Impacts Of Covid-19 On Industrial Growth In The United States, 2023 The University of Akron
Impacts Of Covid-19 On Industrial Growth In The United States, Emily G. Warthman, Charles J. Landis
Williams Honors College, Honors Research Projects
COVID-19 has caused massive ramifications on all parts of life in the world and industry growth/decline is not immune to it. This report will analyze nine different industries’ profit and revenue from quarterly data during the years 2009-2022. Forecast models will be generated using various methods and different techniques of validating to predict the values from Q2 2020- Q4 2022 based on historical data. After which, a comparison will be conducted between those predicted values to the actual average revenue and profit generated by order of greatest error percentage made. Thorough research will then be completed to determine if there …
Statistical Intervals For Neural Network And Its Relationship With Generalized Linear Model, 2023 University of Kentucky
Statistical Intervals For Neural Network And Its Relationship With Generalized Linear Model, Sheng Yuan
Theses and Dissertations--Statistics
Neural networks have experienced widespread adoption and have become integral in cutting-edge domains like computer vision, natural language processing, and various contemporary fields. However, addressing the statistical aspects of neural networks has been a persistent challenge, with limited satisfactory results. In my research, I focused on exploring statistical intervals applied to neural networks, specifically confidence intervals and tolerance intervals. I employed variance estimation methods, such as direct estimation and resampling, to assess neural networks and their performance under outlier scenarios. Remarkably, when outliers were present, the resampling method with infinitesimal jackknife estimation yielded confidence intervals that closely aligned with nominal …
Hamilton Cycles In Bidirected Complete Graphs, 2022 Wright State University - Main Campus
Hamilton Cycles In Bidirected Complete Graphs, Arthur Busch, Mohammed A. Mutar, Daniel Slilaty
Mathematics and Statistics Faculty Publications
Zaslavsky observed that the topics of directed cycles in directed graphs and alternating cycles in edge 2-colored graphs have a common generalization in the study of coherent cycles in bidirected graphs. There are classical theorems by Camion, Harary and Moser, Häggkvist and Manoussakis, and Saad which relate strong connectivity and Hamiltonicity in directed "complete" graphs and edge 2-colored "complete" graphs. We prove two analogues to these theorems for bidirected "complete" signed graphs.
Application Of Distributed Fiber-Optic Sensing For Pressure Predictions And Multiphase Flow Characterization, 2022 Louisiana State University and Agricultural and Mechanical College
Application Of Distributed Fiber-Optic Sensing For Pressure Predictions And Multiphase Flow Characterization, Gerald Kelechi Ekechukwu
LSU Doctoral Dissertations
In the oil and gas industry, distributed fiber optics sensing (DFOS) has the potential to revolutionize well and reservoir surveillance applications. Using fiber optic sensors is becoming increasingly common because of its chemically passive and non-magnetic interference properties, the possibility of flexible installations that could be behind the casing, on the tubing, or run on wireline, as well as the potential for densely distributed measurements along the entire length of the fiber. The main objectives of my research are to develop and demonstrate novel signal processing and machine learning computational techniques and workflows on DFOS data for a variety of …
Towards Structured Planning And Learning At The State Fisheries Agency Scale, 2022 Mississippi State University
Towards Structured Planning And Learning At The State Fisheries Agency Scale, Caleb A. Aldridge
Theses and Dissertations
Inland recreational fisheries has grown philosophically and scientifically to consider economic and sociopolitical aspects (non-biological) in addition to the biological. However, integrating biological and non-biological aspects of inland fisheries has been challenging. Thus, an opportunity exists to develop approaches and tools which operationalize planning and decision-making processes which include biological and non-biological aspects of a fishery. This dissertation expands the idea that a core set of goals and objectives is shared among and within inland fisheries agencies; that many routine operations of inland fisheries managers can be regimented or standardized; and the novel concept that current information and operations can …
(R1899) Asymptotic Normality Of The Conditional Hazard Function In The Local Linear Estimation Under Functional Mixing Data, 2022 Djillali Liabes University
(R1899) Asymptotic Normality Of The Conditional Hazard Function In The Local Linear Estimation Under Functional Mixing Data, Amina Goutal, Boubaker Mechab, Omar Fetitah, Torkia Merouan
Applications and Applied Mathematics: An International Journal (AAM)
In this study, we are interested in using the local linear technique to estimate the conditional hazard function for functional dependent data where the scalar response is conditioned by a functional random variable. The asymptotic normality of this constructed estimator is demonstrated under some extreme conditions. Our estimator’s performance is demonstrated through simulations.
