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Articles 38221 - 38250 of 302474
Full-Text Articles in Physical Sciences and Mathematics
Completing Single-Cell Dna Methylome Profiles Via Transfer Learning Together With Kl-Divergence, Sanjeeva Dodlapati, Zongliang Jiang, Jiangwen Sun
Completing Single-Cell Dna Methylome Profiles Via Transfer Learning Together With Kl-Divergence, Sanjeeva Dodlapati, Zongliang Jiang, Jiangwen Sun
Computer Science Faculty Publications
The high level of sparsity in methylome profiles obtained using whole-genome bisulfite sequencing in the case of low biological material amount limits its value in the study of systems in which large samples are difficult to assemble, such as mammalian preimplantation embryonic development. The recently developed computational methods for addressing the sparsity by imputing missing have their limits when the required minimum data coverage or profiles of the same tissue in other modalities are not available. In this study, we explored the use of transfer learning together with Kullback-Leibler (KL) divergence to train predictive models for completing methylome profiles with …
Visual Descriptor Extraction From Patent Figure Captions: A Case Study Of Data Efficiency Between Bilstm And Transformer, Xin Wei, Jian Wu, Kehinde Ajayi, Diane Oyen
Visual Descriptor Extraction From Patent Figure Captions: A Case Study Of Data Efficiency Between Bilstm And Transformer, Xin Wei, Jian Wu, Kehinde Ajayi, Diane Oyen
Computer Science Faculty Publications
Technical drawings used for illustrating designs are ubiquitous in patent documents, especially design patents. Different from natural images, these drawings are usually made using black strokes with little color information, making it challenging for models trained on natural images to recognize objects. To facilitate indexing and searching, we propose an effective and efficient visual descriptor model that extracts object names and aspects from patent captions to annotate benchmark patent figure datasets. We compared two state-of-the-art named entity recognition (NER) models and found that with a limited number of annotated samples, the BiLSTM-CRF model outperforms the Transformer model by a significant …
Customer Gaze Estimation In Retail Using Deep Learning, Shashimal Senarath, Primesh Pathirana, Dulani Meedeniya, Sampath Jayarathna
Customer Gaze Estimation In Retail Using Deep Learning, Shashimal Senarath, Primesh Pathirana, Dulani Meedeniya, Sampath Jayarathna
Computer Science Faculty Publications
At present, intelligent computing applications are widely used in different domains, including retail stores. The analysis of customer behaviour has become crucial for the benefit of both customers and retailers. In this regard, the concept of remote gaze estimation using deep learning has shown promising results in analyzing customer behaviour in retail due to its scalability, robustness, low cost, and uninterrupted nature. This study presents a three-stage, three-attention-based deep convolutional neural network for remote gaze estimation in retail using image data. In the first stage, we design a mechanism to estimate the 3D gaze of the subject using image data …
D-Lib Magazine Pioneered Web-Based Scholarly Communication, Michael L. Nelson, Herbert Van De Sompel
D-Lib Magazine Pioneered Web-Based Scholarly Communication, Michael L. Nelson, Herbert Van De Sompel
Computer Science Faculty Publications
The web began with a vision of, as stated by Tim Berners-Lee in 1991, “that much academic information should be freely available to anyone”. For many years, the development of the web and the development of digital libraries and other scholarly communications infrastructure proceeded in tandem. A milestone occurred in July, 1995, when the first issue of D-Lib Magazine was published as an online, HTML-only, open access magazine, serving as the focal point for the then emerging digital library research community. In 2017 it ceased publication, in part due to the maturity of the community it served as well as …
Machine Learning-Based Event Generator For Electron-Proton Scattering, Y. Alanazi, P. Ambrozewicz, M. Battaglieri, A.N. Hiller Blin, M. P. Kuchera, Y. Li, T. Liu, R. E. Mcclellan, W. Melnitchouk, E. Pritchard, M. Robertson, N. Sato, R. Strauss, L. Velasco
Machine Learning-Based Event Generator For Electron-Proton Scattering, Y. Alanazi, P. Ambrozewicz, M. Battaglieri, A.N. Hiller Blin, M. P. Kuchera, Y. Li, T. Liu, R. E. Mcclellan, W. Melnitchouk, E. Pritchard, M. Robertson, N. Sato, R. Strauss, L. Velasco
Computer Science Faculty Publications
