We now proceed with the key step of the new algorithm presented in this paper and compute the point values of the conserved quantities at the cell centers, simply by evaluating the reconstruction polynomials in the barycenter of each control volume: mathbf{Q}_{ijk}^{n} = mathbf{w}_{h} bigl( x_{i},y_{j},z_{k},t^{n} bigr).
An example is given, in which instead of computing the fixed point of an operator, we approximate the operator with a contractive-like one.
In 1976, Kellogg et al. (see [5]) gave a constructive proof of the Brouwer fixed point theorem and hence presented a homotopy method for computing the fixed points of a twice continuously differentiable self-mapping (Phi(x)).
For example, people were faster computing the mid-point of 6 and -4 than 8 and -2, even though both pairs of digits were displayed in the same locations on a video screen.
We then evaluate the maximum scallop height along a scallop curve by computing the stationary points of the distance function between the scallop curve and the design surface.
This is via bilateration, computing the intersection points of two circles centered at, with appropriate radii.
We go on to discuss optical computing from the point of view of computational complexity theory, with the aim of putting some old, and some very recent, results in context.
The smartphone is a new technology that combines mobile communication and computation in a handheld-sized device, facilitating mobile computing at the point of care.
However, this approach to the generation of the plant template leads to heavy computational burden since it wastes much computational effort computing the images of points on edges which lie in the interior of the plant template.
With the first derivative of f(t), we can compute the critical point of f(t) through the equation as f ′ ( t ) = [ 1 − P ( A 1 ) ] ζ 0 + P ( A 1 ) ζ p ¯ + δ − φ ′ ( t ) φ ( t ) = 0. (53).
