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Articles 17881 - 17910 of 18297
Full-Text Articles in Physical Sciences and Mathematics
Sediment Survey: Yr061120, Station 3924, Gloucester Point, York River Virginia, Grace M. Massey, Patrick J. Dickhudt, Carl T. Friedrichs
Sediment Survey: Yr061120, Station 3924, 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.
Tripod Deployment: Yr110506 To Yr110705, Adv, Clay Bank, York River Virginia, Grace M. Massey, Carl T. Friedrichs
Tripod Deployment: Yr110506 To Yr110705, 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: Two Acoustic Doppler Velocimeters (ADV), YSI6600 CTD.
Tripod Deployment: Yr120319 To Yr120706, Adv, Clay Bank, York River Virginia, Grace M. Massey, Carl T. Friedrichs
Tripod Deployment: Yr120319 To Yr120706, 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), Sediment Trap.
Marsh Vulnerability Index And Index Applied To Coastal Shorelines, Molly Mitchell, Donna Marie Bilkovic, Julie Herman, Jessica Hendricks, Evan Hill
Marsh Vulnerability Index And Index Applied To Coastal Shorelines, Molly Mitchell, Donna Marie Bilkovic, Julie Herman, Jessica Hendricks, Evan Hill
Data
The Marsh Vulnerability Index (MVI) is a spatially-resolved assessment of Virginia tidal marsh vulnerabilities from important climate-change drivers – erosion vulnerability, inundation from sea level rise, and salinity intrusion from sea level rise – that can support management decisions. Effects were evaluated for two time-steps (near and longer-term planning horizons): 2050 and 2100.
The Marsh Vulnerability Index Applied to Coastal Shorelines layer extends the MVI evaluation for use in evaluating living shoreline (i.e., created or enhanced shoreline marshes) vulnerability and applies it to tidal shorelines in coastal Virginia. Outputs from this analysis were intended to evaluate the vulnerability of areas …
Management Practices For Urban Areas In The Hampton Roads Vicinity: Data Files, Gary F. Anderson
Management Practices For Urban Areas In The Hampton Roads Vicinity: Data Files, Gary F. Anderson
Data
During 1980 through 1981, the Virginia Institute of Marine Science conducted studies in the Hampton Roads Virginia vicinity to assess pollutant loading in runoff from various land use types. The 13 urban study areas also included established BMPs such as grassy swales and retention ponds to measure their effectiveness in reducing pollutant loads to the Chesapeake Bay. The focus was on nutrients, BOD and suspended solids. The studies were conducted with support of the U.S. EPA under section 208 of the Federal Clean Water Act.
Methods and results are documented in the associated publication. Data files were processed using SPSS …
Cruise: Yr071217, Stations S4408-S4420, Gloucester Point, York River Virginia 6-Hour Mudbed Calibration Survey Bracketing A Flood Tide, Grace M. Massey, Carl T. Friedrichs
Cruise: Yr071217, Stations S4408-S4420, Gloucester Point, York River Virginia 6-Hour Mudbed Calibration Survey Bracketing A Flood Tide, Grace M. Massey, Carl T. Friedrichs
Data
Dataset consists of profile and water column burst data and bottom burst data collected as part of a 6-hour anchor station survey in support of an Acoustic Doppler Velocimeter (ADV) tripod deployed in nearby location.
Cruise: Yr150825, Stations S5534-S5540, Yorktown, York River Virginia 6-Hour Mudbed Calibration Survey Bracketing An Ebb Tide, Grace M. Massey, Carl T. Friedrichs
Cruise: Yr150825, Stations S5534-S5540, Yorktown, York River Virginia 6-Hour Mudbed Calibration Survey Bracketing An Ebb Tide, Grace M. Massey, Carl T. Friedrichs
Data
Dataset consists of profile and water column burst data and bottom burst data collected as part of a 6-hour anchor station survey in support of an Acoustic Doppler Velocimeter (ADV) tripod deployed in nearby location.
