To systematically study the effect of the kernel, we introduce a new kernel that allows us to adjust the strength of cross-aggregation over that of self-aggregation.
In Figure11, we presented the upscaled images obtained by varying the size of the Lanczos interpolation kernel to analyze the effect of the kernel size on the image quality.
However, a more systematic assessment on the effect of the kernel and its comparison to shortest-path, direct-interaction-only, or other methods, such as GTOM [38] is certainly in order.
The effects of the flame kernel size, flame kernel temperature and equivalence ratio were also examined on MIT, MIE and IDP (ignition delay period).
In this work, different kernels namely linear kernel, polynomial kernel, sigmoid, and radial basis function (RBF) kernel were used, and the effects of these kernel functions on SVR model based on GS-optimization method are summarized in Table 6.
Table 3 Comparison of the classification effects of the four kernel functions Categories of function Iterations Minimum value by quadratic programming Decision of function bias b nSV nBSV Linear function 205 −20.090207 3.858766 35 21 Polynomial function 34 −58.834062 59.810486 62 59 Radial basis function 48 −45.700202 −0.200129 62 54 Sigmoid kernel function 35 −52.498549 0.482414 62588.
The potential anticancer effects of the ethanolic kernel extract on breast cancer cells (MDA-MB-231 and MCF-7) using MTT, anti-proliferation, neutral red (NR) uptake and lactate dehydrogenase (LDH) release assays were evaluated.
Figure 7 Effect of width of the kernel on edge pixels for an embedding rate of 0.10 bits per pixel (bpp).
We imagine that a database of kernels will emerge, much like the human genome project (i.e., http://genomics.energy.gov/) wherein the breadth, depth, magnitude, and replications of the effects of any given kernel might be reported by the international research community in order to build an open-source molecular technology of behavioral influence.
