![]() However, the names of higher-order hypercubes do not appear to be in common use for higher powers. As a result, the act of raising a number to 2 or 3 is more commonly referred to as " squaring" and "cubing", respectively. Comparison with a re cently proposed scheme called scan indicates that the lazy scheme performs better than scan under a wide range of workloads. Similarly, the exponent 3 will yield a perfect cube, an integer which can be arranged into a cube shape with a side length of the base. Simulation studies show that the hypercube performance is dra matically enhanced by using the lazy scheme as com pared to the FCFS scheduling. For example, the exponent 2 will yield a square number or "perfect square", which can be arranged into a square shape with a side length corresponding to that of the base. It has been observed that all the hypercube allocation policies with the FCFS scheduling provide only incremental performance improvement. Generalized hypercubesĪny positive integer raised to another positive integer power will yield a third integer, with this third integer being a specific type of figurate number corresponding to an n-cube with a number of dimensions corresponding to the exponential. A unit hypercube's longest diagonal in n dimensions is equal to n. It is a closed, compact, convex figure whose 1- skeleton consists of groups of opposite parallel line segments aligned in each of the space's dimensions, perpendicular to each other and of the same length. In geometry, a hypercube is an n-dimensional analogue of a square ( n = 2) and a cube ( n = 3). Latin hypercube sampling and Partial Rank Correlation Coefficient procedure (LHS/PRCC) can be used in combination to perform a sensitivity analysis that. For the four-dimensional object known as “the” hypercube, see Tesseract. Using these simulation results, we then computed PRCCs between each parameter and two different model outcomes across all time points: the total number of tumor cells and the fraction of tumor that has low sensitivity ( Figure 4 ). For the common number scheme of nodes this is between node pairs that differ by exactly one bit in their number. These samples were then randomly paired in a Latin hypercube scheme to run a series of 1,000 Monte Carlo simulations. For internetwork topology, see Hypercube internetwork topology. In an algorithm with a hypercube communication pattern all communication activities take place between nodes that are direct neighbors in the layout of a hypercube. For the computer architecture, see Connection Machine. 15 references, 4 figures, 9 tables.This article is about the mathematical concept. Other techniques for sensitivity/uncertainty analysis, e.g., kriging followed by conditional simulation, will be used also. In this paper we propose two new constructions of such secret sharing schemes based on different combinatorial structures. For example, the adjoint method may be used to reduce the scope to a size that can be readily handled by a technique such as LHS. The Office of Nuclear Waste Isolation will use the technique most appropriate for an individual situation. This unlimited number of parameters capability can be extremely useful for finite element or finite difference codes with a large number of grid blocks. The adjoint method is recommended when there are a limited number of performance measures and an unlimited number of parameters. Of deterministic techniques, the more » direct method is preferred when there are many performance measures of interest and a moderate number of parameters. The LHS technique is easy to apply and should work well for codes with a moderate number of parameters. One approach, based on Latin Hypercube Sampling (LHS), is a statistical sampling method, whereas, the second approach is based on the deterministic evaluation of sensitivities. Two different approaches to sensitivity/uncertainty analysis were used on this code. This study focused on steady-state flow as the performance measure of interest. LHS was described by Michael McKay of Los Alamos National Laboratory in 1979. The sampling method is often used to construct computer experiments or for Monte Carlo integration. The model consists of three coupled equations with only eight parameters and three dependent variables. Latin hypercube sampling ( LHS) is a statistical method for generating a near-random sample of parameter values from a multidimensional distribution. A computer code was used to study steady-state flow for a hypothetical borehole scenario.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |