In comparison between subjects solving the case on computer and those solving the case with paper and pencil, the Chi-square test was used for variables measured on a nominal scale.
This paper presents a genetic algorithm to solve the MCR problem subject to transmission delay and transmission success ratio.
A boundary element method, BEM, is applied to solve the Helmholtz equation subjected to boundary conditions related to structural vibrations.
Second, to solve the "connectedness" problem, subjects had to learn that the food had to be on and connected to the surface of a single uninterrupted tray instead of on a tray with a horizontal gap, thus making this problem more complicated than the "on off" problem (Hauser et al. 1999).
Roeder and Wasserman [ 9] showed that the optimal "oracle" weight can be obtained by setting the derivatives of (3) to zero and solving the equations subject to Wj > 0 and ∑ i = 1 m W i = m.
In configural learning, the subject cannot solve the discrimination task by reference to a single element.
The directional derivative method is shown to be an efficient method to solve the optimum linear transceivers, subject to the p-norm constraint[24, 25].
In this paper a novel method to solve the constant coefficient wave equation, subject to interface jump conditions, is presented.
We therefore incorporate a rolling baseline into the model such that the observation y is represented as a smooth baseline u with peaks on top v and noise, and solve the optimization problem: min ||x||1+u||β||1+½||r||22 subject to u+v+r = y, Ax = v, and Δ2u = β.
Therefore, for uncertain and v, the robust synthetic gene network design is to solve the minimax problem in (5) subject to the regulation error dynamic system in (4).
The sub-optimal synthetic gene network design in (23) is to solve the following constrained optimization (24) subject to (25) see Appendix C in the Supplementary Material.
