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.
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Showing 1 to 20 of 57 for “"Large Data Set"”.
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Measuring the accuracy of four attributes of sound for conveying changes in a large data set.
… generated would changed based on the underlying data value at any given point. An experiment was conducted to determine which attribute of sound most accurately represents data values in an auditory display. The four attributes of sound tested were frequency-sine waveform, frequency-sawtooth …
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Long term statistical studies of ionospheric absorption
… in MATLAB to enable statistical analysis on IRIS data. This toolkit provides a catalogue of analysed IRIS data and statistical analysis in automated and efficient manner. The end results are histograms, tables and plots that are generated automatically from the output of the statistical analysis. …
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Using Graph Clustering to Analyze the Spread of an Infectious Disease on a Random Large Social Network Graph
… the spread of an infectious disease on a random large social network graph. The goal is to determine if graph clustering techniques are a viable option to reduce workload of analyzing of a large data set. A random graph generator was developed using characteristics from the Forest Fire Model. We …
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A system to predict the S&P 500 using a bio-inspired algorithm
… different financial markets using historical data, testing on an in-sample and trend basis with many employing sophisticated mathematical techniques. In reviewing and evaluating these in-sample methodologies, it became evident that this approach was unable to achieve sufficiently reliable …
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Sublinear algorithms for massive data problems
… problems in the models that address massive data sets. The models include streaming algorithms, sublinear time algorithms, property testing algorithms, sublinear query time algorithms with preprocessing, or computing small summaries for large data. More precisely, we study the following …
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Change propagation in large technical systems
… extend prior reasoning through examination of a large data set from industry, including data from more than 41,000 change requests (most technical, but others not) over nearly a decade. Different methods are used to analyze the data from a variety of perspectives, in both the technical and …
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Visualization of spatio-temporal data in two dimensional space
Spatio-temporal data is becoming very popular in the recent times, as there are large number of datasets that collect both location and temporal information in the real time. The main challenge is that extracting useful insights from such large data set is extremely complex and laborious. In this …
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Modelling the influence of the froth phase on recovery in batch and continuous flotation cells
To determine model parameters, a large data set was required. This is due to the semi-empirical nature of the proposed froth model. In this regard, the use of data obtained from continuously operated cells was therefore not suitable for deriving model parameters. It was thought that this could only …
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Inner city shopping centers : national development trends and local community impacts
… economic development strategy. In this thesis, a large data set of all US shopping centers is analyzed to examine general trends in shopping center development, as well as trends in inner-city shopping center development over time. This research showed that inner-city centers are fairly similar to …
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Unsupervised discovery of emphysema subtypes in a large clinical cohort
… approaches to modeling emphysema imaging data have focused on supervised classification of lung textures in patches of CT scans. In this work, we describe a generative model that jointly captures heterogeneity of disease subtypes and of the patient population. We also derive a …
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Semiparametric Bayesian Count Data Models
Count data models have a large number of pratical applications. However there can be several problems which prevent the use of the standard Poisson regression. We may detect individual unobserved heterogeneity, caused by missing covariates, and/or excess of zero observations in our data. Both …
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Stochastic methods for large-scale linear problems, variational inequalities, and convex optimization
This thesis considers stochastic methods for large-scale linear systems, variational inequalities, and convex optimization problems. I focus on special structures that lend themselves to sampling, such as when the linear/nonlinear mapping or the objective function is an expected value or is the sum …
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Effects of environmental shear and buoyancy on simulated supercell interactions
… and were often stronger than simulations with large cell separation distance. Further questions remain with trajectories and machine learning algorithms are tthe next steps for a more detailed analysis of this large data set.
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A comparison of the least squares collocation and the fast Fourier transform methods for gravimetric geoid determination
… due to an increase of both quality and type of data available for geoid determination. The FFT method is most reliable than the LSC method, since it requires less computational time on large data set than the LSC. A system of linear equations of order equal to the number of data points is …
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Managing configuration options for build-to-order highly customized products with application to specialty vehicles
… the need for efficient production processes. A large data set containing more than 27,000 records was obtained from a software product configuration tool in use by a specialty vehicle company. This data was evaluated utilizing several methods including statistical and network analysis. It was …
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Variability of soil erodibility: its relationship to topography and soil properties in cultivated landscape
… slope position than when considered as a single, large data set. This study suggested that the use of a catena approach to examine soil erodibility is an important consideration when studying soil erosion processes in agricultural landscapes.
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Learning-Augmented Algorithms
… methods used to understand the structure of large datasets and 𝑘-means is the most popular clustering formulation by far. In addition, counting triangles in a graph is a basic tool of network analytics and community detection in social networks. Lastly, the problem of estimating the number of …
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EVALUATION OF PHASE ANGLE AS A PRACTICAL PARAMETER FOR LOW TEMPERATURE SPECIFICATION GRADING OF ASPHALT BINDERS
… out on the samples. In addition to this, the data obtained from each test were correlated with limiting phase angle temperature [T(30°), T(45°)]. From the study, Agency B largely met the climatic and traffic requirements when compared with Agency A, due to a much more effective approach …
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Association Between Cognition and Depression: A Cross-Sectional and Longitudinal Study of Individuals with Learning Disabilities.
… vegetative, and cognitive functioning). The data for SEM came from a large data set of children with learning disabilities (n=227). Model fit results supported the proposed model, and a significant association was found between the attention/working memory factor and the depression symptom …
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Wind stress over the open ocean
… RRS Discovery in the Southern Ocean to obtain a large data set of open-ocean wind stress estimates. The wind speed varied from near-calm to 26 m/s, and the sea-air temperature differences ranged from -8 to +4°C. It is shown that, under unstable atmospheric conditions, the assumption of a balance …
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