Development and Preliminary Validation of the Physiological Hyperarousal Scale for Children.

Considerable empirical support exists for the positive affect and negative affect components of the tripartite model of anxiety and depression proposed by L. A. Clark and D. Watson (1991); however, less attention has been paid to the physiological hyperarousal component of the model. The development of the Physiological Hyperarousal Scale for Children (PH-C; J. Laurent, S. J. Catanzaro, & T. E. Joiner Jr., 1995) is described. The psychometric properties of items are examined using students in Grades 6-12 (N = 398). Initial scale validation includes a joint factor analysis with the Positive and Negative Affect Scale for Children (PANAS-C; J. Laurent et al., 1999; J. Laurent, K. Potter, & S. J. Catanzaro, 1994). The relationship between the PH-C and existing measures that tap related constructs is examined. Together, the PH-C and PANAS-C provide a means to assess tripartite model constructs useful in differentiating anxiety and depression. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

On the dimensionality of multi-view hyperspectral measurements of vegetation

This note investigates the structure of two data sets of highly resolved directional-reflectance of vegetation canopies, obtained with a spectroradiometer mounted on a goniometer. One canopy was a grass lawn (largely erectophile) and the other was of watercress (largely planophile). The data sets consist of radiance measurements in 356 spectral bands in visible and near-infrared wavelengths, and in either 61 or 358 different directions, but avoiding directions very close to the hot-spot. The singular value decompositions of the two-dimensional data sets are used to investigate their intrinsic dimensionality, and so also the redundancy contained in the data. A single directional function and a single spectral function together fit the data quite well in a least squares sense, with the root mean square residual amounting to one part in a hundred of the total sum of squares of the data. However, the residuals indicate that one or two further pairs of functions are needed to characterize the systematic variation of spectral reflectance with direction (or equivalently, of the angular reflectance distribution with wavelength). Three such pairs of functions are found to fit the data to better than one part in a thousand, with the residuals then showing no systematic structure. The consequences for atmospheric correction of multi-view remote sensing data are discussed.     

The effect of anisotropic reflectance on imaging spectroscopy of snow properties

How does snow's anisotropic directional reflectance affect the mapping of snow properties from imaging spectrometer data? This sensitivity study applies two spectroscopy models to synthetic images of the spectral hemispherical-directional reflectance factor (HDRF) with prescribed snow-covered area and snow grain size. The MEMSCAG model determines both sub-pixel snow-covered area and the grain size of the fractional snow cover. The Nolin/Dozier model analyzes the ice absorption feature that spans wavelength λ≅1.03 μm to estimate snow grain radius when the pixel is fully snow-covered. Retrievals of subpixel snow-covered area with MEMSCAG are progressively more sensitive to the HDRF as grain size decreases, solar zenith angle increases, and fractional snow cover increases. The model overestimates snow cover in the forward reflectance angles by up to +20% and underestimates it in the backward reflectance angles by as much as −15%. Grain size retrievals from both MEMSCAG and Nolin/Dozier are more sensitive to anisotropy as grain size and solar zenith angle increase. MEMSCAG retrievals of grain size are insensitive to snow-covered area. The largest inferred grain sizes occur around a peak in the backward reflectance angles and the smallest generally occur at the largest view angles in the forward direction. Retrievals of albedo from MEMSCAG and Nolin/Dozier are similarly sensitive to anisotropy, with albedo errors up to 5% for a 30° solar zenith angle and up to 10% at 60°. The albedo differences between the two models are less than 0.015 for all grain sizes and solar zenith angles.     

Does Kripke’s Argument Against Functionalism Undermine the Standard View of What Computers Are?

Kripke’s argument against functionalism extended to physical computers poses a deep philosophical problem (not previously addressed in the literature) for understanding the standard view of what computers are. The problem puts into jeopardy the definition in the standard view that computers are physical machines for performing physical computations. Indeed, it is entirely possible that, unless this philosophical problem is resolved, we will never have a good understanding of computers and may never know just what they are.     

Efficient and scalable omniscient debugging for model transformations

This paper discusses a technique for supporting omniscient debugging for model transformations, which are used to define core operations on software and system models. Similar to software systems developed using general-purpose languages, model transformations are also subject to human error and may possess defects. Existing model-driven engineering tools provide stepwise execution to aid developers in locating and removing defects. In this paper, we describe our investigation into a technique and associated algorithms that support omniscient debugging features for model transformations. Omniscient debugging enables enhanced navigation and exploration features during a debugging session beyond those possible in a strictly stepwise execution environment. Finally, the execution time performance is comparatively evaluated against stepwise execution, and the scalability (in terms of memory usage) is empirically investigated.