This paper describes the concepts of Strictly Positive Definite, Universal, Integrally C0-Universal for Gaussian kernel on a Hilbert space. As consequence we obtain similar characterization an important family kernels studied and developed by Schoenberg also spatial-time popular in geostatistics, Gneiting class, its generalizations. Either using techniques, or direct spaces, characterize same d...

This study aimed to extend the shelf life of walnut kernels by appropriate packaging conditions and physical methods. For this purpose, the kernels were heated at 50 or 70°C for 2 or 10 minutes. About 100g of walnuts were packed in low-density polyethylene (LDPE) packages under ordinary, vacuum or nitrogen conditions. Samples were stored for 18 months at room temperature. Peroxide value and aci...

Kernel methods are widely used in statistical learning techniques. We recently introduced a general kernel framework based on weighted transducers or rational relations, rational kernels, to extend kernel methods to the analysis of variable-length sequences or more generally weighted automata. These kernels are efficient to compute and have been successfully used in applications such as spoken-...

The present study describes the in vitro antimicrobial and antioxidant activity of methanol and water extracts of sweet and bitter apricot (Prunus armeniaca L.) kernels. The antioxidant properties of apricot kernels were evaluated by determining radical scavenging power, lipid peroxidation inhibition activity and total phenol content measured with a DPPH test, the thiocyanate method and the Fol...

Among 500 barley kernels, tested singly, 1.8% (9 kernels) were positive for fecal streptococci. Among 800 malt kernels, tested singly by the same procedure, 68% (540 kernels) were positive for fecal streptococci. In unsulfured and sulfured malts, 67 and 68% of the kernels, respectively, were positive for these bacteria. Fecal streptococci were also isolated by an enrichment procedure from two b...

Non-linear kernel methods can be approximated by fast linear ones using suitable explicit feature maps allowing their application to large scale problems. To this end, explicit feature maps of kernels for vectorial data have been extensively studied. As many real-world data is structured, various kernels for complex data like graphs have been proposed. Indeed, many of them directly compute feat...

We consider the design of kernels for time-frequency distributions through the phase, rather than amplitude, response. While phase kernels do not attenuate troublesome crosscomponents, they can translate them in the time-frequency plane. In contrast to previous work on phase kernels that concentrated on placing the cross-components on top of the auto-components, we set up a “don’t care” region ...

Computational units induced by convolutional kernels together with biologically inspired perceptrons belong to the most widespread types of units used in neurocomputing. Radial convolutional kernels with varying widths form RBF (radial-basis-function) networks and these kernels with fixed widths are used in the SVM (support vector machine) algorithm. We investigate suitability of various convol...

To help understand various reproducing kernels used in applied sciences, we investigate the inclusion relation of two reproducing kernel Hilbert spaces. Characterizations in terms of feature maps of the corresponding reproducing kernels are established. A full table of inclusion relations among widely-used translation invariant kernels is given. Concrete examples for Hilbert-Schmidt kernels are...