Physical Sciences and Mathematics Commons^™

Perspectives On Reproductive Health Education Among Javanese Parents, Bagoes Widjanarko, Ratih Indraswari, Aditya Kusumawati, Novia Handayani

Kesmas

This study aimed to investigate the perspectives of reproductive health education among Javanese parents of children aged 9-11 years. This cross-sectional study was conducted with 12,306 parents in Semarang City, Central Java Province, Indonesia, using a purposive sampling technique. Some parents agreed that reproductive health education at home was unnecessary (29.5%), taboo (45%), difficult (73.1%), and awkward (41.5%). Most parents (72.7%) were not transparent in providing reproductive health information to their children by using other terms to name the genitals, considering the politeness aspect. Good practices of providing reproductive health information are slightly more common in mothers (54.2%), unemployed parents …

Sars-Cov-2 Antibody Seroprevalence In Jakarta, Indonesia, Iwan Ariawan, Hafizah Jusril, Muhammad N Farid, Pandu Riono, Wiji Wahyuningsih, Widyastuti Widyastuti, Dwi Oktavia T L Handayani, Endang Sri Wahyuningsih, Rebekka Daulay, Retno Henderiawati, Safarina G. Malik, Rintis Noviyanti, Leily Trianty, Nadia Fadila, Khin Saw Aye Myint, Frilasita A. Yudhaputri, Neeraja Venkateswaran, Kodumudi Venkateswaran, Venkatachalam Udhayakumar, William A. Hawley, Juliette Morgan, Paul M. Pronyk

Kesmas

The SARS-CoV-2 transmission dynamics in low- and middle-income countries remain poorly understood. This study aimed to estimate the SARS-CoV-2 antibodies seroprevalence in Jakarta, Indonesia, and to increase knowledge of SARS-CoV-2 transmission in urban settings. A population-based serosurvey among individuals aged one year or older was conducted in Jakarta. Employing a multistage sampling design, samples were stratified by district, slum, and non-slum residency, sex, and age group. Blood samples were tested for IgG against three different SARS-CoV-2 antigens. Seroprevalence was estimated after applying sample weights and adjusting for cluster characteristics. In March 2021, this study collected 4,919 respondents. The weighted estimate …

Model Autonomy Of Self-Finance Management For Primary Health Care To Enhance Workers’ Satisfaction, Ahmad Jet Alamin, Ossama Issac, Lina Teo, Atikah Adyas

Kesmas

This study aimed to find an appropriate model of autonomous self-finance management in primary health care (PHC) to enhance workers' satisfaction. This was a cross-sectional study in which data were collected through self-administered questionnaires from 204 workers in ten Regional Public Service Agency for Primary Health Care (RPSAPHC)/Badan Layanan Umum Daerah Pusat Kesehatan Masyarakat (BLUD Puskesmas) in Tangerang District, Banten Province, Indonesia using the partial least squares and structural equation model (PLS-SEM). A total of 73 indicators were used to examine the PHC transformation process to enhance workers' satisfaction. The indicators were grouped into three variables depending on workers' satisfaction: …

Predictors Of Anxiety Toward Covid-19 Delta Variant: A Cross- Sectional Study Among Healthcare Providers In Java And Bali, Indonesia, I Ketut Swarjana, I Gede Putu Darma Suyasa, I Kadek Nuryanto

Kesmas

Health facilities are experiencing overcapacity, oxygen scarcity, and a limited number of healthcare providers due to the coronavirus disease 2019 (COVID-19), thus impacted on anxiety. This study aimed to determine predictors of anxiety among healthcare providers toward the Delta variant of COVID-19 in Indonesia. A cross-sectional study was conducted with 371 healthcare providers in Java and Bali Islands, and the snowball sampling technique was used. Data were collected using a questionnaire and distributed through social media (WhatsApp), then analyzed using univariate analysis, bivariate analysis (Chi-square test), and multivariate analysis (multiple logistic regression). The results showed that 81 (21.8%) respondents experienced …

Spatial Analysis Of Seven Islands In Indonesia To Determine Stunting Hotspots, Tiopan Sipahutar, Tris Eryando, Meiwita Budiharsana

