60,996 research outputs found

    Earth orbital teleoperator system man-machine interface evaluation

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    The teleoperator system man-machine interface evaluation develops and implements a program to determine human performance requirements in teleoperator systems

    Apollo experience report: Electronic systems test program accomplishments and results

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    A chronological record is presented of the Electronic Systems Test Program from its conception in May 1963 to December 1969. The original concept of the program, which was primarily a spacecraft/Manned Space Flight Network communications system compatibility and performance evaluation, is described. The evolution of these concepts to include various levels of test detail, as well as systems level design verification testing, is discussed. Actual implementation of these concepts is presented, and the facility to support the program is described. Test results are given, and significant contributions to the lunar landing mission are underlined. Plans for modifying the facility and the concepts, based on Apollo experience, are proposed

    A non-homogeneous dynamic Bayesian network with sequentially coupled interaction parameters for applications in systems and synthetic biology

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    An important and challenging problem in systems biology is the inference of gene regulatory networks from short non-stationary time series of transcriptional profiles. A popular approach that has been widely applied to this end is based on dynamic Bayesian networks (DBNs), although traditional homogeneous DBNs fail to model the non-stationarity and time-varying nature of the gene regulatory processes. Various authors have therefore recently proposed combining DBNs with multiple changepoint processes to obtain time varying dynamic Bayesian networks (TV-DBNs). However, TV-DBNs are not without problems. Gene expression time series are typically short, which leaves the model over-flexible, leading to over-fitting or inflated inference uncertainty. In the present paper, we introduce a Bayesian regularization scheme that addresses this difficulty. Our approach is based on the rationale that changes in gene regulatory processes appear gradually during an organism's life cycle or in response to a changing environment, and we have integrated this notion in the prior distribution of the TV-DBN parameters. We have extensively tested our regularized TV-DBN model on synthetic data, in which we have simulated short non-homogeneous time series produced from a system subject to gradual change. We have then applied our method to real-world gene expression time series, measured during the life cycle of Drosophila melanogaster, under artificially generated constant light condition in Arabidopsis thaliana, and from a synthetically designed strain of Saccharomyces cerevisiae exposed to a changing environment
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