879 resultados para Transferred Demand
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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The use of refrigeration and air conditioning systems is of fundamental importance when it comes to air-conditioning of environments. Also important is the use of electricity for equipments’ operation related to these systems. Due to high cost of charging for this type of energy, factors economy and efficiency occupy key roles among design parameters of a system. One of the ways to get this economy is the use of a technique called thermal storage, or cold storage, which intends to move the required loads during peak time and also their equalizing, so that the energy is transferred from the peak time to non-peak time, thereby reducing the cost of energy consumed. Cold can be stored in the form of ice or ice water. This work aims to perform a technical-economic analysis of a mall located in Vale do Paraíba checking the feasibility of deploying a thermal storage system to achieve an economy in the cost of the energy used by the establishment. Through the parameters measured by the concessionaire of energy we can get the values of energy demand and power consumed, which will serve as basis for calculation for the study. The results obtained allow the development of two alternative proposals to the current configuration, one chosen by the criteria and results presented by technical-economic and energy analysis
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The arterial hypertension is a chronic disease, which can be controlled by changing the way of life, as well as by drug treatment, which demand specific Health Care sequence. The lack of adherence to sequence/treatment is one of the main obstacles the disease control. Characterize and analyze the profile of Health Care usage by a 192 patient cohort diagnosed with arterial hypertension in 1995, between the period of 2001 – 2005 and 2006 – 2010. It is a longitudinal study, retrospective and descriptive developed on School Health Center(SHC) which belongs to School of Medicine Botucatu –UNESP, in continuity of the previous research which has analyzed the sequence of the referred sample between the period of 1995 – 1999. The database was obtained from the patients records by using structured adapted forms appointed in the previous study phase. In the case there were transfers to other Health Care facilities, the database was obtained by the records either, while the patients attended the CSE. The database was analyzed by means of descriptive statistics. Predominated the patients in the age from 50 – 69 (47,9%), whites (93,2%), female (56,7%) with low level of education (72,7%). In the period of 2001 - 2005, 76 (39,5%) of the patients remained under sequence, and that 44 (22,9%) belonged to adherence group (GAD), 17 belonged to abandonment/adherent group (GAB/GAD) and 15 to the abandonment group (GAB), groups which were already identified by the study which has analyzed the period of 1995 – 1999. At the end of the third period of the sample sequence (2006 – 2010), 60 (31,2%) of the patients kept under medical sequence. The cohort’s mortality rate in the period reached 15,1% and 21,9% were transferred to other Municipal Health Care facilities. We conclude that the Health Care service usage by the 192 sample’s integrants kept the same model already identified in the previous analysis... (Complete abstract click electronic access below)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Given the competitive reality of the globalized market, companies are compelled to develop strategic aspects of the management process, in order to ensure their survival. Among the strategic aspects is the price formation process, whose reasoning occurs mainly of adoption through cost system. Knowledge of costs and expenses provides conditions for the company to position itself strategically in the market, being able to follow the price of competition and sometimes even surpass them, called, more and more attention with regard to price formation. This study aims to identify the best price to be transferred to the market. To this end, were approached concept of pricing and its components, their strategies and pricing objectives, as well as the influence of demand on price formation, as well as the added value the brand and quality; and even a careful analysis of the price established by the said company in the service offered. We used the method of literature review and case study in the company ESA international aeronautical industry. Thus, we sought to explain about the main concepts for pricing in order to support decision making
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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In this work it is discussed the performance of the reactive power demand in three-leg transformer core and three-phase transformer bank, under different conditions of AC/DC double excitation. In order to analyse the influence of double excitation in reactive power theoretically a mathematical model was developed considering the mutual coupling between phases and the magnetic nonlinearity. The validity of the proposed model is verified by means of the experimental and simulated results.
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Considering the importance of spatial issues in transport planning, the main objective of this study was to analyze the results obtained from different approaches of spatial regression models. In the case of spatial autocorrelation, spatial dependence patterns should be incorporated in the models, since that dependence may affect the predictive power of these models. The results obtained with the spatial regression models were also compared with the results of a multiple linear regression model that is typically used in trips generation estimations. The findings support the hypothesis that the inclusion of spatial effects in regression models is important, since the best results were obtained with alternative models (spatial regression models or the ones with spatial variables included). This was observed in a case study carried out in the city of Porto Alegre, in the state of Rio Grande do Sul, Brazil, in the stages of specification and calibration of the models, with two distinct datasets.
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In some operational circumstances a fast evaluation of landfill leachate anaerobic treatability is necessary, and neither Biochemical Methane Potential nor BOD/COD ratio are fast enough. Looking for a fast indicator, this work evaluated the anaerobic treatability of landfill leachate from São Carlos-SP (Brazil) in a pilot scale Anaerobic Sequence Batch Biofilm Reactor (AnSBBR). The experiment was conducted at ambient temperature in the landfill area. After the acclimation, at a second stage of operation, the AnSBBR presented efficiency above 70%, in terms of COD removal, utilizing landfill leachate without water dilution, with an inlet COD of about 11,000 mg.L-1, a TVA/COD ratio of approximately 0.6 and reaction time equal to 7 days. To evaluate the landfill leachate biodegradability variation over time, temporal profiles of concentration were performed in the AnSBBR. The landfill leachate anaerobic biodegradability was verified to have a direct and strong relationship to the TVA/COD ratio. For a TVA/CODTotal ratio lower than 0.20, the biodegradability was considered low, for ratios between 0.20 and 0.40 it was considered medium, and above 0.40 it was considered high.
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We propose an efficient scheduling scheme that optimizes advance-reserved lightpath services in reconfigurable WDM networks. A re-optimization approach is devised to reallocate network resources for dynamic service demands while keeping determined schedule unchanged.
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This paper addressed the problem of water-demand forecasting for real-time operation of water supply systems. The present study was conducted to identify the best fit model using hourly consumption data from the water supply system of Araraquara, Sa approximate to o Paulo, Brazil. Artificial neural networks (ANNs) were used in view of their enhanced capability to match or even improve on the regression model forecasts. The ANNs used were the multilayer perceptron with the back-propagation algorithm (MLP-BP), the dynamic neural network (DAN2), and two hybrid ANNs. The hybrid models used the error produced by the Fourier series forecasting as input to the MLP-BP and DAN2, called ANN-H and DAN2-H, respectively. The tested inputs for the neural network were selected literature and correlation analysis. The results from the hybrid models were promising, DAN2 performing better than the tested MLP-BP models. DAN2-H, identified as the best model, produced a mean absolute error (MAE) of 3.3 L/s and 2.8 L/s for training and test set, respectively, for the prediction of the next hour, which represented about 12% of the average consumption. The best forecasting model for the next 24 hours was again DAN2-H, which outperformed other compared models, and produced a MAE of 3.1 L/s and 3.0 L/s for training and test set respectively, which represented about 12% of average consumption. DOI: 10.1061/(ASCE)WR.1943-5452.0000177. (C) 2012 American Society of Civil Engineers.