(R2024) A New Weighted Poisson Distribution For Over- And Under-Dispersion Situations, 2022 Marien Ngouabi University
(R2024) A New Weighted Poisson Distribution For Over- And Under-Dispersion Situations, Michel Koukouatikissa Diafouka, Gelin Chedly Louzayadio, Rodnellin Onéime Malouata
Applications and Applied Mathematics: An International Journal (AAM)
In this paper, we propose a four-parameter weighted Poisson distribution that includes and generalizes the weighted Poisson distribution proposed by Castillo and Pérez-Casany and the Conway- Maxwell-Poisson distribution, as well as other well-known distributions. It is a distribution that is a member of the exponential family and is an exponential combination formulation between the weighted Poisson distribution proposed by Castillo and Pérez-Casany and the Conway-Maxwell- Poisson distribution. This new distribution with an additional parameter of dispersion is more flexible, and the Fisher dispersion index can be greater than, equal to, or less than one. This last property allows it to …
Statistical Methods For Modern Threats, 2022 Clemson University
Statistical Methods For Modern Threats, Brandon Lumsden
All Dissertations
More than ever before, technology is evolving at a rapid pace across the broad spectrum of biological sciences. As data collection becomes more precise, efficient, and standardized, a demand for appropriate statistical modeling grows as well. Throughout this dissertation, we examine a variety of new age data arising from modern technology of the 21st century. We begin by employing a suite of existing statistical techniques to address research questions surrounding three medical conditions presenting in public health sciences. Here we describe the techniques used, including generalized linear models and longitudinal models, and we summarize the significant associations identified between research …
Statistical Methods For Meta-Analysis In Large-Scale Genomic Experiments, 2022 Old Dominion University
Statistical Methods For Meta-Analysis In Large-Scale Genomic Experiments, Wimarsha Thathsarani Jayanetti
Mathematics & Statistics Theses & Dissertations
Recent developments in high throughput genomic assays have opened up the possibility of testing hundreds and thousands of genes simultaneously. With the availability of vast amounts of public databases, researchers tend to combine genomic analysis results from multiple studies in the form of a meta-analysis. Meta-analysis methods can be broadly classified into two main categories. The first approach is to combine the statistical significance (pvalues) of the genes from each individual study, and the second approach is to combine the statistical estimates (effect sizes) from the individual studies. In this dissertation, we will discuss how adherence to the standard null …
Natural Language Processing For Disaster Tweets, 2022 CUNY New York City College of Technology
Natural Language Processing For Disaster Tweets, Akinyemi D. Apampa, Nan Li
Publications and Research
Our goal is to establish an automatic model that identifies which tweets are about natural disasters based on the content of the tweets. Our method is to construct a decision tree based on keyword searching. We will construct the model using 7,645 tweets and test our model on 3,465 tweets as an assessment of the performance.
Learning Graphical Models Of Multivariate Functional Data With Applications To Neuroimaging, 2022 Clemson University
Learning Graphical Models Of Multivariate Functional Data With Applications To Neuroimaging, Jiajing Niu
All Dissertations
This dissertation investigates the functional graphical models that infer the functional connectivity based on neuroimaging data, which is noisy, high dimensional and has limited samples. The dissertation provides two recipes to infer the functional graphical model: 1) a fully Bayesian framework 2) an end-to-end deep model.
We first propose a fully Bayesian regularization scheme to estimate functional graphical models. We consider a direct Bayesian analog of the functional graphical lasso proposed by Qiao et al. (2019).. We then propose a regularization strategy via the graphical horseshoe. We compare both Bayesian approaches to the frequentist functional graphical lasso, and compare the …
Bayesian Methods For Graphical Models With Neighborhood Selection., 2022 University of Louisville
Bayesian Methods For Graphical Models With Neighborhood Selection., Sagnik Bhadury
Electronic Theses and Dissertations
Graphical models determine associations between variables through the notion of conditional independence. Gaussian graphical models are a widely used class of such models, where the relationships are formalized by non-null entries of the precision matrix. However, in high-dimensional cases, covariance estimates are typically unstable. Moreover, it is natural to expect only a few significant associations to be present in many realistic applications. This necessitates the injection of sparsity techniques into the estimation method. Classical frequentist methods, like GLASSO, use penalization techniques for this purpose. Fully Bayesian methods, on the contrary, are slow because they require iteratively sampling over a quadratic …
Learning From Public Spaces In Historic Cities, 2022 Kennesaw State University
Learning From Public Spaces In Historic Cities, Cody Josh Kucharski
Symposium of Student Scholars
Successful public spaces in cities are key for enhancing social cohesion and improving health and safety. Learning from historic cities involves the development of representational and analytical tools aimed at capturing their essence as places of human interaction. The research reports findings of the spatial analysis of twenty Adriatic and Ionian coastal cities, which addresses the question of how the network of public spaces calibrates different degrees of spatial enclosure necessary for creating successful social interactions. Cities in the littoral region include well-preserved historic centers that are renowned for the successful integration of urban squares into the urban fabric. For …
