855 resultados para Measurement in Bacteriology
Resumo:
We present a simple and practical method for the single-ended distributed fiber temperature measurements using microwave (11-GHz) coherent detection and the instantaneous frequency measurement (IFM) technique to detect spontaneous Brillouin backscattered signal in which a specially designed rf bandpass filter at 11 GHz is used as a frequency discriminator to transform frequency shift to intensity fluctuation. A Brillouin temperature signal can be obtained at 11 GHz over a sensing length of 10 km. The power sensitivity dependence on temperature induced by frequency shift is measured as 2.66%/K. (c) 2007 Society of Photo-Optical Instrumentation Engineers.
Resumo:
abstract {We present a simple and practical method for the single-ended distributed fiber temperature measurements using microwave (11-GHz) coherent detection and the instantaneous frequency measurement (IFM) technique to detect spontaneous Brillouin backscattered signal in which a specially designed rf bandpass filter at 11 GHz is used as a frequency discriminator to transform frequency shift to intensity fluctuation. A Brillouin temperature signal can be obtained at 11 GHz over a sensing length of 10 km. The power sensitivity dependence on temperature induced by frequency shift is measured as 2.66%/K. © 2007 Society of Photo-Optical Instrumentation Engineers.}
Resumo:
250 p. + anexos
Resumo:
Body-size measurement errors are usually ignored in stock assessments, but may be important when body-size data (e.g., from visual sur veys) are imprecise. We used experiments and models to quantify measurement errors and their effects on assessment models for sea scallops (Placopecten magellanicus). Errors in size data obscured modes from strong year classes and increased frequency and size of the largest and smallest sizes, potentially biasing growth, mortality, and biomass estimates. Modeling techniques for errors in age data proved useful for errors in size data. In terms of a goodness of model fit to the assessment data, it was more important to accommodate variance than bias. Models that accommodated size errors fitted size data substantially better. We recommend experimental quantification of errors along with a modeling approach that accommodates measurement errors because a direct algebraic approach was not robust and because error parameters were diff icult to estimate in our assessment model. The importance of measurement errors depends on many factors and should be evaluated on a case by case basis.