Statistics and Probability Commons^™

Research On Automatic Review Method Of Highway Bim Based On Knowledge Graph, Wang Wuyu, Shao Kebo, Zhang Feng

Journal of China & Foreign Highway

Building information modeling (BIM ),characterized by multi-dimensional modeling and multi-source data integration,is becoming a key technology to promote the innovation and digital transformation of the highway design industry.Taking BIM as the design deliverable is an inevitable trend in the future development of highway engineering design.However,the current highway BIM review is mainly conducted manually,which brings about problems such as low efficiency,susceptibility to errors,and high subjectivity.This makes it difficult to adapt to the review requirements of the three-dimensional (3D) digital design mode.To this end,this study proposed an automatic review method of highway BIM based on a knowledge graph.By constructing the knowledge graph …

Research On Multi-Classification Prediction Of Traffic Accident Severity On Mountainous Expressways, Wang Hao, Yan Jie, Guo Jianmin, Zhang Yu, Sun Chengji

Journal of China & Foreign Highway

To enhance the safety level of mountainous expressways and establish an accurate and effective prediction model for traffic accident severity,this study analyzed 2 484 traffic accidents on mountainous expressways in Chongqing from 2010 to 2016.A total of 17 influencing factors were selected from four aspects:human,vehicle,road,and environment,to serve as explanatory variables.Partial proportional odds model,random forest algorithm,and XGBoost algorithm were used to construct multi-class prediction models for traffic accident severity.The model performance was evaluated using the confusion matrix,accuracy,and minority class recall rate.The results show that the XGBoost model achieves the highest prediction accuracy in multi-class prediction of traffic accident severity on mountainous …

Application And Analysis Of Energy-Conservation And Carbon-Reduction Technologies In Green Highways, Huang Xuewen, Wang Kai, Huang Shanqian, Xiong Xinzhu, Fu Jinsheng

Journal of China & Foreign Highway

To improve the low-carbon development level of highway engineering,this study relied on a typical green highway in Anhui Province and established a calculation model for energy-conservation and carbon-reduction in highway engineering based on the emission factor method.A combination of quantitative and qualitative approaches was adopted to evaluate the benefits of 33 energy-conservation and carbon-reduction technologies in reducing life cycle energy consumption and carbon emissions,based on life cycle assessment (LCA ) theory.The results show that during the material production stage,through channel resource coordination and the application of low-carbon,energy-saving materials,comprehensive reductions in the embodied carbon can be achieved.During the construction stage,energy consumption …

Reference And Inspi Ration From Low-Carbon Development Experience Of Foreign Highway Infrastructure, Lu Chunying, Gao Shuohan, Du Xueyua N, Jian Li, Wang Xinjun, Kong Yaping

Journal of China & Foreign Highway

In order to provide supp ort for the scie ntific formulation of low-carbon highway infrastructure development policies in China,empirical analysis,comparative analysis,and other methods were utilized,and the construction goals and action strategies of low-carbon highway infrastructure in the United Kingdom,the United States,and Australia were sorted out.Advanced experience in the development of low-carbon highways abroad was summarized.On this basis,combined with the current situation and existing problems of low-carbon development of China ’s highway infrastructure,the following countermeasures and suggestions were proposed:① strengthening top-level design and formulating low-carbon development goals and paths;② implementing the concept of life cycle and strengthening the research and promotion …

Analysis And Control Of Impact Of Wide Waterway Excavation On Adjacent Bridge Pile Foundations, Zhang Peisheng, Qiao Lyu, Sheng Jianchao, Sheng Haoxiang, Liu Hanchen, Wang Zhe

Journal of China & Foreign Highway

When excavating a waterway beneath an existing bridge,the pile foundations are subjected to unloading from excavation and the loading from the superstructure,which may lead to excessive displacement and potential safety hazards.Based on the underpass project of the Desheng Expressway Bridge along the Zhejiang section of the Beijing ‒ Hangzhou Canal,this study established a three-dimensional finite element model (FEM ) and combined it with field monitoring to investigate the impact of wide waterway excavation on adjacent bridge pile foundations and corresponding control measures.A novel combined control method involving a retaining wall with supporting piles and fully enclosed isolation piles was proposed.The …

Influence Of Horizontal Curve Radius On Vehicle Fuel Consumption And Pollutant Emissions On Tw O-Lane Highways, Tu Shengwen, Lei Meimei, Guo Wenyu

