Statistics and Probability Commons^™

Analysis Of Temperature Field Of Steel Box Girders During Steam Curing Construction Process Of Steel-Uhpc Composite Bridge Decks, Wu Shang, Zhang Yongjian

Journal of China & Foreign Highway

To clarify the influence of high-temperature steam curing of steel-ultra-high performance concrete (UHPC) lightweight composite bridge deck paving on the temperature field of the steel box girder, taking a certain bridge in Hunan Province as an example, finite element numerical simulation and actual bridge testing were conducted on the temperature field of the steel box girder during the high-temperature steam curing process of the bridge deck paving. The numerical calculations were generally consistent with the test results. The analysis results indicate that under the superimposed effect of solar radiation heating and high-temperature steam curing heating, the maximum temperature of the …

Summary And Prospect Of Typical Diseases In Energy Transport Channels In Winter Cold Regions Over Past 20 Years, Jia Qinlong, Hou Zhongfei, Yin Yanping

Journal of China & Foreign Highway

To investigate the typical disease characteristics of energy transport channels in winter cold regions and guide the design for extending road service life, the causes of diseases such as pavement reflective cracks, continuous potholes on bridge decks, and failures of bridge drainage systems were analyzed based on the 20-year operation data of a 531 km in-service expressway in the coal energy region of northern Shaanxi. The research results indicate that when the asphalt pavement thickness reaches 22 cm, the reflective crack spacing of the expressway operated for 15 years can be controlled to over 50 m. Basically, no base layer …

Road Design Methods For Brt Projects Based On French Standard System : A Case Study Of A Project In West Africa, Wang Meng, Wu Cheng

Journal of China & Foreign Highway

With the continuous advancement of China ’s “Belt and Road Initiative”, Chinese enterprises have become increasingly involved in international engineering markets, undertaking numerous transportation infrastructure projects, particularly in Africa and Southeast Asia. However, international engineering projects commonly face the challenge of inconsistent design standard systems across different countries, posing significant difficulties for Chinese enterprises during project implementation. To address this issue, the differences in BRT road design under Chinese and French standards were focused on in this study, and their respective design philosophies and methods were analyzed. Taking a BRT project in a West African country as an example, field …

(R2077) Enhancing Queue Management: Dynamic Server Allocation And Optional Services In Stochastic Modeling, G. Ayyappan, S. Sankeetha

Applications and Applied Mathematics: An International Journal (AAM)

Consider a queueing system with a single server, where customer arrivals follow a Markovian arrival process and service times follow a phase-type distribution. The main server has the capability to recruit an additional server when the number of customers in the system exceeds a certain threshold, denoted as L. Both servers provide normal service to customers, and optional service is provided upon request. The main server takes multiple vacations, with the durations following an exponential distribution with rate parameter η, until there is at least one customer in the system. This system can be represented as a Markov chain process, …

(R2072) A Method To Sample From Transition Densities Of Diffusion Processes With Unknown Densities, Yasin Kikabi, Juma Kasozi

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, we present a reliable method that can be used to sample paths of a diffusion process described by a system of stochastic differential equations. These are types of processes whose transition density is not known in closed form. This reliable method involves solving a partial differential equation of the Fokker-Planck type by rejection sampling techniques applied to the associated densities. We then use the novel method to sample from the Ornstein-Uhlenbeck (OU) process whose transition density is known and has unbounded drift. The results obtained compare excellently with the analytical results, thus rendering the method reliable and …

(R2161) Robust Optimization Of Industrial Hazardous Waste Location-Routing Problem Considering Response Actions To Environmental Risk, Sharareh Teimoori, Farhad Hosseinzadeh Lotfi, Seyyed Esmaeil Najafi, Navid Rafiei

Applications and Applied Mathematics: An International Journal (AAM)

The management of hazardous industrial waste has emerged as a significant global challenge due to rapid technological advancements. Industrial hazardous waste management systems must be designed not only to be cost-effective but also to minimize environmental risks. This study proposes a mixed-integer programming model for the location-routing of industrial hazardous waste that incorporates both primary and secondary environmental risks, along with suitable response actions. Furthermore, a scenario-based robust optimization model is developed to address uncertainties in the quantities of industrial hazardous waste. A case study is conducted to demonstrate the applicability and comparative performance of the nominal and robust models. …

(R2142) Queueing System With Batched Services, Server-Controlled Re-Service, Set-Up Time And Multiple Vacation, S. Karpagam, N. Aarthy, B. Somasundaram

Applications and Applied Mathematics: An International Journal (AAM)

