967 resultados para Scenario


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This paper is an introduction of the regret theory-based scenario building approach combining with a modified Delphi method that uses an interactive process to design and assess four different TDM measures (i.e., cordon toll, parking charge, increased bus frequency and decreased bus fare). The case study of Madrid is used to present the analysis and provide policy recommendations. The new scenario building approach incorporates expert judgement and transport models in an interactive process. It consists of a two-round modified Delphi survey, which was answeared by a group of Spanish transport experts who were the participants of the Transport Engineering Congress (CIT 2012), and an integrated land-use and transport model (LUTI) for Madrid that is called MARS (Metropolitan Activity Relocation Simulator).

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A damage scenario modelling is developed and compared with the damage distribution observed after the 2011 Lorca earthquake. The strong ground motion models considered include five modern ground motion prediction equations (GMPEs) amply used worldwide. Capacity and fragility curves from the Risk-UE project are utilized to model building vulnerability and expected damage. Damage estimates resulting from different combinations of GMPE and capacity/fragility curves are compared with the actual damage scenario, establishing the combination that best explains the observed damage distribution. In addition, some recommendations are proposed, including correction factors in fragility curves in order to reproduce in a better way the observed damage in masonry and reinforce concrete buildings. The lessons learned would contribute to improve the simulation of expected damages due to future earthquakes in Lorca or other regions in Spain with similar characteristics regarding attenuation and vulnerability.

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Uno de los mayores retos para la comunidad científica es conseguir que las máquinas posean en un futuro la capacidad del sistema visual y cognitivo humanos, de forma que, por ejemplo, en entornos de video vigilancia, puedan llegar a proporcionar de manera automática una descripción fiable de lo que está ocurriendo en la escena. En la presente tesis, mediante la propuesta de un marco de trabajo de referencia, se discuten y plantean los pasos necesarios para el desarrollo de sistemas más inteligentes capaces de extraer y analizar, a diferentes niveles de abstracción y mediante distintos módulos de procesamiento independientes, la información necesaria para comprender qué está sucediendo en un conjunto amplio de escenarios de distinta naturaleza. Se parte de un análisis de requisitos y se identifican los retos para este tipo de sistemas en la actualidad, lo que constituye en sí mismo los objetivos de esta tesis, contribuyendo así a un modelo de datos basado en el conocimiento que permitirá analizar distintas situaciones en las que personas y vehículos son los actores principales, dejando no obstante la puerta abierta a la adaptación a otros dominios. Así mismo, se estudian los distintos procesos que se pueden lanzar a nivel interno así como la necesidad de integrar mecanismos de realimentación a distintos niveles que permitan al sistema adaptarse mejor a cambios en el entorno. Como resultado, se propone un marco de referencia jerárquico que integra las capacidades de percepción, interpretación y aprendizaje para superar los retos identificados en este ámbito; y así poder desarrollar sistemas de vigilancia más robustos, flexibles e inteligentes, capaces de operar en una variedad de entornos. Resultados experimentales ejecutados sobre distintas muestras de datos (secuencias de vídeo principalmente) demuestran la efectividad del marco de trabajo propuesto respecto a otros propuestos en el pasado. Un primer caso de estudio, permite demostrar la creación de un sistema de monitorización de entornos de parking en exteriores para la detección de vehículos y el análisis de plazas libres de aparcamiento. Un segundo caso de estudio, permite demostrar la flexibilidad del marco de referencia propuesto para adaptarse a los requisitos de un entorno de vigilancia completamente distinto, como es un hogar inteligente donde el análisis automático de actividades de la vida cotidiana centra la atención del estudio. ABSTRACT One of the most ambitious objectives for the Computer Vision and Pattern Recognition research community is that machines can achieve similar capacities to the human's visual and cognitive system, and thus provide a trustworthy description of what is happening in the scene under surveillance. Thus, a number of well-established scenario understanding architectural frameworks to develop applications working on a variety of environments can be found in the literature. In this Thesis, a highly descriptive methodology for the development of scene understanding applications is presented. It consists of a set of formal guidelines to let machines extract and analyse, at different levels of abstraction and by means of independent processing modules that interact with each other, the necessary information to understand a broad set of different real World surveillance scenarios. Taking into account the challenges that working at both low and high levels offer, we contribute with a highly descriptive knowledge-based data model for the analysis of different situations in which people and vehicles are the main actors, leaving the door open for the development of interesting applications in diverse smart domains. Recommendations to let systems achieve high-level behaviour understanding will be also provided. Furthermore, feedback mechanisms are proposed to be integrated in order to let any system to understand better the environment and the logical context around, reducing thus the uncertainty and noise, and increasing its robustness and precision in front of low-level or high-level errors. As a result, a hierarchical cognitive architecture of reference which integrates the necessary perception, interpretation, attention and learning capabilities to overcome main challenges identified in this area of research is proposed; thus allowing to develop more robust, flexible and smart surveillance systems to cope with the different requirements of a variety of environments. Once crucial issues that should be treated explicitly in the design of this kind of systems have been formulated and discussed, experimental results shows the effectiveness of the proposed framework compared with other proposed in the past. Two case studies were implemented to test the capabilities of the framework. The first case study presents how the proposed framework can be used to create intelligent parking monitoring systems. The second case study demonstrates the flexibility of the system to cope with the requirements of a completely different environment, a smart home where activities of daily living are performed. Finally, general conclusions and future work lines to further enhancing the capabilities of the proposed framework are presented.

