Classification of Satellite Images by means of Fuzzy Rules generated by a Genetic Algorithm

The data acquired by Remote Sensing systems allow obtaining thematic maps of the earth's surface, by means of the registered image classification. This implies the identification and categorization of all pixels into land cover classes. Traditionally, methods based on statistical parameters have been widely used, although they show some disadvantages. Nevertheless, some authors indicate that those methods based on artificial intelligence, may be a good alternative. Thus, fuzzy classifiers, which are based on Fuzzy Logic, include additional information in the classification process through based-rule systems. In this work, we propose the use of a genetic algorithm (GA) to select the optimal and minimum set of fuzzy rules to classify remotely sensed images. Input information of GA has been obtained through the training space determined by two uncorrelated spectral bands (2D scatter diagrams), which has been irregularly divided by five linguistic terms defined in each band. The proposed methodology has been applied to Landsat-TM images and it has showed that this set of rules provides a higher accuracy level in the classification process

CLP Projection for Constraint Handling Rules

This paper introduces and studies the notion of CLP projection for Constraint Handling Rules (CHR). The CLP projection consists of a naive translation of CHR programs into Constraint Logic Programs (CLP). We show that the CLP projection provides a safe operational and declarative approximation for CHR programs. We demónstrate moreover that a confluent CHR program has a least model, which is precisely equal to the least model of its CLP projection (closing henee a ten year-old conjecture by Abdenader et al.). Finally, we illustrate how the notion of CLP projection can be used in practice to apply CLP analyzers to CHR. In particular, we show results from applying AProVE to prove termination, and CiaoPP to infer both complexity upper bounds and types for CHR programs.

Stopping power dependence of nitrogen sputtering yields in copper nitride films under swift-ion irradiation: Exciton model approach

Nitrogen sputtering yields as high as 104 atoms/ion, are obtained by irradiating N-rich-Cu3N films (N concentration: 33 ± 2 at.%) with Cu ions at energies in the range 10?42 MeV. The kinetics of N sputtering as a function of ion fluence is determined at several energies (stopping powers) for films deposited on both, glass and silicon substrates. The kinetic curves show that the amount of nitrogen release strongly increases with rising irradiation fluence up to reaching a saturation level at a low remaining nitrogen fraction (5?10%), in which no further nitrogen reduction is observed. The sputtering rate for nitrogen depletion is found to be independent of the substrate and to linearly increase with electronic stopping power (Se). A stopping power (Sth) threshold of ?3.5 keV/nm for nitrogen depletion has been estimated from extrapolation of the data. Experimental kinetic data have been analyzed within a bulk molecular recombination model. The microscopic mechanisms of the nitrogen depletion process are discussed in terms of a non-radiative exciton decay model. In particular, the estimated threshold is related to a minimum exciton density which is required to achieve efficient sputtering rates.

Relativistic high-current electron-beam stopping-power characterization in solids and plasmas: collisional versus resistive effects.

We present experimental and numerical results on intense-laser-pulse-produced fast electron beams transport through aluminum samples, either solid or compressed and heated by laser-induced planar shock propagation. Thanks to absolute K� yield measurements and its very good agreement with results from numerical simulations, we quantify the collisional and resistive fast electron stopping powers: for electron current densities of � 8 � 1010 A=cm2 they reach 1:5 keV=�m and 0:8 keV=�m, respectively. For higher current densities up to 1012 A=cm2, numerical simulations show resistive and collisional energy losses at comparable levels. Analytical estimations predict the resistive stopping power will be kept on the level of 1 keV=�m for electron current densities of 1014 A=cm2, representative of the full-scale conditions in the fast ignition of inertially confined fusion targets.

Stopping of α particles from the core in corona plasmas

In the laser fusion reactor design, the protection of first wall and the final optics from high energy ions is the key issue. So, it is necessary to predict the precise energy spectra of ions.In the previous reactor designs, the ion energy spectra were provided by the classical ion transport codes. However, this poster shows that the α particle spectrum is significantly modified by the anomalous process in ablated plasmas.

