The related work section is divided accordingly, as follows: solving the downsampling problem, denoising, deblurring, identifying presence of motion, and image regularization.
Author response: We have shortened this section by simply presenting questions/hypotheses to be solved, followed by results.
The reason for adopting the Caputo definition, as pointed by Momani and Noor [47], is as follows: to solve differential equations (both classical and fractional), we need to specify additional conditions in order to produce a unique solution.
It runs as follows: We solve the fully observable problem by Howard's policy iteration, 25 and then we value the determination routine.
Here, we define a modified Hamming distance δ H and modified Multiply Transpose distance δMT for two columns a and b of a ternary matrix M, parametrized by a real number α, as follows: To solve the obtained TSP instances, we use the publicly available TSP solver Concorde, with Ilog CPLEX 11.0.
We code the first-order van der Pol equations into a MATLAB functiona as follows: To solve Eq. (3), we specify the coefficient μ, the initial conditions and the time-span over which the integration is to proceed; then pass these values, along with the name of the van der Pol function, to the Runge-Kutta solver ode45: The calculated results are plotted in Figure 1.
So, a special report should be sent from the General sink node to the Manager sink node containing the description of this urgent event with steps that should be followed to solve the resulting problems.
We consider that two main trails should be followed to solve this problem: i) to deepen the evaluation of the human aspects and how they affect smell detection; and ii) to evaluate cognitive aspects on smell detection, which is related to program comprehension, and requires knowledge both in computer science and cognitive psychology (Jonathan and Maletic 2008).
The σ ⌢ Open image in new window in Equation (4) can also be estimated individually by Equation (5), as follows, or can be solved simultaneously in Equation (4).
q∗ can then be solved as follows.
