Open Access. Powered by Scholars. Published by Universities.®
- Institution
-
- Air Force Institute of Technology (26)
- Old Dominion University (12)
- California Polytechnic State University, San Luis Obispo (8)
- Southern Methodist University (8)
- University of Arkansas, Fayetteville (6)
-
- University of Nebraska - Lincoln (6)
- Embry-Riddle Aeronautical University (5)
- Purdue University (5)
- Clemson University (4)
- Florida Institute of Technology (4)
- Louisiana State University (4)
- Louisiana Tech University (4)
- Michigan Technological University (4)
- Technological University Dublin (4)
- Indian Statistical Institute (3)
- Mississippi State University (3)
- University of Kentucky (3)
- Washington University in St. Louis (3)
- Binghamton University (2)
- Indiana State University (2)
- Missouri University of Science and Technology (2)
- The University of Southern Mississippi (2)
- University of Connecticut (2)
- University of New Mexico (2)
- Utah State University (2)
- Brigham Young University (1)
- Bucknell University (1)
- COBRA (1)
- California State University, San Bernardino (1)
- Central Mining Institute (1)
- Keyword
-
- Statistics (9)
- Machine Learning (7)
- Forecasting (5)
- Machine learning (5)
- Regression (5)
-
- Optimization (4)
- Pure sciences (4)
- Statistical analysis (4)
- Applied sciences (3)
- Goodness-of-fit tests (3)
- Simulation (3)
- Artificial Intelligence (2)
- Calculation (2)
- Deep Learning (2)
- Deep learning (2)
- Degradation (2)
- Energy (2)
- Filtering (2)
- Gaussian process (2)
- LSTM (2)
- Lidar (2)
- Lightning (2)
- Logistic Regression (2)
- Manufacturing (2)
- Matlab (2)
- Monte Carlo method (2)
- Prediction (2)
- Public transportation (2)
- Random forest (2)
- Remote sensing (2)
- Publication Year
- Publication
-
- Theses and Dissertations (29)
- SMU Data Science Review (7)
- Master's Theses (6)
- Faculty Publications (5)
- All Theses (4)
-
- Dissertations, Master's Theses and Master's Reports (4)
- Doctoral Dissertations (4)
- Engineering Management & Systems Engineering Theses & Dissertations (4)
- Graduate Theses and Dissertations (4)
- Mechanical & Aerospace Engineering Theses & Dissertations (4)
- Articles (3)
- Journal Articles (3)
- All-Inclusive List of Electronic Theses and Dissertations (2)
- Department of Industrial and Management Systems Engineering: Instructional Materials (2)
- Electrical and Computer Engineering ETDs (2)
- International Journal of Aviation, Aeronautics, and Aerospace (2)
- LSU Doctoral Dissertations (2)
- LSU Master's Theses (2)
- McKelvey School of Engineering Graduate Student Theses & Dissertations (2)
- Northeast Journal of Complex Systems (NEJCS) (2)
- 15th International Conference on Shot Peening (1)
- All ECSTATIC Materials (1)
- Basic Science Engineering (1)
- Biological and Agricultural Engineering Undergraduate Honors Theses (1)
- Browse all Datasets (1)
- CRHR: Archaeology (1)
- Civil & Environmental Engineering Theses & Dissertations (1)
- Civil and Environmental Engineering Theses and Dissertations (1)
- College of Education and Human Sciences: Dissertations, Theses, and Student Research (1)
- Computer Science and Software Engineering (1)
- Publication Type
- File Type
Articles 1 - 30 of 154
Full-Text Articles in Applied Statistics
Predicting Passenger Demand On National Flights Departing From Hartsfield-Jackson Atlanta International Airport (Atl) In 2024, Brooklyn Gossett, Ana Yu Wen
Predicting Passenger Demand On National Flights Departing From Hartsfield-Jackson Atlanta International Airport (Atl) In 2024, Brooklyn Gossett, Ana Yu Wen
Discovery Day - Daytona Beach
The aviation industry relies heavily on accurate demand forecasting to guide critical decisions regarding route planning, capacity management, and pricing strategy. Misjudging passenger demand can result in significant revenue loss and operational inefficiency, making it essential for airlines and analysts to identify the key drivers of flight patronage. This study investigates the factors that most significantly predict the number of passengers on domestic flights departing from Hartsfield-Jackson Atlanta International Airport (ATL) during the 2024 calendar year. Using passenger and route data sourced from the Bureau of Transportation Statistics (BTS) and the U.S. Department of Transportation (DOT), a multiple regression analysis …
Ground To Roof Snow Load Ratio (Gr) Data Release, Brennan Bean, Cooper Nelson, Jesse Wheeler, Scout Jarman, Salam Adil Al-Rubaye, Marc Maguire
Ground To Roof Snow Load Ratio (Gr) Data Release, Brennan Bean, Cooper Nelson, Jesse Wheeler, Scout Jarman, Salam Adil Al-Rubaye, Marc Maguire
Browse all Datasets
This data release provides historical ground-to-roof snow load ratio (GR) datasets used for snow load research and model development. The release includes original referenced datasets, cleaned country specific datasets, and a master dataset that combines Canadian and United States datasets into a standardized format for research and engineering applications.