We present a new machine learning-based Monte Carlo event generator using generative adversarial networks (GANs) that can be trained with calibrated detector simulations to construct a vertex-level event generator free of theoretical assumptions about femtometer scale physics. Our framework includes a GAN-based detector folding as a fast-surrogate model that mimics detector simulators. The framework is tested and validated on simulated inclusive deep-inelastic scattering data along with existing parametrizations for detector simulation, with uncertainty quantification based on a statistical bootstrapping technique. Our results provide for the first time a realistic proof of concept to mitigate theory bias in inferring vertex-level event …
Toward A Real-Time Index Of Pupillary Activity As An Indicator Of Cognitive Load, Gavindya Jayawardena, Yasith Jayawardana, Sampath Jayarathna, Jonas Högström, Thomas Papa, Deepak Akkil, Andrew T. Duchowski, Vsevolod Peysakhovich, Izabela Krejtz, Nina Gehrer, Krzysztof Krejtz
Toward A Real-Time Index Of Pupillary Activity As An Indicator Of Cognitive Load, Gavindya Jayawardena, Yasith Jayawardana, Sampath Jayarathna, Jonas Högström, Thomas Papa, Deepak Akkil, Andrew T. Duchowski, Vsevolod Peysakhovich, Izabela Krejtz, Nina Gehrer, Krzysztof Krejtz
Computer Science Faculty Publications
The Low/High Index of Pupillary Activity (LHIPA), an eye-tracked measure of pupil diameter oscillation, is redesigned and implemented to function in real-time. The novel Real-time IPA (RIPA) is shown to discriminate cognitive load in re-streamed data from earlier experiments. Rationale for the RIPA is tied to the functioning of the human autonomic nervous system yielding a hybrid measure based on the ratio of Low/High frequencies of pupil oscillation. The paper's contribution is drawn from provision of documentation of the calculation of the RIPA. As with the LHIPA, it is possible for researchers to apply this metric to their own experiments …
Ready Raider One: Exploring The Misuse Of Cloud Gaming Services, Guannan Liu, Daiping Liu, Shuai Hao, Xing Gao, Kun Sun, Haining Wang
Ready Raider One: Exploring The Misuse Of Cloud Gaming Services, Guannan Liu, Daiping Liu, Shuai Hao, Xing Gao, Kun Sun, Haining Wang
Computer Science Faculty Publications
Cloud gaming has become an emerging computing paradigm in recent years, allowing computer games to offload complex graphics and logic computation to the cloud. To deliver a smooth and high-quality gaming experience, cloud gaming services have invested abundant computing resources in the cloud, including adequate CPUs, top-tier GPUs, and high-bandwidth Internet connections. Unfortunately, the abundant computing resources offered by cloud gaming are vulnerable to misuse and exploitation for malicious purposes. In this paper, we present an in-depth study on security vulnerabilities in cloud gaming services. Specifically, we reveal that adversaries can purposely inject malicious programs/URLs into the cloud gaming services …
Scholarly Big Data Quality Assessment: A Case Study Of Document Linking And Conflation With S2orc, Jian Wu, Ryan Hiltabrand, Dominik Soós, C. Lee Giles
Scholarly Big Data Quality Assessment: A Case Study Of Document Linking And Conflation With S2orc, Jian Wu, Ryan Hiltabrand, Dominik Soós, C. Lee Giles
Computer Science Faculty Publications
Recently, the Allen Institute for Artificial Intelligence released the Semantic Scholar Open Research Corpus (S2ORC), one of the largest open-access scholarly big datasets with more than 130 million scholarly paper records. S2ORC contains a significant portion of automatically generated metadata. The metadata quality could impact downstream tasks such as citation analysis, citation prediction, and link analysis. In this project, we assess the document linking quality and estimate the document conflation rate for the S2ORC dataset. Using semi-automatically curated ground truth corpora, we estimated that the overall document linking quality is high, with 92.6% of documents correctly linking to six major …
Edge Fueling And Neutral Density Studies Of The Alcator C-Mod Tokamak Using The Solps-Iter Code, Richard M. Reksoatmodjo
Edge Fueling And Neutral Density Studies Of The Alcator C-Mod Tokamak Using The Solps-Iter Code, Richard M. Reksoatmodjo
Dissertations, Theses, and Masters Projects
