A formula for the index of the operator, i.e., the difference between the dimensions of the kernel and cokernel is obtained.
The probability of transmission depends on the distance between farms (i.e. the kernel) and the species composition of the farms.
This hardware kernel has several advantages over a counterpart kernel implemented in software: higher-speed processing capability, parallel computation, and separation between the kernel itself and the applications being run.
The relation between the heat kernel and the Poisson kernel is P_{t}^{L}f(x)=frac{t}{sqrt{4pi}} int_{0}^{infty}s^{-3/2}exp bigl -t^{2}/4s bigl -t^{2}/4sf(x),ds.
Previous works have attempted to optimize the combination coefficients by maximizing the centralized kernel alignment between the combined kernel and the ideal kernel.
Furthermore, K_POFVS can achieve efficient communication between the kernel space and the user space, via extending the netlink communication between them.
We also consider a heuristic and simple MKL method (Qiu and Lane, 2009), which chooses the kernel weights based on the relationship between the kernel matrix and the covariance matrix of the target labels (AK-MKL) (for more details see the Supplementary Material).
An important aspect of α is that it contains a convolution operator between the Gaussian kernel and the image, G σ ∗f, which helps to suppress noise and other unwanted artifacts thus detecting useful image features robustly, even under harsh imaging conditions (Figs. 5 and 6).
They are composed of: (a) luminance, (b) gradient intensity, (c) local binary pattern, (d) mean value and (e) standard deviation computed in many kernels of different size, (f) the difference between maximum and minimum values in the kernels, and (g) the pixel value in the median filtered image.
