986 resultados para Multidimensional approach


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Research on the problem of feature selection for clustering continues to develop. This is a challenging task, mainly due to the absence of class labels to guide the search for relevant features. Categorical feature selection for clustering has rarely been addressed in the literature, with most of the proposed approaches having focused on numerical data. In this work, we propose an approach to simultaneously cluster categorical data and select a subset of relevant features. Our approach is based on a modification of a finite mixture model (of multinomial distributions), where a set of latent variables indicate the relevance of each feature. To estimate the model parameters, we implement a variant of the expectation-maximization algorithm that simultaneously selects the subset of relevant features, using a minimum message length criterion. The proposed approach compares favourably with two baseline methods: a filter based on an entropy measure and a wrapper based on mutual information. The results obtained on synthetic data illustrate the ability of the proposed expectation-maximization method to recover ground truth. An application to real data, referred to official statistics, shows its usefulness.

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This paper presents a complete, quadratic programming formulation of the standard thermal unit commitment problem in power generation planning, together with a novel iterative optimisation algorithm for its solution. The algorithm, based on a mixed-integer formulation of the problem, considers piecewise linear approximations of the quadratic fuel cost function that are dynamically updated in an iterative way, converging to the optimum; this avoids the requirement of resorting to quadratic programming, making the solution process much quicker. From extensive computational tests on a broad set of benchmark instances of this problem, the algorithm was found to be flexible and capable of easily incorporating different problem constraints. Indeed, it is able to tackle ramp constraints, which although very important in practice were rarely considered in previous publications. Most importantly, optimal solutions were obtained for several well-known benchmark instances, including instances of practical relevance, that are not yet known to have been solved to optimality. Computational experiments and their results showed that the method proposed is both simple and extremely effective.

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A comunicação e a aprendizagem encontram-se intimamente ligadas. Constituem a essência do desenvolvimento e crescimento humanos através das quais legitimamos o nosso processo de vida. É através delas que a pessoa se envolve nas suas atividades diárias e desempenha os papéis que são esperados de si pela sociedade. Para a pessoa com afasia esta realidade encontra-se drasticamente alterada. A afasia pode criar limitações à atividade e restrições à participação do indivíduo resultantes da relação da deficiência com o meio em que a pessoa se move. O impacto dos fatores ambientais na aprendizagem do viver com afasia e consequente renegociação do “eu” precisa de ser foco de reflexão.

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CYCLOTech is a high-tech Project, related with an innovative method for direct production of a radioactive pharmaceutical, used in excess of 85% of 35 Million Nuclear Medicine procedures done yearly, worldwide, representing globally more than 3 Billion Euros. The CYCLOTech team has developed an innovative proprietary methodology based on the use of Cyclotron Centers, formally identified as the Clients (actually, there are around 450 of this Centers in function worldwide), to directly produce and deliver the radiopharmaceutical to the final users, at the Hospitals and other Health Institutions (estimating at around 25.000, worldwide). The investment still need to finish Research and Technological Development (RTD), Industrial, Regulatory and Intellectual Property Rights (IPR) issues and allow the introduction in the Market is 4,35 M€, with a Payback of 3 years, with an Investment Return Rate (IRR) of 81,7% and a Net Present Value (NPV) of 60.620.525€ (in 2020).

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In the business world, there are issues such as globalisation, environmental awareness, and the rising expectations of public opinion which have a specific role in what is required from companies as providers of information to the market. This chapter refers to the current state of corporate reporting (financial reporting and sustainability reporting) and demonstrates the need for evolution to a more integrated method of reporting which meets the stakeholders’ needs. This research offers a reflection on how this development can be achieved, which notes the ongoing efforts by international organisations in implementing the diffusion and adoption, as well as looking at the characteristics which are needed for this type of reporting. It also makes the link between an actual case of a company that is one of the world references in sustainable development and integrated reporting. Whether or not the integrated reporting is the natural evolution of the history of financial and sustainability reporting, it still cannot yet claim to be infallible. However, it may definitely be concluded that a new approach is necessary to meet the needs which are continuously developing for a network of stakeholders.

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In this paper we discuss how the inclusion of semantic functionalities in a Learning Objects Repository allows a better characterization of the learning materials enclosed and improves their retrieval through the adoption of some query expansion strategies. Thus, we started to regard the use of ontologies to automatically suggest additional concepts when users are filling some metadata fields and add new terms to the ones initially provided when users specify the keywords with interest in a query. Dealing with different domain areas and having considered impractical the development of many different ontologies, we adopted some strategies for reusing ontologies in order to have the knowledge necessary in our institutional repository. In this paper we make a review of the area of knowledge reuse and discuss our approach.

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Competitive electricity markets have arisen as a result of power-sector restructuration and power-system deregulation. The players participating in competitive electricity markets must define strategies and make decisions using all the available information and business opportunities.

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Ancillary services represent a good business opportunity that must be considered by market players. This paper presents a new methodology for ancillary services market dispatch. The method considers the bids submitted to the market and includes a market clearing mechanism based on deterministic optimization. An Artificial Neural Network is used for day-ahead prediction of Regulation Down, regulation-up, Spin Reserve and Non-Spin Reserve requirements. Two test cases based on California Independent System Operator data concerning dispatch of Regulation Down, Regulation Up, Spin Reserve and Non-Spin Reserve services are included in this paper to illustrate the application of the proposed method: (1) dispatch considering simple bids; (2) dispatch considering complex bids.

