919 resultados para Hierarchical Petri nets


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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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One common problem in all basic techniques of knowledge representation is the handling of the trade-off between precision of inferences and resource constraints, such as time and memory. Michalski and Winston (1986) suggested the Censored Production Rule (CPR) as an underlying representation and computational mechanism to enable logic based systems to exhibit variable precision in which certainty varies while specificity stays constant. As an extension of CPR, the Hierarchical Censored Production Rules (HCPRs) system of knowledge representation, proposed by Bharadwaj & Jain (1992), exhibits both variable certainty as well as variable specificity and offers mechanisms for handling the trade-off between the two. An HCPR has the form: Decision If(preconditions) Unless(censor) Generality(general_information) Specificity(specific_information). As an attempt towards evolving a generalized knowledge representation, an Extended Hierarchical Censored Production Rules (EHCPRs) system is suggested in this paper. With the inclusion of new operators, an Extended Hierarchical Censored Production Rule (EHCPR) takes the general form: Concept If (Preconditions) Unless (Exceptions) Generality (General-Concept) Specificity (Specific Concepts) Has_part (default: structural-parts) Has_property (default:characteristic-properties) Has_instance (instances). How semantic networks and frames are represented in terms of an EHCPRs is shown. Multiple inheritance, inheritance with and without cancellation, recognition with partial match, and a few default logic problems are shown to be tackled efficiently in the proposed system.

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This study considers the function and complexity of tasks during foraging of three Acromyrmex species. Foraging was classified as a team task composed of 2 or 3 processes: recruitment, selection, and collection. Each process was subdivided into different subtasks. Points were attributed to subtasks considering their hierarchical level to compare the complexity of foraging among species. Total scores obtained were 19 for A. balzani and 14 for A. crassispinus and A. rugosus, indicating different degrees of social complexity for grass-cutting and leaf-cutting ant species. Acromyrmex balzani, a grass-cutting ant species, shows a behavioral repertoire composed of more variable subtasks during foraging.

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Autonomous robots must be able to learn and maintain models of their environments. In this context, the present work considers techniques for the classification and extraction of features from images in joined with artificial neural networks in order to use them in the system of mapping and localization of the mobile robot of Laboratory of Automation and Evolutive Computer (LACE). To do this, the robot uses a sensorial system composed for ultrasound sensors and a catadioptric vision system formed by a camera and a conical mirror. The mapping system is composed by three modules. Two of them will be presented in this paper: the classifier and the characterizer module. The first module uses a hierarchical neural network to do the classification; the second uses techiniques of extraction of attributes of images and recognition of invariant patterns extracted from the places images set. The neural network of the classifier module is structured in two layers, reason and intuition, and is trained to classify each place explored for the robot amongst four predefine classes. The final result of the exploration is the construction of a topological map of the explored environment. Results gotten through the simulation of the both modules of the mapping system will be presented in this paper. © 2008 IEEE.

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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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The development of gas sensors with innovative designs and advanced functional materials has attracted considerable scientific interest given their potential for addressing important technological challenges. This work presents new insight towards the development of high-performance p-type semiconductor gas sensors. Gas sensor test devices, based on copper (II) oxide (CuO) with innovative and unique designs (urchin-like, fiber-like, and nanorods), are prepared by a microwave-assisted synthesis method. The crystalline composition, surface area, porosity, and morphological characteristics are studied by X-ray powder diffraction, nitrogen adsorption isotherms, field-emission scanning electron microscopy and high-resolution transmission electron microscopy. Gas sensor measurements, performed simultaneously on multiple samples, show that morphology can have a substantial influence on gas sensor performance. An assembly of urchin-like structures is found to be most effective for hydrogen detection in the range of parts-per-million at 200 °C with 300-fold larger response than the previously best reported values for semiconducting CuO hydrogen gas sensors. These results show that morphology plays an important role in the gas sensing performance of CuO and can be effectively applied in the further development of gas sensors based on p-type semiconductors. High-performance gas sensors based on CuO hierarchical morphologies with in situ gas sensor comparison are reported. Urchin-like morphologies with high hydrogen sensitivity and selectivity that show chemical and thermal stability and low temperature operation are analyzed. The role of morphological influences in p-type gas sensor materials is discussed. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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Euterpe oleracea, a native palm to the Amazon, has recognized trading importance because of its fruits and heart of palm. However, it still requires general information on its propagation and cultivation. As light is essential for plant growth, this work aimed to study the effect of different color nets and light conditions on the initial growth of E. oleracea, with the objective to obtain high quality seedlings. The experiment was conducted in Jaboticabal County, São Paulo State, Brazil. The experimental design was entirely randomized, with six treatments (six light conditions: red net with 50% of shading - red Chromatinet®; blue net with 50% of shading - blue Chromatinet®; black nets with 70, 50 or 30% of shading; and full sun) and six replications (six evaluation periods: 30, 60, 90, 120, 150 and 180 days after the beginning of the experiment). Each plot consisted of four pots with one plant per pot, resulting in 144 plants. Seedling growth was monthly evaluated by collecting four plants per replication until the end of the experiment. Shoot length, root length, stem diameter, leaf number, leaf area and root and shoot dry matter were evaluated. The best quality seedlings of E. oleracea were obtained when they were cultivated under the black net with 50% of shading.

