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You searched for +publisher:"University of Florida" +contributor:("LAN,GUANGHUI"). Showing records 1 – 13 of 13 total matches.

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University of Florida

1. Zhou, Zhiqiang. Optimal Stochastic Subgradient Methods for Expected-Value Constrained Stochastic Programming.

Degree: MS, Industrial and Systems Engineering, 2014, University of Florida

 The main goal of this paper is to develop a new stochastic subgradient method for constrained stochastic convex optimization problems. The problem we are interested… (more)

Subjects/Keywords: Approximation; Entropy; Estimated cost to complete; Keywords; optimization  – rubust  – stochastic

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

APA (6th Edition):

Zhou, Z. (2014). Optimal Stochastic Subgradient Methods for Expected-Value Constrained Stochastic Programming. (Masters Thesis). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0047301

Chicago Manual of Style (16th Edition):

Zhou, Zhiqiang. “Optimal Stochastic Subgradient Methods for Expected-Value Constrained Stochastic Programming.” 2014. Masters Thesis, University of Florida. Accessed April 05, 2020. http://ufdc.ufl.edu/UFE0047301.

MLA Handbook (7th Edition):

Zhou, Zhiqiang. “Optimal Stochastic Subgradient Methods for Expected-Value Constrained Stochastic Programming.” 2014. Web. 05 Apr 2020.

Vancouver:

Zhou Z. Optimal Stochastic Subgradient Methods for Expected-Value Constrained Stochastic Programming. [Internet] [Masters thesis]. University of Florida; 2014. [cited 2020 Apr 05]. Available from: http://ufdc.ufl.edu/UFE0047301.

Council of Science Editors:

Zhou Z. Optimal Stochastic Subgradient Methods for Expected-Value Constrained Stochastic Programming. [Masters Thesis]. University of Florida; 2014. Available from: http://ufdc.ufl.edu/UFE0047301


University of Florida

2. Su, Suiyi. Sample Path Based Optimal Position Liquidation with CVaR Risk.

Degree: MS, Industrial and Systems Engineering, 2012, University of Florida

 The purpose of this research is to investigate devising theoptimal position liquidation strategies in financial markets. During the transaction of large block orders, investors need… (more)

Subjects/Keywords: Anticipation; Assets; Datasets; Market prices; Mathematical monotonicity; Mathematics; Matrices; Objective functions; Prices; Real prices; convex  – execution  – guard  – nonanticipativity  – optimal  – portfolio  – programming  – safe  – stochastic  – trading

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APA (6th Edition):

Su, S. (2012). Sample Path Based Optimal Position Liquidation with CVaR Risk. (Masters Thesis). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0044708

Chicago Manual of Style (16th Edition):

Su, Suiyi. “Sample Path Based Optimal Position Liquidation with CVaR Risk.” 2012. Masters Thesis, University of Florida. Accessed April 05, 2020. http://ufdc.ufl.edu/UFE0044708.

MLA Handbook (7th Edition):

Su, Suiyi. “Sample Path Based Optimal Position Liquidation with CVaR Risk.” 2012. Web. 05 Apr 2020.

Vancouver:

Su S. Sample Path Based Optimal Position Liquidation with CVaR Risk. [Internet] [Masters thesis]. University of Florida; 2012. [cited 2020 Apr 05]. Available from: http://ufdc.ufl.edu/UFE0044708.

Council of Science Editors:

Su S. Sample Path Based Optimal Position Liquidation with CVaR Risk. [Masters Thesis]. University of Florida; 2012. Available from: http://ufdc.ufl.edu/UFE0044708


University of Florida

3. Ghadimi, Saeed. Finite-Time Convergence Properties of Methods for Stochastic Programming.

Degree: PhD, Industrial and Systems Engineering, 2014, University of Florida

 In this dissertation, we mainly focus on establishing finite-time convergence of the iterative algorithms for solving both convex and nonconvex stochastic programming (SP) problems. In… (more)

Subjects/Keywords: Algorithms; Approximation; Convexity; Data smoothing; Gradient method; Iterative solutions; Objective functions; Optimal solutions; Oracles; Probability mass distributions; algorithm  – approximation  – complexity  – convex  – nonconvex  – optimazation  – programming  – randomized  – stochastic

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APA (6th Edition):

Ghadimi, S. (2014). Finite-Time Convergence Properties of Methods for Stochastic Programming. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0047032

Chicago Manual of Style (16th Edition):

Ghadimi, Saeed. “Finite-Time Convergence Properties of Methods for Stochastic Programming.” 2014. Doctoral Dissertation, University of Florida. Accessed April 05, 2020. http://ufdc.ufl.edu/UFE0047032.

