Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Computer Sciences (4)
- Social and Behavioral Sciences (3)
- Applied Statistics (2)
- Artificial Intelligence and Robotics (2)
- Biostatistics (2)
-
- Computer Engineering (2)
- Engineering (2)
- Life Sciences (2)
- Physics (2)
- Probability (2)
- Sociology (2)
- Animal Sciences (1)
- Applied Mathematics (1)
- Aquaculture and Fisheries (1)
- Biochemistry, Biophysics, and Structural Biology (1)
- Biodiversity (1)
- Computer and Systems Architecture (1)
- Demography, Population, and Ecology (1)
- Design of Experiments and Sample Surveys (1)
- Ecology and Evolutionary Biology (1)
- Education (1)
- Educational Methods (1)
- Electrical and Computer Engineering (1)
- Engineering Physics (1)
- Environmental Policy (1)
- Environmental Sciences (1)
- Higher Education (1)
- Institution
- Publication
-
- CCE Theses and Dissertations (1)
- Department of Electrical Engineering and Computer Science - Daytona Beach (1)
- Graduate Theses and Dissertations (1)
- Journal of Undergraduate Research at Minnesota State University, Mankato (1)
- Kuldeep Kumar (1)
-
- Masters Theses (1)
- Masters Theses, 2010-2019 (1)
- Mathematics Ancillary Materials (1)
- Physics Faculty Scholarship (1)
- RISK: Health, Safety & Environment (1990-2002) (1)
- University of New Orleans Theses and Dissertations (1)
- Williams Honors College, Honors Research Projects (1)
- Zea E-Books Collection (1)
- Publication Type
Articles 1 - 13 of 13
Full-Text Articles in Statistical Models
Mathematical Modeling: Instructor And Student Resources, Marnie Phipps, Patty Wagner
Mathematical Modeling: Instructor And Student Resources, Marnie Phipps, Patty Wagner
Mathematics Ancillary Materials
This collection of student and instructor materials for Mathematical Modeling contains lesson plans, lecture slides, homework, learning goals, and student notes for the following major topics:
- Linear Functions
- Quadratic Functions
- Exponential Functions
- Logarithmic Functions
This is a materials update for a collection of materials created for a Round Nine ALG Textbook Transformation Grant.
Structural Analysis Of The Multifunctional Spoiie Regulatory Protein Of Clostridioides Difficile., Blythe Emily Bunkers
Structural Analysis Of The Multifunctional Spoiie Regulatory Protein Of Clostridioides Difficile., Blythe Emily Bunkers
Graduate Theses and Dissertations
Clostridioides (formally Clostridium) difficile is a medically relevant pathogen pertinent to infectious disease research. C. difficile is distinctly known for its ability to produce two toxins, enterotoxin A and cytotoxin B, and the propensity to colonize the mammalian gastrointestinal tract. It is known that metabolism is tightly correlated with sporulation in endospore producers such as C. difficile, but an interesting and novel regulatory relationship found by the Ivey lab has yet to be understood. The relationship explored in this study is observed between the sporulation factor, SpoIIE, which represses expression of an ABC peptide transporter, app. In this study, two …
An Examination Of Covid-19 Statistical Modeling, Shane Vaughan
An Examination Of Covid-19 Statistical Modeling, Shane Vaughan
Williams Honors College, Honors Research Projects
The 2019 novel coronavirus, also known as COVID-19, is an infectious disease which was first reported in late 2019 and soon spread to become a global pandemic, prompting major action from world governments. Soon after, many institutions began attempts to analyze and predict the spread and severity of the disease via statistical modeling. Some information is not available for public consumption; however, a number of institutions have published the results of their analyses and some have made public repositories of the code used to build the models. This research paper attempts use these and other resources to examine the modeling …
Essentials Of Structural Equation Modeling, Mustafa Emre Civelek
Essentials Of Structural Equation Modeling, Mustafa Emre Civelek
Zea E-Books Collection
Structural Equation Modeling is a statistical method increasingly used in scientific studies in the fields of Social Sciences. It is currently a preferred analysis method, especially in doctoral dissertations and academic researches. However, since many universities do not include this method in the curriculum of undergraduate and graduate courses, students and scholars try to solve the problems they encounter by using various books and internet resources.
