Youth gambling behaviors: An examination of the role of resilience.

The study of resilient children has overturned many deficit-focused models concerning the ontogenesis of children raised in adversity. This study explored the relationship between risk and protective factors, resilience, and youth gambling behavior. More specifically, this study examined the relative contribution of various risk and protective domains in relation to problem gambling behavior and examined whether youth identified as resilient (high risk exposure- high internalized protection) were as likely as those identified as vulnerable (high risk exposure-low internalized protection) to engage in excessive gambling behavior. The sample consisted of 1,273 students ages 12 to 19. The findings demonstrated that risk and protective factors each provide a unique contribution to the prediction model of gambling problems. Resilient and vulnerable youth differed significantly in their self-reported gambling severity. As well, resilient youth were not statistically distinguishable from low-risk exposure groups in terms of their gambling severity. Findings are interpreted with respect to resilience and prevention research. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Towards a general multi-view registration technique

We present an algorithm that reduces significantly the level of the registration errors between all pairs in a set of range views. This algorithm refines initial estimates of the transformation matrices obtained from either the calibrated acquisition setup or a crude manual alignment. It is an instance of a category of registration algorithms known as iterated closest-point (ICP) algorithms. The algorithm considers the network of views as a whole and minimizes the registration errors of all views simultaneously. This leads to a well-balanced network of views in which the registration errors are equally distributed, an objective not met by previously published ICP algorithms which all process the views sequentially. Experimental results show that this refinement technique improves the calibrated registrations and the quality of the integrated model for complex multi-part objects. In the case of scenes comprising man-made objects of very simple shapes, the basic algorithm faces problems common to all ICP algorithms and so must be extended     

Variation du parametre cristallin de l'oxyde de nickel a l'etat divise

Samples of finely divided NiO, obtained from Ni(OH)₂, showing a continuous variation in porosity and deviation from stoichiometry, have been studied by means of X-Ray diffraction. The pseudo-cubic lattice constant has been measured. The crystallite size and the strain value have been inferred from the line broadening analysis.The crystallite size of the most divided of these samples is about 10 nm. The corresponding strain value is ? = 17.10^?3 and the relative increase of the lattice constant is 4.10^?3 with reference to a standard sample of bulk NiO. The decrease of the lattice parameter and of the strain value and the increase of the crystallite size have been followed as the development of texture proceeds with increasing temperature. The high strain value observed is related to the crystal mosaic structure of NiO. The variation of the lattice constant may be related to the high surface-volume ratio or the non-stoichiometry of NiO.     

Evaluating simulation software for postal service use: techniqueversus perception

This paper describes the methodology developed for the Canada Post Corporation (CPC) to evaluate and select a commercial simulation package to be used for operational and long-term planning. The project consisted of three distinct phases. The objective of the first phase was to investigate the potential applications of simulation in the CPC environment. A benefit cost analysis was conducted for this purpose. The phase two objective was to benchmark the existing software and to make a recommendation. The accompanying effort is presented herein. The final phase was aimed at developing a complete facility model to serve as a template for the 22 mechanized mail processing plants throughout Canada. This work is ongoing     

SPiKeS: Superpixel-Keypoints structure for robust visual tracking

In visual tracking, part-based trackers are attractive since they are robust against occlusion and deformation. However, a part represented by a rectangular patch does not account for the shape of the target, while a superpixel does thanks to its boundary evidence. Nevertheless, tracking superpixels is difficult due to their lack of discriminative power. Therefore, to enable superpixels to be tracked discriminatively as object parts, we propose to enhance them with keypoints. By combining properties of these two features, we build a novel element designated as a Superpixel-Keypoints structure (SPiKeS). Being discriminative, these new object parts can be located efficiently by a simple nearest neighbor matching process. Then, in a tracking process, each match votes for the target’s center to give its location. In addition, the interesting properties of our new feature allows the development of an efficient model update for more robust tracking. According to experimental results, our SPiKeS-based tracker proves to be robust in many challenging scenarios by performing favorably against the state of the art.     

Qualitative part-based models in content-based image retrieval

A qualitative, volumetric part-based model is proposed to improve the categorical invariance and viewpoint invariance in content-based image retrieval, and a novel two-step part-categorization method is presented to build it. The method consists first in transforming parts extracted from a segmented contour primitive map and then categorizing the transformed parts using interpretation rules. The first step allows noisy extracted parts to be transformed to the domain of a simple classifier. The second step computes features of the transformed parts for categorization. Content-based image retrieval experiments using real images of complex multi-part objects confirm that a model built from the categorized parts improves both the categorical invariance and the viewpoint invariance. It does so by directly addressing the fundamental limits of low-level models.     

Object-level structured contour map extraction

A new approach is proposed to extract an object-level structured contour map from the junctions in a 2D image. Local junction structures are paired in order to initialize and globally constrain the contour extraction process. An original optimization method is applied to detect and describe the contours in respect of their inherent shape and structure. Any given contour is described using a proper number of constant-curvature primitives according to the complexity of its shape. The contour map produced is represented as a graph. The characterized contours correspond to the edges of the graph and their topological structure is described by the junctions at the vertices. An elaborated experimental evaluation illustrates the capabilities of the proposed approach in demanding situations.     

Detection and characterization of junctions in a 2D image

A new junction characterization and validation method is proposed. Junction branches of volumetric objects are extracted at interest points in a 2D image, using a topologically constrained grouping process. This is followed by structural validation and position refinement of extracted junctions. An interesting feature of the proposed method is that all types of junctions are described uniformly and extracted using the same generic process. For instance, the size of the interest regions is kept constant despite local variations in contour density and curvature. Validation rate of real junctions is high and most false hypotheses are properly rejected. An experimental evaluation illustrates the capabilities of the proposed method in demanding situations.