876 resultados para Models Of Data


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In the paper we report on the results of our experiments on the construction of the opinion ontology. Our aim is to show the benefits of publishing in the open, on the Web, the results of the opinion mining process in a structured form. On the road to achieving this, we attempt to answer the research question to what extent opinion information can be formalized in a unified way. Furthermore, as part of the evaluation, we experiment with the usage of Semantic Web technologies and show particular use cases that support our claims.

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Large-scale structure formation can be modeled as a nonlinear process that transfers energy from the largest scales to successively smaller scales until it is dissipated, in analogy with Kolmogorov’s cascade model of incompressible turbulence. However, cosmic turbulence is very compressible, and vorticity plays a secondary role in it. The simplest model of cosmic turbulence is the adhesion model, which can be studied perturbatively or adapting to it Kolmogorov’s non-perturbative approach to incompressible turbulence. This approach leads to observationally testable predictions, e.g., to the power-law exponent of the matter density two-point correlation function.

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Recently, the Semantic Web has experienced signi�cant advancements in standards and techniques, as well as in the amount of semantic information available online. Even so, mechanisms are still needed to automatically reconcile semantic information when it is expressed in di�erent natural languages, so that access to Web information across language barriers can be improved. That requires developing techniques for discovering and representing cross-lingual links on the Web of Data. In this paper we explore the different dimensions of such a problem and reflect on possible avenues of research on that topic.

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The Web has witnessed an enormous growth in the amount of semantic information published in recent years. This growth has been stimulated to a large extent by the emergence of Linked Data. Although this brings us a big step closer to the vision of a Semantic Web, it also raises new issues such as the need for dealing with information expressed in different natural languages. Indeed, although the Web of Data can contain any kind of information in any language, it still lacks explicit mechanisms to automatically reconcile such information when it is expressed in different languages. This leads to situations in which data expressed in a certain language is not easily accessible to speakers of other languages. The Web of Data shows the potential for being extended to a truly multilingual web as vocabularies and data can be published in a language-independent fashion, while associated language-dependent (linguistic) information supporting the access across languages can be stored separately. In this sense, the multilingual Web of Data can be realized in our view as a layer of services and resources on top of the existing Linked Data infrastructure adding i) linguistic information for data and vocabularies in different languages, ii) mappings between data with labels in different languages, and iii) services to dynamically access and traverse Linked Data across different languages. In this article we present this vision of a multilingual Web of Data. We discuss challenges that need to be addressed to make this vision come true and discuss the role that techniques such as ontology localization, ontology mapping, and cross-lingual ontology-based information access and presentation will play in achieving this. Further, we propose an initial architecture and describe a roadmap that can provide a basis for the implementation of this vision.

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Cross‐lingual link discovery in the Web of Data

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The Semantic Web is growing at a fast pace, recently boosted by the creation of the Linked Data initiative and principles. Methods, standards, techniques and the state of technology are becoming more mature and therefore are easing the task of publication and consumption of semantic information on the Web.

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Data grid services have been used to deal with the increasing needs of applications in terms of data volume and throughput. The large scale, heterogeneity and dynamism of grid environments often make management and tuning of these data services very complex. Furthermore, current high-performance I/O approaches are characterized by their high complexity and specific features that usually require specialized administrator skills. Autonomic computing can help manage this complexity. The present paper describes an autonomic subsystem intended to provide self-management features aimed at efficiently reducing the I/O problem in a grid environment, thereby enhancing the quality of service (QoS) of data access and storage services in the grid. Our proposal takes into account that data produced in an I/O system is not usually immediately required. Therefore, performance improvements are related not only to current but also to any future I/O access, as the actual data access usually occurs later on. Nevertheless, the exact time of the next I/O operations is unknown. Thus, our approach proposes a long-term prediction designed to forecast the future workload of grid components. This enables the autonomic subsystem to determine the optimal data placement to improve both current and future I/O operations.