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The Robuter is a robotic mobile platform that is located in the “Hands-On” Laboratory of the IPP-Hurray! Research Group, at the School of Engineering of the Polytechnic Institute of Porto. Recently, the Robuter was subject of an upgrading process addressing two essential areas: the Hardware Architecture and the Software Architecture. This upgrade in process was triggered due to technical problems on-board of the robot and also to the fact that the hardware/software architecture has become obsolete. This Technical Report overviews the most important aspects of the new Hardware and Software Architectures of the Robuter. This document also presents a first approach on the first steps towards the use of the Robuter platform, and provides some hints on future work that may be carried out using this mobile platform.

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This paper analyzes the Portuguese short-run business cycles over the last 150 years and presents the multidimensional scaling (MDS) for visualizing the results. The analytical and numerical assessment of this long-run perspective reveals periods with close connections between the macroeconomic variables related to government accounts equilibrium, balance of payments equilibrium, and economic growth. The MDS method is adopted for a quantitative statistical analysis. In this way, similarity clusters of several historical periods emerge in the MDS maps, namely, in identifying similarities and dissimilarities that identify periods of prosperity and crises, growth, and stagnation. Such features are major aspects of collective national achievement, to which can be associated the impact of international problems such as the World Wars, the Great Depression, or the current global financial crisis, as well as national events in the context of broad political blueprints for the Portuguese society in the rising globalization process.

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In this paper we present a framework for managing QoS-aware applications in a dynamic, ad-hoc, distributed environment. This framework considers an available set of wireless/mobile and fixed nodes, which may temporally form groups in order to process a set of related services, and where there is the need to support different levels of service and different combinations of quality requirements. This framework is being developed both for testing and validating an approach, based on multidimensional QoS properties, which provides service negotiation and proposal evaluation algorithms, and for assessing the suitability of the Ada language to be used in the context of dynamic, QoS-aware systems.

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The paper investigates the risk factors for the severity of orthodontic root resorption. The multidimensional scaling (MDS) visualization method is used to investigate the experimental data from patients who received orthodontic treatment at the Department of Orthodontics and Dentofacial Orthopedics, Faculty of Dentistry, “Carol Davila” University of Medicine and Pharmacy, during a period of 4 years. The clusters emerging in the MDS plots reveal features and properties not easily captured by classical statistical tools. The results support the adoption of MDS for tackling the dentistry information and overcoming noise embedded into the data. The method introduced in this paper is rapid, efficient, and very useful for treating the risk factors for the severity of orthodontic root resorption.

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In this study, efforts were made in order to put forward an integrated recycling approach for the thermoset based glass fibre reinforced polymer (GPRP) rejects derived from the pultrusion manufacturing industry. Both the recycling process and the development of a new cost-effective end-use application for the recyclates were considered. For this purpose, i) among the several available recycling techniques for thermoset based composite materials, the most suitable one for the envisaged application was selected (mechanical recycling); and ii) an experimental work was carried out in order to assess the added-value of the obtained recyclates as aggregates and reinforcement replacements into concrete-polymer composite materials. Potential recycling solution was assessed by mechanical behaviour of resultant GFRP waste modified concrete-polymer composites with regard to unmodified materials. In the mix design process of the new GFRP waste based composite material, the recyclate content and size grade, and the effect of the incorporation of an adhesion promoter were considered as material factors and systematically tested between reasonable ranges. The optimization process of the modified formulations was supported by the Fuzzy Boolean Nets methodology, which allowed finding the best balance between material parameters that maximizes both flexural and compressive strengths of final composite. Comparing to related end-use applications of GFRP wastes in cementitious based concrete materials, the proposed solution overcome some of the problems found, namely the possible incompatibilities arisen from alkalis-silica reaction and the decrease in the mechanical properties due to high water-cement ratio required to achieve the desirable workability. Obtained results were very promising towards a global cost-effective waste management solution for GFRP industrial wastes and end-of-life products that will lead to a more sustainable composite materials industry.

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For industrial environments it is true that Ethernet technologies are there to stay. In fact, a number of characteristics are boosting the eagerness of extending Ethernet to also cover factory-floor applications. Fullduplex links, non-blocking and priority-based switching, bandwidth availability, just to mention a few, are characteristics upon which that eagerness is building up. But, will Ethernet technologies really manage to replace traditional field bus networks? Fieldbus fundamentalists often argue that the two things are not comparable. In fact, Ethernet technology, by itself, does not include features above the lower layers of the OSI communication model. Where are the higher layers and the application enablers that permit building real industrial applications? And, taking for free that they are available, what is the impact of those protocols, mechanisms and application models on the overall performance of Ethernet-based distributed factory-floor applications?

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The problem of uncertainty propagation in composite laminate structures is studied. An approach based on the optimal design of composite structures to achieve a target reliability level is proposed. Using the Uniform Design Method (UDM), a set of design points is generated over a design domain centred at mean values of random variables, aimed at studying the space variability. The most critical Tsai number, the structural reliability index and the sensitivities are obtained for each UDM design point, using the maximum load obtained from optimal design search. Using the UDM design points as input/output patterns, an Artificial Neural Network (ANN) is developed based on supervised evolutionary learning. Finally, using the developed ANN a Monte Carlo simulation procedure is implemented and the variability of the structural response based on global sensitivity analysis (GSA) is studied. The GSA is based on the first order Sobol indices and relative sensitivities. An appropriate GSA algorithm aiming to obtain Sobol indices is proposed. The most important sources of uncertainty are identified.