20 resultados para Integrated learning systems
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)
Resumo:
Promoting the inclusion of students with disabilities in e-learning systems has brought many challenges for researchers and educators. The use of synchronous communication tools such as interactive whiteboards has been regarded as an obstacle for inclusive education. In this paper, we present the proposal of an inclusive approach to provide blind students with the possibility to participate in live learning sessions with whiteboard software. The approach is based on the provision of accessible textual descriptions by a live mediator. With the accessible descriptions, students are able to navigate through the elements and explore the content of the class using screen readers. The method used for this study consisted of the implementation of a software prototype within a virtual learning environment and a case study with the participation of a blind student in a live distance class. The results from the case study have shown that this approach can be very effective, and may be a starting point to provide blind students with resources they had previously been deprived from. The proof of concept implemented has shown that many further possibilities may be explored to enhance the interaction of blind users with educational content in whiteboards, and further pedagogical approaches can be investigated from this proposal. (C) 2009 Elsevier Ltd. All rights reserved.
Resumo:
Two different fuzzy approaches to voltage control in electric power distribution systems are introduced in this paper. The real-time controller in each case would act on power transformers equipped with under-load tap changers. Learning systems are employed to turn the voltage-control relays into adaptive devices. The scope of this study has been limited to the power distribution substation, and the voltage measurements and control actions are carried out on the secondary bus. The capacity of fuzzy systems to handle approximate data, together with their unique ability to interpret qualitative information, make it possible to design voltage-control strategies that satisfy the requirements of the Brazilian regulatory bodies and the real concerns of the electric power distribution companies. Fuzzy control systems based on these two strategies have been implemented and the test results were highly satisfactory.
Resumo:
This paper uses a fully operational inter-regional computable general equilibrium (CGE) model implemented for the Brazilian economy, based on previous work by Haddad and Hewings, in order to assess the likely economic effects of road transportation policy changes in Brazil. Among the features embedded in this framework, modelling of external scale economies and transportation costs provides an innovative way of dealing explicitly with theoretical issues related to integrated regional systems. The model is calibrated for 109 regions. The explicit modelling of transportation costs built into the inter-regional CGE model, based on origin-destination flows, which takes into account the spatial structure of the Brazilian economy, creates the capability of integrating the inter-regional CGE model with a geo-coded transportation network model enhancing the potential of the framework in understanding the role of infrastructure on regional development. The transportation model used is the so-called Highway Development and Management, developed by the World Bank, implemented using the software TransCAD. Further extensions of the current model specification for integrating other features of transport planning in a continental industrialising country like Brazil are discussed, with the goal of building a bridge between conventional transport planning practices and the innovative use of CGE models. In order to illustrate the analytical power of the integrated system, the authors present a set of simulations, which evaluate the ex ante economic impacts of physical/qualitative changes in the Brazilian road network (for example, a highway improvement), in accordance with recent policy developments in Brazil. Rather than providing a critical evaluation of this debate, they intend to emphasise the likely structural impacts of such policies. They expect that the results will reinforce the need to better specifying spatial interactions in inter-regional CGE models.
Resumo:
In a local production system (LPS), besides external economies, the interaction, cooperation, and learning are indicated by the literature as complementary ways of enhancing the LPS's competitiveness and gains. In Brazil, the greater part of LPSs, mostly composed by small enterprises, displays incipient relationships and low levels of interaction and cooperation among their actors. The size of the participating enterprises itself for specificities that engender organizational constraints, which, in turn, can have a considerable impact on their relationships and learning dynamics. For that reason, it is the purpose of this article to present an analysis of interaction, cooperation, and learning relationships among several types of actors pertaining to an LPS in the farming equipment and machinery sector, bearing in mind the specificities of small enterprises. To this end, the fieldwork carried out in this study aimed at: (i) investigating external and internal knowledge sources conducive to learning and (ii) identifying and analyzing motivating and inhibiting factors related to specificities of small enterprises in order to bring the LPS members closer together and increase their cooperation and interaction. Empirical evidence shows that internal aspects of the enterprises, related to management and infrastructure, can have a strong bearing on their joint actions, interaction and learning processes.
Resumo:
In geophysics and seismology, raw data need to be processed to generate useful information that can be turned into knowledge by researchers. The number of sensors that are acquiring raw data is increasing rapidly. Without good data management systems, more time can be spent in querying and preparing datasets for analyses than in acquiring raw data. Also, a lot of good quality data acquired at great effort can be lost forever if they are not correctly stored. Local and international cooperation will probably be reduced, and a lot of data will never become scientific knowledge. For this reason, the Seismological Laboratory of the Institute of Astronomy, Geophysics and Atmospheric Sciences at the University of Sao Paulo (IAG-USP) has concentrated fully on its data management system. This report describes the efforts of the IAG-USP to set up a seismology data management system to facilitate local and international cooperation.
Resumo:
Cooling towers are widely used in many industrial and utility plants as a cooling medium, whose thermal performance is of vital importance. Despite the wide interest in cooling tower design, rating and its importance in energy conservation, there are few investigations concerning the integrated analysis of cooling systems. This work presents an approach for the systemic performance analysis of a cooling water system. The approach combines experimental design with mathematical modeling. An experimental investigation was carried out to characterize the mass transfer in the packing of the cooling tower as a function of the liquid and gas flow rates, whose results were within the range of the measurement accuracy. Then, an integrated model was developed that relies on the mass and heat transfer of the cooling tower, as well as on the hydraulic and thermal interactions with a heat exchanger network. The integrated model for the cooling water system was simulated and the temperature results agree with the experimental data of the real operation of the pilot plant. A case study illustrates the interaction in the system and the need for a systemic analysis of cooling water system. The proposed mathematical and experimental analysis should be useful for performance analysis of real-world cooling water systems. (C) 2009 Elsevier Ltd. All rights reserved.
