Classification efficiencies for robust linear discriminant analysis.

Linear discriminant analysis is typically carried out using Fisher’s method. This method relies on the sample averages and covariance matrices computed from the different groups constituting the training sample. Since sample averages and covariance matrices are not robust, it has been proposed to use robust estimators of location and covariance instead, yielding a robust version of Fisher’s method. In this paper relative classification efficiencies of the robust procedures with respect to the classical method are computed. Second order influence functions appear to be useful for computing these classification efficiencies. It turns out that, when using an appropriate robust estimator, the loss in classification efficiency at the normal model remains limited. These findings are confirmed by finite sample simulations.Classification efficiency; Discriminant analysis; Error rate; Fisher rule; Influence function; Robustness;

Robust linear discriminant analysis for multiple groups: influence and classification efficiencies.

Linear discriminant analysis for multiple groups is typically carried out using Fisher's method. This method relies on the sample averages and covariance ma- trices computed from the different groups constituting the training sample. Since sample averages and covariance matrices are not robust, it is proposed to use robust estimators of location and covariance instead, yielding a robust version of Fisher's method. In this paper expressions are derived for the influence that an observation in the training set has on the error rate of the Fisher method for multiple linear discriminant analysis. These influence functions on the error rate turn out to be unbounded for the classical rule, but bounded when using a robust approach. Using these influence functions, we compute relative classification efficiencies of the robust procedures with respect to the classical method. It is shown that, by using an appropriate robust estimator, the loss in classification efficiency at the normal model remains limited. These findings are confirmed by finite sample simulations.Classification; Covariance; Discriminant analysis; Efficiency; Error rate; Estimator; Fisher rule; Functions; Influence function; Model; Multiple groups; Research; Robustness; Simulation; Training;

Multi-order interference is generally nonzero

It is demonstrated that the third-order interference, as obtained from explicit solutions of Maxwell's equations for realistic models of three-slit devices, including an idealized version of the three-slit device used in a recent three-slit experiment with light (U. Sinha et al., Science 329, 418 (2010)), is generally nonzero. The hypothesis that the third-order interference should be zero is shown to be fatally flawed because it requires dropping the one-to-one correspondence between the symbols in the mathematical theory and the different experimental configurations.Comment: Replaced Figs. 4,5 and caption of Fig.

Tree Cover in the Surrounding Landscape Reduces Burrowing Owl (Athene cunicularia) Occupancy of Black-Tailed Prairie Dog Colonies in South Dakota

Burrowing Owl (Athene cunicularia) population declines have led to the owl’s designation as a species of conservation concern in South Dakota. Burrowing Owls nest primarily in black-tailed prairie dog (Cynomys ludovicianus) colonies, but a significant proportion of colonies in South Dakota are not occupied by owls. We studied the influence of landscape-level habitat variables on colony selection by Burrowing Owls. We used call-playback surveys to document presence or absence of Burrowing Owls at 613 prairie dog colonies throughout western and central South Dakota. We used a geographic information system to calculate the percent cover of prairie dog colonies, grassland, cropland, and tree canopy in the surrounding landscape at four buffer sizes. We modeled Burrowing Owl occupancy of prairie dog colonies using logistic regression, and ranked models using Akaike’s Information Criterion. All competitive models contained a tree-canopy-cover variable. Increasing tree canopy cover within 800 m and 1200 m of colony centers was associated with decreasing likelihood of occupancy by Burrowing Owls. Grassland, cropland, and prairie dog colony cover variables did not influence occupancy by Burrowing Owls, and these variables did not improve model fit or discrimination. In landscapes where the presence of nesting burrows is not a limiting factor, as in central and western South Dakota, Burrowing Owls occupied colonies based on the absence of trees. Trees provide habitat for avian and mammalian predators and reduce the available foraging area for Burrowing Owls around prairie dog colonies. Management for Burrowing Owls should include conserving prairie dog colonies in landscapes with few trees and preventing the establishment of trees near occupied colonies

