872 resultados para Concept hierarchy
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Most financial and economic time-series display a strong volatility around their trends. The difficulty in explaining this volatility has led economists to interpret it as exogenous, i.e., as the result of forces that lie outside the scope of the assumed economic relations. Consequently, it becomes hard or impossible to formulate short-run forecasts on asset prices or on values of macroeconomic variables. However, many random looking economic and financial series may, in fact, be subject to deterministic irregular behavior, which can be measured and modelled. We address the notion of endogenous volatility and exemplify the concept with a simple business-cycles model.
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This paper aims to present a contrastive approach between three different ways of building concepts after proving the similar syntactic possibilities that coexist in terms. However, from the semantic point of view we can see that each language family has a different distribution in meaning. But the most important point we try to show is that the differences found in the psychological process when communicating concepts should guide the translator and the terminologist in the target text production and the terminology planning process. Differences between languages in the information transmission process are due to the different roles the different types of knowledge play. We distinguish here the analytic-descriptive knowledge and the analogical knowledge among others. We also state that none of them is the best when determining the correctness of a term, but there has to be adequacy criteria in the selection process. This concept building or term building success is important when looking at the linguistic map of the information society.
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OBJETIVO: Analisar a qualidade dos serviços oferecidos por empresas operadoras de planos de saúde, segundo a percepção de usuários. MÉTODOS: Estudo transversal com 360 usuários de sete operadoras de planos de saúde da cidade de Curitiba, PR, e região metropolitana em 2008. Foi aplicado questionário sobre as preferências dos usuários em relação a seis atributos (localização dos pontos de atendimento; efetividade da ação dos médicos, clínicas e hospitais; rapidez e amabilidade no atendimento; facilidade na liberação de guias; preço; abrangência da rede credenciada) de cada uma das empresas operadoras. Para a análise das respostas foi utilizado o método Analytic Hierarchy Process (AHP, ou Processo Analítico de Hierarquia), ferramenta de análise de decisão e planejamento de múltiplos critérios. RESULTADOS: O atributo mais valorizado pelos usuários foi "preço". As empresas foram agrupadas em dois conjuntos de preferências em relação aos atributos: dos sete planos de saúde, dois apresentaram menor preferência (entre 23% e 19%) e cinco, maior preferência (em torno de 10%). CONCLUSÕES: Com esse tipo de pesquisa, as empresas operadoras de planos de saúde poderiam reformular suas estruturas, processos, preços e redes credenciadas com o objetivo de melhorar seu posicionamento no mercado.
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Tese de doutoramento em Filosofia
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Securing group communication in wireless sensor networks has recently been extensively investigated. Many works have addressed this issue, and they have considered the grouping concept differently. In this paper, we consider a group as being a set of nodes sensing the same data type, and we alternatively propose an efficient secure group communication scheme guaranteeing secure group management and secure group key distribution. The proposed scheme (RiSeG) is based on a logical ring architecture, which permits to alleviate the group controller’s task in updating the group key. The proposed scheme also provides backward and forward secrecy, addresses the node compromise attack, and gives a solution to detect and eliminate the compromised nodes. The security analysis and performance evaluation show that the proposed scheme is secure, highly efficient, and lightweight. A comparison with the logical key hierarchy is preformed to prove the rekeying process efficiency of RiSeG. Finally, we present the implementation details of RiSeG on top of TelosB sensor nodes to demonstrate its feasibility.
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Banks that has introduced CRM system, had to make some difficult changes in their organization in order to become more customer oriented. Beside the pure CRM banks try to adopt other innovative tools related with the core CRM. Some of these solutions are constructed in such a way so that ensured could be also access to the information beside to bank’s organization.
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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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Dissertation to obtain the degree of Master in Music - Artistic Interpretation
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Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies
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Some of the main challenges in Incorporating Sustainable Development practices into Engineering Education reside in establishing the bridge between concept and application. In particular the relation between value creation and the knowledge economy, innovation and entrepreneurship, as the main vehicles to a relevant application of the sustainable development concept, is not yet part of the majority of the engineering curricula in schools. Porto Polytechnical Engineering School (ISEP), a Global Reporting Initiative training partner in Portugal, as just presented its Sustainable Development Action Plan, with the main objective of creating a new kind of engineers, with Sustainable Development at the core of their degrees. The plan has several issues like publish an annual sustainability report, sustainable buildings, minimization of energy consumption and water policy, waste management, sustainable mobility, green procurement, EMAS certification, research and postgraduate activity and promotion of lectures and seminars in Sustainable Development.
