957 resultados para Quasi contracts


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O Código dos contratos públicos (CCP) veio introduzir alguns novos conceitos, nas empreitadas de obras públicas, sobre erros e omissões e também sobre trabalhos a mais. Tais conceitos têm estado na origem de algumas polémicas envolvendo donos de obra, projectistas, fiscalizações, empreiteiros e técnicos. Por outro, quer à luz da anterior legislação quer ao abrigo da actual os desvios de preço e prazo, em empreitadas de obras públicas, continuam a ser frequentes, dir-se-á mesmo, praticamente uma constante e frequentemente alvo nos meios de comunicação. No âmbito desta dissertação pretende-se partilhar algumas reflexões emergentes da observação efectuada, como participante activo em diversos empreendimentos. Verificar-se-á ao longo da mesma dissertação que nela é atribuída grande relevância ao programa preliminar constante do Anexo I à Portaria n.º 701-H/2008 de 29 de Julho, que dá origem ao projecto. Com efeito, este documento embora a sua designação de preliminar possa induzir em erro, levando a conferir-lhe pouca importância, é, em boa verdade, o programa fundamental, para um bom entendimento entre o dono de obra e o projectista e subsequentemente com o empreiteiro. Nesta dissertação faz-se uma incursão pelos conteúdos mais relevantes do CCP, no âmbito dos desvios de preço e custo, das empreitadas de obras públicas. Procede-se, também, a uma análise detalhada e sequencial das fases e actividades que contribuem para a concretização de uma obra pública, observando simultaneamente o papel dos diversos intervenientes.

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Copyright © 2005, Idea Group Inc., distributing in print or electronic forms without written permission of IGI is prohibited.

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Electrical resistivity, transverse magnetoresistance and thermoelectric power measurements were performed on CuS high quality single crystals in the range 1.2-300 K and under fields of up to 16 T. The zero field resistivity data are well described below 55 K by a quasi-2D model, consistent with a carrier confinement at lower temperatures, before the transition to the superconducting state. The transverse magnetoresistance develops mainly below 30 K and attains values as large as 470% for a 16 T field at 5 K, this behaviour being ascribed to a band effect mechanism, with a possible magnetic field induced DOS change at the Fermi level. The transverse magnetoresistance shows no signs of saturation, following a power law with field Delta rho/rho(0) proportional to H(1.4), suggesting the existence of open orbits for carriers at the Fermi surface. The thermoelectric power shows an unusual temperature dependence, probably as a result of the complex band structure of CuS.

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Nos últimos anos verificou-se uma alteração das condições e modo de funcionamento de empresas e instituições, privadas e públicas, muitas delas através da introdução de novas ferramentas de gestão. De entre elas, podemos destacar o outsourcing, que apesar de não ser um fenómeno actual, é ainda em Portugal uma ferramenta recente e pouco explorada, que pode contribuir de forma decisiva para a modernização, flexibilidade e competitividade das empresas. O presente estudo pretende abordar a contratação de serviços externos nos serviços de saúde públicos, também conhecido como outsourcing, mediante uma análise prática da realidade de uma instituição hospitalar com sete serviços em regime de outsourcing, com recolha dos dados durante o triénio 2008-2010. No Serviço de Urgência durante 2010 o principal prestador recebeu mais 104,28% acima do valor referência/hora, no Serviço de Oftalmologia no ano de 2010 o prestador recebeu um valor superior em 24,91%, no Serviço de Limpeza, Higiene e Conforto é pago ao prestador durante o ano de 2010 um valor superior em 13,85%, no Serviço de Vigilância e Segurança o prestador recebeu durante o ano de 2010 um valor superior em 27,5%, caso a instituição hospitalar optasse por contratar, para os serviços atrás referidos, profissionais para o quadro de pessoal. Ainda em relação ao Serviço de Urgência foi pago mais 21,38% acima do valor de referência publicado por Despacho governamental. Em relação aos Serviços de Lavandaria e de Tratamento de Resíduos Sólidos, não foi possível recolher os dados necessários que pudessem levar a uma conclusão válida sobre os custos pagos pela instituição hospitalar. Pode-se concluir que a contratação de prestadores externos, para os serviços de saúde, essenciais e não essenciais, em regime de outsourcing, revela-se na maioria dos casos analisados a opção menos económica, com custos bastantes elevados.

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The advances made in channel-capacity codes, such as turbo codes and low-density parity-check (LDPC) codes, have played a major role in the emerging distributed source coding paradigm. LDPC codes can be easily adapted to new source coding strategies due to their natural representation as bipartite graphs and the use of quasi-optimal decoding algorithms, such as belief propagation. This paper tackles a relevant scenario in distributedvideo coding: lossy source coding when multiple side information (SI) hypotheses are available at the decoder, each one correlated with the source according to different correlation noise channels. Thus, it is proposed to exploit multiple SI hypotheses through an efficient joint decoding technique withmultiple LDPC syndrome decoders that exchange information to obtain coding efficiency improvements. At the decoder side, the multiple SI hypotheses are created with motion compensated frame interpolation and fused together in a novel iterative LDPC based Slepian-Wolf decoding algorithm. With the creation of multiple SI hypotheses and the proposed decoding algorithm, bitrate savings up to 8.0% are obtained for similar decoded quality.