Impact of minority concentration on fundamental (H)D ICRF heating performance in JET-ILW

ITER will start its operation with non-activated hydrogen and helium plasmas at a reduced magnetic field of B-0 = 2.65 T. In hydrogen plasmas, the two ion cyclotron resonance frequency (ICRF) heating schemes available for central plasma heating (fundamental H majority and 2nd harmonic He-3 minority ICRF heating) are likely to suffer from relatively low RF wave absorption, as suggested by numerical modelling and confirmed by previous JET experiments conducted in conditions similar to those expected in ITER's initial phase. With He-4 plasmas, the commonly adopted fundamental H minority heating scheme will be used and its performance is expected to be much better. However, one important question that remains to be answered is whether increased levels of hydrogen (due to e. g. H pellet injection) jeopardize the high performance usually observed with this heating scheme, in particular in a full-metal environment. Recent JET experiments performed with the ITER-likewall shed some light onto this question and the main results concerning ICRF heating performance in L-mode discharges are summarized here

Gas Concentration Mapping of Arenal Volcano Using AVEMS

The Airborne Volcanic Emissions Mass Spectrometer (AVEMS) System developed by NASA-Kennedy Space Center and deployed in collaboration with the National Center for Advanced Technology (CENAT) and the University of Costa Rica was used for mapping the volcanic plume of Arenal Volcano, the most active volcano in Costa Rica. The measurements were conducted as part of the second CARTA (Costa Rica Airborne Research and Technology Application) mission conducted in March 2005. The CARTA 2005 mission, involving multiple sensors and agencies, consisted of three different planes collecting data over all of Costa Rica. The WB-57F from NASA collected ground data with a digital camera, an analog photogrametric camera (RC-30), a multispectral scanner (MASTER) and a hyperspectral sensor (HYMAP). The second aircraft, a King Air 200 from DoE, mounted with a LIDAR based instrument, targeted topography mapping and forest density measurements. A smaller third aircraft, a Navajo from Costa Rica, integrated with the AVEMS instrument and designed for real-time measurements of air pollutants from both natural and anthropogenic sources, was flown over the volcanoes. The improved AVEMS system is designed for deployment via aircraft, car or hand-transport. The 85 pound system employs a 200 Da quadrupole mass analyzer, has a volume of 92,000 cubic cm, requires 350 W of power at steady state, can operate up to an altitude of 41,000 feet above sea level (-65 C; 50 torr). The system uses on-board gas bottles on-site calibration and is capable of monitoring and quantifying up to 16 gases simultaneously. The in-situ gas data in this work, consisting of helium, carbon dioxide, sulfur dioxide and acetone, was acquired in conjunction of GPS data which was plotted with the ground imagery, topography and remote sensing data collected by the other instruments, allowing the 3 dimensional visualization of the volcanic plume at Arenal Volcano. The modeling of possible scenarios of Arenal s activity and its direct impact on the surrounding populated areas in now possible with the combined set of data, linking in-situ data with remote sensing data. The study also helps in the understanding of pyroclastic flow behavior in case of a major eruption

Hidden assumptions in the derivation of the Theorem of Bell

John Bell's inequalities have already been considered by Boole in 1862. Boole established a one-to-one correspondence between experimental outcomes and mathematical abstractions of his probability theory. His abstractions are two-valued functions that permit the logical operations AND, OR and NOT and are the elements of an algebra. Violation of the inequalities indicated to Boole an inconsistency of definition of the abstractions and/or the necessity to revise the algebra. It is demonstrated in this paper, that a violation of Bell's inequality by Einstein-Podolsky-Rosen type of experiments can be explained by Boole's ideas. Violations of Bell's inequality also call for a revision of the mathematical abstractions and corresponding algebra. It will be shown that this particular view of Bell's inequalities points toward an incompleteness of quantum mechanics, rather than to any superluminal propagation or influences at a distance

Experimental Study of Convective Cells and RF Sheaths Ex- cited by a Fast Wave Antenna in the LAPD

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