Use of decision trees in colour feature selection: application to object recognition in outdoor scenes

A new method for the automated selection of colour features is described. The algorithm consists of two stages of processing. In the first, a complete set of colour features is calculated for every object of interest in an image. In the second stage, each object is mapped into several n-dimensional feature spaces in order to select the feature set with the smallest variables able to discriminate the remaining objects. The evaluation of the discrimination power for each concrete subset of features is performed by means of decision trees composed of linear discrimination functions. This method can provide valuable help in outdoor scene analysis where no colour space has been demonstrated as being the most suitable. Experiment results recognizing objects in outdoor scenes are reported

Monocular-based 3-D seafloor reconstruction and ortho-mosaicing by piecewise planar representation

Photo-mosaicing techniques have become popular for seafloor mapping in various marine science applications. However, the common methods cannot accurately map regions with high relief and topographical variations. Ortho-mosaicing borrowed from photogrammetry is an alternative technique that enables taking into account the 3-D shape of the terrain. A serious bottleneck is the volume of elevation information that needs to be estimated from the video data, fused, and processed for the generation of a composite ortho-photo that covers a relatively large seafloor area. We present a framework that combines the advantages of dense depth-map and 3-D feature estimation techniques based on visual motion cues. The main goal is to identify and reconstruct certain key terrain feature points that adequately represent the surface with minimal complexity in the form of piecewise planar patches. The proposed implementation utilizes local depth maps for feature selection, while tracking over several views enables 3-D reconstruction by bundle adjustment. Experimental results with synthetic and real data validate the effectiveness of the proposed approach

Finite field treatment of vibrational polarizabilities and hyperpolarizabilities: on the role of the Eckart conditions, their implementation, and their use in characterizing key vibrations

In the finite field (FF) treatment of vibrational polarizabilities and hyperpolarizabilities, the field-free Eckart conditions must be enforced in order to prevent molecular reorientation during geometry optimization. These conditions are implemented for the first time. Our procedure facilities identification of field-induced internal coordinates that make the major contribution to the vibrational properties. Using only two of these coordinates, quantitative accuracy for nuclear relaxation polarizabilities and hyperpolarizabilities is achieved in π-conjugated systems. From these two coordinates a single most efficient natural conjugation coordinate (NCC) can be extracted. The limitations of this one coordinate approach are discussed. It is shown that the Eckart conditions can lead to an isotope effect that is comparable to the isotope effect on zero-point vibrational averaging, but with a different mass-dependence

Key competences in the new ventures: a model for evaluating

This research studies from an internal view based on the Competency-Based Perspective (CBP), key organizational competencies developed for small new business. CBP is chosen in an attempt to explain the differences characterizing the closed companies from the consolidated ones. The main contribution of this paper is the definition of a set of key organizational competencies for new ventures from services and low technology based sectors. Using the classification proposed by [1] and a review of the entrepreneurship literature, the main competencies were defined and classified as: managerial, input-based, transformation-based, and output-based competencies. The proposed model for evaluating new ventures organizational competence is tested by means of Structural Equation

Biofilm formation as a novel phenotypic feature of adherent-invasive Escherichia coli (AIEC)

Crohn's disease (CD) is a high morbidity chronic inflammatory disorder of unknown aetiology. Adherent-invasive Escherichia coli (AIEC) has been recently implicated in the origin and perpetuation of CD. Because bacterial biofilms in the gut mucosa are suspected to play a role in CD and biofilm formation is a feature of certain pathogenic E. coli strains, we compared the biofilmformation capacity of 27 AIEC and 38 non-AIEC strains isolated from the intestinal mucosa. Biofilmformation capacity was then contrasted with the AIEC phenotype, the serotype, the phylotype, andthe presence of virulence genes. Results: Specific biofilm formation (SBF) indices were higher amongst AIEC than non-AIEC strains(P = 0.012). In addition, 65.4% of moderate to strong biofilms producers were AIEC, whereas74.4% of weak biofilm producers were non-AIEC (P = 0.002). These data indicate that AIEC strainswere more efficient biofilm producers than non-AIEC strains. Moreover, adhesion (P = 0.009) andinvasion (P = 0.003) indices correlated positively with higher SBF indices. Additionally, motility(100%, P < 0.001), H1 type flagellin (53.8%, P < 0.001), serogroups O83 (19.2%, P = 0.008) and O22(26.9%, P = 0.001), the presence of virulence genes such as sfa/focDE (38.5%, P = 0.003) and ibeA(26.9%, P = 0.017), and B2 phylotype (80.8%, P < 0.001) were frequent characteristics amongstbiofilm producers.Conclusion: The principal contribution of the present work is the finding that biofilm formationcapacity is a novel, complementary pathogenic feature of the recently described AIEC pathovar. Characterization of AIEC specific genetic determinants, and the regulatory pathways, involved in biofilm formation will likely bring new insights into AIEC pathogenesis