948 resultados para hierarchical structure criteria


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The purpose of this paper is to make quantitative and qualitative analysis of foreign citizens who may participate on the Swedish labor market (in text refers to as ‘immigrants’). This research covers the period 1973-2005 and gives prediction figures of immigrant population, age and gender structure, and education attainment in 2010. To cope with data regarding immigrants from different countries, the population was divided into six groups. The main chapter is divided into two parts. The first part specifies division of immigrants into groups by country of origin according to geographical, ethnical, economical and historical criteria. Brief characteristics and geographic position, dynamic and structure description were given for each group; historical review explain rapid changes in immigrant population. Statistical models for description and estimation future population were given. The second part specifies education and qualification level of the immigrants according to international and Swedish standards. Models for estimating age and gender structure, level of education and professional orientation of immigrants in different groups are given. Inferences were made regarding ethnic, gender and education structure of immigrants; the distribution of immigrants among Swedish counties is given. Discussion part presents the results of the research, gives perspectives for the future brief evaluation of the role of immigrants on the Swedish labor market.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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The use of clustering methods for the discovery of cancer subtypes has drawn a great deal of attention in the scientific community. While bioinformaticians have proposed new clustering methods that take advantage of characteristics of the gene expression data, the medical community has a preference for using classic clustering methods. There have been no studies thus far performing a large-scale evaluation of different clustering methods in this context. This work presents the first large-scale analysis of seven different clustering methods and four proximity measures for the analysis of 35 cancer gene expression data sets. Results reveal that the finite mixture of Gaussians, followed closely by k-means, exhibited the best performance in terms of recovering the true structure of the data sets. These methods also exhibited, on average, the smallest difference between the actual number of classes in the data sets and the best number of clusters as indicated by our validation criteria. Furthermore, hierarchical methods, which have been widely used by the medical community, exhibited a poorer recovery performance than that of the other methods evaluated. Moreover, as a stable basis for the assessment and comparison of different clustering methods for cancer gene expression data, this study provides a common group of data sets (benchmark data sets) to be shared among researchers and used for comparisons with new methods

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We consider the management branch model where the random resources of the subsystem are given by the exponential distributions. The determinate equivalent is a block structure problem of quadratic programming. It is solved effectively by means of the decomposition method, which is based on iterative aggregation. The aggregation problem of the upper level is resolved analytically. This overcomes all difficulties concerning the large dimension of the main problem.

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A set of 25 quinone compounds with anti-trypanocidal activity was studied by using the density functional theory (DFT) method in order to calculate atomic and molecular properties to be correlated with the biological activity. The chemometric methods principal component analysis (PCA), hierarchical cluster analysis (HCA), stepwise discriminant analysis (SDA), Kth nearest neighbor (KNN) and soft independent modeling of class analogy (SIMCA) were used to obtain possible relationships between the calculated descriptors and the biological activity studied and to predict the anti-trypanocidal activity of new quinone compounds from a prediction set. Four descriptors were responsible for the separation between the active and inactive compounds: T-5 (torsion angle), QTS1 (sum of absolute values of the atomic charges), VOLS2 (volume of the substituent at region B) and HOMO-1 (energy of the molecular orbital below HOMO). These descriptors give information on the kind of interaction that occurs between the compounds and the biological receptor. The prediction study was done with a set of three new compounds by using the PCA, HCA, SDA, KNN and SIMCA methods and two of them were predicted as active against the Trypanosoma cruzi. (c) 2005 Elsevier SAS. All rights reserved.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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The complexes MeHgL and PhHgL (HL = 2-mercaptobenzothiazole) have been obtained from the reaction of the ligand with methylmercury hydroxide and phenylmercury acetate, respectively, in methanol. MeHgL, which has been characterized by single-crystal X-ray diffraction analysis (crystal data: triclinic, space group P1, with a = 8.009 (4) Å, b = 10.042 (4) Å, c = 13.074 (3) Å, α = 101.25 (2)°, β = 102.61(3)°, γ = 101.42 (3)°, R = 0.067), crystallizes with two independent molecules, I and I′, contained in each asymmetric unit with a coordination geometry based on the almost linear C-Hg-S group (Hg-S = 2.369 (6) Å, Hg-C = 2.06 (2) Å, and C-Hg-S = 177.7 (7)° for I; Hg-S = 2.375 (6) Å, Hg-C = 2.10 (3) Å, and C-Hg-S = 178.8 (6)° for I′). A secondary intramolecular interaction between the mercury atom and the C=N group of the ring and some weak intermolecular interactions between the metal and sulfur atoms were also found. The vibrational spectra of this compound and the phenylmercury(II) compound are discussed in light of the crystal structure. Diagnostic criteria of the bonding modes for the ligand are assessed. © 1985 American Chemical Society.

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One way to organize knowledge and make its search and retrieval easier is to create a structural representation divided by hierarchically related topics. Once this structure is built, it is necessary to find labels for each of the obtained clusters. In many cases the labels have to be built using only the terms in the documents of the collection. This paper presents the SeCLAR (Selecting Candidate Labels using Association Rules) method, which explores the use of association rules for the selection of good candidates for labels of hierarchical document clusters. The candidates are processed by a classical method to generate the labels. The idea of the proposed method is to process each parent-child relationship of the nodes as an antecedent-consequent relationship of association rules. The experimental results show that the proposed method can improve the precision and recall of labels obtained by classical methods. © 2010 Springer-Verlag.

