974 resultados para deterministic trend


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This paper introduces the concept of common deterministic shifts (CDS). This concept is simple, intuitive and relates to the common structure of shifts or policy interventions. We propose a Reduced Rank technique to investigate the presence of CDS. The proposed testing procedure has standard asymptotics and good small-sample properties. We further link the concept of CDS to that of superexogeneity. It is shown that CDS tests can be constructed which allow to test for super-exogeneity. The Monte Carlo evidence indicates that the CDS test for super-exogeneity dominates testing procedures proposed in the literature.

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In the present paper, we report on the occurrence of the cockroach Pycnoscelus surinamensis (Linnaeus, 1758) in Brachymyrmex cordemoyi Forel, 1895 nests, indicating a possible symbiosis between these two species. Also, the finding of intradomicile P. surinamensis nymphs may indicate this species is extending its habitat to human habitations, i.e. changing its ecological category from peridomestic to domestic.

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

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É feita uma análise da evolução dos conhecimentos sobre as coquinas-reservatório da Formação Lagoa Feia, com base em cinco publicações de geologia de desenvolvimento dos campos de Badejo, Linguado e Pampo. Trata-se de uma única acumulação, onde o controle é misto, ou seja, estrutural, estratigráfico e principalmente diagenético. Falhas antitéticas herdadas do rifteamento pós-basáltico exercem um importante papel no controle das coquinas, promovendo crescimento da seção nos blocos baixos, e servindo de conduto para a circulação de água meteórica, relacionada à discordância pós-coquina que promove dissolução e criação de porosidade secundária nas coquinas. A compreensão do modelo de acumulação do óleo é fundamental tendo em vista oportunidades para projetos de recuperação suplementar de óleo.

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The regional geological work for the oil industry, in order to find potential areas for hydrocarbon exploration and understand the geological parameters responsible for the formation of the deposit are known importance. This work fits into that scenario, with regional research with the aid of wells and 2D and 3D seismic sold by DBEP (Database Exploration and Production). Were also used as GeoGraphix software package Landmarks modules Prizm and SeisWork 2D and 3D, and the Surfer 8 and ArcGIS 9.2 with the infrastructure provided by the 05 PRH - ANP with LSGI (Laboratory of Seismic and Geological Interpretation) located at UNESP -- Campus de Rio Claro. The work focuses on study the trend of oil-Badejo-Linguado-Pampo, producing fields since the beginning of offshore holdings. The Campos Basin is now known as the offshore basin of the country more productive, and the high structural Badejo is a structure of great importance in the basin presents itself as largely responsible for the conditioning of hydrocarbon fields Pampo, Linguado and Badejo. Therefore this work also aims to increase knowledge of the region in terms of tectonic and stratigraphic characterize the geometry of the structures associated with this major regional structure. For this we used structural contour maps of the main chrono-horizons, and Isopach maps for the purpose of better understanding the tectono-sedimentary evolution of the Campos Basin locally.

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Chain topology, including branch node, chain link and cross-link dynamics that contribute to the number of elastically active strands and junctions, are calculated using purely deterministic derivations. Solutions are not coupled to population density distributions. An eigenzeit transformation assists in the conversion of expressions derived by chemical reaction principles from time to conversion space, yielding transport phenomena type expressions where the rate of change in the molar concentrations of branch nodes with respect to conversion is expressed as functions of the fraction of reactive sites on precursors and reactants. Analogies are hypothesized to exist in cross-linking space that effectively distribute branch nodes with i reacted moieties between cross-links having j bonds extending to the gel. To obtain solutions, reacted sites on nodes or links with finite chain extensions are examined in terms of stoichiometry associated with covalent bonding. Solutions replicate published results based on Miller and Macosko’s recursive procedure and results obtained from truncated weighted sums of population density distributions as suggested by Flory.

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OBJECTIVE: To analyze drug use trends among college students in 1996, 2001 and 2009. METHODS: A cross-sectional epidemiological study with a multistage stratified cluster sample with 9,974 college students was conducted in the city of Sao Paulo, southeastern Brazil. An anonymous self-administered questionnaire was used to collect information on drug use assessed in lifetime, the preceding 12 months and the preceding 30 days. The Bonferroni correction was used for multiple comparisons of drug use rates between surveys. RESULTS: There were changes in the lifetime use of tobacco and some other drugs (hallucinogens [6.1% to 8.8%], amphetamines [4.6% to 8.7%], and tranquilizers [5.7% to 8.2%]) from 1996 to 2009. Differences in the use of other drugs over the 12 months preceding the survey were also seen: reduced use of inhalants [9.0% to 4.8%] and increased use of amphetamines [2.4% to 4.8%]. There was a reduction in alcohol [72.9% to 62.1%], tobacco [21.3% to 17.2%] and marijuana [15.0% to 11.5%] use and an increase in amphetamine use [1.9% to 3.3%] in the preceeding 30 days. CONCLUSIONS: Over the 13-year study period, there was an increase in lifetime use of tobacco, hallucinogens, amphetamines, and tranquilizers. There was an increase in amphetamine use and a reduction in alcohol use during the preceding 12 months. There was an increase in amphetamine use during the preceding 30 days.