MLA Handbook (7th Edition):

Ghadimi, Saeed. “Finite-Time Convergence Properties of Methods for Stochastic Programming.” 2014. Web. 05 Apr 2020.

Vancouver:

Ghadimi S. Finite-Time Convergence Properties of Methods for Stochastic Programming. [Internet] [Doctoral dissertation]. University of Florida; 2014. [cited 2020 Apr 05]. Available from: http://ufdc.ufl.edu/UFE0047032.

Council of Science Editors:

Ghadimi S. Finite-Time Convergence Properties of Methods for Stochastic Programming. [Doctoral Dissertation]. University of Florida; 2014. Available from: http://ufdc.ufl.edu/UFE0047032


University of Florida

4. Sethi, Manu. Incorporating Feature Matching and Supervoxels into Multiframe Optical Flow.

Degree: PhD, Computer Engineering - Computer and Information Science and Engineering, 2015, University of Florida

 The focus in this dissertation is to estimate the motion of pixels in images. Specifically, we make contributions in the areas of image registration and… (more)

Subjects/Keywords: Computer vision; Data smoothing; Fourier transformations; Hogs; Images; Images of transformations; Line segments; Moving images; Objective functions; Pixels; flow  – majorization  – multiframe  – optical  – registration  – supervoxels

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APA (6th Edition):

Sethi, M. (2015). Incorporating Feature Matching and Supervoxels into Multiframe Optical Flow. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0049274

Chicago Manual of Style (16th Edition):

Sethi, Manu. “Incorporating Feature Matching and Supervoxels into Multiframe Optical Flow.” 2015. Doctoral Dissertation, University of Florida. Accessed April 05, 2020. http://ufdc.ufl.edu/UFE0049274.

MLA Handbook (7th Edition):

Sethi, Manu. “Incorporating Feature Matching and Supervoxels into Multiframe Optical Flow.” 2015. Web. 05 Apr 2020.

Vancouver:

Sethi M. Incorporating Feature Matching and Supervoxels into Multiframe Optical Flow. [Internet] [Doctoral dissertation]. University of Florida; 2015. [cited 2020 Apr 05]. Available from: http://ufdc.ufl.edu/UFE0049274.

Council of Science Editors:

Sethi M. Incorporating Feature Matching and Supervoxels into Multiframe Optical Flow. [Doctoral Dissertation]. University of Florida; 2015. Available from: http://ufdc.ufl.edu/UFE0049274


University of Florida

5. Nguyen, Trang Thi Le. Convexification Techniques for Complementarity and Multilinear Constraints.

Degree: PhD, Industrial and Systems Engineering, 2013, University of Florida

 In this Dissertation, we develop tighter convex relaxations for polyhedral sets with complementarity constraints and multilinear constraints using tools inspired from integer programming. Firstly, we… (more)

Subjects/Keywords: Algorithms; Integers; Linear inequalities; Linear programming; Mathematical inequalities; Optimal solutions; Polyhedrons; Polynomials; Relaxation techniques; Tableaux; complementarity  – convexification  – multilinear

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APA (6th Edition):

Nguyen, T. T. L. (2013). Convexification Techniques for Complementarity and Multilinear Constraints. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0045295

Chicago Manual of Style (16th Edition):

Nguyen, Trang Thi Le. “Convexification Techniques for Complementarity and Multilinear Constraints.” 2013. Doctoral Dissertation, University of Florida. Accessed April 05, 2020. http://ufdc.ufl.edu/UFE0045295.

MLA Handbook (7th Edition):

Nguyen, Trang Thi Le. “Convexification Techniques for Complementarity and Multilinear Constraints.” 2013. Web. 05 Apr 2020.

Vancouver:

Nguyen TTL. Convexification Techniques for Complementarity and Multilinear Constraints. [Internet] [Doctoral dissertation]. University of Florida; 2013. [cited 2020 Apr 05]. Available from: http://ufdc.ufl.edu/UFE0045295.

