Abilities, motives, and personal styles: Reply.

Responds to the comments of P. L. Ackerman (see record 2006-12925-012), D. Y. Dai (see record 2006-12925-013), and M. C. Gridley (see record 2006-12925-014) on E. S. Spelke's original article "Sex differences in intrinsic aptitude for mathematics and science? A critical review" (see record 2005-15840-001). Here, the current authors first consider Ackerman's criticism of IQ measures of cognitive sex differences, as well as his suggestion that Advanced Placement tests be used as a second measure. Next, the authors discuss Dai's suggestion that cognition and motivation, abilities and strategies, are inseparably bound in any meaningful measure of aptitude for mathematics and science. Finally, the authors address Gridley's suggestion that differences in men's and women's thinking styles and preferences explain gender disparities in math and science fields. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Job Allocation Strategies with User Run Time Estimates for Online Scheduling in Hierarchical Grids

We address non-preemptive non-clairvoyant online scheduling of parallel jobs on a Grid. We consider a Grid scheduling model with two stages. At the first stage, jobs are allocated to a suitable Grid site, while at the second stage, local scheduling is independently applied to each site. We analyze allocation strategies depending on the type and amount of information they require. We conduct a comprehensive performance evaluation study using simulation and demonstrate that our strategies perform well with respect to several metrics that reflect both user- and system-centric goals. Unfortunately, user run time estimates and information on local schedules does not help to significantly improve the outcome of the allocation strategies. When examining the overall Grid performance based on real data, we determined that an appropriate distribution of job processor requirements over the Grid has a higher performance than an allocation of jobs based on user run time estimates and information on local schedules. In general, our experiments showed that rather simple schedulers with minimal information requirements can provide a good performance.     

Multi-agent Physical A* with Large Pheromones

Physical A* (PHA*) and its multi-agent version MAPHA* are algorithms that find the shortest path between two points in an unknown real physical environment with one or many mobile agents [A. Felner et al. Journal of Artificial Intelligence Research, 21:631–679, 2004; A. Felner et al. Proceedings of the First International Joint Conference on Autonomous Agents and Multi-Agent Systems, Bologna, Italy, 2002:240–247]. Previous work assumed a complete sharing of knowledge between agents. Here we apply this algorithm to a more restricted model of communication which we call large pheromones, where agents communicate by writing and reading data at nodes of the graph that constitutes their environment. Previous works on pheromones usually assumed that only a limited amount of data can be written at each node. The large pheromones model assumes no limitation on the size of the pheromones and thus each agent can write its entire knowledge at a node. We show that with this model of communication the behavior of a multi-agent system is almost as good as with complete knowledge sharing. Under this model we also introduce a new type of agent, a communication agent, that is responsible for spreading the knowledge among other agents by moving around the graph and copying pheromones. Experimental results show that the contribution of communication agents is rather limited as data is already spread to other agents very well with large pheromones     

Developmental Psychology and Public Policy: Progress and Prospects.

This article outlines a framework for developmentally oriented policy research. Drawing from U. Bronfenbrenner's (1995) dynamic developmental systems theory, the authors suggest ways in which the key tenets of process, persons, context, and time can inform policy research in developmental psychology and can be used to support a causal interpretation of the results of those analyses. Conceptualizing public policies from a dynamic developmental systems perspective has a variety of implications for future research, and this article considers some of these implications. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Quality enhancements of digital outline fonts

Digital fonts are easily available today and their use has become widespread. Nevertheless, the visual quality of printed and displayed text and the technical quality of digital typefaces are often unsatisfactory. The foremost reason for this situation is that font manufacturing systems manipulate font representations through low-level operations. In this paper we examine several aspects of font quality, and present a method for enhancing the quality of a typeface given in today's standard representation, the outline (boundary) representation. The method is based on the usage of high-level typographic features, and includes enhancements to both individual glyphs and complete fonts. Glyph enhancements include elimination of redundant points, insertion of essential points, corrections to contour orientations and inter-penetrations, and vertical and horizontal coherence. Font enhancements include regularization of font weights and sizes, serif unification, and feature extraction and discrimination. Our method is comprised of several algorithms that have been implemented in a commercial font manufacturing system, achieving enhanced quality of the fonts produced.     

Duality in permutation state spaces and the dual search algorithm

Geometrical symmetries are commonly exploited to improve the efficiency of search algorithms. A new type of symmetry in permutation state spaces, duality, is introduced. Each state has a dual state. Both states share important attributes such as their distance to the goal. Given a state S, it is shown that an admissible heuristic of the dual state of S is an admissible heuristic for S. This provides opportunities for additional heuristic evaluations. An exact definition of the class of problems where duality exists is provided. A new search algorithm, dual search, is presented which switches between the original state and the dual state when it seems likely that the switch will improve the chance of reaching the goal faster. The decision of when to switch is very important and several policies for doing this are investigated. Experimental results show significant improvements for a number of applications, for using the dual state's heuristic evaluation and/or dual search.     

A Part-aware Surface Metric for Shape Analysis

The notion of parts in a shape plays an important role in many geometry problems, including segmentation, correspondence, recognition, editing, and animation. As the fundamental geometric representation of 3D objects in computer graphics is surface-based, solutions of many such problems utilize a surface metric, a distance function defined over pairs of points on the surface, to assist shape analysis and understanding. The main contribution of our work is to bring together these two fundamental concepts: shape parts and surface metric. Specifically, we develop a surface metric that is part-aware. To encode part information at a point on a shape, we model its volumetric context – called the volumetric shape image (VSI) – inside the shape's enclosed volume, to capture relevant visibility information. We then define the part-aware metric by combining an appropriate VSI distance with geodesic distance and normal variation. We show how the volumetric view on part separation addresses certain limitations of the surface view, which relies on concavity measures over a surface as implied by the well-known minima rule. We demonstrate how the new metric can be effectively utilized in various applications including mesh segmentation, shape registration, part-aware sampling and shape retrieval.     

The rise and fall of word retrieval across the lifespan.

Picture-naming performance for 48 black-and-white drawings was investigated in 1,145 Hebrew speakers, ages 5–86. Both a linear and a curvilinear quadratic model fit the data, reflecting an increase in ability with age as well as an increase followed by a decrease beyond that linear rise. Late-life performance was more affected by access difficulty than was early-life performance, with children's responses limited by lexicon size. Immigrants performed more poorly than nonimmigrants, but an identical correlation between participant age and naming scores was found in both groups. We discuss the role of vocabulary funds and controlled access in naming pictures throughout life. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Learning Explicit Smoothing Kernels for Joint Image Filtering

Smoothing noises while preserving strong edges in images is an important problem in image processing. Image smoothing filters can be either explicit (based on local weighted average) or implicit (based on global optimization). Implicit methods are usually time‐consuming and cannot be applied to joint image filtering tasks, i.e., leveraging the structural information of a guidance image to filter a target image. Previous deep learning based image smoothing filters are all implicit and unavailable for joint filtering. In this paper, we propose to learn explicit guidance feature maps as well as offset maps from the guidance image and smoothing parameter that can be utilized to smooth the input itself or to filter images in other target domains. We design a deep convolutional neural network consisting of a fully‐convolution block for guidance and offset maps extraction together with a stacked spatially varying deformable convolution block for joint image filtering. Our models can approximate several representative image smoothing filters with high accuracy comparable to state‐of‐the‐art methods, and serve as general tools for other joint image filtering tasks, such as color interpolation, depth map upsampling, saliency map upsampling, flash/non‐flash image denoising and RGB/NIR image denoising.