Sediment Survey: Yr060503 , Station 3908, Clay Bank, York River Virginia, Grace M. Massey, Patrick J. Dickhudt, Carl T. Friedrichs
Sediment Survey: Yr060503 , Station 3908, 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: Yr061117, Station 3923, Clay Bank, York River Virginia, Grace M. Massey, Patrick J. Dickhudt, Carl T. Friedrichs
Sediment Survey: Yr061117, Station 3923, 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: Yr070627, Station 3942, Clay Bank, York River Virginia, Grace M. Massey, Patrick J. Dickhudt, Carl T. Friedrichs
Sediment Survey: Yr070627, Station 3942, 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: Yr070808, Station 3943, Clay Bank, York River Virginia, Grace M. Massey, Patrick J. Dickhudt, Carl T. Friedrichs
Sediment Survey: Yr070808, Station 3943, 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: Yr071015, Station 3946, Clay Bank, York River Virginia, Grace M. Massey, Patrick J. Dickhudt, Carl T. Friedrichs
Sediment Survey: Yr071015, Station 3946, 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: Yr110822, Station S4968-S4971, Clay Bank, York River Virginia, Grace M. Massey, Kelsey A. Fall, Carl T. Friedrichs
Sediment Survey: Yr110822, Station S4968-S4971, Clay Bank, York River Virginia, Grace M. Massey, Kelsey A. Fall, 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: Yr120120, Station S4989-S4991, Clay Bank, York River Virginia, Grace M. Massey, Kelsey A. Fall, Carl T. Friedrichs
Sediment Survey: Yr120120, Station S4989-S4991, Clay Bank, York River Virginia, Grace M. Massey, Kelsey A. Fall, 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: Yr120507, Station S5015-S5018, Clay Bank, York River Virginia, Grace M. Massey, Kelsey A. Fall, Carl T. Friedrichs
Sediment Survey: Yr120507, Station S5015-S5018, Clay Bank, York River Virginia, Grace M. Massey, Kelsey A. Fall, 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: Yr120628, Station S5019-S5021, Clay Bank, York River Virginia, Grace M. Massey, Kelsey A. Fall, Carl T. Friedrichs
Sediment Survey: Yr120628, Station S5019-S5021, Clay Bank, York River Virginia, Grace M. Massey, Kelsey A. Fall, 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: Yr140127, Station S5372-S5375, Clay Bank, York River Virginia, Grace M. Massey, Kelsey A. Fall, Carl T. Friedrichs
Sediment Survey: Yr140127, Station S5372-S5375, Clay Bank, York River Virginia, Grace M. Massey, Kelsey A. Fall, 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: Yr140409, Station S5376-S5380, Clay Bank, York River Virginia, Grace M. Massey, Kelsey A. Fall, Carl T. Friedrichs
Sediment Survey: Yr140409, Station S5376-S5380, Clay Bank, York River Virginia, Grace M. Massey, Kelsey A. Fall, 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: Yr071016, Station 3947, Gloucester Point, York River Virginia, Grace M. Massey, Patrick J. Dickhudt, Carl T. Friedrichs
Sediment Survey: Yr071016, Station 3947, 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: Yr150821 To Yr150831, Light Sensor, Clay Bank, York River Virginia, Grace M. Massey, Kelsey A. Fall, Carl T. Friedrichs
Tower Deployment: Yr150821 To Yr150831, Light Sensor, 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 multiple ONSET light sensors at varying depths to monitor light intensity and temperature.
Tower Deployment: Yr160406 To Yr160420, Light Sensor, Clay Bank, York River Virginia, Grace M. Massey, Kelsey A. Fall, Carl T. Friedrichs
Tower Deployment: Yr160406 To Yr160420, Light Sensor, 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 multiple ONSET light sensors at varying depths to monitor light intensity and temperature.
Tripod Deployment: Yr090226 To Yr090430, Adv, Clay Bank, York River Virginia, Grace M. Massey, Carl T. Friedrichs
Tripod Deployment: Yr090226 To Yr090430, 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), YSI6600 CTD, Sequoia LISST.
Tripod Deployment: Yr100927 To Yr110314, Adv, Clay Bank, York River Virginia, Grace M. Massey, Carl T. Friedrichs
Tripod Deployment: Yr100927 To Yr110314, 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), YSI6600 CTD.
