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Articles 1 - 14 of 14
Full-Text Articles in Physical Sciences and Mathematics
Making Data-Driven Decisions For Investing In Restaurant Business: A Case Study Based On Zomato Dataset, Rachna Shah
Making Data-Driven Decisions For Investing In Restaurant Business: A Case Study Based On Zomato Dataset, Rachna Shah
All Graduate Theses, Dissertations, and Other Capstone Projects
In today’s fast-paced world, where time is a precious commodity, the ability to order a wide array of cuisines from the comfort of your home or office impacts your quality of life. With an increasing number of food delivery services, with just a few taps on the smartphone or clicks on the computer, we can enjoy the food we want. The importance of this convenience cannot be overstated, as it allows people to save time and effort that would otherwise be spent on cooking, grocery shopping, or dining out. As the food delivery system grows and develops, its economic framework …
Assessing And Forecasting Chlorophyll Abundances In Minnesota Lake Using Remote Sensing And Statistical Approaches, Ben Von Korff
Assessing And Forecasting Chlorophyll Abundances In Minnesota Lake Using Remote Sensing And Statistical Approaches, Ben Von Korff
All Graduate Theses, Dissertations, and Other Capstone Projects
Harmful algae blooms (HABs) can negatively impact water quality, lake aesthetics, and can harm human and animal health. However, monitoring for HABs is rare in Minnesota. Detecting blooms which can vary spatially and may only be present briefly is challenging, so expanding monitoring in Minnesota would require the use of new and cost efficient technologies. Unmanned aerial vehicles (UAVs) were used for bloom mapping using RGB and near-infrared imagery. Real time monitoring was conducted in Bass Lake, in Faribault County, MN using trail cameras. Time series forecasting was conducted with high frequency chlorophyll-a data from a water quality sonde. Normalized …
Comparing Various Robust Estimation Techniques In Regression Analysis, Tracy S. Morrison
Comparing Various Robust Estimation Techniques In Regression Analysis, Tracy S. Morrison
All Graduate Theses, Dissertations, and Other Capstone Projects
In regression analysis, the use of the ordinary least squares (OLS) method is inadvisable when dealing with outlier or extreme observations. As a result, we require a method of robust estimation in which the estimation value is not significantly affected by outlier or extreme observations. Four methods of estimation will be compared in this paper in order to determine the best estimation: the M estimation method, the Least Trimmed Square Estimator, the S-estimation method, and the MM estimation method in robust regression. We discover that the best method is the MM-estimation method in this study. The M-estimation method is an …
Classification Of Chess Games: An Exploration Of Classifiers For Anomaly Detection In Chess, Masudul Hoque
Classification Of Chess Games: An Exploration Of Classifiers For Anomaly Detection In Chess, Masudul Hoque
All Graduate Theses, Dissertations, and Other Capstone Projects
Chess is a strategy board game with its inception dating back to the 15th century. The Covid-19 pandemic has led to a chess boom online with 95,853,038 chess games being played during January, 2021 on lichess.com. Along with the chess boom, instances of cheating have also become more rampant. Classifications have been used for anomaly detection in different fields and thus it is a natural idea to develop classifiers to detect cheating in chess. However, there are no specific examples of this, and it is difficult to obtain data where cheating has occurred. So, in this paper, we develop 4 …
A Mathematical Model For Malaria With Age-Heterogeneous Biting Rate, Sho Kawakami
A Mathematical Model For Malaria With Age-Heterogeneous Biting Rate, Sho Kawakami
All Graduate Theses, Dissertations, and Other Capstone Projects
We propose a mathematical model for malaria with age-heterogeneous biting rate from mosquitos. The existence of the model, the local behavior of the disease free equilibrium are explored. Furthermore the model is extended to an optimal control problem and the corresponding adjoint equations and optimality conditions are derived. Age dependent parameter values are estimated and numerical simulations are carried out for the model. The new model better accounts for difference in biting rates of mosquitos to different age groups, and improvements in stability to the explicit algorithm. The optimal control is also shown to depend on the age distribution of …
Theory Of Principal Components For Applications In Exploratory Crime Analysis And Clustering, Daniel Silva
Theory Of Principal Components For Applications In Exploratory Crime Analysis And Clustering, Daniel Silva
All Graduate Theses, Dissertations, and Other Capstone Projects
The purpose of this paper is to develop the theory of principal components analysis succinctly from the fundamentals of matrix algebra and multivariate statistics. Principal components analysis is sometimes used as a descriptive technique to explain the variance-covariance or correlation structure of a dataset. However, most often, it is used as a dimensionality reduction technique to visualize a high dimensional dataset in a lower dimensional space. Principal components analysis accomplishes this by using the first few principal components, provided that they account for a substantial proportion of variation in the original dataset. In the same way, the first few principal …
Adaptive Smoothing Parameter In Kernel Density Estimation And Parameter Estimation In Normal Mixture Distributions, Sabiha Mahzabeen
Adaptive Smoothing Parameter In Kernel Density Estimation And Parameter Estimation In Normal Mixture Distributions, Sabiha Mahzabeen
All Graduate Theses, Dissertations, and Other Capstone Projects
Kernel density estimation is a widely used tool in nonparametric density estimation procedures. Choice of a kernel function and a smoothing parameter are two important issues in implementing kernel density estimation procedures. In this paper, four different kernel functions are considered in implementing an adaptive selection procedure in choosing the smoothing parameter. In simulation, a skewed bimodal density which is a mixture of two normal distributions is considered along with the standard normal and the standard exponential densities. In skewed bimodal data, parameter estimation is also explored in the context of the parameter estimation in mixtures of normal distributions. Maximum …