To analyze a bulk queueing system with server-controlled admission for reservice, low-batch service, multiple vacation and set-up time. The study explores how the server dynamically adjusts between low-batch and bulk services based on the queue size. After completing a bulk service, the departing batch may request reservice with a certain probability. However, accepting the request is not mandatory, and the server admits it with some probability. Whenever the queue becomes empty, whether after reservicing, completing service with no reservice request, or ending the low-batch service, the server enters a random-length vacation. If the queue still has less than ‘a’ customers …

(R2174) A Stationary First-Order Autoregressive Process With New Discrete Lindley Marginal Distribution, Tégawendé Martin Kabore, Jean-Etienne Ouindllassida Ouédraogo

Applications and Applied Mathematics: An International Journal (AAM)

This paper introduces a new stationary first-order autoregressive integer-valued process with a marginal distribution following the New Discrete Lindley distribution, referred to as NDLINAR( 1). The process is developed to model over-dispersed count time series exhibiting a mixed behavior arising from the combination of multiple distributions. Its statistical properties are thoroughly investigated, and the parameters are estimated using conditional maximum likelihood. The asymptotic properties of the estimators are also analyzed. The performance of the proposed model is evaluated by comparing it with other existing INAR(1) processes through applications to real datasets. Results demonstrate that the NDL-INAR(1) process effectively captures the …

Risk-Aware Deep Reinforcement Learning In Portfolio Optimization, Shimin Zhang

USF Tampa Graduate Theses and Dissertations

Portfolio optimization is important in investment, with the purpose of maximizing profit whilemanaging risk. The traditional portfolio optimization method, Modern Portfolio Theory, is based on the assumption that returns are normally distributed, which is always violated in practical financial market settings. In addition, traditional approaches to portfolio optimization are mostly designed as static optimizations and fail to account for the nonlinearity and non-stationarity of contemporary financial markets. Recent developments in deep reinforcement learning have attracted considerable attention for treating portfolio optimization as a sequential decision-making process. Traditional portfolio optimization methods usually evaluate risk based on the variance of the returns. …

Statistical Methods For Mendelian Randomization Under Nonlinearity And Non-Normality, Mary Appah

ETDs from 2020-2029

Instrumental variable (IV) methods are widely used for estimating causal effects in observational studies where unmeasured confounding may bias traditional regression estimates. The core idea is to use a variable referred to as an instrument that is associated with the exposure of interest, independent of unmeasured confounders, and influences the outcome only through the exposure. While originally developed in econometrics, IV methods have been increasingly adopted in epidemiology and genetic research under the framework of Mendelian Randomization (MR), where genetic variants, most commonly single nucleotide polymorphisms (SNPs), serve as instruments. MR provides a powerful tool for investigating causal relationships between …

The Interplay Between Deficit Spending And Financial Instability: An Examination Of Fiscal And Monetary Policy Interactions, Heidie Jean George

Doctoral Dissertations and Projects

This study investigates the impact of fiscal and monetary policy on financial stability and fragility, focusing on how government spending and deficits contribute to the economic and financial system. Drawing on Minsky’s Financial Instability Hypothesis (FIH) and Financial Fragility Hypothesis (FFH), the research examines the dynamic relationship between fiscal policy, financial stability, and economic stability. The study focuses on understanding how government spending and deficits affect the economic and financial system in context of private and public debt and policy interactions and the role of system risk factors. The study uses Principal Component Analysis (PCA), Vector Autoregression (VAR), Impulse Response …

Mycelial Modeling: Teaching Biology Students Statistical Modeling With Mushrooms, Colette Wolf

University Honors Theses

This paper summarizes and describes the development of a set of learning materials that were created to educate students and professionals from other fields in statistical modeling techniques. These materials are primarily aimed at biology students, but are still intended to be useful for anyone who is interested in incorporating decision trees and random forest models into their personal research in the future. By directing the reader towards the JMP software, these materials navigate around the statistical knowledge base and coding implementation practices that otherwise would serve as a barrier to learning statistical modeling techniques, and instead focus on the …

Bias, Structure, And Inference In Applied Network Analysis, Anna Vasenina

Dartmouth College Ph.D Dissertations

This dissertation develops mathematical and statistical methods for extracting reliable information from network data across biological applications, with an emphasis on understanding what observed network structure can and cannot resolve. The first study leverages protein–protein interaction network topology in the c-di-GMP signaling system of Pseudomonas fluorescens, showing that node centrality measures accurately classify protein domain types and that physical interaction structure contributes statistically significant predictive power for biofilm formation phenotypes across nearly 200 environments, while gene expression does not. The second study examines sampling bias in lemur-plant trophic interaction networks in Madagascar, demonstrating that differential detection of diurnal versus …

