955 resultados para Mixtures-of-experts
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Portugal had only very few foresight exercises on the automobile sector, and the most recent one was a survey held in a project on work organisation systems in the automobile industry, its recent historical paths and the special strategies of location of companies (the WorTiS project). This involved several teams with different disciplinary backgrounds and from two Portuguese universities. The provisional main results of the first round of a Delphi survey held in Portugal on the automotive sector were already published, but a further analysis was not yet done. This foresight survey was done under the WorTiS project, developed in 2004 by IET – Research Centre on Enterprise and Work Innovation (at FCT-UNL), and financed by the Portuguese Ministry of Science and Technology. Some of this experience on foresight analysis is also been transferred to other projects, namely the WORKS project on work organisation restructuring in the knowledge society that received the support from EC and still is running. The majority of experts considered having an average of less knowledge in almost all the scenario topics presented. This means that information on the automotive industry is not spread enough among academics or experts in related fields (regional scientists, innovation economists, engineers, sociologists). Some have a good knowledge but in very specialised fields. Others have expertise on foresight, or macroeconomics, or management sciences, but feel insecure on issues related with futures of automobile sector. Nevertheless, we considered specially the topics where the experts considered themselves to have some knowledge. There were no “irrelevant” topics considered as such by the expert panel. There are also no topics that are not considered a need for co-operation. The lack of technological infrastructures was not considered as a hindered factor for the accomplishment of any scenario. The experts’ panel considered no other international competence besides US, Japan or Germany in these topics. Special focus will be made in this paper on the topic 2. Public policy and automobile industries, and more specifically on the technological and/or research policies issues, where one can specify the automobile’s role in transport policies with further implications like environment, safety, energy, mobility.
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This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.
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The present study is focused on the characterization of ultrafine particles emitted in welding of steel using mixtures of Ar+CO2, and intends to analyze which are the main process parameters which may have influence on the emission itself. It was found that the amount of emitted ultrafine particles (measured by particle number and alveolar deposited surface area) are clearly dependent from the distance to the welding front and also from the main welding parameters, namely the current intensity and heat input in the welding process. The emission of airborne ultrafine particles seem to increase with the current intensity as fume formation rate does. When comparing the tested gas mixtures, higher emissions are observed for more oxidant mixtures, that is, mixtures with higher CO2 content, which result in higher arc stability. The later mixtures originate higher concentrations of ultrafine particles (as measured by number of particles by cm3 of air) and higher values of alveolar deposited surface area of particles, thus resulting in a more hazardous condition regarding worker's exposure. © 2014 Sociedade Portuguesa de Materiais (SPM). Published by Elsevier España, S.L. All rights reserved.
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The reactions between 4'-phenyl-terpyridine (L) and nitrate, acetate or chloride Cu(II) salts led to the formation of [Cu(NO3)(2)L] (1), [Cu(OCOCH3)(2)L]center dot CH2Cl2 (2 center dot CH2Cl2)and [CuCl2L]center dot[Cu(Cl)(mu-Cl)L](2) (3), respectively. Upon dissolving 1 in mixtures of DMSO-MeOH or EtOH-DMF the compounds [Cu(H2O){OS(CH3)(2)}L]-(NO3)(2) (4) and [Cu(HO)(CH3CH2OH)L](NO3) (5) were obtained, in this order. Reaction of 3 with AgSO3CF3 led to [CuCl(OSO2CF3)L] (6). The compounds were characterized by ESI-MS, IR, elemental analysis, electrochemical techniques and, for 2-6, also by single crystal X-ray diffraction. They undergo, by cyclic voltammetry, two single-electron irreversible reductions assigned to Cu(II) -> Cu(I)and Cu(I) -> Cu(0) and, for those of the same structural type, the reduction potential appears to correlate with the summation of the values of the Lever electrochemical EL ligand parameter, which is reported for the first time for copper complexes. Complexes 1-6 in combination with TEMPO (2,2,6,6-tetramethylpiperidinyl-1-oxyl radical) can exhibit a high catalytic activity, under mild conditions and in alkaline aqueous solution, for the aerobic oxidation of benzylic alcohols. Molar yields up to 94% (based on the alcohol) with TON values up to 320 were achieved after 22 h.
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ABSTRACT OBJECTIVE To validate a Spanish version of the Test of Gross Motor Development (TGMD-2) for the Chilean population. METHODS Descriptive, transversal, non-experimental validity and reliability study. Four translators, three experts and 92 Chilean children, from five to 10 years, students from a primary school in Santiago, Chile, have participated. The Committee of Experts has carried out translation, back-translation and revision processes to determine the translinguistic equivalence and content validity of the test, using the content validity index in 2013. In addition, a pilot implementation was achieved to determine test reliability in Spanish, by using the intraclass correlation coefficient and Bland-Altman method. We evaluated whether the results presented significant differences by replacing the bat with a racket, using T-test. RESULTS We obtained a content validity index higher than 0.80 for language clarity and relevance of the TGMD-2 for children. There were significant differences in the object control subtest when comparing the results with bat and racket. The intraclass correlation coefficient for reliability inter-rater, intra-rater and test-retest reliability was greater than 0.80 in all cases. CONCLUSIONS The TGMD-2 has appropriate content validity to be applied in the Chilean population. The reliability of this test is within the appropriate parameters and its use could be recommended in this population after the establishment of normative data, setting a further precedent for the validation in other Latin American countries.
