880 resultados para Network security constraints


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A Resolução do Conselho de Ministros n.º 120/2008, de 30 de Julho, definiu como prioridade estratégica para o País, no sector das comunicações electrónicas, a promoção do investimento em redes de nova geração. Com o objectivo de dar execução às orientações estratégicas estabelecidas, o Decreto -Lei n.º 123/2009, de 21 de Maio, veio estabelecer um conjunto de obrigações aplicáveis ao Estado, às Regiões Autónomas, às autarquias locais, empresas públicas, concessionárias e, genericamente, às entidades que detenham infra-estruturas que se integrem em domínio público, de forma a garantir a todas empresas de comunicações electrónicas, o acesso às infra-estruturas aptas ao alojamento de redes de comunicações electrónicas. Em Portugal, o caminho a ser traçado até as redes de nova geração passa pela, abertura eficaz e não discriminatória de todas as condutas e outras infra-estruturas aptas ao alojamento de redes de comunicações electrónicas, elaboração de regras técnicas aplicáveis às infra-estruturas de telecomunicações em loteamentos, urbanizações e conjuntos de edifícios, adopção de soluções que eliminem ou atenuem as barreiras verticais à instalação de fibra óptica e que evitem a monopolização do acesso aos edifícios pelo primeiro operador. Neste âmbito, excluem-se, pela sua especial natureza e fins a que estão afectas, as redes privativas dos órgãos políticos de soberania, do Ministério da Defesa Nacional, das forças e serviços de segurança, de emergência e de protecção civil. Assim, este trabalho visa apresentar procedimentos aplicáveis às infra-estruturas de telecomunicações para elaboração de um cadastro de todas as infra-estruturas, públicas e privadas, aptas ao alojamento de redes de comunicações electrónicas, e propor instruções técnicas para as condições e direitos de acesso, construção e intervenção sobre estas infra-estruturas.

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O presente projecto tem como objectivo a disponibilização de uma plataforma de serviços para gestão e contabilização de tempo remunerável, através da marcação de horas de trabalho, férias e faltas (com ou sem justificação). Pretende-se a disponibilização de relatórios com base nesta informação e a possibilidade de análise automática dos dados, como por exemplo excesso de faltas e férias sobrepostas de trabalhadores. A ênfase do projecto está na disponibilização de uma arquitectura que facilite a inclusão destas funcionalidades. O projecto está implementado sobre a plataforma Google App Engine (i.e. GAE), de forma a disponibilizar uma solução sob o paradigma de Software as a Service, com garantia de disponibilidade e replicação de dados. A plataforma foi escolhida a partir da análise das principais plataformas cloud existentes: Google App Engine, Windows Azure e Amazon Web Services. Foram analisadas as características de cada plataforma, nomeadamente os modelos de programação, os modelos de dados disponibilizados, os serviços existentes e respectivos custos. A escolha da plataforma foi realizada com base nas suas características à data de iniciação do presente projecto. A solução está estruturada em camadas, com as seguintes componentes: interface da plataforma, lógica de negócio e lógica de acesso a dados. A interface disponibilizada está concebida com observação dos princípios arquitecturais REST, suportando dados nos formatos JSON e XML. A esta arquitectura base foi acrescentada uma componente de autorização, suportada em Spring-Security, sendo a autenticação delegada para os serviços Google Acounts. De forma a permitir o desacoplamento entre as várias camadas foi utilizado o padrão Dependency Injection. A utilização deste padrão reduz a dependência das tecnologias utilizadas nas diversas camadas. Foi implementado um protótipo, para a demonstração do trabalho realizado, que permite interagir com as funcionalidades do serviço implementadas, via pedidos AJAX. Neste protótipo tirou-se partido de várias bibliotecas javascript e padrões que simplificaram a sua realização, tal como o model-view-viewmodel através de data binding. Para dar suporte ao desenvolvimento do projecto foi adoptada uma abordagem de desenvolvimento ágil, baseada em Scrum, de forma a implementar os requisitos do sistema, expressos em user stories. De forma a garantir a qualidade da implementação do serviço foram realizados testes unitários, sendo também feita previamente a análise da funcionalidade e posteriormente produzida a documentação recorrendo a diagramas UML.

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The devastating impact of the Sumatra tsunami of 26 December 2004, raised the question for scientists of how to forecast a tsunami threat. In 2005, the IOC-UNESCO XXIII assembly decided to implement a global tsunami warning system to cover the regions that were not yet protected, namely the Indian Ocean, the Caribbean and the North East Atlantic, the Mediterranean and connected seas (the NEAM region). Within NEAM, the Gulf of Cadiz is the more sensitive area, with an important record of devastating historical events. The objective of this paper is to present a preliminary design for a reliable tsunami detection network for the Gulf of Cadiz, based on a network of sea-level observatories. The tsunamigenic potential of this region has been revised in order to define the active tectonic structures. Tsunami hydrodynamic modeling and GIS technology have been used to identify the appropriate locations for the minimum number of sea-level stations. Results show that 3 tsunameters are required as the minimum number of stations necessary to assure an acceptable protection to the large coastal population in the Gulf of Cadiz. In addition, 29 tide gauge stations could be necessary to fully assess the effects of a tsunami along the affected coasts of Portugal, Spain and Morocco.

