Isabel M. Flores-Parra

National and Regional Analysis of Road Accidents in Spain

Objective: In Spain, the absolute fatality figures decreased almost 50 percent between 1998 and 2009. Despite this great effort, road mortality is still of great concern to political authorities. Further progress requires efficient road safety policy based on an optimal set of measures and targets that consider the initial conditions and characteristics in each region. This study attempts to analyze road accidents in Spain and its provinces in time and space during 1998–2009. Methods: First, we analyzed daily, monthly, and nationwide (NUTS 0) development of road accidents, the correlation between logarithmic transformations of road accidents and territorial and socioeconomic variables, the causality by simple linear regression of road accidents and territorial and socioeconomic variables, and preliminary frequency by fast Fourier transform. Then we analyzed the annual trend in accidents in the Spanish provinces (NUTS 3) and found a correlation between the logarithmic transformations of the mortality rate, fatalities per fatal accident, and accidents resulting in injuries per inhabitant variables and population, population density, gross domestic product (GDP), length of road network, and area. Finally, causality was analyzed by simple linear regression. Results: The most outstanding results were the negative correlation between mortality rate and population density in Spanish provinces, which has increased over time, and that road accidents in Spain have an approximate periodicity of 57 days. Conclusions: The fast Fourier transform analysis of road accident frequency in Spain was useful in identifying the periodic, harmonic components of accidents and casualties. The periodicity observed both for the period 1998–2009 and by year showed that the highest intensity in road accidents was bimonthly, despite the lower number of accidents and casualties in the spectra of amplitude and power and efforts to reduce the intensity and concentration during off-season travel (summer and December). Supplemental materials are available for this article. Go to the publishers online edition of Traffic Injury Prevention to view the supplemental file.

Knowledge Based Modeling of the Design Processes as a Base of Design Tools. Application to the Development of Agricultural Structures

Actual advancements of the design tools for industrial elements include the addition of knowledge based elements to the classic design tools. In this sense, we propose a general design model, which is represented using an extension of CommonKADS, as a framework for the development of design tools for different industrial objects. This model was used developing the latest version of DAMOCIA-Design, a knowledge based design tool of greenhouse structures. One key point of our design framework is using alternative knowledge blocks, which are selected dynamically using an ad-hoc mechanism, assembled using sets of selection criteria associated to the methods.

National road mortality reduction targets under European Union road safety policy: 2011–2020

The European Union (EU) has proposed renewing the target for halving the number of road fatalities in the period 2011–2020. In this paper, a nonlinear distribution method for dynamic fatality reduction targets is applied for the purpose of finding individual national mortality reduction targets for each of the 27 member countries in the EU. Weighting is undertaken for four scenarios based on the following indicators: road mortality rates, fatality rates, fatality risks, and fatality density. Results are presented for four proposals to reduce the number of fatalities in each Member State, based on the original situation of the indicators considered in the study. The results seek to provide policy-makers with a broader vision with regard to the achievement of the goals of EU road safety policy.

Territorial Distribution Proposal for the Biofuel Consumption Target in the Transportation Sector in Accordance with the EU Energy Policy for 2020

AbstractOne of the current targets of European Union (EU) energy policy is to reach at least a 10% share of biofuels in fuel consumed for transportation (petrol and diesel) in 2020. However, it has not been specified how this global target should be distributed among the Member States according to its different starting points and potentials. Therefore, the purpose of this study is to propose a dynamic nonlinear target distribution method for increasing the share of biofuels in fuel consumed for transportation. We applied the proposed distribution based on the following indicators: nonbiofuels in fuel consumed for transportation, nonbiofuels per capita, nonbiofuels per gross domestic product (GDP), and GDP per capita, in the reference year (2005). In addition, a multicriteria analysis was also conducted to weigh the variables in the study. The proposed methodology is innovative, easy-to-use, and attempts to contribute to the political discussion on the importance of territorial weighing of the biofuel con...

