911 resultados para Train scheduling
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Diversos fatores têm contribuído para o aumento da demanda por transporte ferroviário no Brasil. Dentre eles, citam-se: o aumento das exportações brasileiras nos últimos anos e a aprovação do novo marco regulatório para o setor ferroviário brasileiro que permitiu o uso da capacidade ociosa das ferrovias e o compartilhamento da malha por diversos operadores. Investimentos para construção de novas ferrovias e melhorias nas já existentes são muito elevados, o que dificulta a implantação de novos projetos. Assim, faz-se necessário melhorar o planejamento da circulação de trens visando o aumento de capacidade sem a necessidade de novos investimentos, otimizando o uso da estrutura já existente. Esta dissertação tem como objetivo propor um modelo matemático para realizar o planejamento da circulação de trens em uma ferrovia de linha singela, que minimize o transit time, isto é, o tempo total de viagem de todos os trens e consequentemente reduza o tempo parado em pátios de cruzamento. O modelo proposto permite que os trens sejam atrasados ou adiantados na partida visando reduzir o tempo parado em pátios de cruzamento. O modelo é resolvido de forma ótima usando o solver CPLEX 12.6. Foram realizados testes com dados reais da Ferrovia Centro Atlântica (FCA) e os resultados alcançados pelo CPLEX foram comparados com os resultados do planejamento manual da FCA. O modelo obteve redução do tempo de viagem dos trens em todos os cenários testados.
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The exponential increase of home-bound persons who live alone and are in need of continuous monitoring requires new solutions to current problems. Most of these cases present illnesses such as motor or psychological disabilities that deprive of a normal living. Common events such as forgetfulness or falls are quite common and have to be prevented or dealt with. This paper introduces a platform to guide and assist these persons (mostly elderly people) by providing multisensory monitoring and intelligent assistance. The platform operates at three levels. The lower level, denominated ‘‘Data acquisition and processing’’performs the usual tasks of a monitoring system, collecting and processing data from the sensors for the purpose of detecting and tracking humans. The aim is to identify their activities in an intermediate level called ‘‘activity detection’’. The upper level, ‘‘Scheduling and decision-making’’, consists of a scheduler which provides warnings, schedules events in an intelligent manner and serves as an interface to the rest of the platform. The idea is to use mobile and static sensors performing constant monitoring of the user and his/her environment, providing a safe environment and an immediate response to severe problems. A case study on elderly fall detection in a nursery home bedroom demonstrates the usefulness of the proposal.
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Cognitive impaired population face with innumerable problems in their daily life. Surprisingly, they are not provided with any help to perform those tasks for which they have difficulties. As a consequence, it is necessary to develop systems that allow those people to live independently and autonomously. Living in a technological era, people could take advantage of the available technology, being provided with some solutions to their needs. This paper presents a platform that assists users with remembering where their possessions are. Mainly, an object recognition process together with an intelligent scheduling applications are integrated in an Ambient Assisted Living (AAL) environment.
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The progressive aging of the population requires new kinds of social and medical intervention and the availability of different services provided to the elder population. New applications have been developed and some services are now provided at home, allowing the older people to stay home instead of having to stay in hospitals. But an adequate response to the needs of the users will imply a high percentage of use of personal data and information, including the building up and maintenance of user profiles, feeding the systems with the data and information needed for a proactive intervention in scheduling of events in which the user may be involved. Fundamental Rights may be at stake, so a legal analysis must also be considered.
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Pectus excavatum is the most common congenital deformity of the anterior chest wall, in which several ribs and the sternum grow abnormally. Nowadays, the surgical correction is carried out in children and adults through Nuss technic. This technic has been shown to be safe with major drivers as cosmesis and the prevention of psychological problems and social stress. Nowadays, no application is known to predict the cosmetic outcome of the pectus excavatum surgical correction. Such tool could be used to help the surgeon and the patient in the moment of deciding the need for surgery correction. This work is a first step to predict postsurgical outcome in pectus excavatum surgery correction. Facing this goal, it was firstly determined a point cloud of the skin surface along the thoracic wall using Computed Tomography (before surgical correction) and the Polhemus FastSCAN (after the surgical correction). Then, a surface mesh was reconstructed from the two point clouds using a Radial Basis Function algorithm for further affine registration between the meshes. After registration, one studied the surgical correction influence area (SCIA) of the thoracic wall. This SCIA was used to train, test and validate artificial neural networks in order to predict the surgical outcome of pectus excavatum correction and to determine the degree of convergence of SCIA in different patients. Often, ANN did not converge to a satisfactory solution (each patient had its own deformity characteristics), thus invalidating the creation of a mathematical model capable of estimating, with satisfactory results, the postsurgical outcome
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With the number of elderly people increasing tremendously worldwide, comes the need for effective methods to maintain or improve older adults' cognitive performance. Using continuous neurofeedback, through the use of EEG techniques, people can learn how to train and alter their brain electrical activity. A software platform that puts together the proposed rehabilitation methodology has been developed: a digital game protocol that supports neurofeedback training of alpha and theta rhythms, by reading the EEG activity and presenting it back to the subject, interleaved with neurocognitive tasks such as n-Back and Corsi Block-Tapping. This tool will be used as a potential rehabilitative platform for age-related memory impairments.
