860 resultados para multi-concern autonomic management


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Geographic information systems give us the possibility to analyze, produce, and edit geographic information. Furthermore, these systems fall short on the analysis and support of complex spatial problems. Therefore, when a spatial problem, like land use management, requires a multi-criteria perspective, multi-criteria decision analysis is placed into spatial decision support systems. The analytic hierarchy process is one of many multi-criteria decision analysis methods that can be used to support these complex problems. Using its capabilities we try to develop a spatial decision support system, to help land use management. Land use management can undertake a broad spectrum of spatial decision problems. The developed decision support system had to accept as input, various formats and types of data, raster or vector format, and the vector could be polygon line or point type. The support system was designed to perform its analysis for the Zambezi river Valley in Mozambique, the study area. The possible solutions for the emerging problems had to cover the entire region. This required the system to process large sets of data, and constantly adjust to new problems’ needs. The developed decision support system, is able to process thousands of alternatives using the analytical hierarchy process, and produce an output suitability map for the problems faced.

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Double degree. A Work Project presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA- School of Business and Economics and Warsaw School of Economics

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The way in which electricity networks operate is going through a period of significant change. Renewable generation technologies are having a growing presence and increasing penetrations of generation that are being connected at distribution level. Unfortunately, a renewable energy source is most of the time intermittent and needs to be forecasted. Current trends in Smart grids foresee the accommodation of a variety of distributed generation sources including intermittent renewable sources. It is also expected that smart grids will include demand management resources, widespread communications and control technologies required to use demand response are needed to help the maintenance in supply-demand balance in electricity systems. Consequently, smart household appliances with controllable loads will be likely a common presence in our homes. Thus, new control techniques are requested to manage the loads and achieve all the potential energy present in intermittent energy sources. This thesis is focused on the development of a demand side management control method in a distributed network, aiming the creation of greater flexibility in demand and better ease the integration of renewable technologies. In particular, this work presents a novel multi-agent model-based predictive control method to manage distributed energy systems from the demand side, in presence of limited energy sources with fluctuating output and with energy storage in house-hold or car batteries. Specifically, here is presented a solution for thermal comfort which manages a limited shared energy resource via a demand side management perspective, using an integrated approach which also involves a power price auction and an appliance loads allocation scheme. The control is applied individually to a set of Thermal Control Areas, demand units, where the objective is to minimize the energy usage and not exceed the limited and shared energy resource, while simultaneously indoor temperatures are maintained within a comfort frame. Thermal Control Areas are overall thermodynamically connected in the distributed environment and also coupled by energy related constraints. The energy split is performed based on a fixed sequential order established from a previous completed auction wherein the bids are made by each Thermal Control Area, acting as demand side management agents, based on the daily energy price. The developed solutions are explained with algorithms and are applied to different scenarios, being the results explanatory of the benefits of the proposed approaches.

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For the purpose of analyzing how did the considerable increase in the Portuguese tourism has influenced its cultural sector, this paper seeks to explore how has the company AntiFrame | Art Consulting replied to it. Arts Management: Contemporary Art Guides. Alibi – The Portuguese Case reviews some Arts Management literature whilst a multi-method approach is used. A market research was conducted, in which existing contemporary guides were analyzed as well as interviews made to tourists in Lisbon. Findings show that there is a flaw in the Portuguese contemporary art market, which the project Alibi aims to solve. Metrics on how the project’s results should be monitored, as part of a follow-up phase, were included, as well as limitations.

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Traffic Engineering (TE) approaches are increasingly impor- tant in network management to allow an optimized configuration and resource allocation. In link-state routing, the task of setting appropriate weights to the links is both an important and a challenging optimization task. A number of different approaches has been put forward towards this aim, including the successful use of Evolutionary Algorithms (EAs). In this context, this work addresses the evaluation of three distinct EAs, a single and two multi-objective EAs, in two tasks related to weight setting optimization towards optimal intra-domain routing, knowing the network topology and aggregated traffic demands and seeking to mini- mize network congestion. In both tasks, the optimization considers sce- narios where there is a dynamic alteration in the state of the system, in the first considering changes in the traffic demand matrices and in the latter considering the possibility of link failures. The methods will, thus, need to simultaneously optimize for both conditions, the normal and the altered one, following a preventive TE approach towards robust configurations. Since this can be formulated as a bi-objective function, the use of multi-objective EAs, such as SPEA2 and NSGA-II, came nat- urally, being those compared to a single-objective EA. The results show a remarkable behavior of NSGA-II in all proposed tasks scaling well for harder instances, and thus presenting itself as the most promising option for TE in these scenarios.

