The Pool Critical Assembly Pressure Vessel (PCA) benchmark is a well known in the reactor shielding community which described Shielding Integral Benchmark Archive and Database (SINBAD). It based on experiments performed at PCA facility Oak Ridge National Laboratory (ORNL) it can be used for qualification of pressure vessel fluence calculational methodology. measured quantities to compared again...

In face recognition, Principal Component Analysis (PCA) is often used to extract a low dimensional face representation based on the eigenvector of the face image autocorrelation matrix. Kernel Principal Component Analysis (Kernel PCA) has recently been proposed as a non-linear extension of PCA. While PCA is able to discover and represent linearly embedded manifolds, Kernel PCA can extract low d...

linear–dendrite copolymers containing hyper branched poly(citric acid) and linear poly(ethylene glycol) blocks pca–peg–pca are promising nonmaterial to use  in nanomedicine. to investigate their potential application in biological systems (especially for drug carries) oniom2 calculations were applied to study the nature of particular interactions between drug and the polymeric nanoparticles.  b...

Principal Components Analysis (PCA), which is more recently referred to as Proper Orthogonal Decomposition (POD) in the literature, is a popular technique in many fields of engineering, science, and mathematics. The benefit of PCA for dynamical systems comes from its ability to detect and rank the dominant coherent spatial structures of dynamic response, such as operating deflection shapes or m...

remotely sensed imagery is proving to be a useful tool to estimate water depths in coastalzones. bathymetric algorithms attempt to isolate water attenuation and hence depth from other factors byusing different combinations of spectral bands. in this research, images of absolute bathymetry using twodifferent but related methods in a region in the southern caspian sea coasts has been produced. th...

frost is one of the atmospheric phenomena which seriously threaten crop production. it also causes numerousaccidents in mountainous roads. in this research the spatial synoptic classification ssc method was employed toclassify the type of air masses. for the classification, such meteorological data as: temperature, dew point, mean sealevel pressure, cloudiness, direction and speed of wind were ...

the analysis of geochemical data in frequency domain, as indicated in this research study, can provide new exploratory informationthat may not be exposed in spatial domain. to identify deep geochemical anomalies, sulfide zone and geochemical noises in dalli cu–au porphyry deposit, a new approach based on coupling fourier transform (ft) and principal component analysis (pca) has beenused. the re...

The aim of this article is to present the potential of Kernel Principal Component Analysis (Kernel PCA) in the field of vision based robot localization. Using Kernel PCA we can extract features from the visual scene of a mobile robot. The analysis is applied only to local features so as to guarantee better computational performance as well as translation invariance. Compared with the classical ...