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Operations Research, Systems Engineering and Industrial Engineering Commons™
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Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Multi-Modular Integral Pressurized Water Reactor Control And Operational Reconfiguration For A Flow Control Loop, Sergio Ricardo Pereira Perillo
Multi-Modular Integral Pressurized Water Reactor Control And Operational Reconfiguration For A Flow Control Loop, Sergio Ricardo Pereira Perillo
Doctoral Dissertations
This dissertation focused on the IRIS design since this will likely be one of the designs of choice for future deployment in the U.S and developing countries. With a net 335 MWe output IRIS novel design falls in the “medium” size category and it is a potential candidate for the so called modular reactors, which may be appropriate for base load electricity generation, especially in regions with smaller electricity grids, but especially well suited for more specialized non-electrical energy applications such as district heating and process steam for desalination. The first objective of this dissertation is to evaluate and quantify …
A New Lean Model: Improving Race Team Performance Through Team-Driver Communication Efficacy, Joseph Ruric Stainback Iv
A New Lean Model: Improving Race Team Performance Through Team-Driver Communication Efficacy, Joseph Ruric Stainback Iv
Doctoral Dissertations
In some organizational settings and in the field of competitive automobile racing, certain situations and rules place an emphasis on and sometimes escalate the need for effective team communications. This dissertation hypothesizes that effective and dense communications contributes directly to team performance. Supported by organizational behavioral and lean six sigma theory, communications is declared a form of waste within the context of Industrial Engineering subject to data collection, measurements, and real-time, value-added metrics. Measuring and reporting trends in communications provides a basis for a new and unique model called a Communications Productivity Model (CPM) with an associated Communications Density Report …
Kernel-Based Data Mining Approach With Variable Selection For Nonlinear High-Dimensional Data, Seung Hyun Baek
Kernel-Based Data Mining Approach With Variable Selection For Nonlinear High-Dimensional Data, Seung Hyun Baek
Doctoral Dissertations
In statistical data mining research, datasets often have nonlinearity and high-dimensionality. It has become difficult to analyze such datasets in a comprehensive manner using traditional statistical methodologies. Kernel-based data mining is one of the most effective statistical methodologies to investigate a variety of problems in areas including pattern recognition, machine learning, bioinformatics, chemometrics, and statistics. In particular, statistically-sophisticated procedures that emphasize the reliability of results and computational efficiency are required for the analysis of high-dimensional data. In this dissertation, first, a novel wrapper method called SVM-ICOMP-RFE based on hybridized support vector machine (SVM) and recursive feature elimination (RFE) with information-theoretic …