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The research described in this thesis has been developed as a part of the Reliability and Field Data Management for Multi-component Products (REFIDAM) Project. This project was founded under the Applied Research Grants Scheme administered by Enterprise Ireland. The project was a partnership between Galway-Mayo Institute of Technology and Thermo King Europe. The project aimed to develop a system in order to manage the information required for reliability assessment and improvement of multi-component products, by establishing information flows within the company and information exchange with fleet users.

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The research described in this thesis has been developed as a part of the Reliability and Field Data Management for Multi-Component Products (REFIDAM) Project. This project was funded under the Applied Research Grants Scheme administered by Enterprise Ireland. The project was a partnership between Galway-Mayo Institute of Technology and an industrial company, Thermo King Europe. The project aimed to develop a system to manage the information required for maintenance costing, cost of ownership, reliability assessment and improvement of multi-component products, by establishing information flows between the customer network and across the Thermo King organisation.

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Background: Although resistance exercise training is part of cardiovascular rehabilitation programs, little is known about its role on the cardiac and autonomic function after myocardial infarction. Objective: To evaluate the effects of resistance exercise training, started early after myocardial infarction, on cardiac function, hemodynamic profile, and autonomic modulation in rats. Methods: Male Wistar rats were divided into four groups: sedentary control, trained control, sedentary infarcted and trained infarcted rats. Each group with n = 9 rats. The animals underwent maximum load test and echocardiography at the beginning and at the end of the resistance exercise training (in an adapted ladder, 40% to 60% of the maximum load test, 3 months, 5 days/week). At the end, hemodynamic, baroreflex sensitivity and autonomic modulation assessments were made. Results: The maximum load test increased in groups trained control (+32%) and trained infarcted (+46%) in relation to groups sedentary control and sedentary infarcted. Although no change occurred regarding the myocardial infarction size and systolic function, the E/A ratio (-23%), myocardial performance index (-39%) and systolic blood pressure (+6%) improved with resistance exercise training in group trained infarcted. Concomitantly, the training provided additional benefits in the high frequency bands of the pulse interval (+45%), as well as in the low frequency band of systolic blood pressure (-46%) in rats from group trained infarcted in relation to group sedentary infarcted. Conclusion: Resistance exercise training alone may be an important and safe tool in the management of patients after myocardial infarction, considering that it does not lead to significant changes in the ventricular function, reduces the global cardiac stress, and significantly improves the vascular and cardiac autonomic modulation in infarcted rats.

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Visual data mining, multi-dimensional scaling, POLARMAP, Sammon's mapping, clustering, outlier detection

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Invasive plants can have different effects of ecosystem functioning and on the provision of ecosystem services, from strongly deleterious impacts to positive effects. The nature and intensity of such effects will depend on the service and ecosystem being considered, but also on features of life strategies of invaders that influence their invasiveness as well as their influence of key processes of receiving ecosystems. To address the combined effect of these various factors we developed a robust and efficient methodological framework that allows to identify areas of possible conflict between ecosystem services and alien invasive plants, considering interactions between landscape invasibility and species invasiveness. Our framework combines the statistical robustness of multi-model inference, efficient techniques to map ecosystem services, and life strategies as a functional link between invasion, functional changes and potential provision of services by invaded ecosystems. The framework was applied to a test region in Portugal, for which we could successfully predict the current patterns of plant invasion, of ecosystem service provision, and finally of probable conflict (expressing concern for negative impacts, and value for positive impacts on services) between alien species richness (total and per plant life strategy) and the potential provision of selected services. Potential conflicts were identified for all combinations of plant strategy and ecosystem service, with an emphasis for those concerning conflicts with carbon sequestration, water regulation and wood production. Lower levels of conflict were obtained between invasive plant strategies and the habitat for biodiversity supporting service. The added value of the proposed framework in the context of landscape management and planning is discussed in perspective of anticipation of conflicts, mitigation of negative impacts, and potentiation of positive effects of plant invasions on ecosystems and their services.

