Physical Sciences and Mathematics Commons^™

Research On The Collision Risk Of Ships Off Keelung Based On Ais Data, Shih-Tzung Chen, Ming-Feng Yang, Sheng-Long Kao, Mengru Tu, Jun-Yuan Kuo, Yen-Ting Chao, Huang-Kai Hsu

Journal of Marine Science and Technology

In previous literature, several computational methods have been proposed to analyze collision risks for vessels navigating at sea, most of which rely on the calculation of DCPA and TCPA between two vessels. However, this study adopts an enhanced version of the Vessel Conflict Ranking Operator (VCRO) to assess vessel collision risks. This approach not only considers the relative distance and relative velocity between two vessels but also takes their relative aspect into account. This methodology was applied to real-world vessels’ dynamic data collected through AIS. From a near-collision perspective, it identifies high-risk areas near Keelung water where commercial vessels and …

Cooling Performance Analysis For Mobile Vehicles By Thermal Resistance Network, Chia-An Yang, Jung-Chang Wang, Pi-Hsia Yen

Journal of Marine Science and Technology

This paper used CFD software to simulate the cooling situation of the engine space of a mobile vehicle. We used thermal resistance network diagram to calculate the heat flux at each position of the power system, and discussed the CFD simulation results. The error between the simulation results and the experiment was 10.07%. The thermal resistance network diagram proposed in this paper can reduce the time for numerical simulation by evaluate the heat flux at each position of the power system.

Microbial Community And Genome Structure In Coastal Seawater From A Commercial Port And Nearby Offshore Island In Northern Taiwan, Chi-Yu Shih, Ching-Hsiang Chin, Shiow-Yi Chen, Chun-Ru Hsu, Lee-Kuo Kan, Wen-Shyong Tzou

Journal of Marine Science and Technology

The pollution stemming from the use of petroleum by boats, the presence of deceased marine life, hazardous chemicals, and wastewater is a major issue in human-made commercial ports. This pollution poses a considerable challenge to the diverse organisms inhabiting the seawater. To comprehend the impact of this pollution on the microbiome, we conducted a study in which we collected surface water samples from a commercial port called Keelung Port, as well as a nearby offshore island known as Keelung Islet. These locations are situated in northern Taiwan, along the Northwestern Pacific Ocean. Through the use of whole-metagenome shotgun sequencing, we …

A Computational Study Of The Copper-Catalyzed Trifluoromethylation Of Boronic Acids, Kevin Nyhuis

Theses, Dissertations and Culminating Projects

This work is a computational study of a reaction mechanism for the trifluoromethylation of boronic acids. Three steps of the proposed reaction mechanism are studied, •CF₃ addition to a copper catalyst center, base promoted transmetalation between copper and aryl boronic acid, and bond forming reductive elimination in which the CF₃ and aryl substituent form a bond. Limited information is known about this mechanism. This study uses computational methods to attempt to elucidate the mechanism and provide the groundwork for potential improvement. Quantum chemical methods in conjunction with tight-binding based conformational sampling methods are used to investigate the possible …

Tiny Language Models Enriched With Multimodal Knowledge From Multiplex Networks, Clayton Fields, Osama Natouf, Andrew Mcmains, Catherine Henry, Casey Kennington

Computer Science Faculty Publications and Presentations

Large transformer language models trained exclusively on massive quantities of text are now the standard in NLP. In addition to the impractical amounts of data used to train them, they require enormous computational resources for training. Furthermore, they lack the rich array of sensory information available to humans, who can learn language with much less exposure to language. In this study, performed for submission in the BabyLM challenge, we show that we can improve a small transformer model’s data efficiency by enriching its embeddings by swapping the learned word embeddings from a tiny transformer model with vectors extracted from a …

Exploring Transformers As Compact, Data-Efficient Language Models, Clayton Fields, Casey Kennington

Computer Science Faculty Publications and Presentations

Large scale transformer models, trained with massive datasets have become the standard in natural language processing. The huge size of most transformers make research with these models impossible for those with limited computational resources. Additionally, the enormous pretraining data requirements of transformers exclude pretraining them with many smaller datasets that might provide enlightening results. In this study, we show that transformers can be significantly reduced in size, with as few as 5.7 million parameters, and still retain most of their downstream capability. Further we show that transformer models can retain comparable results when trained on human-scale datasets, as few as …

Pacific Northwest Streamflow Data Landscape: A Report From The 2022 Streamflow Data Roundtables, Kendra E. Kaiser

Geosciences Faculty Publications and Presentations

This project was funded by the U.S. Geological Survey Northwest Climate Adaptation Science Center to catalog the location, temporal extent and purpose of non-USGS streamflow datasets. As part of this project, roundtable meetings convened local, state and federal agencies, and nonprofits to explore the complexity of gathering and integrating the identified datasets and identify issues surrounding data-sharing across organizations.

