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Articles 24511 - 24540 of 294411

Full-Text Articles in Physical Sciences and Mathematics

Overview For Exploring The Multisensory Landscape, Brent Chamberlain, Richard Smardon Sep 2024

Overview For Exploring The Multisensory Landscape, Brent Chamberlain, Richard Smardon

Landscape Architecture and Environmental Planning Faculty Publications

Land use change has had a fundamental impact on the livelihoods of people throughout the world. This Special Issue focuses on the research being conducted at the intersection of this land use change and the importance of maintaining landscapes that enrich humanity and our engagement with nature. Within this Special Issue, we explored the value of landscapes that heighten the senses. Visual Resource Stewardship is an area of research that closely aligns with understanding how changes in the environment may be perceived and experienced. Understanding the tools, processes, and theories involved helps us to better understand how land use change …

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Locating Diversity In Reservoir Computing Using Bayesian Hyperparameter Optimization, Whitney Lunceford Sep 2024

Locating Diversity In Reservoir Computing Using Bayesian Hyperparameter Optimization, Whitney Lunceford

Theses and Dissertations

Reservoir computers rely on an internal network to predict the future state(s) of dynamical processes. To understand how a reservoir's accuracy depends on this network, we study how varying the networ's topology and scaling affects the reservoir's ability to predict the chaotic dynamics on the Lorenz attractor. We define a metric for diversity, the property describing the variety of the responses of the nodes that make up reservoir's internal network. We use Bayesian hyperparameter optimization to find optimal hyperparameters and explore the relationships between diversity, accuracy of model predictions, and model hyperparameters. The content regarding the VPT metric, the effects …

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Designing Cybersecurity Escape Rooms: A Gamified Approach To Undergraduate Learning, Thitima Srivatanakul Sep 2024

Designing Cybersecurity Escape Rooms: A Gamified Approach To Undergraduate Learning, Thitima Srivatanakul

Journal of Cybersecurity Education, Research and Practice

Gamification, including game-based learning (GBL), is a widely recognized pedagogical approach used for imparting and reinforcing cybersecurity knowledge and skills to learners. One innovative form of GBL gaining popularity across various educational levels, from secondary schools to professional development, is escape room-style education. This study is centered on the development and design of escape room activities tailored for teaching cybersecurity concepts, with a particular focus on web and software security, to undergraduate students at York College. The primary objectives of this research are twofold: firstly, to evaluate the effectiveness of educational escape room activities in reinforcing cybersecurity concepts taught in …

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Density-Dependence Inside A Marine Protected Area Increases Natural Mortality And Stunts The Growth Of A Spiny Lobster, Emma-Jade Tuffley, Simon De Lestang Sep 2024

Density-Dependence Inside A Marine Protected Area Increases Natural Mortality And Stunts The Growth Of A Spiny Lobster, Emma-Jade Tuffley, Simon De Lestang

Fisheries Research Articles

Sustainable fisheries management often requires the modelling of stocks under unfished conditions, when the influence of population densities on animal growth and mortality can be substantial. This can be especially true for species such as spiny rock lobster, which are very habitat specific. Using western rock lobster (Panulirus cygnus) tag-recapture data from adjacent and similar fished and unfished areas, the key life history parameters of natural mortality and growth were examined and compared under different population density scenarios. In an area representative of virgin biomass levels, lobsters exhibited reduced growth rates and a substantially higher rate of natural mortality …

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C-H Amination Chemistry Mediated By Trinuclear Cu(I) Sites Supported By A Ligand Scaffold Featuring An Arene Platform And Tetramethylguanidinyl Residues, Meenakshi Sharma, Reece M. Fritz, Himanshu Bhatia, Joseph O. Adebanjo, Zhou Lu, Mohammad A. Omary, Thomas R. Cundari, Amitava Choudhury, Pericles Stavropoulos Sep 2024

C-H Amination Chemistry Mediated By Trinuclear Cu(I) Sites Supported By A Ligand Scaffold Featuring An Arene Platform And Tetramethylguanidinyl Residues, Meenakshi Sharma, Reece M. Fritz, Himanshu Bhatia, Joseph O. Adebanjo, Zhou Lu, Mohammad A. Omary, Thomas R. Cundari, Amitava Choudhury, Pericles Stavropoulos

