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Fine-Tuning Large Language Models For Folder Structure Generation, Likhith Nemani Jan 2024

Fine-Tuning Large Language Models For Folder Structure Generation, Likhith Nemani

Master's Projects

Starting a new project is a significant challenge in the software development world. Building a new project skeleton and configurations will require vast amounts of time and effort. This project aims to overcome the difficulty presented by this challenge using advanced large language models, specifically fine-tuning LLMs. Our initial focus with the implementation is to use the powerful capabilities of advanced modern models to simplify and accelerate the complicated process of getting new projects started. The solution process begins with a user posting a README file to a predetermined repository. This README file then is used as a source for …

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Credit Score-Based Lending System On The Ethereum Platform, Mayuri Shimpi Jan 2024

Credit Score-Based Lending System On The Ethereum Platform, Mayuri Shimpi

Master's Projects

Traditional banking systems act as intermediaries, assessing risks and profiting from interest rate differentials. Credit scores, provided by trusted bureaus, are commonly used to evaluate the creditworthiness of borrowers. Cryptocurrencies have emerged as a significant and innovative medium due to their decentralized nature, operating without reliance on a central authority, such as a government.

This report describes a project to implement the Autonomous Lending system on the Ethereum Platform (ALOE), as proposed in [1], aiming to seamlessly integrate traditional credit scoring methodologies for evaluating a borrower's risk of default. The objective of this project report is to establish a robust …

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Adaptive Metric-Driven Load Balancing For Specialized Clusters Using Nginx, Juhi Raju Malkani Jan 2024

Adaptive Metric-Driven Load Balancing For Specialized Clusters Using Nginx, Juhi Raju Malkani

Master's Projects

Adaptive Metric-Driven Load Balancer is an innovative two-tier load-balancing system that uses NGINX and Prometheus to optimize resource allocation in specialized cloud clusters. This framework is built to give great performance and flexibility and runs on Google Kubernetes Engine (GKE), but it may also be deployed on local cloud environments for added security. The first tier of our system uses an NGINX-based load balancer to route incoming requests based on content type, sending traffic to hardware-optimized clusters for processing requests through specialized hardware. In our algorithm, the second tier dynamically modifies load distribution throughout each cluster by calculating pod weights …

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The Anticipation Is Killing Me! - Examining The Mediating And Moderating Relationships Between Mistreatment Anticipation And Work Engagement, Mia N. Fagan Jan 2024

The Anticipation Is Killing Me! - Examining The Mediating And Moderating Relationships Between Mistreatment Anticipation And Work Engagement, Mia N. Fagan

Master's Theses

The mistreatment of workers by customers in the service industry is widespread and well-known. Although customer mistreatment is associated with negative consequences for employees, there is little knowledge about the potential consequences of the expectation of future mistreatment. The present study examined the relationship between mistreatment anticipation and work engagement and hypothesized that mistreatment anxiety would mediate the relationship between the two and that perceived organizational support (POS) would moderate the relationship between mistreatment anticipation and mistreatment anxiety. Data were collected from a sample of 183 individuals via an online survey. Results showed a significant and negative relationship between mistreatment …

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Optimizing Field-Linked Simulations Of Dry Season Uptake And Monsoon Infiltration Within An Aspen-Mixed Conifer Forest, Raymond J. Hess Jan 2024

Optimizing Field-Linked Simulations Of Dry Season Uptake And Monsoon Infiltration Within An Aspen-Mixed Conifer Forest, Raymond J. Hess

Master's Theses

Climate models forecast that headwater catchments in the western U.S. will undergo a reduction in snowpack, early season snowmelt, and increases in evapotranspiration. The resulting extended dry season will stress vegetation in mountainous watersheds throughout the Upper Colorado River Basin. We investigate infiltration patterns and root water uptake in response to dry season disturbances within the East River watershed in Colorado. To do this, we collected soil cores, measured matric potential and sap flow, and monitored tree xylem and soil for stable isotopes of water (2H, 18O) in two soil profiles to 90 cm depth (with three Engelmann spruce and …