Kesmas

Indonesia is a vast country struggling to reduce its stunting prevalence. Hence, identifying priority areas is urgent. In determining areas to prioritize, one needs to consider geographical issues, particularly correlations among areas. This study aimed to discover whether stunting prevalence in Indonesia occurs randomly or in clusters; and, if it occurs in clusters, which areas are the hotspots. This ecological study used aggregate data from the 2018 National Basic Health Research and Poverty Data and Information Report from the Statistics Indonesia. This study analyzed 514 districts/cities across 34 provinces on seven main islands in Indonesia. The method used was the …

Copulas, Maximal Dependence, And Anomaly Detection In Bi-Variate Time Series, Ning Sun

Electronic Thesis and Dissertation Repository

This thesis focuses on discussing non-parametric estimators and their asymptotic behaviors for indices developed to characterize bi-variate time series. There are typically two types of indices depending on whether the distributional information is involved. For the indices containing the distributional information of the bivariate stationary time series, we particularly focus on the index called the tail order of maximal dependence (TOMD), which is an improvement of the tail order. For the indices without distributional information of the bivariate time series, we focus on an anomaly detection index for univariate input-output systems.

This thesis integrates three articles. The first article (Chapter …

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, 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) …

Between “Breaking” And “Building”: The Bridge Theory Of Research Evaluation, Fang Xu, Xiaoxuan Li

Bulletin of Chinese Academy of Sciences (Chinese Version)

How to build "new standards" after breaking "Siwei" is a hot and difficult issue in the current reform of research evaluation, which urgently needs good theoretical and methodological support. In this context, this study puts forward the BRIDGE theory of research evaluation of scientific researchers' achievements, which is to integrate the reasonable elements in the quantitative evaluation based on SCI papers into the "new standard" based on peer review, so as to build a bridge between quantitative analysis and qualitative evaluation. The practical application of BRIDGE theory is expressed as "Six Steps", in which the second step "Recode" and the …

Exploring Human-Caused Fire Occurrence Prediction, Ruyi Jin

Undergraduate Student Research Internships Conference

Wildland Fire Science has become an increasingly hot topic in recent years. The goal of this report is to investigate human-caused wildland fire occurrence prediction. The two main predictors of interest are the mean value of the Fine Fuel Moisture Code (FFMC) and the month when a fire ignites. An Exploratory Data Analysis is presented first, after which we fit models to predict daily fire counts. We first consider Poisson models to fit the count data, but also attempt to fit Negative Binomial models to deal with overdispersion. We compare these models in the following ways: plotting the difference in …

An Analysis Of Weighted Least Squares Monte Carlo, Xiaotian Zhu

Electronic Thesis and Dissertation Repository

Since Longstaff and Schwartz [2001] brought the amazing Regression-based Monte Carlo (LSMC) method in pricing American options, it has received heated discussion. Based on the research done by Fabozzi et al. [2017] that applies the heteroscedasticity correction method to LSMC, we further extend the study by introducing the methods from Park [1966] and Harvey [1976]. Our work shows that for a single stock American Call option modelled by GBM with two exercise opportunities, WLSMC or IRLSMC provides better estimates in continuation value than LSMC. However, they do not lead to better exercise decisions and hence have little to no effect …

Release Of Vocs, Gasses, And Bacteria From Contaminated Landings And Creeks Of Ogeechee River Basin, Victoria A. Clower, Melanie Sparrow, Atin Adhikari

Department of Biostatistics, Epidemiology, and Environmental Health Sciences Faculty Publications

River landings are common public grounds, visited by many people every day. The aftermath of visiting these places may be unsettling since much trash is left behind and scattered throughout. The litter collects and with each rain or high wind, it has a better chance of ending up in our streams, rivers, creeks, and eventually our oceans. The main purpose of this study was to measure both air and water quality throughout the Ogeechee River basin in South Georgia to determine how each was impacted by trash. Ammonia, methane, and volatile organic compounds (VOCs) along with temperature and humidity were …