Chemistry Faculty Research & Creative Works

Tripodal ligands that can encapsulate single or multiple metal sites in C3-symmetric geometric configurations constitute valuable targets for novel catalysts. Of particular interest in ligand development are efforts toward incorporating apical elements that exhibit little if any electron donicity, to enhance the electrophilic nature of a trans positioned active oxidant (e.g., metal-oxo, -nitrene). The tripodal ligand TMG3trphen-Arene has been synthesized, featuring an arene platform 1,3,5-substituted with phenylene arms possessing tetramethylguanidinyl (TMG) residues. Compound [(TMG3trphen-Arene) Cu3(μ-Cl)3] has been subsequently synthesized by extracting a Cu3(μ-Cl)3 cluster from anhydrous CuCl and shown to encapsulate a crown-shaped …

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Development And Benchmark Of Polarizable Models For Ions, Luke Landry Sep 2024

Development And Benchmark Of Polarizable Models For Ions, Luke Landry

Dissertations

Metalloproteins are ubiquitous in biology, playing crucial roles in diverse processes. Meanwhile, molecular simulations have become an important tool in scientific research. To accurately simulate metalloprotein systems, accounting for polarization and charge transfer effects is required. The fluctuating charge (FQ) model can effectively simulate the charge transfer effect, but the existing models often lack specificity for metalloproteins. In our research, a tailored FQ model for zinc-containing metalloproteins, leveraging the extended charge equilibration (EQeq) scheme, was introduced. CM5 charges were used as the target in our model parameterization, which offers advantages over RESP/CHELPG charges. Most notably, CM5 charges hold independence over …

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Saas Application Maturity Assessment Model, Saiqa Aleem, Rabia Batool, Shayma Alkobaisi, Faheem Ahmed, Asad Masood Khattak Sep 2024

Saas Application Maturity Assessment Model, Saiqa Aleem, Rabia Batool, Shayma Alkobaisi, Faheem Ahmed, Asad Masood Khattak

All Works

Software-as-a-service (SaaS), as a software delivery model, has received substantial attention from software providers and users alike. In recent years, it has become one of the most promising service delivery models in cloud computing. Many existing companies are transferring their business into the SaaS delivery model. Network vendors also migrate to a SaaS business model by offering on-demand remote IT support. This increasingly competitive landscape and the variety in markets have imposed many challenges for SaaS developers and vendors and made it difficult to find a consensus on the factors contributing to the positive performance of SaaS businesses. This paper …

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Multimodal Mixing Convolutional Neural Network And Transformer For Alzheimer’S Disease Recognition, Junde Chen, Yun Wang, Adnan Zeb, M. D. Suzauddola, Yuxin Wen Sep 2024

Multimodal Mixing Convolutional Neural Network And Transformer For Alzheimer’S Disease Recognition, Junde Chen, Yun Wang, Adnan Zeb, M. D. Suzauddola, Yuxin Wen

Engineering Faculty Articles and Research

Early recognition of Alzheimer’s disease (AD) and its precursor state, mild cognitive impairment (MCI), is pivotal in interrupting the progression of the disease and providing suitable treatment. Recent development in deep learning techniques has drawn great research attention for improving the efficacy of AD recognition. However, numerous current methods solely utilize data from a single auxiliary domain, limiting their ability to harness valuable intrinsic insights from multiple domains. To cope with the challenge, this paper is devoted to establishing an innovative multimodal medical data fusion model, termed as MMDF, to perform Alzheimer’s disease recognition. Multimodal data including clinical records and …

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Size Fractionation Informs Microbial Community Composition And Interactions In The Eastern Tropical North Pacific Ocean, Madeleine A. Thompson, David L. Valentine, Xuefeng Peng Sep 2024

Size Fractionation Informs Microbial Community Composition And Interactions In The Eastern Tropical North Pacific Ocean, Madeleine A. Thompson, David L. Valentine, Xuefeng Peng

Faculty Publications

Marine microorganisms are drivers of biogeochemical cycles in the world’s oceans, including oxygen minimum zones (OMZs). Using a metabarcoding survey of the 16S rRNA gene, we investigated prokaryotic communities, as well as their potential interactions with fungi, at the coastal, offshore, and peripheral OMZ of the eastern tropical North Pacific. Water samples were collected along a vertical oxygen gradient, and large volumes were filtered through three size fractions, 0.22, 2, and 22 µm. The changes in community composition along the oxygen gradient were driven by Planctomycetota, Bacteroidota, Verrucomicrobiota, and Gammaproteobacteria; most are known degraders of marine polysaccharides and usually associated …

