Data Patterns Discovery Using Unsupervised Learning,
2019
Georgia Southern University
Data Patterns Discovery Using Unsupervised Learning, Rachel A. Lewis
College of Graduate Studies: Theses & Dissertations
Self-care activities classification poses significant challenges in identifying children’s unique functional abilities and needs within the exceptional children healthcare system. The accuracy of diagnosing a child's self-care problem, such as toileting or dressing, is highly influenced by an occupational therapists’ experience and time constraints. Thus, there is a need for objective means to detect and predict in advance the self-care problems of children with physical and motor disabilities. We use clustering to discover interesting information from self-care problems, perform automatic classification of binary data, and discover outliers. The advantages are twofold: the advancement of knowledge on identifying self-care problems in …
A Multilayer Exponential Random Graph Modelling Approach For Weighted Networks,
2019
Technological University Dublin
A Multilayer Exponential Random Graph Modelling Approach For Weighted Networks, Alberto Caimo, Isabella Gollini
Articles
A new modelling approach for the analysis of weighted networks with ordinal/polytomous dyadic values is introduced. Specifically, it is proposed to model the weighted network connectivity structure using a hierarchical multilayer exponential random graph model (ERGM) generative process where each network layer represents a different ordinal dyadic category. The network layers are assumed to be generated by an ERGM process conditional on their closest lower network layers. A crucial advantage of the proposed method is the possibility of adopting the binary network statistics specification to describe both the between-layer and across-layer network processes and thus facilitating the interpretation of the …
Some New Generalized Distribution Via Lindley-Weibuli And Lindley-Log-Logistic Distributions With Applications,
2019
Georgia Southern University
Some New Generalized Distribution Via Lindley-Weibuli And Lindley-Log-Logistic Distributions With Applications, Soliu A. Raheem
College of Graduate Studies: Theses & Dissertations
In this thesis, new generalized distributions, namely Beta Lindley-Log-Logistic (BLLLoG) distribution, Marshall-Olkin Lindley-Weibull (MOLW) distribution, and Gamma LindleyWeibull (GLW) distribution as well as related sub-distributions are proposed. Series expansion of the densities are obtained. Statistical properties of these distributions, including hazard function, reverse hazard function, moments, reliability, quantile function, mean deviations, Bonferroni and Lorenz curves, entropy and Fisher information are derived. Method of maximum likelihood is used to estimate the parameters of the new distributions. Monte Carlo simulation is employed to examine the performance of the proposed distributions. Applications of the generalized distributions to real lifetime data are presented to …
Variable Selection In Accelerated Failure Time (Aft) Frailty Models: An Application Of Penalized Quasi-Likelihood,
2019
Georgia Southern University
Variable Selection In Accelerated Failure Time (Aft) Frailty Models: An Application Of Penalized Quasi-Likelihood, Sarbesh R. Pandeya
College of Graduate Studies: Theses & Dissertations
Variable selection is one of the standard ways of selecting models in large scale datasets. It has applications in many fields of research study, especially in large multi-center clinical trials. One of the prominent methods in variable selection is the penalized likelihood, which is both consistent and efficient. However, the penalized selection is significantly challenging under the influence of random (frailty) covariates. It is even more complicated when there is involvement of censoring as it may not have a closed-form solution for the marginal log-likelihood. Therefore, we applied the penalized quasi-likelihood (PQL) approach that approximates the solution for such a …
Quantifying Human Biological Age: A Machine Learning Approach,
2019
West Virginia University
Quantifying Human Biological Age: A Machine Learning Approach, Syed Ashiqur Rahman
Graduate Theses, Dissertations, and Problem Reports (ETD)
Quantifying human biological age is an important and difficult challenge. Different biomarkers and numerous approaches have been studied for biological age prediction, each with its advantages and limitations. In this work, we first introduce a new anthropometric measure (called Surface-based Body Shape Index, SBSI) that accounts for both body shape and body size, and evaluate its performance as a predictor of all-cause mortality. We analyzed data from the National Health and Human Nutrition Examination Survey (NHANES). Based on the analysis, we introduce a new body shape index constructed from four important anthropometric determinants of body shape and body size: body …
Adult Atlantic Sturgeon Population Dynamics In The York River, Virginia,
2019
West Virginia University
Adult Atlantic Sturgeon Population Dynamics In The York River, Virginia, Jason E. Kahn
Graduate Theses, Dissertations, and Problem Reports (ETD)
Sturgeon first appear in the fossil record in the Triassic Period just over 200 million years ago and are among the most primitive of the bony fishes. Despite their large size and historic presence along the East Coast, Atlantic sturgeon were not targeted for their meat and caviar as a commercial fishery until 1880. By 1905 they had declined to less than one percent of their pre-fishing abundance but the fishery continued. Prior to 1980, there had been very little research on Atlantic sturgeon, primarily limited to documenting landing location and poundage, maximum longevity, or weight of eggs per fish. …
International Risk Sharing In Overlapping Generations Models,
2018
Babson College
International Risk Sharing In Overlapping Generations Models, James Staveley-O'Carroll, Olena M. Staveley-O'Carroll
Economics Department Working Papers
We present a solution to the Backus-Smith puzzle that, instead of relying on extreme parameter values or complex modeling assumptions, simply switches the framework from infinitely lived agents to overlapping generations. Young agents face non-diversifiable wage risk that leads to a low degree of risk sharing within each country. Subsequently, international price movements are not sufficient to achieve the high consumption-real exchange rate correlation produced in standard infinitely lived agent DSGE models.