An Analytical Framework For Quantifying Urban And Community Resilience To Natural Hazards From Cell-Phone Gps-Location And Traffic-Flow Data, Georgios Chatzikyriakidis
An Analytical Framework For Quantifying Urban And Community Resilience To Natural Hazards From Cell-Phone Gps-Location And Traffic-Flow Data, Georgios Chatzikyriakidis
Civil and Environmental Engineering Theses and Dissertations
Urban areas are increasingly exposed to natural hazards while accommodating a growing share of the global population, yet a consistent science-based framework for quantifying urban and community resilience remains lacking. This dissertation develops a physics-based analytical framework grounded in statistical mechanics and the quantitative theory of Brownian motion. A city is conceptualized as a complex medium in which citizens move analogously to Brownian particles within a viscoelastic environment, influenced by socioeconomic interactions and infrastructure functionality.
A central premise is that urban resilience, interpreted as engineering resilience (an outcome), can be quantified through a single metric: the mean-square displacement MSD=⟨r²(t)⟩, of …
Factors Affecting Pedestrian-Vehicle Conflicts: An Empirical Analysis, Christo D. Jamo
Factors Affecting Pedestrian-Vehicle Conflicts: An Empirical Analysis, Christo D. Jamo
Honors Scholar Theses
The number of pedestrian deaths increased by 78% between 2009 and 2023, while other motor vehicle crash deaths increased by 13% in the same period [1]. To identify potential pedestrian safety measures, this study analyzed the effects of location-based demographics, pedestrian phasing type, and other physical infrastructure and behavior variables on the probability of pedestrian-vehicle conflicts at signalized intersections, which is a surrogate measure of crash risk. Data were collected from 55 intersections in Connecticut, and the pedestrian-vehicle interactions were classified by severity based on the Swedish Traffic Conflict Technique: undisturbed passage, potential conflict, minor conflict, or serious conflict. Because …
Feasibility Study Of Transitioning From Thick Plates (0.250”) Mounted On 30-Point Pvc Carriers To Thinner Plate Technologies Mounted On Recyclable Foam And Pet (0.155”) For Post-Print Corrugated, Nathaniel J. Poole
All Theses
In the United States, the most common press configuration for brown-box printing is a 0.280” undercut press. These press configurations have long relied on thick 0.250” plates mounted on 0.030” PVC sheets to print onto corrugated substrates. Each year, around twenty million pounds of waste are produced by the printing industry, through paper waste, plate waste, among other materials. One large factor of that waste is flexographic plate waste, which either ends its life in a landfill or is repurposed into other products. This study establishes a comparison between traditionally used 0.250” plates on 30pt PVC versus 0.155” plates mounted …
A New Approach To Generate Combinatorial Patterns In Logical Analysis Of Data And Its Application To Predict College Retention, Salihah Ahmed E. Jaafari
A New Approach To Generate Combinatorial Patterns In Logical Analysis Of Data And Its Application To Predict College Retention, Salihah Ahmed E. Jaafari
Theses and Dissertations
Student retention and degree completion remain central challenges for higher-education institutions, with significant implications for student success, institutional effectiveness, and public accountability. While advances in predictive analytics have enabled earlier identification of students at risk of withdrawal, many commonly used machine learning approaches suffer from limited interpretability, constraining their practical usefulness for advising, intervention, and policy decision making. This dissertation addresses the problem of predicting student persistence by developing and evaluating optimization based, interpretable classification models within the Logical Analysis of Data (LAD) framework. Building on existing LAD formulations, this research introduces two novel pattern generation models, the Best Term …
Preliminary Sonification Of Enso Using Traditional Javanese Gamelan Scales, Sandy Hs Herho, Rusmawan Suwarman, Nurjanna J. Trilaksono, Iwan P. Anwar, Faiz R. Fajary
Preliminary Sonification Of Enso Using Traditional Javanese Gamelan Scales, Sandy Hs Herho, Rusmawan Suwarman, Nurjanna J. Trilaksono, Iwan P. Anwar, Faiz R. Fajary
Northeast Journal of Complex Systems (NEJCS)
