911 resultados para Learning Orientation Activity


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This paper aims to find relations between the socioeconomic characteristics, activity participation, land use patterns and travel behavior of the residents in the Sao Paulo Metropolitan Area (SPMA) by using Exploratory Multivariate Data Analysis (EMDA) techniques. The variables influencing travel pattern choices are investigated using: (a) Cluster Analysis (CA), grouping and characterizing the Traffic Zones (17), proposing the independent variable called Origin Cluster and, (b) Decision Tree (DT) to find a priori unknown relations among socioeconomic characteristics, land use attributes of the origin TZ and destination choices. The analysis was based on the origin-destination home-interview survey carried out in SPMA in 1997. The DT application revealed the variables of greatest influence on the travel pattern choice. The most important independent variable considered by DT is car ownership, followed by the Use of Transportation ""credits"" for Transit tariff, and, finally, activity participation variables and Origin Cluster. With these results, it was possible to analyze the influence of a family income, car ownership, position of the individual in the family, use of transportation ""credits"" for transit tariff (mainly for travel mode sequence choice), activities participation (activity sequence choice) and Origin Cluster (destination/travel distance choice). (c) 2010 Elsevier Ltd. All rights reserved.

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The Learning Object (OA) is any digital resource that can be reused to support learning with specific functions and objectives. The OA specifications are commonly offered in SCORM model without considering activities in groups. This deficiency was overcome by the solution presented in this paper. This work specified OA for e-learning activities in groups based on SCORM model. This solution allows the creation of dynamic objects which include content and software resources for the collaborative learning processes. That results in a generalization of the OA definition, and in a contribution with e-learning specifications.

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One of the e-learning environment goal is to attend the individual needs of students during the learning process. The adaptation of contents, activities and tools into different visualization or in a variety of content types is an important feature of this environment, bringing to the user the sensation that there are suitable workplaces to his profile in the same system. Nevertheless, it is important the investigation of student behaviour aspects, considering the context where the interaction happens, to achieve an efficient personalization process. The paper goal is to present an approach to identify the student learning profile analyzing the context of interaction. Besides this, the learning profile could be analyzed in different dimensions allows the system to deal with the different focus of the learning.

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In this paper, a framework for detection of human skin in digital images is proposed. This framework is composed of a training phase and a detection phase. A skin class model is learned during the training phase by processing several training images in a hybrid and incremental fuzzy learning scheme. This scheme combines unsupervised-and supervised-learning: unsupervised, by fuzzy clustering, to obtain clusters of color groups from training images; and supervised to select groups that represent skin color. At the end of the training phase, aggregation operators are used to provide combinations of selected groups into a skin model. In the detection phase, the learned skin model is used to detect human skin in an efficient way. Experimental results show robust and accurate human skin detection performed by the proposed framework.

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This paper investigates how to make improved action selection for online policy learning in robotic scenarios using reinforcement learning (RL) algorithms. Since finding control policies using any RL algorithm can be very time consuming, we propose to combine RL algorithms with heuristic functions for selecting promising actions during the learning process. With this aim, we investigate the use of heuristics for increasing the rate of convergence of RL algorithms and contribute with a new learning algorithm, Heuristically Accelerated Q-learning (HAQL), which incorporates heuristics for action selection to the Q-Learning algorithm. Experimental results on robot navigation show that the use of even very simple heuristic functions results in significant performance enhancement of the learning rate.

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How does knowledge management (KM) by a government agency responsible for environmental impact assessment (EIA) potentially contribute to better environmental assessment and management practice? Staff members at government agencies in charge of the EIA process are knowledge workers who perform judgement-oriented tasks highly reliant on individual expertise, but also grounded on the agency`s knowledge accumulated over the years. Part of an agency`s knowledge can be codified and stored in an organizational memory, but is subject to decay or loss if not properly managed. The EIA agency operating in Western Australia was used as a case study. Its KM initiatives were reviewed, knowledge repositories were identified and staff surveyed to gauge the utilisation and effectiveness of such repositories in enabling them to perform EIA tasks. Key elements of KM are the preparation of substantive guidance and spatial information management. It was found that treatment of cumulative impacts on the environment is very limited and information derived from project follow-up is not properly captured and stored, thus not used to create new knowledge and to improve practice and effectiveness. Other opportunities for improving organizational learning include the use of after-action reviews. The learning about knowledge management in EIA practice gained from Western Australian experience should be of value to agencies worldwide seeking to understand where best to direct their resources for their own knowledge repositories and environmental management practice. (C) 2011 Elsevier Ltd. All rights reserved.