Understanding edge neutral dynamics in high-field tokamaks has strong consequencesfor both fueling and plasma profile predictions. We validate the ability of SOLPS-ITER, a 2D fluid plasma/kinetic Monte Carlo neutral code, to accurately model the upstream neutral density profiles of L-mode, I-mode, and H-mode discharges in the Alcator CMod tokamak, for which Lyman-alpha emission measurements were available. We achieve simulated Lyman-alpha emission and neutral density profiles that are within one standard deviation of empirically inferred profiles for all three discharges, via iterative tuning of the perpendicular transport coefficient profiles alone, providing confidence in the conclusion that while further physics (drifts, impurities, …
Exploring The Effects Of Microplastics On Marine Biota, Meredith Evans Seeley
Exploring The Effects Of Microplastics On Marine Biota, Meredith Evans Seeley
Dissertations, Theses, and Masters Projects
There is mounting evidence that microplastics are a persistent and increasing hazard for aquatic organisms. The effects of microplastics on organisms and ecosystems are complex, however, and may be linked to a wide variety of particle characteristics including size, shape, polymer, additive chemistry, and degree of weathering. Assessing risk is complicated by the fact that many known effects of microplastics are sublethal, and that plastics have been postulated to interact with other stressors, such as pathogens. The work presented here expands our understanding of these complex effects. First, the impacts of microplastics on sedimentary microbial ecosystems and biogeochemical carbon and …
Quantum Sensing For Low-Light Imaging, Savannah Cuozzo
Quantum Sensing For Low-Light Imaging, Savannah Cuozzo
Dissertations, Theses, and Masters Projects
In high-precision optical measurements, noise due to quantum fluctuations in the amplitude and phase of the probing field becomes the limiting factor in detection sensitivity. While this quantum noise is fundamental and not a result of detection, it is possible to engineer a quantum state that has reduced noise in either amplitude or phase (at the cost of increasing noise in the other) called a quadrature-squeezed state. In this dissertation, we study the use of quadrature-squeezed vacuum states for low-light imaging and develop a quantum detection method to measure the spatial dependence of the quantum noise using a camera instead …
Deep Learning From Space: Methods & Applications In High-Resolution Satellite Imagery Analysis, Ethan Brewer
Deep Learning From Space: Methods & Applications In High-Resolution Satellite Imagery Analysis, Ethan Brewer
Dissertations, Theses, and Masters Projects
Satellite imagery analysis using deep learning methods, specifically convolutional neural networks (CNNs), has grown in popularity since 2012, with uses extending into the estimation of population, wealth, poverty, conflict, migration, education, and infrastructure, among other applications. This dissertation contributes to this body of literature in three parts. First, I explore the use of deep learning to overcome the sparsity, or complete lack, of accurate information regarding existing road infrastructure across much of the world. Using a novel labeled dataset generated by a custom-coded Android application, I show that a transfer learning approach can estimate road quality based on high-resolution satellite …
Investigation Of Stripes, Spin Density Waves And Superconductivity In The Ground State Of The Two-Dimensional Hubbard Model, Hao Xu
Dissertations, Theses, and Masters Projects
The Hubbard model is a "paradigmatic" model in the realm of condensed matter physics. Recently a work with various state-or-art methods established the ground state stripe order near 1/8 doping and strong on-site interaction. Therefore, in this thesis, we determine the spin and charge order of ground state of 2D doped Hubbard model in its simplest form (with only on site repulsion and nearest-neighbor hoping) with various doping and small to medium interaction. At half-filling, the ground state is known to be an antiferromagnetic Mott insulator. Doping Mott insulators is believed to be relevant to the superconductivity observed in cuprates. …
Enabling Practical Evaluation Of Privacy Of Commodity-Iot, Sunil Manandhar
Enabling Practical Evaluation Of Privacy Of Commodity-Iot, Sunil Manandhar
Dissertations, Theses, and Masters Projects
There has been a massive shift towards the use of IoT products in recent years. While companies have come a long way in making these devices and services easily accessible to the consumers, very little is known about the privacy issues pertaining to these devices. In this dissertation, we focus on evaluating privacy pertaining to commodity-IoT devices by studying device usage behavior of consumers and privacy disclosure practices of IoT vendors. Our analyses consider deep intricacies tied to commodity-IoT domain, revealing insightful findings that help with building automated tools for a large scale analysis. We first present the design and …