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Cyberattack Detection And Handling For Neural Network-Approximated Economic Model Predictive Control, Jihan Abou Halloun, Helen E. Durand Sep 2024

Cyberattack Detection And Handling For Neural Network-Approximated Economic Model Predictive Control, Jihan Abou Halloun, Helen E. Durand

Chemical Engineering and Materials Science Faculty Research Publications

Cyberattacks on control systems can create unprofitable and unsafe operating conditions. To enhance safety and attack resiliency of control systems, cyberattack detection strategies can be developed. Prior work in our group has sought to develop cyberattack detection strategies that are integrated with an advanced control formulation known as Lyapunov-based economic model predictive control (LEMPC), in the sense that the controller properties can be used to analyze closed-loop stability in the presence or absence of undetected attacks. In this work, we consider neural network-approximated control laws, concepts for mitigating cyberattacks on such control laws, and how these ideas elucidate concepts in …

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Lyapunov-Based Cyberattack Detection For Distinguishing Between Sensor And Actuator Attacks, Dominic Messina, Helen E. Durand Sep 2024

Lyapunov-Based Cyberattack Detection For Distinguishing Between Sensor And Actuator Attacks, Dominic Messina, Helen E. Durand

Chemical Engineering and Materials Science Faculty Research Publications

Control-theoretic cyberattack detection strategies are control strategies where control theory can be used in the design of the detection policies and analysis of stability properties with and without cyberattacks. This work provides a step toward understanding how to diagnose cyberattacks using control-theoretic cyberattack detection mechanisms. Specifically, we analyze the conditions under which a control-theoretic cyberattack detection strategy developed in our prior work to handle detection of simultaneous actuator and sensor attacks can be extended to distinguish between whether attacks are occurring on sensors or actuators. We present and evaluate heuristic concepts for attempting to diagnose sensor attacks; these again demonstrate …

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Scientific History, Sampling Approach, And Physical Characterization Of The Camp Century Subglacial Material, A Rare Archive From Beneath The Greenland Ice Sheet, Paul R. Bierman, Andrew J. Christ, Catherine M. Collins, Halley M. Mastro, Juliana Souza, Pierre Henri Blard, Stefanie Brachfeld, Zoe R. Courville, Tammy M. Rittenour, Elizabeth K. Thomas, Jean Louis Tison, François Fripiat Sep 2024

Scientific History, Sampling Approach, And Physical Characterization Of The Camp Century Subglacial Material, A Rare Archive From Beneath The Greenland Ice Sheet, Paul R. Bierman, Andrew J. Christ, Catherine M. Collins, Halley M. Mastro, Juliana Souza, Pierre Henri Blard, Stefanie Brachfeld, Zoe R. Courville, Tammy M. Rittenour, Elizabeth K. Thomas, Jean Louis Tison, François Fripiat

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

Basal materials in ice cores hold information about paleoclimate conditions, glacial processes, and the timing of past ice-free intervals, all of which aid understanding of ice sheet stability and its contribution to sea level rise in a warming climate. Only a few cores have been drilled through ice sheets into the underlying sediment and bedrock, producing limited material for analysis. The last of three Camp Century ice cores, which the U.S. Army collected in northwestern Greenland from 1963-1966 CE, recovered about 3.5 m of subglacial material, including ice and sediment. Here, we document the scientific history of the Camp Century …

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Regulating Algorithmic Harms, Sylvia Lu Sep 2024

Regulating Algorithmic Harms, Sylvia Lu

Law & Economics Working Papers

In recent years, the rapid expansion of artificial intelligence (AI) innovations has led to a rise in algorithmic harms—harms emerging from AI operations that pose significant threats to civil rights and democratic values in today’s technological landscape. A facial recognition system for improving criminal detection wrongly collected sensitive personal data and flagged racial minorities as shoplifters. A risk-prediction algorithm adopted to identify patients denied medical treatment to Black individuals with poor health conditions. A social media algorithm intended to boost social engagement exacerbated addictive behavior and mental illness in teenagers. These harms are becoming increasingly ubiquitous yet often manifest in …