Detection of structures using a robust edge detection algorithm with expansion of border windows

Searching specific structures of different scales in digital images, we tested multiple alternatives of a mobile window method, developed starting from an algorithm by Cayula and Cornillon. These alternatives presented an increasing computing cost when detecting meso-structures in complex images. Quality borders required processing a great number of window-threshold pairs, because to detect some structures was required to relax the work conditions (bimodality and cohesion). Our proposal, in this work, is relaxing the conditions but not for all the window-threshold pairs, only to a selected set of windows, those near windows that accomplish strict conditions. We propose a new method that is a combination of the mobile window one, previously used, and the seeded regions approach. In this case, we seed not regions but borders.

Extended Models of Dynamic Selection Using Ontological Elements – Application to Design and Image Analysis Problems

In this work, we present two practical extensions about the integration of knowledge elements into ontologies and the dynamic selection of methods. First, we propose a mechanism to integrate the abstracted methods and other elements of the knowledge model developed for the given problem into an ontology, using them later via a set of adapters or bridges. Second, as we detected the recurrence of some complex patterns of selection, we propose some extensions of the basic selection mechanism, in order to simplify the notation and the treatment; these new selection processes are transferred to an external layer (called meta-application). Finally, we point the use of these extensions in two cases: design of new structures and digital image analysis.

Integration of multiple classic segmentation algorithms, oriented to the detection of edges, into a CommonKADS knowledge model

The existence of specific domain and case problems when extracting relevant information from complex images have generated segmentation methods, as they are found in the bibliography, adapted to specific problems and situations. Working with satellite image of different areas, we developed multiple variations of a previous mobile windows algorithm from Cayula and Cornillon (1992). We started classifying our alternatives by their possible application, realizing the suitability of a general model of applicability. Our objective could be described as formalizing the knowledge about the application of multiple previous segmentation algorithms. This is a knowledge modeling task; deciding to use as knowledge system development framework, CommonKADS, which is, actually, a de facto standard in Europe. We present the first level TMD schema of the segmentation model (for edge detection algorithms) and the CML description of the general task and a specific sample method. Main conclusions include the interest of developing a knowledge model integrating existing segmentation algorithm in order to reuse them, and analyze their applicability in different domains.

Development of a GIS catalog of hydrological resources and consumption points of a semiarid area with intensive agriculture

Almer/spl inodot//spl acute/a is a Spanish province located southeast the Iberian Peninsula, with a semiarid climate, that holds the largest concentration of greenhouses in the world (>30000 hectares). Main restriction of its development if given by its semiarid condition, with overexploited water resources. From 1992 to 1996 our group developed ESTIARA-SIG, a GIS based decision support system for the rural development of the province. Taking advantage of the data included into this system, we evaluated the suitability of developing a catalog of inputs and outputs of the hydrological resources of the Poniente area, where greenhouses and tourist installations are concentrated. The final objective of this catalog is modeling the use of water of the whole area, taking account not only of the quantity of the resources but of their quality.

Automatic Generation of the Behavior Definition of Distributed Design Tools from Task Method Diagrams and Method Flux Diagrams by Diagram Composition

Developing a knowledge-based version of a greenhouse design and simulation tools, DAMOCIA-Design and DAMOCIA-Sim, we realized the convenience of using multiple diagrammatic notations, and their advantages. First, we used an extension of the Task-Method Diagrams of the CommonKADS methodology to model the relation between the different tasks to be done and the methods we could use to solve them. Method Flux Diagrams model the relation between the different elements composing the method. In order to implement the design software, we selected a distributed architecture, DACAS, that integrated agents using behavior definitions. These are modeled as execution plan diagrams. In this work, we present how these execution plan diagrams can be generated in a general way from task-method and method-flux diagrams included into the knowledge model of the system.

ESKMod, a CommonKADS Knowledge Model Integrating Multiple Classic Edge Based Segmentation Algorithms

Bibliography offers us a wide set of image segmentation methods, which are usually oriented to solve specific problems. These are evaluated, mainly, in specific work fields, as the analysis of industrial pieces, classification of agricultural products or remote sensing. Actually, main efforts are concentrated in the definition of new algorithms, generating a wider collection of alternative methods. Taking account of our experience about applying segmentation methods to diverse work fields, we realized the advantages of integrating previously used methods into a single segmentation model, with multiple alternatives. In this work, we present how some classic methods are integrated into a single segmentation knowledge model, using the CommonKADS modeling tools. Our final objective is building a model of the applicatibility of the alternatives in order to relate them with searched results. Here, we present how this composed knowledge model was assembled.