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This paper presents a new methodology to build parametric models to estimate global solar irradiation adjusted to specific on-site characteristics based on the evaluation of variable im- portance. Thus, those variables higly correlated to solar irradiation on a site are implemented in the model and therefore, different models might be proposed under different climates. This methodology is applied in a study case in La Rioja region (northern Spain). A new model is proposed and evaluated on stability and accuracy against a review of twenty-two already exist- ing parametric models based on temperatures and rainfall in seventeen meteorological stations in La Rioja. The methodology of model evaluation is based on bootstrapping, which leads to achieve a high level of confidence in model calibration and validation from short time series (in this case five years, from 2007 to 2011). The model proposed improves the estimates of the other twenty-two models with average mean absolute error (MAE) of 2.195 MJ/m2 day and average confidence interval width (95% C.I., n=100) of 0.261 MJ/m2 day. 41.65% of the daily residuals in the case of SIAR and 20.12% in that of SOS Rioja fall within the uncertainty tolerance of the pyranometers of the two networks (10% and 5%, respectively). Relative differences between measured and estimated irradiation on an annual cumulative basis are below 4.82%. Thus, the proposed model might be useful to estimate annual sums of global solar irradiation, reaching insignificant differences between measurements from pyranometers.

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In recent years new models for organizations working on overty alleviation have emerged. One of them, the social enterprise, has attracted the attention of both academics and practitioners all over the world. Even if defined in different ways depending on the context, social enterprise has an enormous potential to generate social benefits and to promote local agency and private initiative in poverty alleviation. In this sense, it is fitting to highlight the importance of identifying the main standards that permit the characterization of diverse social enterprises, in order to understand their main specificities and guarantee value generation for low-income populations. Another crucial factor is understanding innovation as a critical factor in promoting social enterprises. A powerful tool to enhance the impact and application of this model is Information and Communication Technologies. In the 21st century,these tools allow users to find new ways of collaboration, new sustainable business models and a cost-effective way of scaling-up initiatives. This paper, a product of the collaborative research between the Universidad Politécnica de Madrid and the Universidade Federal Fluminense, examines different business models for social enterprises and the role that ICT can play in scale and impact of these initiatives

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In order to improve the body of knowledge about brain injury impairment is essential to develop image database with different types of injuries. This paper proposes a new methodology to model three types of brain injury: stroke, tumor and traumatic brain injury; and implements a system to navigate among simulated MRI studies. These studies can be used on research studies, to validate new processing methods and as an educational tool, to show different types of brain injury and how they affect to neuroanatomic structures.

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Ion beam therapy is a valuable method for the treatment of deep-seated and radio-resistant tumors thanks to the favorable depth-dose distribution characterized by the Bragg peak. Hadrontherapy facilities take advantage of the specific ion range, resulting in a highly conformal dose in the target volume, while the dose in critical organs is reduced as compared to photon therapy. The necessity to monitor the delivery precision, i.e. the ion range, is unquestionable, thus different approaches have been investigated, such as the detection of prompt photons or annihilation photons of positron emitter nuclei created during the therapeutic treatment. Based on the measurement of the induced β+ activity, our group has developed various in-beam PET prototypes: the one under test is composed by two planar detector heads, each one consisting of four modules with a total active area of 10 × 10 cm2. A single detector module is made of a LYSO crystal matrix coupled to a position sensitive photomultiplier and is read-out by dedicated frontend electronics. A preliminary data taking was performed at the Italian National Centre for Oncological Hadron Therapy (CNAO, Pavia), using proton beams in the energy range of 93–112 MeV impinging on a plastic phantom. The measured activity profiles are presented and compared with the simulated ones based on the Monte Carlo FLUKA package.