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Profit Considerations For Nonlinear Control-Integrated Cyberattack Detection On Process Actuators, Keshav Kasturi Rangan, Helen E. Durand Sep 2024

Profit Considerations For Nonlinear Control-Integrated Cyberattack Detection On Process Actuators, Keshav Kasturi Rangan, Helen E. Durand

Chemical Engineering and Materials Science Faculty Research Publications

Prior research from our group developed a control-integrated active actuator cyberattack detection strategy. This strategy continuously probed for cyberattacks by updating target steady-states at every sampling time and then moving the process state toward these over the subsequent sampling period. Attacks were fagged if a Lyapunov function around the target steady-state did not decrease over a sampling period. This strategy had the benefit of ensuring safety of the process until an attack was detected. However, the continuous probing for attacks could decrease profit from the process compared to not probing for the attacks, which could limit the attractiveness of the …

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Supplementary Files For: Quantifying The Impact Of Rain-On-Snow Induced Flooding In The Western United States, Emma Watts, Brennan Bean Sep 2024

Supplementary Files For: Quantifying The Impact Of Rain-On-Snow Induced Flooding In The Western United States, Emma Watts, Brennan Bean

Browse all Datasets

Serious flooding can happen when rain falls on snow, which we call a rain-on-snow (ROS) event. Increasing our understanding of the behavior of floods resulting from ROS events can help us design better systems to manage flood water and prevent it from causing damage. This thesis explores how ROS events affect streamflow in the Western United States by examining the weather conditions that precede a streamflow surge. We classify stream surges as ROS or non-ROS induced based on these weather conditions, which helps us separate floods caused by ROS events from those caused by other factors. By comparing these different …

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Tracing Atlantic Sea Scallops Using Radio Frequency Identification (Rfid) Technology, Will Shoup, David Rudders, Jonathon Peros Sep 2024

Tracing Atlantic Sea Scallops Using Radio Frequency Identification (Rfid) Technology, Will Shoup, David Rudders, Jonathon Peros

Journal of Extension

Radio Frequency Identification (RFID) represents a technology that has the potential to enhance many aspects of the Atlantic sea scallop fishery. Driven by fishery management and market forces, fishery product traceability benefits fisheries managers, consumers, and fishermen. In order to demonstrate the capabilities of RFID technology in the scallop fishery, a solution is proposed that would help establish clear Chain of Custody (CoC) so that the scallop supply chain can be better documented. Implementation and acceptance of any new technology will hinge on effective communication and extension efforts that can leverage the multi-benefit aspects of adopting RFID into the fishery.

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Improving Ligand Pharmacokinetics Via Bioisosteric Substitution Of Amides With 1, 2, 3-Triazoles While Maintaining Dopamine D4 Receptor Selectivity And Potency, Mohammad Alkhatib Sep 2024

Improving Ligand Pharmacokinetics Via Bioisosteric Substitution Of Amides With 1, 2, 3-Triazoles While Maintaining Dopamine D4 Receptor Selectivity And Potency, Mohammad Alkhatib

Theses and Dissertations

Several neurophysiological functions, such as attention, cognition, and emotional regulation, are regulated by the binding of dopamine on G-Protein coupled receptors. D4Rs are mainly located in the prefrontal cortex and the hippocampus and are known to have a key role in decision-making, memory formation, cognition, and attention. Administration of D4Rs- selective ligands during the preclinical studies enhance the outcomes and the results in animal models suffering from neuropsychiatric disorders, including ADHD, substance use disorders (SUD), and Alzheimer's disease. Recently, we reported a group of D4R-selective ligands with different efficacies depending on their phenylpiperazine ring scaffold to illustrate D4R function during …

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Meta-Analysis Of Set-Based Multiple Phenotype Association Test Based On Gwas Summary Statistics From Different Cohorts, Lirong Zhu, Shuanglin Zhang, Qiuying Sha Sep 2024

Meta-Analysis Of Set-Based Multiple Phenotype Association Test Based On Gwas Summary Statistics From Different Cohorts, Lirong Zhu, Shuanglin Zhang, Qiuying Sha