Council of Science Editors:

Nguyen TTL. Convexification Techniques for Complementarity and Multilinear Constraints. [Doctoral Dissertation]. University of Florida; 2013. Available from: http://ufdc.ufl.edu/UFE0045295


University of Florida

6. Deng, Qi. New Nonsmooth Convex Optimization Methods for Machine Learning.

Degree: PhD, Computer Engineering - Computer and Information Science and Engineering, 2015, University of Florida

 Machine learning studies how to build models and develop algorithms that can learn from the data. Central to the machine learning area is the design… (more)

Subjects/Keywords: Algorithms; Approximation; Averaging methods; Coordinate systems; Data smoothing; Datasets; Linear regression; Machine learning; Saddle points; Search engine optimization; learning  – machine  – optimization

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APA (6th Edition):

Deng, Q. (2015). New Nonsmooth Convex Optimization Methods for Machine Learning. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0049608

Chicago Manual of Style (16th Edition):

Deng, Qi. “New Nonsmooth Convex Optimization Methods for Machine Learning.” 2015. Doctoral Dissertation, University of Florida. Accessed April 05, 2020. http://ufdc.ufl.edu/UFE0049608.

MLA Handbook (7th Edition):

Deng, Qi. “New Nonsmooth Convex Optimization Methods for Machine Learning.” 2015. Web. 05 Apr 2020.

Vancouver:

Deng Q. New Nonsmooth Convex Optimization Methods for Machine Learning. [Internet] [Doctoral dissertation]. University of Florida; 2015. [cited 2020 Apr 05]. Available from: http://ufdc.ufl.edu/UFE0049608.

Council of Science Editors:

Deng Q. New Nonsmooth Convex Optimization Methods for Machine Learning. [Doctoral Dissertation]. University of Florida; 2015. Available from: http://ufdc.ufl.edu/UFE0049608


University of Florida

7. Wang, Qianfan. Two-Stage Chance and Expected Value Constrained Stochastic Unit Commitment Formulations, Algorithms and Case Studies.

Degree: PhD, Industrial and Systems Engineering, 2013, University of Florida

 Stochastic programming is a common approach to solving decision-making problems under uncertainty in power systems optimization. In this dissertation, we first present a unit commitment… (more)

Subjects/Keywords: Algorithms; Approximation; Electricity; Expected values; Objective functions; Randomness; Sample size; Transmission lines; Unit costs; Wind power; algorithms  – optimization  – stochastic

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APA (6th Edition):

Wang, Q. (2013). Two-Stage Chance and Expected Value Constrained Stochastic Unit Commitment Formulations, Algorithms and Case Studies. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0045153

Chicago Manual of Style (16th Edition):

Wang, Qianfan. “Two-Stage Chance and Expected Value Constrained Stochastic Unit Commitment Formulations, Algorithms and Case Studies.” 2013. Doctoral Dissertation, University of Florida. Accessed April 05, 2020. http://ufdc.ufl.edu/UFE0045153.

MLA Handbook (7th Edition):

Wang, Qianfan. “Two-Stage Chance and Expected Value Constrained Stochastic Unit Commitment Formulations, Algorithms and Case Studies.” 2013. Web. 05 Apr 2020.

Vancouver:

Wang Q. Two-Stage Chance and Expected Value Constrained Stochastic Unit Commitment Formulations, Algorithms and Case Studies. [Internet] [Doctoral dissertation]. University of Florida; 2013. [cited 2020 Apr 05]. Available from: http://ufdc.ufl.edu/UFE0045153.

Council of Science Editors:

Wang Q. Two-Stage Chance and Expected Value Constrained Stochastic Unit Commitment Formulations, Algorithms and Case Studies. [Doctoral Dissertation]. University of Florida; 2013. Available from: http://ufdc.ufl.edu/UFE0045153


University of Florida

8. Li, Junjie. GPU Algorithms for Bioinformatics.

Degree: PhD, Computer Engineering - Computer and Information Science and Engineering, 2014, University of Florida

 Graphics Processing Units (GPUs) were developed originally to meet the computational needs of algorithms for rendering computer graphics. Their low cost per gigaflop has motivated… (more)

Subjects/Keywords: Algorithms; Bioinformatics; Bytes; Computer memory; Input output; Matrices; Multiprocessors; RNA; Run time; Sequence alignment; algorithms  – bioinformatics  – gpu

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APA (6th Edition):

Li, J. (2014). GPU Algorithms for Bioinformatics. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0046103

Chicago Manual of Style (16th Edition):

Li, Junjie. “GPU Algorithms for Bioinformatics.” 2014. Doctoral Dissertation, University of Florida. Accessed April 05, 2020. http://ufdc.ufl.edu/UFE0046103.

