Abstract: A hard disk drive protection system comprises a sensor configured to detect an impending shock event and a hard drive protection module configured to determine whether to issue a fast park command for a hard disk drive in response to detecting the impending shock event based on a permissible quantity of fast park cycles for the hard disk drive.

Abstract: A new approach to multispectral image compression where the intra- and cross-band correlations are jointly exploited in a surprisingly simple yet very effective manner. The key component of the algorithm is a bijection mapping of the original multispectral image into a virtual 2 dimensional scalar image. By optimally mapping the multispectral image set into a single 2 dimensional array and by subsequently applying a scalar image coding algorithm, the spatial correlation and the spectral correlation of the multispectral data set are jointly exploited. Based on the statistical characteristics of the multispectral data, the bijection mapping can be optimized to minimize the distortion introduced by the compression algorithm. The optimization reduces to the maximization of a function of the second-order statistics of the multispectral data.

Abstract: A computationally efficient modeling system for imagery scales both the original image and corresponding principal component tiles in the same proportion to be able to extract scaled principal components. The system includes recovery of feature weights for the image model by extracting the weights from the reduced size principal component tiles. The use of the reduced size tiles to derive weights dramatically reduces computer overhead both in the generation of the files and in the generation of the weights, and is made possible by the fact that the weights from the scaled down tiles are nearly equal to the weights of the tiles associated with the full size image. The subject system thus reduces computation and the number of bits required to represent features by first scaling the image and then tiling the image in the same proportion. In one embodiment, the scaled down tiles are used as training exemplars used to generate the principal components.

Abstract: An apparatus and method for detecting gases, gasified agents or other analytes. The apparatus includes a solid body having a first surface area and a second surface area. A first, preferably polymeric, coating is superimposed on the first surface area of the solid body. A second, preferably polymeric, coating is superimposed on the second surface area of this solid body. The first coating and the second coating are different materials which adsorb different agents at different rates. A wave propagating transducer is positioned adjacent the solid body to propagate a first wavefront adjacent the first surface area of the solid body. This wave propagating transducer also propagates a second wavefront adjacent the second surface area of the solid body. These first and second wavefronts interfere to produce an interference pattern which is unique to the particular agent which is adsorbed by the first and second coatings.

Abstract: A computationally efficient modeling system for imagery scales both the original image and corresponding principal component tiles in the same proportion to be able to extract scaled principal components. The system includes recovery of feature weights for the image model by extracting the weights from the reduced size principal component tiles. The use of the reduced size tiles to derive weights dramatically reduces computer overhead both in the generation of the files and in the generation of the weights, and is made possible by the fact that the weights from the scaled down tiles are nearly equal to the weights of the tiles associated with the full size image. The subject system thus reduces computation and the number of bits required to represent features by first scaling the image and then tiling the image in the same proportion. In one embodiment, the scaled down tiles are used as training exemplars used to generate the principal components.

Abstract: An outer product neural network provides a predetermined number of processing elements for extracting principal components of an input vector. The residual vector of the network when cascaded into a similar outer product neural network provides additional principal components defining a subspace orthogonal to the subspace defined by the principal components of the first network.