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Roundtable On Warhol V. Goldsmith: An Introduction To Warhol V. Goldsmith, Amy Adler, Lionel Bently, Susan Bielstein, Johanna Burton, Martha Buskirk, Noam M. Elcott, Jane Ginsburg, Branden W. Joseph, Joan Kee, Liz Linden, Rebecca Tushnet, Graeme Williams, Winnie Wong Jan 2024

Roundtable On Warhol V. Goldsmith: An Introduction To Warhol V. Goldsmith, Amy Adler, Lionel Bently, Susan Bielstein, Johanna Burton, Martha Buskirk, Noam M. Elcott, Jane Ginsburg, Branden W. Joseph, Joan Kee, Liz Linden, Rebecca Tushnet, Graeme Williams, Winnie Wong

Faculty Research, Scholarly, and Creative Activity

No abstract provided.

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A Comparative Multivariate Analysis Of Var And Deep Learning-Based Models For Forecasting Volatile Time Series Data, Saroj Gopali, Sima Siami-Namini, Faranak Abri, Akbar Siami Namin Jan 2024

A Comparative Multivariate Analysis Of Var And Deep Learning-Based Models For Forecasting Volatile Time Series Data, Saroj Gopali, Sima Siami-Namini, Faranak Abri, Akbar Siami Namin

Faculty Research, Scholarly, and Creative Activity

The existing literature on forecasting time series data is primarily based on univariate analysis and techniques such as Univariate Autoregressive (UAR), Univariate Moving Average (UMA), Simple Exponential Smoothing (SES), deep learning models, and, most notably, univariate Long Short-Term Memory (LSTM) built based on univariate variable where the next lag of time series is leveraged for forecasting the next cycle of data. This paper takes this line of research to the next level by focusing on forecasting time series data based on “multivariate” modeling and analysis. To have a better insight of the performance of various deep learning-based models when multivariate …

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Use Or Not: A Qualitative Study On The User Adoption And Abandonment Of Voice Shopping With Smart Speakers, Jiahe Lan, Yu Chen, Zheng Yan Jan 2024

Use Or Not: A Qualitative Study On The User Adoption And Abandonment Of Voice Shopping With Smart Speakers, Jiahe Lan, Yu Chen, Zheng Yan

Faculty Research, Scholarly, and Creative Activity

The recent advances in smart speakers impel the emergence and prevalence of voice shopping - placing orders on voice assistants. Previous work has studied user acceptance of voice shopping and the factors influencing users' experience of voice shopping. However, despite the growing interest in the use of voice shopping, little is known about the limited usage or abandonment of voice shopping. In this paper, we address this research gap through a qualitative study of 43 users of Tmall Genie, a smart speaker popular in China. We found that participants are willing to make low-involvement purchases via voice shopping. However, after …

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Tracked Gulls Help Identify Potential Zones Of Interaction Between Whales And Shipping Traffic, Megan A. Cimino, Heather Welch, Jarrod A. Santora, David Kroodsma, Elliott L. Hazen, Steven J. Bograd, Pete Warzybok, Jaime Jahncke, Scott A. Shaffer Jan 2024

Tracked Gulls Help Identify Potential Zones Of Interaction Between Whales And Shipping Traffic, Megan A. Cimino, Heather Welch, Jarrod A. Santora, David Kroodsma, Elliott L. Hazen, Steven J. Bograd, Pete Warzybok, Jaime Jahncke, Scott A. Shaffer

Faculty Research, Scholarly, and Creative Activity

Seabird-vessel interactions are often studied through the lens of fisheries bycatch, but seabirds encounter many watercraft types. Western Gulls Larus occidentalis breeding on the Farallon Islands (California, USA) have a foraging domain that encompasses both shipping lanes and productive fishing grounds, resulting in ample opportunities for vessel encounters. Previous research showed that these Western Gulls can serve as ecosystem indicators because their foraging behavior is linked to ocean prey conditions, and because their foraging grounds overlap with that of Humpback Whales Megaptera novaeangliae, which can make prey accessible. Because ship strikes and entanglement in fishing gear are concerns for whales …