Sonification—the mapping of data to non-speech audio—offers an underexplored channel for representing complex dynamical systems. We treat El Niño-Southern Oscillation (ENSO), a canonical example of low-dimensional climate chaos, as a test case for culturally-situated sonification evaluated through complex systems diagnostics. Using parameter-mapping sonification of the Niño 3.4 sea surface temperature anomaly index (1870–2024), we encode ENSO variability into two traditional Javanese gamelan pentatonic systems (pelog and slendro) across four composition strategies, then analyze the resulting audio as trajectories in a two- dimensional acoustic phase space. Recurrence-based diagnostics, convex hull ge- ometry, and coupling analysis reveal that the sonification …
Statistical Analysis Of Log Transformation Effectiveness In Air Traffic Movement Forecasting During Covid-19 In South Africa, John Lehlaka Masekoameng
Statistical Analysis Of Log Transformation Effectiveness In Air Traffic Movement Forecasting During Covid-19 In South Africa, John Lehlaka Masekoameng
Journal of Aviation Technology and Engineering
This study evaluates the effectiveness of log transformation in enhancing multiple regression models used to forecast air traffic movements (ATMs) in South Africa during the COVID-19 pandemic. Using 60 monthly observations from October 2016 to September 2021, the analysis incorporates variables such as revenue, lockdown levels, COVID-19 metrics, exchange rates, gross domestic product, and population. Two models are compared: one using raw ATMs and another with log-transformed ATMs as the dependent variable.
While the untransformed model shows stronger explanatory power (R² = 0.904, adjusted R² = 0.891) compared to the log-transformed model (R² = 0.772, adjusted R² = 0.741), the …
A Bump Hunting Approach To Finding Interpretable Data Pockets, Tushar Ojha
A Bump Hunting Approach To Finding Interpretable Data Pockets, Tushar Ojha
Electrical and Computer Engineering ETDs
This dissertation approaches the problem of extracting simple interpretations from local regions of data. This is sometimes called bump hunting because the local regions of interest have a high concentration of a particular output value. This work develops a bump hunting method for discrete-valued tabular data where each bump is modeled by a rectangular region of the input data space so its rule-based description admits a simple logical interpretation that can inform decisions. This method is designed for labeled data where each input feature has a distinct meaning that may or may not be related to the output, and the …
Component Model Development Of Heat Exchangers, Expanders, And Control Valves For Autonomous Cryogenics Plant Cool-Down, William Harris Buhrig Iv
Component Model Development Of Heat Exchangers, Expanders, And Control Valves For Autonomous Cryogenics Plant Cool-Down, William Harris Buhrig Iv
Mechanical & Aerospace Engineering Theses & Dissertations
The traditional method of cryogenic plant cool-down involves having continuous on-call staff to head into the office at any time to modify the existing multi-layered PID control systems if the on-call staff member detects a significant deviation from the cool-down plan. This thesis aims to outline an effective method for modeling the structure of systems with performance characteristics that deviate from design requirements and from ideal inlet-outlet correspondence, enabling the adjustment and modification of existing control structures across all Thomas Jefferson National Accelerator Facility (JLab) cryogenic refrigeration plants. Analytical Modeling and Gaussian Process Regression (GPR) are applied to model the …
Reduced Order Approach For Peening Stress Field Variability, Langdon Feltner, Paul Mort
Reduced Order Approach For Peening Stress Field Variability, Langdon Feltner, Paul Mort
15th International Conference on Shot Peening
A common goal in shot peening research is to connect operational parameters to resultant residual stress fields, providing a means to control and optimize the effectiveness of surface treatment. In practice, experimental measurements of residual stresses are often averaged values over regions that are large in comparison to an impact dimple. In fact, the stochastic nature of impact locations leads to residual stress fields that are distributed. Finite element peening simulations confirm this observation. The goal of this report is to connect operational parameters to localized fluctuations in residual stress through probabilistic reasoning (Figure 1). In particular, the development of …
Advancing Real-World Implementation Of The Well Optimized Linear Finder (Wolf) High-Speed Atmospheric Turbulence Compensation Method, Timothy Evan Coon