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A common view is that the current global warming rate will continue or accelerate. But we argue that rapid warming in recent decades has been driven mainly by non-CO2 greenhouse gases (GHGs), such as chlorofluorocarbons, CH4, and N2O, not by the products of fossil fuel burning, CO2 and aerosols, the positive and negative climate forcings of which are partially offsetting. The growth rate of non-CO2 GHGs has declined in the past decade. If sources of CH4 and O3 precursors were reduced in the future, the change in climate forcing by non-CO2 GHGs in the next 50 years could be near zero. Combined with a reduction of black carbon emissions and plausible success in slowing CO2 emissions, this reduction of non-CO2 GHGs could lead to a decline in the rate of global warming, reducing the danger of dramatic climate change. Such a focus on air pollution has practical benefits that unite the interests of developed and developing countries. However, assessment of ongoing and future climate change requires composition-specific long-term global monitoring of aerosol properties.

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I conjecture that the mechanism of superconductivity in the cuprates is a saving, due to the improved screening resulting from Cooper pair formation, of the part of the Coulomb energy associated with long wavelengths and midinfrared frequencies. This scenario is shown to provide a plausible explanation of the trend of transition temperature with layering structure in the Ca-spaced compounds and to predict a spectacularly large decrease in the electron-energy-loss spectroscopy cross-section in the midinfrared region on transition to the superconducting state, as well as less spectacular but still surprisingly large changes in the optical behavior. Existing experimental results appear to be consistent with this picture.

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Central compact objects (CCOs) are X-ray sources lying close to the centre of supernova remnants, with inferred values of the surface magnetic fields significantly lower (≲1011 G) than those of standard pulsars. In this paper, we revise the hidden magnetic field scenario, presenting the first 2D simulations of the submergence and re-emergence of the magnetic field in the crust of a neutron star. A post-supernova accretion stage of about 10−4–10−3 M⊙ over a vast region of the surface is required to bury the magnetic field into the inner crust. When accretion stops, the field re-emerges on a typical time-scale of 1–100 kyr, depending on the submergence conditions. After this stage, the surface magnetic field is restored close to its birth values. A possible observable consequence of the hidden magnetic field is the anisotropy of the surface temperature distribution, in agreement with observations of several of these sources. We conclude that the hidden magnetic field model is viable as an alternative to the antimagnetar scenario, and it could provide the missing link between CCOs and the other classes of isolated neutron stars.

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Several recent works deal with 3D data in mobile robotic problems, e.g., mapping. Data comes from any kind of sensor (time of flight, Kinect or 3D lasers) that provide a huge amount of unorganized 3D data. In this paper we detail an efficient approach to build complete 3D models using a soft computing method, the Growing Neural Gas (GNG). As neural models deal easily with noise, imprecision, uncertainty or partial data, GNG provides better results than other approaches. The GNG obtained is then applied to a sequence. We present a comprehensive study on GNG parameters to ensure the best result at the lowest time cost. From this GNG structure, we propose to calculate planar patches and thus obtaining a fast method to compute the movement performed by a mobile robot by means of a 3D models registration algorithm. Final results of 3D mapping are also shown.