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Defect Detection And Closed-Loop Feedback Using Machine Learning For Fused Filament Fabrication, Amaris De La Rosa, Amir Armani, Marcia Golmohamadi Jan 2024

Defect Detection And Closed-Loop Feedback Using Machine Learning For Fused Filament Fabrication, Amaris De La Rosa, Amir Armani, Marcia Golmohamadi

Faculty Research, Scholarly, and Creative Activity

The objective of this study was to develop a closed-loop system for a commercial fused filament fabrication printer based on visual machine learning inspection of common defects. Convolutional neural network was used to identify levels of common defects: stringing, over/under-extrusion, and weak infill. Transfer learning was used to adapt a pre-trained model to fit this problem, as it involves incrementally fine-tuning the model parameters to new data. The observation model achieved an accuracy of 92.86% on validation data set and 90.0% on the testing data set. By modifying the input G-code, the custom program could adjust the feed-rate, nozzle temperature, …

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Eyes On Higher Education: Evaluating Web Usability In Kuwaiti Private Universities Using Eye-Tracking And Supr-Q Metrics, Reem Albaghli, Ayah Beidas, Nada Attar Jan 2024

Eyes On Higher Education: Evaluating Web Usability In Kuwaiti Private Universities Using Eye-Tracking And Supr-Q Metrics, Reem Albaghli, Ayah Beidas, Nada Attar

Faculty Research, Scholarly, and Creative Activity

Website design and usability are critical factors that impact the effectiveness of a website, influencing both user attraction and retention. Understanding user preferences is essential for designers and researchers when optimizing user interfaces (UI) and user experiences (UX). This study addressed key research questions about usability by examining which design heuristics have the most impact on students’ interactions with private university websites in Kuwait. By assessing web design and usability across three private universities in Kuwait through specific tasks, we analyzed user experiences using eye-tracking data, task completion times, user inputs, and qualitative feedback from the Standardized User Experience Percentile …

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Marine Protection And Environmental Forcing Influence Fish-Derived Nutrient Cycling In Kelp Forests, June Shrestha, Joseph R. Peters, Jennifer E. Caselle, Scott L. Hamilton Jan 2024

Marine Protection And Environmental Forcing Influence Fish-Derived Nutrient Cycling In Kelp Forests, June Shrestha, Joseph R. Peters, Jennifer E. Caselle, Scott L. Hamilton

Faculty Research, Scholarly, and Creative Activity

Animal consumers excrete dissolved inorganic nitrogen, an essential nutrient for regulating primary production and macroalgal growth in the ocean. Often overlooked in attempts to explain kelp forest productivity, relatively little is known about the role of consumers in nutrient cycling in temperate systems, such as the magnitude of nutrients excreted and the factors that influence spatial and temporal variability in consumer-derived nutrients. To investigate the supply of ammonium (NH4+) excreted by the dominant members of the nearshore rocky reef fish community, we combined empirically-measured relationships between excretion rate and body mass with data on fish density and size structure from …

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Mitigating Risk: Predicting H5n1 Avian Influenza Spread With An Empirical Model Of Bird Movement, Fiona Mcduie, Cory T. Overton, Austen A. Lorenz, Elliott L. Matchett, Andrea L. Mott, Desmond A. Mackell, Joshua T. Ackerman, Susan E.W. De La Cruz, Vijay P. Patil, Diann J. Prosser, John Y. Takekawa, Dennis L. Orthmeyer, Maurice E. Pitesky, Samuel L. Díaz-Muñoz, Brock M. Riggs, Joseph Gendreau, Eric T. Reed, Mark J. Petrie, Chris K. Williams Jan 2024