Evaluation Of Circular Logistic Regression Models With Asymmetrical Link Functions, 2022 Illinois State University
Evaluation Of Circular Logistic Regression Models With Asymmetrical Link Functions, Feridun Tasdan
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Incorporating Interventions To An Extended Seird Model With Vaccination: Application To Covid-19 In Qatar, 2022 Virginia Commonwealth University
Incorporating Interventions To An Extended Seird Model With Vaccination: Application To Covid-19 In Qatar, Elizabeth Amona
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Improving The Accuracy Of Interactive Voice Response (Ivr) Technology For Pediatric Experience Scores, 2022 Ann & Robert H. Lurie Children's Hospital of Chicago
Improving The Accuracy Of Interactive Voice Response (Ivr) Technology For Pediatric Experience Scores, Elizabeth Spaargaren Ms, Mph, Cpxp, Abigail Kozak Mba, Cpxp, Cara Herbener Cpxp, Barbara Lawlor Burke Ma, Cpxp
Patient Experience Journal
The increased use of interactive voice response (IVR) in assessing patient and family experience should be paired with evidence-based practices on how to obtain the most accurate information via this survey mode. We added a brief clarification sentence of the survey scale at the start of the IVR call to improve our experience data both qualitatively and quantitatively. Our setting was an urban pediatric hospital. We gathered lived experiences from our patients, families, and providers to understand and design a change to the IVR survey mode that would reduce survey inaccuracies. Outcome measures were assessed by baseline measurement and post-intervention …
Predicting Insulin Pump Therapy Settings, 2022 Southern Methodist University & Tandem Diabetes Care, Inc
Predicting Insulin Pump Therapy Settings, Riccardo L. Ferraro, David Grijalva, Alex Trahan
SMU Data Science Review
Millions of people live with diabetes worldwide [7]. To mitigate some of the many symptoms associated with diabetes, an estimated 350,000 people in the United States rely on insulin pumps [17]. For many of these people, how effectively their insulin pump performs is the difference between sleeping through the night and a life threatening emergency treatment at a hospital. Three programmed insulin pump therapy settings governing effective insulin pump function are: Basal Rate (BR), Insulin Sensitivity Factor (ISF), and Carbohydrate Ratio (ICR). For many people using insulin pumps, these therapy settings are often not correct, given their physiological needs. While …
Application Of Probabilistic Ranking Systems On Women’S Junior Division Beach Volleyball, 2022 Southern Methodist University
Application Of Probabilistic Ranking Systems On Women’S Junior Division Beach Volleyball, Cameron Stewart, Michael Mazel, Bivin Sadler
SMU Data Science Review
Women’s beach volleyball is one of the fastest growing collegiate sports today. The increase in popularity has come with an increase in valuable scholarship opportunities across the country. With thousands of athletes to sort through, college scouts depend on websites that aggregate tournament results and rank players nationally. This project partnered with the company Volleyball Life, who is the current market leader in the ranking space of junior beach volleyball players. Utilizing the tournament information provided by Volleyball Life, this study explored replacements to the current ranking systems, which are designed to aggregate player points from recent tournament placements. Three …
Understanding Consumers' Use Experience On Electrically Heated Jacket: A Study On Online Review Using Topic Modeling, 2022 Louisiana State University and Agricultural and Mechanical College
Understanding Consumers' Use Experience On Electrically Heated Jacket: A Study On Online Review Using Topic Modeling, Md Nakib-Ul Hasan
LSU Doctoral Dissertations
The demand for heated jackets is anticipated to be fuelled by frequent temperature drops, severe winter weather, and increasing outdoor activities. Electrically heated jackets (EHJ) are primarily marketed through online distribution channels and expansion of online sales channels is expected to boost the global market. Consumers are increasingly relying on online reviews from other consumers to help them decide what to buy. Businesses also actively monitor and manage their online reviews to build trust in their brand and make it more likely that customers will buy. Traditional approaches for assessing customer behavior, such as market research surveys and focus groups, …
Improving Data-Driven Infrastructure Degradation Forecast Skill With Stepwise Asset Condition Prediction Models, 2022 Air Force Institute of Technology
Improving Data-Driven Infrastructure Degradation Forecast Skill With Stepwise Asset Condition Prediction Models, Kurt R. Lamm, Justin D. Delorit, Michael N. Grussing, Steven J. Schuldt
Faculty Publications
Organizations with large facility and infrastructure portfolios have used asset management databases for over ten years to collect and standardize asset condition data. Decision makers use these data to predict asset degradation and expected service life, enabling prioritized maintenance, repair, and renovation actions that reduce asset life-cycle costs and achieve organizational objectives. However, these asset condition forecasts are calculated using standardized, self-correcting distribution models that rely on poorly-fit, continuous functions. This research presents four stepwise asset condition forecast models that utilize historical asset inspection data to improve prediction accuracy: (1) Slope, (2) Weighted Slope, (3) Condition-Intelligent Weighted Slope, and (4) …