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This paper describes preliminary work on the generation of synthesis gas from water electrolysis using graphite electrodes without the separation of the generated gases. This is an innovative process, that has no similar work been done earlier. Preliminary tests allowed to establish correlations between the applied current to the electrolyser and flow rate and composition of the generated syngas, as well as a characterisation of generated carbon nanoparticles. The obtained syngas can further be used to produce synthetic liquid fuels, for example, methane, methanol or DME (dimethyl ether) in a catalytic reactor, in further stages of a present ongoing project, using the ELECTROFUEL® concept. The main competitive advantage of this project lies in the built-in of an innovative technology product, from RE (renewable energy) power in remote locations, for example, islands, villages in mountains as an alternative for energy storage for mobility constraints.
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Recent studies have shown that, besides the well-recognized T3 and T4 hormones, there are other relevant thyroid hormones circulating in the human body. In particular, this is the case for 3-iodothyronamine (T1AM) and thyronamine (T0AM). One of the reasons for the lack of studies showing their precise importance is the absence of analytical methodologies available. Herein, for the first time, T1AM and T0AM are electrochemically characterized. T0AM was sensed by means of a glassy carbon electrode; furthermore, T1AM was sensed both with a graphitic surface (oxidatively) as well as with mercury (reductively). For both compounds, after oxidation, it was possible to observe the reversible redox reaction concerning the benzoquinone/hydroquinone couple, thus increasing the specificity of the electroanalysis. Therefore, this work provides the basis for an ‘at-point-of-use’ electrochemical strip test for T1AM and T0AM.
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This work introduces a novel idea for wireless energy transfer, proposing for the first time the unit-cell of an indoor localization and RF harvesting system embedded into the floor. The unit-cell is composed by a 5.8 GHz patch antenna surrounded by a 13.56 MHz coil. The coil locates a device and activate the patch which, connected to a power grid, radiates to wirelessly charge the localized device. The HF and RF circuits co-existence and functionality are demonstrated in this paper, the novelty of which is also in the adoption of low cost and most of all ecofriendly materials, such as wood and cork, as substrates for electronics.
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Based on a report for the seminar Industrial Networks, at Goethe Universität Frankfurt am Main Dozent: Prof. Dr. Blättel-Mink, Prof. Dr. António Moniz SS 2011
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Background: Childhood asthma represents an increasing health problem and is the leading cause of hospital admission and absenteeism in children with chronic disease. It also compromises quality of life, eventually contributing to disturbances in self-concept. Self-concept is a recent and global perspective of “the self” and relates to skills, self-image and self-esteem. Little information is available on this topic and there are no data from Portuguese countryside towns. Objective: The aim of this study was to determine the prevalence of asthma among all school children in the 5th and 6th grades in a Portuguese countryside town and to establish its possible correlation with absenteeism and self-concept. Methods: In April 2002, two questionnaires were administered in the presence of the researcher to a group of 950 children attending different schools. The children completed the internationally renowned questionnaires: ISAAC and the Self-Concept Scale by Susan Harter. Results: Our sample (n = 818) had a mean age of 11 years (10-15 years) and a male-to-female ratio of 1/1. The cumulative prevalence of asthma was11.9% and that of active asthma was 8.8 %; 63.9% of asthmatics were male and 36.1 % were female. The mean age of asthmatics was 11.34 years and 74 % had active symptoms. Comparison of this group of 97 asthmatic children with the remaining children revealed a statistically significant correlation between the presence of asthma and school absenteeism (global: p = 0.04; gymnastics: 0.05). Regarding the Self-Concept Scale a statistically significant association was found between the presence of asthma and school achievement (p = 0.027), physical appearance (p = 0.015), behavior (p < 0.000) and self-esteem (p < 0.000). No statistically significant correlations were found in social acceptance (p = 0.289) or athletic competence (p = 0.085). Asthmatic boys had higher self-concept scores than girls, except in the domain of behavior. Conclusions: Twelve percent of the population studied was asthmatic. In asthmatic children, absenteeism was higher and self-concept was lower for almost all domains, except social acceptance and athletic achievement, probably due to overprotection.