Mitigating Risk: Predicting H5n1 Avian Influenza Spread With An Empirical Model Of Bird Movement, Fiona Mcduie, Cory T. Overton, Austen A. Lorenz, Elliott L. Matchett, Andrea L. Mott, Desmond A. Mackell, Joshua T. Ackerman, Susan E.W. De La Cruz, Vijay P. Patil, Diann J. Prosser, John Y. Takekawa, Dennis L. Orthmeyer, Maurice E. Pitesky, Samuel L. Díaz-Muñoz, Brock M. Riggs, Joseph Gendreau, Eric T. Reed, Mark J. Petrie, Chris K. Williams

Faculty Research, Scholarly, and Creative Activity

Understanding timing and distribution of virus spread is critical to global commercial and wildlife biosecurity management. A highly pathogenic avian influenza virus (HPAIv) global panzootic, affecting 600 bird and mammal species globally and over 83 million birds across North America (December 2023), poses a serious global threat to animals and public health. We combined a large, long-term waterfowl GPS tracking dataset (16 species) with on-ground disease surveillance data (county-level HPAIv detections) to create a novel empirical model that evaluated spatiotemporal exposure and predicted future spread and potential arrival of HPAIv via GPS tracked migratory waterfowl through 2022. Our model was …

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Next Steps For Assessing Ocean Iron Fertilization For Marine Carbon Dioxide Removal, Ken O. Buesseler, Daniele Bianchi, Fei Chai, Jay T. Cullen, Margaret Estapa, Nicholas Hawco, Seth John, Dennis J. Mcgillicuddy, Paul J. Morris, Sara Nawaz, Nishioka, Anh Pham, Kilaparti Ramakrishna, David A. Siegel, Sarah R. Smith, Deborah Steinberg, Kendra A. Turk-Kubo, Benjamin S. Twining, Romany M. Webb Jan 2024

Next Steps For Assessing Ocean Iron Fertilization For Marine Carbon Dioxide Removal, Ken O. Buesseler, Daniele Bianchi, Fei Chai, Jay T. Cullen, Margaret Estapa, Nicholas Hawco, Seth John, Dennis J. Mcgillicuddy, Paul J. Morris, Sara Nawaz, Nishioka, Anh Pham, Kilaparti Ramakrishna, David A. Siegel, Sarah R. Smith, Deborah Steinberg, Kendra A. Turk-Kubo, Benjamin S. Twining, Romany M. Webb

Faculty Research, Scholarly, and Creative Activity

There are many potential approaches to marine carbon dioxide removal (mCDR), of which ocean iron fertilization (OIF) has the longest history of study. However, OIF studies to date were not primarily designed to quantify the durability of carbon (C) storage, nor how wise OIF might be as an mCDR approach. To quantify C sequestration, we introduce a metric called the “centennial tonne,” defined as 1,000 kg of C isolated from atmospheric contact for on average at least 100 years. We present the activities needed to assess OIF from a scientific and technological perspective, and additionally, how it might be responsibly …

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Resume Content Generation Using Llama 2 With Adapters, Navaneeth Sai Nidadavolu, William B. Andreopoulos Jan 2024

Resume Content Generation Using Llama 2 With Adapters, Navaneeth Sai Nidadavolu, William B. Andreopoulos

Faculty Research, Scholarly, and Creative Activity

This paper presents a novel approach to enhancing the Llama language model for generating customized resumes tailored to domain-specific job descriptions. Unlike traditional methods that rely heavily on extensive fine-tuning, we implement scalable adapter modules to minimize parameter adjustments. This approach preserves the model's inherent ability to generate coherent and contextually appropriate language across diverse tasks, ensuring that its general linguistic capabilities remain intact. Additionally, we employ a prompting strategy to dynamically create a diverse and comprehensive dataset, ensuring high relevance to various job roles. Using a dataset of 10,000 job descriptions and resumes, our approach resulted in a 20% …

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Selective Laser Melting And Mechanical Characterization Of Superalloys Made From Recycled Parts, Hugo Tupac-Yupanqui, Amir Armani Jan 2024

