78 resultados para Dynamic Changes
Resumo:
Controlled fires in forest areas are frequently used in most Mediterranean countries as a preventive technique to avoid severe wildfires in summer season. In Portugal, this forest management method of fuel mass availability is also used and has shown to be beneficial as annual statistical reports confirm that the decrease of wildfires occurrence have a direct relationship with the controlled fire practice. However prescribed fire can have serious side effects in some forest soil properties. This work shows the changes that occurred in some forest soils properties after a prescribed fire action. The experiments were carried out in soil cover over a natural site of Andaluzitic schist, in Gramelas, Caminha, Portugal, that had not been burn for four years. The composed soil samples were collected from five plots at three different layers (0-3cm, 3-6cm and 6-18cm) during a three-year monitoring period after the prescribed burning. Principal Component Analysis was used to reach the presented conclusions.
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This work deals with the numerical simulation of air stripping process for the pre-treatment of groundwater used in human consumption. The model established in steady state presents an exponential solution that is used, together with the Tau Method, to get a spectral approach of the solution of the system of partial differential equations associated to the model in transient state.
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Trabalho de Projeto Apresentado ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Auditoria, sob orientação do Mestre Carlos Mendes e coorientação da Engª Sónia Rodrigues
Resumo:
Dynamic and distributed environments are hard to model since they suffer from unexpected changes, incomplete knowledge, and conflicting perspectives and, thus, call for appropriate knowledge representation and reasoning (KRR) systems. Such KRR systems must handle sets of dynamic beliefs, be sensitive to communicated and perceived changes in the environment and, consequently, may have to drop current beliefs in face of new findings or disregard any new data that conflicts with stronger convictions held by the system. Not only do they need to represent and reason with beliefs, but also they must perform belief revision to maintain the overall consistency of the knowledge base. One way of developing such systems is to use reason maintenance systems (RMS). In this paper we provide an overview of the most representative types of RMS, which are also known as truth maintenance systems (TMS), which are computational instances of the foundations-based theory of belief revision. An RMS module works together with a problem solver. The latter feeds the RMS with assumptions (core beliefs) and conclusions (derived beliefs), which are accompanied by their respective foundations. The role of the RMS module is to store the beliefs, associate with each belief (core or derived belief) the corresponding set of supporting foundations and maintain the consistency of the overall reasoning by keeping, for each represented belief, the current supporting justifications. Two major approaches are used to reason maintenance: single-and multiple-context reasoning systems. Although in the single-context systems, each belief is associated to the beliefs that directly generated it—the justification-based TMS (JTMS) or the logic-based TMS (LTMS), in the multiple context counterparts, each belief is associated with the minimal set of assumptions from which it can be inferred—the assumption-based TMS (ATMS) or the multiple belief reasoner (MBR).
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In future power systems, in the smart grid and microgrids operation paradigms, consumers can be seen as an energy resource with decentralized and autonomous decisions in the energy management. It is expected that each consumer will manage not only the loads, but also small generation units, heating systems, storage systems, and electric vehicles. Each consumer can participate in different demand response events promoted by system operators or aggregation entities. This paper proposes an innovative method to manage the appliances on a house during a demand response event. The main contribution of this work is to include time constraints in resources management, and the context evaluation in order to ensure the required comfort levels. The dynamic resources management methodology allows a better resources’ management in a demand response event, mainly the ones of long duration, by changing the priorities of loads during the event. A case study with two scenarios is presented considering a demand response with 30 min duration, and another with 240 min (4 h). In both simulations, the demand response event proposes the power consumption reduction during the event. A total of 18 loads are used, including real and virtual ones, controlled by the presented house management system.
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We consider an optimal control problem with a deterministic finite horizon and state variable dynamics given by a Markov-switching jump–diffusion stochastic differential equation. Our main results extend the dynamic programming technique to this larger family of stochastic optimal control problems. More specifically, we provide a detailed proof of Bellman’s optimality principle (or dynamic programming principle) and obtain the corresponding Hamilton–Jacobi–Belman equation, which turns out to be a partial integro-differential equation due to the extra terms arising from the Lévy process and the Markov process. As an application of our results, we study a finite horizon consumption– investment problem for a jump–diffusion financial market consisting of one risk-free asset and one risky asset whose coefficients are assumed to depend on the state of a continuous time finite state Markov process. We provide a detailed study of the optimal strategies for this problem, for the economically relevant families of power utilities and logarithmic utilities.
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Introduction: Healthcare improvements have allowed prevention but have also increased life expectancy, resulting in more people being at risk. Our aim was to analyse the separate effects of age, period and cohort on incidence rates by sex in Portugal, 2000–2008. Methods: From the National Hospital Discharge Register, we selected admissions (aged ≥49 years) with hip fractures (ICD9-CM, codes 820.x) caused by low/moderate trauma (falls from standing height or less), readmissions and bone cancer cases. We calculated person-years at risk using population data from Statistics Portugal. To identify period and cohort effects for all ages, we used an age–period–cohort model (1-year intervals) followed by generalised additive models with a negative binomial distribution of the observed incidence rates of hip fractures. Results: There were 77,083 hospital admissions (77.4 % women). Incidence rates increased exponentially with age for both sexes (age effect). Incidence rates fell after 2004 for women and were random for men (period effect). There was a general cohort effect similar in both sexes; risk of hip fracture altered from an increasing trend for those born before 1930 to a decreasing trend following that year. Risk alterations (not statistically significant) coincident with major political and economic change in the history of Portugal were observed around birth cohorts 1920 (stable–increasing), 1940 (decreasing–increasing) and 1950 (increasing–decreasing only among women). Conclusions: Hip fracture risk was higher for those born during major economically/politically unstable periods. Although bone quality reflects lifetime exposure, conditions at birth may determine future risk for hip fractures.