A Transformer-Based Classification System For Volcanic Seismic Signals, Anthony P. Rinaldi, Cindy Mora Stock, Cristián Bravo Roman, Alexander Hemming

Undergraduate Student Research Internships Conference

Monitoring volcanic events as they occur is a task that, to this day, requires significant human capital. The current process requires geologists to monitor seismographs around the clock, making it extremely labour-intensive and inefficient. The ability to automatically classify volcanic events as they happen in real-time would allow for quicker responses to these events by the surrounding communities. Timely knowledge of the type of event that is occurring can allow these surrounding communities to prepare or evacuate sooner depending on the magnitude of the event. Up until recently, not much research has been conducted regarding the potential for machine learning …

Bias-Corrected Bagging In Active Learning With An Actuarial Application, Yangxuan Xu

Undergraduate Student Research Internships Conference

The variable annuity (VA) is a modern insurance product that offers certain guaranteed protection and tax-deferred treatment. Because of the inherent complexity of guarantees’ payoff, the closed-form solution of fair market values (FMVs) is often not available. Most insurance companies depend on Monte Carlo (MC) simulation to price the FMVs of these products, which is an extremely computational intensive and time-consuming approach. The metamodeling approach can be used to circumvent the heavy computation.

In the modeling stage, the bagged tree method has proved to outperform other parametric approaches. Also, a bias-corrected (BC) bagging model was tried and showed significant improvement …

A Review Of Statistical Learning Methods With Applications, Natalie R. Masse

Major Papers

Statistical learning refers to a set of tools for modelling and understanding complex datasets. It is a recently developed area in statistics and blends with parallel developments in computer science and, in particular, machine learning. This paper aims to outline some of the key statistical learning methods in the areas of prediction and classification of data. The goal is to discuss the theory and methodology of Ordinary Least Squares Regression, Ridge Regression, Lasso Regression, Logistic Regression, K-Nearest Neighbours method of classification, Linear and Quadratic Discriminant analysis, and Classification Trees. We then discuss the idea of Cross Validation, and demonstrate these …

Investigating Distributions Of Epochs In Wildland Fire Lifetimes, Xinlei Wang

Undergraduate Student Research Internships Conference

The objective of my research project is to explore the relationship between variables related to wildland fire and to model distributions of epochs in wildland fire lifetimes. Several distributional families are considered for modeling these epochs, including the exponential distribution, gamma distribution, Weibull distribution and continuous phase-type distribution. I explain each of these distributions in short terms and illustrate how they are fit. Visual results of my exploratory data analysis are illustrated in two parts, data visualization and data modeling, along with my interpretation of each. Since this work is preliminary, I conclude the report with a discussion on what …

The Q-Analogue Of The Extended Generalized Gamma Distribution, Wenhao Chen

Undergraduate Student Research Internships Conference

This project introduces a flexible univariate probability model referred to as the q-analogue of the Extended Generalized Gamma (or q-EGG) distribution, which encompasses the majority of the most frequently used continuous distributions, including the gamma, Weibull, logistic, type-1 and type-2 beta, Gaussian, Cauchy, Student-t and F. Closed form representations of its moments and cumulative distribution function are provided. Additionally, computational techniques are proposed for determining estimates of its parameters. Both the method of moments and the maximum likelihood approach are utilized. The effect of each parameter is also graphically illustrated. Certain data sets are modeled with q-EGG distributions; goodness of …

Investigation Of Key Factors To Earthquake Insurance Take-Up Rates In Quebec And British Columbia Households And Prediction Model Building, Yongcheng Jiang

Undergraduate Student Research Internships Conference

Maintaining an adequate level of earthquake take-up rate could protect the insurance industry from systemic failure. Past research has shown that British Columbia and Quebec have significant differences in earthquake insurance take-up rate. This report investigates key factors from the structure (default options and various types) of the insurance plan and personal characteristics along with socioeconomic/demographic profiles that affect the demand for earthquake protection in the form of insurance. The report also provides a prediction model for earthquake insurance take-up rate. The results show an importance ranking of key factors of earthquake insurance take up, the most important three are …