Advancing Real-World Implementation Of The Well Optimized Linear Finder (Wolf) High-Speed Atmospheric Turbulence Compensation Method, Timothy Evan Coon
Theses and Dissertations
This dissertation advances the real-world implementation of the Well Optimized Linear Finder (WOLF) method for high-speed Atmospheric Turbulence Compensation (ATC). Atmospheric turbulence introduces phase aberrations into optical wavefronts and degrades image quality in terrestrial imaging systems. Traditional phase diversity methods are computationally intensive and poorly suited to real-time operation. The WOLF method addresses these limitations through a novel, point-wise formulation of the optical transfer function (OTF) as a structured autocorrelation of the generalized pupil function (GPF). This formulation enables the estimation of phase aberrations at individual spatial coordinates with distributed computational complexity.
The research begins by developing a MATLAB-based simulation …
Unified Hybrid Censoring Samples From Power Pratibha Distribution And Its Applications, Mahmoud Mansour, Hebatalla H. Mohammad Dr, Khalaf S. Sultan Prof.
Unified Hybrid Censoring Samples From Power Pratibha Distribution And Its Applications, Mahmoud Mansour, Hebatalla H. Mohammad Dr, Khalaf S. Sultan Prof.
Basic Science Engineering
This paper suggests an extensive inferential method for the Power Pratibha Distribution (PPD) under Unified Hybrid Censoring Schemes (UHCSs), since there is a growing interest in flexible models in both reliability and service operations. This work studies the PPD model using standard Maximum Likelihood Estimation methods and modern Bayesian approaches too. Using a complex architecture, UHCS simulates tests more closely to what is done in practice than by using more basic censoring schemes. Using analysis, the probability and statistical ranges are carefully calculated for the parameters. Tests demonstrate that Bayesian estimation gives better results than many other methods for estimation, …
Syntax-Enhanced Boundary-Aware Named Entity Recognition Model, Chuanming Yu, Bin Deng, Zhengang Zhang
Syntax-Enhanced Boundary-Aware Named Entity Recognition Model, Chuanming Yu, Bin Deng, Zhengang Zhang
Journal of Scientific Information Research
[Purpose/significance] This study addresses the issue of inadequate perception of entity boundaries in traditional character-level modeling-based named entity recognition models by integrating syntax information containing entity boundary features into the task using a multi-head graph attention network with dense connections. This integration enhances the effectiveness of named entity recognition.
[Method/process] This study proposes a Syntax-enhanced Boundary-aware Named Entity Recognition Model (SynBNER), which utilizes BERT for text semantic representation and integrates syntax information using a dense-connected graph attention network. This integration incorporates implicit entity boundary information from syntax information into word representations, thereby enhancing the model's entity boundary perception capability.
[Result/conclusion] …
How’S It Growing? Tools For Observing Snow And Sea Ice In A Changing Arctic Ocean, Ian Alexander Raphael
How’S It Growing? Tools For Observing Snow And Sea Ice In A Changing Arctic Ocean, Ian Alexander Raphael
Dartmouth College Ph.D Dissertations
September Arctic sea ice extent has diminished by roughly 50% in the 45 years since satellite observations began. The Arctic Ocean may experience ice-free summers within the next decade, with implications for habitat, resource extraction, geopolitics, and local and global climate change. To predict how Arctic sea ice will change in the future, we need to understand its behavior in the present. In situ sea ice mass balance measurements (snow accumulation, ice growth, snow and ice surface melt, and bottom melt) are essential for studying the processes driving rapid changes in the ice pack, and for validating remote sensing measurements …
Data Driven Analysis Of Samara Seed Kinematics And Dynamics, Shashwat Sparsh
Data Driven Analysis Of Samara Seed Kinematics And Dynamics, Shashwat Sparsh
Master's Theses
Samara Seeds are a class of fruit most famously belonging to the Acer species and are characterized by their single-bladed geometry and their auto-rotation response during descent. This steady-state auto-rotation response is the subject of aerodynamic analysis which aim to quantify the performance. The period prior to the beginning of steady-state auto-rotation is classified as the transition regime and has not been the subject of intense scrutiny.
