928 resultados para Cross-sector network
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OBJETIVO: Investigar la percepción y acción del gremio médico en el marco de la descentralización del Sector de Salud en dos estados de México, Guanajuato y Sonora. MÉTODOS: Se han utilizado técnicas cualitativas de investigación. Fueron realizadas 35 entrevistas, semiestructuradas, en total entre los dos estados, a médicos colegiados, Guanajuato y Sonora, tanto de instituciones públicas como privadas y representantes de las asociaciones gremiales y sindicales. RESULTADOS: Para el gremio médico de los dos estados investigados, la descentralización ha implicado en inseguridad, como resultado de la falta de claridad en la regulación del Sector de Salud. La acción de los Colegios de Médicos de ambos estados, se tradujo en una mayor politización de los Colegios de Médicos estatales, en la elaboración de propuestas con el objetivo de incidir en el control del mercado laboral médico de dichos estados y participación en la estructura de poder regional. CONCLUSIONES: La investigación comprueba una readaptación del gremio médico en el ámbito regional, indicando su permanencia como grupo de poder. Contrariamente a lo que informa la literatura estadounidense en México, los médicos han logrado influenciar en la regulación, con la finalidad de no perder su status privilegiado dentro de la competencia existente.
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XV Encuentro AECA "Nuevos caminos para Europa: El papel de las empresas y los gobiernos" Organizado por AECA, CICF, IPCA Ofir-Esposende, 20 y 21 de septiembre de 2012
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O catálogo é um produto de comunicação com presença forte no mundo da moda, reflexo por excelência de cada coleção e imagem de marca. Verifica-se que os critérios objectivos de avaliação dos catálogos não foram ainda alvo de uma análise estruturada e aprofundada, apesar da importância que possuem para as empresas do sector do Vestuário. Assim, decidiuse estudar os elementos que definem o nível de qualidade estética e gráfica dos catálogos de vestuário. Analisaram-se catálogos de marcas portuguesas e internacionais da indústria da moda cuja qualidade é reconhecida pelos profissionais de design. Como resultado desse estudo foi criada a Matriz AQC - Matriz de Avaliação da Qualidade dos Catálogos Produto e a Matriz AQC – Matriz de avaliação da Qualidade dos Catálogos Imagem.
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Integrated manufacturing constitutes a complex system made of heterogeneous information and control subsystems. Those subsystems are not designed to the cooperation. Typically each subsystem automates specific processes, and establishes closed application domains, therefore it is very difficult to integrate it with other subsystems in order to respond to the needed process dynamics. Furthermore, to cope with ever growing marketcompetition and demands, it is necessary for manufacturing/enterprise systems to increase their responsiveness based on up-to-date knowledge and in-time data gathered from the diverse information and control systems. These have created new challenges for manufacturing sector, and even bigger challenges for collaborative manufacturing. The growing complexity of the information and communication technologies when coping with innovative business services based on collaborative contributions from multiple stakeholders, requires novel and multidisciplinary approaches. Service orientation is a strategic approach to deal with such complexity, and various stakeholders' information systems. Services or more precisely the autonomous computational agents implementing the services, provide an architectural pattern able to cope with the needs of integrated and distributed collaborative solutions. This paper proposes a service-oriented framework, aiming to support a virtual organizations breeding environment that is the basis for establishing short or long term goal-oriented virtual organizations. The notion of integrated business services, where customers receive some value developed through the contribution from a network of companies is a key element.
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Dissertação de Mestrado em Finanças Empresariais
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OBJECTIVE: Voluntary HIV counseling and testing are provided to all Brazilian pregnant women with the purpose of reducing mother-to-child HIV transmission. The purpose of the study was to assess characteristics of HIV testing and identify factors associated with HIV counseling and testing. METHODS: A cross-sectional study was carried out comprising 1,658 mothers living in Porto Alegre, Brazil. Biological, reproductive and social variables were obtained from mothers by means of a standardized questionnaire. Being counseling about HIV testing was the dependent variable. Confidence intervals, chi-square test and hierarchical logistic model were used to determine the association between counseling and maternal variables. RESULTS: Of 1,658 mothers interviewed, 1,603 or 96.7% (95% CI: 95.7-97.5) underwent HIV testing, and 51 or 3.1% (95% CI: 2.3-4.0) were not tested. Four (0.2%) refused to undergo testing after counseling. Of 51 women not tested in this study, 30 had undergone the testing previously. Of 1,603 women tested, 630 or 39.3% (95% CI: 36.9-41.7) received counseling, 947 or 59.2% (95% CI: 56.6-61.5) did not, and 26 (1.6%) did not inform. Low income, lack of prenatal care, late beginning of prenatal care, use of rapid testing, and receiving prenatal in the public sector were variables independently associated with a lower probability of getting counseling about HIV testing. CONCLUSIONS: The study findings confirmed the high rate of prenatal HIV testing in Porto Alegre. However, women coming from less privileged social groups were less likely to receive information and benefit from counseling.
