Multivariate Modeling of Age and Retest in Longitudinal Studies of Cognitive Abilities.

Longitudinal multivariate mixed models were used to examine the correlates of change between memory and processing speed and the contribution of age and retest to such change correlates. Various age- and occasion-mixed models were fitted to 2 longitudinal data sets of adult individuals (N > 1,200). For both data sets, the results indicated that the correlation between the age slopes of memory and processing speed decreased when retest effects were included in the model. If retest effects existed in the data but were not modeled, the correlation between the age slopes was positively biased. The authors suggest that although the changes in memory and processing speed may be correlated over time, age alone does not capture such a covariation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Frame-rate spatial referencing based on invariant indexing and alignment with application to online retinal image registration

This paper describes an algorithm to continually and accurately estimate the absolute location of a diagnostic or surgical tool (such as a laser) pointed at the human retina, from a series of image frames. We treat the problem as a registration problem using diagnostic images to build a spatial map of the retina and then registering each online image against this map. Since the image location where the laser strikes the retina is easily found, this registration determines the position of the laser in the global coordinate system defined by the spatial map. For each online image, the algorithm computes similarity invariants, locally valid despite the curved nature of the retina, from constellations of vascular landmarks. These are detected using a high-speed algorithm that iteratively traces the blood vessel structure. Invariant indexing establishes initial correspondences between landmarks from the online image and landmarks stored in the spatial map. Robust alignment and verification steps extend the similarity transformation computed from these initial correspondences to a global, high-order transformation. In initial experimentation, the method has achieved 100 percent success on 1024 /spl times/ 1024 retina images. With a version of the tracing algorithm optimized for speed on 512 /spl times/ 512 images, the computation time is only 51 milliseconds per image on a 900MHz PentiumIII processor and a 97 percent success rate is achieved. The median registration error in either case is about 1 pixel.     

Fast horizon computation at all points of a terrain with visibilityand shading applications

A terrain is most often represented with a digital elevation map consisting of a set of sample points from the terrain surface. This paper presents a fast and practical algorithm to compute the horizon, or skyline, at all sample points of a terrain. The horizons are useful in a number of applications, including the rendering of self-shadowing displacement maps, visibility culling for faster flight simulation, and rendering of cartographic data. Experimental and theoretical results are presented which show that the algorithm is more accurate that previous algorithms and is faster than previous algorithms in terrains of more than 100,000 sample points     

Positive Versions of Polynomial Time

We show that restricting a number of characterizations of the complexity classPto be positive (in natural ways) results in the same class of (monotone) problems, which we denote byposP. By a well-known result of Razborov,posPis a proper subclass of the class of monotone problems inP. We exhibit complete problems forposPvia weak logical reductions, as we do for other logically defined classes of problems. Our work is a continuation of research undertaken by Grigni and Sipser, and subsequently Stewart; indeed, we introduce the notion of a positive deterministic Turing machine and consequently solve a problem posed by Grigni and Sipser.     

Mood-Induced Increases in Alcohol Expectancy Strength in Internally Motivated Drinkers.

This study investigated whether exposure to musical mood induction procedures (MMIP) differentially increases the strength of specific alcohol expectancies for coping motivated (CM) versus enhancement motivated (EM) drinkers. Participants were 86 undergraduates who had elevated scores on either the CM or EM subscale of the Drinking Motives Questionnaire (M. L. Cooper, 1994). Participants were randomly assigned to either a positive or negative mood condition. The Alcohol Craving Questionnaire (E. G. Singleton, S. T. Tiffany, & J. E. Henningfield, 1994) was administered at baseline and after MMIP to assess phasic changes in alcohol expectancy strength. Consistent with hypotheses, only CM drinkers in the negative mood condition reported increased relief expectancies, and only EM drinkers in the positive mood condition reported increased reward expectancies. Theoretical and clinical implications are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Comparison of the wear resistance of various grades of cemented carbides that may find application in wood machining

A laboratory test is described in which specimens of rectangular cemented carbide tool inserts of a standard size are allowed to slide against a rapidly rotating fiberboard disc in either the presence or the absence of a mist spray of a dilute organic acid (tannic acid or acetic acid) to simulate the cutting of green wood and cured wood respectively. It is shown that the worn surfaces of cemented carbide tools used in (field) service are remarkably similar to the worn surfaces of specimens used in the laboratory (simulation) tests.Extensive results are presented that show quantitatively the progressive wear of a wide range of cemented carbides as a function of time for sliding under wet and dry conditions. It is shown that wear depends on the type and amount of binder present in the cemented carbide and on the nature of the environment. Materials with Co-Cr and Ni-Cr binders containing significant amounts of chromium showed the greatest resistance to wear.     

Investigating the Financial Implications and Viability of Diversified Water Supply Systems in an Urban Water Supply Zone

Water Resources Management - Diversified water supply schemes can reduce both peak demand and overall demand in the urban water supply network. Consequently, they provide benefits to both the water...     

Case-base maintenance with multi-objective evolutionary algorithms

Case-Base Reasoning is a problem-solving methodology that uses old solved problems, called cases, to solve new problems. The case-base is the knowledge source where the cases are stored, and the amount of stored cases is critical to the problem-solving ability of the Case-Base Reasoning system. However, when the case-base has many cases, then performance problems arise due to the time needed to find those similar cases to the input problem. At this point, Case-Base Maintenance algorithms can be used to reduce the number of cases and maintain the accuracy of the Case-Base Reasoning system at the same time. Whereas Case-Base Maintenance algorithms typically use a particular heuristic to remove (or select) cases from the case-base, the resulting maintained case-base relies on the proportion of redundant and noisy cases that are present in the case-base, among other factors. That is, a particular Case-Base Maintenance algorithm is suitable for certain types of case-bases that share some indicators, such as redundancy and noise levels. In the present work, we consider Case-Base Maintenance as a multi-objective optimization problem, which is solved with a Multi-Objective Evolutionary Algorithm. To this end, a fitness function is introduced to measure three different objectives based on the Complexity Profile model. Our hypothesis is that the Multi-Objective Evolutionary Algorithm performing Case-Base Maintenance may be used in a wider set of case-bases, achieving a good balance between the reduction of cases and the problem-solving ability of the Case-Based Reasoning system. Finally, from a set of the experiments, our proposed Multi-Objective Evolutionary Algorithm performing Case-Base Maintenance shows regularly good results with different sets of case-bases with different proportion of redundant and noisy cases.