Conceptual Interpretation of LOM and its Mapping to Common Sense Ontologies

Peer-reviewed

A Sparse Bayesian Approach for Joint Feature Selection and Classifier Learning

Peer-reviewed

A Forwarding Cooperation Protocol for Plain and Cluster-based Ad Hoc Networks

Peer-reviewed

Collaborative group membership and access control for JXTA

Peer-reviewed

Quality in work and aggregate productivity

We explore the relationship between quality in work and aggregate productivity in regions and sectors. Using recent Spanish aggregate data for the period 2001-2006, we find that quality in work may be an important factor to explain productivity levels in sectors and regions. We use two alternatives definitions of quality in work: one from survey data and the other from a social indicators approach. We also use two different measurements of labour productivity to test the robustness of our results. The estimates are run using a simultaneous equation model for our panel of data, and find important differences between high tech and low tech sectors: a positive relationship between quality in work and productivity in the former case, and a negative relationship in the latter. Consequently, on the one hand we see that quality in work is not only an objective per se, but may also be a production factor able to increase the wealth of regions; on the other hand, at the aggregate level, we may also find that high productivity levels coincide with lower quality in work conditions.

Inventors on the move: tracing inventors’ mobility and its spatial distribution

This paper aims to provide insights into the phenomenon of knowledge flows. We study one of the main mechanisms through which these flows occur, i.e., the mobility of highly-skilled individuals. We focus on the geographical mobility of inventors across European regions. Thus, patent data are used to trace the pattern of inventors’ mobility across european regions, to track down focuses of attraction of talent throughout the continent, and to study their distribution across the space. To do so, we gather information from PCT patent documents and we first match the names which seemed to belong to the same inventor and then we create a new algorithm to decide whether each patent applied for under each name belongs to the same inventor.

Regional economic growth and human capital: the role of overeducation

The paper analyses the link between human capital and regional economic growth in the European Union. Using different indicators of human capital calculated from census microdata, we conclude that the recent economic performance of European regions is associated to an increase in overeducation. In fact, measures of educational mismatch seem to have a stronger connection to regional economic performance than other traditional measures of human capital stocks.

Erwinia amylovora Novel Plasmid pEI70: Complete Sequence, Biogeography, and Role in Aggressiveness in the Fire Blight Phytopathogen

Comparative genomics of several strains of Erwinia amylovora, a plant pathogenic bacterium causal agent of fire blight disease, revealed that its diversity is primarily attributable to the flexible genome comprised of plasmids. We recently identified and sequenced in full a novel 65.8 kb plasmid, called pEI70. Annotation revealed a lack of known virulence-related genes, but found evidence for a unique integrative conjugative element related to that of other plant and human pathogens. Comparative analyses using BLASTN showed that pEI70 is almost entirely included in plasmid pEB102 from E. billingiae, an epiphytic Erwinia of pome fruits, with sequence identities superior to 98%. A duplex PCR assay was developed to survey the prevalence of plasmid pEI70 and also that of pEA29, which had previously been described in several E. amylovora strains. Plasmid pEI70 was found widely dispersed across Europe with frequencies of 5–92%, but it was absent in E. amylovora analyzed populations from outside of Europe. Restriction analysis and hybridization demonstrated that this plasmid was identical in at least 13 strains. Curing E. amylovora strains of pEI70 reduced their aggressiveness on pear, and introducing pEI70 into low-aggressiveness strains lacking this plasmid increased symptoms development in this host. Discovery of this novel plasmid offers new insights into the biogeography, evolution and virulence determinants in E. amylovora

Human Capital Spillovers Productivity and Regional Convergence in Spain

This paper analyses the differential impact of human capital, in terms of different levels of schooling, on regional productivity and convergence. The potential existence of geographical spillovers of human capital is also considered by applying spatial panel data techniques. The empirical analysis of Spanish provinces between 1980 and 2007 confirms the positive impact of human capital on regional productivity and convergence, but reveals no evidence of any positive geographical spillovers of human capital. In fact, in some specifications the spatial lag presented by tertiary studies has a negative effect on the variables under consideration.

A new approach to segmentation based on fusing circumscribed contours, region growing and clustering

One of the major problems in machine vision is the segmentation of images of natural scenes. This paper presents a new proposal for the image segmentation problem which has been based on the integration of edge and region information. The main contours of the scene are detected and used to guide the posterior region growing process. The algorithm places a number of seeds at both sides of a contour allowing stating a set of concurrent growing processes. A previous analysis of the seeds permits to adjust the homogeneity criterion to the regions's characteristics. A new homogeneity criterion based on clustering analysis and convex hull construction is proposed

Active regions for colour texture segmentation integrating region and boundary information

In this paper a colour texture segmentation method, which unifies region and boundary information, is proposed. The algorithm uses a coarse detection of the perceptual (colour and texture) edges of the image to adequately place and initialise a set of active regions. Colour texture of regions is modelled by the conjunction of non-parametric techniques of kernel density estimation (which allow to estimate the colour behaviour) and classical co-occurrence matrix based texture features. Therefore, region information is defined and accurate boundary information can be extracted to guide the segmentation process. Regions concurrently compete for the image pixels in order to segment the whole image taking both information sources into account. Furthermore, experimental results are shown which prove the performance of the proposed method

A new approach to the classification of mammographic masses and normal breast tissue

A new approach to mammographic mass detection is presented in this paper. Although different algorithms have been proposed for such a task, most of them are application dependent. In contrast, our approach makes use of a kindred topic in computer vision adapted to our particular problem. In this sense, we translate the eigenfaces approach for face detection/classification problems to a mass detection. Two different databases were used to show the robustness of the approach. The first one consisted on a set of 160 regions of interest (RoIs) extracted from the MIAS database, being 40 of them with confirmed masses and the rest normal tissue. The second set of RoIs was extracted from the DDSM database, and contained 196 RoIs containing masses and 392 with normal, but suspicious regions. Initial results demonstrate the feasibility of using such approach with performances comparable to other algorithms, with the advantage of being a more general, simple and cost-effective approach

Present and future methodology for the implementation of decision support systems for traffic management

Real-time predictions are an indispensable requirement for traffic management in order to be able to evaluate the effects of different available strategies or policies. The combination of predicting the state of the network and the evaluation of different traffic management strategies in the short term future allows system managers to anticipate the effects of traffic control strategies ahead of time in order to mitigate the effect of congestion. This paper presents the current framework of decision support systems for traffic management based on short and medium-term predictions and includes some reflections on their likely evolution, based on current scientific research and the evolution of the availability of new types of data and their associated methodologies.

Simulating fuel consumption and vehicle emissions in an Australian context

Road transport is a major source of air pollution and greenhouse gas emissions around the world. There is an increasing interest in accurate information on local vehicle emission levels for policy development and sustainable traffic management. Previous studies have shown that emission predictions for the Australian situation need to reflect both the Australian fleet and driving behaviour to avoid unreliable outcomes. This paper discusses a new Australian vehicle emission software (PΔP) and a case-study where traffic simulation software (Aimsun) is combined with PΔP to demonstrate how consistent results can be achieved for the Australian situation. The case-study is an Australian city modelled using the microscopic simulator to generate the required trajectory data of each individual vehicle for the emission model. The simulation results are used in a number of ways: to assess the impacts of urban driving behaviour on fuel consumption, to create maps showing where and when elevated emission levels occur and to compare results with another program (COPERT Australia). The paper will also discuss where further research is required.