955 resultados para hybrid learning


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Hybrid matrices of polysiloxane-polyvinyl alcohol (POS-PVA) were prepared by sol-gel technique using different concentrations of the organic component (polyvinyl alcohol, PVA) in the synthesis medium. The goal was to prepare carriers for immobilizing enzyme by taking into consideration properties as hardness, mean pore diameter, specific surface area and pore size distribution. The matrices were activated with sodium metaperiodate to render functional groups for binding the lipase from Candida rugosa, used here as a study model. Results showed that low proportion of PVA gave POS-PVA with low surface area and pore volume, although with higher hardness. The chemical activation decreased the pore volume and increased the pore size with a decrease on the surface area of about 60-75%. The matrices for enzyme immobilization were chosen considering the best combination of high surface area and hardness. Thus, the POS-PVA prepared with 5.56 x 10(-5) M of PVA with a surface area of 123 m(2)/g and hardness of 71 HV (50 gf 30 s) was shown to be suitable to immobilize the lipase, with an immobilization yield of about 40%. (c) 2008 Elsevier B.V. All rights reserved.

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Candida rugosa lipase was immobilized by covalent binding on hybrid matrix of polysiloxane-polyvinyl alcohol chemically modified with different activating agents as glutaraldehyde, sodium metaperiodate and carbonyldiimidazole. The experimental results suggested that functional activating agents render different interactions between enzyme and support, producing consequently alterations in the optimal reaction conditions. Properties of the immobilized systems were assessed and their performance on hydrolytic and synthetic reactions were evaluated and compared with the free enzyme. In hydrolytic reactions using p-nitrophenyl palmitate as substrate all immobilized systems showed higher thermal stability and optima pH and temperature values in relation to the free lipase. Among the activating compounds, carbonyldiimidazole resulted in a total recovery of activity on the support and the highest thermal stability. For the butyl butyrate synthesis, the best performance (molar conversion of 95% and volumetric productivity of 2.33 g L-1 h(-1)) was attained with the lipase immobilized on POS-PVA activated with sodium metaperiodate. The properties of the support and immobilized derivatives were also evaluated by scanning electron microscopy (SEM), energy dispersive X-ray spectroscopies and chemical composition (FTIR). (c) 2007 Elsevier B.V. All rights reserved.

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This work aimed at the production of stabilized derivatives of Thermomyces lanuginosus lipase (TLL) by multipoint covalent immobilization of the enzyme on chitosan-based matrices. The resulting biocatalysts were tested for synthesis of biodiesel by ethanolysis of palm oil. Different hydrogels were prepared: chitosan alone and in polyelectrolyte complexes (PEC) with kappa-carrageenan, gelatin, alginate, and polyvinyl alcohol (PVA). The obtained supports were chemically modified with 2,4,6-trinitrobenzene sulfonic acid (TNBS) to increase support hydrophobicity, followed by activation with different agents such as glycidol (GLY), epichlorohydrin (EPI), and glutaraldehyde (GLU). The chitosan-alginate hydrogel, chemically modified with TNBS, provided derivatives with higher apparent hydrolytic activity (HA(app)) and thermal stability, being up to 45-fold more stable than soluble lipase. The maximum load of immobilized enzyme was 17.5 mg g(-1) of gel for GLU, 7.76 mg g(-1) of gel for GLY, and 7.65 mg g(-1) of gel for EPI derivatives, the latter presenting the maximum apparent hydrolytic activity (364.8 IU g(-1) of gel). The three derivatives catalyzed conversion of palm oil to biodiesel, but chitosan-alginate-TNBS activated via GLY and EPI led to higher recovered activities of the enzyme. Thus, this is a more attractive option for both hydrolysis and transesterification of vegetable oils using immobilized TLL, although industrial application of this biocatalyst still demands further improvements in its half-life to make the enzymatic process economically attractive.

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A hybrid system to automatically detect, locate and classify disturbances affecting power quality in an electrical power system is presented in this paper. The disturbances characterized are events from an actual power distribution system simulated by the ATP (Alternative Transients Program) software. The hybrid approach introduced consists of two stages. In the first stage, the wavelet transform (WT) is used to detect disturbances in the system and to locate the time of their occurrence. When such an event is flagged, the second stage is triggered and various artificial neural networks (ANNs) are applied to classify the data measured during the disturbance(s). A computational logic using WTs and ANNs together with a graphical user interface (GU) between the algorithm and its end user is then implemented. The results obtained so far are promising and suggest that this approach could lead to a useful application in an actual distribution system. (C) 2009 Elsevier Ltd. All rights reserved.

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Generally, quadriplegic individuals have difficulties performing object manipulation. Toward satisfactory manipulation, reach and grasp movements must be performed with voluntary control, and for that, grasp force feedback is essential. A hybrid system aiming at partial upper limb sensory-motor restoration for quadriplegics was built. Such device is composed of an elbow dynamic orthosis that provides elbow flexion/extension (range was approximately from 20 degrees to 120 degrees, and average angular speed was approximately 15 degrees/s) with forearm support, a wrist static orthosis and neuromuscular electrical stimulation for grasping generation, and a glove with force sensors that allows grasping force feedback. The glove presents two user interface modes: visual by light emitting diodes or audio emitted by buzzer. Voice control of the entire system (elbow dynamic orthosis and electrical stimulator) is performed by the patient. The movements provided by the hybrid system, combined with the scapular and shoulder movements performed by the patient, can aid quadriplegic individuals in tasks that involve reach and grasp movements.