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ABSTRACT The aim of the present study was to analyze the influence of enriched environment on the distribution of perineuronal nets (PNNs) using a stereogically based unbiased protocol and visual acuity in adult Swiss albino mice that underwent monocular deprivation during the critical period of postnatal development. Eight female Swiss albino mice were monocular deprived were removed and cut at 70 µm thickness in a vibratome and processed for lectin histochemical staining with Wisteria floribunda agglutinin (WFA). Architectonic limits of area 17 were conspicuously defined by WFA histochemical staining, and the optical fractionator stereological method was applied to estimate the total number of PNNs in the supragranular, granular, and infragranular layers. All groups were compared using Student's t-test at a 95% confidence level. Comparative analysis of the average PNN estimations revealed that the EE group had higher PNNs in the supragranular layer (2726.33 ± 405.416, mean ± standard deviation) compared with the SE group (1543.535 ± 260.686; Student's t-test, p = .0495). No differences were found in the other layers. Visual acuity was significantly lower in the SE group (0.55 cycles/degree) than in the EE group (1.06 cycles/degree). Our results suggest that the integrity of the specialized extracellular matrix PNNs of the supragranular layer may be essential for normal visual acuity development.

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O bico ou trabalho paralelo é umas das práticas mais comuns entre os policiais militares; é exercido por eles: em festas, eventos e segurança de pessoas físicas. Embora seja a garantia de uma renda extra, entretanto, isso propicia que o policial se torne uma pessoa sem lazer e sempre ausente da família. Posto isso, informamos que neste trabalho temos por objetivo mostrar como se estruturam as redes do bico entre os policiais, as quais criam uma verdadeira organização de venda de trabalho que, para isso, se utilizam do status quo ou do poder de polícia para garantirem a segurança privada. Também mostraremos como ocorrem as jornadas de trabalho paralelo e os seus riscos, bem como as conseqüências de sua informalidade. Além disso, apresentaremos os meandros destas organizações, a sua estrutura, a sua hierarquia e como ela opera, onde constatamos que há uma inversão dos valores hierárquicos da organização militar.

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This study evaluated alternatives for producing erosion susceptibility maps, considering different weight combinations for an environment's attributes, according to four different points of views. The attributes considered were landform, steepness, soils, rocks and land occupation. Considered alternatives were: (1) equal weights, more traditional approach, (2) different weights, according to a previous study in the area, (3) different weights, based on other works in the literature, and (4) different weights based on the analytical hierarchical process. The area studied included the Prosa Basin located in Campo Grande-Mato Grosso do Sul State, Brazil. The results showed that the assessed alternatives can be used together or in different stages of studies aiming at urban planning and decision-making on the interventions to be applied.

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

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This paper describes a new methodology adopted for urban traffic stream optimization. By using Petri net analysis as fitness function of a Genetic Algorithm, an entire urban road network is controlled in real time. With the advent of new technologies that have been published, particularly focusing on communications among vehicles and roads infrastructures, we consider that vehicles can provide their positions and their destinations to a central server so that it is able to calculate the best route for one of them. Our tests concentrate on comparisons between the proposed approach and other algorithms that are currently used for the same purpose, being possible to conclude that our algorithm optimizes traffic in a relevant manner.