the utility of a convolutional neural network (CNN), which is a deep learning feed-forward neural network. The CNN inputs include Landsat satellite images, an Advanced Land Observation Satellite (ALOS) digital elevation model (DEM) and DEM-derived land-surface parameters. Our CNN based deep-learning approach named GlacierNet was designed by appropriately choosing the type, number …

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Ev Charging Behavior Analysis Using Hybrid Intelligence For 5g Smart Grid, Yi Shen, Wei Fang, Feng Ye, Michel Kadoch Jan 2020

Ev Charging Behavior Analysis Using Hybrid Intelligence For 5g Smart Grid, Yi Shen, Wei Fang, Feng Ye, Michel Kadoch

Electrical and Computer Engineering Faculty Publications

With the development of the Internet of Things (IoT) and the widespread use of electric vehicles (EV), vehicle-to-grid (V2G) has sparked considerable discussion as an energy-management technology. Due to the inherently high maneuverability of EVs, V2G systems must provide on-demand service for EVs. Therefore, in this work, we propose a hybrid computing architecture based on fog and cloud with applications in 5G-based V2G networks. This architecture allows the bi-directional flow of power and information between schedulable EVs and smart grids (SGs) to improve the quality of service and cost-effectiveness of energy service providers. However, it is very important to select …

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