Journal of China & Foreign Highway

To investigate the influence of horizontal curve radius on vehicle fuel consumption and pollutant emissions on two-lane highways,this study developed a model based on running speed theory,vehicle driving dynamics,and a fuel consumption and emission analysis system.Fuel consumption and emissions of CO2,CO,HC,and NOx were calculated for a passenger car traveling along horizontal curves under three design speeds:40 km/h,60 km/h,and 80 km/h.The results show that the horizontal curve radius has a significant effect on vehicle fuel consumption and pollutant emissions.The trends of fuel consumption,CO2,and NOx emissions vary consistently with curve radius,while CO and HC emissions follow a similar but different trend.At the …

Nitrogen Fertilizer Equivalence Of Red Clover When Inter-Seeded Into Corn, Hannah R. Francis, Ting Fung Ma, Rodrigo Werle, Chelsea H. Zegler, Daniel H. Smith, Douglas J. Soldat, Erika Marin-Spiotta, Matthew D. Ruark

Faculty Publications

Inter-seeding red clover (Trifolium pratense L.) provides an alternative method toincorporate cover crops into continuous corn (Zea mays L.) in the Upper US Midwest. Red clover is a leguminous cover crop that can grow in low-radiation environments and is winter hardy. Systems with red clover have demonstrated improved corn yield and a fertilizer N equivalence but understanding these effects with inter-seeding war-rants further investigation. The objectives of this study were to determine the effect of inter-seeding red clover on (i) plant-available N during and after red clover decomposition, (ii) optimum N rates for corn, and (iii) corn yields. The …

Nitrogen Fertilizer Equivalence Of Red Clover When Inter-Seeded Into Corn, Hannah R. Francis, Ting Fung Ma, Rodrigo Werle, Chelsea H. Zegler, Daniel H. Smith, Douglas J. Soldat, Erika Marin-Spiotta, Matthew D. Ruark

Faculty Publications

Inter-seeding red clover (Trifolium pratense L.) provides an alternative method to incorporate cover crops into continuous corn (Zea mays L.) in the Upper US Midwest. Red clover is a leguminous cover crop that can grow in low-radiation environments and is winter hardy. Systems with red clover have demonstrated improved corn yield and a fertilizer N equivalence but understanding these effects with inter-seeding warrants further investigation. The objectives of this study were to determine the effect of inter-seeding red clover on (i) plant-available N during and after red clover decomposition, (ii) optimum N rates for corn, and (iii) corn …

The Dual Impact Of Moral Injury: Links To Ptsd Symptoms And Disinhibited Externalizing In U.S. Combat Veterans, Bianca S. Islas

UNLV Theses, Dissertations, Professional Papers, and Capstones

Moral injury is an experience of psychological distress that occurs when a person’s morals are violated by themselves or others, including institutions and organizations. Such violations of morality can be impairing and have high rates of comorbidity with internalizing disorders (posttraumatic stress, depression, anxiety, suicidality), which may indicate that moral injury is a transdiagnostic construct. This study had four aims, which were accomplished using from a nationally representative, probability-based sample of 1,353 US military veterans. In the first aim, we created structural models of moral injury using the Moral Injury Events Scale (for which a bifactor structure with a specific …

Rna’S Symphony: Harmonizing Splice Junctions And Exon Counts For A Novel Approach To Differential Splicing Analysis, Jelard Aquino

UNLV Theses, Dissertations, Professional Papers, and Capstones

Alternative Splicing (AS) plays a critical role in transcriptome complexity and cell-type-specific gene regulation, yet its analysis remains methodologically fragmented, especially in the context of noisy and sparse single-cell RNA sequencing (scRNA-seq) data. This dissertation addresses key computational challenges in AS detection by evaluating existing tools, developing integrative frameworks, and proposing new strategies for improving analysis accuracy in both bulk and single-cell contexts. In chapter 1, I present a comprehensive literature review of computational tools designed for detecting and quantifying AS from bulk and scRNA-seq data. This review outlines major methodological paradigms, including exon-based and splice junction-based approaches, and evaluates …

Empowering Science With The World's First High Accuracy And High Throughput Functional Assay, Christopher Giacoletto

UNLV Theses, Dissertations, Professional Papers, and Capstones

Understanding the functional consequences of genetic mutations remains a central challenge in modern biology, with far-reaching implications for human health and disease. While early systematic methods like alanine scanning and phage display provided foundational insights into protein structure and function, the emergence of high-throughput approaches—such as Multiplexed Assays of Variant Effect (MAVEs)—and predictive tools powered by artificial intelligence have vastly expanded our ability to profile mutational landscapes. However, these methods are often constrained by trade-offs between accuracy, scalability, and biological relevance.This dissertation presents the development and application of the GigaAssay, the world’s first high-throughput functional assay capable of delivering both …

