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Investigation of the presence of rod-shaped bacteria on food surface via elastic light scattering
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作者 Euiwon Bae Huisung Kim +2 位作者 Helen A. McNally Arun K. Bhunia E. Daniel Hirleman 《Advances in Bioscience and Biotechnology》 2012年第4期344-352,共9页
We investigated the presence and related signal-to-noise ratio (SNR) of rod-shaped bacteria on a produce surface using elastic scattering. The theoretical noise was defined as a scattering signal from a rough produce ... We investigated the presence and related signal-to-noise ratio (SNR) of rod-shaped bacteria on a produce surface using elastic scattering. The theoretical noise was defined as a scattering signal from a rough produce surface while the signal was defined as a scattering signal from the increasing numbers of rod-shaped bacteria on the produce surface. In this research, we measured the surface topography of a tomato using BioAFM to provide the quantitative nature of the surface roughness which was, in turn, modeled with the discrete dipole approximation (DDA) for an accurate estimation of the background scattering signature. Then we included the DDA model of rod-shaped bacteria and calculated the combined elastic scattering signature in the upper hemispherical space with different polarizations, wavelengths, and incident angles. The total scattering cross-section (TSC) and partial scattering cross-section (PSC) were both computed on six predefined aperture locations. The results indicate that, upon proper selection of the wavelength and incident angle, it was possible to provide the minimum number of bacteria (~32) to provide a differentiable elastic scattering signal from the produce surface. 展开更多
关键词 Scattering ROUGHNESS E. COLI O157 FOOD SURFACE Diffraction
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Eigenvector Sensitivity: A Kharitonov Result
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作者 Vincent Winstead 《American Journal of Computational Mathematics》 2013年第2期158-168,共11页
This study is motivated by a need to effectively determine the difference between a system fault and normal system operation under parametric uncertainty using eigenstructure analysis. This involves computational robu... This study is motivated by a need to effectively determine the difference between a system fault and normal system operation under parametric uncertainty using eigenstructure analysis. This involves computational robustness of eigenvectors in linear state space systems dependent upon uncertain parameters. The work involves the development of practical algorithms which provide for computable robustness measures on the achievable set of eigenvectors associated with certain state space matrix constructions. To make connections to a class of systems for which eigenvalue and characteristic root robustness are well understood, the work begins by focusing on companion form matrices associated with a polynomial whose coefficients lie in specified intervals. The work uses an extension of the well known theories of Kharitonov that provides computational efficient tests for containment of the roots of the polynomial (and eigenvalues of the companion matrices) in “desirable” regions, such as the left half of the complex plane. 展开更多
关键词 EIGENVECTORS Kharitonov ROBUSTNESS
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