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Physical Sciences and Mathematics Commons™
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- ADAMS modeling (1)
- Color invariants (1)
- Cone signals (1)
- Gaussian process (1)
- Information theory (1)
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- Lighting (1)
- Multi-Objective (1)
- Natural scenes (1)
- Nondestructive testing (1)
- Numerical simulation (1)
- Optimization (1)
- Pattern recognition (1)
- Probability (1)
- Regression (1)
- Social Media (1)
- Spatio-temporal Data Analysis (1)
- Support vector machine (SVM) (1)
- Threat Detection (1)
- Uncertainty (1)
- Visual Analytics (1)
Articles 1 - 4 of 4
Full-Text Articles in Physical Sciences and Mathematics
Nondestructive Testing And Structural Health Monitoring Based On Adams And Svm Techniques, Gang Jiang, Yi Ming Deng, Ji Tai Niu
Nondestructive Testing And Structural Health Monitoring Based On Adams And Svm Techniques, Gang Jiang, Yi Ming Deng, Ji Tai Niu
The 8th International Conference on Physical and Numerical Simulation of Materials Processing
No abstract provided.
Design Optimization Of A Stochastic Multi-Objective Problem: Gaussian Process Regressions For Objective Surrogates, Juan Sebastian Martinez, Piyush Pandita, Rohit K. Tripathy, Ilias Bilionis
Design Optimization Of A Stochastic Multi-Objective Problem: Gaussian Process Regressions For Objective Surrogates, Juan Sebastian Martinez, Piyush Pandita, Rohit K. Tripathy, Ilias Bilionis
The Summer Undergraduate Research Fellowship (SURF) Symposium
Multi-objective optimization (MOO) problems arise frequently in science and engineering situations. In an optimization problem, we want to find the set of input parameters that generate the set of optimal outputs, mathematically known as the Pareto frontier (PF). Solving the MOO problem is a challenge since expensive experiments can be performed only a constrained number of times and there is a limited set of data to work with, e.g. a roll-to-roll microwave plasma chemical vapor deposition (MPCVD) reactor for manufacturing high quality graphene. State-of-the-art techniques, e.g. evolutionary algorithms; particle swarm optimization, require a large amount of observations and do not …
Passive Visual Analytics Of Social Media Data For Detection Of Unusual Events, Kush Rustagi, Junghoon Chae
Passive Visual Analytics Of Social Media Data For Detection Of Unusual Events, Kush Rustagi, Junghoon Chae
The Summer Undergraduate Research Fellowship (SURF) Symposium
Now that social media sites have gained substantial traction, huge amounts of un-analyzed valuable data are being generated. Posts containing images and text have spatiotemporal data attached as well, having immense value for increasing situational awareness of local events, providing insights for investigations and understanding the extent of incidents, their severity, and consequences, as well as their time-evolving nature. However, the large volume of unstructured social media data hinders exploration and examination. To analyze such social media data, the S.M.A.R.T system provides the analyst with an interactive visual spatiotemporal analysis and spatial decision support environment that assists in evacuation planning …
Failure Of Surface Color Cues Under Natural Changes In Lighting, David H. Foster, Iván Marín-Franch
Failure Of Surface Color Cues Under Natural Changes In Lighting, David H. Foster, Iván Marín-Franch
MODVIS Workshop
Color allows us to effortlessly discriminate and identify surfaces and objects by their reflected light. Although the reflected spectrum changes with the illumination spectrum, cone photoreceptor signals can be transformed to give useful cues for surface color. But what happens when both the spectrum and the geometry of the illumination change, as with lighting from the sun and sky? Is it possible, as a matter of principle, to obtain reliable cues by processing cone signals alone? This question was addressed here by estimating the information provided by cone signals from time-lapse hyperspectral radiance images of five outdoor scenes under natural …