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Articles 32461 - 32490 of 302638

Full-Text Articles in Physical Sciences and Mathematics

Bioactivity Of Suberitenones A And B, Jared G. Waters Apr 2022

Bioactivity Of Suberitenones A And B, Jared G. Waters

USF Tampa Graduate Theses and Dissertations

Throughout human history, natural products have formed the foundation of medicine. In ancient times, a myriad of herbs and fungi have been attributed properties of healing and rejuvenation. Today, that foundation still very much exists, as natural product chemists isolate bioactive compounds from plants, fungi, animals, and microorganisms alike. As more of these secondary metabolites are discovered, scientists pursue more and more sources of biodiversity that may yield new and unprecedented compounds. To this end, Antarctica has become of particular note, as its unique environmental conditions and highly isolated nature make for rare and unusual adaptations in its native wildlife. …

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Image Provenance Analysis, Daniel Moreira, William Theisen, Walter Scheirer, Aparna Bharati, Joel Brogan, Anderson Rocha Apr 2022

Image Provenance Analysis, Daniel Moreira, William Theisen, Walter Scheirer, Aparna Bharati, Joel Brogan, Anderson Rocha

Computer Science: Faculty Publications and Other Works

The literature of multimedia forensics is mainly dedicated to the analysis of single assets (such as sole image or video files), aiming at individually assessing their authenticity. Different from this, image provenance analysis is devoted to the joint examination of multiple assets, intending to ascertain their history of edits, by evaluating pairwise relationships. Each relationship, thus, expresses the probability of one asset giving rise to the other, through either global or local operations, such as data compression, resizing, color-space modifications, content blurring, and content splicing. The principled combination of these relationships unveils the provenance of the assets, also constituting an …

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Closing Social Apr 2022

Closing Social

Computer Science Graduate Research Workshop

No abstract provided.

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Prediction Of Balance Control And Instability In Walking At Sea, Jungyeon Choi Apr 2022

Prediction Of Balance Control And Instability In Walking At Sea, Jungyeon Choi

Computer Science Graduate Research Workshop

No abstract provided.

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Interactive Visualizations For Explanation In Ai, Ashley Ramsey Apr 2022

Interactive Visualizations For Explanation In Ai, Ashley Ramsey

Computer Science Graduate Research Workshop

No abstract provided.

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Automated Program Repair For Api Misuse Vulnerabilities, Dip Kiran Pradhan Newar Apr 2022

Automated Program Repair For Api Misuse Vulnerabilities, Dip Kiran Pradhan Newar

Computer Science Graduate Research Workshop

No abstract provided.

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New Approaches To Convex Polygon Formations, Rui Yang Apr 2022

New Approaches To Convex Polygon Formations, Rui Yang

Computer Science Graduate Research Workshop

No abstract provided.

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Workload Prediction With Cost-Aware Data Analytics System, Anshuman Das Mohapatra Apr 2022

Workload Prediction With Cost-Aware Data Analytics System, Anshuman Das Mohapatra

Computer Science Graduate Research Workshop

No abstract provided.

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Artificial-Intelligence-Based Approaches For Estimating Irregular Walking Surface With Wearable Sensor, Ru Ng Apr 2022

Artificial-Intelligence-Based Approaches For Estimating Irregular Walking Surface With Wearable Sensor, Ru Ng

Computer Science Graduate Research Workshop

No abstract provided.

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Building Interpretable Methods For Identifying Bridge Maintenance Patterns, Akshay Kale Apr 2022

Building Interpretable Methods For Identifying Bridge Maintenance Patterns, Akshay Kale

Computer Science Graduate Research Workshop

No abstract provided.

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Using Deep Neural Network And Transformers To Extract Graphene Compounds And Properties, Ayman Ibn Jaman Apr 2022

Using Deep Neural Network And Transformers To Extract Graphene Compounds And Properties, Ayman Ibn Jaman

Computer Science Graduate Research Workshop

No abstract provided.

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Deep Learning-Based Image Watermarking With Transform Invariant Representation Learning, Arjon Das Apr 2022

Deep Learning-Based Image Watermarking With Transform Invariant Representation Learning, Arjon Das

Computer Science Graduate Research Workshop

No abstract provided.

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Opening Social Apr 2022

Opening Social

Computer Science Graduate Research Workshop

No abstract provided.

