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Physical Sciences and Mathematics Commons

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Full-Text Articles in Physical Sciences and Mathematics

A Data-Driven Approach For Processing Heterogeneous Categorical Sensor Signals, Randy Paffenroth, Christopher Calderon, Austin Jones, Scott Lundberg Sep 2011

A Data-Driven Approach For Processing Heterogeneous Categorical Sensor Signals, Randy Paffenroth, Christopher Calderon, Austin Jones, Scott Lundberg

Randy C. Paffenroth

False alarms generated by sensors pose a substantial problem to a variety of fusion applications. We focus on situations where the frequency of a genuine alarm is "rare" but the false alarm rate is high. The goal is to mitigate the false alarms while retaining power to detect true events. We propose to utilize data streams contaminated by false alarms (generated in the field) to compute statistics on a single sensor's misclassification rate. The nominal misclassification rate of a deployed sensor is often suspect because it is unlikely that these rates were tuned to the specific environmental conditions in which …


Part I: Policy Dimensions Of Offshore Wind Energy Development, Erik Nordman Ph.D., Betty Gajewski, Paul Isely Ph.D., John Koches, Kurt Thompson, Jon Vandermolen, Yue Fan, Sara Damm, Aaron Ferguson, Ryan Gajewski, Claire Schoolmaster Apr 2011

Part I: Policy Dimensions Of Offshore Wind Energy Development, Erik Nordman Ph.D., Betty Gajewski, Paul Isely Ph.D., John Koches, Kurt Thompson, Jon Vandermolen, Yue Fan, Sara Damm, Aaron Ferguson, Ryan Gajewski, Claire Schoolmaster

Erik Edward Nordman

The deployment of thousands of wind energy facilities required to meet various renewable energy targets will bring changes to the nation’s landscapes, communities, and economies.

The intent of this integrated assessment project is to comprehensively analyze the benefits and challenges to wind energy development in one particular region of coastal West Michigan, including Oceana, Muskegon, Ottawa and Allegan counties.

By combining science and public participation, our integrated assessment will empower citizens and local governments to make informed decisions about wind energy facilities in their communities. Our project will enhance local capacity to mitigate conflicts surrounding wind energy development, and will …


An Investigation Of Thermal Shock In Porous Clay Ceramics, Nima Rahbar, F. Nyongesa, S. Obwoya, J. Zimba, B. Aduda, W. Soboyejo Mar 2011

An Investigation Of Thermal Shock In Porous Clay Ceramics, Nima Rahbar, F. Nyongesa, S. Obwoya, J. Zimba, B. Aduda, W. Soboyejo

Nima Rahbar

The thermal shock resistance of porous ceramic materials is often characterized by the Hasselman parameters. However, in other scenarios, the room-temperature residual strengths after thermal shock are also used to quantify the damage due to thermal shock. This paper attempts to link the measured residual strengths to the dominant crack features that are introduced due to thermal shock in porous clay ceramics produced by the sintering of clay powders with well-controlled size ranges. Residual strength estimates from bend tests are compared with fracture mechanics predictions. The implications of the residual strength results are then discussed for the characterization of damage …


Identification And Thermochemical Analysis Of High-Lignin Feedstocks For Biofuel And Biochemical Production, V. Mendu, A. Harman-Ware, M. Crocker, J. Jae, J. Stork, Samuel Morton, A. Placido, G. Huber, S. Debolt Dec 2010

Identification And Thermochemical Analysis Of High-Lignin Feedstocks For Biofuel And Biochemical Production, V. Mendu, A. Harman-Ware, M. Crocker, J. Jae, J. Stork, Samuel Morton, A. Placido, G. Huber, S. Debolt

Samuel A Morton

No abstract provided.


Windows Executable For Gaussian Copula With Nbd Margins, Michael S. Smith Dec 2010

Windows Executable For Gaussian Copula With Nbd Margins, Michael S. Smith

Michael Stanley Smith

This is an example Windows 32bit program to estimate a Gaussian copula model with NBD margins. The margins are estimated first using MLE, and the copula second using Bayesian MCMC. The model was discussed in Danaher & Smith (2011; Marketing Science) as example 4 (section 4.2).