Patterns Of Interdisciplinary Collaboration Resemble Biogeochemical Relationships In The Mcmurdo Dry Valleys, Antarctica: A Historical Social Network Analysis Of Science, 1907–2016, Stephen M. Chignell, Adrian Howkins, Poppie Gullett, Andrew G. Fountain
Patterns Of Interdisciplinary Collaboration Resemble Biogeochemical Relationships In The Mcmurdo Dry Valleys, Antarctica: A Historical Social Network Analysis Of Science, 1907–2016, Stephen M. Chignell, Adrian Howkins, Poppie Gullett, Andrew G. Fountain
Geology Faculty Publications and Presentations
Co-authorship networks can provide key insights into the production of scientific knowledge. This is particularly interesting in Antarctica, where most human activity relates to scientific research. Bibliometric studies of Antarctic science have provided a useful understanding of international and interdisciplinary collaboration, yet most research has focused on broad-scale analyses over recent time periods. Here, we take advantage of a ‘Goldilocks’ opportunity in the McMurdo Dry Valleys, an internationally important region of Antarctica and the largest ice-free region on the continent. The McMurdo Dry Valleys have attracted continuous and diverse scientific activity since 1958. It is a geographically confined region with …
Automated Conjecturing On The Independence Number And Minimum Degree Of Diameter-2-Critical Graphs, Joshua R. Forkin
Automated Conjecturing On The Independence Number And Minimum Degree Of Diameter-2-Critical Graphs, Joshua R. Forkin
Theses and Dissertations
A diameter-2-critical (D2C) graph is a graph with diameter two such that removing any edge increases the diameter or disconnects the graph. In this paper, we look at other lesser-studied properties of D2C graphs, focusing mainly on their independence number and minimum degree. We show that there exist D2C graphs with minimum degree strictly larger than their independence number, and that this gap can be arbitrarily large. We also exhibit D2C graphs with maximum number of common neighbors strictly greater than their independence number, and that this gap can be arbitrarily large. Furthermore, we exhibit a D2C graph whose number …
Radiative Width Of K*(892) From Lattice Quantum Chromodynamics, Archana Radhakrishnan
Radiative Width Of K*(892) From Lattice Quantum Chromodynamics, Archana Radhakrishnan
Dissertations, Theses, and Masters Projects
In this dissertation, we use lattice quantum chromodynamics to explore the radiative transitions of πK to K, to calculate the radiative width of the resonant K*(892) which appears in the P-wave πK → γK transition amplitude. The matrix elements are extracted from three-point functions calculated in a finite-volume discretized lattice with a pion mass of 284 MeV. The finite-volume amplitudes, which are constrained over a large number of πK energy points and four-momentum transfers, are mapped to the infinite volume transition amplitude by using the Lellouch-Lüscher formalism. The radiative width is determined to be …
Multi-Step Prediction Using Tree Generation For Reinforcement Learning, Kevin Prakash
Multi-Step Prediction Using Tree Generation For Reinforcement Learning, Kevin Prakash
Master's Projects
The goal of reinforcement learning is to learn a policy that maximizes a reward function. In some environments with complete information, search algorithms are highly useful in simulating action sequences in a game tree. However, in many practical environments, such effective search strategies are not applicable since their state transition information may not be available. This paper proposes a novel method to approximate a game tree that enables reinforcement learning to use search strategies even in incomplete information environments. With an approximated game tree, the agent predicts all possible states multiple steps into the future and evaluates the states to …
Jparsec - A Parser Combinator For Javascript, Sida Zhong
Jparsec - A Parser Combinator For Javascript, Sida Zhong
Master's Projects
Parser combinators have been a popular parsing approach in recent years. Compared with traditional parsers, a parser combinator has both readability and maintenance advantages.
This project aims to construct a lightweight parser construct library for Javascript called Jparsec. Based on the modular nature of a parser combinator, the implementation uses higher-order functions. JavaScript provides a friendly and simple way to use higher-order functions, so the main construction method of this project will use JavaScript's lambda functions. In practical applications, a parser combinator is mainly used as a tool, such as parsing JSON files.
In order to verify the utility of …
Enabling Use Of Signal In A Disconnected Village Environment, Evan Chopra
Enabling Use Of Signal In A Disconnected Village Environment, Evan Chopra
Master's Projects
A significant portion of the world still does not have a stable internet connection. Those people should have the ability to communicate with their loved ones who may not live near by or to share ideas with friends. To power this achievable reality, our lab has set out on making infrastructure for enabling delay tolerant applications. This network will communicate using existing smartphones that will relay the information to a connected environment. The proof of concept application our lab is using is Signal as it offers end to end encryption messaging and an open source platform our lab can develop.
Using Machine Learning To Maximize First-Generation Student Success A Contribution To The Mission Of Aiding The Underserved, Mustafa Emre Yesilyurt
Using Machine Learning To Maximize First-Generation Student Success A Contribution To The Mission Of Aiding The Underserved, Mustafa Emre Yesilyurt
Master's Projects
The Leadership and Career Accelerator (UNVS 101) is a course offered at San José State University (SJSU) designed to hone industry skills in and provide support to students of underserved backgrounds. The main goal of this study is to determine which features are most significant to identifying the students at risk of failing the course. This will allow faculty to better focus data collection efforts and facilitate an increase in classifier accuracy. The data came as three distinct sets (sources). One contained features describing student demographics and academic history, another described the students’ experience in the course, and a third …