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The water activity of aqueous solutions of EO-PO block copolymers of six different molar masses and EO/PO ratios and of maltodextrins of three different molar masses was determined at 298.15 K. The results showed that these aqueous solutions present a negative deviation from Raoult`s law. The Flory-Huggins and UNIFAC excess Gibbs energy models were employed to model the experimental data. While a good agreement was obtained with the Flory-Huggins equation, discrepancies were observed when predicting the experimental behavior with the UNIFAC model. The water activities of ternary systems formed by a synthetic polymer, maltodextrin and water were also measured and used to test the predictive capability of both models.

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Experimental results for the activity of water in aqueous solutions of 10 single, synthetic polyelectrolytes (polysodium acrylate, polysodium methacrylate, polyammonium acrylate, polysodium ethylene sulfonate, and polysodium styrene sulfonate) and sodium chloride at 298.2 K are presented. The experimental work was performed by applying the isopiestic method with sodium chloride as a reference substance. As expected, the activity of water decreases when the concentration of a polyelectrolyte and/or sodium chloride increases. At constant concentration of a polyelectrolyte and sodium chloride, the activity of water depends on the monomer unit and the molecular mass of the polyelectrolyte. The new data are to be used in future work to develop and test models for the Gibbs excess energy of aqueous solutions of polyelectrolytes.

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Experimental results for the activity of water in aqueous solutions of 10 single polyelectrolytes (two polysodium acrylates, two polysodium methacrylates, three polyammonium acrylates, two polysodium ethylene sulfonates, and one polysodium styrene sulfonate) at (298.2 and 323.2) K are reported. The isopiestic method was employed in these experiments with aqueous solutions of sodium chloride as references. The polyelectrolytes were characterized by three averaged molecular masses determined by gel permeation chromatography. Furthermore, the density and the refractive index increments of the aqueous polyelectrolyte solutions are reported. Although a similar pattern for the activity of water was observed for all systems (i.e., the osmotic coefficient increases with rising polyelectrolyte concentration), the experimental results show that this property depends on the monomer type as well as on the size of the polymer chain. The temperature (varied from (298.2 to 323.2) K) has only a small influence on the activity of water.

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We address here aspects of the implementation of a memory evolutive system (MES), based on the model proposed by A. Ehresmann and J. Vanbremeersch (2007), by means of a simulated network of spiking neurons with time dependent plasticity. We point out the advantages and challenges of applying category theory for the representation of cognition, by using the MES architecture. Then we discuss the issues concerning the minimum requirements that an artificial neural network (ANN) should fulfill in order that it would be capable of expressing the categories and mappings between them, underlying the MES. We conclude that a pulsed ANN based on Izhikevich`s formal neuron with STDP (spike time-dependent plasticity) has sufficient dynamical properties to achieve these requirements, provided it can cope with the topological requirements. Finally, we present some perspectives of future research concerning the proposed ANN topology.

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This work characterizes the analog performance of SOI n-MuGFETs with HfSiO gate dielectric and TiN metal gate with respect to the influence of the high-k post-nitridation. TiN thickness and device rotation. A thinner TiN metal gate is found favorable for improved analog characteristics showing an increase in intrinsic voltage gain. The devices where the high-k material is subjected to a nitridation step indicated a degradation of the Early voltage (V(EA)) values which resulted in a lower voltage gain. The 45 degrees rotated devices have a smaller V(EA) than the standard ones when a HfSiO dielectric is used. However, the higher transconductance of these devices, due to the increased mobility in the (1 0 0) sidewall orientation, compensates this V(EA) degradation of the voltage gain, keeping it nearly equal to the voltage gain values of the standard devices. (C) 2011 Elsevier Ltd. All rights reserved.

