5,018 research outputs found

    Estimating Sensor Motion from Wide-Field Optical Flow on a Log-Dipolar Sensor

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    Log-polar image architectures, motivated by the structure of the human visual field, have long been investigated in computer vision for use in estimating motion parameters from an optical flow vector field. Practical problems with this approach have been: (i) dependence on assumed alignment of the visual and motion axes; (ii) sensitivity to occlusion form moving and stationary objects in the central visual field, where much of the numerical sensitivity is concentrated; and (iii) inaccuracy of the log-polar architecture (which is an approximation to the central 20°) for wide-field biological vision. In the present paper, we show that an algorithm based on generalization of the log-polar architecture; termed the log-dipolar sensor, provides a large improvement in performance relative to the usual log-polar sampling. Specifically, our algorithm: (i) is tolerant of large misalignmnet of the optical and motion axes; (ii) is insensitive to significant occlusion by objects of unknown motion; and (iii) represents a more correct analogy to the wide-field structure of human vision. Using the Helmholtz-Hodge decomposition to estimate the optical flow vector field on a log-dipolar sensor, we demonstrate these advantages, using synthetic optical flow maps as well as natural image sequences

    The NWRA Classification Infrastructure: Description and Extension to the Discriminant Analysis Flare Forecasting System (DAFFS)

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    A classification infrastructure built upon Discriminant Analysis has been developed at NorthWest Research Associates for examining the statistical differences between samples of two known populations. Originating to examine the physical differences between flare-quiet and flare-imminent solar active regions, we describe herein some details of the infrastructure including: parametrization of large datasets, schemes for handling "null" and "bad" data in multi-parameter analysis, application of non-parametric multi-dimensional Discriminant Analysis, an extension through Bayes' theorem to probabilistic classification, and methods invoked for evaluating classifier success. The classifier infrastructure is applicable to a wide range of scientific questions in solar physics. We demonstrate its application to the question of distinguishing flare-imminent from flare-quiet solar active regions, updating results from the original publications that were based on different data and much smaller sample sizes. Finally, as a demonstration of "Research to Operations" efforts in the space-weather forecasting context, we present the Discriminant Analysis Flare Forecasting System (DAFFS), a near-real-time operationally-running solar flare forecasting tool that was developed from the research-directed infrastructure.Comment: J. Space Weather Space Climate: Accepted / in press; access supplementary materials through journal; some figures are less than full resolution for arXi

    Improving Treatment Through Research Directing Attention to the Role of Development in Adolescent Treatment Success

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    Treatment of adolescents with alcohol use problems can be as successful as in adults, but the success often is short-lived, with most treated adolescents relapsing within a few months. Developmental differences among adolescents may contribute to this high rate of relapse, and treatment approaches that pay direct attention to the patients’ developmental status may improve outcomes. To date, studies assessing adolescent alcohol treatment rarely have investigated the association between developmental stage and outcome. In addition, even experts do not fully agree on the developmentally appropriate outcomes that should be evaluated in adolescent treatment studies. Research methods and variables used to assess the outcome of adolescent alcohol treatment often rely on those used in treatment studies of adults. Developmental factors that may directly influence adolescents’ amenability to treatment, such as pubertal status, psychological development (e.g., executive mental functions), social relationships, and developmental transitions, have not been adequately investigated. Studies using concepts from developmental science are needed to determine how individual characteristics, various contextual influences (e.g., from peers, family, or the social environment), and the interactions of these factors influence alcohol use behavior, amenability to treatment, and treatment outcomes. Knowledge gained in studies directly examining developmental factors should help in the design of more effective treatment programs with lower relapse rates
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