perceptual reasoning or working memory. A consistent finding is that individuals who perform well in one domain tend to perform well in the others, which led to the derivation of a general factor of intelligence calledg-factor10. While theg-factor also targets learned ...
In Fig. 3a, the conditional GAN receives input with random noise conditioned on one of three classes (Class Vector; C): patient, Normal_Y, and Normal_A. This input is processed through a multilayer perceptron (MLP; M), resulting in a latent vector. The latent vector is then fed into ...
One can query the node types database using the Python tool sol-flow-node-type-find.py, as an example say we want to query the nodes with at least the same ports as gpio/writer (a single boolean OUT port): sol-flow-node-type-find.py --format=simple \ --similar-ports=gpio/writer...
An uncertain IElement can be thought of as a random variable which may take a range of numerical outcomes, and the probability of sampling each outcome is defined by the underlying probability distribution. This is useful for the definition of optimization problems that have uncertainties. Section ...
Dilay - A 3D sculpting application that provides an intuitive workflow using a number of powerful modelling tools. GNU GPLv3 or later. Procedural Generators SpaceshipGenerator - A Blender script allowing generation of spaceships from a random seed and some parameters. Expat. Spritesheet Tools Piskel...
Because an auto-incrementing integer might yield a predictable and therefore insecure relationship between PID and RID, the TRID is generated pseudorandomly (with a random or a pre-specified seed for the random number generator). The TRID, therefore, is convenient for within-query use (for ...
To this end, we generate a random number using the PDF with the associated parameters of month m. This generated random number is the average 𝜂(𝑚,𝑑)η(m,d). Then, using the computed thresholds resulting from the optimization problem (5), the type of day d of month m is ...
We used a normal distribution generator to generate the random stimulus and rewards. We trained the model in simulation for 100 rounds. Then, we ran two additional simulations with a random stimulus perception forcing the reward to be obtained before and after the 300-s mark to analyse how ...
This new approach improves the convergence rate and reduces the cost of calculations in the comparison [25], and the second one achieves a true optimal solution and avoids premature convergence, allowing a random walk process for PSO [20]. Among the applications reported in 2018, PSO, together...
In the field of intelligent surface inspection systems, particular attention is paid to decision making problems, based on data from different sensors. The combination of such data helps to make an intelligent decision. In this research, an approach to intelligent decision making based on a data ...