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Trabalho de Projeto submetido à Escola Superior de Teatro e Cinema para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Desenvolvimento de Projeto Cinematográfico - especialização em Dramaturgia e Realização
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One of the most challenging task underlying many hyperspectral imagery applications is the linear unmixing. The key to linear unmixing is to find the set of reference substances, also called endmembers, that are representative of a given scene. This paper presents the vertex component analysis (VCA) a new method to unmix linear mixtures of hyperspectral sources. The algorithm is unsupervised and exploits a simple geometric fact: endmembers are vertices of a simplex. The algorithm complexity, measured in floating points operations, is O (n), where n is the sample size. The effectiveness of the proposed scheme is illustrated using simulated data.
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Linear unmixing decomposes an hyperspectral image into a collection of re ectance spectra, called endmember signatures, and a set corresponding abundance fractions from the respective spatial coverage. This paper introduces vertex component analysis, an unsupervised algorithm to unmix linear mixtures of hyperpsectral data. VCA exploits the fact that endmembers occupy vertices of a simplex, and assumes the presence of pure pixels in data. VCA performance is illustrated using simulated and real data. VCA competes with state-of-the-art methods with much lower computational complexity.
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau Mestre em Engenharia Biomédica
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Dissertation to obtain the Master Degree in Biotechnology
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Dissertation for the Degree of Master in Biotechnology
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Dissertação para obtenção do Grau de Doutor em Engenharia Química e Bioquímica
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A total of 123 stool specimens collected in Teresina, Piauí between 1994 and 1996, from 0 to 2-year-old children with diarrhea, were used for this study. Molecular characterization of the G and P rotavirus genotypes was performed using the reverse transcriptase polymerase chain reaction. The following results were obtained for the P genotypes: P[8] (17. 1%), P[1] (4. 9%), P[4] (3. 3%), P[6, M37] (2. 4%) and mixtures (27. 6%). The P[1]+P[8] mixture was found in 19. 5% of the samples. For the G genotypes, the results were: G1 (25. 2%), G5 (13. 8%), G2 (2. 5%), G4 (2. 5%), G9 (0. 8%) and mixtures (41. 5%). G1+G5 was the mixture most frequently found (12. 1%). Our results showed unusual combinations such as P[1]G5 and P[1]+P[8]G5. The high percentage of mixtures and unusual combinations containing mixtures of human and animal rotavirus genotypes strongly suggests the possibility of gene reassortment and interspecies transmission.
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A ready-mixed and several laboratory formulated mortars were produced and tested in fresh state and after hardening, simulating a masonry plaster for indoor application. All the mortars used a clayish earth from the same region and different compositions of aggregates, eventually including fibres and a phase change material. All the formulated mortars were composed by 1:3 volumetric proportions of earth and aggregate. Tests were developed for consistency, fresh bulk density, thermal conductivity, capillary absorption and drying, water vapour permeability and sorption-desorption. The use of PCM changed drastically the workability of the mortars and increased their capillary absorption. The use of fibres and variations on particle size distribution of the mixtures of sand that were used had no significant influence on tested properties. But particularly the good workability of these mortars and the high capacity of sorption and desorption was highlighted. With this capacity plasters made with these mortars are able to adsorb water vapour from indoor atmosphere when high levels of relative humidity exist and release water vapour when the indoor atmosphere became too dry. This fact makes them able to contribute passively for a healthier indoor environment. The technical, ecological and environmental advantages of the application of plasters with this type of mortars are emphasized, with the aim of contributing for an increased use for new or existent housing.
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Nowadays manufacturing companies are facing a more challenging environment due to the unpredictability of the markets in order to survive. Enterprises need to keep innovating and deliver products with new internal or external characteristics. There are strategies and solutions, to different organisational level from strategic to operational, when technology is growing faster in operational level, more specifically in manufacturing system. This means that companies have to deal with the changes of the emergent manufacturing systems while it can be expensive and not easy to be implement. An agile manufacturing system can help to cope with the markets changeability. Evolvable Production Systems (EPS) is an emergent paradigm which aims to bring new solutions to deal with changeability. The proposed paradigm is characterised by modularity and intends to introduce high flexibility and dynamism at shop floor level through the use of the evolution of new computational devices and technology. This new approach brings to enterprises the ability to plug and unplug new devices and allowing fast reformulation of the production line without reprogramming. There is no doubt about the advantages and benefits of this emerging technology but the feasibility and applicability is still under questioned. Most researches in this area are focused on technical side, explaining the advantages of those systems while there are no sufficient works discussing the implementation risks from different perspective, including business owner. The main objective of this work is to propose a methodology and model to identify, classify and measure potential risk associated with an implementation of this emergent paradigm. To quantify the proposed comprehensive risk model, an Intelligent Decision system is developed employing Fuzzy Inference System to deal with the knowledge of experts, as there are no historical data and sufficient research on this area. The result can be the vulnerability assessment of implementing EPS technology in manufacturing companies when the focus is more on SMEs. The present dissertation used the experts’ knowledge and experiences, who were involved in FP7 project IDEAS, which is one of the leading projects in this area.