La participación de las Fuerzas y Cuerpos de Seguridad en los sistemas de prevención de la delincuencia vial en España

A través de este trabajo se reflejó la gran prevalencia de la delincuencia vial en España, siendo la tipología delictiva con mayor número de condenas solo superada por los delitos contra el patrimonio, así como el escaso impacto de las medidas de expansión punitiva en su prevención, haciendo necesaria la implicación de los poderes públicos para reducir su incidencia. Con el fin de implicar en esta tarea a las Fuerzas y Cuerpos de Seguridad, dependientes de las diferentes administraciones públicas, se determinaron las posibles estrategias de prevención por parte de los diferentes cuerpos policiales en los sistemas de prevención primaria, secundaria y terciaria, así como su adecuación a la actual legislación en materia de fuerzas y cuerpos de seguridad. Por último, se estudió la aplicación de estas estrategias dentro de los cuerpos policiales españoles y el grado de aceptación de sus miembros, determinándose una escasa utilización de aquellas a pesar de la buena aceptación por sus efectivos.In this work, the high prevalence of road crime in Spain was reflected, being the criminal typology with the highest number of convictions only surpassed by crimes against property, as well as the low impact of punitive expansion measures in its prevention, making the involvement of public authorities necessary to reduce its incidence. In order to involve the police forces, dependent on the different public administrations, in this task, possible prevention strategies were determined by the different police forces in the primary, secondary and tertiary prevention systems, as well as its adaptation to the current legislation on police forces. Finally, the application of these strategies within the Spanish police forces and the degree of acceptance of their members was studied, determining a scarce use of those despite the good acceptance by their members

Circuit FPGA for active rules selection in a transition P system region

P systems or Membrane Computing are a type of a distributed, massively parallel and non deterministic system based on biological membranes. These systems perform a computation through transition between two consecutive configurations. As it is well known in membrane computing, a configuration consists in a m-tuple of multisets present at any moment in the existing m regions of the system at that moment time. Transitions between two configurations are performed by using evolution rules which are in each region of the system in a non-deterministic maximally parallel manner. This article shows the development of a hardware circuit of selection of active rules in a membrane of a transition P-system. This development has been researched by using the Quartus II tool of Altera Semiconductors. In the first place, the initial specifications are defined in orfer to outline the synthesis of the circuit of active rules selection. Later on the design and synthesis of the circuit will be shown, as well as, the operation tests required to present the obtained results