Importance Of Muddy Bed Aggregate Processes In Cohesive Sediment Dynamics Associated With Sediment Management Projects, David Perkey
Importance Of Muddy Bed Aggregate Processes In Cohesive Sediment Dynamics Associated With Sediment Management Projects, David Perkey
Dissertations, Theses, and Masters Projects
The erosion and transport processes of fine sediment is largely impacted by the aggregation state. Understanding fine sediment transport processes is a key component to managing the nation’s navigation channels, ports, and reservoirs. To improve its ability to apply management strategies related to fine sediments, the USACE has undertaken research that focusses on the aggregation state of fine sediment. Of particular interest is the ability to expand the use of fine-grained sediment in projects that seek to beneficially use dredge material. In this study, a newly developed camera system was used to evaluate the aggregation state of eroded sediment from …
Physiological Condition And Recruitment Of Mytilus Edulis And Donax Variabilis On Virginia Barrier Islands, Taylor Walker
Physiological Condition And Recruitment Of Mytilus Edulis And Donax Variabilis On Virginia Barrier Islands, Taylor Walker
Dissertations, Theses, and Masters Projects
Climate change has caused gradual changes within marine environments within the last couple decades and is expected to continue to impact these ecosystems. Changes to these ecosystems are anticipated to emerge as adverse effects reach the lowest and highest levels within trophic food webs. For example, these environmental changes may change the abundance and distribution of species within their current geographic range. In extreme cases, climate change has already resulted in range shifts of terrestrial and marine species. A need for bioindicator species has emerged, so that they may be used to indicate when climate change may impact marine communities …
Communication And Computation Efficient Deep Learning, Zeyi Tao
Communication And Computation Efficient Deep Learning, Zeyi Tao
Dissertations, Theses, and Masters Projects
Recent advances in Artificial Intelligence (AI) are characterized by ever-increasing datasets and rapid growth of model complexity. Many modern machine learning models, especially deep neural networks (DNNs), cannot be efficiently carried out by a single machine. Hence, distributed optimization and inference have been widely adopted to tackle large-scale machine learning problems. Meanwhile, quantum computers that process computational tasks exponentially faster than classical machines offer an alternative solution for resource-intensive deep learning. However, there are two obstacles that hinder us from building large-scale DNNs on the distributed systems and quantum computers. First, when distributed systems scale to many nodes, the training …
Environmental Justice In The Elizabeth River Watershed: Exploring The Utility Of Environmental Justice Screening Tools, Julianna M. Ramirez
Environmental Justice In The Elizabeth River Watershed: Exploring The Utility Of Environmental Justice Screening Tools, Julianna M. Ramirez
Dissertations, Theses, and Masters Projects
The Environmental Justice (EJ) movement has long highlighted the disproportionate exposure to environmental hazards experienced by Black, Indigenous, People of Color (BIPOC) and low-income communities across the country. Environmental practitioners have recently focused on utilizing EJ screening tools, which combine environmental and social data to visualize vulnerable communities, to begin to address environmental injustice rampant in BIPOC and low-income communities. This project explores EJ theoretical frameworks and the historical context of social oppression and environmental pollution in the Elizabeth River watershed (ERW) of Virginia to: 1) understand the social, political, and economic context behind environmental injustice; and 2) generate goals …
Sediment Survey: Yr060822, Station 3916, Clay Bank, York River Virginia, Grace M. Massey, Patrick J. Dickhudt, Carl T. Friedrichs
Sediment Survey: Yr060822, Station 3916, Clay Bank, York River Virginia, Grace M. Massey, Patrick J. Dickhudt, Carl T. Friedrichs
Data
This dataset consists of sediment properties including grain size distribution, percent moisture, percent organic matter, sediment bed erodibility, as well as (in most cases) x-ray images of the sediment structure. Most samples were taken in support of an Acoustic Doppler Velocimeter (ADV) tripod deployed in nearby location.