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Effects Of Meteorologic Events On Wave Climate And Current Regime In A Shallow, Microtidal Bay, Jay S. Merrill Apr 2022

Effects Of Meteorologic Events On Wave Climate And Current Regime In A Shallow, Microtidal Bay, Jay S. Merrill

LSU Master's Theses

Along coastal Louisiana and within the shallow microtidal Barataria Bay estuary, meteorological events can play a primary role in influencing wave climate and circulation patterns. Understanding the effects of hurricanes and smaller tropical storms on hydrodynamic processes is important for constraining and predicting hydrodynamic variation in Barataria Bay, which, largely due to impacts from wave energy, is currently experiencing rapid wetland loss and is a major focus of coastal restoration efforts. Two bottom-mounted upward-facing Acoustic Current Doppler Profilers and wave, temperature, and depth recorders were installed in the lower portions of Barataria Bay to measure the wave climate and three-dimensional …

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Using Field Scale Electrical Data To Understand Real-Time Agricultural Water Delivery, Bradley Dowell Apr 2022

Using Field Scale Electrical Data To Understand Real-Time Agricultural Water Delivery, Bradley Dowell

Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research

Areas across the High Plains (Ogallala) Aquifer region are experiencing unsustainable groundwater level declines and impacts to streamflow due to increasing human influence, posing challenges for sustaining future agricultural economies and groundwater resources. State and local agencies manage water using groundwater models, which are not at the same temporal and spatial scale as water management on farms. Well-informed agricultural water usage cannot be achieved without reliable and cost-effective water use at farm scale. Water meters are expensive and rarely installed unless required by the state or other regulatory agency; however, most center pivots have their own power supply, which reports …

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Protecting Terrapins With Teds In Virginia: Lessons From Other States, Bridget Verrekia, Shelby Fuchs Apr 2022

Protecting Terrapins With Teds In Virginia: Lessons From Other States, Bridget Verrekia, Shelby Fuchs

Virginia Coastal Policy Center

This paper highlights case studies about other states' efforts to require or incentivize the use of TEDs [terrapin excluder devices] and recommends policies for Virginia to adopt that have proven successful elsewhere. First, it outlines the threats to terrapins at large, as well as the threat posed by commercial and recreational crabbing, specifically. Next, it details the efforts that other East Coast states have made to combat the problem, including policies that require or incentivize the use of TEDs on crab pots, and discusses the regulatory framework currently in place in Virginia. Finally, this paper concludes by analyzing the approaches …

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Ionic Liquids As Both Solvent And Reagent In Electrophilic Addition Reactions, Hannah Artz, Roseann K. Sachs Apr 2022

Ionic Liquids As Both Solvent And Reagent In Electrophilic Addition Reactions, Hannah Artz, Roseann K. Sachs

Honors Projects and Presentations: Undergraduate

Ionic Liquids (ILs) are an environmentally friendly alternative to organic and aqueous reaction solvents. ILs do not emit hazardous gasses, are readily recycled and reused, and often do not require an excess volume of harmful reagents and purification solvents. The IL anion’s capacity to participate in a reaction as the nucleophile source is a much less understood area of this research, and it may advance the use of ILs in organic synthesis, particularly for addition and substitution reactions. Markovnikov hydrohalogenation of alkenes is one addition reaction that is generally taught as an introduction to organic chemical reactions; however, this reaction …

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Estimation Of Radium-226 Concentrations In Produced Water From Shale Gas, Tight Gas And Conventional Hydrocarbon Wells, Richard Frank Haaker Apr 2022

Estimation Of Radium-226 Concentrations In Produced Water From Shale Gas, Tight Gas And Conventional Hydrocarbon Wells, Richard Frank Haaker

Mathematics & Statistics ETDs

This study examined data from the United States Geological Survey Produced Water database, version 2.3 (USGS DB) and built models to estimate the concentration of radium-226 in produced water given the values of other predictor variables. The dataset had only about 254 observations that were useable. Although the USGS DB had up to 190 possible attributes, it also had extreme rates of missingness, and many of the candidate variables were highly correlated. Multiple imputation techniques were employed using the Mice, Hmisc, and RMS packages for the R language to deal with the missing data. A multiple linear regression and two …

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Unreasonable: A Strict Liability Solution To The Ftc’S Data Security Problem, James C. Cooper, Bruce H. Kobayashi Apr 2022

