988 resultados para Selection tool


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Grounded on Raymond Williams‘s definition of knowable community as a cultural tool to analyse literary texts, the essay reads the texts D.H.Lawrence wrote while travelling in the Mediterranean (Twilight in Italy, Sea and Sardinia and Etruscan Places) as knowable communities, bringing to the discussion the wide importance of literature not only as an object for aesthetic or textual readings, but also as a signifying practice which tells stories of culture. Departing from some considerations regarding the historical development of the relationship between literature and culture, the essay analyses the ways D. H. Lawrence constructed maps of meaning, where the readers, in a dynamic relation with the texts, apprehend experiences, structures and feelings; putting into perspective Williams‘s theory of culture as a whole way of life, it also analyses the ways the author communicates and organizes these experiences, creating a space of communication and operating at different levels of reality: on the one hand, the reality of the whole way of Italian life, and, on the other hand, the reality of the reader who aspires to make sense and to create an interpretative context where all the information is put, and, also, the reality of the writer in the poetic act of writing. To read these travel writings as knowable communities is to understand them as a form that invents a community with no other existence but that of the literary text. The cultural construction we find in these texts is the result of the selection, and interpretation done by D.H.Lawrence, as well as the product of the author‘s enunciative positions, and of his epistemological and ontological filigrees of existence, structured by the conditions of possibility. In the rearticulation of the text, of the writer and of the reader, in a dynamic and shared process of discursive alliances, we understand that Lawrence tells stories of the Mediterranean through his literary art.

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The treatment efficiency of laboratory wastewaters was evaluated and ecotoxicity tests with Chlorella vulgaris were performed on them to assess the safety of their environmental discharge. For chemical oxygen demand wastewaters, chromium (VI), mercury (II) and silver were efficiently removedby chemical treatments.Areduction of ecotoxicitywas achieved; nevertheless, an EC50 (effective concentration that causes a 50% inhibition in the algae growth) of 1.5% (v/v) indicated still high level of ecotoxicity. For chloride determination wastewaters, an efficient reduction of chromium and silver was achieved after treatment. Regarding the reduction of ecotoxicity observed, EC50 increased from 0.059% to 0.5%, only a 0.02% concentration in the aquatic environment would guarantee no effects. Wastewaters containing phenanthroline/iron (II) complex were treated by chemical oxidation. Treatmentwas satisfactory concerning chemical parameters, although an increase in ecotoxicitywas observed (EC50 reduced from 0.31% to 0.21%). The wastes from the kinetic study of persulphate and iodide reaction were treated with sodium bisulphite until colour was removed. Although they did not reveal significant ecotoxicity, only over 1% of the untreated waste produced observable effects over algae. Therefore, ecotoxicity tests could be considered a useful tool not only in laboratory effluents treatment, as shown, but also in hazardous wastewaters management.

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Clustering analysis is a useful tool to detect and monitor disease patterns and, consequently, to contribute for an effective population disease management. Portugal has the highest incidence of tuberculosis in the European Union (in 2012, 21.6 cases per 100.000 inhabitants), although it has been decreasing consistently. Two critical PTB (Pulmonary Tuberculosis) areas, metropolitan Oporto and metropolitan Lisbon regions, were previously identified through spatial and space-time clustering for PTB incidence rate and risk factors. Identifying clusters of temporal trends can further elucidate policy makers about municipalities showing a faster or a slower TB control improvement.

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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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Resource constraints are becoming a problem as many of the wireless mobile devices have increased generality. Our work tries to address this growing demand on resources and performance, by proposing the dynamic selection of neighbor nodes for cooperative service execution. This selection is in uenced by user's quality of service requirements expressed in his request, tailoring provided service to user's speci c needs. In this paper we improve our proposal's formulation algorithm with the ability to trade o time for the quality of the solution. At any given time, a complete solution for service execution exists, and the quality of that solution is expected to improve overtime.

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Electrocardiography (ECG) biometrics is emerging as a viable biometric trait. Recent developments at the sensor level have shown the feasibility of performing signal acquisition at the fingers and hand palms, using one-lead sensor technology and dry electrodes. These new locations lead to ECG signals with lower signal to noise ratio and more prone to noise artifacts; the heart rate variability is another of the major challenges of this biometric trait. In this paper we propose a novel approach to ECG biometrics, with the purpose of reducing the computational complexity and increasing the robustness of the recognition process enabling the fusion of information across sessions. Our approach is based on clustering, grouping individual heartbeats based on their morphology. We study several methods to perform automatic template selection and account for variations observed in a person's biometric data. This approach allows the identification of different template groupings, taking into account the heart rate variability, and the removal of outliers due to noise artifacts. Experimental evaluation on real world data demonstrates the advantages of our approach.

