Understanding species richness patterns represents one of the most fundamental problems in ecology. Most research in this area has focused on spatial gradients of species richness, with a smaller area of emphasis dedicated to understanding the temporal dynamics of richness. However, few attempts have been made to understand the linkages between the spatial and temporal patterns related to richn...

A spatial pattern recognition algorithm is proposed to determine root causes of defects on semiconductor wafers by visually identifying regional defect point set patterns. The algorithm classifies defects into either random patterns or regional patterns. Four different types of regional patterns are identified: rings, blobs, lines and arcs. Ring and blob patterns are detected by template matchi...

the study of spatial and temporal changes in climate parameters, is one the most important issues in the world's climate research. study of changes in cloud cover as one of the most important climate parameters is important, because clouds are in top of hydrologic cycle and changes in them make changes in spatial and temporal variations in other climate parameters. in this study, the spati...

In mining exploration it is often desired to predict the occurrence of ore deposits given other geological information, such as the locations of faults. More generally it is of interest to measure the spatial association between two spatial patterns observed in the same survey region. Berman (1986) developed parametric methods for conditional inference about a point process X given another spat...

We present analysis and measurements of the polarization patterns produced by non-collinear superpositions of Laguerre-Gauss spatial modes in orthogonal polarization states, which are known as Poincaré modes. Our findings agree with predictions (I. Freund Opt. Lett. 35, 148-150 (2010)), that superpositions containing a C-point lead to a rotation of the polarization ellipse in 3-dimensions. Here...

[1] We point out the pitfall of using spatial patterns of correlation coefficients obtained from filtered data to infer physical mechanisms. Filtering is often used to emphasize a signal of interest by removing unrelated variability, but it alters subsequent correlation maps when the removed variance contains spatial structure, as is most often the case in geophysical applications. This then re...

S1. RA-SHG data for Sin-Pout and Sin-Sout geometries above and below TΩ S2. Mathematical expressions used for fitting RA-SHG patterns S3. Visualizing the 2/m1 magnetic point group symmetry of the Néel phase S4. Loop-current order in cuprates versus iridates S5. Behavior of hidden order domains under repeated thermal cycles S6. Survey of RA-SHG patterns of Sr2IrO4 across spatial regions S7. Fun...

background: using spatial analysis tools to determine the spatial patterns of china province-level perinatal mortality and using spatial econometric model to examine the impacts of health care resources and different socio-economic factors on perinatal mortality. methods: the global moran’s i index is used to examine whether the spatial autocorrelation exists in selected regions and moran’s i s...