Selective Laser Melting And Mechanical Characterization Of Superalloys Made From Recycled Parts, Hugo Tupac-Yupanqui, Amir Armani

Faculty Research, Scholarly, and Creative Activity

Geometrically complex functional parts from recycled Inconel 718 were additively manufactured and characterized. Scrap parts were melted, recycled, and used in a new gas atomization process to produce the feedstock for a selective laser melting printer. Optimal print parameters were determined using finite element simulations. Standard test methods were employed to experimentally examine the properties of parts, including their density, anisotropic tensile behavior, chemical composition, and fracture surface. The results indicated that scrap Inconel 718 parts can be used to additively manufacture high-quality functional parts. As a case-study, an automotive turbocharger was resigned and additively manufactured based on the findings …

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Student Understanding Of Divergence And Curl In Upper-Division Electromagnetism, J. Toby Stuckey, Gina M. Quan Jan 2024

Student Understanding Of Divergence And Curl In Upper-Division Electromagnetism, J. Toby Stuckey, Gina M. Quan

Faculty Research, Scholarly, and Creative Activity

The purpose of this paper is to understand and characterize student thinking about the physics concepts of divergence and curl in the context of upper-division electromagnetism for physics majors. We interviewed five students at a west coast university who had taken at least one semester of upper-division electricity and magnetism. The interview prompted students to describe divergence and curl in multiple representations (visually, mathematically, qualitatively). Our analysis identified that students can notice but struggle to resolve discrepancies between the mathematical calculations and the graphical representations of vector fields. We illustrate examples of when students appear to have a disconnect between …

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Study Of Using Variational Quantum Linear Solver For Solving Poisson Equation, Nithin Reddy Govindugari, Hiu Yung Wong Jan 2024

Study Of Using Variational Quantum Linear Solver For Solving Poisson Equation, Nithin Reddy Govindugari, Hiu Yung Wong

Faculty Research, Scholarly, and Creative Activity

Quantum computing is promising in speeding up the system of linear equations (SLE) solving process. However, its performance is limited by noise. The variational quantum linear solver (VQLS) algorithm is expected to be more resilient to noise than gate-based quantum computing algorithms. This is because error correction is not available yet and VQLS is based on cost function minimization. In this paper, the gate insulator Poisson equation is solved using VQLS. The results are compared to technology computer-aided design (TCAD) results and gate-based quantum algorithm results. We show that, even without error-free qubits, the IBM-Q quantum computer hardware can solve …

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Tcad Structure Input File Generation Using Large Language Model, Le Minh Long Nguyen, Albert Lu, Hiu Yung Wong Jan 2024

Tcad Structure Input File Generation Using Large Language Model, Le Minh Long Nguyen, Albert Lu, Hiu Yung Wong

Faculty Research, Scholarly, and Creative Activity

In this paper, we study the possibility of using Large Language Models (LLMs) to create Technology Computer-Aided-Design (TCAD) structure generation input files. LLMs are machine learning models trained on vast amounts of text data from the Web and are designed to understand, generate, and interact with humans through natural languages such as English. However, unlike programming languages with abundant training examples on the Web, TCAD examples are scarce. In this work, by using TCAD Sentaurus Structure Editor (SSE) as an example, 7000 nanowire data are generated to fine-tune open-source models (Llama 2 and 3) to obtain chatbots that can generate …

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Towards A Context-Contingent Stage Theory Of Entrepreneurial Opportunity: Introducing The Petii Model, Xiaohong Iris Quan Jan 2024

Towards A Context-Contingent Stage Theory Of Entrepreneurial Opportunity: Introducing The Petii Model, Xiaohong Iris Quan