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En los últimos años ha habido una fuerte tendencia a disminuir las emisiones de CO2 y su negativo impacto medioambiental. En la industria del transporte, reducir el peso de los vehículos aparece como la mejor opción para alcanzar este objetivo. Las aleaciones de Mg constituyen un material con gran potencial para el ahorro de peso. Durante la última década se han realizado muchos esfuerzos encaminados a entender los mecanismos de deformación que gobiernan la plasticidad de estos materiales y así, las aleaciones de Mg de colada inyectadas a alta presión y forjadas son todavía objeto de intensas campañas de investigación. Es ahora necesario desarrollar modelos que contemplen la complejidad inherente de los procesos de deformación de éstos. Esta tesis doctoral constituye un intento de entender mejor la relación entre la microestructura y el comportamiento mecánico de aleaciones de Mg, y dará como resultado modelos de policristales capaces de predecir propiedades macro- y microscópicas. La deformación plástica de las aleaciones de Mg está gobernada por una combinación de mecanismos de deformación característicos de la estructura cristalina hexagonal, que incluye el deslizamiento cristalográfico en planos basales, prismáticos y piramidales, así como el maclado. Las aleaciones de Mg de forja presentan texturas fuertes y por tanto los mecanismos de deformación activos dependen de la orientación de la carga aplicada. En este trabajo se ha desarrollado un modelo de plasticidad cristalina por elementos finitos con el objetivo de entender el comportamiento macro- y micromecánico de la aleación de Mg laminada AZ31 (Mg-3wt.%Al-1wt.%Zn). Este modelo, que incorpora el maclado y tiene en cuenta el endurecimiento por deformación debido a las interacciones dislocación-dislocación, dislocación-macla y macla-macla, predice exitosamente las actividades de los distintos mecanismos de deformación y la evolución de la textura con la deformación. Además, se ha llevado a cabo un estudio que combina difracción de electrones retrodispersados en tres dimensiones y modelización para investigar el efecto de los límites de grano en la propagación del maclado en el mismo material. Ambos, experimentos y simulaciones, confirman que el ángulo de desorientación tiene una influencia decisiva en la propagación del maclado. Se ha observado que los efectos no-Schmid, esto es, eventos de deformación plástica que no cumplen la ley de Schmid con respecto a la carga aplicada, no tienen lugar en la vecindad de los límites de baja desorientación y se hacen más frecuentes a medida que la desorientación aumenta. Esta investigación también prueba que la morfología de las maclas está altamente influenciada por su factor de Schmid. Es conocido que los procesos de colada suelen dar lugar a la formación de microestructuras con una microporosidad elevada, lo cuál afecta negativamente a sus propiedades mecánicas. La aplicación de presión hidrostática después de la colada puede reducir la porosidad y mejorar las propiedades aunque es poco conocido su efecto en el tamaño y morfología de los poros. En este trabajo se ha utilizado un enfoque mixto experimentalcomputacional, basado en tomografía de rayos X, análisis de imagen y análisis por elementos finitos, para la determinación de la distribución tridimensional (3D) de la porosidad y de la evolución de ésta con la presión hidrostática en la aleación de Mg AZ91 (Mg- 9wt.%Al-1wt.%Zn) colada por inyección a alta presión. La distribución real de los poros en 3D obtenida por tomografía se utilizó como input para las simulaciones por elementos finitos. Los resultados revelan que la aplicación de presión tiene una influencia significativa tanto en el cambio de volumen como en el cambio de forma de los poros que han sido cuantificados con precisión. Se ha observado que la reducción del tamaño de éstos está íntimamente ligada con su volumen inicial. En conclusión, el modelo de plasticidad cristalina propuesto en este trabajo describe con éxito los mecanismos intrínsecos de la deformación de las aleaciones de Mg a escalas meso- y microscópica. Más