This report synthesizes discussions from each of the state roundtable discussions convened in the spring of 2022, and highlights common challenges and needs across the region. Additional information from organizations not able to be present at the meetings were added after …

Cyberinfrastructure Deployments On Public Research Clouds Enable Accessible Environmental Data Science Education, Tyler L. Mcintosh, Erick Verleye, Jennifer K. Balch, Megan E. Cattau, Nayani T. Ilangakoon, Nathan Korinek, R. Chelsea Nagy, James Sanovia, Edwin Skidmore, Tyson L. Swetnam, Ty Tuff, Nathan Quarderer, Carol A. Wessman

Human-Environment Systems Research Center Faculty Publications and Presentations

Modern science depends on computers, but not all scientists have access to the scale of computation they need. A digital divide separates scientists who accelerate their science using large cyberinfrastructure from those who do not, or who do not have access to the compute resources or learning opportunities to develop the skills needed. The exclusionary nature of the digital divide threatens equity and the future of innovation by leaving people out of the scientific process while over-amplifying the voices of a small group who have resources. However, there are potential solutions: recent advancements in public research cyberinfrastructure and resources developed …

Drivers Of Spatiotemporal Patterns Of Surface Water Inputs In A Catchment At The Rain-Snow Transition Zone Of The Water-Limited Western United States, E. Trujillo, J. Mcnamara

Geosciences Faculty Publications and Presentations

Spatial and temporal dynamics of rainfall and snowmelt (i.e., surface water inputs, SWI) control soil moisture, groundwater recharge, and streamflow at annual, seasonal, and event scales. In the rain-snow transition zone, comprising a large portion of the mountainous western United States, there is limited understanding of the sensitivity of spatiotemporal SWI dynamics across hydrologically variable water years (WYs). We modeled rainfall and snowpack dynamics in a small headwater catchment (1.8 km²) spanning the rain-snow transition in southwestern Idaho, USA, for two hydrologically distinct WYs (2011 and 2014). In wet WY 2011 and dry WY 2014, total precipitation drove …

Ethics Of Emerging Communication And Collaboration Technologies For Children, Juan Pablo Hourcade, Elizabeth Bonsignore, Tamara Clegg, Flannery Currin, Jerry A. Fails, Georgie Qiao Jin, Summer R. Schmuecker, Lana Yarosh

Computer Science Faculty Publications and Presentations

This SIG will provide child-computer interaction researchers and practitioners, as well as other interested CSCW attendees, an opportunity to discuss topics related to the ethics of emerging communication and collaboration technologies for children. The child-computer interaction community has conducted many discussions on ethical issues, including a recent SIG at CHI 2023. However, the angle of communication and collaboration has not been a focus, even though emerging technologies could affect these aspects in significant ways. Hence, there is a need to consider emerging technologies, such as extended reality, and how they may impact the way children communicate and collaborate in face-to-face, …

Social Networks Impact Flood Risk Mitigation Behavior: A Case Study Of Lidar Adoption In The Pacific Northwest, Us, Tara Pozzi, Vicken Hillis

Human-Environment Systems Research Center Faculty Publications and Presentations

Flood risk and damage are expected to increase in the Pacific Northwest due to climate change. Light Detection and Ranging (lidar) is a remote sensing technology that generates high-resolution topographic data and can therefore produce higher accuracy floodplain maps, an important tool that communities use to assess their flood risk. Despite the promise of lidar for flood risk mitigation, both the availability of lidar data and the use of that data when available varies across the U.S. What factors drive the adoption of technology, such as lidar, for flood risk management? How can we better promote the use of technologies …

A Machine Learning Approach To Classify Open Water And Ice Cover On Slave River Delta, Ida Moalemi

Theses and Dissertations (Comprehensive)

