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You searched for +publisher:"Clemson University" +contributor:("Goasguen, Sebastian"). Showing records 1 – 2 of 2 total matches.

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Clemson University

1. Chahal, Dheeraj. Automated, Parallel Optimization Algorithms for Stochastic Functions.

Degree: PhD, Computer Science, 2011, Clemson University

The optimization algorithms for stochastic functions are desired specifically for real-world and simulation applications where results are obtained from sampling, and contain experimental error or random noise. We have developed a series of stochastic optimization algorithms based on the well-known classical down hill simplex algorithm. Our parallel implementation of these optimization algorithms, using a framework called MW, is based on a master-worker architecture where each worker runs a massively parallel program. This parallel implementation allows the sampling to proceed independently on many processors as demonstrated by scaling up to more than 100 vertices and 300 cores. This framework is highly suitable for clusters with an ever increasing number of cores per node. The new algorithms have been successfully applied to the reparameterization of a model for liquid water, achieving thermodynamic and structural results for liquid water that are better than a standard model used in molecular simulations, with the the advantage of a fully automated parameterization process. Advisors/Committee Members: Goasguen, Sebastian, Stuart , Steve, Stevenson , D E, Srimani , Pradip.

Subjects/Keywords: Algorithm; Automated; Optimization; Parallel; Simplex; Stochastic; Computer Sciences

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Chahal, D. (2011). Automated, Parallel Optimization Algorithms for Stochastic Functions. (Doctoral Dissertation). Clemson University. Retrieved from https://tigerprints.clemson.edu/all_dissertations/706

Chicago Manual of Style (16th Edition):

Chahal, Dheeraj. “Automated, Parallel Optimization Algorithms for Stochastic Functions.” 2011. Doctoral Dissertation, Clemson University. Accessed December 14, 2019. https://tigerprints.clemson.edu/all_dissertations/706.

MLA Handbook (7th Edition):

Chahal, Dheeraj. “Automated, Parallel Optimization Algorithms for Stochastic Functions.” 2011. Web. 14 Dec 2019.

Vancouver:

Chahal D. Automated, Parallel Optimization Algorithms for Stochastic Functions. [Internet] [Doctoral dissertation]. Clemson University; 2011. [cited 2019 Dec 14]. Available from: https://tigerprints.clemson.edu/all_dissertations/706.

Council of Science Editors:

Chahal D. Automated, Parallel Optimization Algorithms for Stochastic Functions. [Doctoral Dissertation]. Clemson University; 2011. Available from: https://tigerprints.clemson.edu/all_dissertations/706


Clemson University

2. Esswein, Samuel. Environmental Observing Systems for Assessing Impacts of Land Use Change.

Degree: MS, Forest Resources, 2008, Clemson University

The purpose of this research is to evaluate the application of technology solutions for enabling environmental research. This project develops a complete environmental observing system in support of an investigation of the hydrological and ecological impacts of land use change on the coast of South Carolina. The land use change study is an ongoing multi-disciplinary effort involving the collection of a large number of monitored and sampled parameters at Bannockburn Plantation, which is located near the City of Georgetown in South Carolina. Long term monitoring will support a hydrological and ecological assessment of the study site before, during, and after proposed residential and commercial development. There are three primary objectives of this work. The first is the comprehensive instrumentation of a portion of the Bannockburn study site for hydrological parameters. The second is the implementation of a wireless sensor network to support the remote acquisition of monitored data. The third objective is the creation of a reliable and robust software solution for transmitting and distributing real time observation data. Collectively, these three objectives provide a complete environmental observing system. Results of this work will benefit land use change research by providing access to real time observation data and enabling the integration of powerful analysis tools. This research will provide a basis for the development of future environmental observation systems. Advisors/Committee Members: Post, Christopher J, Goasguen , Sebastian, Mikhailova , Elena, Hitchcock , Dan R.

Subjects/Keywords: Agriculture

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Esswein, S. (2008). Environmental Observing Systems for Assessing Impacts of Land Use Change. (Masters Thesis). Clemson University. Retrieved from https://tigerprints.clemson.edu/all_theses/357

Chicago Manual of Style (16th Edition):

Esswein, Samuel. “Environmental Observing Systems for Assessing Impacts of Land Use Change.” 2008. Masters Thesis, Clemson University. Accessed December 14, 2019. https://tigerprints.clemson.edu/all_theses/357.

MLA Handbook (7th Edition):

Esswein, Samuel. “Environmental Observing Systems for Assessing Impacts of Land Use Change.” 2008. Web. 14 Dec 2019.

Vancouver:

Esswein S. Environmental Observing Systems for Assessing Impacts of Land Use Change. [Internet] [Masters thesis]. Clemson University; 2008. [cited 2019 Dec 14]. Available from: https://tigerprints.clemson.edu/all_theses/357.

Council of Science Editors:

Esswein S. Environmental Observing Systems for Assessing Impacts of Land Use Change. [Masters Thesis]. Clemson University; 2008. Available from: https://tigerprints.clemson.edu/all_theses/357

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