The focus of this article is on studying the descriptive proximity of manifolds in images useful in digital image pattern recognition. Extraction of lowdimensional manifolds underlying high-dimensional image data spaces leads to efficient digital image analysis controlled by fewer parameters. The end result of this approach is dimensionality reduction, important for automatic learning in patter...

ions, “Communications of the ACM, vol. 21, no. 5, pp. 401-410, 1978. [59] J. R. Quinlan, “Discovering rules by induction from large collections of examples” In D. Michie, editor, Expert Systems in the Micro-Electronic Age, pp. 168-210. Edinberg University

Subspace analysis methods have gained interest for identifying patterns in subspaces of high-dimensional data. Existing techniques allow to visualize and compare patterns in subspaces. However, many subspace analysis methods produce an abundant amount of patterns, which often remain redundant and are difficult to relate. Creating effective layouts for comparison of subspace patterns remains cha...

Crime pattern analysis (CPA) is the process of analytical reasoning facilitated by an understanding about the nature of an underlying spatial framework that generates crime. For example, law enforcement agencies may seek to identify regions of sudden increase in crime activity, namely, crime outbreaks. Many analytical tools facilitate this reasoning process by providing support for techniques s...

This paper contains a new analysis for the Generalized Pattern Search (GPS) methods of Torczon and Lewis and Torczon. The two novel aspects are that the proofs are much shorter, and they use weaker continuity assumptions. Speciically, under very mild conditions, the method nds an interesting limit point even if the objective function is not continuous and is even extended valued. If the objecti...

A useful discriminant vector for pattern classification is one that maximizes the minimum separation of discriminant function values for two pattern classes. This optimality criterion can prove valuable in many situations because it emphasizes the class elements that are most difficult to classify. A method for computing this discriminant vector by quadratic programming is derived. The resultin...

The present collection is the result of a review process done on the contributions received in response to an open call for a thematic special issue dealing with pattern recognition and crowd analysis. Part of the submitted contributions are significantly extended versions of papers discussed at the first edition of the Workshop on ''Pattern Recognition and Crowd Analysis'' of the, grouping con...

Abstract: The spatial pattern analysis can be used to discover the distribution of people’s behaviors in space. Traditional spatial pattern analysis does not consider the decision making process of human activities. This paper presents two adjusted spatial choice models that include models of decision-making process. These new adjusted spatial choice models are applied to detect the spatial pat...

The analytic approaches used in nutritional epidemiology for dietary pattern analyses share common characteristics with those of genetic epidemiology. In this issue of the Journal, Gorst-Rasmussen et al. (Am J Epidemiol. 2011;173(10):1097-1104) discuss one such approach. Application of methods used in genetic pattern analyses to nutritional epidemiology could prove valuable but raises important...

In this paper an evaluation of BPMN is presented, using the Workflow Patterns as an analysis framework. The analysis provided for BPMN is part of a larger effort aiming at an unbiased and vendor-independent survey of the expressive power of some mainstream modelling languages for process-aware information systems. It is a sequel to an analysis series where languages like BPEL and UML 2.0 A.D we...