This thesis employs a data-driven approach to analyzing the kinematic and dynamic response of these seeds during both the transition and auto-rotation stages of flight to quantify the performance with respect to the …
Impacts Of Cognitive Workload On Veteran Driver Reaction Time: Predictive Modeling Using Bayesian And Machine Learning Methods, Kenneth Ofosu-Kwabe
Impacts Of Cognitive Workload On Veteran Driver Reaction Time: Predictive Modeling Using Bayesian And Machine Learning Methods, Kenneth Ofosu-Kwabe
All Theses
In high-demand environments, the ability to manage cognitive workload can mean the difference between optimal or safe performance and critical failure or accidents. Veterans face an elevated risk of fatal motor vehicle accidents due to post-deployment stress, combat-related injuries, and challenges readjusting to civilian driving. This study explores how cognitive workload affects reaction time performance using a driving simulator by collecting and analyzing subjective workload ratings (using the NASA-TLX survey), physiological signals from eye-tracking and performance data from a sample of 28 Veterans.
We examined how task difficulty, cognitive indicators and personal attributes influence reaction times across an interactive driving …
Expressive And Interpretable User Engagement Prediction Using Multivariate Survival Processes, Akshay Aravamudan
Expressive And Interpretable User Engagement Prediction Using Multivariate Survival Processes, Akshay Aravamudan
Theses and Dissertations
The ability to characterize how information diffuses online is of paramount importance to stakeholders that are interested in tasks such as proposing solutions for mitigating and countering dis/misinformation, predicting user engagement of content in social media, planning marketing campaigns to roll-out products and planning dissemination of political campaign messaging among others. One such facet of learning the dynamics of information diffusion is the ability to predict user engagement or the popularity of a single piece of information as it spreads through an online medium. Existing works in this regard mainly either obfuscate user level information or utilize frameworks that are …
Robust Spacecraft Autonomy For Deep Space Exploration In Special Euclidean Group Se(3), Matthew Wittal
Robust Spacecraft Autonomy For Deep Space Exploration In Special Euclidean Group Se(3), Matthew Wittal
Doctoral Dissertations and Master's Theses
Over the past half-century, humanity has gained extensive experience conducting manned spaceflight near Earth. Arguably, "near Earth" could even include the Moon — the most distant destination humans have reached. However, "near" in this work primarily refers low Earth orbit (LEO). One could argue that we have not truly left Earth since the Apollo, as spacecraft in some LEOs remain subject to atmospheric drag thus emphasizing their continued connection to Earth's immediate environment. Reflecting on this, it becomes clear that humanity has largely remained bound to Earth’s immediate vicinity since the Apollo missions reached the Moon. However, that is set …
Analysis Of Systematic Trade-Offs Between Military And Healthcare Expenditure Alongside Gdp Growth Of Select Asian And Western Exporting Economies In The 21st Century, Rahul Balamurugan, Carlos Gershenson, Preethi Nanjundan, Hiroki Sayama
Analysis Of Systematic Trade-Offs Between Military And Healthcare Expenditure Alongside Gdp Growth Of Select Asian And Western Exporting Economies In The 21st Century, Rahul Balamurugan, Carlos Gershenson, Preethi Nanjundan, Hiroki Sayama
Northeast Journal of Complex Systems (NEJCS)
This study explores the complexity in the trade-offs between military expenditure, healthcare expenditure, and GDP growth across select Asian nations and major weapon-exporting countries, examining how nations allocate finite resources between national security and human well-being over the past two decades. Using a systems science approach, the research integrates Granger causality testing to analyze temporal and directional relationships among GDP growth, military expenditure, and healthcare expenditure, uncovering their dynamic interdependencies. The methodology includes trend and slope analysis, Granger causality testing, outlier detection, and clustering to identify heterogeneity in resource allocation strategies. Developed, weapon-exporting nations exhibit complementary trends, with strong causality …
Optimized Hiv/Aids Resource Allocation In Ohio: A Linear Programming Approach, Godfred Ahenkroa Kesse
Optimized Hiv/Aids Resource Allocation In Ohio: A Linear Programming Approach, Godfred Ahenkroa Kesse