Functional Structure Of Excess Return And Volatility, Chenxi Zhao

Undergraduate Student Research Internships Conference

Capturing the relation between excess returns and volatility can help making better decisions in the stock market in terms of portfolio allocation and assets risk management. This paper takes the data of a minute-by-minute series of S&P500 from January 2009 to January 2021 as the research object and explores the best structural representation for the excess return as a function of the volatility, for a well-known index. This is implemented via regression models for volatility and excess returns. The results reveal that there’s a structural break in the relationship between the excess return and volatility based on the sign of …

Financial Literacy: Self-Evaluation And Reality, Yangsijia Wang

Undergraduate Student Research Internships Conference

This study is on the topic of financial literacy, with the data source containing information on clients' demographic information and self-evaluation, change in account value, and trade record, three major problems were investigated: first, whether a client's demographic traits are related to his/her self-evaluation of financial knowledge level; second, does the trading behaviour differ for clients who self-identified as in different financial knowledge groups; and third, do people who self-identified as financially knowledgeable have better investment result. Data manipulation was done using SQL and R. Exploratory analysis including multiple types of plots and proportion tables was used to derive the …

Mathematical Models Yield Insights Into Cnns: Applications In Natural Image Restoration And Population Genetics, Ryan Cecil

Electronic Theses and Dissertations

Due to a rise in computational power, machine learning (ML) methods have become the state-of-the-art in a variety of fields. Known to be black-box approaches, however, these methods are oftentimes not well understood. In this work, we utilize our understanding of model-based approaches to derive insights into Convolutional Neural Networks (CNNs). In the field of Natural Image Restoration, we focus on the image denoising problem. Recent work have demonstrated the potential of mathematically motivated CNN architectures that learn both `geometric' and nonlinear higher order features and corresponding regularizers. We extend this work by showing that not only can geometric features …

The Association Between Dietary Inflammatory Index, Dietary Antioxidant Index, And Mental Health In Adolescent Girls: An Analytical Study, Parvin Dehghan, Marzieh Nejati, Amir Almasi-Hashiani, Sevda Saleh-Ghadimi, Rezza Parsi, Hamed Jafari-Vayghan, Nitin Shivappa Mbbs, Mph, Ph.D., James Hébert Scd

Faculty Publications

Background Diet is considered as one of the modifiable factors that appears to exert a vital role in psychological status. In this way, we designed this study to examine the association between dietary inflammatory index (DII), dietary antioxidant index (DAI), and mental health in female adolescents. Methods This cross-sectional study included 364 female adolescents selected from high schools in the five regions of Tabriz, Iran. A 3-day food record was used to extract the dietary data and calculate DII/DAI scores. DII and DAI were estimated to assess the odds of depression, anxiety, and stress based on the Depression Anxiety Stress …

Defining Viable Solar Resource Locations In The Southeast United States Using The Satellite-Based Glass Product, Jolie Kavanagh

Theses and Dissertations

This research uses satellite data and the moment statistics to determine if solar farms can be placed in the Southeast US. From 2001-2019, the data are analyzed in reference to the Southwest US, where solar farms are located. The clean energy need is becoming more common; therefore, more locations than arid environments must be observed. The Southeast US is the main location of interest due to the warm, moist environment throughout the year. This research uses the Global Land Surface Satellite (GLASS) photosynthetically active radiation product (PAR) to determine viable locations for solar panels. A probability density function (PDF) along …

Exploration In Mental Performance For Division 1 Sec College Football Student Athletes, Alex Burgdorf

Department of Occupational Therapy Entry-Level Capstone Projects

The stigma surrounding mental health in sports has made intervention difficult. “There is a need for various actors to provide more effective strategies to overcome the stigma that surrounds mental illness, increase mental health literacy in the athlete/coach community, and address athlete-specific barriers to seeking treatment for mental illness” (Castadelli-Maia et.al 2019). The athletes in the football program at the University of Tennessee face more pressure today than ever in history. They have their class schedule, practice and training every day, and meetings with their position coaches. Now, with the introduction of name, image, and likeness (NIL) allowing players to …

