983 resultados para Reasonable profits


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Dissertação para obtenção do Grau de Mestre em Contabilidade e Finanças Orientador: Mestre, Gabriela Pinheiro

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O objetivo central deste estudo consiste em demonstrar de que forma o trabalho do auditor interno contribui no processo de gestão de riscos empresariais. Neste sentido, faz-se uma abordagem sobre o conceito de Auditoria Interna, sendo uma atividade destinada a acrescentar valor à organização na medida em que a auxilia na consecução dos seus objetivos, proporcionando-lhe informações oportunas e relevantes para a tomada de decisão. Faz também considerações ao Controlo Interno, no sentido de que as organizações vão sentir diferentes necessidades de controlo interno dependendo da sua dimensão e complexidade do negócio. O controlo interno é um processo desenvolvido pelos Orgãos de Gestão com o propósito de garantir uma segurança razoável no cumprimento dos objetivos estabelecidos. Cabe ao auditor interno auxiliar nesse sentido, ou seja, debruçar-se sobre a avaliação da adequação e eficiência do Sistema de Controlo Interno. Por fim é abordada a importância da Gestão do Risco, neste contexto as organizações têm como compromisso prioritário a implementação de mecanismos de avaliação e gestão dos riscos que possam afetar as suas operações e o cumprimento dos objetivos estratégicos definidos. A Auditoria Interna vai fornecer segurança acerca da eficácia das atividades de gestão do risco das organizações para assegurar que os principais riscos de negócio estão a ser geridos de forma apropriada bem como os sistemas de controlo interno estão a funcionar eficazmente. Ainda na gestão do risco é abordado o modelo COSO ERM, instrumento importante para as organizações na medida em que melhoram a performance e o desempenho dos controlos internos implementados e progridem para um processo de gestão do risco. Faz-se também uma breve referência sobre a Lei Sox, que veio promover uma profunda reforma na elaboração dos relatórios financeiros, no detalhe minucioso sobre os aspetos do controlo interno nas organizações e na transparência das informações divulgadas pelas organizações.

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Trabalho de projeto apresentado à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Gestão Estratégica das Relações Públicas.

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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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Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. This paper presents a methodology to provide decision support to electricity market negotiating players. This model allows integrating different strategic approaches for electricity market negotiations, and choosing the most appropriate one at each time, for each different negotiation context. This methodology is integrated in ALBidS (Adaptive Learning strategic Bidding System) – a multiagent system that provides decision support to MASCEM's negotiating agents so that they can properly achieve their goals. ALBidS uses artificial intelligence methodologies and data analysis algorithms to provide effective adaptive learning capabilities to such negotiating entities. The main contribution is provided by a methodology that combines several distinct strategies to build actions proposals, so that the best can be chosen at each time, depending on the context and simulation circumstances. The choosing process includes reinforcement learning algorithms, a mechanism for negotiating contexts analysis, a mechanism for the management of the efficiency/effectiveness balance of the system, and a mechanism for competitor players' profiles definition.

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RESUMO: Em cuidados de saúde diferenciados, a promoção da saúde e as actividades de educação para a saúde são indispensáveis à capacitação individual, habilitando a pessoa a prevenir complicações da sua patologia e a agir no sentido de exercerem um maior controlo sobre a sua própria saúde para a obtenção de ganhos em saúde. Com esta investigação pretendeu-se analisar a satisfação da pessoa transplantada hepática sobre os cuidados de enfermagem prestados, no âmbito da educação para a saúde e identificar dimensões que influenciaram a percepção e experiência da pessoa, face à preparação do regresso a casa. Foi realizado um estudo descritivo, transversal, de abordagem de investigação mista e exploratório, com orientação quantitativa e qualitativa, num movimento dedutivo-indutivo, baseado numa amostra de conveniência de 75 pessoas transplantadas hepáticas do Hospital de Curry Cabral. Os resultados foram analisados no âmbito da problemática em estudo, baseada na estrutura do movimento metodológico, ao nível das expectativas, experiência e percepção da satisfação da pessoa transplantada hepática. Neste estudo, salienta-se que os factores do domínio sócio-demográfico que influenciaram as expectativas são a idade e o tempo de internamento, assim como as experiências anteriores influenciaram a forma como a pessoa transplantada hepática recebeu as informações nesse internamento. As pessoas submetidas a transplante hepático, inquiridas neste estudo, afirmaram, em termos globais, que os cuidados de enfermagem recebidos durante o internamento, no âmbito da educação para a saúde, para o regresso a casa foram “Bons/Muito Bons” e “Razoáveis”. As expectativas, experiências anteriores, experiência com os cuidados de enfermagem e as percepções sobre os cuidados de enfermagem e a preparação para o regresso a casa são, neste contexto, reconhecidas como influenciadoras da satisfação com os cuidados de enfermagem. É imprescindível, portanto, que as actividades de educação para a saúde desenvolvidas pelos enfermeiros, usando a sua autonomia, contribuam para enfatizar o cuidar profissional em enfermagem, dando visibilidade à sua intervenção com a pessoa e/ou família no regresso a casa. SUMMARY: In differentiated healthcare, the promotion of health and health education activities are indispensable for personal empowerment, preparing the individual to prevent complications of his own disease, exercising a greater control over his own health, resulting in global health gains. This investigation was intended to analyse the satisfaction of liver transplant patients about the nursing care given, concerning health education, as well as to try and identify aspects that influenced the patient’s perception and experience when dealing with the preparation of returning home. The study was descriptive, with a mixed approach of exploratory and mixed inquiry, with qualitative and quantitative orientation, in a deductive-inductive direction. The population integrated a convenience sample of 75 liver transplant patients admitted at the Curry Cabral Hospital. The results were analysed according to the objectives, based on the methodological movement structure, level of expectations, experience and perception of the patient’s satisfaction. This study draws attention to the fact that demographic factors such as age and hospitalisation time influenced expectations, as well as previous experiences influenced the manner in which these patients received information during their hospital stay. The patients submitted to liver transplant, questioned in this study, affirmed, in a global manner, that nursing care given during admission, concerning health education for returning home were "Good/Very Good" and "Reasonable". Expectations, previous experiences, experience with and perceptions about nursing care as well as hospital discharge preparation were in this context, recognized as influences on the satisfaction of nursing care given. It is indispensable, therefore, that activities related to health education autonomously developed by nurses, contribute to emphasize the professional role of nursing care, highlighting the nurse’s intervention with the patient and/or family when returning home.

