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In the past fractal dimension has often been computed using a stochastic approach based on a random walk process, which has been found to be very time consuming. More recently, mathematical morphology has been used to compute the fractal dimension in a more timely fashion. This paper describes how the fractal dimension computed using mathematical morphology can be used in the texture analysis of ultrasonic imagery. The discriminatory ability of the fractal dimension as a pattern recognition feature is evaluated and compared to more traditional parameters. This analysis includes comparisons with statistical features in which each parameter is treated as an independent variable and in which interactions between those variables are evaluated. Pattern recognition techniques include Stepwise Discriminant Analysis, Linear Discriminant Analysis, and Nearest Neighbor Analyisis in addition to Backpropagation Neural Network Classifiers. Our results identify the fractal dimension as one of the most important parameters for distinguishing between normal and abnormal livers. In this study, consisting of 186 images, a significant statistical difference was found for both the mean and standard deviation of the fractal dimension between the normal and abnormal groups using parametric and nonparametric statistical techniques. © 1993 SPIE. All rights reserved.
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Hybrid knowledge bases (HKBs), proposed by Nerode and Subrahmanian, provide a uniform theoretical framework for dealing with the mixed data types and multiple reasoning modes required for solving logical deployment problems. Algorithms based on mixed integer linear programming techniques have been developed for the syntactic subset of HKBs corresponding to function-free Prolog-like logic programs. In this study, we examine the ability of neural networks to solve a more comprehensive set of problems expressed within the hybrid knowledge base framework. The objective of this research is to design and implement a nonlinear optimization procedure for solving extended logic programs with neural networks. We focus upon two types of extensions which are typically required in the formulation of logical deployment problems. The first type of extension, which we shall refer to as a Type I extension, consists of embedding numerical and geometric constraints into logic programs. The second type of extension, which we shall call a Type II extension, consists of incorporating optimization problems into logic clauses. © 1993 SPIE. All rights reserved.
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Potential environmental impacts on wildlife result from siting and construction (short-term impacts) and habitat removal and fragmentation (long-term impacts) as a consequence of transportation corridor construction. Especially in rural districts, wildlife migration corridors and dispersal orientation are altered or destroyed and wildlife populations and their gene pools are isolated. This significantly weakens the wildlife community. Prudent selection of construction corridors reduces fragmentation impacts by maximizing preserved fragment sizes, and by running parallel to, not through, natural areas. Corridor width determines the degree to which wildlife movement is restricted except that culverts, underpasses, overpasses, and one-way gates, can aid wildlife in cross movements. Minimum underpass dimensions for large wildlife should be no smaller than 14 ft×14 ft and should include natural substratum inverts. Rail corridors have four characteristics that minimize adverse environmental impacts. The railbed is dry, ballast fillters runoff, there is little runoff beyond the toe of slope, and drainage ditches serve to control sheet flow and erosion, sediment movement, and uncontrolled channel flow. Rail corridors usually occupy smaller land areas because they are narrower and are more feasible to elevate so as to allow free movement of wildlife across the corridor. © 1993 Springer-Verlag New York Inc.
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