1000 resultados para Instantiation Approach


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Decision making in any environmental domain is a complex and demanding activity, justifying the development of dedicated decision support systems. Every decision is confronted with a large variety and amount of constraints to satisfy as well as contradictory interests that must be sensibly accommodated. The first stage of a project evaluation is its submission to the relevant group of public (and private) agencies. The individual role of each agency is to verify, within its domain of competence, the fulfilment of the set of applicable regulations. The scope of the involved agencies is wide and ranges from evaluation abilities on the technical or economical domains to evaluation competences on the environmental or social areas. The second project evaluation stage involves the gathering of the recommendations of the individual agencies and their justified merge to produce the final conclusion. The incorporation and accommodation of the consulted agencies opinions is of extreme importance: opinions may not only differ, but can be interdependent, complementary, irreconcilable or, simply, independent. The definition of adequate methodologies to sensibly merge, whenever possible, the existing perspectives while preserving the overall legality of the system, will lead to the making of sound justified decisions. The proposed Environmental Decision Support System models the project evaluation activity and aims to assist developers in the selection of adequate locations for their projects, guaranteeing their compliance with the applicable regulations.

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19-22 June 2012 Madrid, Spain

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The massification of electric vehicles (EVs) can have a significant impact on the power system, requiring a new approach for the energy resource management. The energy resource management has the objective to obtain the optimal scheduling of the available resources considering distributed generators, storage units, demand response and EVs. The large number of resources causes more complexity in the energy resource management, taking several hours to reach the optimal solution which requires a quick solution for the next day. Therefore, it is necessary to use adequate optimization techniques to determine the best solution in a reasonable amount of time. This paper presents a hybrid artificial intelligence technique to solve a complex energy resource management problem with a large number of resources, including EVs, connected to the electric network. The hybrid approach combines simulated annealing (SA) and ant colony optimization (ACO) techniques. The case study concerns different EVs penetration levels. Comparisons with a previous SA approach and a deterministic technique are also presented. For 2000 EVs scenario, the proposed hybrid approach found a solution better than the previous SA version, resulting in a cost reduction of 1.94%. For this scenario, the proposed approach is approximately 94 times faster than the deterministic approach.

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Trabalho de Projecto submetido à Escola Superior de Teatro e Cinema para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Teatro - especialização em Encenação.

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A schistosomiasis control program was implemented between 1974/87 in Peri-Peri,. MG (622 inhabitants). Molluscicide (niclosamide) was applied at three monthly intervals in water sources with Biomphalaria glabrata, and individuals eliminating Schistosoma mansoni eggs in the feces were treated annually with oxamniquine. From 1974 to 1983 the control measures were undertaken by staff of the "René Rachou" Research Center FIOCRUZ (CPqRR), and from 1984 to 1987 these measures were included in the Capim Branco basic health network activities. During both periods, the prevalence, incidence, intensity of infection and hepatosplenic form as well as the number of infected snails decreased significantly. The prevalence decreased from 43.5 to 4.4%, the incidence from 19.0 to 2.9%, the overall intensity of S. mansoni from 281 to 87 and of the hepatosplenic form from 5.9 to 0.0%. The results obtained suggest that the municipal management of control measures was as effective as the vertical program conducted by CPqRR staff.

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In recent years, mobile learning has emerged as an educational approach to decrease the limitation of learning location and adapt the teaching-learning process to all type of students. However, the large number and variety of Web-enabled devices poses challenges for Web content creators who want to automatic get the delivery context and adapt the content to mobile devices. This paper studies several approaches to adapt the learning content to mobile phones. It presents an architecture for deliver uniform m-Learning content to students in a higher School. The system development is organized in two phases: firstly enabling the educational content to mobile devices and then adapting it to all the heterogeneous mobile platforms. With this approach, Web authors will not need to create specialized pages for each kind of device, since the content is automatically transformed to adapt to any mobile device capabilities from WAP to XHTML MP-compliant devices.

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The efficacy, cellular uptake and specific transport of dietary antioxidants to target organs, tissues and cells remains the most important setback for their application in the treatment of oxidative-stress related disorders and in particular in neurodegenerative diseases, as brain targeting remains a still unsolved challenge. Nanotechnology based delivery systems can be a solution for the above mentioned problems, specifically in the case of targeting dietary antioxidants with neuroprotective activity. Nanotechnology-based delivery systems can protect antioxidants from degradation, improve their physicochemical drug-like properties and in turn their bioavailability. The impact of nanomedicine in the improvement of the performance of dietary antioxidants, as protective agents in oxidative- stress events, specifically through the use of drug delivery systems, is highlighted in this review as well as the type of nanomaterials regularly used for drug delivery purposes. From the data one can conclude that the research combining (dietary) antioxidants and nanotechnology, namely as a therapeutic solution for neurodegenerative diseases, is still in a very early stage. So, a huge research area remains to be explored that hopefully will yield new and effective neuroprotective therapeutic agents in a foreseeable future.

