Multivariate Analysis Commons^™

Measuring The Performance Of Sdgs In Provincial Level Using Regional Sustainable Development Index, Nurafiza Thamrin, Ika Yuni Wulansari, Puguh Bodro Irawan

Journal of Environmental Science and Sustainable Development

Measuring the national and sub-national progress in achieving such globally adopted development agendas as Sustainable Development Goals (SDGs) is particularly challenging due to data availability and compatibility of indicators to measure SDGs, especially in Indonesia. This paper attempts to measure the performance of sustainable development at the regional level in Indonesia by newly constructing a multidimensional composite index called the Regional Sustainable Development Index (RSDI). RSDI comprises four dimensions, covering comprehensive economic, social, environmental, and governance indicators. By applying factor analysis, the paper assesses the uncertainty of RSDI and the sensitivity of its composing indicators, then further investigates the relationship …

Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia

Journal of Nonprofit Innovation

Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.

Imagine Doris, who is …

Differentiation Of Human, Dog, And Cat Hair Fibers Using Dart Tofms And Machine Learning, Laura Ahumada, Erin R. Mcclure-Price, Chad Kwong, Edgard O. Espinoza, John Santerre

SMU Data Science Review

Hair is found in over 90% of crime scenes and has long been analyzed as trace evidence. However, recent reviews of traditional hair fiber analysis techniques, primarily morphological examination, have cast doubt on its reliability. To address these concerns, this study employed machine learning algorithms, specifically Linear Discriminant Analysis (LDA) and Random Forest, on Direct Analysis in Real Time time-of-flight mass spectra collected from human, cat, and dog hair samples. The objective was to develop a chemistry- and statistics-based classification method for unbiased taxonomic identification of hair. The results of the study showed that LDA and Random Forest were highly …

Nonparametric Derivative Estimation Using Penalized Splines: Theory And Application, Bright Antwi Boasiako

Doctoral Dissertations

This dissertation is in the field of Nonparametric Derivative Estimation using
Penalized Splines. It is conducted in two parts. In the first part, we study the L2
convergence rates of estimating derivatives of mean regression functions using penalized splines. In 1982, Stone provided the optimal rates of convergence for estimating derivatives of mean regression functions using nonparametric methods. Using these rates, Zhou et. al. in their 2000 paper showed that the MSE of derivative estimators based on regression splines approach zero at the optimal rate of convergence. Also, in 2019, Xiao showed that, under some general conditions, penalized spline estimators …

Parameter Estimation For Normally Distributed Grouped Data And Clustering Single-Cell Rna Sequencing Data Via The Expectation-Maximization Algorithm, Zahra Aghahosseinalishirazi

Electronic Thesis and Dissertation Repository

The Expectation-Maximization (EM) algorithm is an iterative algorithm for finding the maximum likelihood estimates in problems involving missing data or latent variables. The EM algorithm can be applied to problems consisting of evidently incomplete data or missingness situations, such as truncated distributions, censored or grouped observations, and also to problems in which the missingness of the data is not natural or evident, such as mixed-effects models, mixture models, log-linear models, and latent variables. In Chapter 2 of this thesis, we apply the EM algorithm to grouped data, a problem in which incomplete data are evident. Nowadays, data confidentiality is of …

Statistical And Biological Analyses Of Acoustic Signals In Estrildid Finches, Moises Rivera

Dissertations, Theses, and Capstone Projects

Acoustic communication is a process that involves auditory perception and signal processing. Discrimination and recognition further require cognitive processes and supporting mechanisms in order to successfully identify and appropriately respond to signal senders. Although acoustic communication is common across birds, classical research has largely disregarded the perceptual abilities of perinatal altricial taxa. Chapter 1 reviews the literature of perinatal acoustic stimulation in birds, highlighting the disproportionate focus on precocial birds (e.g., chickens, ducks, quails). The long-held belief that altricial birds were incapable of acoustic perception in ovo was only recently overturned, as researchers began to find behavioral and physiological evidence …

Employee Attrition: Analyzing Factors Influencing Job Satisfaction Of Ibm Data Scientists, Graham Nash

