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 8426 for “"Large-scale"”.
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Large Scale Disease Modeling
<p>In this we study large scale disease modeling. After understanding the mechanics behind the SIR disease model in an ODE sense, we will apply this knowledge to model disease spread in more and more increasing advanced cellular automata. Eventually, some of our cellular automata will include long …
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Large scale phylogenomic estimation
… and supertree estimation, and is designed to scale to very large datasets while maintaining a high level of accuracy. FastRFS is a supertree method that uses an exact constrained optimization algorithm to find accurate supertrees. SVDquest is a coalescent-aware species tree estimation method …
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Large scale disease prediction
… is to present the foundation of an automated large-scale disease prediction system. Unlike previous work that has typically focused on a small self-contained dataset, we explore the possibility of combining a large amount of heterogeneous data to perform gene selection and phenotype …
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Large-scale biological transportation networks
Großskalige Tierbewegungen und Transportsysteme besitzen oft eine inheränte Netzwerkstruktur und können leicht als Bewegungsereignisse zwischen diskreten Regionen modelliert werden. Das Ziel dieser Arbeit besteht in der Entwicklung und Beschreibung von Transportnetzwerken, die zum Einen den …
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Large Scale Aggregated Sentiment Analytics
… possible capturing sentiments and opinions at a large scale and with the ever-growing precision. Sentiment Analytics came a long way from product review mining to full-fledged multi-dimensional analysis of social sentiment, exposing people attitude towards any topic aggregated along different …
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Dynamics in large scale networks
In this thesis we study the properties of two large dynamic networks, the competition network of advertisers on the Google and Bing search engines and the dynamic network of friend relationships among avatars in the massively multiplayer online game (MMOG) Planetside 2. We are particularly …
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Problems in large-scale estimation
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-09-01 without embargo terms
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Large scale quantum mechanical enzymology
… results for a range of small molecule and large biomolecular systems. Previous authors have shown that DFT calculations yield an unphysical, negligible energy gap between the highest occupied and lowest unoccupied molecular orbitals for proteins and large water clusters, a characteristic …
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Large-scale probabilistic aerial reconstruction
While much emphasis has been placed on large-scale 3D scene reconstruction from a single data source such as images or distance sensors, models that jointly utilize multiple data types remain largely unexplored. In this work, we will present a Bayesian formulation of scene reconstruction from …
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Algorithms for large-scale personalization
… key challenges and new applications for modern, large-scale personalization. In particular, this thesis is outlined as follows: First, we formulate a generic, flexible framework for learning from matrix-valued data, including the kinds of data commonly collected in e-commerce. Underlying this …
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Large scale video action understanding
The goal of the project is to build a large scale video dataset called Moments, and train existing/novel models for action recognition. To aid automation of video collection and annotation selection, I trained Convolutional Neural Network models to estimate the likelihood of a desired action …
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Evolutionary Algorithm For Large-Scale Optimization
… an evolutionary framework capable of handling large and complex optimization problems. In this thesis, an algorithmic framework for solving Large-scale Global Optimization (LSGO) problems, which contains decomposition and optimization approaches, is proposed. Firstly, a set of problems that can …
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Large scale optimization for machine learning
… to robotics. In entering the era of big data, large scale machine learning tools become increasingly important in training a big model on big data. Since machine learning problems are fundamentally empirical risk minimization problems, large scale optimization plays a key role in building a …
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Large-scale forcing of coastal communities
… increased density, faster growth and larger maximum sizes.<br/>The study was divided into five sections examining community structure, growth rates, predation and grazing pressures, effects of wave exposure, and stable isotope analysis. Individual species tended to vary between sites …
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Resource Management in Large-scale Systems
… focus of this thesis is resource management in large-scale systems. Our primary concerns are energy management and practical principles for self-organization and self-management. The main contributions of our work are: 1. Models. We proposed several models for different aspects of resource …
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Distributed Computing for Large-scale Graphs
… last decade has seen an increased attention on large-scale data analysis, caused mainly by the availability of new sources of data and the development of programming model that allowed their analysis. Since many of these sources can be modeled as graphs, many large-scale graph processing …
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Storage management for large scale systems
… management is crucial to the performance of many large scale computer systems. This thesis studies performance issues in buffer cache management and disk layout management, two important components of storage management. The buffer cache stores popular disk pages in memory to speed up the access …
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Solving Large Scale Crew Pairing Problems
… Finding quickly a good and robust solution for large scale problems is more and more critical to airlines. They are the main targets which are studied by the thesis. The thesis presents exact methods which are usually based on a branch-and-bound scheme. A branch-and-cut approach applies …
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Large Scale Simulation of Spinodal Decomposition
… that the parallel domain decomposition method scales well to a thousand processor cores. For short time, the Wiener chaos Karhunen-Loeve expansion (WCKLE) method is more efficient than the Monte Carlo simulation. We simulate the whole spinodal decomposition process by the Wiener chaos …
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Large-Scale Pattern Discovery in Music
… on extracting patterns in musical data from very large collections. The problem is split in two parts. First, we build such a large collection, the Million Song Dataset, to provide researchers access to commercial-size datasets. Second, we use this collection to study cover song recognition which …
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