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This paper presents an artificial neural network approach for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. The accuracy of the wind power forecasting attained with the proposed approach is evaluated against persistence and ARIMA approaches, reporting the numerical results from a real-world case study.

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This paper is on the problem of short-term hydro scheduling, particularly concerning head-dependent reservoirs under competitive environment. We propose a new nonlinear optimization method to consider hydroelectric power generation as a function of water discharge and also of the head. Head-dependency is considered on short-term hydro scheduling in order to obtain more realistic and feasible results. The proposed method has been applied successfully to solve a case study based on one of the main Portuguese cascaded hydro systems, providing a higher profit at a negligible additional computation time in comparison with a linear optimization method that ignores head-dependency.

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This paper is on the unit commitment problem, considering not only the economic perspective, but also the environmental perspective. We propose a bi-objective approach to handle the problem with conflicting profit and emission objectives. Numerical results based on the standard IEEE 30-bus test system illustrate the proficiency of the proposed approach.

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It is shown that type I seesaw models based on the standard model Lagrangian extended with three heavy Majorana right-handed fields do not have leptogenesis in leading order, if the symmetries of mass matrices are also the residual symmetry of the Lagrangian. In particular, flavor models that lead to a mass-independent leptonic mixing have a vanishing leptogenesis CP asymmetry. Based on symmetry arguments, we prove that in these models the Dirac-neutrino Yukawa coupling combinations relevant for leptogenesis are diagonal in the physical basis where the charged leptons and heavy Majorana neutrinos are diagonal.

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Communities of Practice are places which provide a sound basis for organizational learning, enabling knowledge creation and acquisition thus improving organizational performance, leveraging innovation and consequently increasing competitively. Virtual Communities of Practice (VCoP‟s) can perform a central role in promoting communication and collaboration between members who are dispersed in both time and space. The ongoing case study, described here, aims to identify both the motivations and the constraints that members of an organization experience when taking part in the knowledge creating processes of the VCoP‟s to which they belong. Based on a literature review, we have identified several factors that influence such processes; they will be used to analyse the results of interviews carried out with the leaders of VCoP‟s in four multinationals. As future work, a questionnaire will be developed and administered to the other members of these VCoP‟s

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With accelerated market volatility, faster response times and increased globalization, business environments are going through a major transformation and firms have intensified their search for strategies which can give them competitive advantage. This requires that companies continuously innovate, to think of new ideas that can be transformed or implemented as products, processes or services, generating value for the firm. Innovative solutions and processes are usually developed by a group of people, working together. A grouping of people that share and create new knowledge can be considered as a Community of Practice (CoP). CoP’s are places which provide a sound basis for organizational learning and encourage knowledge creation and acquisition. Virtual Communities of Practice (VCoP's) can perform a central role in promoting communication and collaboration between members who are dispersed in both time and space. Nevertheless, it is known that not all CoP's and VCoP's share the same levels of performance or produce the same results. This means that there are factors that enable or constrain the process of knowledge creation. With this in mind, we developed a case study in order to identify both the motivations and the constraints that members of an organization experience when taking part in the knowledge creating processes of VCoP's. Results show that organizational culture and professional and personal development play an important role in these processes. No interviewee referred to direct financial rewards as a motivation factor for participation in VCoPs. Most identified the difficulty in aligning objectives established by the management with justification for the time spent in the VCoP. The interviewees also said that technology is not a constraint.

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Paper accepted for the OKLC 2009 - International Conference on Organizational Learning, Knowledge and Capabilities (26-28th, April 2009, Amsterdam, the Netherlands).

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In the sequence of the recent financial and economic crisis, the recent public debt accumulation is expected to hamper considerably business cycle stabilization, by enlarging the budgetary consequences of the shocks. This paper analyses how the average level of public debt in a monetary union shapes optimal discretionary fiscal and monetary stabilization policies and affects stabilization welfare. We use a two-country micro-founded New-Keynesian model, where a benevolent central bank and the fiscal authorities play discretionary policy games under different union-average debt-constrained scenarios. We find that high debt levels shift monetary policy assignment from inflation to debt stabilization, making cooperation welfare superior to noncooperation. Moreover, when average debt is too high, welfare moves directly (inversely) with debt-to-output ratios for the union and the large country (small country) under cooperation. However, under non-cooperation, higher average debt levels benefit only the large country.

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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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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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In this paper, a novel mixed-integer nonlinear approach is proposed to solve the short-term hydro scheduling problem in the day-ahead electricity market, considering not only head-dependency, but also start/stop of units, discontinuous operating regions and discharge ramping constraints. Results from a case study based on one of the main Portuguese cascaded hydro energy systems are presented, showing that the proposedmixed-integer nonlinear approach is proficient. Conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.