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1st European IAHR Congress,6-4 May, Edinburg, Scotland

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Dissertação de Mestrado apresentada ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Contabilidade e Finanças sob orientação de Professor Doutor Adalmiro Alvaro Malheiro de Castro Andrade Pereira

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Trabalho de Dissertação de Natureza Científica para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização em Estruturas

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The intensive use of distributed generation based on renewable resources increases the complexity of power systems management, particularly the short-term scheduling. Demand response, storage units and electric and plug-in hybrid vehicles also pose new challenges to the short-term scheduling. However, these distributed energy resources can contribute significantly to turn the shortterm scheduling more efficient and effective improving the power system reliability. This paper proposes a short-term scheduling methodology based on two distinct time horizons: hour-ahead scheduling, and real-time scheduling considering the point of view of one aggregator agent. In each scheduling process, it is necessary to update the generation and consumption operation, and the storage and electric vehicles status. Besides the new operation condition, more accurate forecast values of wind generation and consumption are available, for the resulting of short-term and very short-term methods. In this paper, the aggregator has the main goal of maximizing his profits while, fulfilling the established contracts with the aggregated and external players.

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The aggregation and management of Distributed Energy Resources (DERs) by an Virtual Power Players (VPP) is an important task in a smart grid context. The Energy Resource Management (ERM) of theses DERs can become a hard and complex optimization problem. The large integration of several DERs, including Electric Vehicles (EVs), may lead to a scenario in which the VPP needs several hours to have a solution for the ERM problem. This is the reason why it is necessary to use metaheuristic methodologies to come up with a good solution with a reasonable amount of time. The presented paper proposes a Simulated Annealing (SA) approach to determine the ERM considering an intensive use of DERs, mainly EVs. In this paper, the possibility to apply Demand Response (DR) programs to the EVs is considered. Moreover, a trip reduce DR program is implemented. The SA methodology is tested on a 32-bus distribution network with 2000 EVs, and the SA results are compared with a deterministic technique and particle swarm optimization results.

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Artificial Intelligence has been applied to dynamic games for many years. The ultimate goal is creating responses in virtual entities that display human-like reasoning in the definition of their behaviors. However, virtual entities that can be mistaken for real persons are yet very far from being fully achieved. This paper presents an adaptive learning based methodology for the definition of players’ profiles, with the purpose of supporting decisions of virtual entities. The proposed methodology is based on reinforcement learning algorithms, which are responsible for choosing, along the time, with the gathering of experience, the most appropriate from a set of different learning approaches. These learning approaches have very distinct natures, from mathematical to artificial intelligence and data analysis methodologies, so that the methodology is prepared for very distinct situations. This way it is equipped with a variety of tools that individually can be useful for each encountered situation. The proposed methodology is tested firstly on two simpler computer versus human player games: the rock-paper-scissors game, and a penalty-shootout simulation. Finally, the methodology is applied to the definition of action profiles of electricity market players; players that compete in a dynamic game-wise environment, in which the main goal is the achievement of the highest possible profits in the market.

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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.

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An intensive use of dispersed energy resources is expected for future power systems, including distributed generation, especially based on renewable sources, and electric vehicles. The system operation methods and tool must be adapted to the increased complexity, especially the optimal resource scheduling problem. Therefore, the use of metaheuristics is required to obtain good solutions in a reasonable amount of time. This paper proposes two new heuristics, called naive electric vehicles charge and discharge allocation and generation tournament based on cost, developed to obtain an initial solution to be used in the energy resource scheduling methodology based on simulated annealing previously developed by the authors. The case study considers two scenarios with 1000 and 2000 electric vehicles connected in a distribution network. The proposed heuristics are compared with a deterministic approach and presenting a very small error concerning the objective function with a low execution time for the scenario with 2000 vehicles.

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The operation of distribution networks has been facing changes with the implementation of smart grids and microgrids, and the increasing use of distributed generation. The specific case of distribution networks that accommodate residential buildings, small commerce, and distributed generation as the case of storage and PV generation lead to the concept of microgrids, in the cases that the network is able to operate in islanding mode. The microgrid operator in this context is able to manage the consumption and generation resources, also including demand response programs, obtaining profits from selling electricity to the main network. The present paper proposes a methodology for the energy resource scheduling considering power flow issues and the energy buying and selling from/to the main network in each bus of the microgrid. The case study uses a real distribution network with 25 bus, residential and commercial consumers, PV generation, and storage.