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The antiproliferative activity of two prenylated benzophenones isolated from Rheedia brasiliensis. the tri-prenylated garciniaphenone and the tetraprenylated benzophenone 7-epiclusianone, was investigated against human cancer cell lines. The antiproliferative activity on melanoma (UACC-62), breast (MCF-7), drug-resistant breast (NCI-ADR), lung/non-small cells (NCI460), ovarian (OVCAR 03), prostate (PC03), kidney (786-0), lung (NCI-460) and tongue (CRL-1624 and CRL-1623) cancer cells was determined using spectrophotometric quantification of the cellular protein content. The effect of these benzophenones on the activity of cathepsins B and G was also investigated. Garciniaphenone displayed cytostatic activity in all cell lines, whereas 7-epiclusianone showed a dose-dependent cytotoxic effect. The IC(50) values for cell proliferation revealed that 7-epiclusianone is more active than garciniaphenone against most of the cell lines. Furthermore, the antiproliferative effects demonstrated by garciniaphenone and 7-epiclusianone were related to their cathepsin inhibiting properties. In conclusion, 7-epiclusianone is a promising naturally occurring agent which displays multiple inhibitory effects which may be working in concert to inhibit cancer cell proliferation in vitro. The putative pathway by which 7-epiclusianone affects cancer cell development may involve cathepsin inhibition. Copyright (C) 2009 John Wiley & Sons, Ltd.

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This in vitro study evaluated the antimicrobial activity of extracts obtained from Rheedia brasiliensis fruit (bacupari) and its bioactive compound against Streptococcus mutans. Hexane, ethyl-acetate and ethanolic extracts obtained (concentrations ranging from 6.25 to 800 mu g/ml) were tested against S. mutans UA159 through MIC/MBC assays. S. mutans 5-days-old biofilms were treated with the active extracts (100 x MIC) for 0, 1, 2, 3 and 4 h (time-kill) and plated for colony counting (CFU/ml). Active extracts were submitted to exploratory chemical analyses so as to isolate and identify the bioactive compound using spectroscopic methods. The bioactive compound (concentrations ranging from 0.625 to 80 mu g/ml) was then tested through MIC/MBC assays. Peel and seed hexane extracts showed antimicrobial activity against planktonic cells at low concentrations and were thus selected for the time kill test. These hexane extracts reduced S. mutans biofilm viability after 4 h, certifying of the bioactive compound presence. The bioactive compound identified was the polyprenylated benzophenone 7-epiclusianone, which showed a good antimicrobial activity at low concentrations (MIC: 1.25-2.5 mu g/ml; MBC: 10-20 mu g/ml). The results indicated that 7-epiclusianone may be used as a new agent to control S. mutans biofilms; however, more studies are needed to further elucidate the mechanisms of action and the anticariogenic potential of such compound found in R. brasiliensis. (C) 2008 Elsevier GmbH. All rights reserved.

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We progressively reduced the complexity of humic matter by a mild sequential removal of unbound or free components, weakly, and strongly bound molecules. The auxin-like response of residues from each step was tested using tomato (cv. Micro-Tom) seedlings expressing DR5 auxin synthetic promoter fused to the beta-glucuronidase (GUS) reporter gene and the low auxin-sensitivity diageotropica (dgt) mutant. Both exogenous auxin and humic matter promoted lateral root emergence in the control, but failed to induce lateral roots in the dgt mutant. When strongly bound components were removed from humic matter by breaking the ester and ether bonds, the humic residues lost their ability to induce the DR5

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Plants synthesize a variety of molecules to defend themselves against an attack by insects. Talisin is a reserve protein from Talisia esculenta seeds, the first to be characterized from the family Sapindaceae. In this study, the insecticidal activity of Talisin was tested by incorporating the reserve protein into an artificial diet fed to the velvetbean caterpillar Anticarsia gemmatalis, the major pest of soybean crops in Brazil. At 1.5% (w/w) of the dietary protein, Talisin affected larval growth, pupal weight, development and mortality, adult fertility and longevity, and produced malformations in pupae and adult insects. Talisin inhibited the trypsin-like activity of larval midgut homogenates. The trypsin activity in Talisin-fed larvae was sensitive to Talisin, indicating that no novel protease-resistant to Talisin was induced in Talisin-fed larvae. Affinity chromatography showed that Talisin bound to midgut proteinases of the insect A. gemmatalis, but was resistant to enzymatic digestion by these larval proteinases. The transformation of genes coding for this reserve protein could be useful for developing insect resistant crops. (C) 2010 Elsevier Inc. All rights reserved.