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Complex networks have attracted increasing interest from various fields of science. It has been demonstrated that each complex network model presents specific topological structures which characterize its connectivity and dynamics. Complex network classification relies on the use of representative measurements that describe topological structures. Although there are a large number of measurements, most of them are correlated. To overcome this limitation, this paper presents a new measurement for complex network classification based on partially self-avoiding walks. We validate the measurement on a data set composed by 40000 complex networks of four well-known models. Our results indicate that the proposed measurement improves correct classification of networks compared to the traditional ones. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4737515]

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Cone beam computed tomography (CBCT) can be considered as a valuable imaging modality for improving diagnosis and treatment planning to achieve true guidance for several craniofacial surgical interventions. A new concept and perspective in medical informatics is the highlight discussion about the new imaging interactive workflow. The aim of this article was to present, in a short literature review, the usefulness of CBCT technology as an important alternative imaging modality, highlighting current practices and near-term future applications in cutting-edge thought-provoking perspectives for craniofacial surgical assessment. This article explains the state of the art of CBCT improvements, medical workstation, and perspectives of the dedicated unique hardware and software, which can be used from the CBCT source. In conclusion, CBCT technology is developing rapidly, and many advances are on the horizon. Further progress in medical workstations, engineering capabilities, and improvement in independent software-some open source-should be attempted with this new imaging method. The perspectives, challenges, and pitfalls in CBCT will be delineated and evaluated along with the technological developments.

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In this paper, the effects of uncertainty and expected costs of failure on optimum structural design are investigated, by comparing three distinct formulations of structural optimization problems. Deterministic Design Optimization (DDO) allows one the find the shape or configuration of a structure that is optimum in terms of mechanics, but the formulation grossly neglects parameter uncertainty and its effects on structural safety. Reliability-based Design Optimization (RBDO) has emerged as an alternative to properly model the safety-under-uncertainty part of the problem. With RBDO, one can ensure that a minimum (and measurable) level of safety is achieved by the optimum structure. However, results are dependent on the failure probabilities used as constraints in the analysis. Risk optimization (RO) increases the scope of the problem by addressing the compromising goals of economy and safety. This is accomplished by quantifying the monetary consequences of failure, as well as the costs associated with construction, operation and maintenance. RO yields the optimum topology and the optimum point of balance between economy and safety. Results are compared for some example problems. The broader RO solution is found first, and optimum results are used as constraints in DDO and RBDO. Results show that even when optimum safety coefficients are used as constraints in DDO, the formulation leads to configurations which respect these design constraints, reduce manufacturing costs but increase total expected costs (including expected costs of failure). When (optimum) system failure probability is used as a constraint in RBDO, this solution also reduces manufacturing costs but by increasing total expected costs. This happens when the costs associated with different failure modes are distinct. Hence, a general equivalence between the formulations cannot be established. Optimum structural design considering expected costs of failure cannot be controlled solely by safety factors nor by failure probability constraints, but will depend on actual structural configuration. (c) 2011 Elsevier Ltd. All rights reserved.

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Texture image analysis is an important field of investigation that has attracted the attention from computer vision community in the last decades. In this paper, a novel approach for texture image analysis is proposed by using a combination of graph theory and partially self-avoiding deterministic walks. From the image, we build a regular graph where each vertex represents a pixel and it is connected to neighboring pixels (pixels whose spatial distance is less than a given radius). Transformations on the regular graph are applied to emphasize different image features. To characterize the transformed graphs, partially self-avoiding deterministic walks are performed to compose the feature vector. Experimental results on three databases indicate that the proposed method significantly improves correct classification rate compared to the state-of-the-art, e.g. from 89.37% (original tourist walk) to 94.32% on the Brodatz database, from 84.86% (Gabor filter) to 85.07% on the Vistex database and from 92.60% (original tourist walk) to 98.00% on the plant leaves database. In view of these results, it is expected that this method could provide good results in other applications such as texture synthesis and texture segmentation. (C) 2012 Elsevier Ltd. All rights reserved.

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In this paper,we present a novel texture analysis method based on deterministic partially self-avoiding walks and fractal dimension theory. After finding the attractors of the image (set of pixels) using deterministic partially self-avoiding walks, they are dilated in direction to the whole image by adding pixels according to their relevance. The relevance of each pixel is calculated as the shortest path between the pixel and the pixels that belongs to the attractors. The proposed texture analysis method is demonstrated to outperform popular and state-of-the-art methods (e.g. Fourier descriptors, occurrence matrix, Gabor filter and local binary patterns) as well as deterministic tourist walk method and recent fractal methods using well-known texture image datasets.

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Recently there has been a considerable interest in dynamic textures due to the explosive growth of multimedia databases. In addition, dynamic texture appears in a wide range of videos, which makes it very important in applications concerning to model physical phenomena. Thus, dynamic textures have emerged as a new field of investigation that extends the static or spatial textures to the spatio-temporal domain. In this paper, we propose a novel approach for dynamic texture segmentation based on automata theory and k-means algorithm. In this approach, a feature vector is extracted for each pixel by applying deterministic partially self-avoiding walks on three orthogonal planes of the video. Then, these feature vectors are clustered by the well-known k-means algorithm. Although the k-means algorithm has shown interesting results, it only ensures its convergence to a local minimum, which affects the final result of segmentation. In order to overcome this drawback, we compare six methods of initialization of the k-means. The experimental results have demonstrated the effectiveness of our proposed approach compared to the state-of-the-art segmentation methods.

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Dynamic texture is a recent field of investigation that has received growing attention from computer vision community in the last years. These patterns are moving texture in which the concept of selfsimilarity for static textures is extended to the spatiotemporal domain. In this paper, we propose a novel approach for dynamic texture representation, that can be used for both texture analysis and segmentation. In this method, deterministic partially self-avoiding walks are performed in three orthogonal planes of the video in order to combine appearance and motion features. We validate our method on three applications of dynamic texture that present interesting challenges: recognition, clustering and segmentation. Experimental results on these applications indicate that the proposed method improves the dynamic texture representation compared to the state of the art.