Titlebook: Importance Sampling; Applications in Comm Rajan Srinivasan Book 2002 Springer-Verlag Berlin Heidelberg 2002 Detection Theory.Importance Sam

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Rajan Srinivasan of time scales on the magnitude and control of the process. Based on measurements using the eddy covariance method, both the latent and sensible heat fluxes were consistently small following ice break up, but increased dramatically as ice formation commenced. Half of the total evaporative water los

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Rajan Srinivasanld rolling forming process.Presents the latest advances, exp.This book presents in detail the theory, processes and equipment involved in cold rolling precision forming technologies, focusing on spline and thread shaft parts. The main topics discussed include the status quo of research on these tech

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Rajan Srinivasanvity, and lower thermal conductivity when compared to conventionally fabricated or fusion-based additive manufactured counterparts due to the inherent defects (i.e., porosity and unbonded interparticle boundary) found in the cold sprayed deposits. These defects generally exist in as-fabricated depos

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Rajan Srinivasanng the production of complex and functional components in a single manufacturing step. It allows the creation of high complexity components with minimal time and cost, as opposed to traditional subtractive manufacturing techniques. Current metallic AM technologies include selective laser melting, di

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Rajan Srinivasancomposite substrates. Although the deposition on metallic substrates has been widely studied and there are interesting books reporting the phenomena occurring and describing the process in detail, the deposition on polymeric substrates is a relatively new branch of cold spraying and to date there ar

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en more difficult by the severe environment conditions experienced by crops due to global warming. Plant biologists and breeders are facing a great challenge in order to improve crop yields along with developing stress-tolerant crops. In order to bioengineer future crops, it is essential to identify

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Elements of Importance Sampling,ways defined on the tails of probability density functions. They have small probabilities and occur infrequently in real applications or in a simulation. This makes it difficult to generate them in sufficiently large numbers that statistically significant conclusions may be drawn. However, these eve

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Methods of Importance Sampling,d biasing schemes in use are motivated by the requirement that for tail probability estimation, the biasing density should effect an increase in the event probability as compared to the original density. In the previous chapter we introduced the problem of estimating the tail probability of a random

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Sums of Random Variables,es frequently appear as quantities of importance. For example, they play a central role in most estimation operations in signal processing applications. In this chapter we apply IS concepts to sums of i.i.d. random variables. Apart from the usual biasing techniques, a method referred to as the ., Sr

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