Exploring the spatial distribution of variation in plant secondary metabolites is critical for understanding the evolutionary ecology of biochemical diversity in wild organisms. In the present study, concentrations of foliar sideroxylonal, an important and highly heritable defense chemical of Eucalyptus melliodora, displayed strong, fine-scale spatial autocorrelation. The spatial patterns obser...

Most spatial data in GIS are not independent, they have high autocorrelation. For example, temperatures of nearby locations are often related. Most of the spatial association rule mining algorithms derived from the attribute association rule mining algorithms which assume that spatial data is independent. In these situations, the rules or knowledge derived from spatial mining will be wrong. It ...

The transition state wave packet ~TSWP! approach to the thermal rate constant based on the flux-flux autocorrelation function is used to investigate the diffusion dynamics of an H atom on the Cu~100! surface in the uncorrelated hopping regime. The high efficiency of the approach makes it feasible to include up to eight Cu modes explicitly in the time dependent quantum simulation. This is necess...

Information on the spatial relationships between disease vectors and environmental factors is fundamental to vector-borne disease control. Although it is well known that mosquito abundance is associated with the amount of rainfall and thus the number of larval breeding sites, the spatial relationship between larval habitat availability and adult mosquito abundance is not clear. We investigated ...

An autocorrelation measurement of femtosecond laser pulse duration using the Kerr-lens mechanism is demonstrated. This technique can also be used as a sensitive and absolutely calibratable method for measuring ultrafast optical nonlinearities. A method that uses an electronic spectral-filtering scheme is proposed for determining the frequency chirp of pulses by interferometric autocorrelation.

This paper presents an efficient and homogeneous paradigm for automatic acquisition and recognition of nonparametric shapes. Acquisition time varies from linear to cubic in the number of object features. Recognition time is linear to cubic in the number of features in the image and grows slowly with the number of stored models. Nonparametric shape representation is achieved by spatial autocorre...

EXt = μ Cov(Xt, Xt−k) = γk (lag-k autocovariance). The lag zero autocovariance γ0 is just the variance of the time series. γk’s are of central importance in time series analysis as they characterize the serial dependence over observations (i.e. over time). We usually do not have iid data in time series contexts. A white noise series is stationary. A white noise (WN) series is defined as an unco...

Judgmental detection of changes in time series is an ubiquitous task. Previous research has shown that human observers are often relatively poor at detecting change, especially when the series are serially dependent (autocorrelated). We present two experiments in which participants were asked to judge the occurrence of changes in time series with varying levels of autocorrelation. Results show ...

I examined the degree to which population sizes of North American wintering birds exhibit spatial synchrony (autocorrelation) and local disappearances based on 30 yr of Christmas Bird Counts. The primary goal of these analyses was to determine whether processes expected in metapopulations, including low spatial synchrony, frequent local disappearances, and colonization leading to population res...