An Evidence-Based Intervention To Increase Trypanosoma Cruzi, A Neglected Parasitic Infection, Diagnosis In Rural And Moderate-Size-City Us Clinics, M K. Lynn, Hunter M. Boehme, Jeffrey Hall, Patrick Kent, Alain H. Litwin, Quang H. Pham, Melissa Nolan Ph.D., Mph, Prisma Chagas Team

Faculty Publications

Background

Chagas disease is a chronic, insidious parasitic infection (Trypanosoma cruzi) that slowly develops to irreversible organomegaly over several decades. The disease is traditionally acquired in endemic Latin American countries during childhood; < 1% of foreign-born adult residents in the United States have been diagnosed or treated with this potentially fatal disease. Low physician knowledge is a primary factor leading to misdiagnosis.

Methods

Starting in April 2022, a 4-part T cruzi clinical education intervention began, which included (i) 2 grand rounds presentations to >100 internal medicine providers; (ii) implementation of a “clinical Chagas champions program” incorporating 14 key clinical staff at varying departments and administrative levels educated on their specific role related to T cruzi screening, diagnosis confirmation, clinical management, and medical billing; ( …

Changes In Mental Health Care Utilisation Before And During The Covid-19 Pandemic Among People Living With Hiv In The Usa: A Retrospective Cohort Study Using The All Of Us Dataset, Atena Pasha, Shan Qiao, Jiajia Zhang Ph.D., Ruilie Cai, Buwei He, Xueying Yang, Chen Liang Ph.D., Sharon Weissman, Xiaoming Li Ph.D.

Faculty Publications

Introduction Despite the profound impact of the COVID-19 pandemic on people living with HIV (PLWH) mental health, large-scale, real-world data on mental healthcare utilisation and associated factors among PLWH remain limited. This study explores mental healthcare utilisation and associated factors among PLWH during the COVID-19 pandemic.

Methods Using a retrospective cohort design, we identified and included 4575 PLWH through computational phenotyping based on relevant Observational Medical Outcomes Partnership Common Data Model concept sets from the All of Us programme between March 2018 and March 2022. Mental healthcare utilisation was measured using the yearly count of mental healthcare visits and compared …

Neighborhood Socioeconomic Status And Overall Survival Among Children With Acute Lymphoblastic Leukemia, Anna Hoppmann, Debroah M. Hurley, Stuart Cramer, Monique J. Brown Ph.D., Mph

Faculty Publications

A disadvantaged neighborhood, as represented by area-level socioeconomic status (SES) has been associated with adverse outcomes among children with acute lymphoblastic leukemia (ALL) in the US, but the duration of impact after ALL diagnosis is not well understood. This retrospective cohort study utilized the National Cancer Database (NCDB) to examine the impact of area-level SES on overall survival among children with ALL. Median income and education quartiles based on residential zip code were used to create a composite area-level SES variable. Individual-level variables included age, sex, race, year of diagnosis, primary payer, distance to care, rurality, time to treatment, and …

Statistical Methods For Joint Outcome Modeling And Dynamic Assessment Of Recurrent Events, Zifang Kong

Statistical Science Theses and Dissertations

Recurrent event data frequently arise in clinical studies where individuals experience repeated, possibly related, events over time. These data are often accompanied by sparse and irregular longitudinal measurements, creating challenges for traditional joint modeling approaches that struggle to account for time-dependent associations and within-subject correlations. We propose FRAILTY (Functional Regression with AutoRegressIve fraiLTY), a novel two-step framework that integrates functional principal component analysis (PACE) with a dynamic frailty model featuring autoregressive structure. FRAILTY accommodates both scalar and functional predictors and captures within-subject dependence across recurrent events. To further extend its utility, we develop a multivariate joint modeling framework that simultaneously …

Towards Reliable Clinical Applications Of Ai Models In Radiotherapy, Biling Wang

Statistical Science Theses and Dissertations

Over the past decade, artificial intelligence (AI), particularly through deep learning (DL) techniques, has made significant strides in fields like computer vision (CV) and natural language processing (NLP), leading to transformative advancements across numerous applications. This progress has sparked considerable enthusiasm within the medical field, where DL-related research has grown exponentially since 2015. However, despite these promising developments, the real-world deployment of DL models in healthcare remains limited, especially in safety-critical domains such as radiotherapy (RT), where reliability, safety, and sustained performance are critical. This thesis addresses three core challenges associated with the clinical application of DL models: (1) post-deployment …

Crop Yield Prediction At Multiple Spatial Scales With Statistical Machine Learning, Vaibhav Charan, Pratishtha Poudel