Data Science and Data Mining
This study employs a linear and integer programming approach to optimize HIV resource allocation in Ohio, aiming to minimize new infections and enhance the impact of limited resources. With the advances in HIV prevention and treatment, Ohio faces challenges in addressing disparities in access to healthcare, particularly among high-risk populations. The proposed model integrates data on infection rates, transmission patterns, demographic factors, and cost-effectiveness to provide a decision-support framework for policymakers. Using epidemiological data and equity constraints, the model prioritizes high-risk regions and populations while ensuring fair resource distribution. Results indicate that increased funding allocations significantly enhance the potential to …
Evaluation Of Practical Methods To Determine If A Karst Creek Is Gaining Or Losing: Case Study Of Leith Creek, Elizabeth Jones
Evaluation Of Practical Methods To Determine If A Karst Creek Is Gaining Or Losing: Case Study Of Leith Creek, Elizabeth Jones
Graduate Theses/Dissertations
Karst landscapes are abundant in Missouri, with features such as caves, springs, and sinkholes that form through the dissolution of limestone. Leith Creek is a small stream in Polk County, Missouri fed by two springs and the shallow unconfined Springfield Plateau aquifer, a highly karstified aquifer which is made up of limestone and minor interbedded shale-mudstone units. To determine if Leith Creek is gaining or losing, stream flow, water chemistry and temperature sensors were monitored. Stream flow results required multiple visits to take measurements while temperature sensors required two visits, one to install the dataloggers and another to remove the …
Effects Of Chain Length, Saturation, And Bases On Saponification, Sarah Fenik
Effects Of Chain Length, Saturation, And Bases On Saponification, Sarah Fenik
Williams Honors College, Honors Research Projects
This project will analyze the effects of chain length and saturation of fatty acids on saponification processes, as well as the effects of the base used in the reaction. Stearic acid, lauric acid, and oleic acid will be used for the fatty acid comparisons, and sodium hydroxide and potassium hydroxide will be used for the base comparisons. Stearic acid is considered a long chain fatty acid, while lauric acid is considered a short chain fatty acid. Oleic acid is a monounsaturated fatty acid. Five soap products are be made: sodium stearate, sodium laurate, sodium oleate, potassium stearate, and potassium oleate. …
Modeling Neighborhoods As Fuel For Wildfire, Bryce Alan Young
Modeling Neighborhoods As Fuel For Wildfire, Bryce Alan Young
Graduate Student Theses, Dissertations, & Professional Papers
Wildfire models drive billions of dollars in risk mitigation efforts. However, the modeling community currently lacks a representative fuelscape on which to base simulations of fire spread in the built environment and the wildland-urban interface (WUI) where vegetation and structures act together as fuel for wildfire. This thesis advances wildfire risk modeling by addressing the underdeveloped representation of the built environment in existing frameworks. By identifying inconsistencies in how structure and defensible space features are defined and used across empirical studies, predictive indices, and fire spread models, this research lays the groundwork for standardized modeling approaches and feature selection (Chapter …
Striking A Balance: Market Shock & Responses In Automotive Components Manufacturing, Emma Lane Mcgahey
Striking A Balance: Market Shock & Responses In Automotive Components Manufacturing, Emma Lane Mcgahey
All Theses
This thesis examines the effects of extreme market shocks on supply chain dynamics within the automotive industry. Through an analysis of demand data from an automotive manufacturer to its component suppliers (January 2018 to May 2024), the study investigates the relationship between market shocks and supply chain responses, providing insights into how auto components inventory management handles downstream responses to market shocks. With supporting public data—from FRED, BLS, and the U.S. Census Bureau resources—we explore two primary relationships: the impact of market shocks on the Average Standard Deviation of Demand (SDO) and the effect of demand variability on expedited pricing …
A Strategic Insight Into The Market For Carbon Management Capacity, Mahelet G. Fikru, Ting Shen, Jennifer Brodmann, Hongyan Ma
A Strategic Insight Into The Market For Carbon Management Capacity, Mahelet G. Fikru, Ting Shen, Jennifer Brodmann, Hongyan Ma
Economics Faculty Research & Creative Works