especificamente, es capaz de capturar las activadades del deslizamiento cristalográfico y maclado, sus interacciones, así como los efectos en la porosidad derivados de los procesos de colada. ---ABSTRACT--- The last few years have seen a growing effort to reduce CO2 emissions and their negative environmental impact. In the transport industry more specifically, vehicle weight reduction appears as the most straightforward option to achieve this objective. To this end, Mg alloys constitute a significant weight saving material alternative. Many efforts have been devoted over the last decade to understand the main mechanisms governing the plasticity of these materials and, despite being already widely used, high pressure die-casting and wrought Mg alloys are still the subject of intense research campaigns. Developing models that can contemplate the complexity inherent to the deformation of Mg alloys is now timely. This PhD thesis constitutes an attempt to better understand the relationship between the microstructure and the mechanical behavior of Mg alloys, as it will result in the design of polycrystalline models that successfully predict macro- and microscopic properties. Plastic deformation of Mg alloys is driven by a combination of deformation mechanisms specific to their hexagonal crystal structure, namely, basal, prismatic and pyramidal dislocation slip as well as twinning. Wrought Mg alloys present strong textures and thus specific deformation mechanisms are preferentially activated depending on the orientation of the applied load. In this work a crystal plasticity finite element model has been developed in order to understand the macro- and micromechanical behavior of a rolled Mg AZ31 alloy (Mg-3wt.%Al-1wt.%Zn). The model includes twinning and accounts for slip-slip, slip-twin and twin-twin hardening interactions. Upon calibration and validation against experiments, the model successfully predicts the activity of the various deformation mechanisms and the evolution of the texture at different deformation stages. Furthermore, a combined three-dimensional electron backscatter diffraction and modeling approach has been adopted to investigate the effect of grain boundaries on twin propagation in the same material. Both experiments and simulations confirm that the misorientation angle has a critical influence on twin propagation. Non-Schmid effects, i.e. plastic deformation events that do not comply with the Schmid law with respect to the applied stress, are absent in the vicinity of low misorientation boundaries and become more abundant as misorientation angle increases. This research also proves that twin morphology is highly influenced by the Schmid factor. Finally, casting processes usually lead to the formation of significant amounts of gas and shrinkage microporosity, which adversely affect the mechanical properties. The application of hydrostatic pressure after casting can reduce the porosity and improve the properties but little is known about the effects on the casting’s pores size and morphology. In this work, an experimental-computational approach based on X-ray computed tomography, image analysis and finite element analysis is utilized for the determination of the 3D porosity distribution and its evolution with hydrostatic pressure in a high pressure diecast Mg AZ91 alloy (Mg-9wt.%Al-1wt.%Zn). The real 3D pore distribution obtained by tomography is used as input for the finite element simulations using an isotropic hardening law. The model is calibrated and validated against experimental stress-strain curves. The results reveal that the pressure treatment has a significant influence both on the volume and shape changes of individuals pores, which have been precisely quantified, and which are found to be related to the initial pore volume. In conclusion, the crystal plasticity model proposed in this work successfully describes the intrinsic deformation mechanisms of Mg alloys both at the mesoscale and the microscale. More specifically, it can capture slip and twin activities, their interactions, as well as the potential porosity effects arising from casting processes.