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One way to organize knowledge and make its search and retrieval easier is to create a structural representation divided by hierarchically related topics. Once this structure is built, it is necessary to find labels for each of the obtained clusters. In many cases the labels must be built using all the terms in the documents of the collection. This paper presents the SeCLAR method, which explores the use of association rules in the selection of good candidates for labels of hierarchical document clusters. The purpose of this method is to select a subset of terms by exploring the relationship among the terms of each document. Thus, these candidates can be processed by a classical method to generate the labels. An experimental study demonstrates the potential of the proposed approach to improve the precision and recall of labels obtained by classical methods only considering the terms which are potentially more discriminative. © 2012 - IOS Press and the authors. All rights reserved.

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Um conjunto de dezoito compostos de neolignanas com atividade antiesquistossomose foi estudado com o método semi-empírico PM3 e outros métodos teóricos com o intuito de avaliar algumas propriedades (variáveis ou descritores) moleculares selecionadas e correlacioná-las com a atividade biológica. Análise exploratória dos dados (análise de componentes principais, PCA, e análise hierárquica de agrupamentos, HCA), análise discriminante (DA) e o método KNN foram utilizados na obtenção de possíveis correlações entre os descritores calculados e a atividade biológica em questão e na predição da atividade antiesquistossimose de algumas moléculas teste. Os descritores moleculares responsáveis pela separação entre os compostos ativos e inativos foram: energia de hidratação (HE), refratividade molecular (MR) e carga sobre o átomo C19 (Q19). Estes descritores fornecem informações a respeito do tipo de interação que pode ocorrer entre os compostos e seu respectivo receptor biológico. Após a construção do modelo para compostos ativos e inativos, os métodos PCA, HCA, DA e KNN foram empregados em um estudo de predição. Foram estudados 10 novos compostos e somente 5 deles foram classificados como ativos contra esquistossomose.

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Studies of consumer-resource interactions suggest that individual diet specialisation is empirically widespread and theoretically important to the organisation and dynamics of populations and communities. We used weighted networks to analyze the resource use by sea otters, testing three alternative models for how individual diet specialisation may arise. As expected, individual specialisation was absent when otter density was low, but increased at high-otter density. A high-density emergence of nested resource-use networks was consistent with the model assuming individuals share preference ranks. However, a density-dependent emergence of a non-nested modular network for core resources was more consistent with the competitive refuge model. Individuals from different diet modules showed predictable variation in rank-order prey preferences and handling times of core resources, further supporting the competitive refuge model. Our findings support a hierarchical organisation of diet specialisation and suggest individual use of core and marginal resources may be driven by different selective pressures.

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For many tree species, mating system analyses have indicated potential variations in the selfing rate and paternity correlation among fruits within individuals, among individuals within populations, among populations, and from one flowering event to another. In this study, we used eight microsatellite markers to investigate mating systems at two hierarchical levels (fruits within individuals and individuals within populations) for the insect pollinated Neotropical tree Tabebuia roseo-alba. We found that T. roseo-alba has a mixed mating system with predominantly outcrossed mating. The outcrossing rates at the population level were similar across two T. roseo-alba populations; however, the rates varied considerably among individuals within populations. The correlated paternity results at different hierarchical levels showed that there is a high probability of shared paternal parentage when comparing seeds within fruits and among fruits within plants and full-sibs occur in much higher proportion within fruits than among fruits. Significant levels of fixation index were found in both populations and biparental inbreeding is believed to be the main cause of the observed inbreeding. The number of pollen donors contributing to mating was low. Furthermore, open-pollinated seeds varied according to relatedness, including half-sibs, full-sibs, self-sibs and self- half-sibs. In both populations, the effective population size within a family (seed-tree and its offspring) was lower than expected for panmictic populations. Thus, seeds for ex situ conservation genetics, progeny tests and reforestation must be collected from a large number of seed-trees to guarantee an adequate effective population in the sample.

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The mechanisms responsible for containing activity in systems represented by networks are crucial in various phenomena, for example, in diseases such as epilepsy that affect the neuronal networks and for information dissemination in social networks. The first models to account for contained activity included triggering and inhibition processes, but they cannot be applied to social networks where inhibition is clearly absent. A recent model showed that contained activity can be achieved with no need of inhibition processes provided that the network is subdivided into modules (communities). In this paper, we introduce a new concept inspired in the Hebbian theory, through which containment of activity is achieved by incorporating a dynamics based on a decaying activity in a random walk mechanism preferential to the node activity. Upon selecting the decay coefficient within a proper range, we observed sustained activity in all the networks tested, namely, random, Barabasi-Albert and geographical networks. The generality of this finding was confirmed by showing that modularity is no longer needed if the dynamics based on the integrate-and-fire dynamics incorporated the decay factor. Taken together, these results provide a proof of principle that persistent, restrained network activation might occur in the absence of any particular topological structure. This may be the reason why neuronal activity does not spread out to the entire neuronal network, even when no special topological organization exists.