Sediment Survey: Yr070523, Station 3939, Clay Bank, York River Virginia, Grace M. Massey, Patrick J. Dickhudt, Carl T. Friedrichs
Sediment Survey: Yr070523, Station 3939, Clay Bank, York River Virginia, Grace M. Massey, Patrick J. Dickhudt, Carl T. Friedrichs
Data
This dataset consists of sediment properties including grain size distribution, percent moisture, percent organic matter, sediment bed erodibility, as well as (in most cases) x-ray images of the sediment structure. Most samples were taken in support of an Acoustic Doppler Velocimeter (ADV) tripod deployed in nearby location.
Sediment Survey: Yr060925, Station 3918, Gloucester Point, York River Virginia, Grace M. Massey, Patrick J. Dickhudt, Carl T. Friedrichs
Sediment Survey: Yr060925, Station 3918, Gloucester Point, York River Virginia, Grace M. Massey, Patrick J. Dickhudt, Carl T. Friedrichs
Data
This dataset consists of sediment properties including grain size distribution, percent moisture, percent organic matter, sediment bed erodibility, as well as (in most cases) x-ray images of the sediment structure. Most samples were taken in support of an Acoustic Doppler Velocimeter (ADV) tripod deployed in nearby location.
Sediment Survey: Yr070810, Station 3945, Gloucester Point, York River Virginia, Grace M. Massey, Patrick J. Dickhudt, Carl T. Friedrichs
Sediment Survey: Yr070810, Station 3945, Gloucester Point, York River Virginia, Grace M. Massey, Patrick J. Dickhudt, Carl T. Friedrichs
Data
This dataset consists of sediment properties including grain size distribution, percent moisture, percent organic matter, sediment bed erodibility, as well as (in most cases) x-ray images of the sediment structure. Most samples were taken in support of an Acoustic Doppler Velocimeter (ADV) tripod deployed in nearby location.
Tower Deployment: Yr130313 To Yr130426, Adv, Clay Bank, York River Virginia, Grace M. Massey, Kelsey A. Fall, Carl T. Friedrichs
Tower Deployment: Yr130313 To Yr130426, Adv, Clay Bank, York River Virginia, Grace M. Massey, Kelsey A. Fall, Carl T. Friedrichs
Data
Dataset consists of data collected during a tower deployment of four Nortek Vector ADV sensors which were mounted at different depths in the water column to monitor suspended sediment concentrations and sizes. Conductivity and temperature were also monitored at corresponding depths.
Tower Deployment: Yr160831 To Yr160912, Lisst, Clay Bank, York River Virginia, Grace M. Massey, Kelsey A. Fall, Carl T. Friedrichs
Tower Deployment: Yr160831 To Yr160912, Lisst, Clay Bank, York River Virginia, Grace M. Massey, Kelsey A. Fall, Carl T. Friedrichs
Data
Dataset consists of data collected during a tower deployment of a Sequoia LISST 100-ST sensor in the surface waters to monitor suspended sediment concentrations and sizes.
Tripod Deployment: Yr131211 To Yr140225, Adv, Clay Bank, York River Virginia, Grace M. Massey, Carl T. Friedrichs
Tripod Deployment: Yr131211 To Yr140225, Adv, Clay Bank, York River Virginia, Grace M. Massey, Carl T. Friedrichs
Data
Dataset consists of burst data collected as part of a tripod deployment. The tripod included the following instruments: Acoustic Doppler Velocimeter (ADV), RBR CTD, Sediment Trap.