MLA Handbook (7th Edition):

Li, Junjie. “GPU Algorithms for Bioinformatics.” 2014. Web. 05 Apr 2020.

Vancouver:

Li J. GPU Algorithms for Bioinformatics. [Internet] [Doctoral dissertation]. University of Florida; 2014. [cited 2020 Apr 05]. Available from: http://ufdc.ufl.edu/UFE0046103.

Council of Science Editors:

Li J. GPU Algorithms for Bioinformatics. [Doctoral Dissertation]. University of Florida; 2014. Available from: http://ufdc.ufl.edu/UFE0046103


University of Florida

9. Fan,Neng. Combinatorial and Nonlinear Optimization Methods with Applications in Data Clustering, Biclustering and Power Systems.

Degree: PhD, Industrial and Systems Engineering, 2011, University of Florida

 With the increasing number of databases appearing in computational biology, biomedical engineering, consumers' behavior survey, social networks, power systems, and many other areas, finding the… (more)

Subjects/Keywords: Algorithms; Bioinformatics; Cardinality; Integers; Linear programming; Matrices; Objective functions; Power grids; Spectral methods; Vertices; biclustering  – clustering  – combinatorial  – graph  – integer  – islanding  – nonlinear

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APA (6th Edition):

Fan,Neng. (2011). Combinatorial and Nonlinear Optimization Methods with Applications in Data Clustering, Biclustering and Power Systems. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0043200

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

Fan,Neng. “Combinatorial and Nonlinear Optimization Methods with Applications in Data Clustering, Biclustering and Power Systems.” 2011. Doctoral Dissertation, University of Florida. Accessed April 05, 2020. http://ufdc.ufl.edu/UFE0043200.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

Fan,Neng. “Combinatorial and Nonlinear Optimization Methods with Applications in Data Clustering, Biclustering and Power Systems.” 2011. Web. 05 Apr 2020.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

Fan,Neng. Combinatorial and Nonlinear Optimization Methods with Applications in Data Clustering, Biclustering and Power Systems. [Internet] [Doctoral dissertation]. University of Florida; 2011. [cited 2020 Apr 05]. Available from: http://ufdc.ufl.edu/UFE0043200.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

Fan,Neng. Combinatorial and Nonlinear Optimization Methods with Applications in Data Clustering, Biclustering and Power Systems. [Doctoral Dissertation]. University of Florida; 2011. Available from: http://ufdc.ufl.edu/UFE0043200

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete


University of Florida

10. Xu, Hongsheng. Electricity Blackout and Power Security Survey and Analysis.

Degree: PhD, Industrial and Systems Engineering, 2012, University of Florida

 Electricity power systems are critical to any country’s economy and security. Blackout, the most severe form of power loss to a relatively wide area, posting… (more)

Subjects/Keywords: Algorithms; Blackouts; Buses; Economic models; Electric power; Linear programming; Modeling; Power grids; Power lines; Transmission lines; contingency  – grid  – power  – security

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APA (6th Edition):

Xu, H. (2012). Electricity Blackout and Power Security Survey and Analysis. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0044419

Chicago Manual of Style (16th Edition):

Xu, Hongsheng. “Electricity Blackout and Power Security Survey and Analysis.” 2012. Doctoral Dissertation, University of Florida. Accessed April 05, 2020. http://ufdc.ufl.edu/UFE0044419.

MLA Handbook (7th Edition):

Xu, Hongsheng. “Electricity Blackout and Power Security Survey and Analysis.” 2012. Web. 05 Apr 2020.

Vancouver:

Xu H. Electricity Blackout and Power Security Survey and Analysis. [Internet] [Doctoral dissertation]. University of Florida; 2012. [cited 2020 Apr 05]. Available from: http://ufdc.ufl.edu/UFE0044419.

Council of Science Editors:

Xu H. Electricity Blackout and Power Security Survey and Analysis. [Doctoral Dissertation]. University of Florida; 2012. Available from: http://ufdc.ufl.edu/UFE0044419


University of Florida

11. Dang, Cong Dinh. Randomized First Order Methods for Convex and Nonconvex Optimization.

Degree: PhD, Industrial and Systems Engineering, 2015, University of Florida

In this dissertation, we propose some first order methods for solving various problems of convex Advisors/Committee Members: LAN,GUANGHUI (committee chair), LAWPHONGPANICH,SIRIPHONG (committee member), XIA,YE (committee member).