Special issue: Advances in learning schemes for function approximation

The eleven papers included in this special issue represent a selection of extended contributions presented at the 11th International Conference on Intelligent Systems Design and Applications (ISDA) held in Córdoba, Spain November 22–24, 2011. Papers were selected on the basis of fundamental ideas and concepts rather than the direct usage of well-established techniques. This special issue is then aimed at practitioners, researchers and postgraduate students, who are engaged in developing and applying, advanced Intelligent Systems to solving real-world problems in the Industrial and Environmental fields. The papers are organized as follows. In the first contribution, Barros et al., propose a novel Bottom-Up Oblique Decision-Tree Induction Framework called BUTIF. BUTIF does not rely on an impurity-measure for dividing nodes, since the data resulting from each split is known a priori. BUTIF allows the adoption of distinct clustering algorithms and binary classifiers, respectively, for generating the initial leaves of the tree and the splitting hyperplanes in its internal nodes. It is also capable of performing embedded feature selection, which may reduce the number of features in each hyperplane, thus improving model comprehension. Different from virtually every top-down decision-tree induction algorithm, BUTIF does not require the further execution of a pruning procedure in order to avoid overfitting, due to its bottom-up nature that does not overgrow the tree. Empirical results show the effectiveness of the proposed framework. The second contribution by Bolón-Canedo et al., propose an ensemble of filters for classification, aimed at achieving a good classification performance together with a reduction in the input dimensionality. This approach overcomes the problem of selecting an appropriate method for each problem at hand, as it is overly dependent on the characteristics of the datasets. The adequacy of using an ensemble of filters rather than a single filter was demonstrated on synthetic and real data, paving the way for its final application over a challenging scenario such as DNA microarray classification. Cruz-Ramírez et al., in the sequel present a study of the use of a multi-objective optimization approach in the context of ordinal classification and propose a new performance metric, the Maximum Mean Absolute Error (MMAE). MMAE considers per-class distribution of patterns and the magnitude of the errors, both issues being crucial for ordinal regression problems. In addition the authors empirically show that some of the performance metrics are competitive objectives, which justifies the use of multi-objective optimization strategies. In this study, a multi-objective evolutionary algorithm optimizes a artificial neural network ordinal model with different pairs of metrics combinations, concluding that the pair of the Mean Absolute Error (MAE) and the proposed MMAE is the most favorable. A study of the relationship between the metrics of this proposal is performed, and the graphical representation in the 2 dimensional space where the search of the evolutionary algorithm takes place is analyzed. The results obtained show a good classification performance, opening new lines of research in the evaluation and model selection of ordinal classifiers. In the fourth contribution, Cateni et al., present a novel resampling method for binary classification problems on imbalanced datasets combining an oversampling and an undersampling technique. Several tests have been developed aiming at assessing the efficiency of the proposed method. Four classifiers based, respectively, on Support Vector Machine, Decision Tree, labeled Self Organizing Map and Bayesian Classifiers have been developed and applied for binary classification on the following four datasets: a synthetic dataset, a widely used public dataset and two datasets coming from industrial applications. In the sequel, Ibañez et al., propose two greedy wrapper forward cost-sensitive selective naive Bayes approaches. Both approaches readjust the probability thresholds of each class to select the class with the minimum expected cost. The first algorithm (CS-SNB-Accuracy) considers adding each variable to the model and measures the performance of the resulting model on the training data. In contrast, the second algorithm (CS-SNB-Cost) considers adding variables that reduce the misclassification cost, that is, the distance between the readjusted class and actual class. The authors tested the algorithms on the bibliometric indices prediction area. Considering the popularity of the well-known h-index, they have researched and built several prediction models to forecast the annual increase of the h-index for Neurosciences journals in a four-year time horizon. Results show that the approaches, particularly CS-SNB-Accuracy, often achieved higher accuracy values than other Bayesian classifiers. Furthermore, it has been also noted that the CS-SNB-Cost almost always achieved a lower average cost than the analyzed standard classifiers. These cost-sensitive selective naive Bayes approaches outperform the selective naive Bayes in terms of accuracy and average cost, so the cost-sensitive learning approach could be also applied in different probabilistic classification approaches. Sobrino et al., in the sixth paper approach causal questions with the aim of: (1) answering what-questions as identifying the cause of an effect; (2) answering how-questions as selecting an appropriate part of a mechanism that relates pairs of cause effect (3) answering why-questions as identifying central causes in the mechanism which answer how-questions. To automatically get answers to why-questions, the authors hypothesize that the deepest knowledge associated to them can be obtained from the central nodes of the graph that schematizes the mechanism. This contribution is concerned with medical question answering systems, even though that this approach does not address how to retrieve medical documents as a primary answer to a question, but how to extract relevant causal answers from a given document previously extracted by using a search engine. Thus, this research deals with the automatic detection and extraction of causal relations from medical documents. In the seventh paper, Sleiman and Corchuelo propose a hybrid approach that explores the use of standard machine-learning techniques to extract web information. The results illustrate that the proposal outperforms three state-of-the-art techniques in the literature, which opens up quite a new approach for information extraction. García-Hernández et al. in the eighth paper, present a hybrid system for incorporating human expert knowledge into the unequal area facility layout problem. A subset of facility designs is generated using a genetic algorithm and then, evaluated by a human expert. The hybrid system consists of assigning a mark, where the principal aim is to substitute the human expert′s knowledge to, avoid fatiguing or burdening him or her. The novel proposed approach was tested using a real case study of 365 facility layout designs for an ovine slaughterhouse. The validation phase of the intelligent model presented was performed using a new subset of 181 facility layout designs evaluated by a different human expert. The results of the experiment, which validate the proposed approach, are presented and discussed in this study. Kang et al. in the sequel present an effective control method based on adaptive PID neural network and particle swarm optimization (PSO) algorithm. PSO algorithm is introduced to initialize the neural network for improving the convergent speed and preventing weights trapping into local optima. To adapt the initially uncertain and varying parameters in the control system, the authors introduce an improved gradient descent method to adjust the network parameters. The stability of our controller is analyzed according to the Lyapunov method. The simulation of complex nonlinear multiple-input and multiple-output (MIMO) system is presented with strong coupling. Empirical results illustrate that the proposed controller can obtain good precisión with shorter time compared with the other considered methods. In the tenth paper, Castellano et al. introduce a multi-agent system that exploits positioning information coming from mobile devices to detect the occurrence of user′s situations related to social events. In the functional view of the system, the first level of information processing is managed by marking agents which leave marks in the environment in correspondence to the users′ positions. The accumulation of marks enables a stigmergic cooperation mechanism, generating short-term memory structures in the local environment. Information provided by such structures is granulated by event agents which associate a certainty degree with each event. Finally, an inference level, managed by situation agents, deduces user situations from the underlying events by exploiting fuzzy rules whose parameters are generated automatically by a neuro-fuzzy approach. Fuzziness allows the system to cope with the uncertainty of the events. In the architectural view of the system, the authors adopt semantic web standards to guarantee structural interoperability in an open application environment. The system has been tested on different real-world scenarios to show the effectiveness of the proposed approach. Chira et al. in the final paper modeled the real-world optimization problem of urban bicycles renting systems as a capacitated Vehicle Routing Problem (VRP) with multiple depots and the simultaneous need for pickup and delivery at each base station location. Evolutionary algorithms and ant colony systems are proposed and real data from the cities of Barcelona and Valencia is used for experimental simulations. We would like to thank our peer-reviewers for their diligent work and efficient efforts. We are also grateful to the Editor-in-Chief of Neuro-computing, Prof. Tom Heskes, for his continued support for the ISDA conference and for the opportunity to organize this Special issue