Unreasonable: A Strict Liability Solution To The Ftc’S Data Security Problem, James C. Cooper, Bruce H. Kobayashi

Michigan Technology Law Review

For over two decades, the FTC creatively employed its capacious statute to police against shoddy data practices. Although the FTC’s actions were arguably needed at the time to fill a gap in enforcement, there are reasons to believe that its current approach has outlived its usefulness and is in serious need of updating. In particular, our analysis shows that the FTC’s current approach to data security is unlikely to instill anything close to optimal incentives for data holders. These shortcomings cannot be fixed through changes to the FTC enforcement approach, as they are largely generated by a mismatch between the …

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Are Soybean Models Ready For Climate Change Food Impact Assessments?, Kritika Kothari, Rafael Battisti, Kenneth J. Boote, Sotirios V. Archontoulis, Adriana Confalone, Julie Constantin, Santiago V. Cuadra, Philippe Debaeke, Babacar Faye, Brian Grant, Gerrit Hoogenboom, Qi Jing, Michael Van Der Laan, Fernando Antônio Macena Da Silva, Fabio R. Marin, Alireza Nehbandani, Claas Nendel, Larry C. Purcell, Budong Qian, Alex C. Ruane, Céline Schoving, Evandro H. F. M. Silva, Ward Smith, Afshin Soltani, Amit Srivastava, Nilson A. Vieira Jr., Stacey Slone, Montserrat Salmerón Apr 2022

Are Soybean Models Ready For Climate Change Food Impact Assessments?, Kritika Kothari, Rafael Battisti, Kenneth J. Boote, Sotirios V. Archontoulis, Adriana Confalone, Julie Constantin, Santiago V. Cuadra, Philippe Debaeke, Babacar Faye, Brian Grant, Gerrit Hoogenboom, Qi Jing, Michael Van Der Laan, Fernando Antônio Macena Da Silva, Fabio R. Marin, Alireza Nehbandani, Claas Nendel, Larry C. Purcell, Budong Qian, Alex C. Ruane, Céline Schoving, Evandro H. F. M. Silva, Ward Smith, Afshin Soltani, Amit Srivastava, Nilson A. Vieira Jr., Stacey Slone, Montserrat Salmerón

Plant and Soil Sciences Faculty Publications

An accurate estimation of crop yield under climate change scenarios is essential to quantify our ability to feed a growing population and develop agronomic adaptations to meet future food demand. A coordinated evaluation of yield simulations from process-based eco-physiological models for climate change impact assessment is still missing for soybean, the most widely grown grain legume and the main source of protein in our food chain. In this first soybean multi-model study, we used ten prominent models capable of simulating soybean yield under varying temperature and atmospheric CO2 concentration [CO2] to quantify the uncertainty in soybean yield …

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Industrial Digital Twins At The Nexus Of Nextg Wireless Networks And Computational Intelligence: A Survey, Shah Zeb, Aamir Mahmood, Syed Ali Hassan, Md. Jalil Piran, Mikael Gidlund, Mohsen Guizani Apr 2022

Industrial Digital Twins At The Nexus Of Nextg Wireless Networks And Computational Intelligence: A Survey, Shah Zeb, Aamir Mahmood, Syed Ali Hassan, Md. Jalil Piran, Mikael Gidlund, Mohsen Guizani

Machine Learning Faculty Publications

By amalgamating recent communication and control technologies, computing and data analytics techniques, and modular manufacturing, Industry 4.0 promotes integrating cyber–physical worlds through cyber–physical systems (CPS) and digital twin (DT) for monitoring, optimization, and prognostics of industrial processes. A DT enables interaction with the digital image of the industrial physical objects/processes to simulate, analyze, and control their real-time operation. DT is rapidly diffusing in numerous industries with the interdisciplinary advances in the industrial Internet of things (IIoT), edge and cloud computing, machine learning, artificial intelligence, and advanced data analytics. However, the existing literature lacks in identifying and discussing the role and …

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Circulation, Volume 27, No. 2, Center For Coastal Physical Oceanography, Old Dominion University Apr 2022

Circulation, Volume 27, No. 2, Center For Coastal Physical Oceanography, Old Dominion University

CCPO Circulation

Spring 2022 issue of CCPO Circulation featuring the article "Looking Back While Moving Forward," by Sönke Dangendorf.

