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Algorithms for mutual exclusion
The problem of mutual exclusion - or of defining fundamental operations so that it is possible to resolve conflicts resulting from several concurrent processes sharing the resources of a computer system - has emerged over the last 20 years as a prime example of the difficulties associated with parallel or distributed programming. Expand
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Decision making: whether or not to have prenatal diagnosis and abortion for X-linked conditions.
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Valuable Theoretical Lessons Learned From the Application of Metamodels to a Variety of Industrial Problems
Metamodeling techniques are now being widely used by many industries to replace complex and expensive simulation models so that optimization and probabilistic design studies can be done in a more practical and affordable way. Expand
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Anxiety engendered by amniocentesis.
Anxiety was measured and compared in three groups of 12 pregnant couples undergoing amniocentesis for prenatal diagnosis of chromosomal disorders. Significant elevations in anxiety were found in allExpand
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A Comparison Of Meta -modeling Methods Using Practical Industry Requirements
In spite of the exponential growth of computing power, the enormous computational cost of complex and large -scale engineering design problems make it impractical to rely exclusively on original highExpand
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Efficient Moment and Probability Distribution Estimation Using the Point Estimate Method for High- dimensional Engineering Problems
evaluations when there are n random variables, which is unaffordable for many engineering applications. In the previous paper by the authors [15], a variable-point PEM method was proposed to improveExpand
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Prenatal diagnosis of fetal disorders. Part II: Issues and implications.
Some of the important issues raised by genetic diagnosis include the psychological implications of parents waiting weeks for test results, aborting a defective fetus, accidentally aborting, learningExpand
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Gaussian Process Meta-Models for Efficient Probabilistic Design in Complex Engineering Design Spaces
Probabilistic design in complex design spaces is often a computationally expensive and difficult task because of the highly nonlinear and noisy nature of those spaces. Approximate probabilisticExpand
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Efficient and Accurate Point Estimate Method for Moments and Probability Distribution Estimation
The point estimate method (PEM) is an alternative to Monte Carlo Simulation (MCS) and First Order Second Moments (FOSM) for evaluating the moments and probability distribution of the system orExpand
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Challenges in Uncertainty, Calibration, Validation and Predictability of Engineering Analysis Models
Model calibration, validation, prediction and uncertainty quantification have progressed remarkably in the past decade. However, many issues remain. This paper attempts to provide answers to the keyExpand
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