Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 330 for “"statistical sciences"”.
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Regression modeling: Latent structure, theories and algorithms
… Protection Agency/National Institute of Statistical Sciences) projects, which require the use of available data to make risk assessment, estimate uncertainty and suggest future studies. Based on the heterogeneous and batch correlated nature of the data, the thesis invents some new …
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Applications of functional data analysis to environmental problems.
… is a relatively recent framework within the statistical sciences, and while it offers compelling benefits to many applications, it has not yet gained widespread applied use. Two important environmental applications, water quality profile forecasting and larval fish photolocomotor response …
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Statistical investigation into academic performance in the Faculty of Science at the University of Cape Town in the period 1990-1997
… (UCT) accepted a proposal from the Department of Statistical Sciences to investigate several issues affecting students' performance in the Faculty. The proposal has led to developing this M.Sc. thesis. The major issue of concern in this study is to describe, on a retrospective basis, the extent to …
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Covariate-adjusted ROC regressions and the extensions in trend tests.
… graduate students within the Department of Statistical Sciences at Baylor University met with statisticians from Eli Lilly and Company to discuss ongoing long-term problems with the possibility that the department would begin collaborative work with the Lilly statisticians. One such problem …
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Biophysical Characterization of the Interaction between the Universal Stress G4LZI3 protein and Schistosoma mansoni Hsp60 Substrate Binding Domain
… of mathematical, computer, biological and statistical sciences to successfully analyse and interpret biological data. It can be used in the identification of molecule inhibitors as well as in identifying potential antigenic peptides that can be used in drug design (Blundell et al., 2006; …
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Data analysis in proteomics novel computational strategies for modeling and interpreting complex mass spectrometry data
… in proteomics -- with the computational and statistical sciences is still recent, and several avenues of exploratory data analysis and statistical methodology remain relatively unexplored. The current study focuses on three broad analytical domains, and develops novel exploratory approaches …
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Modelling highly imbalanced credit card fraud detection data using statistical learning
… has on the predictive capabilities of various statistical learning techniques. This study investigates the effect of three factors on model performance: 1) sampling technique, 2) supervised learning method, and 3) prevalence rate, also known as imbalance ratio (IR), which refers to the …
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Examination timetabling at the University of Cape Town: a tabu search approach to automation
With the rise of schedules and scheduling problems, solutions proposed in literature have expanded yet the disconnect between research and reality remains. The University of Cape Town's (UCT) Examinations Office currently produces their schedules manually with software relegated to error-checking …
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Automated detection and classification of red roman in unconstrained underwater environments using Mask R-CNN
… – this is critical for the utility of any statistical model outside of “laboratory conditions”. This research serves as a proof-of-concept that machine learning based methods of video analysis of marine data can replace or at least supplement human analysis.
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A web API service for calculating credit attributable to authors
The academic project “UniCoin” is designed to use the Ethereum blockchain to provide researchers with a way to licence their work. This provides a relatively economically efficient way to receive compensation for novel ideas, but is limited to research that is commercialisable. Foundational …
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Machine learning approaches towards tuning ALICE TRD simulations
In this work an exploration of the discrepancies existing between real and simulated data pertaining to the ALICE Transition Radiation Detector is carried out as a motivation to tune the necessary parameters in the ALICE Online-Offline simulation software (O2 ). After such exploration a single …
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Investigating automated bird detection from webcams using machine learning
… the large datasets using manual and traditional statistical techniques. Recent developments in the field of deep learning are showing promising results towards automating the analysis of these extremely large datasets. The primary objective of this study is to test the capabilities of the …
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Simplified approaches for portfolio decision analysis
Traditional choice decisions involve selecting a single, best alternative from a larger set of potential options. In contrast, portfolio decisions involve selecting the best subset of alternatives — alternatives that together maximize some measure of value to the decision maker and are within their …
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Bayesian analysis of historical functional linear models with application to air pollution forecasting
Historical functional linear models are used to analyse the relationship between a functional response and a functional predictor whereby only the past of the predictor process can affect the current outcome. In this work, we develop a Bayesian framework for the analysis of the historical …
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Deep hedging in incomplete markets
This dissertation presents an extensive analysis of the neural network approximation of mean-variance hedging with a comparison between the current neural network approaches and the theoretical solutions. These theoretical solutions provide a simulation-based performance benchmark for this …
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Changes in rainfall seasonality in the Western Cape, South Africa: an exploration of methods for determining the start and end of the rainfall season
The aim of this thesis is to detect and analyse changes in seasonality in rainfall for various groups of weather stations in the Western Cape area. Weather stations with similar seasonal patterns are firstly grouped together using certain clustering algorithms. The start and end of the rainfall …
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Radar-Based Multi-Target Classification Using Deep Learning
Real-time, radar-based human activity and target recognition has several applications in various fields. Examples include hand gesture recognition, border and home surveillance, pedestrian recognition for automotive safety and fall detection for assisted living. This dissertation sought to improve …
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A Machine Learning Model for Octane Number Prediction
Assessing the quality of gasoline blends in blending circuits is an important task in quality control. Gasoline quality however , cannot be measured directly on a process stream. Therefore a quality indicator which can be determined from the stream composition is required. Various quality …
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Sequential nonparametric estimation via Hermite series estimators
Algorithms for estimating the statistical properties of streams of data in real time, as well as for the efficient analysis of massive data sets, are becoming particularly pertinent given the increasing ubiquity of such data. In this thesis we introduce novel approaches to sequential (online) …
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Performance analysis of text classification algorithms for PubMed articles
The Medical Subject Headings (MeSH) thesaurus is a controlled vocabulary developed by the US National Library of Medicine (NLM) for indexing articles in Pubmed Central (PMC) archive. The annotation process is a complex and time-consuming task relying on subjective manual assignment of MeSH …
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