Michigan Tech Publications

Genome-wide association studies (GWAS) have emerged as popular tools for identifying genetic variants that are associated with complex diseases. Standard analysis of a GWAS involves assessing the association between each variant and a disease. However, this approach suffers from limited reproducibility and difficulties in detecting multi-variant and pleiotropic effects. Although joint analysis of multiple phenotypes for GWAS can identify and interpret pleiotropic loci which are essential to understand pleiotropy in diseases and complex traits, most of the multiple phenotype association tests are designed for a single variant, resulting in much lower power, especially when their effect sizes are small and …

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Methane Fluxes In Tidal Marshes Of The Conterminous United States, Ariane Arias-Ortiz, Jaxine Wolfe, Scott D. Bridgham, Sara Knox, Gavin Mcnicol, Brian A. Needelman, Julie Shahan, Ellen J. Stuart-Haëntjens, Lisamarie Windham-Myers, Patty Y. Oikawa, Dennis D. Baldocchi, Joshua S. Caplan, Margaret Capooci, Kenneth M. Czapla, R. Kyle Derby, Heida L. Diefenderfer, Inke Forbrich, Gina Groseclose, Jason K. Keller, Cheryl Kelley, Amir E. Keshta, Helena S. Kleiner, Ken W. Krauss, Robert R. Lane, Sarah Mack, Serena Moseman-Valtierra, Thomas J. Mozdzer, Peter Mueller, Scott C. Neubauer, Genevieve Noyce, Katrina V. R. Schäfer, Rebecca Sanders-Demott, Charles A. Schutte, Rodrigo Vargas, Nathaniel B. Weston, Benjamin Wilson, J. Patrick Megonigal, James R. Homquist Sep 2024

Methane Fluxes In Tidal Marshes Of The Conterminous United States, Ariane Arias-Ortiz, Jaxine Wolfe, Scott D. Bridgham, Sara Knox, Gavin Mcnicol, Brian A. Needelman, Julie Shahan, Ellen J. Stuart-Haëntjens, Lisamarie Windham-Myers, Patty Y. Oikawa, Dennis D. Baldocchi, Joshua S. Caplan, Margaret Capooci, Kenneth M. Czapla, R. Kyle Derby, Heida L. Diefenderfer, Inke Forbrich, Gina Groseclose, Jason K. Keller, Cheryl Kelley, Amir E. Keshta, Helena S. Kleiner, Ken W. Krauss, Robert R. Lane, Sarah Mack, Serena Moseman-Valtierra, Thomas J. Mozdzer, Peter Mueller, Scott C. Neubauer, Genevieve Noyce, Katrina V. R. Schäfer, Rebecca Sanders-Demott, Charles A. Schutte, Rodrigo Vargas, Nathaniel B. Weston, Benjamin Wilson, J. Patrick Megonigal, James R. Homquist

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Methane (CH4) is a potent greenhouse gas (GHG) with atmospheric concentrations that have nearly tripled since pre-industrial times. Wetlands account for a large share of global CH4 emissions, yet the magnitude and factors controlling CH4 fluxes in tidal wetlands remain uncertain. We synthesized CH4 flux data from 100 chamber and 9 eddy covariance (EC) sites across tidal marshes in the conterminous United States to assess controlling factors and improve predictions of CH4 emissions. This effort included creating an open-source database of chamber-based GHG fluxes (https://doi.org/10.25573/serc.14227085). Annual fluxes across chamber and EC sites averaged 26 ± 53 g CH4 …

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Angular Momentum Flow Without Anything Carrying It, Yakir Aharonov, Daniel Collins, Sandu Popescu Sep 2024

Angular Momentum Flow Without Anything Carrying It, Yakir Aharonov, Daniel Collins, Sandu Popescu

Mathematics, Physics, and Computer Science Faculty Articles and Research

Transfer of conserved quantities between two remote regions is generally assumed to be a rather trivial process: a flux of particles carrying the conserved quantities propagates from one region to another. However, we demonstrate a flow of angular momentum from one region to another across a region of space in which there is a vanishingly small probability of any particles (or fields) being present. This shows that the usual view of how conservation laws work needs to be revisited.

