作者:
DAVIS, CBMCNICHOLS, RJCharles B. Davis is principal statistician with Environmet- rics & Statistics Ltd. (EnviroStat
1853 Wellington Court Henderson NV 89014). After receiving his M.S. in mathematics and statistics and Ph.D. in statistics from the University of New Mexico he joined the Mathematics Department of the University of Toledo to establish its graduate program in statistics with emphasis on consulting and applications. He and McNichols became involved in consulting and research related to statistical issues arising in RCRA ground water monitoring regulation in 1985 and formed EnviroStat in 1990. Davis left academia in 1992 to concentrate on environmental statistics. Roger J. McNichols is professor and chairman of the Industrial Engineering Department at The University of Toledo
(Toledo OH 43606). After receiving his Ph.D. in industrial engineering from The Ohio State University he joined the faculty of Texas A and M University where he directed the Maintainability Engineering Graduate Program at Red River Army Depot. At University of Toledo he is also chairman of the Systems Doctoral Program and has served as associate dean of engineering. His research and consulting interests include reliability quality control manufacturing environmental monitoring mathematical modeling and applied statistics.
Current federal ground water monitoring statistical regulation dates from the revised RCRA Subtitle C Final Rule of 1988. That rule was a considerable advance over previous RCRA statistical rules. However, two major p...
Current federal ground water monitoring statistical regulation dates from the revised RCRA Subtitle C Final Rule of 1988. That rule was a considerable advance over previous RCRA statistical rules. However, two major problem areas remained: facility-wide false positive rate (FWFPR) control and spatial variability. Progress has been made in the 1991 Subtitle D Final Rule and in guidance;the 1992 Addendum to Interim Final Guidance in particular includes a substantial conceptual advance toward resolving the FWFPR problem. Other areas of improvement include normality testing and distribution assumptions, dropping the four independent samples per monitoring period requirement, allowing a preliminary evaluation short of a 40 CFR Part 258 Appendix II assessment upon finding a statistically significant increase, and suggesting superior alternatives to analyses of variance (ANOVAs) and tests of proportions. The problem of dealing with natural spatial variability remains. Although certain techniques listed in the regulations can control for inherent spatial variability and the performance standards require doing so ''when necessary,'' little attention has been paid to the ubiquity of such spatial variation. Moreover, regulatory traditions favoring upgradient-downgradient comparisons often make control of natural spatial variation difficult and ineffective. With new, lined facilities easily implemented statistical solutions are available;however, dealing with the several existing solid waste facilities which will now be regulated under Subtitle D will present major challenges. In short, the 1988 revision of the Subtitle C rules made it more possible to provide statistically sound monitoring programs, and there has been steady progress since then. Challenges remain, however. These vary from state to state, particularly with regard to controlling false positives and false negatives in the presence of natural spatial variability.
Osteocytes regulate the response of osteoclasts and osteoblasts to mechanical loading through signaling molecules, the levels of which are controlled by post-translational modification or degradation and by differenti...
Osteocytes regulate the response of osteoclasts and osteoblasts to mechanical loading through signaling molecules, the levels of which are controlled by post-translational modification or degradation and by differential gene transcription and translation. The magnitude and mode of bone tissue deformation that elicits a transcriptional response in individual osteocytes in situ has been difficult to quantify. We measured SOST, Wnt11, TNF, and FRZB gene expression in osteocytes within loaded and unloaded control porcine trabecular bone explants using RNAScope® and compared the local tissue level strain and strain gradient-which we used as an indicator of potential poroelastic fluid flow-in the tissue surrounding osteocytes with high vs. low gene expression. The measured expression of all four genes differed between loaded and unloaded explants, on average, with the mean SOST expression level decreasing by 45%. In the loaded explants, gene expression was altered from baseline in about 30% of the osteocytes, and they were surrounded by tissue with higher strain and strain gradient than the 20 to 25% of osteocytes that remained near baseline expression. Both deviatoric strain and hydrostatic strain gradient were sensitive and specific predictors of the mechanobiological response for individual genes as well as combinations. SOST expression was highly related to elevated strain gradient, providing evidence that osteocytes respond to fluid flow in the lacunar-canalicular system.
Nowadays most communications are done by utilizing digital transmission *** security of this digital information transmitted through different communication systems is quite *** secrecy of digital data is one of the b...
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Nowadays most communications are done by utilizing digital transmission *** security of this digital information transmitted through different communication systems is quite *** secrecy of digital data is one of the burning topics of the digitally developed *** exist many traditional algorithms in the literature to provide methods for robust *** most important and recent modern block cipher named the advanced encryption standard(AES)is one of the extensively utilized encryption schemes with binary *** is a succession of four fundamental steps:round key,sub-byte,shift row,and mix *** this work,we will provide an innovative methodology for extending the AES in a Galois fieldwith any characteristic *** four steps in the fundamental process with binary characteristics will be adjusted because of the new *** applying double affine transformations,we have enhanced the number of options in our suggested substitution *** reconstruction of the nonlinear confusion component and encryption structure provides robustness in the generalized *** increase in the keyspace due to the Galois field generalization implies that we have improved additional confusion abilities and broadened the current *** implementation of the proposed structure of AES for image,audio,and video encryption will provide high security for secure communication.
When subpopulation objects are to be analyzed, qualitative data is frequently transformed into a contingency table. The categories of rows and columns in the contingency table are sequentially treated as objects and v...
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In this paper, we introduce an approach for obtaining probabilistically guaranteed upper and lower bounds on the true optimal value of stopping problems. Bounds of existing simulation-and-regression approaches, such a...
In this paper, we introduce an approach for obtaining probabilistically guaranteed upper and lower bounds on the true optimal value of stopping problems. Bounds of existing simulation-and-regression approaches, such as those based on least squares Monte Carlo and information relaxation, are stochastic in nature and therefore do not come with a finite sample guarantee. Our data-driven approach is fundamentally different as it allows replacing the sampling error with a pre-specified confidence level. The key to this approach is to use high- and low-biased estimates that are guaranteed to over- and underestimate, respectively, the conditional expected continuation value that appears in the stopping problem’s dynamic programming formulation with a pre-specified confidence level. By incorporating these guaranteed over- and underestimates into a backward recursive procedure, we obtain probabilistically guaranteed bounds on the problem’s true optimal value. As a byproduct we present novel kernel-based non-asymptotic uniform confidence bands for regression functions from a reproducing kernel Hilbert space. We derive closed-form formulas for the cases where the data-generating distribution is either known or unknown, which makes our data-driven approach readily applicable in a range of practical situations including simulation. We illustrate the applicability of the proposed bounding procedure by valuing a Bermudan put option.
In this paper, we introduce a new algorithm based on total variation for denoising speckle noise images. Total variation was introduced by Rudin, Osher, and Fatemi in 1992 for regularizing images. Chambolle proposed a...
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The reduced basis methodology is an efficient approach to solve parameterized discrete partial differential equations when the solution is needed at many parameter values. An offline step approximates the solution spa...
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Tests based on higher-order orm-step spacings have been considered in the literature for the goodness of fit problem. This paper studies the asymptotic distribution theory for such tests based on non-overlappingm-step...
Tests based on higher-order orm-step spacings have been considered in the literature for the goodness of fit problem. This paper studies the asymptotic distribution theory for such tests based on non-overlappingm-step spacings whenm, the length of the step, also increases with the sample sizen, to inifinity. By utilizing the asymptotic distributions under a sequence of close alternatives and studying their relative efficiencies, we try to answer a central question about the choice ofm in relation ton. Efficiency comparisons are made with tests based on overlappingm-step spacings, as well as corresponding chi-square tests.
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