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O presente Trabalho Final de Mestrado reporta-se ao desenvolvimento de um Projecto de Execução na especialidade de Via Férrea, no âmbito do SMM - Sistema de Mobilidade do Mondego. Este projecto consiste na modernização do actual Ramal da Lousã, considerando o aproveitamento do espaço canal da actual infra-estrutura ferroviária em bitola ibérica (1668mm) para adaptação à bitola europeia (1435mm), para circulação de um novo material circulante do tipo “tram-train”. O actual Ramal da Lousã tem aproximadamente uma extensão de 35km, e assegura a ligação entre a cidade de Coimbra e a freguesia de Serpins. O presente projecto remete-se à modernização de um troço do actual ramal, localizado entre a vila de Miranda do Corvo e Serpins, e apresenta uma extensão aproximada de 17km. Com base em elementos de projecto previamente definidos foi determinada a geometria de traçado de via tendo em consideração as normas europeias vigentes, com as devidas adaptações para o tipo de infra-estrutura em causa, e com algum apoio de processos de cálculo automático, concretamente, o software Civil 3D da Autodesk. Definida a geometria de traçado caracterizaram-se os tipos e materiais de via a implementar na superstrutura da via, devidamente quantificados no Armamento de Via e nas MD - Medições Detalhadas. No âmbito deste trabalho foram ainda identificados os trabalhos de via necessários a desenvolver na materialização do projecto, encontrando-se quantificados e definidos, respectivamente nas MD, MQT - Mapa de Quantidades de Trabalho e DPU – Definição de Preços Unitários.
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In this paper, two wind turbines equipped with a permanent magnet synchronous generator (PMSG) and respectively with a two-level or a multilevel converter are simulated in order to access the malfunction transient performance. Three different drive train mass models, respectively, one, two and three mass models, are considered in order to model the bending flexibility of the blades. Moreover, a fractional-order control strategy is studied comparatively to a classical integer-order control strategy. Computer simulations are carried out, and conclusions about the total harmonic distortion (THD) of the electric current injected into the electric grid are in favor of the fractional-order control strategy.
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Link do editor: http://www.igi-global.com/chapter/role-lifelong-learning-creation-european/13314
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One of the main concerns of today’s organizations is to cope with the rapid pace of change while maintaining their competitive advantage. This means that firms must be innovative, create new knowledge and have new ideas constantly. Similarly, one of the main concerns of lecturers is to help students to develop creativity. According to some authors, new ideas, new thoughts, innovation can arise in an appropriate environment and with the development and train of adequate competences and skills. This means that although some persons were born more creative than others, it is possible to help those less creative to improve their innovative capacities and competences. The question that remains now is “how”. How can we, as lecturers and educators help our students to become more creative? In this paper we describe a Portuguese case study that took place at ISCAP (School of Accountancy and Administration of Porto – Portugal), in the course of Business Communication, in the unit “Marketing Communication” (3rd year (1st Bologna cycle), 1st semester). We will describe and characterize the situation at the beginning of the semester (situation A), explain the tasks and activities proposed to students and the final result (situation A2). We will discuss differences between situation A and A2, formulate some hypotheses concerning differences and draw some recommendations.
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The dominant discourse in education and training policies, at the turn of the millennium, was on lifelong learning (LLL) in the context of a knowledge-based society. As Green points (2002, pp. 611-612) several factors contribute to this global trend: The demographic change: In most advanced countries, the average age of the population is increasing, as people live longer; The effects of globalisation: Including both economic restructuring and cultural change which have impacts on the world of education; Global economic restructuring: Which causes, for example, a more intense demand for a higher order of skills; the intensified economic competition, forcing a wave of restructuring and creating enormous pressure to train and retrain the workforce In parallel, the “significance of the international division of labour cannot be underestimated for higher education”, as pointed out by Jarvis (1999, p. 250). This author goes on to argue that globalisation has exacerbated differentiation in the labour market, with the First World converting faster to a knowledge economy and a service society, while a great deal of the actual manufacturing is done elsewhere.
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AGM and Conference in Mechelen 27 – 30 April 2010
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In recent years, power systems have experienced many changes in their paradigm. The introduction of new players in the management of distributed generation leads to the decentralization of control and decision-making, so that each player is able to play in the market environment. In the new context, it will be very relevant that aggregator players allow midsize, small and micro players to act in a competitive environment. In order to achieve their objectives, virtual power players and single players are required to optimize their energy resource management process. To achieve this, it is essential to have financial resources capable of providing access to appropriate decision support tools. As small players have difficulties in having access to such tools, it is necessary that these players can benefit from alternative methodologies to support their decisions. This paper presents a methodology, based on Artificial Neural Networks (ANN), and intended to support smaller players. In this case the present methodology uses a training set that is created using energy resource scheduling solutions obtained using a mixed-integer linear programming (MIP) approach as the reference optimization methodology. The trained network is used to obtain locational marginal prices in a distribution network. The main goal of the paper is to verify the accuracy of the ANN based approach. Moreover, the use of a single ANN is compared with the use of two or more ANN to forecast the locational marginal price.
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In this paper, a novel mixed-integer nonlinear approach is proposed to solve the short-term hydro scheduling problem in the day-ahead electricity market, considering not only head-dependency, but also start/stop of units, discontinuous operating regions and discharge ramping constraints. Results from a case study based on one of the main Portuguese cascaded hydro energy systems are presented, showing that the proposedmixed-integer nonlinear approach is proficient. Conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.
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The large penetration of intermittent resources, such as solar and wind generation, involves the use of storage systems in order to improve power system operation. Electric Vehicles (EVs) with gridable capability (V2G) can operate as a means for storing energy. This paper proposes an algorithm to be included in a SCADA (Supervisory Control and Data Acquisition) system, which performs an intelligent management of three types of consumers: domestic, commercial and industrial, that includes the joint management of loads and the charge/discharge of EVs batteries. The proposed methodology has been implemented in a SCADA system developed by the authors of this paper – the SCADA House Intelligent Management (SHIM). Any event in the system, such as a Demand Response (DR) event, triggers the use of an optimization algorithm that performs the optimal energy resources scheduling (including loads and EVs), taking into account the priorities of each load defined by the installation users. A case study considering a specific consumer with several loads and EVs is presented in this paper.