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Data Analysis On Predicting The Top 12 Fantasy Football Players By Position, Alan Abadzic, Jacquelyn Cheun, Milan Patel Sep 2024

Data Analysis On Predicting The Top 12 Fantasy Football Players By Position, Alan Abadzic, Jacquelyn Cheun, Milan Patel

SMU Data Science Review

Fantasy football enthusiasts rely on rankings populated by their platform of choice to draft winning teams and make strategic roster decisions. This study presents a comprehensive analysis of player performance data to forecast the top 12 fantasy points performers per position for the upcoming season. Leveraging machine learning techniques and historical data, our model identifies key performance indicators and trends to inform player evaluations. Insights gleaned from positional trends, breakout candidates, risk assessment, and matchup analysis offer a competitive edge. By addressing limitations, ethical considerations, and avenues for future research, this study contributes to the advancement of fantasy sports analysis …

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Enhancing Imputation Accuracy: A Multi-Faceted Approach For Missing Data In Chicago Arrest Records, Steve Bramhall, Jae Chung, Nicholas Mueller Sep 2024

Enhancing Imputation Accuracy: A Multi-Faceted Approach For Missing Data In Chicago Arrest Records, Steve Bramhall, Jae Chung, Nicholas Mueller

SMU Data Science Review

This paper introduces a novel approach to enhance the imputation process for missing data, utilizing crime records from Chicago with arrests as the target feature. Robust imputation techniques are crucial in the era of burgeoning datasets for generating reliable insights. Our core objective is to present an innovative method that improves imputation techniques, augmenting model performance and bolstering the reliability of analytical outcomes. Leveraging numeric crime data, we establish a Gradient Boosting (GBM) baseline model, then introduce ensemble methods including Random Forest and Decision Trees for further refinement. By systematically exploring multiple imputation processes, we establish a baseline for comparative …

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Geospatial Temporal Crime Prediction Using Convolution And Lstm Neural Networks: Enhancing The Las Vegas Cardiff Model, Corey D. Holmes, Christian Orji, Chris Papesh Sep 2024

Geospatial Temporal Crime Prediction Using Convolution And Lstm Neural Networks: Enhancing The Las Vegas Cardiff Model, Corey D. Holmes, Christian Orji, Chris Papesh

SMU Data Science Review

According to the Department of Justice, more than half of violent crimes go unreported to law enforcement in the United States (Kollar et al., 2018). This data gap reduces the opportunity to implement proven solutions in the areas with the greatest need. In 1996, Dr. Shepherd developed the Cardiff Model with the aim of bringing together hospitals, law enforcement, and community leaders through the sharing of data. We partnered with ongoing efforts to implement the Cardiff Model in Las Vegas, Nevada. Our goal was to provide a geospatial temporal model that can predict the next 30 days of crime. By …

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Rethinking Retrieval Augmented Fine-Tuning In An Evolving Llm Landscape, Nicholas Sager, Timothy Cabaza, Matthew Cusack, Ryan Bass, Joaquin Dominguez Sep 2024

Rethinking Retrieval Augmented Fine-Tuning In An Evolving Llm Landscape, Nicholas Sager, Timothy Cabaza, Matthew Cusack, Ryan Bass, Joaquin Dominguez

SMU Data Science Review

This study explores the utilization of Retrieval Augmented Fine-Tuning (RAFT) to enhance the performance of Large Language Models (LLMs) in domain-specific Retrieval Augmented Generation (RAG) tasks. By integrating domain-specific information during the retrieval process, RAG aims to reduce hallucination and improve the accuracy of LLM outputs. We investigate the use of RAFT, an approach that enhances LLMs by incorporating domain-specific knowledge and effectively handling distractor documents. This paper validates previous work, which found that RAFT can considerably improve the performance of Llama2-7B in specific domains. We also expand upon previous work into new state-of-the-art open-source models and other datasets with …

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Enhancing Shap With Multi-Core Parallelization And Distributed Computation, Matthew David, William Jones, Hayley Horn Sep 2024

Enhancing Shap With Multi-Core Parallelization And Distributed Computation, Matthew David, William Jones, Hayley Horn

SMU Data Science Review

In recent years, the adoption of complex machine learning algorithms, often perceived as “black box” models, has grown exponentially across various disciplines. However, the lack of understanding regarding how these models come to their predictions often fosters skepticism and mistrust. In response to the demand for transparency and interpretability, Explainable AI techniques, such as SHapley Additive exPlanations (SHAP), have emerged as powerful tools for comprehending and trusting these algorithms. However, SHAP has an exponential computational demand O( x2 ), where x is the number of features. This becomes increasingly problematic with the larger datasets standard in most industries. Many frameworks …

