799 resultados para context-based retrieval


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Previous analyses of mitochondrial (mt)DNA and allozymes covering the range of the Iberian endemic golden-striped salamander, Chioglossa lusitanica, suggested a Pleistocene split of the historical species distribution into two population units (north and south of the Mondego river), postglacial expansion into the northernmost extant range, and secondary contact with neutral diffusion of genes close to the Mondego river. We extended analysis of molecular variation over the species range using seven microsatellite loci and the nuclear P-fibrinogen intron 7 (beta-fibint7). Both microsatellites and beta-fibint7 showed moderate to high levels of population structure, concordant with patterns detected with mtDNA and allozymes; and a general pattern of isolation-by-distance, contrasting the marked differentiation of two population groups suggested by mtDNA and allozymes. Bayesian multilocus analyses showed contrasting results as populations north and south of the Douro river were clearly differentiated based on microsatellites, whereas allozymes revealed differentiation north and south of the Mondego river. Additionally, decreased microsatellite variability in the north supported the hypothesis of postglacial colonization of this region. The well-documented evolutionary history of C. lusitanica, provides an excellent framework within which the advantages and limitations of different classes of markers can be evaluated in defining patterns of population substructure and inferring evolutionary processes across distinct spatio-temporal scales. The present study serves as a cautionary note for investigations that rely on a single type of molecular marker, especially when the organism under study exhibits a widespread distribution and complex natural history. (C) 2008 The Linnean Society of London, Biological Journal of the Linnean Society, 2008, 95, 371-387.

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Scientific research plays a fundamental role in the health and development of any society, since all technological advances depend ultimately on scientific discovery and the generation of wealth is intricately dependent on technological advance. Due to their importance, science and technology generally occupy important places in the hierarchical structure of developed societies, and they receive considerable public and private investment. Publicly funded science is almost entirely devoted to discovery, and it is administered and structured in a very similar way throughout the world. Particularly in the biological sciences, this structure, which is very much centered on the individual scientist and his own hypothesis-based investigations, may not be the best suited for either discovery in the context of complex biological systems, or for the efficient advancement of fundamental knowledge into practical utility. The adoption of other organizational paradigms, which permit a more coordinated and interactive research structure, may provide important opportunities to accelerate the scientific process and further enhance its relevance and contribution to society. The key alternative is a structure that incorporates larger organizational units to tackle larger and more complex problems. One example of such a unit is the research network. Brazil has utilized such networks to great effect in genome sequencing projects, demonstrating their relevance to the Brazilian research community and opening the possibility of their wider utility in the future.

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This article presents considerations about viability on reutilize existing web based e-Learning systems on Interactive Digital TV environment according to Digital TV standard adopted in Brazil. Considering the popularity of Moodle system in academic and corporative area, such system was chosen as a foundation for a survey into its properties to create a specification of an Application Programming Interface (API) for convergence to t-Learning characteristics that demands efforts in interface design area due the fact that computer and TV concepts are totally different. This work aims to present studies concerning user interface design during two stages: survey and detail of functionalities from an e-Learning system and how to adapt them for the Interactive TV regarding usability context and Information Architecture concepts.

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In the last years there was an exponential growth in the offering of Web-enabled distance courses and in the number of enrolments in corporate and higher education using this modality. However, the lack of efficient mechanisms that assures user authentication in this sort of environment, in the system login as well as throughout his session, has been pointed out as a serious deficiency. Some studies have been led about possible biometric applications for web authentication. However, password based authentication still prevails. With the popularization of biometric enabled devices and resultant fall of prices for the collection of biometric traits, biometrics is reconsidered as a secure remote authentication form for web applications. In this work, the face recognition accuracy, captured on-line by a webcam in Internet environment, is investigated, simulating the natural interaction of a person in the context of a distance course environment. Partial results show that this technique can be successfully applied to confirm the presence of users throughout the course attendance in an educational distance course. An efficient client/server architecture is also proposed. © 2009 Springer Berlin Heidelberg.

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Includes bibliography

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A method for context-sensitive analysis of binaries that may have obfuscated procedure call and return operations is presented. Such binaries may use operators to directly manipulate stack instead of using native call and ret instructions to achieve equivalent behavior. Since definition of context-sensitivity and algorithms for context-sensitive analysis have thus far been based on the specific semantics associated to procedure call and return operations, classic interprocedural analyses cannot be used reliably for analyzing programs in which these operations cannot be discerned. A new notion of context-sensitivity is introduced that is based on the state of the stack at any instruction. While changes in 'calling'-context are associated with transfer of control, and hence can be reasoned in terms of paths in an interprocedural control flow graph (ICFG), the same is not true of changes in 'stack'-context. An abstract interpretation based framework is developed to reason about stack-contexts and to derive analogues of call-strings based methods for the context-sensitive analysis using stack-context. The method presented is used to create a context-sensitive version of Venable et al.'s algorithm for detecting obfuscated calls. Experimental results show that the context-sensitive version of the algorithm generates more precise results and is also computationally more efficient than its context-insensitive counterpart. Copyright © 2010 ACM.

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This paper aims to examine the relevance of a production management model, in the shop-floor operations environment, that integrates the dimensions of production organisation (lean and mass production), work organisation (enriched and semi-autonomous groups) and knowledge management. A theoretical model has been applied to automotive companies to verify model adherence. Each of those dimensions has been described by factors. Shop-floor personnel interviews were conducted to confirm the factors relevance to that company. Results have shown that the model represented the reality of those companies concerning the researched dimensions. The factors allow managers to promote a favourable context for knowledge sharing. © 2010 Inderscience Enterprises Ltd.