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El principio de Teoría de Juegos permite desarrollar modelos estocásticos de patrullaje multi-robot para proteger infraestructuras criticas. La protección de infraestructuras criticas representa un gran reto para los países al rededor del mundo, principalmente después de los ataques terroristas llevados a cabo la década pasada. En este documento el termino infraestructura hace referencia a aeropuertos, plantas nucleares u otros instalaciones. El problema de patrullaje se define como la actividad de patrullar un entorno determinado para monitorear cualquier actividad o sensar algunas variables ambientales. En esta actividad, un grupo de robots debe visitar un conjunto de puntos de interés definidos en un entorno en intervalos de tiempo irregulares con propósitos de seguridad. Los modelos de partullaje multi-robot son utilizados para resolver este problema. Hasta el momento existen trabajos que resuelven este problema utilizando diversos principios matemáticos. Los modelos de patrullaje multi-robot desarrollados en esos trabajos representan un gran avance en este campo de investigación. Sin embargo, los modelos con los mejores resultados no son viables para aplicaciones de seguridad debido a su naturaleza centralizada y determinista. Esta tesis presenta cinco modelos de patrullaje multi-robot distribuidos e impredecibles basados en modelos matemáticos de aprendizaje de Teoría de Juegos. El objetivo del desarrollo de estos modelos está en resolver los inconvenientes presentes en trabajos preliminares. Con esta finalidad, el problema de patrullaje multi-robot se formuló utilizando conceptos de Teoría de Grafos, en la cual se definieron varios juegos en cada vértice de un grafo. Los modelos de patrullaje multi-robot desarrollados en este trabajo de investigación se han validado y comparado con los mejores modelos disponibles en la literatura. Para llevar a cabo tanto la validación como la comparación se ha utilizado un simulador de patrullaje y un grupo de robots reales. Los resultados experimentales muestran que los modelos de patrullaje desarrollados en este trabajo de investigación trabajan mejor que modelos de trabajos previos en el 80% de 150 casos de estudio. Además de esto, estos modelos cuentan con varias características importantes tales como distribución, robustez, escalabilidad y dinamismo. Los avances logrados con este trabajo de investigación dan evidencia del potencial de Teoría de Juegos para desarrollar modelos de patrullaje útiles para proteger infraestructuras. ABSTRACT Game theory principle allows to developing stochastic multi-robot patrolling models to protect critical infrastructures. Critical infrastructures protection is a great concern for countries around the world, mainly due to terrorist attacks in the last decade. In this document, the term infrastructures includes airports, nuclear power plants, and many other facilities. The patrolling problem is defined as the activity of traversing a given environment to monitoring any activity or sensing some environmental variables If this activity were performed by a fleet of robots, they would have to visit some places of interest of an environment at irregular intervals of time for security purposes. This problem is solved using multi-robot patrolling models. To date, literature works have been solved this problem applying various mathematical principles.The multi-robot patrolling models developed in those works represent great advances in this field. However, the models that obtain the best results are unfeasible for security applications due to their centralized and predictable nature. This thesis presents five distributed and unpredictable multi-robot patrolling models based on mathematical learning models derived from Game Theory. These multi-robot patrolling models aim at overcoming the disadvantages of previous work. To this end, the multi-robot patrolling problem was formulated using concepts of Graph Theory to represent the environment. Several normal-form games were defined at each vertex of a graph in this formulation. The multi-robot patrolling models developed in this research work have been validated and compared with best ranked multi-robot patrolling models in the literature. Both validation and comparison were preformed by using both a patrolling simulator and real robots. Experimental results show that the multirobot patrolling models developed in this research work improve previous ones in as many as 80% of 150 cases of study. Moreover, these multi-robot patrolling models rely on several features to highlight in security applications such as distribution, robustness, scalability, and dynamism. The achievements obtained in this research work validate the potential of Game Theory to develop patrolling models to protect infrastructures.

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This study analyses the differences between two calculation models for guardrails on building sites that use wooden boards and tubular steel posts. Wood was considered an isotropic material in one model and an orthotropic material in a second model. The elastic constants of the wood were obtained with ultrasound. Frequencies and vibration modes were obtained for both models through linear analysis using the finite element method. The two models were experimentally calibrated through operational modal analysis. The results obtained show that for the three types of wood under analysis, the model which considered them as an orthotropic material fitted the experimental results better than the model which considered them as an isotropic material.

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This special issue gathers together a number of recent papers on fractal geometry and its applications to the modeling of flow and transport in porous media. The aim is to provide a systematic approach for analyzing the statics and dynamics of fluids in fractal porous media by means of theory, modeling and experimentation. The topics covered include lacunarity analyses of multifractal and natural grayscale patterns, random packing's of self-similar pore/particle size distributions, Darcian and non-Darcian hydraulic flows, diffusion within fractals, models for the permeability and thermal conductivity of fractal porous media and hydrophobicity and surface erosion properties of fractal structures.