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Dissertação de Mestrado apresentada ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Auditoria, sob orientação do Doutor Eduardo Sá e Silva, Professor Adjunto do Instituto Superior de Contabilidade e Administração do Porto
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This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.
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This paper studies the dynamical properties of systems with backlash and impact phenomena. This type of non-linearity can be tackled in the perspective of the fractional calculus theory. Fractional and integer order models are compared and their influence upon the emerging dynamics is analysed. It is demonstrated that fractional models can memorize dynamical effects due to multiple micro-collisions.
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Introdução: Lesões como o AVE interferem com a capacidade de recrutar níveis adequados de atividade muscular, podendo levar ao aparecimento de movimentos compensatórios como a excessiva translação anterior do tronco, associada ao gesto de alcance. Objetivos: Descrever a relação entre a atividade dos estabilizadores da omoplata e o movimento compensatório do tronco no gesto de alcance, em 4 indivíduos pós AVE. Pretendeu-se também analisar o papel dos estabilizadores da omoplata na função do membro superior. Métodos: Quatro indivíduos com diagnóstico de AVE, que apresentavam alterações no nível de actividade dos estabilizadores da omoplata contralesional, foram sujeitos a uma avaliação realizada em três momentos, antes (M0), durante (M1) e após (M2) e a um período de intervenção, segundo os princípios do Conceito de Bobath. Recorreu-se à electromiografia de superfície para avaliar a atividade e o timming dos músculos grande dorsal, trapézio superior e trapézio inferior do hemicorpo contralesional e ao software de Avaliação Postural (SAPO) para analisar o deslocamento do tronco no sentido anterior, associados à realização do gesto de alcance. Foram aplicadas as escalas RPS e MESUPES para avaliar as componentes de movimento do gesto de alcance e a função do membro superior, respetivamente. Recorreu-se ao registo fotográfico para análise dos componentes de movimento na posição de sentado e em pé.Resultados: Os dados eletromiográficos registam atividade dos estabilizadores da omoplata unicamente num indivíduo em M2. A análise do deslocamento anterior do tronco revela melhorias em M1 em todos os indivíduos, sendo que em M2 essa evolução positiva não foi observada em três dos participantes. Entre M0 e M2, na escala RPS registam-se melhorias de 7 a 9 pontos no alvo próximo e de 5 a 10 pontos no alvo distante. Na escala MESUPES verificam-se melhorias entre 5 a 18 pontos na sub-escala braço e entre 5 a 8 pontos na sub-escala mão, em M2. A avaliação do registo fotográfico revela modificações nos componentes de movimento dos quatro indivíduos, nomeadamente na integração dos MI na base de suporte, na atividade do tronco inferior e superior e no alinhamento do MS contralesional. Conclusão: A melhoria do nível da atividade dos estabilizadores dinâmicos da omoplata sugere ter influência na diminuição do movimento compensatório do tronco no gesto de alcance e parece ter um papel na melhoria da eficácia distal do MS do mesmo lado.
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A revision of several paths for the Quality journey is presented: from Quality Gurus and Total Quality Management (TQM) models to the ISO 9000 International Standards Series. Since ISO 9001:2008 is now in the revision process to the expected ISO 9001:2015 version, an analysis is made of he proposed changes and the underlying reasons and the impacts foreseen on the more than 1.3 Million certified organizations. This revision should be a step towards TQM and reflect the changes of an increasingly complex, demanding and dynamic environment, while assuring that complying organizations are able to provide conformity products and services that satisfy their customers. Major benefits are expected such as less emphasis on documentation and new/reinforced approaches: consideration of Organizational Context and (relevant) Stakeholders, Risk Based thinking and Knowledge Management.
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Electricity markets are complex environments with very particular characteristics. A critical issue concerns the constant changes they are subject to. This is a result of the electricity markets’ restructuring, performed so that the competitiveness could be increased, but with exponential implications in the increase of the complexity and unpredictability in those markets’ scope. The constant growth in markets unpredictability resulted in an amplified need for market intervenient entities in foreseeing market behavior. The need for understanding the market mechanisms and how the involved players’ interaction affects the outcomes of the markets, contributed to the growth of usage of simulation tools. Multi-agent based software is particularly well fitted to analyze dynamic and adaptive systems with complex interactions among its constituents, such as electricity markets. This paper presents the Multi-Agent System for Competitive Electricity Markets (MASCEM) – a simulator based on multi-agent technology that provides a realistic platform to simulate electricity markets, the numerous negotiation opportunities and the participating entities.
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The restructuring of electricity markets, conducted to increase the competition in this sector, and decrease the electricity prices, brought with it an enormous increase in the complexity of the considered mechanisms. The electricity market became a complex and unpredictable environment, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. Software tools became, therefore, essential to provide simulation and decision support capabilities, in order to potentiate the involved players’ actions. This paper presents the development of a metalearner, applied to the decision support of electricity markets’ negotiation entities. The proposed metalearner executes a dynamic artificial neural network to create its own output, taking advantage on several learning algorithms implemented in ALBidS, an adaptive learning system that provides decision support to electricity markets’ players. The proposed metalearner considers different weights for each strategy, depending on its individual quality of performance. The results of the proposed method are studied and analyzed in scenarios based on real electricity markets’ data, using MASCEM - a multi-agent electricity market simulator that simulates market players’ operation in the market.