Faculty Research, Scholarly, and Creative Activity

Understanding opportunity is a crucial aspect of entrepreneurship research. Existing studies have extensively examined individual factors in facilitating entrepreneurial activities such as new venture creation. Although there are some discussions on contextual factors, few connect context with the origin of entrepreneurship—opportunity. Recognising the objectivity of entrepreneurial opportunity, this theoretical article first proposes two types of opportunities—innovative opportunity and imitative opportunity—to understand the nature of opportunity. It then proposes a systematic framework—the PETII (Population, Economic status, Technological advancement, Industry life cycle, Institutions) model—to analyse the role of context in the distribution of opportunity. Furthermore, it examines how both objective contextual factors …

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Optimal Tool Path For Extrusion-Based Additive Manufacturing To Improve Geometrical Accuracy And Productivity, Robert Ehlers, Amir Armani Jan 2024

Optimal Tool Path For Extrusion-Based Additive Manufacturing To Improve Geometrical Accuracy And Productivity, Robert Ehlers, Amir Armani

Faculty Research, Scholarly, and Creative Activity

The objective of this study was to improve the geometrical accuracy and productivity of extrusion-based additive manufacturing processes. Four algorithms were developed to adaptively change the track width in each layer (i.e., adaptive rastering); optimize the rastering orientation for each layer; adaptively change the layer thickness (i.e., adaptive slicing); and optimize the overall orientation of part. These algorithms were implemented in a commercial 3D printer and several case-studies were conducted to examine their efficacy (individually and combined). The results were compared with standard tool path planning software and indicated a significant improvement in both geometrical accuracy and productivity.

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Navigating Enterprise Constraints: Building A Hybrid Multi-Modal Mobile Intelligent App, Ketan Malempati, Akshat Gupta, Kaikai Liu Jan 2024

Navigating Enterprise Constraints: Building A Hybrid Multi-Modal Mobile Intelligent App, Ketan Malempati, Akshat Gupta, Kaikai Liu

Faculty Research, Scholarly, and Creative Activity

The promise of artificial intelligence (AI) has prompted various industries to explore how it can enhance their businesses and improve customer experiences. However, the practical deployment of AI services faces challenges due to internal infrastructure limitations, data policies, and network restrictions. In this paper, we present our current project - a solution designed to empower mental health centers with AI tools while adhering to stringent data and network constraints. Our approach involves deploying AI services and data within internal enterprise networks, while the customer-facing mobile app resides in the public cloud. We introduce a custom AI agent system that monitors …

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Rescaling: Change Agency And The Emerging Geography Of Economic Relationships, Markus Grillitsch, Björn Asheim, Nichola Lowe, Sophie Kelmenson, Lea Fünfschilling, Karl Johan Lundquist, Yahia Mahmoud, Mikhail Martynovich, Pauline Mattsson, Magnus Nilsson, Johan Miörner, Torben Schubert Jan 2024

Rescaling: Change Agency And The Emerging Geography Of Economic Relationships, Markus Grillitsch, Björn Asheim, Nichola Lowe, Sophie Kelmenson, Lea Fünfschilling, Karl Johan Lundquist, Yahia Mahmoud, Mikhail Martynovich, Pauline Mattsson, Magnus Nilsson, Johan Miörner, Torben Schubert

Faculty Research, Scholarly, and Creative Activity

In this paper, we propose a theoretical and conceptual framework for articulating and studying changes in the global economic landscape and illustrate this framework in the current context. The framework pivots around the notion of rescaling, which is interpreted from a human agency perspective. We disentangle three theoretically distinct dimensions of rescaling and show how they play together using concrete examples. The theoretical and conceptual framework links the intended and unintended consequences of globalisation to current rescaling efforts, and allows us to investigate when, why, and how changes to the geography of economic relationships occur.

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Assessment Of Digital Collaboration Skills, Esperanza Huerta, Ana Lidia Franzoni Velázquez, Scott Jensen Jan 2024

Assessment Of Digital Collaboration Skills, Esperanza Huerta, Ana Lidia Franzoni Velázquez, Scott Jensen

Faculty Research, Scholarly, and Creative Activity

This exploratory study proposes a methodology for assessing digital collaboration skills based on the students' actual behavior. Students' comments using a digital collaboration tool during a one-month long project were manually coded. This methodology is not context specific and can be used across different domains. This assessment contrasts with self-reported measures in which students rate themselves as already possessing collaboration skills. Finally, the study explores the use of generative AI to automatically code student's comments to alleviate the labor-intensive process that coding requires and to enable scalability in coding data.