This study presents the market for carbon management capacity via carbon capture, utilization, and storage technologies, identifying demand and supply forces, as well as clarifying the potential impact of market and non-market-based shocks on technology developers versus adopters. The paper addresses a prevailing gap in market analysis, introducing a microeconomic framework and unique dataset to identify key players, market forces, and policy incentives shaping the carbon capture, utilization, and storage landscape. The analysis equips industry stakeholders, policymakers, and investors with valuable insights regarding (1) leaders in the design, development, and manufacture of carbon capture, utilization, and storage technologies (supply), (2) …
Exploring Healthcare Chatbot Information Presentation: Applying Hierarchical Bayesian Regression And Inductive Thematic Analysis In A Mixed Methods Study, Samuel Nelson Koscelny
Exploring Healthcare Chatbot Information Presentation: Applying Hierarchical Bayesian Regression And Inductive Thematic Analysis In A Mixed Methods Study, Samuel Nelson Koscelny
All Theses
High blood pressure, also known as hypertension, significantly increases the risk of heart disease and stroke, which are leading causes of death in the United States. While contributing to over 691,000 deaths in 2021 alone in the United States (U.S.), it also imposes immense economic burden on the healthcare system, costing approximately $131 billion annually. One way to address this issue is for increased self-care behaviors and medication adherence, both of which require sufficient health literacy. Despite the importance of health literacy, 90% of U.S. adults struggle with health-related subjects. Overcoming the issues associated with health literacy requires addressing the …
Gender-Based Service Quality Evaluation Of Multimodal Public Transportation In Dki Jakarta, Mohammad Owais, Jachrizal Sumabrata, Nahry Yusuf
Gender-Based Service Quality Evaluation Of Multimodal Public Transportation In Dki Jakarta, Mohammad Owais, Jachrizal Sumabrata, Nahry Yusuf
Smart City
In DKI Jakarta, despite the extensive infrastructure development, there has been a significant decline in the usage of public transportation. This can be attributed to the inadequate quality of the services provided. Various studies have highlighted the significance of evaluating the quality of service in public transportation to ensure passenger satisfaction and attract new users. However, there is no agreement on the most effective methodology and suitable indicators for conducting such analyses. In addition, there is a growing recognition of the importance of promoting gender equality in multimodal public transportation (MMPT) and understanding gender differences and perceptions of MMPT services. …
Cost-Risk Analysis Of The Ercot Region Using Modern Portfolio Theory, Megan Sickinger
Cost-Risk Analysis Of The Ercot Region Using Modern Portfolio Theory, Megan Sickinger
Master's Theses
In this work, we study the use of modern portfolio theory in a cost-risk analysis of the Electric Reliability Council of Texas (ERCOT). Based upon the risk-return concepts of modern portfolio theory, we develop an n-asset minimization problem to create a risk-cost frontier of portfolios of technologies within the ERCOT electricity region. The levelized cost of electricity for each technology in the region is a step in evaluating the expected cost of the portfolio, and the historical data of cost factors estimate the variance of cost for each technology. In addition, there are several constraints in our minimization problem to …
Representation Learning For Generative Models With Applications To Healthcare, Astronautics, And Aviation, Van Minh Nguyen
Representation Learning For Generative Models With Applications To Healthcare, Astronautics, And Aviation, Van Minh Nguyen
Theses and Dissertations
This dissertation explores applications of representation learning and generative models to challenges in healthcare, astronautics, and aviation.
The first part investigates the use of Generative Adversarial Networks (GANs) to synthesize realistic electronic health record (EHR) data. An initial attempt at training a GAN on the MIMIC-IV dataset encountered stability and convergence issues, motivating a deeper study of 1-Lipschitz regularization techniques for Auxiliary Classifier GANs (AC-GANs). An extensive ablation study on the CIFAR-10 dataset found that Spectral Normalization is key for AC-GAN stability and performance, while Weight Clipping fails to converge without Spectral Normalization. Analysis of the training dynamics provided further …