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Calcium phosphate-based bioactive ceramics in various physical and chemical formulations have been extensively utilized as biomaterials for bone regeneration/conduction. However, the determination of their in vivo temporal behavior from the short to long term in humans has been a challenge due to the lack of physical reference for morphologic and morphometric evaluation. The present study evaluated bone morphology and morphometry (bone-to-implant contact [BIC]) around plasma-sprayed hydroxyapatite (PSHA)-coated endosseous implants that were retrieved due to prosthetic reasons while successfully in function at the posterior region of the jaws from as early as 2 months to ~13 years after a 6-month healing period after placement. Bone morphology was evaluated by light microscopy, and BIC was determined using computer software. Irrespective of the time in vivo, lamellar bone was observed in close contact with the implant PSHA-coated surface and between plateaus. BIC ranged from ~35-95%, was highly directional, and Haversian-like osteonic morphology between plateaus was observed for most implants. The PSHA coating was present with little variation in thickness between the samples retrieved regardless of time in vivo. © 2010 by Begell House, Inc.

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Includes bibliography

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Musical genre classification has been paramount in the last years, mainly in large multimedia datasets, in which new songs and genres can be added at every moment by anyone. In this context, we have seen the growing of musical recommendation systems, which can improve the benefits for several applications, such as social networks and collective musical libraries. In this work, we have introduced a recent machine learning technique named Optimum-Path Forest (OPF) for musical genre classification, which has been demonstrated to be similar to the state-of-the-art pattern recognition techniques, but much faster for some applications. Experiments in two public datasets were conducted against Support Vector Machines and a Bayesian classifier to show the validity of our work. In addition, we have executed an experiment using very recent hybrid feature selection techniques based on OPF to speed up feature extraction process. © 2011 International Society for Music Information Retrieval.

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Parkinson's disease (PD) automatic identification has been actively pursued over several works in the literature. In this paper, we deal with this problem by applying evolutionary-based techniques in order to find the subset of features that maximize the accuracy of the Optimum-Path Forest (OPF) classifier. The reason for the choice of this classifier relies on its fast training phase, given that each possible solution to be optimized is guided by the OPF accuracy. We also show results that improved other ones recently obtained in the context of PD automatic identification. © 2011 IEEE.

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Dental recognition is very important for forensic human identification, mainly regarding the mass disasters, which have frequently happened due to tsunamis, airplanes crashes, etc. Algorithms for automatic, precise, and robust teeth segmentation from radiograph images are crucial for dental recognition. In this work we propose the use of a graph-based algorithm to extract the teeth contours from panoramic dental radiographs that are used as dental features. In order to assess our proposal, we have carried out experiments using a database of 1126 tooth images, obtained from 40 panoramic dental radiograph images from 20 individuals. The results of the graph-based algorithm was qualitatively assessed by a human expert who reported excellent scores. For dental recognition we propose the use of the teeth shapes as biometric features, by the means of BAS (Bean Angle Statistics) and Shape Context descriptors. The BAS descriptors showed, on the same database, a better performance (EER 14%) than the Shape Context (EER 20%). © 2012 IEEE.

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Digital data sets constitute rich sources of information, which can be extracted and evaluated applying computational tools, for example, those ones for Information Visualization. Web-based applications, such as social network environments, forums and virtual environments for Distance Learning, are good examples for such sources. The great amount of data has direct impact on processing and analysis tasks. This paper presents the computational tool Mapper, defined and implemented to use visual representations - maps, graphics and diagrams - for supporting the decision making process by analyzing data stored in Virtual Learning Environment TelEduc-Unesp. © 2012 IEEE.

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Reuse of industrial and agricultural wastes as supplementary cementitious materials (SCMs) in concrete and mortar productions contribute to sustainable development. In this context, fluid catalytic cracking catalyst residue (spent FCC), a byproduct from the petroleum industry and petrol refineries, have been studied as SCM in blended Portland cement in the last years. Nevertheless, another environmental friendly alternative has been conducted in order to produce alternative binders with low CO2 emissions. The use of aluminosilicate materials in the production of alkali-activated materials (AAMs) is an ongoing research topic which can present low CO2 emissions associated. Hence, this paper studies some variables that can influence the production of AAM based on spent FCC. Specifically, the influence of SiO 2/Na2O molar ratio and the H2O/spent FCC mass ratio on the mechanical strength and microstructure are assessed. Some instrumental techniques, such as SEM, XRD, pH and electrical conductivity measurements, and MIP are performed in order to assess the microstructure of formed alkali-activated binder. Alkali activated mortars with compressive strength up to 80 MPa can be formed after curing for 3 days at 65°C. The research demonstrates the potential of spent FCC to produce alkali-activated cements and the importance of SiO2/Na2O molar ratio and the H2O/spent FCC mass ratio in optimising properties and microstructure. © 2013 Elsevier Ltd. All rights reserved.

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This paper presents a methodology for modeling high intensity discharge lamps based on artificial neural networks. The methodology provides a model which is able to represent the device operating in the frequency of distribution systems, facing events related to power quality. With the aid of a data acquisition system to monitor the laboratory experiment, and using $$\text{ MATLAB }^{\textregistered }$$ software, data was obtained for the training of two neural networks. These neural networks, working together, were able to represent with high fidelity the behavior of a discharge lamp. The excellent performance obtained by these models allowed the simulation of a group of lamps in a distribution system with shorter simulation time when compared to mathematical models. This fact justified the application of this family of loads in electric power systems. The representation of the device facing power quality disturbances also proved to be a useful tool for more complex studies in distribution systems. © 2013 Brazilian Society for Automatics - SBA.