Effectiveness Of Prescribed Fire On Meeting Fuel Load And Wildlife Habitat Management Objectives In East Texas National Forests,
2018
Stephen F Austin State University
Effectiveness Of Prescribed Fire On Meeting Fuel Load And Wildlife Habitat Management Objectives In East Texas National Forests, Trey Wall
Electronic Theses and Dissertations
Using standardized methodology outlined by the United States Forest Service and the National Forests and Grasslands in Texas’ Fire Monitoring Program for data collection, the efficacy of current Forest Service prescribed burn regimes were analyzed for 24 study sites in East Texas National Forests. Study sites were located within Sam Houston, Davy Crockett, and Angelina/Sabine National Forests. Efficacy was determined by comparing defined management objectives established by the Forest Service to the data collected at the study sites. The results conclude that most objectives, as outlined by the Forest Service, are not being met with the current practices. Re-visitation of …
Rfviz: An Interactive Visualization Package For Random Forests In R,
2018
Utah State University
Rfviz: An Interactive Visualization Package For Random Forests In R, Christopher Beckett
All Graduate Plan B and other Reports, Spring 1920 to Spring 2023
Random forests are very popular tools for predictive analysis and data science. They work for both classification (where there is a categorical response variable) and regression (where the response is continuous). Random forests provide proximities, and both local and global measures of variable importance. However, these quantities require special tools to be effectively used to interpret the forest. Rfviz is a sophisticated interactive visualization package and toolkit in R, specially designed for interpreting the results of a random forest in a user-friendly way. Rfviz uses a recently developed R package (loon) from the Comprehensive R Archive Network (CRAN) to create …
Statistical Investigation Of Road And Railway Hazardous Materials Transportation Safety,
2018
University of Nebraska-Lincoln
Statistical Investigation Of Road And Railway Hazardous Materials Transportation Safety, Amirfarrokh Iranitalab
Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research
Transportation of hazardous materials (hazmat) in the United States (U.S.) constituted 22.8% of the total tonnage transported in 2012 with an estimated value of more than 2.3 billion dollars. As such, hazmat transportation is a significant economic activity in the U.S. However, hazmat transportation exposes people and environment to the infrequent but potentially severe consequences of incidents resulting in hazmat release. Trucks and trains carried 63.7% of the hazmat in the U.S. in 2012 and are the major foci of this dissertation. The main research objectives were 1) identification and quantification of the effects of different factors on occurrence and …
Snakebite Dynamics Of Colombia: Effects Of Precipitation Seasonality Of Incidence,
2018
Illinois State University
Snakebite Dynamics Of Colombia: Effects Of Precipitation Seasonality Of Incidence, Carlos Cruz
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Season-Ahead Forecasting Of Water Storage And Irrigation Requirements – An Application To The Southwest Monsoon In India,
2018
CUNY City College
Season-Ahead Forecasting Of Water Storage And Irrigation Requirements – An Application To The Southwest Monsoon In India, Arun Ravindranath, Naresh Devineni, Upmanu Lall, Paulina Concha Larrauri
Publications and Research
Water risk management is a ubiquitous challenge faced by stakeholders in the water or agricultural sector. We present a methodological framework for forecasting water storage requirements and present an application of this methodology to risk assessment in India. The application focused on forecasting crop water stress for potatoes grown during the monsoon season in the Satara district of Maharashtra. Pre-season large-scale climate predictors used to forecast water stress were selected based on an exhaustive search method that evaluates for highest ranked probability skill score and lowest root-mean-squared error in a leave-one-out cross-validation mode. Adaptive forecasts were made in the years …
Nonlinearities In The Real Exchange Rates: New Evidence From Developed And Developing Countries,
2018
University of Wisconsin - Whitewater
Nonlinearities In The Real Exchange Rates: New Evidence From Developed And Developing Countries, Yamin S. Ahmad, Ming Chien Lo, Olena M. Staveley-O'Carroll
Economics Department Working Papers
This paper investigates nonlinearities in the dynamics of real exchange rates. We use Monte Carlo simulations to establish the size properties of the Teräsvirta-Anderson (1992) and the Teräsvirta (1994) test, when the dynamics of the real exchange rate is influenced by an exogenous process. In addition, we examine the modification proposed by Ahmad, Lo and Mykhaylova (2013; Journal of International Economics) to show that the modified nonlinearity test performs much better than the original in both Monte Carlo exercises and in the actual data on 1431 bilateral real exchange rate series. Finally, we investigate the dynamics of the real exchange …
