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Physical Sciences and Mathematics Commons

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Full-Text Articles in Physical Sciences and Mathematics

Renewable Energy Investment Planning And Policy Design, Alireza Ghalebani Apr 2016

Renewable Energy Investment Planning And Policy Design, Alireza Ghalebani

USF Tampa Graduate Theses and Dissertations

In this dissertation, we leverage predictive and prescriptive analytics to develop decision support systems to promote the use of renewable energy in society. Since electricity from renewable energy sources is still relatively expensive, there are variety of financial incentive programs available in different regions. Our research focuses on financial incentive programs and tackles two main problem: 1) how to optimally design and control hybrid renewable energy systems for residential and commercial buildings given the capacity based and performance based incentives, and 2) how to develop a model-based system for policy makers for designing optimal financial incentive programs to promote investment …


Hpc Enabled Data Analytics For High-Throughput High-Content Cellular Analysis, Ross A. Smith, Rhonda J. Vickery, Jack Harris, Sara Gharabaghi, Thomas Wischgoll, David Short, Robert Trevino, Steven A. Kawamoto, Thomas J. Lamkin, Kevin Schoen, Eric E. Bardes, Scott C. Tabar, Bruce J. Aronow Jan 2016

Hpc Enabled Data Analytics For High-Throughput High-Content Cellular Analysis, Ross A. Smith, Rhonda J. Vickery, Jack Harris, Sara Gharabaghi, Thomas Wischgoll, David Short, Robert Trevino, Steven A. Kawamoto, Thomas J. Lamkin, Kevin Schoen, Eric E. Bardes, Scott C. Tabar, Bruce J. Aronow

Computer Science and Engineering Faculty Publications

Biologists doing high-throughput high-content cellular analysis are generally not computer scientists or high performance computing (HPC) experts, and they want their workflow to support their science without having to be. We describe a new HPC enabled data analytics workflow with a web interface, HPC pipeline for analysis, and both traditional and new analytics tools to help them transition from a single workstation mode of operation to power HPC users. This allows the processing of multiple plates over a short period of time to ensure timely query and analysis to match potential countermeasures to individual responses.


A Fuzzy Rough Sets-Based Multi-Agent Analytics Framework For Dynamic Supply Chain Configuration, Nagesh Shukla, Senevi Kiridena Jan 2016

A Fuzzy Rough Sets-Based Multi-Agent Analytics Framework For Dynamic Supply Chain Configuration, Nagesh Shukla, Senevi Kiridena

SMART Infrastructure Facility - Papers

Considering the need for more effective decision support in the context of distributed manufacturing, this paper develops an advanced analytics framework for configuring supply chain networks. The proposed framework utilizes a distributed multi-agent system architecture to deploy fuzzy rough sets-based algorithms for knowledge elicitation and representation. A set of historical sales data, including network node-related information, is used together with the relevant details of product families to predict supply chain configurations capable of fulfilling desired customer orders. Multiple agents such as data retrieval agent, knowledge acquisition agent, knowledge representation agent, configuration predictor agent, evaluator agent and dispatching agent are used …


Celestial Sources For Random Number Generation, Erin Chapman, Jerina Grewar, Tim Natusch Jan 2016

Celestial Sources For Random Number Generation, Erin Chapman, Jerina Grewar, Tim Natusch

Australian Information Security Management Conference

In this paper, we present an alternative method of gathering seed data for random number generation (RNG) in cryptographic applications. Our proposed method utilises the inherent randomness of signal data from celestial sources in radio astronomy to provide seeds for RNG. The data sets were collected from two separate celestial sources, and run through the SHA-256 algorithm to deskew the data and produce random numbers with a uniform distribution. The resulting data sets pass all tests in the NIST Statistical Test Suite for random data, with a mean of 98.9% of the 512 total bitstreams from the two sources passing …