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Dissertação apresentada ao Instituto Superior de Contabilidade para a obtenção do Grau de Mestre em Empreendedorismo e Internacionalização Orientada por Professor Doutor José Freitas Santos

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Dissertação apresentada ao Instituto Superior de Contabilidade e Administração do Porto (ISCAP) para a obtenção do Grau de Mestre em Auditoria Docente orientador: Mestre Domingos da Silva Duarte

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Four ruthenium(II) complexes with the formula [Ru(eta(5)-C(5)H(5))(PP)L][CF(3)SO(3)], being (PP = two triphenylphosphine molecules), L = 1-benzylimidazole, 1; (PP = two triphenylphosphine molecules), L = 2,2'bipyridine, 2; (PP = two triphenylphosphine molecules), L = 4-Methylpyridine, 3; (PP = 1,2-bis(diphenylphosphine) ethane), L = 4-Methylpyridine, 4, were prepared, in view to evaluate their potentialities as antitumor agents. The compounds were completely characterized by NMR spectroscopy and their crystal and molecular structures were determined by X-ray diffraction. Electrochemical studies were carried out giving for all the compounds quasi-reversible processes. The images obtained by atomic force microscopy (AFM) suggest interaction with pBR322 plasmid DNA. Measurements of the viscosity of solutions of free DNA and DNA incubated with different concentrations of the compounds confirmed this interaction. The cytotoxicity of compounds 1234 was much higher than that of cisplatin against human leukemia cancer cells (HL-60 cells). IC(50) values for all the compounds are in the range of submicromolar amounts. Apoptotic death percentage was also studied resulting similar than that of cisplatin. (C) 2010 Elsevier Inc. All rights reserved.

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The use of distributed energy resources, based on natural intermittent power sources, like wind generation, in power systems imposes the development of new adequate operation management and control methodologies. A short-term Energy Resource Management (ERM) methodology performed in two phases is proposed in this paper. The first one addresses the day-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. The ERM scheduling is a complex optimization problem due to the high quantity of variables and constraints. In this paper the main goal is to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixedinteger non-linear programming approach. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units and 1000 electric vehicles has been implemented in a simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.

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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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The introduction of new distributed energy resources, based on natural intermittent power sources, in power systems imposes the development of new adequate operation management and control methods. This paper proposes a short-term Energy Resource Management (ERM) methodology performed in two phases. The first one addresses the hour-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. Both phases consider the day-ahead resource scheduling solution. The ERM scheduling is formulated as an optimization problem that aims to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixed-integer non-linear programming approach and by a heuristic approach based on genetic algorithms. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units has been implemented in a PSCADbased simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.

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The present research paper presents five different clustering methods to identify typical load profiles of medium voltage (MV) electricity consumers. These methods are intended to be used in a smart grid environment to extract useful knowledge about customer’s behaviour. The obtained knowledge can be used to support a decision tool, not only for utilities but also for consumers. Load profiles can be used by the utilities to identify the aspects that cause system load peaks and enable the development of specific contracts with their customers. The framework presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partition, which is supported by cluster validity indices. The process ends with the analysis of the discovered knowledge. To validate the proposed framework, a case study with a real database of 208 MV consumers is used.

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The spread and globalization of distributed generation (DG) in recent years has should highly influence the changes that occur in Electricity Markets (EMs). DG has brought a large number of new players to take action in the EMs, therefore increasing the complexity of these markets. Simulation based on multi-agent systems appears as a good way of analyzing players’ behavior and interactions, especially in a coalition perspective, and the effects these players have on the markets. MASCEM – Multi-Agent System for Competitive Electricity Markets was created to permit the study of the market operation with several different players and market mechanisms. MASGriP – Multi-Agent Smart Grid Platform is being developed to facilitate the simulation of micro grid (MG) and smart grid (SG) concepts with multiple different scenarios. This paper presents an intelligent management method for MG and SG. The simulation of different methods of control provides an advantage in comparing different possible approaches to respond to market events. Players utilize electric vehicles’ batteries and participate in Demand Response (DR) contracts, taking advantage on the best opportunities brought by the use of all resources, to improve their actions in response to MG and/or SG requests.

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The increasing importance given by environmental policies to the dissemination and use of wind power has led to its fast and large integration in power systems. In most cases, this integration has been done in an intensive way, causing several impacts and challenges in current and future power systems operation and planning. One of these challenges is dealing with the system conditions in which the available wind power is higher than the system demand. This is one of the possible applications of demand response, which is a very promising resource in the context of competitive environments that integrates even more amounts of distributed energy resources, as well as new players. The methodology proposed aims the maximization of the social welfare in a smart grid operated by a virtual power player that manages the available energy resources. When facing excessive wind power generation availability, real time pricing is applied in order to induce the increase of consumption so that wind curtailment is minimized. The proposed method is especially useful when actual and day-ahead wind forecast differ significantly. The proposed method has been computationally implemented in GAMS optimization tool and its application is illustrated in this paper using a real 937-bus distribution network with 20310 consumers and 548 distributed generators, some of them with must take contracts.

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This paper proposes a particle swarm optimization (PSO) approach to support electricity producers for multiperiod optimal contract allocation. The producer risk preference is stated by a utility function (U) expressing the tradeoff between the expectation and variance of the return. Variance estimation and expected return are based on a forecasted scenario interval determined by a price range forecasting model developed by the authors. A certain confidence level is associated to each forecasted scenario interval. The proposed model makes use of contracts with physical (spot and forward) and financial (options) settlement. PSO performance was evaluated by comparing it with a genetic algorithm-based approach. This model can be used by producers in deregulated electricity markets but can easily be adapted to load serving entities and retailers. Moreover, it can easily be adapted to the use of other type of contracts.