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La gestión de recursos en los procesadores multi-core ha ganado importancia con la evolución de las aplicaciones y arquitecturas. Pero esta gestión es muy compleja. Por ejemplo, una misma aplicación paralela ejecutada múltiples veces con los mismos datos de entrada, en un único nodo multi-core, puede tener tiempos de ejecución muy variables. Hay múltiples factores hardware y software que afectan al rendimiento. La forma en que los recursos hardware (cómputo y memoria) se asignan a los procesos o threads, posiblemente de varias aplicaciones que compiten entre sí, es fundamental para determinar este rendimiento. La diferencia entre hacer la asignación de recursos sin conocer la verdadera necesidad de la aplicación, frente a asignación con una meta específica es cada vez mayor. La mejor manera de realizar esta asignación és automáticamente, con una mínima intervención del programador. Es importante destacar, que la forma en que la aplicación se ejecuta en una arquitectura no necesariamente es la más adecuada, y esta situación puede mejorarse a través de la gestión adecuada de los recursos disponibles. Una apropiada gestión de recursos puede ofrecer ventajas tanto al desarrollador de las aplicaciones, como al entorno informático donde ésta se ejecuta, permitiendo un mayor número de aplicaciones en ejecución con la misma cantidad de recursos. Así mismo, esta gestión de recursos no requeriría introducir cambios a la aplicación, o a su estrategia operativa. A fin de proponer políticas para la gestión de los recursos, se analizó el comportamiento de aplicaciones intensivas de cómputo e intensivas de memoria. Este análisis se llevó a cabo a través del estudio de los parámetros de ubicación entre los cores, la necesidad de usar la memoria compartida, el tamaño de la carga de entrada, la distribución de los datos dentro del procesador y la granularidad de trabajo. Nuestro objetivo es identificar cómo estos parámetros influyen en la eficiencia de la ejecución, identificar cuellos de botella y proponer posibles mejoras. Otra propuesta es adaptar las estrategias ya utilizadas por el Scheduler con el fin de obtener mejores resultados.

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The problem of waste management is causing growing concern due to increasing generation rates, the emissions into soil, water and air, the social conflicts derived from the election of disposal sites and the loss of resources and energy among others. In this work, an innovative methodology is used to enable a better understanding of the waste generation and management system in Italy. Two new waste indicators are built to complement the conventional indicators used by official statistics. Then a multi-scale analysis of the Density of Waste Disposed (DWD) is carried out to highlight the territorial diversity of waste performances and test its contribution to detect plausible risky areas. Starting from Italian regions, the scale down goes on to the provincial level and, only for the region of Campania, the municipal one. First, the analysis shows that the DWD is able to complement the information provided by the conventional waste indicators. Second, the analysis shows the limitations of using a unique institutional solution to waste management problems. In this sense the multi-scale analysis provides with a more realistic picture of Italian waste system than using a single scale.

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This paper presents the Juste-Neige system for predicting the snow height on the ski runs of a resort using a multi-agent simulation software. Its aim is to facilitate snow cover management in order to i) reduce the production cost of artificial snow and to improve the profit margin for the companies managing the ski resorts; and ii) to reduce the water and energy consumption, and thus to reduce the environmental impact, by producing only the snow needed for a good skiing experience. The software provides maps with the predicted snow heights for up to 13 days. On these maps, the areas most exposed to snow erosion are highlighted. The software proceeds in three steps: i) interpolation of snow height measurements with a neural network; ii) local meteorological forecasts for every ski resort; iii) simulation of the impact caused by skiers using a multi-agent system. The software has been evaluated in the Swiss ski resort of Verbier and provides useful predictions.