Discovery Undergraduate Interdisciplinary Research Internship

Understanding and accurately predicting crop yield is becoming increasingly important today in the face of global food security challenges, and thus, the availability of standardized data and scalable models is the need of the hour. To support this, researchers have developed CY-Bench (Crop Yield Benchmark), a comprehensive dataset that helps forecast maize and wheat yields on a global scale. This research project primarily involved working with the CY-Bench dataset aiming to improve crop yield prediction through machine learning. Initially, papers explaining the CY-Bench dataset and other papers for agriculture modeling were studied and analyzed in detail. The research then progressed …

Breast Cancer Survival Rates And Determinants In Ethiopia: A Systematic Review And Meta-Analysis Of Longitudinal Studies, Abenezer M. Tafese, Meseker T. Fentie, Beminate L. Seifu, Angwach A. Asnake, Bikiltu D. Dirbaba, Abdisa G. Jara, Elsabeth Tizazu Asare, Brandon George

College of Population Health Faculty Papers

BACKGROUND: Breast cancer is the most common cancer and the leading cause of cancer mortality among women in Ethiopia, accounting for 32% of new cancer cases and 17.6% of cancer deaths. Despite its growing burden, comprehensive data on survival rates and contributing factors remain limited. This systematic review and meta-analysis aimed to synthesize existing data on breast cancer survival in Ethiopia and identify key determinants influencing outcomes.

METHODS: A comprehensive systematic search was conducted in PubMed, Web of Science, Scopus, Embase, and CINAHL to identify studies on breast cancer survival in Ethiopia published between January 2014 and August 2024. Eligible …

The Bandages Problem, James E. Marengo, Joseph G. Voelkel, David L. Farnsworth

Articles

A new probability problem, named the Bandages Problem, is described and solved. The problem involves repeatedly selecting and removing an item at random from a finite population that initially consists of a known configuration of single and paired items. For each selection, the probability that the chosen item is single is found. Generalizations are suggested.

Performance Of The Two Sample Likelihood Ratio Test Under A Nested Dirichlet: A Simulation Study, Edwina Agyeman

Electronic Theses and Dissertations

Compositional data analysis (CoDA) addresses multivariate data constrained to a constant sum, such as proportions or percentages. Originating from early warnings regarding misinterpretation by Pearson (1897), the field was formalized by John Aitchison in 1986, whose foundational work remains highly influential. Over time, new modeling techniques and visualization tools have advanced the field, as noted by Greenacre et al. More recently, Turner et al. proposed an approach based on the Nested Dirichlet Distribution (NDD), which accommodates more flexible dependence structures than the standard Dirichlet model. This thesis builds on the methodology of Turner et al. Chapter 1 introduces the nature …

Evaluating Alpha Spending Functions Applied To Observational Time-To-Event Analysis, Moses Torgbenu

Electronic Theses and Dissertations

This thesis explores the theoretical foundation of the alpha spending approach and extends its application beyond the conventional setting of randomized controlled trials (RCTs) to observational studies with time to event analyses. In these less structured environments, key design parameters such as the total number of events are often unknown, posing challenges for the standard implementation of sequential analysis methods.

Through simulation studies, this research delivers several important contributions. First, it presents a modified approach that uses calendar time to define the timing of interim analyses while relying on event-based information to estimate the correlation among test statistics. This adjustment …

Experimental Design And Analysis For Decision Making: Methodology And Applications, Yezhuo Li

All Dissertations

This dissertation develops and applies advanced statistical and optimization frameworks to enhance decision-making under uncertainty, particularly in engineering and manufacturing contexts. First, we introduce an approach for the optimal design of controlled experiments that accounts for observational covariates, enabling more precise and personalized decisions. Second, we explore the application of constrained Bayesian optimization, using Gaussian process surrogate models, to optimize composite cure processes, significantly reducing computational effort while maintaining high predictive accuracy. Building on this foundation, we extend Bayesian optimization to bivariate Gaussian process models that capture correlations between objective and constraint functions, offering new insights into multidimensional decision landscapes. …

Simultaneous Application Of Multiple Process Control Rules, Tran B. Ngo

Electronic Theses and Dissertations

Statistical Process Control (SPC) charts are tools used in quality control to monitor and analyze the stability of a process over time. This study evaluates the effectiveness of eight individual Western Electric rules, also known as WECO rules, and the various combinations of these rules with Shewhart rule (or WECO rule 1) to SPC charts. As more rules are added to a process control scheme with Rule 1, there is a trade-off: a higher false out-of-control signal rate but an increase in sensitivity, that is the ability of a specified process control scheme to capture a true out-of-control signal. This …