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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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Smart Grids (SGs) appeared as the new paradigm for power system management and operation, being designed to integrate large amounts of distributed energy resources. This new paradigm requires a more efficient Energy Resource Management (ERM) and, simultaneously, makes this a more complex problem, due to the intensive use of distributed energy resources (DER), such as distributed generation, active consumers with demand response contracts, and storage units. This paper presents a methodology to address the energy resource scheduling, considering an intensive use of distributed generation and demand response contracts. A case study of a 30 kV real distribution network, including a substation with 6 feeders and 937 buses, is used to demonstrate the effectiveness of the proposed methodology. This network is managed by six virtual power players (VPP) with capability to manage the DER and the distribution network.
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This paper presents a methodology that aims to increase the probability of delivering power to any load point of the electrical distribution system by identifying new investments in distribution components. The methodology is based on statistical failure and repair data of the distribution power system components and it uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A mixed integer non-linear optimization technique is developed to identify adequate investments in distribution networks components that allow increasing the availability level for any customer in the distribution system at minimum cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a real distribution network.
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We study a model consisting of particles with dissimilar bonding sites ("patches"), which exhibits self-assembly into chains connected by Y-junctions, and investigate its phase behaviour by both simulations and theory. We show that, as the energy cost epsilon(j) of forming Y-junctions increases, the extent of the liquid-vapour coexistence region at lower temperatures and densities is reduced. The phase diagram thus acquires a characteristic "pinched" shape in which the liquid branch density decreases as the temperature is lowered. To our knowledge, this is the first model in which the predicted topological phase transition between a fluid composed of short chains and a fluid rich in Y-junctions is actually observed. Above a certain threshold for epsilon(j), condensation ceases to exist because the entropy gain of forming Y-junctions can no longer offset their energy cost. We also show that the properties of these phase diagrams can be understood in terms of a temperature-dependent effective valence of the patchy particles. (C) 2011 American Institute of Physics. [doi: 10.1063/1.3605703]
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We introduce a microscopic model for particles with dissimilar patches which displays an unconventional "pinched'' phase diagram, similar to the one predicted by Tlusty and Safran in the context of dipolar fluids [Science 290, 1328 (2000)]. The model-based on two types of patch interactions, which account, respectively, for chaining and branching of the self-assembled networks-is studied both numerically via Monte Carlo simulations and theoretically via first-order perturbation theory. The dense phase is rich in junctions, while the less-dense phase is rich in chain ends. The model provides a reference system for a deep understanding of the competition between condensation and self-assembly into equilibrium-polymer chains.
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In competitive electricity markets with deep concerns for the efficiency level, demand response programs gain considerable significance. As demand response levels have decreased after the introduction of competition in the power industry, new approaches are required to take full advantage of demand response opportunities. Grid operators and utilities are taking new initiatives, recognizing the value of demand response for grid reliability and for the enhancement of organized spot markets’ efficiency. This paper proposes a methodology for the selection of the consumers that participate in an event, which is the responsibility of the Portuguese transmission network operator. The proposed method is intended to be applied in the interruptibility service implemented in Portugal, in convergence with Spain, in the context of the Iberian electricity market. This method is based on the calculation of locational marginal prices (LMP) which are used to support the decision concerning the consumers to be schedule for participation. The proposed method has been computationally implemented and its application is illustrated in this paper using a 937 bus distribution network with more than 20,000 consumers.
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This paper presents an artificial neural network applied to the forecasting of electricity market prices, with the special feature of being dynamic. The dynamism is verified at two different levels. The first level is characterized as a re-training of the network in every iteration, so that the artificial neural network can able to consider the most recent data at all times, and constantly adapt itself to the most recent happenings. The second level considers the adaptation of the neural network’s execution time depending on the circumstances of its use. The execution time adaptation is performed through the automatic adjustment of the amount of data considered for training the network. This is an advantageous and indispensable feature for this neural network’s integration in ALBidS (Adaptive Learning strategic Bidding System), a multi-agent system that has the purpose of providing decision support to the market negotiating players of MASCEM (Multi-Agent Simulator of Competitive Electricity Markets).
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In smart grids context, the distributed generation units based in renewable resources, play an important rule. The photovoltaic solar units are a technology in evolution and their prices decrease significantly in recent years due to the high penetration of this technology in the low voltage and medium voltage networks supported by governmental policies and incentives. This paper proposes a methodology to determine the maximum penetration of photovoltaic units in a distribution network. The paper presents a case study, with four different scenarios, that considers a 32-bus medium voltage distribution network and the inclusion storage units.
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Energy resource scheduling becomes increasingly important, as the use of distributed resources is intensified and massive gridable vehicle use is envisaged. The present paper proposes a methodology for dayahead energy resource scheduling for smart grids considering the intensive use of distributed generation and of gridable vehicles, usually referred as Vehicle- o-Grid (V2G). This method considers that the energy resources are managed by a Virtual Power Player (VPP) which established contracts with V2G owners. It takes into account these contracts, the user´s requirements subjected to the VPP, and several discharge price steps. Full AC power flow calculation included in the model allows taking into account network constraints. The influence of the successive day requirements on the day-ahead optimal solution is discussed and considered in the proposed model. A case study with a 33 bus distribution network and V2G is used to illustrate the good performance of the proposed method.