Subjects/Keywords: Algorithms; Approximation; Convexity; Coordinate systems; Datasets; Machine learning; Mathematical programming; Random variables; Saddle points; Systems engineering; first  – methods  – order  – randomized

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APA (6th Edition):

Dang, C. D. (2015). Randomized First Order Methods for Convex and Nonconvex Optimization. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0046978

Chicago Manual of Style (16th Edition):

Dang, Cong Dinh. “Randomized First Order Methods for Convex and Nonconvex Optimization.” 2015. Doctoral Dissertation, University of Florida. Accessed April 05, 2020. http://ufdc.ufl.edu/UFE0046978.

MLA Handbook (7th Edition):

Dang, Cong Dinh. “Randomized First Order Methods for Convex and Nonconvex Optimization.” 2015. Web. 05 Apr 2020.

Vancouver:

Dang CD. Randomized First Order Methods for Convex and Nonconvex Optimization. [Internet] [Doctoral dissertation]. University of Florida; 2015. [cited 2020 Apr 05]. Available from: http://ufdc.ufl.edu/UFE0046978.

Council of Science Editors:

Dang CD. Randomized First Order Methods for Convex and Nonconvex Optimization. [Doctoral Dissertation]. University of Florida; 2015. Available from: http://ufdc.ufl.edu/UFE0046978


University of Florida

12. Wang, Ximing. Machine Learning Optimization Models with Data Uncertainties.

Degree: PhD, Industrial and Systems Engineering, 2015, University of Florida

Subjects/Keywords: machine-learning; optimization; uncertainties

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

APA (6th Edition):

Wang, X. (2015). Machine Learning Optimization Models with Data Uncertainties. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0049100

Chicago Manual of Style (16th Edition):

Wang, Ximing. “Machine Learning Optimization Models with Data Uncertainties.” 2015. Doctoral Dissertation, University of Florida. Accessed April 05, 2020. http://ufdc.ufl.edu/UFE0049100.

MLA Handbook (7th Edition):

Wang, Ximing. “Machine Learning Optimization Models with Data Uncertainties.” 2015. Web. 05 Apr 2020.

Vancouver:

Wang X. Machine Learning Optimization Models with Data Uncertainties. [Internet] [Doctoral dissertation]. University of Florida; 2015. [cited 2020 Apr 05]. Available from: http://ufdc.ufl.edu/UFE0049100.

Council of Science Editors:

Wang X. Machine Learning Optimization Models with Data Uncertainties. [Doctoral Dissertation]. University of Florida; 2015. Available from: http://ufdc.ufl.edu/UFE0049100


University of Florida

13. Xanthopoulos,Petros. Robust Data Mining Techniques with Application in Biomedicine and Engineering.

Degree: PhD, Industrial and Systems Engineering, 2011, University of Florida

Analysis and interpretation of large datasets is a very significant problem that Advisors/Committee Members: Pardalos, Panagote M (committee chair), Geunes, Joseph P (committee member), Lan, Guanghui (committee member), Thai, My Tra (committee member).

Subjects/Keywords: Algorithms; Datasets; Eigenvalues; Hyperplanes; Least squares; Linear programming; Mathematical vectors; Matrices; Mining; Robust optimization; data  – robust  – supervised  – uncertainty

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APA (6th Edition):

Xanthopoulos,Petros. (2011). Robust Data Mining Techniques with Application in Biomedicine and Engineering. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0043173

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

Xanthopoulos,Petros. “Robust Data Mining Techniques with Application in Biomedicine and Engineering.” 2011. Doctoral Dissertation, University of Florida. Accessed April 05, 2020. http://ufdc.ufl.edu/UFE0043173.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

Xanthopoulos,Petros. “Robust Data Mining Techniques with Application in Biomedicine and Engineering.” 2011. Web. 05 Apr 2020.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

Xanthopoulos,Petros. Robust Data Mining Techniques with Application in Biomedicine and Engineering. [Internet] [Doctoral dissertation]. University of Florida; 2011. [cited 2020 Apr 05]. Available from: http://ufdc.ufl.edu/UFE0043173.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

Xanthopoulos,Petros. Robust Data Mining Techniques with Application in Biomedicine and Engineering. [Doctoral Dissertation]. University of Florida; 2011. Available from: http://ufdc.ufl.edu/UFE0043173

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

.