Seasonal temperature trend and ice phenology in Great Slave lake (GSL), are strongly influenced by warmer inflow from Slave river. The Slave river flows to GSL through Slave river delta (SRD), bringing a rise in temperature that triggers the ice break-up process of the lake. Slave river discharge is subject to multiple stressors including climate warming and upstream water activities, which in turn, directly affects the GSL break-up process. Consequently, monitoring the break-up process at SRD, where the river connects to the lake, serves as an indicator to better understand the cascading effects on GSL ice break-up. This research aims …

Distributed Spatial Data Sharing: A New Era In Sharing Spatial Data, Majid Hojati

Theses and Dissertations (Comprehensive)

The advancements in information and communications technology, including the widespread adoption of GPS-based sensors, improvements in computational data processing, and satellite imagery, have resulted in new data sources, stakeholders, and methods of producing, using, and sharing spatial data. Daily, vast amounts of data are produced by individuals interacting with digital content and through automated and semi-automated sensors deployed across the environment. A growing portion of this information contains geographic information directly or indirectly embedded within it. The widespread use of automated smart sensors and an increased variety of georeferenced media resulted in new individual data collectors. This raises a new …

Computational Investigation Of The Ionization Potential Of Lead Sulfide Quantum Dots, Jessica Beyer

Scripps Senior Theses

The purpose of this work was to determine the impact of quantum dot size on ionization potential and to determine how the presence of carbonyl-based ligands affect the ionization potential of lead sulfide quantum dot systems. Ionization potential (IP) is defined as the energy required to remove an electron from an atom, molecule, or material. IP helps scientists determine how reactive the material of interest is, which is crucial information when manufacturing nanomaterials. Accurate quantum chemical calculations of ionization potential are challenging due to the computational cost associated with the numerical solution of the Dyson equation. In this work, the …

Method Development For The Quantification Of Heavy Metals In Biological Matrices And Its Application To Clinical And Environmental Samples, Michelle Catherine Gende

Dissertations

A three-fold approach was taken to develop a method for the detection of heavy metals in different matrices and had to be performed sequentially. The first was to develop a method capable of quantifying lead in complex matrices by graphite furnace atomic absorption (GFAA). The developed method needed to meet specific analytical requirements, namely, to be robust, sensitive, and accurate. Initially, four different sample preparation methods were explored for the quantification of lead using Escherichia coli (E. coli) as a sample matrix. The sample preparation procedures attempted were acidic dilution, matrix modification, conventional heating digestion, and microwave assisted acid digestion …

Quantifying The Carbon Stored And Sequestered By The Trees On Pomona College’S Campus, Paola A. Giron-Carson

Scripps Senior Theses

We are experiencing a climate crisis that must be confronted with strategic mitigation. Pomona College contributes to the climate crisis through its emissions for which there is a baseline record. However there is no baseline record of the climate mitigation currently performed by the trees on Pomona’s campus through carbon storage. This study seeks to determine a current baseline quantity of carbon stored and sequestrated by Pomona’s trees as well as possible courses of climate mitigation for Pomona College to take. Initial information gathering was conducted through interviews with several stakeholders. This study was conducted using data collected prior to …

A Machine Learning Approach To Sector Based Market Efficiency, Angus Zuklie

Honors Projects

In economic circles, there is an idea that the increasing prevalence of algorithmic trading is improving the information efficiency of electronic stock markets. This project sought to test the above theory computationally. If an algorithm can accurately forecast near-term equity prices using historical data, there must be predictive information present in the data. Changes in the predictive accuracy of such algorithms should correlate with increasing or decreasing market efficiency.

By using advanced machine learning approaches, including dense neural networks, LSTM, and CNN models, I modified intra day predictive precision to act as a proxy for market efficiency. Allowing for the …

Covid-19 Crowd Detection, Mustafa Ibrahim, Aly M. Zeineldin, Yameen Khan, Ayman Elmesalami, Soad Ibrahim

OUR Journal: ODU Undergraduate Research Journal

Object detection was introduced by researchers for face detection. Researchers explain how the detected face is divided into minor frames to be recognized by the algorithm. Due to COVID-19 and government regulations, many people face problems going to shopping centers and shop safely. It has been very hard for both the government and the people to manage social distancing. In our study, we developed a system using Raspberry Pi-4 that will detect the distance between people along with counting the number of distance and mask violations. An error message will appear on the screen in red, showing the total number …

Analysis Of Ab Initio Protein Structure Prediction Methods, Maytha Alshammari, Jing He