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A Fresh Take: Seasonal Changes In Terrestrial Freshwater Inputs Impact Salt Marsh Hydrology And Vegetation Dynamics, Maya S. Montalvo, Emilio Grande, Anna E. Braswell, Ate Visser, Bhavna Arora, Erin C. Seybold, Corianne Tatariw, John C. Haskins, Charlie A. Endris, Fuller Gerbl, Mong Han Huang, Darya Morozov, Margaret A. Zimmer Jan 2024

A Fresh Take: Seasonal Changes In Terrestrial Freshwater Inputs Impact Salt Marsh Hydrology And Vegetation Dynamics, Maya S. Montalvo, Emilio Grande, Anna E. Braswell, Ate Visser, Bhavna Arora, Erin C. Seybold, Corianne Tatariw, John C. Haskins, Charlie A. Endris, Fuller Gerbl, Mong Han Huang, Darya Morozov, Margaret A. Zimmer

Faculty Research, Scholarly, and Creative Activity

Salt marshes exist at the terrestrial-marine interface, providing important ecosystem services such as nutrient cycling and carbon sequestration. Tidal inputs play a dominant role in salt marsh porewater mixing, and terrestrially derived freshwater inputs are increasingly recognized as important sources of water and solutes to intertidal wetlands. However, there remains a critical gap in understanding the role of freshwater inputs on salt marsh hydrology, and how this may impact marsh subsurface salinity and plant productivity. Here, we address this knowledge gap by examining the hydrologic behavior, porewater salinity, and pickleweed (Sarcocornia pacifica also known as Salicornia pacifica) plant productivity along …

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Fuzzy Similarity Analysis Of Effective Training Samples To Improve Machine Learning Estimations Of Water Quality Parameters Using Sentinel-2 Remote Sensing Data, Alireza Taheri Dehkordi, Mohammad Javad Valadan Zoej, Ali Mehran, Mohsen Jafari, Amir Masoud Chegoonian Jan 2024

Fuzzy Similarity Analysis Of Effective Training Samples To Improve Machine Learning Estimations Of Water Quality Parameters Using Sentinel-2 Remote Sensing Data, Alireza Taheri Dehkordi, Mohammad Javad Valadan Zoej, Ali Mehran, Mohsen Jafari, Amir Masoud Chegoonian

Faculty Research, Scholarly, and Creative Activity

Continuous monitoring of water quality parameters (WQPs) is crucial due to the global degradation of water quality, primarily caused by climate change and population growth. Typically, machine learning (ML) models are employed to retrieve WQPs, but they require a large amount of training samples to accurately capture the data relationships. Even with sufficient training data, discrepancies still exist between values of predicted and in-situ WQPs. This study proposes a fuzzy similarity analysis (FSA) technique to enhance ML estimates of WQPs by using the prediction errors in effective training samples. The method was successfully applied to retrieve turbidity (Turb) and specific …

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Using Problem-Based Exploratory Training To Improve Pilot Understanding Of Autopilot Functions, Jordy K.Van Leeuwen, Annemarie Landman, Eric L. Groen, Randall J. Mumaw, Olaf Stroosma, Marinus M.Van Paassen, Max Mulder Jan 2024

Using Problem-Based Exploratory Training To Improve Pilot Understanding Of Autopilot Functions, Jordy K.Van Leeuwen, Annemarie Landman, Eric L. Groen, Randall J. Mumaw, Olaf Stroosma, Marinus M.Van Paassen, Max Mulder