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In this paper, we present a deterministic approach to tsunami hazard assessment for the city and harbour of Sines, Portugal, one of the test sites of project ASTARTE (Assessment, STrategy And Risk Reduction for Tsunamis in Europe). Sines has one of the most important deep-water ports, which has oil-bearing, petrochemical, liquid-bulk, coal, and container terminals. The port and its industrial infrastructures face the ocean southwest towards the main seismogenic sources. This work considers two different seismic zones: the Southwest Iberian Margin and the Gloria Fault. Within these two regions, we selected a total of six scenarios to assess the tsunami impact at the test site. The tsunami simulations are computed using NSWING, a Non-linear Shallow Water model wIth Nested Grids. In this study, the static effect of tides is analysed for three different tidal stages: MLLW (mean lower low water), MSL (mean sea level), and MHHW (mean higher high water). For each scenario, the tsunami hazard is described by maximum values of wave height, flow depth, drawback, maximum inundation area and run-up. Synthetic waveforms are computed at virtual tide gauges at specific locations outside and inside the harbour. The final results describe the impact at the Sines test site considering the single scenarios at mean sea level, the aggregate scenario, and the influence of the tide on the aggregate scenario. The results confirm the composite source of Horseshoe and Marques de Pombal faults as the worst-case scenario, with wave heights of over 10 m, which reach the coast approximately 22 min after the rupture. It dominates the aggregate scenario by about 60 % of the impact area at the test site, considering maximum wave height and maximum flow depth. The HSMPF scenario inundates a total area of 3.5 km2. © Author(s) 2015.

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In this article we provide homotopy solutions of a cancer nonlinear model describing the dynamics of tumor cells in interaction with healthy and effector immune cells. We apply a semi-analytic technique for solving strongly nonlinear systems – the Step Homotopy Analysis Method (SHAM). This algorithm, based on a modification of the standard homotopy analysis method (HAM), allows to obtain a one-parameter family of explicit series solutions. By using the homotopy solutions, we first investigate the dynamical effect of the activation of the effector immune cells in the deterministic dynamics, showing that an increased activation makes the system to enter into chaotic dynamics via a period-doubling bifurcation scenario. Then, by adding demographic stochasticity into the homotopy solutions, we show, as a difference from the deterministic dynamics, that an increased activation of the immune cells facilitates cancer clearance involving tumor cells extinction and healthy cells persistence. Our results highlight the importance of therapies activating the effector immune cells at early stages of cancer progression.

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The fractal geometry is used to model of a naturally fractured reservoir and the concept of fractional derivative is applied to the diffusion equation to incorporate the history of fluid flow in naturally fractured reservoirs. The resulting fractally fractional diffusion (FFD) equation is solved analytically in the Laplace space for three outer boundary conditions. The analytical solutions are used to analyze the response of a naturally fractured reservoir considering the anomalous behavior of oil production. Several synthetic examples are provided to illustrate the methodology proposed in this work and to explain the diffusion process in fractally fractured systems.

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Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Electrotécnica, Especialidade de Sistemas Digitais, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

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Radiotherapy is one of the main treatments used against cancer. Radiotherapy uses radiation to destroy cancerous cells trying, at the same time, to minimize the damages in healthy tissues. The planning of a radiotherapy treatment is patient dependent, resulting in a lengthy trial and error procedure until a treatment complying as most as possible with the medical prescription is found. Intensity Modulated Radiation Therapy (IMRT) is one technique of radiation treatment that allows the achievement of a high degree of conformity between the area to be treated and the dose absorbed by healthy tissues. Nevertheless, it is still not possible to eliminate completely the potential treatments’ side-effects. In this retrospective study we use the clinical data from patients with head-and-neck cancer treated at the Portuguese Institute of Oncology of Coimbra and explore the possibility of classifying new and untreated patients according to the probability of xerostomia 12 months after the beginning of IMRT treatments by using a logistic regression approach. The results obtained show that the classifier presents a high discriminative ability in predicting the binary response “at risk for xerostomia at 12 months”

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Conservação e Restauro

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The Evidence Accumulation Clustering (EAC) paradigm is a clustering ensemble method which derives a consensus partition from a collection of base clusterings obtained using different algorithms. It collects from the partitions in the ensemble a set of pairwise observations about the co-occurrence of objects in a same cluster and it uses these co-occurrence statistics to derive a similarity matrix, referred to as co-association matrix. The Probabilistic Evidence Accumulation for Clustering Ensembles (PEACE) algorithm is a principled approach for the extraction of a consensus clustering from the observations encoded in the co-association matrix based on a probabilistic model for the co-association matrix parameterized by the unknown assignments of objects to clusters. In this paper we extend the PEACE algorithm by deriving a consensus solution according to a MAP approach with Dirichlet priors defined for the unknown probabilistic cluster assignments. In particular, we study the positive regularization effect of Dirichlet priors on the final consensus solution with both synthetic and real benchmark data.

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Mestrado em Engenharia Informática - Área de Especialização em Tecnologias do Conhecimento e Decisão