Symposium of Student Scholars

Employee attrition is a relevant issue that every business employer must consider when gauging the effectiveness of their employees. Whether or not an employee chooses to leave their job can come from a multitude of factors. As a result, employers need to develop methods in which they can measure attrition by calculating the several qualities of their employees. Factors like their age, years with the company, which department they work in, their level of education, their job role, and even their marital status are all considered by employers to assist in predicting employee attrition. This project will be analyzing a …

Application Of Gaussian Mixture Models To Simulated Additive Manufacturing, Jason Hasse, Semhar Michael, Anamika Prasad

SDSU Data Science Symposium

Additive manufacturing (AM) is the process of building components through an iterative process of adding material in specific designs. AM has a wide range of process parameters that influence the quality of the component. This work applies Gaussian mixture models to detect clusters of similar stress values within and across components manufactured with varying process parameters. Further, a mixture of regression models is considered to simultaneously find groups and also fit regression within each group. The results are compared with a previous naive approach.

Modeling And Fitting Two-Way Tables Containing Outliers, David L. Farnsworth

Articles

A model is proposed for two-way tables of measurement data containing outliers. The two independent variables are categorical and error free. Neither missing values nor replication are present. The model consists of the sum of a customary additive part that can be fit using least squares and a part that is composed of outliers. Recommendations are made for methods for identifying cells containing outliers and for fitting the model. A graph of the observations is used to determine the outliers’ locations. For all cells containing an outlier, replacement values are determined simultaneously using a classical missing-data tool. The result is …

The Impact Of Subjective Risk Analysis On Real Estate Prices In The Nisqually Region Following The 2001 Nisqually Earthquake, Ryan Espedal

All Master's Theses

Earthquakes are an environmental hazard that pose great risks to communities almost every day. With earthquakes, the main cause of concern is physical destruction of property, however, there are also psychological effects that are researched and discussed much less. In 2001, the Nisqually area of western Washington experienced a substantial earthquake that produced minimal physical damage but caused a significant decrease in real estate prices. Studying single-family homes from 1986-2012, this research utilizes hedonic property models to measure the change in consumer’s subjective risk calculations with reference to real estate purchases after the Nisqually earthquake, measure the relationship between earthquake …

Impacts Of Covid-19 On Industrial Growth In The United States, Emily G. Warthman, Charles J. Landis

Williams Honors College, Honors Research Projects

COVID-19 has caused massive ramifications on all parts of life in the world and industry growth/decline is not immune to it. This report will analyze nine different industries’ profit and revenue from quarterly data during the years 2009-2022. Forecast models will be generated using various methods and different techniques of validating to predict the values from Q2 2020- Q4 2022 based on historical data. After which, a comparison will be conducted between those predicted values to the actual average revenue and profit generated by order of greatest error percentage made. Thorough research will then be completed to determine if there …

Enforcement Penalties At The Itc, Andrea R. Hugill, John C. Jarosz, Katherine D. Cappaert

Northwestern Journal of International Law & Business

The U.S. International Trade Commission (“ITC” or “Commission”) has grown in importance as a venue for U.S. companies to pursue intellectual property (“IP”) violators and to block the sale or importation of goods from overseas that infringe U.S. IP rights. Once a violation of the Section 337 of the Tariff Act of 1930 is found, an order halting further infringement, including importation, is almost always entered. In theory, potentially sizeable penalties may be imposed on entities that do not comply with the terms of an import restriction. In practice, the terms of an import restriction are almost always honored, but …

Modeling Growth And Stress Factors For Converted Silvopasture Systems In The Missouri Ozarks, Bailee N. Suedmeyer

MSU Graduate Theses

Silvopasture systems are becoming increasingly popular among sustainable agriculture ranchers, due to the increase in knowledge of benefits to the cattle and ability to grow cool season grasses beneath the canopy. This project focuses on the forest crop aspect of silvopasture systems from monitoring of the health of the trees over time to recommendations for thinning management to keep it functioning as viable silvopasture. The study site consists of five acres of upland hardwood forest area in Southern Missouri with 18 monumented fixed area plots. Arial and ground data was collected at each plot throughout the growing season, along with …