Habitat Preferences Of Blue Marlin (Makaira Nigricans) And Black Marlin (Istiompax Indica) In The Eastern Pacific Ocean,
2018
University of San Diego
Habitat Preferences Of Blue Marlin (Makaira Nigricans) And Black Marlin (Istiompax Indica) In The Eastern Pacific Ocean, Nima Farchadi, Michael G. Hinton, Andrew R. Thompson, Zhi-Yong Yin
Theses
Overexploitation and climate change can reduce the abundance and shift the spatial distribution of marine species. Determining the habitat suitability of a mobile pelagic species, such as Makaira nigricans (BUM) and Istiompax indica (BLM), can help describe their spatiotemporal distribution patterns over a broad spatial scale, which is a crucial need for fisheries management. Using 14 years (1997-2010) of Inter-American Tropical Tuna Commission (IATTC) catch data from purse-seine vessels in the eastern Pacific Ocean (EPO), we modeled the dynamic habitat suitability of BUM and BLM in response to environmental variables within the EPO using a species distribution model (MaxEnt) with …
Overcoming Small Data Limitations In Heart Disease Prediction By Using Surrogate Data,
2018
Southern Methodist University
Overcoming Small Data Limitations In Heart Disease Prediction By Using Surrogate Data, Alfeo Sabay, Laurie Harris, Vivek Bejugama, Karen Jaceldo-Siegl
SMU Data Science Review
In this paper, we present a heart disease prediction use case showing how synthetic data can be used to address privacy concerns and overcome constraints inherent in small medical research data sets. While advanced machine learning algorithms, such as neural networks models, can be implemented to improve prediction accuracy, these require very large data sets which are often not available in medical or clinical research. We examine the use of surrogate data sets comprised of synthetic observations for modeling heart disease prediction. We generate surrogate data, based on the characteristics of original observations, and compare prediction accuracy results achieved from …
Minimizing The Perceived Financial Burden Due To Cancer,
2018
Southern Methodist University
Minimizing The Perceived Financial Burden Due To Cancer, Hassan Azhar, Zoheb Allam, Gino Varghese, Daniel W. Engels, Sajiny John
SMU Data Science Review
In this paper, we present a regression model that predicts perceived financial burden that a cancer patient experiences in the treatment and management of the disease. Cancer patients do not fully understand the burden associated with the cost of cancer, and their lack of understanding can increase the difficulties associated with living with the disease, in particular coping with the cost. The relationship between demographic characteristics and financial burden were examined in order to better understand the characteristics of a cancer patient and their burden, while all subsets regression was used to determine the best predictors of financial burden. Age, …
Yelp’S Review Filtering Algorithm,
2018
Southern Methodist University
Yelp’S Review Filtering Algorithm, Yao Yao, Ivelin Angelov, Jack Rasmus-Vorrath, Mooyoung Lee, Daniel W. Engels
SMU Data Science Review
In this paper, we present an analysis of features influencing Yelp's proprietary review filtering algorithm. Classifying or misclassifying reviews as recommended or non-recommended affects average ratings, consumer decisions, and ultimately, business revenue. Our analysis involves systematically sampling and scraping Yelp restaurant reviews. Features are extracted from review metadata and engineered from metrics and scores generated using text classifiers and sentiment analysis. The coefficients of a multivariate logistic regression model were interpreted as quantifications of the relative importance of features in classifying reviews as recommended or non-recommended. The model classified review recommendations with an accuracy of 78%. We found that reviews …
Cryptocurrency Price Prediction Using Tweet Volumes And Sentiment Analysis,
2018
Southern Methodist University
Cryptocurrency Price Prediction Using Tweet Volumes And Sentiment Analysis, Jethin Abraham, Daniel Higdon, John Nelson, Juan Ibarra
SMU Data Science Review
In this paper, we present a method for predicting changes in Bitcoin and Ethereum prices utilizing Twitter data and Google Trends data. Bitcoin and Ethereum, the two largest cryptocurrencies in terms of market capitalization represent over \$160 billion dollars in combined value. However, both Bitcoin and Ethereum have experienced significant price swings on both daily and long term valuations. Twitter is increasingly used as a news source influencing purchase decisions by informing users of the currency and its increasing popularity. As a result, quickly understanding the impact of tweets on price direction can provide a purchasing and selling advantage to …
Study On The Efficiency Of China’S Main River Ports Based On Dea Model,
2018
World Maritime University
Study On The Efficiency Of China’S Main River Ports Based On Dea Model, Yunwu Cao
World Maritime University Dissertations
No abstract provided.
Optimization For Lng Terminals Routing In North China,
2018
World Maritime University
Optimization For Lng Terminals Routing In North China, Shuting Wang
World Maritime University Dissertations
No abstract provided.