College of Sciences Posters

Protein structure prediction produces atomic models of three-dimensional structure of a protein from its amino acid sequence. Understanding the function mechanism of proteins requires knowledge of three-dimensional structures. When developing new enzymes and drugs, it's essential to understand the structure of the target protein. In this study, we analyze models predicted using two ab initio protein structure prediction methods, trRosetta and Quark. A set of thirty protein chains was used to evaluate the effectiveness of the methods. The thirty chains were collected from Protein Data Bank (June – November, 2020). The length and the relative position of the predicted secondary …

A Bootstrap Test For Informative Intra-Cluster Group Sizes In Clustered Data, Hasika K. Wickrama Senevirathne, Sandipan Dutta

College of Sciences Posters

Clustered data are frequently observed in various domains of scientific and social studies. In a typical clustered data, units within a cluster are correlated while units between different clusters are independent. An example of such clustered data can be found in dental studies where individuals are treated as clusters and the teeth in an individual are the units within a cluster. While analyzing such clustered data, it has been observed that the number of units present in a cluster can be informative in terms of being associated with the outcome from that cluster. Specifically, when the aim is to compare …

Hydrodynamics And Sediment Transport In The Tidally Influenced James River, Ollie Gilchrest, Rip Hale

The Graduate School Posters

The tidally influenced James River is an important economic, ecologic, and cultural resource for VA residents. Tidal rivers have been historically understudied, however they are critical transition zones, the dynamics of which have implications for freshwater supply and sediment trapping. Globally, estimates suggest that >30% of fluvial sediment is trapped in the tidal zone, the location and dynamics of which are actively changing due to sea level rise and saltwater encroachment. In addition, analysis of historical water levels on the James River has shown a decrease in the tidal range since 1940. The present study combines >1-year’s worth of hydrographic …

Organic Matter Content And Grain Size Analysis In Seagrass Sediments, Adriana Amrhein, Rip Hale

College of Sciences Posters

Anthropogenic stresses including increased water temperatures, decreased water quality, sea level rise, ocean acidification and sediment biogeochemical processes have caused a significant loss in seagrass meadow acreage. Seagrass meadows provide coastal protection from storms and recently have been emphasized for their importance in sequestering and storing “Blue Carbon” from the atmosphere and ocean. Seagrass meadows can trap this blue carbon in their sediment as organic carbon, and it can be stored for hundreds to thousands of years. Restoration efforts of seagrass meadows in the Virginia coast started in the 1990s and effects of increasing seagrass density can be observed in …

Dust Deposition To The Bermuda Region: A Comparison Of Estimates Using Seasonally-Resolved Measurements Of Aluminum In Water-Column, Aerosol, And Rain Samples, Tara Williams, Peter Sedwick, Bettina Sohst, Joe Resing, Kristen Buck, Salvatore Caprara, Rod Johnson, Dan Ohnemus, Ben Twining, Alessandro Tagliabue

College of Sciences Posters

Dust deposition is a major source of bioactive trace elements to the surface ocean, yet this flux remains difficult to constrain. Previously, time-averaged dust flux has been estimated using surface ocean dissolved aluminum (DAl) concentrations, assumed values for aerosol aluminum solubility (%Al_S), and the residence time of DAl in the surface mixed layer (SML). We apply this method to estimate dust deposition in the Bermuda Atlantic Time-series Study (BATS) region using water-column DAl data from cruises in 2019, which is compared with direct flux estimates from contemporaneous measurements of aluminum in aerosols and rain collected on Bermuda. Seasonal …

Acceleration Of U.S. Southeast And Gulf Coast Sea-Level Rise Amplified By Internal Climate Variability, Sönke Dangendorf, Noah Hendricks, Qiang Sun, John Klinck, Tal Ezer, Thomas Frederikse, Francisco M. Calafat, Thomas Wahl, Torbjörn E. Törnqvist

CCPO Publications

While there is evidence for an acceleration in global mean sea level (MSL) since the 1960s, its detection at local levels has been hampered by the considerable influence of natural variability on the rate of MSL change. Here we report a MSL acceleration in tide gauge records along the U.S. Southeast and Gulf coasts that has led to rates (>10 mm yr⁻¹ since 2010) that are unprecedented in at least 120 years. We show that this acceleration is primarily induced by an ocean dynamic signal exceeding the externally forced response from historical climate model simulations. However, when the …