Boletín de la Sociedad Geológica Mexicana Volumen 67

Abstract The fossil record of sclerorhynchid elasmobranchs in Mexico has been relatively scarce. In this paper we report a partial rostral tooth assigned to the cosmopolitan genus Onchosaurus ( †Sclerorhynchidae), originally preserved in a shell-bed matrix, collected at the Potrero del Llano locality, municipality of Aldama, Chihuahua, Mexico. The specimen most likely came from the Upper Cretaceous San Carlos Formation. The tooth has morpho-anatomical features that allow its attribution to the species Onchosaurus cf. O. pharao, which has been previously described from localities in Egypt, Niger, DR of Congo, Angola, Syria, Japan, U.S.A., Brazil, Colombia and Peru. The rostral tooth represents the first record of Onchosaurus in Mexico and the fourth in North America, thus expanding its paleobiogeographic distribution. Keywords: Chihuahua, Cretaceous, Batoidea, Sclerorhynchidae, Onchosaurus. Resumen El registro fósil de elasmobranquios esclerorrínquidos en México ha sido relativamente escaso. En este trabajo reportamos u

A Study of Catalogued Nearby Galaxy Clusters in the SDSS-DR4: I. Cluster Global Properties

We have selected a sample of 88 nearby (z<0.1) galaxy clusters from the SDSS-DR4 with redshift information for the cluster members. We have derived global properties for each cluster, such as their mean recessional velocity, velocity dispersion, and virial radii. Cluster galaxies have been grouped in two families according to their $u-r$ colours. The total sample consists of 10865 galaxies. As expected, the highest fraction of galaxies (62%) turned to be early-type (red) ones, being located at smaller distances from the cluster centre and showing lower velocity dispersions than late-type (blue) ones. The brightest cluster galaxies are located in the innermost regions and show the smallest velocity dispersions. Early-type galaxies also show constant velocity dispersion profiles inside the virial radius and a mild decline in the outermost regions. In contrast, late-type galaxies show always decreasing velocity dispersions profiles. No correlation has been found between the fraction of blue galaxies and cluster global properties, such as cluster velocity dispersion and galaxy concentration. In contrast, we found correlation between the X-ray luminosity and the fraction of blue galaxies. These results indicate that early- and late-type galaxies may have had different evolution. Thus, blue galaxies are located in more anisotropic and radial orbits than early-type ones. Their star formation seems to be independent of the cluster global properties in low mass clusters, but not for the most massive ones. These observational results suggest that the global environment could be important for driving the evolution of galaxies in the most massive cluster ($\sigma > 800$ km s$^{-1}$). However, the local environment could play a key role in galaxy evolution for low mass clusters.Comment: 19 pages, 11 figures, accepted for publication in A&

Atmospheric effects on extensive air showers observed with the Surface Detector of the Pierre Auger Observatory

Atmospheric parameters, such as pressure (P), temperature (T) and density, affect the development of extensive air showers initiated by energetic cosmic rays. We have studied the impact of atmospheric variations on extensive air showers by means of the surface detector of the Pierre Auger Observatory. The rate of events shows a ~10% seasonal modulation and ~2% diurnal one. We find that the observed behaviour is explained by a model including the effects associated with the variations of pressure and density. The former affects the longitudinal development of air showers while the latter influences the Moliere radius and hence the lateral distribution of the shower particles. The model is validated with full simulations of extensive air showers using atmospheric profiles measured at the site of the Pierre Auger Observatory.Comment: 24 pages, 9 figures, accepted for publication in Astroparticle Physic

The Fluorescence Detector of the Pierre Auger Observatory

The Pierre Auger Observatory is a hybrid detector for ultra-high energy cosmic rays. It combines a surface array to measure secondary particles at ground level together with a fluorescence detector to measure the development of air showers in the atmosphere above the array. The fluorescence detector comprises 24 large telescopes specialized for measuring the nitrogen fluorescence caused by charged particles of cosmic ray air showers. In this paper we describe the components of the fluorescence detector including its optical system, the design of the camera, the electronics, and the systems for relative and absolute calibration. We also discuss the operation and the monitoring of the detector. Finally, we evaluate the detector performance and precision of shower reconstructions.Comment: 53 pages. Submitted to Nuclear Instruments and Methods in Physics Research Section

Anisotropy studies around the galactic centre at EeV energies with the Auger Observatory

Data from the Pierre Auger Observatory are analyzed to search for anisotropies near the direction of the Galactic Centre at EeV energies. The exposure of the surface array in this part of the sky is already significantly larger than that of the fore-runner experiments. Our results do not support previous findings of localized excesses in the AGASA and SUGAR data. We set an upper bound on a point-like flux of cosmic rays arriving from the Galactic Centre which excludes several scenarios predicting sources of EeV neutrons from Sagittarius $A$. Also the events detected simultaneously by the surface and fluorescence detectors (the `hybrid' data set), which have better pointing accuracy but are less numerous than those of the surface array alone, do not show any significant localized excess from this direction.Comment: Matches published versio