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The confined flows in tubes with permeable surfaces arc associated to tangential filtration processes (microfiltration or ultrafiltration). The complexity of the phenomena do not allow for the development of exact analytical solutions, however, approximate solutions are of great interest for the calculation of the transmembrane outflow and estimate of the concentration, polarization phenomenon. In the present work, the generalized integral transform technique (GITT) was employed in solving the laminar and permanent flow in permeable tubes of Newtonian and incompressible fluid. The mathematical formulation employed the parabolic differential equation of chemical species conservation (convective-diffusive equation). The velocity profiles for the entrance region flow, which are found in the connective terms of the equation, were assessed by solutions obtained from literature. The velocity at the permeable wall was considered uniform, with the concentration at the tube wall regarded as variable with an axial position. A computational methodology using global error control was applied to determine the concentration in the wall and concentration boundary layer thickness. The results obtained for the local transmembrane flux and the concentration boundary layer thickness were compared against others in literature. (C) 2007 Elsevier B.V. All rights reserved.

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This study proposes a new PSOS-model based damage identification procedure using frequency domain data. The formulation of the objective function for the minimization problem is based on the Frequency Response Functions (FRFs) of the system. A novel strategy for the control of the Particle Swarm Optimization (PSO) parameters based on the Nelder-Mead algorithm (Simplex method) is presented; consequently, the convergence of the PSOS becomes independent of the heuristic constants and its stability and confidence are enhanced. The formulated hybrid method performs better in different benchmark functions than the Simulated Annealing (SA) and the basic PSO (PSO(b)). Two damage identification problems, taking into consideration the effects of noisy and incomplete data, were studied: first, a 10-bar truss and second, a cracked free-free beam, both modeled with finite elements. In these cases, the damage location and extent were successfully determined. Finally, a non-linear oscillator (Duffing oscillator) was identified by PSOS providing good results. (C) 2009 Elsevier Ltd. All rights reserved

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This work is related to the so-called non-conventional finite element formulations. Essentially, a methodology for the enrichment of the initial approximation which is typical of the meshless methods and based on the clouds concept is introduced in the hybrid-Trefftz formulation for plane elasticity. The formulation presented allows for the approximation and direct enrichment of two independent fields: stresses in the domains and displacements on the boundaries of the elements. Defined by a set of elements and interior boundaries sharing a common node, the cloud notion is employed to select the enrichment support for the approximation fields. The numerical analysis performed reveals an excellent performance of the resulting formulation, characterized by the good approximation ability and a reduced computational effort. Copyright (C) 2009 John Wiley & Sons, Ltd.

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A round robin program zoos conducted to assess the ability of three different X-radiographic systems for imaging internal fatigue cracks in riveted lap joints of composite glass reinforced fiber/metal laminate. From an engineering perspective, conventional film radiography and direct radiography have produced the best results, identifying and characterizing in detail internal damage on metallic faying surfaces of fastened glass reinforced fiber/metal laminate joints. On the other hand, computed radiographic images presented large projected geometric distortions and feature shifts due to the angular incident radiation beam, disclosing only partial internal cracking patterns.

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This paper presents a strategy for the solution of the WDM optical networks planning. Specifically, the problem of Routing and Wavelength Allocation (RWA) in order to minimize the amount of wavelengths used. In this case, the problem is known as the Min-RWA. Two meta-heuristics (Tabu Search and Simulated Annealing) are applied to take solutions of good quality and high performance. The key point is the degradation of the maximum load on the virtual links in favor of minimization of number of wavelengths used; the objective is to find a good compromise between the metrics of virtual topology (load in Gb/s) and of the physical topology (quantity of wavelengths). The simulations suggest good results when compared to some existing in the literature.

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Power distribution automation and control are import-ant tools in the current restructured electricity markets. Unfortunately, due to its stochastic nature, distribution systems faults are hardly avoidable. This paper proposes a novel fault diagnosis scheme for power distribution systems, composed by three different processes: fault detection and classification, fault location, and fault section determination. The fault detection and classification technique is wavelet based. The fault-location technique is impedance based and uses local voltage and current fundamental phasors. The fault section determination method is artificial neural network based and uses the local current and voltage signals to estimate the faulted section. The proposed hybrid scheme was validated through Alternate Transient Program/Electromagentic Transients Program simulations and was implemented as embedded software. It is currently used as a fault diagnosis tool in a Southern Brazilian power distribution company.

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Several studies using vegetable fibers as the exclusive reinforcement in fiber-cement composites have shown acceptable mechanical performance at the first ages. However, after the exposure to accelerated aging tests, these composites have shown significant reduction in the toughness or increase in embrittlement. This was mainly attributed to the improved fiber-matrix adhesion and fiber mineralization after aging process. The objective of the present research was to evaluate composites produced by the slurry dewatering technique followed by pressing and air curing, reinforced with combinations of polypropylene fibers and sisal kraft pulp at different pulp freeness. The physical properties, mechanical performance, and microstructural characteristics of the composites were evaluated before and after accelerated and natural aging. Results showed the great contribution of pulp refinement on the improvement of the mechanical strength in the composites. Higher intensities of refinement resulted in higher modulus of rupture for the composites with hybrid reinforcement after accelerated and natural aging. The more compact microstructure was due to the improved packing of the mineral particles with refined sisal pulp. The toughness of the composites after aging was maintained in relation to the composites at 28 days of cure.

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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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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.