948 resultados para Development Permit System


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This paper defines Die Surface Designer (DSD) System for fast draw die in the product development feasibility phase on surfaces coming from styling. We propose a CAD integration, for better support the design process in industry, particularly on the development of new products in automotive sector. The DSD system intends to reduce the lead time by providing and integrating flexible and efficient capabilities for testing early concepts from surface analysis points of view in automotive product development.

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HENRE II (Higher Education Network for Radiography in Europe)

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March 19 - 22, 2006, São Paulo, BRAZIL World Congress on Computer Science, Engineering and Technology Education

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The conjugation of antigens with ligands of pattern recognition receptors (PRR) is emerging as a promising strategy for the modulation of specific immunity. Here, we describe a new Escherichia coli system for the cloning and expression of heterologous antigens in fusion with the OprI lipoprotein, a TLR ligand from the Pseudomonas aeruginosa outer membrane (OM). Analysis of the OprI expressed by this system reveals a triacylated lipid moiety mainly composed by palmitic acid residues. By offering a tight regulation of expression and allowing for antigen purification by metal affinity chromatography, the new system circumvents the major drawbacks of former versions. In addition, the anchoring of OprI to the OM of the host cell is further explored for the production of novel recombinant bacterial cell wall-derived formulations (OM fragments and OM vesicles) with distinct potential for PRR activation. As an example, the African swine fever virus ORF A104R was cloned and the recombinant antigen was obtained in the three formulations. Overall, our results validate a new system suitable for the production of immunogenic formulations that can be used for the development of experimental vaccines and for studies on the modulation of acquired immunity.

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This paper describes the development and the implementation of a multi-agent system for integrated diagnosis of power transformers. The system is divided in layers which contain a number of agents performing different functions. The social ability and cooperation between the agents lead to the final diagnosis and to other relevant conclusions through integrating various monitoring technologies, diagnostic methods and data sources, such as the dissolved gas analysis.

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This paper presents a project consisting on the development of an Intelligent Tutoring System, for training and support concerning the development of electrical installation projects to be used by electrical engineers, technicians and students. One of the major goals of this project is to devise a teaching model based on Intelligent Tutoring techniques, considering not only academic knowledge but also other types of more empirical knowledge, able to achieve successfully the training of electrical installation design.

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All over the world Distributed Generation is seen as a valuable help to get cleaner and more efficient electricity. To get negotiation power and advantages of scale economy, distributed producers can be aggregated giving place to a new concept: the Virtual Power Producer. Virtual Power Producers are multitechnology and multi-site heterogeneous entities. Virtual Power Producers should adopt organization and management methodologies so that they can make Distributed Generation a really profitable activity, able to participate in the market. In this paper we address the development of a multi-agent market simulator – MASCEM – able to study alternative coalitions of distributed producers in order to identify promising Virtual Power Producers in an electricity market.

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Many of the most common human functions such as temporal and non-monotonic reasoning have not yet been fully mapped in developed systems, even though some theoretical breakthroughs have already been accomplished. This is mainly due to the inherent computational complexity of the theoretical approaches. In the particular area of fault diagnosis in power systems however, some systems which tried to solve the problem, have been deployed using methodologies such as production rule based expert systems, neural networks, recognition of chronicles, fuzzy expert systems, etc. SPARSE (from the Portuguese acronym, which means expert system for incident analysis and restoration support) was one of the developed systems and, in the sequence of its development, came the need to cope with incomplete and/or incorrect information as well as the traditional problems for power systems fault diagnosis based on SCADA (supervisory control and data acquisition) information retrieval, namely real-time operation, huge amounts of information, etc. This paper presents an architecture for a decision support system, which can solve the presented problems, using a symbiosis of the event calculus and the default reasoning rule based system paradigms, insuring soft real-time operation with incomplete, incorrect or domain incoherent information handling ability. A prototype implementation of this system is already at work in the control centre of the Portuguese Transmission Network.

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Natural gas industry has been confronted with big challenges: great growth in demand, investments on new GSUs – gas supply units, and efficient technical system management. The right number of GSUs, their best location on networks and the optimal allocation to loads is a decision problem that can be formulated as a combinatorial programming problem, with the objective of minimizing system expenses. Our emphasis is on the formulation, interpretation and development of a solution algorithm that will analyze the trade-off between infrastructure investment expenditure and operating system costs. The location model was applied to a 12 node natural gas network, and its effectiveness was tested in five different operating scenarios.

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Metalearning is a subfield of machine learning with special pro-pensity for dynamic and complex environments, from which it is difficult to extract predictable knowledge. The field of study of this work is the electricity market, which due to the restructuring that recently took place, became an especially complex and unpredictable environment, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. This paper presents the development of a metalearner, applied to the decision support of electricity markets’ negotia-tion entities. The proposed metalearner takes advantage on several learning algorithms implemented in ALBidS, an adaptive learning system that pro-vides decision support to electricity markets’ participating players. Using the outputs of each different strategy as inputs, the metalearner creates its own output, considering each strategy with a different weight, depending on its individual quality of performance. The results of the proposed meth-od are studied and analyzed using MASCEM - a multi-agent electricity market simulator that models market players and simulates their operation in the market. This simulator provides the chance to test the metalearner in scenarios based on real electricity market´s data.

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This paper studies Optimal Intelligent Supervisory Control System (OISCS) model for the design of control systems which can work in the presence of cyber-physical elements with privacy protection. The development of such architecture has the possibility of providing new ways of integrated control into systems where large amounts of fast computation are not easily available, either due to limitations on power, physical size or choice of computing elements.

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Emotion although being an important factor in our every day life it is many times forgotten in the development of systems to be used by persons. In this work we present an architecture for a ubiquitous group decision support system able to support persons in group decision processes. The system considers the emotional factors of the intervenient participants, as well as the argumentation between them. Particular attention will be taken to one of components of this system: the multi-agent simulator, modeling the human participants, considering emotional characteristics, and allowing the exchanges of hypothetic arguments among the participants.

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The present paper results of an ongoing research project were it is expected to develop an information system to monitoring a cultural-touristic route. The route to monitor is the Romanesque Route of Tâmega. This Route is composed of 58 monuments located in the region of Tâmega in the North of Portugal. Due to the particular location of this region, that is between coastal zone, but not yet in the inland, it has a weak political influence, and it is reflected in the low levels of development at several levels, observed. The Romanesque Route was implemented in a part of this region in 1998, and enlarged to the all-region in 2010. In order to evaluate the socio-ecomonic impact of this route in the region a research project is being developed. The main goal of this paper is to open a discussion on the elements that must be taken into consideration to evaluate the economic and social impact of a touristic cultural route within a region and this one in particular.

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Mestrado em Engenharia Electrotécnica e de Computadores

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Thesis submitted in the fulfilment of the requirements for the Degree of Master in Electronic and Telecomunications Engineering