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In general equilibrium models the reference scenario is important, as the evaluation of the alternative policies modelled is based on their deviation from the reference scenario. The reference scenario relates to the development of an economic outlook for each region and sector of the model. This means that assumptions are made about the main drivers of growth, e.g. population growth and technical progress. This report provides the main assumptions used for the development of the reference scenario in the MEDPRO project. The report also provides a brief country and sectoral overview for each of the southern and eastern Mediterranean countries covered by the MEDPRO project.

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Rising atmospheric CO2-concentrations will have severe consequences for a variety of biological processes. We investigated the responses of the green alga Ulva lactuca (Linnaeus) to rising CO2-concentrations in a rockpool scenario. U. lactuca was cultured under aeraton with air containing either preindustrial pCO2 (280µatm) or for the end of the 21st century predicted (700µatm) pCO2 for 31 days. We addressed the following question: Will elevated CO2-concentrations affect photosynthesis (net photosynthesis, rETR(max), Fv/Fm, pigment composition) and growth of U. lactuca in rockpools with limited water exchange? Two phases of the experiment were distinguished: In the initial phase (day 1-4) the Seawater Carbonate System (SWCS) of the culture medium could be adjusted to the selected atmospheric pCO2 condition by continuous aeration with target pCO2 values. In the second phase (day 4-31) the SWCS was largely determined by the metabolism of the growing U. lactuca biomass. In the initial phase, Fv/Fm and rETR(max) were only slightly elevated at high CO2-concentrations whereas growth was significantly enhanced. After 31 days the Chl a content of the thalli was significantly lower under future conditions and the photosynthesis of thalli grown under preindustrial conditions was not dependent on external carbonic anhydrase. Biomass increased significantly at high CO2-concentrations. At low CO2-concentrations most adult thalli disintegrated between day 14 and 21, whereas at high CO2-concentrations most thalli remained integer until day 31. Thallus disintegration at low CO2-concentrations was mirrored in a drastic decline in seawater DIC and HCO3-. Accordingly, the SWCS differed significantly between the treatments. Our results indicated a slight enhancement of photosynthetic performance and significantly elevated growth of U. lactuca at future CO2-concentrations. The accelerated thallus disintegration at high CO2-concentrations under conditions of limited water exchange indicates additional CO2 effects on the life cycle of U. lactuca when living in rockpools.

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Numbering irregular: v. 9-13 repeated.

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Mode of access: Internet.

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The purpose of this analysis is threefold: first, to extract from the literature, current levels of GP detection of at-risk drinking by their patients, rates at which general practitioners (GPs) offer an intervention; and the effectiveness of these interventions; secondly, to develop a model based on this literature to be used in conjunction with scenario analysis; and thirdly, to consider the cost implications of current efforts and various scenarios. This study deals specifically with Australian general practice. A two-step procedure is used in the scenario analysis, which involves identifying opportunities for detection, intervention, effectiveness and assigning probabilities to outcomes. The results suggest that increasing rates of GP intervention achieves greatest benefit and return on resource use. For every 5% point increase in the rate of GP intervention, an additional 26 754 at-risk drinkers modify their drinking behaviour at a cost of $231.45 per patient. This compares with a cost per patient modifying drinking behaviour of $232.60 and $208.31 for every 5% point increase in the rates of detection and effectiveness, respectively. The knowledge, skill and attitude of practitioners toward drinking are significant, and they can be the prime motivators in persuading their patients to modify drinking behaviour.

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Using imaging from the Hubble Space Telescope, we derive surface brightness profiles for ultracompact dwarfs in the Fornax Cluster and for the nuclei of dwarf elliptical galaxies in the Virgo Cluster. Ultracompact dwarfs are more extended and have higher surface brightnesses than typical dwarf nuclei, while the luminosities, colors, and sizes of the nuclei are closer to those of Galactic globular clusters. This calls into question the production of ultracompact dwarfs via threshing, whereby the lower surface brightness envelope of a dwarf elliptical galaxy is removed by tidal processes, leaving behind a bare nucleus. Threshing may still be a viable model if the relatively bright Fornax ultracompact dwarfs considered here are descended from dwarf elliptical galaxies whose nuclei are at the upper end of their luminosity and size distributions.