This book aims to guide the researcher who wants to use this method in a way that is free from math expressions. It teaches the steps of a research program using structured equality modeling …
Automated Sea State Classification From Parameterization Of Survey Observations And Wave-Generated Displacement Data, Jason A. Teichman
Automated Sea State Classification From Parameterization Of Survey Observations And Wave-Generated Displacement Data, Jason A. Teichman
University of New Orleans Theses and Dissertations
Sea state is a subjective quantity whose accuracy depends on an observer’s ability to translate local wind waves into numerical scales. It provides an analytical tool for estimating the impact of the sea on data quality and operational safety. Tasks dependent on the characteristics of local sea surface conditions often require accurate and immediate assessment. An attempt to automate sea state classification using eleven years of ship motion and sea state observation data is made using parametric modeling of distribution-based confidence and tolerance intervals and a probabilistic model using sea state frequencies. Models utilizing distribution intervals are not able to …
Niche-Based Modeling Of Japanese Stiltgrass (Microstegium Vimineum) Using Presence-Only Information, Nathan Bush
Niche-Based Modeling Of Japanese Stiltgrass (Microstegium Vimineum) Using Presence-Only Information, Nathan Bush
Masters Theses
The Connecticut River watershed is experiencing a rapid invasion of aggressive non-native plant species, which threaten watershed function and structure. Volunteer-based monitoring programs such as the University of Massachusetts’ OutSmart Invasives Species Project, Early Detection Distribution Mapping System (EDDMapS) and the Invasive Plant Atlas of New England (IPANE) have gathered valuable invasive plant data. These programs provide a unique opportunity for researchers to model invasive plant species utilizing citizen-sourced data. This study took advantage of these large data sources to model invasive plant distribution and to determine environmental and biophysical predictors that are most influential in dispersion, and to identify …
Using Capture-Mark-Recapture Techniques To Estimate Detection Probabilities & Fidelity Of Expression For The Critically Endangered James Spinymussel (Pleurobema Collina)., Alaina C. Esposito
Using Capture-Mark-Recapture Techniques To Estimate Detection Probabilities & Fidelity Of Expression For The Critically Endangered James Spinymussel (Pleurobema Collina)., Alaina C. Esposito
Masters Theses, 2010-2019
The critically endangered James Spinymussel (Pleurobema collina) is a species of freshwater mussel endemic to Virginia’s James and Dan River basins. In the last 20 years, P. collina has experienced a substantial decline in numbers and currently occupies approximately 10% of its original habitat; however, little information is known about this species to assist in conservation. A 230-meter reach of transitional habitat in Swift Run was selected for repeat observations to estimate detection probabilities using a Capture-Mark-Recapture framework. In June 2014, visual scouting began to locate and tag P. collina (including other mussels in the community) with PIT …
Dependency-Topic-Affects-Sentiment-Lda Model For Sentiment Analysis, Shunshun Yin, Jun Han, Yu Huang, Kuldeep Kumar
Dependency-Topic-Affects-Sentiment-Lda Model For Sentiment Analysis, Shunshun Yin, Jun Han, Yu Huang, Kuldeep Kumar
Kuldeep Kumar
Sentiment analysis tends to use automated approaches to mine the sentiment information expressed in text, such as reviews, blogs and forum discussions. As most traditional approaches for sentiment analysis are based on supervised learning models and need many labeled corpora as their training data which are not always easily obtained, various unsupervised models based on Latent Dirichlet Allocation (LDA) have been proposed for sentiment classification. In this paper, we propose a novel probabilistic modeling framework based on LDA, called Dependency-Topic-Affects-Sentiment-LDA (DTAS) model, which drops the ”bag of words” assumption and assumes that the topics of sentences in a document form …
A Predictive Modeling System: Early Identification Of Students At-Risk Enrolled In Online Learning Programs, Mary L. Fonti
A Predictive Modeling System: Early Identification Of Students At-Risk Enrolled In Online Learning Programs, Mary L. Fonti
CCE Theses and Dissertations
Predictive statistical modeling shows promise in accurately predicting academic performance for students enrolled in online programs. This approach has proven effective in accurately identifying students who are at-risk enabling instructors to provide instructional intervention. While the potential benefits of statistical modeling is significant, implementations have proven to be complex, costly, and difficult to maintain. To address these issues, the purpose of this study is to develop a fully integrated, automated predictive modeling system (PMS) that is flexible, easy to use, and portable to identify students who are potentially at-risk for not succeeding in a course they are currently enrolled in. …
Mathematical Modeling And Simulation Of Multialleic Migration-Selection Models, Chad N. Vidden
Mathematical Modeling And Simulation Of Multialleic Migration-Selection Models, Chad N. Vidden
Journal of Undergraduate Research at Minnesota State University, Mankato
Population ecology is concerned with the growth and decay of specific populations. This field has a variety of applications ranging from evolution and survival at the environmental level to the spread of infectious disease at the cellular and molecular levels. Many ecological circumstances require the use of mathematical methods and reasoning in order to acquire better knowledge of the issue at hand. This study considered and analyzed multiple different mathematical models of population dynamics along with their purposes. This foundation was then applied in order to explore the migration of populations from one isolated region to another along with the …
Measuring Security: A Challenge For The Generation, Janusz Zalewski, Steven Drager, William Mckeever, Andrew J. Kornecki
Measuring Security: A Challenge For The Generation, Janusz Zalewski, Steven Drager, William Mckeever, Andrew J. Kornecki
Department of Electrical Engineering and Computer Science - Daytona Beach
This paper presents an approach to measuring computer security understood as a system property, in the category of similar properties, such as safety, reliability, dependability, resilience, etc. First, a historical discussion of measurements is presented, beginning with views of Hermann von Helmholtz in his 19th century work “Zählen und Messen”. Then, contemporary approaches related to the principles of measuring software properties are discussed, with emphasis on statistical, physical and software models. A distinction between metrics and measures is made to clarify the concepts. A brief overview of inadequacies of methods and techniques to evaluate computer security is presented, followed by …
Modeling A Sensor To Improve Its Efficacy, Nabin K. Malakar, Daniil Gladkov, Kevin H. Knuth
Modeling A Sensor To Improve Its Efficacy, Nabin K. Malakar, Daniil Gladkov, Kevin H. Knuth
Physics Faculty Scholarship
Robots rely on sensors to provide them with information about their surroundings. However, high-quality sensors can be extremely expensive and cost-prohibitive. Thus many robotic systems must make due with lower-quality sensors. Here we demonstrate via a case study how modeling a sensor can improve its efficacy when employed within a Bayesian inferential framework. As a test bed we employ a robotic arm that is designed to autonomously take its own measurements using an inexpensive LEGO light sensor to estimate the position and radius of a white circle on a black field. The light sensor integrates the light arriving from a …
Monte Carlo Simulation In Environmental Risk Assessment--Science, Policy And Legal Issues, Susan R. Poulter
Monte Carlo Simulation In Environmental Risk Assessment--Science, Policy And Legal Issues, Susan R. Poulter
RISK: Health, Safety & Environment (1990-2002)
Dr. Poulter notes that agencies should anticipate judicial requirements for justification of Monte Carlo simulations and, meanwhile, should consider, e.g., whether their use will make risk assessment policy choices more opaque or apparent.