Mazur’S Intersection Property And Its Variants, Deepak Gothwal

Doctoral Theses

We discuss various differentiability notions in connection with ball separation prop- erties. We characterise the uniform Mazur’s intersection property (UMIP) in terms of w*-semidenting points in attempt to resolve a long standing open question: “Does UMIP imply uniformly smooth renorming?” Further, we discuss a stronger version of UMIP called the hyperplane uniform Mazur intersection property (HUMIP) which is shown to characterise uniform smoothness. Similar ball separation char- acterisations are obtained for Fr´echet smoothness and asymptotic uniform smoothness (AUS). These ball separation properties are then shown to be residual properties. Thus, we obtain that norms which have UMIP or norms which …

Detection Of Activity Cliffs Produced By Anti-Cancer Drugs And An Algorithm For Reliable Predictions In Affected Areas, Sarah Josephine Aurit

Department of Statistics: Dissertations, Theses, and Student Research

An activity cliff (AC) occurs when drugs close in chemical space produce dissimilar biological results. We focus on developing an inferential procedure to detect the presence of ACs in a chemical landscape. If detected, we provide a distance-based procedure that can be used to identify regions of stability in the chemical landscape of interest and generate prediction with higher precision in those areas of stability. We conceptualize the chemical landscape as a spatial random field and use spatial models for prediction of efficacy for new drugs based on “distance” in chemical space. We argue that an AC manifests itself by …

Online Prediction Of Streaming Data, Aleena Chanda

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

We present two new approaches for point prediction with streaming data based on a) the Count-Min sketch and b) Gaussian Process Priors with random bias. The methods are intended for the most general case where no true model can be usefully formulated for the data stream. In statistical contexts, this is often called the M open problem class. For the Count Min Sketch method we show that the predicted distribution function ^F converges to F under the assumption that the data consists of i.i.d samples from a fixed distribution function F. To implement the Gaussian Process Prior methods, we used …

Rethinking Iterative Proportional Fitting: Scalable And Hybrid Approaches To Joint Distribution Fitting, William Ofosu Agyapong

Open Access Theses & Dissertations

The Iterative Proportional Fitting (IPF) algorithm is widely used in contingency table estimation, survey weighting, and synthetic population generation due to its simplicity and strong theoretical foundation for matching observed marginal distributions. However, in high-dimensional settings, IPF faces substantial computational and memory demands, as well as statistical instability caused by sparse contingency tables. Moreover, IPF is less useful in modern population synthesis tasks that require both scalability and realism because, despite its superiority in matching known marginal distributions, it cannot produce realistic out-of-sample data points. To address these limitations, we first propose a blockwise IPF framework, in which the feature …

A Multi-Modal Method For Synthetic Data Generation In Social Network Analysis, Hortencia Josefina Hernandez

Open Access Theses & Dissertations

Social network analysis (SNA) research is often rife with data collection pitfalls, frequently leading to incomplete and missing data. With the growing use of SNA-based research, researchers must address the challenge of missing data and synthetic data generation in these settings. Missing data occurs due to longitudinal non-response or lack of response to sensitive or difficult-to-answer questions. Synthetic data generation in SNA settings addresses the lack of representation that is often present in large-scale SNA studies. This dissertation investigates synthetic data generation methods to address these challenges and develops a novel algorithm that leverages information from multi-modal data, e.g., databases …

Simultaneous Selection Of Inflations And Variables In Multiple Inflations Poisson Model (Mip), John Koomson

Open Access Theses & Dissertations

Count data frequently arise in biomedical, economic, and social science research and are often characterized by structural excesses at specific count levels. To accommodate such patterns, Su et al. (2013), among others, introduced the Multiple-Inflation Poisson (MIP) model, which allows for multiple inflated counts within the distribution. However, two critical challenges remain in modeling such data: (i) identifying the true inflation points where excess counts occur, and (ii) selecting the relevant covariates that explain variation in the inflation and count process. This dissertation addresses these issues by advancing the MIP model through a novel methodology that enables the simultaneous selection …

Comparative Analysis Of Sequential And Non-Sequential Modeling Techniques For Ddos Attack Detection With Explainable Ai, Vincent Agbenyeavu

Theses and Dissertations

Cybersecurity is known today as one of the greatest challenges of the modern era. Among the various types of cyber-attacks that threaten our security, the Distributed Denial of Service (DDoS) attack is among some of the most common, effective, and well-recognized attack strategies. Since this form of attack is meant to disrupt the availability factor covertly, it can be detrimental to the targeted machines and difficult to discover. Because of that, there have been several approaches, as well as solutions that have been devised to detect it as accurately and efficiently as possible. In this study, four sequential data modeling …