Resumo:
We propose and analyze two different Bayesian online algorithms for learning in discrete Hidden Markov Models and compare their performance with the already known Baldi-Chauvin Algorithm. Using the Kullback-Leibler divergence as a measure of generalization we draw learning curves in simplified situations for these algorithms and compare their performances.
Resumo:
A simple and easy approach to produce polymeric microchips with integrated copper electrodes for capacitively coupled contactless conductivity detection (CD) is described. Copper electrodes were fabricated using a printed circuit board (PCB) as an inexpensive thin-layer of metal. The electrode layout was first drawn and laser printed on a wax paper sheet. The toner layer deposited on the paper sheet was thermally transferred to the PCB surface working as a mask for wet chemical etching of the copper layer. After the etching step, the toner was removed with an acetonitrile-dampened cotton. A poly(ethylene terephthalate) (PET) film coated with a thin thermo-sensitive adhesive layer was used to laminate the PCB plate providing an insulator layer of the electrodes to perform CID measurements. Electrophoresis microchannels were fabricated in poly(dimethylsiloxane) (PDMS) by soft lithography and reversibly sealed against the PET film. These hybrid PDMS/PET chips exhibited a stable electroosmotic mobility of 4.25 +/- 0.04 x 10(-4) V cm(-2) s(-1), at pH 6.1, over fifty runs. Efficiencies ranging from 1127 to 1690 theoretical plates were obtained for inorganic cations.
Resumo:
Two screenings of commercial lipases were performed to find a lipase with superior performance for the integrated production of biodiesel and monoglycerides. The first screening was carried out under alcoholysis conditions using ethanol as acyl acceptor to convert triglycerides to their corresponding ethyl esters (biodiesel). The second screening was performed under glycerolysis conditions to yield monoglycerides (MG). All lipases were immobilized on silica-PVA composite by covalent immobilization. The assays were performed using babassu oil and alcohols (ethanol or glycerol) in solvent free systems. For both substrates, lipase from Burkholderia cepacia (lipase PS) was found to be the most suitable enzyme to attain satisfactory yields. To further improve the process, the Response Surface Methodology (RSM) was used to determine the optima operating conditions for each biotransformation. For biodiesel production, the highest transesterification yield (>98%) was achieved within 48 h reaction at 39 degrees C using an oil-to-ethanol molar ratio of 1:7. For MG production, optima conditions corresponded to oil-to-glycerol molar ratio of 1: 15 at 55 degrees C, yielding 25 wt.% MG in 6 h reaction. These results show the potential of B. cepacia lipase to catalyze both reactions and the feasibility to consider an integrated approach for biodiesel and MG production. (C) 2009 Elsevier Ltd. All rights reserved.
Resumo:
This article discusses possible approaches for optical network capacity upgrade by considering the use of different modulation formats at 40 Gb/s. First, a performance evaluation is carried out regarding tolerance to three impairments: spectral narrowing due to filter cascading, chromatic dispersion, and self-phase modulation. Next, a cost-benefit analysis is conducted, considering the specific optoelectronic components required for the optical transmitter/receiver configuration of each format.
Resumo:
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.
Resumo:
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.
Resumo:
In this paper, a novel adaptive strategy to obtain technically justified fault-ride-through requirements for wind turbines (WTs) is proposed. The main objective is to promote an effective integration of wind turbines into power systems with still low penetration levels of wind power based on technical and economical considerations. The level of requirement imposed by the strategy is increased stepwise over time, depending on system characteristics and on wind power penetration level. The idea behind is to introduce stringent requirements only when they are technically needed for a reliable and secure power system operation. Voltage stability support and fault-ride-through requirements are considered in the strategy. Simulations are based on the Chilean transmission network, a midsize isolated power system with still low penetration levels of wind power. Simulations include fixed speed induction generators and doubly fed induction generators. The effects on power system stability of the wind power injections, integrated into the network by adopting the adaptive strategy, are compared with the effects that have the same installed capacity of wind power but only considering WTs able to fulfill stringent requirements (fault-ride-through capability and support voltage stability). Based on simulations and international experience, technically justified requirements for the Chilean case are proposed.
Resumo:
This paper concern the development of a stable model predictive controller (MPC) to be integrated with real time optimization (RTO) in the control structure of a process system with stable and integrating outputs. The real time process optimizer produces Optimal targets for the system inputs and for Outputs that Should be dynamically implemented by the MPC controller. This paper is based oil a previous work (Comput. Chem. Eng. 2005, 29, 1089) where a nominally stable MPC was proposed for systems with the conventional control approach where only the outputs have set points. This work is also based oil the work of Gonzalez et at. (J. Process Control 2009, 19, 110) where the zone control of stable systems is studied. The new control for is obtained by defining ail extended control objective that includes input targets and zone controller the outputs. Additional decision variables are also defined to increase the set of feasible solutions to the control problem. The hard constraints resulting from the cancellation of the integrating modes Lit the end of the control horizon are softened,, and the resulting control problem is made feasible to a large class of unknown disturbances and changes of the optimizing targets. The methods are illustrated with the simulated application of the proposed,approaches to a distillation column of the oil refining industry.
Resumo:
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.