Faculty Research, Scholarly, and Creative Activity

Previous research indicated a need to improve pilot training with regard to understanding of autopilot logic and behavior, especially in non-routine situations. Therefore, we tested the effect of problem-based exploratory training on pilots’ understanding of autopilot functions. Using a moving-base flight simulator, general aviation pilots (n = 45) were trained to diagnose failures either without foreknowledge and guidance (exploratory group), without foreknowledge but with some guidance (exploratory-guidance group) or with foreknowledge and full guidance (control group). They subsequently performed six test scenarios in which their understanding of the effects of failures was tested by requiring them to deduce the failures …

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The Effect Of A Night Shift Nap On Post-Night Shift Performance, Sleepiness, Mood, And First Recovery Sleep: A Randomized Crossover Trial, P. Daniel Patterson, Cassie J. Hilditch, Matthew D. Weaver, David G.L. Roach, Tiffany S. Okerman, Sarah E. Martin, Charity G. Patterson, Leonard S. Weiss Jan 2024

The Effect Of A Night Shift Nap On Post-Night Shift Performance, Sleepiness, Mood, And First Recovery Sleep: A Randomized Crossover Trial, P. Daniel Patterson, Cassie J. Hilditch, Matthew D. Weaver, David G.L. Roach, Tiffany S. Okerman, Sarah E. Martin, Charity G. Patterson, Leonard S. Weiss

Faculty Research, Scholarly, and Creative Activity

Objectives This study aimed to test the effect of a 30-minute nap versus a 2-hour nap opportunity taken during a simulated night shift on performance, fatigue, sleepiness, mood, and sleep at the end of shift and during post-night shift recovery. Methods We conducted a randomized crossover trial of three nap conditions (30-minute, 2-hour, and no-nap) during 12-hour simulated night shifts. We tested for differences in performance, fatigue, sleepiness, mood, and sleep during in-lab and at-home recovery. Performance was measured with the Brief Psychomotor Vigilance Test (PVT-B). Subjective ratings were assessed with single-item surveys. Results Twenty-eight individuals consented to participate [mean …

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Lessons From A Professional Learning Community: Navigating Tensions While Moving Between Theory And Practice In Teaching Chemistry For Social Justice, Kathryn Ribay Jan 2024

Lessons From A Professional Learning Community: Navigating Tensions While Moving Between Theory And Practice In Teaching Chemistry For Social Justice, Kathryn Ribay

Faculty Research, Scholarly, and Creative Activity

Maintaining a commitment to social justice teaching can be especially challenging when navigating the bureaucratic systems and ever-spiraling responsibilities of the education system. To better understand how social-justice-oriented educators navigate these tensions, this paper uses qualitative methods to investigate the social justice problems of practice identified by five chemistry teachers in a year-long professional learning community. By analyzing the challenges described in their problem-posing segments, I identify seven major themes that represent key sources of tension and possibility as teachers move from theory to practice in teaching chemistry for social justice. These findings indicate that the practical considerations of day-to-day …

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Clots Reveal Anomalous Elastic Behavior Of Fiber Networks, Andrei Zakharov, Myra Awan, Terrence Cheng, Arvind Gopinath, Sang Joon John Lee, Anand K. Ramasubramanian, Kinjal Dasbiswas Jan 2024

Clots Reveal Anomalous Elastic Behavior Of Fiber Networks, Andrei Zakharov, Myra Awan, Terrence Cheng, Arvind Gopinath, Sang Joon John Lee, Anand K. Ramasubramanian, Kinjal Dasbiswas

Faculty Research, Scholarly, and Creative Activity

The adaptive mechanical properties of soft and fibrous biological materials are relevant to their functionality. The emergence of the macroscopic response of these materials to external stress and intrinsic cell traction from local deformations of their structural components is not well understood. Here, we investigate the nonlinear elastic behavior of blood clots by combining microscopy, rheology, and an elastic network model that incorporates the stretching, bending, and buckling of constituent fibrin fibers. By inhibiting fibrin cross-linking in blood clots, we observe an anomalous softening regime in the macroscopic shear response as well as a reduction in platelet-induced clot contractility. Our …

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