Passing or stopping by: meeting points on the fly

In traditional nomadic societies, social life was created around mobile points rekindled in different places each time. After the settled urbanization period, where social life centred on fixed attractions, we are opening a new era, where thanks to technology, we are able to create meeting points on the fly. Contemporary public space for passer-by users will be again based on traces instead of lines, reflecting current reality far more accurately.

Vision-based active safety system for automatic stopping

ntelligent systems designed to reduce highway fatalities have been widely applied in the automotive sector in the last decade. Of all users of transport systems, pedestrians are the most vulnerable in crashes as they are unprotected. This paper deals with an autonomous intelligent emergency system designed to avoid collisions with pedestrians. The system consists of a fuzzy controller based on the time-to-collision estimate – obtained via a vision-based system – and the wheel-locking probability – obtained via the vehicle’s CAN bus – that generates a safe braking action. The system has been tested in a real car – a convertible Citroën C3 Pluriel – equipped with an automated electro-hydraulic braking system capable of working in parallel with the vehicle’s original braking circuit. The system is used as a last resort in the case that an unexpected pedestrian is in the lane and all the warnings have failed to produce a response from the driver.

Fusion of probabilistic knowledge-based classification rules and learning automata for automatic recognition of digital images

In this paper, the fusion of probabilistic knowledge-based classification rules and learning automata theory is proposed and as a result we present a set of probabilistic classification rules with self-learning capability. The probabilities of the classification rules change dynamically guided by a supervised reinforcement process aimed at obtaining an optimum classification accuracy. This novel classifier is applied to the automatic recognition of digital images corresponding to visual landmarks for the autonomous navigation of an unmanned aerial vehicle (UAV) developed by the authors. The classification accuracy of the proposed classifier and its comparison with well-established pattern recognition methods is finally reported.

Changing assessment methods: New rules, new roles

Over the past 20 years,theuse of Computer Algebra Systems(CAS) has helped with the teaching of mathematics inengineer-ingschools. However the traditional use of CAS only in math labs has led to a narrow view by the student: the CAS is an additional work, not included in the learning process. The didactic guidelines of the European Higher Education Area(EHEA) propose a new teaching–learning model based on competencies. We suggest the use of the CAS be adapted to the new rules. In this paper,we present a model for the integrated use of the CAS,and we describe and analyze two experiments carried out in the academic year2011–2012. Our analysis suggests that the use of CAS in all learning and assessment activities has the potential to positively influence the development of competencies.

Evaluation/Optimization of reservoir operation rules for flood management using an integrated hydrologic-hydraulic framework

Se ha presentado la evaluación y optimización de las reglas de operación de un embalse para gestión de avenidas usando un entorno integrado hidrológico- hidráulico de tipo Monte Carlo. Some reservoirs play a major role in flood protection, managing the floods and reducing or delaying the peak discharges in the river downstream. However, the changing environment (natural and anthropological changes) requires the development of more elaborated strategies for reservoir operation. Three factors are relevant: 1) the natural variability of inflow hydrographs, 2) the competition for reservoir storage capacity between flood control and other uses, and 3) the existence of built-up areas on downstream river reaches. A framework for evaluation/optimization of reservoir operation rules for flood management in a changing environment is presented in this study. The study was carried out using an integrated hydrologic – hydraulic model in a Monte Carlo framework.

Effects of inspections in small world social networks with different contagion rules

Inspections are used to prevent tax evasion or any other unlawful behavior. ? The effect of inspections depends on the network topology and the contagion rule. ? The network is modeled as a Watts?Strogatz Small World that is tuned from regular to random. ? Two contagion rules are applied: continuous and discontinuous. ? The equilibrium populations of payers and evaders are obtained in terms of these system parameters.