Tripod Deployment: Yr140404 To Yr140717, Adv, Clay Bank, York River Virginia, Grace M. Massey, Carl T. Friedrichs
Tripod Deployment: Yr140404 To Yr140717, Adv, Clay Bank, York River Virginia, Grace M. Massey, Carl T. Friedrichs
Data
Dataset consists of burst data collected as part of a tripod deployment. The tripod included the following instruments: Acoustic Doppler Velocimeter (ADV), two HOBOs, Sediment Trap.
Storm Surge Simulation From The 2009 Nor’Easter On The Virginia Shoreline, Karinna Nunez, Yinglong J. Zhang, Evan Hill, Catherine Riscassi Duning
Storm Surge Simulation From The 2009 Nor’Easter On The Virginia Shoreline, Karinna Nunez, Yinglong J. Zhang, Evan Hill, Catherine Riscassi Duning
Data
The November 2009 nor’easter formed from the remnants of Hurricane Ida and generated strong winds, heavy rain, and storm surge across the east coast of the United States. The height of the storm surge generated by the nor’easter was modelled throughout Virginia using SCHISM (Semi-implicit Cross-scale Hydroscience Integrated System Model). SCHISM outputs were translated to GIS and processed to be overlaid upon the LUBC (land use and bank cover) shoreline of coastal Virginia.
Coastal Virginia Flooding Duration Maps Current And Projected For 2020, 2050 And 2100, Molly Mitchell, Daniel Schatt, Jessica Hendricks
Coastal Virginia Flooding Duration Maps Current And Projected For 2020, 2050 And 2100, Molly Mitchell, Daniel Schatt, Jessica Hendricks
Data
Geospatial layers displaying annual flooding duration in the coastal zone of Virginia. These were generated from publicly available historical hourly tidal data from the NOAA Tides and Currents website from various tide gauges in the Chesapeake Bay region for the last 20 years. Particular tide gauges were linked to specific localities depending on location. The data was processed to determine average annual flooding duration at various flooding levels. Flood levels corresponding to specified average annual duration levels were then determined and used with lidar-derived digital elevation models to extract flood areas corresponding to the specified ranges of flood duration. Specifically, …
Identifying Network Biomarkers For Each Breast Cancer Subtypes Along With Their Effective Single And Paired Repurposed Drugs Using Network-Based Machine Learning Techniques, Forough Firoozbakht
Identifying Network Biomarkers For Each Breast Cancer Subtypes Along With Their Effective Single And Paired Repurposed Drugs Using Network-Based Machine Learning Techniques, Forough Firoozbakht
Electronic Theses and Dissertations
Breast cancer is a complex disease that can be classified into at least 10 different molecular subtypes. Appropriate diagnosis of specific subtypes is critical for ensuring the best possible patient treatment and response to therapy. Current computational methods for determining the subtypes are based on identifying differentially expressed genes (i.e., biomarkers) that can best discriminate the subtypes. Such approaches, however, are known to be unreliable since they yield different biomarker sets when applied to data sets from different studies. Gathering knowledge about the functional relationship among genes will identify “network biomarkers” that will enrich the criteria for biomarker selection. Cancer …
Partial Wave Analysis Of Strange Mesons Decaying To K + Π − Π + In The Reaction Γp → K + Π + Π − Λ(1520) And The Commissioning Of The Gluex Dirc Detector, Andrew Hurley
Dissertations, Theses, and Masters Projects
Hadron spectroscopy is a cornerstone of our understanding of the strong nuclear interac-tions. Studying the hadron spectrum led to the postulation of quarks and gluons, and the development of Quantum Chromodynamics (QCD), the theory of the strong nuclear force. Today hadron spectroscopy provides an important test of QCD, particularly in the non-perturbative energy regime. One such test is the existence of hybrid hadrons that have gluonic degrees of freedom, e.g. qq̄g states, that are allowed by QCD but have remained elusive in experimental searches. The GlueX experiment located at Thomas Jefferson National Accelerator Facility, is designed to map the light …