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Active Polar Liquid Crystal Channel Flows: Analyzing The Roles Of Nematic Strength And Activation Parameter, Lacey Schenk, Ruhai Zhou Apr 2022

Active Polar Liquid Crystal Channel Flows: Analyzing The Roles Of Nematic Strength And Activation Parameter, Lacey Schenk, Ruhai Zhou

College of Sciences Posters

Suspensions of active polar liquid crystalline polymers (APLC) exhibit complex phenomena such as spontaneous flows, pattern formations and defects. Using the Kinetic Model, which couples the Smoluchowski Equation and the Navier-Stokes Equations, we conduct numerical simulations of APLC in a microfluidic channel to investigate the competitive effect among different material constants, such as the nematic concentration (the strength of the potential for nematic order) and active strength (the individual nano-rods strength of their individual movement) with and without a pressure gradient. Both Dirichlet and Neumann boundary conditions on the mathematical model are employed. Steady states, including isotropic and nematic states, …

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A Machine Learning Approach To Denoising Particle Detector Observations In Nuclear Physics, Polykarpos Thomadakis, Angelos Angelopoulos, Gagik Gavalian, Nikos Chrisochoides Apr 2022

A Machine Learning Approach To Denoising Particle Detector Observations In Nuclear Physics, Polykarpos Thomadakis, Angelos Angelopoulos, Gagik Gavalian, Nikos Chrisochoides

College of Sciences Posters

With the evolution in detector technologies and electronic components used in the Nuclear Physics field, experimental setups become larger and more complex. Faster electronics enable particle accelerator experiments to run with higher beam intensity, providing more interactions per time and more particles per interaction. However, the increased beam intensities present a challenge to particle detectors because of the higher amount of noise and uncorrelated signals. Higher noise levels lead to a more challenging particle reconstruction process by increasing the number of combinatorics to analyze and background signals to eliminate. On the other hand, increasing the beam intensity can provide physics …

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Reframing The Achievement Gap In Mathematics Education, Madeline Pavolovich '22 Apr 2022

Reframing The Achievement Gap In Mathematics Education, Madeline Pavolovich '22

Posters

Much of math education research focuses on a so-called “achievement gap” measured by test scores and similar quantitative measures of “success.” By framing issues of equity in this way, methods to remedy the gap often require subordinated groups to become more like the “higher achieving” group. In other areas of study, we have been quicker to incorporate sociopolitical lenses into teaching and learning with an emphasis on identity and power. Such a sociopolitical turn could help us rethink what it means for math education to be truly equitable.

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Gender Discrimination In Ai, Nicole Papert '22 Apr 2022

Gender Discrimination In Ai, Nicole Papert '22

Posters

There are several studies revealing that AI tools used in job search applications and sites will promote different opportunities depending on the gender of the user. Specifically, men are typically shown more competitive job postings than women, given that the users have similar skills and qualifications. In this poster, I will closely examine why algorithms utilized for the job search process may present differently between men and women.

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Belonging In Math And How It’S Affected By Groupwork, Kara Mathes '22 Apr 2022

Belonging In Math And How It’S Affected By Groupwork, Kara Mathes '22

Posters

Interactions in groups for class assignments are an important part of a student’s sense of belonging in mathematics and other academic disciplines. This sense of belonging has an impact on the student’s sense of self as well as their academic performance.

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Cross-Sectoral Climate Change Modeling, Jeremy Gordon '22 Apr 2022

Cross-Sectoral Climate Change Modeling, Jeremy Gordon '22

Posters

Although climate data originates from various integrated sectors, it continues to be evaluated in isolation. By using cross-sectoral modeling, climate change modeling can more effectively represent data, and the possible consequences of misjudging future models.

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Ranked Choice Voting: Who’S The Real Winner?, Brendan Magill '23 Apr 2022

Ranked Choice Voting: Who’S The Real Winner?, Brendan Magill '23

Posters

Ranked choice voting is a voting system in which voters rank candidates in order or preference. The winning candidate is determined by eliminating candidates and reassigning their votes until one has a majority. It provides solutions to some of the fundamental issues with traditional voting. But is it more fair? Should it be instituted in American democratic elections?

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Racial Bias In Health Care Machine Learning Algorithms, Esther Akinpelu '22 Apr 2022

Racial Bias In Health Care Machine Learning Algorithms, Esther Akinpelu '22

Posters

Machine learning algorithms in healthcare are racially biased, especially when diagnosing patients and choosing candidates for care management programs.

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