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Performance Studies Of An Axial Flow Waterjet Pump Using An Unsteady Reynolds-Averaged Navier-Stokes Model, Stephen E. Monroe, Junfeng Wang, Chunlei Liang Sep 2024

Performance Studies Of An Axial Flow Waterjet Pump Using An Unsteady Reynolds-Averaged Navier-Stokes Model, Stephen E. Monroe, Junfeng Wang, Chunlei Liang

Northeast Journal of Complex Systems (NEJCS)

In this study, an Unsteady Reynolds-Averaged Navier-Stokes (URANS) model is demonstrated its suitability for studying the flow and performance of open marine propellers and waterjet pumps. First, the accuracy of the URANS model is validated by studying turbulent flow past counter-rotating propellers (CRPs). Specifically, experimental data from Miller (1976) is employed for comparison against the URANS results. Subsequently, URANS is used to study the flow and performance of an Office of Naval Research (ONR) axial flow waterjet pump (AxWJ-2). Due to the large number of degrees of freedom for both simulations, parallel computations over 80 cores are performed. For the …

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A Marine Knowledge System For Ocean Affairs: Integrating Data, Evaluating Usage, And Enabling Sustainable Marine Management, Yu-Jen Pan Sep 2024

A Marine Knowledge System For Ocean Affairs: Integrating Data, Evaluating Usage, And Enabling Sustainable Marine Management, Yu-Jen Pan

Journal of Marine Science and Technology–Taiwan

This study presents the evolution and assessment of the Marine Knowledge Education System (MKES), designed to improve user acceptance among students in professional marine science courses in Taiwan. The MKES leverages real-world maritime cases from the General Coast Guard Administration and is built upon existing technologies like cloud services, social networks, and data analysis tools. The technology acceptance model (TAM) provides the theoretical underpinning for the assessment of user confidence. Data was collected from 190 participants through purposive sampling. Path analysis confirmed all hypothesized relationships within the TAM with statistical significance (p < 0.001). Additionally, paired-sample t-tests revealed a significant increase in student acceptance of the MKES after integrating it into the marine science curriculum. These findings underscore the capacity of the MKES as a digital learning tool to enrich course pedagogy and improve student learning outcomes, thereby offering valuable support in advancing the education of professional marine managers.

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A Practical Guide To Light-Sheet Microscopy For Nanoscale Imaging: Looking Beyond The Cell, Stephanie N. Kramer, Jeanpun Antarasen, Cole R. Reinholt, Lydia Kisley Sep 2024

A Practical Guide To Light-Sheet Microscopy For Nanoscale Imaging: Looking Beyond The Cell, Stephanie N. Kramer, Jeanpun Antarasen, Cole R. Reinholt, Lydia Kisley

Faculty Scholarship

We present a comprehensive guide to light-sheet microscopy (LSM) to assist scientists in navigating the practical implementation of this microscopy technique. Emphasizing the applicability of LSM to image both static microscale and nanoscale features, as well as diffusion dynamics, we present the fundamental concepts of microscopy, progressing through beam profile considerations, to image reconstruction. We outline key practical decisions in constructing a home-built system and provide insight into the alignment and calibration processes. We briefly discuss the conditions necessary for constructing a continuous 3D image and introduce our home-built code for data analysis. By providing this guide, we aim to …

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Re: Approved Silver Bow Creek Conservation Area Repository Data Gap Quality Assurance Project Plan Request For Change To Install Additional Test Pits And Perform Material Characterization, Josh Bryson Sep 2024

Re: Approved Silver Bow Creek Conservation Area Repository Data Gap Quality Assurance Project Plan Request For Change To Install Additional Test Pits And Perform Material Characterization, Josh Bryson

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Draft Comments On Bpsou “Diggings East 60% Remedial Design Package” Received From British Petroleum - Atlantic Richfield Company (Bp-Ar) On 4/23/2024, Jim Ford Sep 2024

Draft Comments On Bpsou “Diggings East 60% Remedial Design Package” Received From British Petroleum - Atlantic Richfield Company (Bp-Ar) On 4/23/2024, Jim Ford

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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