Abstract: A biological hazard mitigation apparatus permitting a material handling operation in the vicinity of a work area includes a plenum pneumatically coupled and proximate to one side of the work area, a filter sized to trap biological hazards and including an exhaust port, a blower including an inlet port and an exhaust port, and ducting pneumatically coupling the exhaust port of the filter to the inlet port of the blower, wherein the filter is disposed in the plenum, and adjacent surfaces of the filter and the plenum are substantially equal in surface area. If desired, the ducting includes first and second ducts, permitting a silencer to be disposed between the first and second ducts. Methods for operating the apparatus are also described.

Abstract: A biological hazard mitigation apparatus permitting a material handling operation in the vicinity of a work area includes a plenum pneumatically coupled and proximate to one side of the work area, a filter sized to trap biological hazards and including an exhaust port, a blower including an inlet port and an exhaust port, and ducting pneumatically coupling the exhaust port of the filter to the inlet port of the blower, wherein the filter is disposed in the plenum, and adjacent surfaces of the filter and the plenum are substantially equal in surface area. If desired, the ducting includes first and second ducts, permitting a silencer to be disposed between the first and second ducts. Methods for operating the apparatus are also described.

Abstract: Image analysis is performed by defining segmentation boundaries within an image by using wavelet theory or some other suitable method. Such boundaries can be incomplete, irregular, and/or multi-valued. The segmentation boundaries are then incorporated into feature calculations related to fractal dimensions for each pixel using a diffusion related method or a Dijkstra potential related method. These features are then used in statistical techniques to distinguish among textures or classes of interest. The system performing the image analysis is trained (or supervised) on data from different classes within an image or images. This enables the system to then later identify these classes in different images. The system can be used for Computer Aided Diagnosis (CAD) of mammograms or other medical imagery.