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Constrained and unconstrained Nonlinear Optimization Problems often appear in many engineering areas. In some of these cases it is not possible to use derivative based optimization methods because the objective function is not known or it is too complex or the objective function is non-smooth. In these cases derivative based methods cannot be used and Direct Search Methods might be the most suitable optimization methods. An Application Programming Interface (API) including some of these methods was implemented using Java Technology. This API can be accessed either by applications running in the same computer where it is installed or, it can be remotely accessed through a LAN or the Internet, using webservices. From the engineering point of view, the information needed from the API is the solution for the provided problem. On the other hand, from the optimization methods researchers’ point of view, not only the solution for the problem is needed. Also additional information about the iterative process is useful, such as: the number of iterations; the value of the solution at each iteration; the stopping criteria, etc. In this paper are presented the features added to the API to allow users to access to the iterative process data.

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The problem of selecting suppliers/partners is a crucial and important part in the process of decision making for companies that intend to perform competitively in their area of activity. The selection of supplier/partner is a time and resource-consuming task that involves data collection and a careful analysis of the factors that can positively or negatively influence the choice. Nevertheless it is a critical process that affects significantly the operational performance of each company. In this work, there were identified five broad selection criteria: Quality, Financial, Synergies, Cost, and Production System. Within these criteria, it was also included five sub-criteria. After the identification criteria, a survey was elaborated and companies were contacted in order to understand which factors have more weight in their decisions to choose the partners. Interpreted the results and processed the data, it was adopted a model of linear weighting to reflect the importance of each factor. The model has a hierarchical structure and can be applied with the Analytic Hierarchy Process (AHP) method or Value Analysis. The goal of the paper it's to supply a selection reference model that can represent an orientation/pattern for a decision making on the suppliers/partners selection process

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In research on Silent Speech Interfaces (SSI), different sources of information (modalities) have been combined, aiming at obtaining better performance than the individual modalities. However, when combining these modalities, the dimensionality of the feature space rapidly increases, yielding the well-known "curse of dimensionality". As a consequence, in order to extract useful information from this data, one has to resort to feature selection (FS) techniques to lower the dimensionality of the learning space. In this paper, we assess the impact of FS techniques for silent speech data, in a dataset with 4 non-invasive and promising modalities, namely: video, depth, ultrasonic Doppler sensing, and surface electromyography. We consider two supervised (mutual information and Fisher's ratio) and two unsupervised (meanmedian and arithmetic mean geometric mean) FS filters. The evaluation was made by assessing the classification accuracy (word recognition error) of three well-known classifiers (knearest neighbors, support vector machines, and dynamic time warping). The key results of this study show that both unsupervised and supervised FS techniques improve on the classification accuracy on both individual and combined modalities. For instance, on the video component, we attain relative performance gains of 36.2% in error rates. FS is also useful as pre-processing for feature fusion. Copyright © 2014 ISCA.

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The state of research on the evolution of marine bivalve taxonomic diversity of the Mediterranean Pliocene is analysed. The following assertions are discussed: 1) The Early Pliocene malacofauna is characterized by a high number of warm-water taxa and a high taxonomic diversity with respect to that of the present time. 2) The first appreciable extinction event in the Mediterranean Pliocene approximates or just follows the FO of Globorotalia bononiensis. 3) The second appreciable extinction event is between the LAD of Discoaster tamalis and the LAD of Discoaster surculus . 4) A third minor extinction event is penecontemporaneous with the FO of Globorotalia inflaia. Taking into account the available data on the Pliocene extinction events it has been possible to distinguish 4 different molluscan units with different climatic-oceanographic significance.

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Mestrado em Segurança e Higiene no Trabalho

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Informática

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Fiber reinforced plastics are increasing their importance as one of the most interesting groups of material on account of their low weight, high strength, and stiffness. To obtain good quality holes, it is important to identify the type of material, ply stacking sequence, and fiber orientation. In this article, the drilling of quasi-isotropic hybrid carbon +glass/epoxy plates is analyzed. Two commercial drills and a special step drill are compared considering the thrust force and delamination extension. Results suggest that the proposed step drill can be a suitable option in laminate drilling.

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In this work, a comparative study on different drill point geometries and feed rate for composite laminates drilling is presented. For this goal, thrust force monitoring during drilling, hole wall roughness measurement and delamination extension assessment after drilling is accomplished. Delamination is evaluated using enhanced radiography combined with a dedicated computational platform that integrates algorithms of image processing and analysis. An experimental procedure was planned and consequences were evaluated. Results show that a cautious combination of the factors involved, like drill tip geometry or feed rate, can promote the reduction of delamination damage.

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This paper presents a computational tool (PHEx) developed in Excel VBA for solving sizing and rating design problems involving Chevron type plate heat exchangers (PHE) with 1-pass-1-pass configuration. The rating methodology procedure used in the program is outlined, and a case study is presented with the purpose to show how the program can be used to develop sensitivity analysis to several dimensional parameters of PHE and to observe their effect on transferred heat and pressure drop.