Towards A Holistic And Comparative Analysis Of The Free Content Web: Security, Privacy, And Performance, Abdulrahman Alabduljabbar

Electronic Theses and Dissertations, 2020-2023

Free content websites that provide free books, music, games, movies, etc., have existed on the Internet for many years. While it is a common belief that such websites might be different from premium websites providing the same content types in terms of their security, a rigorous analysis that supports this belief is lacking from the literature. In particular, it is unclear if those websites are as safe as their premium counterparts. In this dissertation, we set out to investigate the similarities and differences between free content and premium websites, including their risk profiles. Moreover, we analyze and quantify through measurements …

Analysis Of Polycyclic Aromatic Hydrocarbons In Tobacco Related Samples Via High Performance Liquid Chromatography And Laser Excited Time Resolved Shpol' Skii Spectroscopy, Ahmed Comas

Electronic Theses and Dissertations, 2020-2023

Human exposure to polycyclic aromatic hydrocarbons (PAHs) due to cigarette smoke is well known. It is also known that PAHs are not inherent components of tobacco. Their presence in cigarette smoke results from the curing process of tobacco leaves used for the fabrication of cigarettes and the incomplete combustion of tobacco during the smoking process. The two chromatographic versions of EPA method 610 are popular approaches for the analysis of PAHs in a wide variety of samples. This method, which is based either on High-Performance Liquid-Chromatography (HPLC) or Gas-Chromatography (GC) has shown the presence of Benzo[a]pyrene (B[a]P) in tobacco samples …

Analysis Of Multi-Drug Resistant Mycobacterium Tuberculosis Using Split Deoxyribozymes, Abryana Fergus

Electronic Theses and Dissertations, 2020-2023

Globally, tuberculosis, a disease caused by the species of Mycobacterium tuberculosis (Mtb) complex, stands as a leading cause of death from a single infectious agent. Even though antituberculous drugs are available, treatment is challenging due to antibiotic resistance associated with point mutations in the bacterial genome. Resistance to the first-line antibiotics – rifampin and isoniazid – results in multidrug-resistant tuberculosis (MDR) requiring a more complicated treatment regimen. Timely and accurate identification of drug-resistant TB cases can help prescribe the most effective treatment and prevent the spread of infection. This research aims to develop an assay to discern multi-drug resistant forms …

Mapping The Focal Points Of Wordpress: A Software And Critical Code Analysis, Bryce Jackson

Electronic Theses and Dissertations, 2020-2023

Programming languages or code can be examined through numerous analytical lenses. This project is a critical analysis of WordPress, a prevalent web content management system, applying four modes of inquiry. The project draws on theoretical perspectives and areas of study in media, software, platforms, code, language, and power structures. The applied research is based on Critical Code Studies, an interdisciplinary field of study that holds the potential as a theoretical lens and methodological toolkit to understand computational code beyond its function. The project begins with a critical code analysis of WordPress, examining its origins and source code and mapping selected …

Probing The Structure-Activity Relationships Of Electrocatalytic Nanomaterials Using Scanning Electrochemical Microscopy, Zackary Parsons

Electronic Theses and Dissertations, 2020-2023

Electrocatalysis plays a central role in the development of renewable energy technologies as it enables direct conversion between renewable electricity and chemical energy. To design efficient electrocatalysts, it is essential to understand the relationship between the structure and the activity of electrocatalytic materials. Scanning electrochemical microscopy (SECM) is a scanning probe technique capable of imaging local electrocatalytic activity under operating conditions, of which the spatial resolution depends on the size and shape of the probe. Compared to commercial SECM probes which have limited resolution capabilities, I have developed novel nanoelectrode probes by etching sharp platinum tips followed by electropolymerization coating …

Discovering Vulnerabilities And Designing Trustworthy Defenses In Iot Systems And Devices, Bryan Pearson

Electronic Theses and Dissertations, 2020-2023

Internet of Things (IoT) dominates many functions in the modern world, from sensing and reporting temperature, humidity, and air quality, to controlling and automating homes, commercial buildings, and equipment. However, IoT systems have received scrutiny in recent years due to countless security incidents, which can have physical and even deadly consequences. This research provides a comprehensive assessment of the security of IoT systems and devices, including low-cost microcontroller (MCU) based sensors, cloud services, and Building Automation Systems (BAS). We begin by exploring the current landscape of vulnerabilities and defenses in modern IoT applications. We show that many security needs can …