It is established that the perceived image contrast is affected by surround luminance. In order to get the same perceived image contrast, the optimum surround compensation ratios for those surround conditions is needed. Much research has been performed for dark, dim, and average surrounds. In this study, a wide range of surround luminance from dark up to 2087 cd/m 2 was considered. Using magnit...

Regression analysis was used to develop a relationship between Landsat 5 Thematic Mapper data and site quality of permanent sample plots. The thermal band (6) produced misleading results, but the ratio of band 4 on 5 showed promise when combined with geological information. Best results were obtained when regression analysis was restricted to ensure that at least one each of the visible (1 to 3...

The long-term goal of the work described here is to develop and test a general methodology for predicting unmeasured river characteristics using a variety of potentially incomplete remotely sensed data sets. Rather than addressing the problem using various geostatistical techniques to interpolate and extrapolate the remotely sensed data, we are developing two physically based techniques, each o...

Say that a cycle C almost contains a cycle C− if every edge except one of C− is an edge of C. Call a graph G strongly pancyclic if every nontriangular cycle C almost contains another cycle C− and every nonspanning cycle C is almost contained in another cycle C. This is equivalent to requiring, in addition, that the sizes of C− and C differ by one from the size of C. Strongly pancyclic graphs ar...

Computational fluid dynamics (CFD) is widely used to predict the indoor thermal environment; however, large time cost represents a significant disadvantage. Several deep learning approaches have been introduced reduce prediction in steady-state predictions, though their feasibility under unsteady ones has yet be investigated. Considering flexibility of multilayer perceptron (MLP) input–output f...

Gaussian processes are rich distributions over functions, which provide a Bayesian nonparametric approach to smoothing and interpolation. We introduce simple closed form kernels that can be used with Gaussian processes to discover patterns and enable extrapolation. These kernels are derived by modelling a spectral density – the Fourier transform of a kernel – with a Gaussian mixture. The propos...