A Statistical Analysis And Machine Learning Of Genomic Data, Jongyun Jung
A Statistical Analysis And Machine Learning Of Genomic Data, Jongyun Jung
All Graduate Theses, Dissertations, and Other Capstone Projects
Machine learning enables a computer to learn a relationship between two assumingly related types of information. One type of information could thus be used to predict any lack of informaion in the other using the learned relationship. During the last decades, it has become cheaper to collect biological information, which has resulted in increasingly large amounts of data. Biological information such as DNA is currently analyzed by a variety of tools. Although machine learning has already been used in various projects, a flexible tool for analyzing generic biological challenges has not yet been made. The recent advancements in the DNA …
Selection Portfolio: Applying Modern Portfolio Theory To Personnel Selection, Eric Leingang
Selection Portfolio: Applying Modern Portfolio Theory To Personnel Selection, Eric Leingang
All Graduate Theses, Dissertations, and Other Capstone Projects
Modern Portfolio Theory (MPT) is a framework for building a portfolio of risky assets such that the ratio of risk to return is minimized. While this theory has been used in the field of financial economics for over sixty years, the method has not yet been applied to compensatory personnel selection. A common method for personnel selection is multiple regression to maximize the predicted performance of the selected group given a cut-off score on the predictor(s). Recognizing that maximizing the performance of the selected group is not the only consideration, and that, for many jobs and organizations, the outcomes of …
Derivation And Validation Of The Friction, Gravitational, And Air Forces Encountered During Installation Of Fiber Optic Cable, Faheed Olayemi Owokoniran
Derivation And Validation Of The Friction, Gravitational, And Air Forces Encountered During Installation Of Fiber Optic Cable, Faheed Olayemi Owokoniran
All Graduate Theses, Dissertations, and Other Capstone Projects
This paper presents an introduction to fiber optic cable and the fiber optic communication system. An important phase in the supply of this new technology is to transport the fiber optic cable to the vicinity of service. Cable pulling and cable blowing - laminar flow; piston type - are the two main methods of installing fiber optic cable. Both methods of installation have limiting factors that need to be evaluated in order to perform a successful installation. The limiting factors for laminar type cable blowing are further discussed in this paper. A method was proposed to determine the forces - …
Building A Predictive Model For Baseball Games, Jordan Robertson Tait
Building A Predictive Model For Baseball Games, Jordan Robertson Tait
All Graduate Theses, Dissertations, and Other Capstone Projects
In this paper, we will discuss a method of building a predictive model for Major League Baseball Games. We detail the reasoning for pursuing the proposed predictive model in terms of social popularity and the complexity of analyzing individual variables. We apply a coarse-grain outlook inspired by Simon Dedeos' work on Human Social Systems, in particular the open source website Wikipedia [2] by attempting to quantify the influence of winning and losing streaks instead of analyzing individual performance variables. We will discuss initial findings of data collected from the LA Dodgers and Colorado Rockies and apply further statistical analysis to …
Creating A User Satisfaction Index From A Parsimonious Survey Instrument, Brian Barthel
Creating A User Satisfaction Index From A Parsimonious Survey Instrument, Brian Barthel
All Graduate Theses, Dissertations, and Other Capstone Projects
In this paper we present a comprehensive method for creating a user satisfaction index using a survey instrument. First we construct a parsimonious survey instrument, using the PageRank Centrality, to measure attributes of user satisfaction. Then confirmatory factor analysis is applied to extract ``weights'' on the questions that are used in a linear model of computing the user satisfaction index. Throughout the paper an analysis of an existing data set is implemented to illustrate the proposed method. In addition the validity of the confirmatory factor model is tested using bootstrap sampling.
Internal Consistency Of The Self-Perception Profile For Children: Using Covariance Structure Modeling To Overcome The Limitations Of Cronbach's Α, Ian Cero
All Graduate Theses, Dissertations, and Other Capstone Projects
Self-perception is linked to a variety of psychosocial outcomes and its measurement has become a priority across a several disciplines. The Self-Perception Profile for Children (SPP-C) is commonly utilized to measure both global self worth and several important sub-domains of self-perception. Although much research has suggested this instrument possesses good internal consistency, previous investigations have primarily employed Cronbach's α; to estimate the stability of responding across items. This represents an important limitation, as α; is vulnerable to mis-estimation in the presence of correlated errors and non-τ-equivalent indicators, neither of which have been ruled out for the SPP-C. The present investigation …
Class Discovery And Prediction Of Tumor With Microarray Data, Bo Liu
Class Discovery And Prediction Of Tumor With Microarray Data, Bo Liu
All Graduate Theses, Dissertations, and Other Capstone Projects
Current microarray technology is able take a single tissue sample to construct an Affymetrix oglionucleotide array containing (estimated) expression levels of thousands of different genes for that tissue. The objective is to develop a more systematic approach to cancer classification based on Affymetrix oglionucleotide microarrays. For this purpose, I studied published colon cancer microarray data. Colon cancer, with 655,000 deaths worldwide per year, has become the fourth most common form of cancer in the United States and the third leading cause of cancer - related death in the Western world. This research has been focuses in two areas: class discovery, …