Shape estimation from topographic primal sketch

In this paper, a technique for estimating object shape from topographic primal sketch is investigated. Given a gray tone image of a three-dimensional object, a topographic labeling of the image indicates the peaks and pits, ridges and valleys, and flats and hillsides of the underlying, continuous, gray tone surface. The patterns of these topographic labels capture information about the original three-dimensional object in the scene and about the illumination. In order to determine if estimation of three-dimensional shape from a topographic labeling is feasible, we have both analytically and experimentally determined the topographic labelings for images of some mathematically generated surfaces with varied directions of illumination. Our results indicate that such patterns do exist and will be useful in determining three-dimensional shape from two-dimensional images. A scheme for partial classification of three-dimensional object surface is proposed. Preliminary results are illustrated.     

Personality trait structure as a human universal.

Patterns of covariation among personality traits in English-speaking populations can be summarized by the five-factor model (FFM). To assess the cross-cultural generalizability of the FFM, data from studies using 6 translations of the Revised NEO Personality Inventory (P. T. Costa & R. R. McCrae, 1992) were compared with the American factor structure. German, Portuguese, Hebrew, Chinese, Korean, and Japanese samples (N?=?7,134) showed similar structures after varimax rotation of 5 factors. When targeted rotations were used, the American factor structure was closely reproduced, even at the level of secondary loadings. Because the samples studied represented highly diverse cultures with languages from 5 distinct language families, these data strongly suggest that personality trait structure is universal. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Energy use in Minnesota State-owned facilities

This paper describes and analyzes the contents of a large data base containing information on monthly energy use at state-owned facilities in Minnesota. The data base, managed by the State Department of Administration, includes information on 42 community colleges, state universities, hospitals, prisons, and the St. Paul Capitol Complex. The data span a seven year period (1972 – 1978) and include about 3,500 observations.Several data base management issues are discussed. These include errors and their correction, development of simple and consistent definitions for key terms, and collection of information on key determinants of energy use at these facilities.Total annual energy use at these 42 institutions averaged 245 kBtu/ft² (2.78 GJ/m²) for 1978. Fossil fuels accounted for 56% of this total; electricity accounted for the remainder. Energy use at the Capitol Complex, hospitals and prisons was higher than average.Regression equations were developed to predict monthly heating fuel use and total energy use. These equations show that more than 60% of the variation in energy use per unit floorspace can be explained by a few variables: heating degree days; electricity and fossil fuel prices; number of buildings; number of boilers; facility age; and whether or not the facility is all electric.     

Subbottom Acoustic Impedance Profiles from Magnitude And Phase Analysis of Echoes

A method for analyzing subbottom echoes is presented using both magnitude and phase analysis. Previous analysis have used only the magnitude of the signal as definitive phase information was not available as the targets insonated were always smaller than the beam size [7], [8]. However, more than half the information is contained in the phase of the signal, which can be obtained from high resolution pencil-point beams. These techniques which have been extensively used in radio and radar sounding of the ionosphere have been applied in this paper in the analysis of sonar sounding of a lake subbottom.     

Calculated Contribution of Surface Microlayer PCB to Contamination of Lake Michigan Lake Trout

The possible significance of PCB concentration in the surface microlayer of Lake Michigan to contamination of lake trout was examined using a modification of a previously developed food chain model. Vertically migrating zooplankton were assumed to spend a fraction of each day exposed to a surface microlayer with dissolved and phytoplankton PCB concentrations at values that resulted in an average exposure concentration 2.1 times greater than subsurface levels. Considering a worst case scenario, the model indicated that approximately 12% (3 μg/g) of the PCB concentration in adult lake trout could be contributed from the microlayer.     

A new psychodiagnostic tool for clients in rehabilitation settings: The MBHI.

The Millon Behavioral Health Inventory (MBHI), a 150-item self-report inventory, may provide measures relevant to the client's psychological outlook and prognosis. It also appears useful as a guide for treatment planning and psychological counseling. The rationale, development, and uses of the MBHI are briefly described, and the focus of each of the instrument's 20 scales is outlined. (45 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Predicting Variability in a Lake Ontario Phosphorus Model

The prediction of a model always has a degree of uncertainty. Because the level of uncertainty is inversely related to the value of information contained in the prediction, there is a need to quantify the uncertainty. One approach to estimate prediction uncertainty is first-order error analysis. In this method, the error in a characteristic (variable or parameter) is defined by its first nonzero moment (the variance). Errors are propagated through the model using first-order terms in the Taylor series, and the variances are then combined to yield the total prediction uncertainty. An alternative approach to model prediction error analysis is Monte Carlo simulation. In this technique, probability density functions are assigned to each characteristic (variable or parameter), reflecting the uncertainty in that characteristic. Then, values are randomly selected from the distribution for each term and inserted into the model, to calculate a prediction. Repeating this process a number of times produces a distribution of predicted values, which reflects the combined uncertainties. These two approaches (first-order error analysis and Monte Carlo simulation) are applied to Lake Ontario data using a steady state mass balance phosphorus model. Comparisons are made which suggest guidelines for the use of each.     

Stress activated Raman scattering and microcrack detection

A new technique for the detection of microcrack precursors and for the study of the dynamics of crack propagation is proposed. The technique uses laser Raman scattering off of adsorbed surface species to detect microcrack precursors via variations in the Raman spectrum associated with the stresses localized within such precursors. We give extensive theoretical justification and detail several approaches designed to substantiate the plausability of the technique proposed. This technique can become a valuable tool for the detection of microcrack precursors as well as studies of phenomena including adsorption, catalysis. adhesion, wear and the dynamics of stress-corrosion cracking.