Sentence examples for both function and value from inspiring English sources

For older patients, several designs of Total Hip Arthroplasty have shown excellent results in terms of both function and value for money.

For older patients, several designs of Total Hip Arthroplasty (THA) have shown excellent results in terms of both function and value for money [ 1].

For patients older than 65 years with severe arthritis of the hip, several implant designs for total hip arthroplasty (or replacement) have shown excellent long term results in terms of both function and value for money. 1 However, in younger and more active patients, these traditional implants have a failure rate of about 50% after 25 years.

HWENO was first proposed for solving nonlinear hyperbolic problems by evolving both function values and its first derivative values (Qiu and Shu (2004) [23]).

In this paper a bivariate rational interpolation is constructed using both function values and partial derivatives of the function being interpolated as the interpolation data.

In this paper a bivariate rational Hermite interpolation is developed to create a space surface using both function values and the first-order partial derivatives of the function being interpolated as the interpolation data.

On the other hand, it is easy to observe that both functions and do not have limiting value as.

To investigate the dependence of the collected signal on phase function, sets of simulations were run that investigated variations in both phase function and anisotropy values.

where Δ Q t depends on the reward value, the quality function and the value function.

The idea of the reconstruction in the HWENO schemes comes from the original WENO schemes, however both the function and its first derivative values are evolved in time and used in the reconstruction, while only the function values are evolved and used in the original WENO schemes.

The approximation is based on the numerical properties of the Bernstein polynomial, which is capable of effectively controlling the approximation error for both the function value and gradient.