Comparative Antiplatelet Effects Of Chlorthalidone And Hydrochlorothiazide, Khalid Bashir, Tammy Burns, Samuel J. Pirruccello, Sarah J. Aurit

Department of Statistics: Faculty Publications

Chlorthalidone (CTD) may be superior to hydrochlorothiazide (HCTZ) in the reduction of adverse cardiovascular events in hypertensive patients. The mechanism of the potential benefit of CTD could be related to antiplatelet effects. The objective of this study was to determine if CTD or HCTZ have antiplatelet effects. This study was a prospective, double-blind, randomized, three-way crossover comparison evaluating the antiplatelet effects of CTD, HCTZ, and aspirin (ASA) in healthy volunteers. The effects of these treatments on platelet activation and aggregation were assessed using a well-established method with five standard platelet agonists. Thirty-four patients completed the three-way crossover comparing pre- and …

Abm Simulation Model Of A Pandemic For Optimizing Vaccination Strategy, Gibeom Park

Theses and Dissertations

This study presents a process-oriented hybrid model for individuals' immune responses and interactions involving vaccination to describe the trend of contagious disease and estimate the future societal cost. The model considers "recovery" as a non-absorbing state and incorporates various infection stage states including two symptomatic states. To model contagiousness to be consistent with the current pandemic and include that the spread of a disease depends on the mobility of people, we developed an Agent-Based Simulator that fitted to the particular model used in this study and can test various what-if scenarios. We improved the simulator considerably by appying data structures …

Debiasing Cyber Incidents – Correcting For Reporting Delays And Under-Reporting, Seema Sangari

Doctor of Data Science and Analytics Dissertations

This research addresses two key problems in the cyber insurance industry – reporting delays and under-reporting of cyber incidents. Both problems are important to understand the true picture of cyber incident rates. While reporting delays addresses the problem of delays in reporting due to delays in timely detection, under-reporting addresses the problem of cyber incidents frequently under-reported due to brand damage, reputation risk and eventual financial impacts.

The problem of reporting delays in cyber incidents is resolved by generating the distribution of reporting delays and fitting modeled parametric distributions on the given domain. The reporting delay distribution was found to …

Dynamic Prediction For Alternating Recurrent Events Using A Semiparametric Joint Frailty Model, Jaehyeon Yun

Statistical Science Theses and Dissertations

Alternating recurrent events data arise commonly in health research; examples include hospital admissions and discharges of diabetes patients; exacerbations and remissions of chronic bronchitis; and quitting and restarting smoking. Recent work has involved formulating and estimating joint models for the recurrent event times considering non-negligible event durations. However, prediction models for transition between recurrent events are lacking. We consider the development and evaluation of methods for predicting future events within these models. Specifically, we propose a tool for dynamically predicting transition between alternating recurrent events in real time. Under a flexible joint frailty model, we derive the predictive probability of …

To Logit Or Not To Logit Data In The Unit Interval: A Simulation Study, Kayode Idris Hamzat

Major Papers

In this paper, we recommend a mechanism for determining whether to logit or not to logit data in the unit interval which is based on quantile estimation of data between 0 and 1. By using a simulated dataset generated from a Beta regression model, the estimated quantile for this model perform better than those based on the linear quantile regression with logit transformation.

Further, we investigate the performance of the quantile regression estimators based on the LQR and we conclude that it is better than those based on the Beta regression when the distribution is contaminated with 10% uniform numbers …

Machine Learning Model Comparison And Arma Simulation Of Exhaled Breath Signals Classifying Covid-19 Patients, Aaron Christopher Segura

Mathematics & Statistics ETDs

This study compared the performance of machine learning models in classifying COVID-19 patients using exhaled breath signals and simulated datasets. Ground truth classification was determined by the gold standard Polymerase Chain Reaction (PCR) test results. A residual bootstrapped method generated the simulated datasets by fitting signal data to Autoregressive Moving Average (ARMA) models. Classification models included neural networks, k-nearest neighbors, naïve Bayes, random forest, and support vector machines. A Recursive Feature Elimination (RFE) study was performed to determine if reducing signal features would improve the classification models performance using Gini Importance scoring for the two classes. The top 25% of …