Statistical Methods In Research, Horahenage Dixon Vimalajeewa

UNL Faculty Course Portfolios

This course portfolio documents the design, delivery, assessment, student-learning evidence, and reflective evaluation of STAT 801A-700: Statistical Methods in Research, an online asynchronous service course designed to introduce students from diverse disciplinary backgrounds to foundational statistical reasoning and applied data analysis. The course is a non-calculus-based introduction to statistical methods used to answer research questions, with emphasis on collecting, organizing, describing, analyzing, and drawing conclusions from data. The course also emphasizes applications relevant to biology, agriculture, and other research-oriented fields. This is an online distance course aimed to develop students’ understanding of basic probability and statistical concepts, recognize the importance …

On M-Estimation: From Theory To Examples, Alexander Yuan

Master's Theses

M-estimation provides a unified framework for statistical procedures defined as optimizers of data-dependent criterion functions. This thesis gives an expository account of M-estimation in classical and high-dimensional settings. The classical part develops weak convergence, empirical process tools, and the argmax framework for studying consistency, rates of convergence, and weak limits. Examples including least squares, maximum likelihood, robust location estimation, change-point estimation, and empirical risk minimization illustrate regular and non-regular asymptotic behavior.

The high-dimensional part studies regularized M-estimators, where the focus shifts to finite-sample error bounds and model selection guarantees. Topics include decomposable regularizers, restricted strong convexity, non-convex penalties, and sparsistency. …

Structured Dynamic Factor Analysis Of Environmental Time Series With Application To Morro Bay Estuary, Jose Garcia

Master's Theses

This thesis develops a structured dynamic factor analysis (sDFA) framework for decomposing multivariate environmental time series into latent biological and physical components. The methodology is applied to five years of high-resolution passive monitoring data collected from two sites in Morro Bay, California from 2020 through 2024. Relative contribution indices are developed based on the structured DFA that measure how much each latent process contributes to each observed variable at any given time. Structured DFA models fit to the application data suggest site-specific patterns in how biological and physical processes affect water quality variables. At the bay mouth location, physical processes …

Developing A Humpback Whale Vocalization Detector Using Machine Learning Models, Lucas Kantorowski

Master's Theses

Humpback whale songs are notoriously complex. Identification of humpback whale song units requires bioacousticians to tediously listen, analyze, and annotate collected sound data. Even sparse data requires listening to the entirety of the collected acoustic data. In this study, three hours of audio containing over one-thousand humpback whale song units was collected in Monterey Bay, California.

Prior studies have seen success using convolutional neural networks by performing image classification on hundreds of hours worth of spectrograms. Our study uses traditional machine learning models, as they are less computationally demanding, and require less data.

We use time splitting and Mel-frequency cepstrum …

(R2133) Analysis Of A Bulk Queue With Balking, Adaptive Overloading Service, Multiple Vacation, Inspection And Rework, S. Karpagam, R. Lokesh

Applications and Applied Mathematics: An International Journal (AAM)

We consider a queueing system that utilizes a single server to manage product flow through bulk and overload service modes, depending on queue length. Balking occurs when the queue length reaches ‘N’. After completion of service, products undergo quality inspection, with defective products sent for rework based on specific probabilities. If the product is non-defective, the server continues processing until the queue length exceeds a certain threshold; beyond this point, the server is either routed back to bulk service or directed to an overload service. Also, the server goes into a vacation mode when the queue size is below a …

Muon Lifetime: Theory, Experiment, And Simulation, Soren Agustin Munoz

Physics

This senior project investigates the muon lifetime through three complementary approaches: theoretical calculation, laboratory measurement, and computational simulation. The theoretical component develops the necessary background from relativistic field theory to the effective weak interaction, culminating in the leading-order Fermi-theory prediction of τ ≈ 2.2 μs, which explains why the muon lifetime lies on the microsecond scale.

The experimental component measures the lifetime of stopped cosmic-ray muons using a plastic scintillator, photomultiplier tube, and analog timing electronics. A binned Poisson likelihood fit to the primary 15-day acquisition run τ = 2.17^+0.03_-0.09 μs, consistent with the accepted value within the …

A2s Uplink Latency Minimization For Wildfire Monitoring Systems Using Mbse And Stochastic Modeling, Luis Giovanni Wang

Master's Theses

Wildfire response depends on how quickly a detection reaches the people who act on it, and the slowest remaining step is often the link that carries an alert from a remote sensing platform to a satellite. This thesis models the latency of that link, the Air-to-Space uplink, for a wildfire-monitoring UAV that carries a Starlink terminal and sends an ALERT packet to a serving Low Earth Orbit satellite. The uplink is difficult to predict because both the UAV and the satellite move, and because the wildfire environment degrades the channel at the moment the data matters most.

The thesis uses …