840 resultados para hybrid prediction method
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The resistive-type superconducting fault current limiters (RSFCL) prototypes using YBCO-coated conductors have shown current limitation for medium voltage class applications for acting time up to 80 ms. By connecting an air-core reactor in parallel with the RSFCL, thus making an hybrid current limiter, one can extend the acting time for up to 1 s. In this work, we report the performance of a hybrid current limiter subjected to an AC peak fault current of 2 kA during 1 s for which within the first 80 ms the SFCL limits the current concurrently with the air-core reactor, and for the remaining 920 ms, only the air-core reactor limits the current. In order to evaluate the actual conditions for subsequent reconnection of RSFCL to the power grid, the hybrid fault current limiter was tested varying the time interval for recovery from 900 ms and 1.2 s, followed again by the concurrent operation of the hybrid limiter during 1 s (SFCL during 80 ms). From this evaluation test, the recovery time can be measured and compared using the voltage peak generated in superconducting module from the first and second fault test. The recovery time was also determined through the pulsed current method (PCM) on short-length sample test. The results showed that the fault current was limited from 1.9 kA down to 514 A after 1 cycle of 60 Hz frequency, with recovery time lower than 1.2 s for two subsequent fault current tests.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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At present the prediction and characterization of the emission output of a diffusive random laser remains a challenge, despite the variety of investigated materials and theoretical interpretations given up to now. Here, a new mode selection method, based on spatial filtering and ultrafast detection, which allows to separate individual lasing modes and follow their temporal evolution is presented. In particular, the work explores the random laser behavior of a ground powder of an organic-inorganic hybrid compound based on Rhodamine B incorporated into a di-ureasil host. The experimental approach gives direct access to the mode structure and dynamics, shows clear modal relaxation oscillations, and illustrates the lasing modes stochastic behavior of this diffusive scattering system. The effect of the excitation energy on its modal density is also investigated. Finally, imaging measurements reveal the dominant role of diffusion over amplification processes in this kind of unconventional lasers. (C) 2015 Optical Society of America
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With the currently strict environmental law in present days, researchers and industries are seeking to reduce the amount of cutting fluid used in machining. Minimum quantity lubrication is a potential alternative to reduce environmental impacts and overall process costs. This technique can substantially reduce cutting fluids in grinding, as well as provide better performance in relation to conventional cutting fluid application (abundant fluid flow). The present work aims to test the viability of minimum quantity lubrication (with and without water) in grinding of advanced ceramics, when compared to conventional method (abundant fluid flow). Measured output variables were grinding power, surface roughness, roundness errors and wheel wear, as well as scanning electron micrographs. The results show that minimum quantity lubrication with water (1:1) was superior to conventional lubrication-cooling in terms of surface quality, also reducing wheel wear, when compared to the other methods tested.
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Rapid in vitro methods for measuring digestibility may be useful in analysing aqua feeds if the extent and limits of their application are clearly defined. The pH-stat protein digestibility routine with shrimp hepatopancreas enzymes was previously related to apparent protein digestibility with juvenile Litopenaeus vannamei fed diets containing different protein ingredients. The potential of the method to predict culture performance of shrimp fed six commercial feeds (T3, T4, T5, T6, T7 and T8) with 350 g kg(-1) declared crude-protein content was assessed. The consistency of results obtained using hepatopancreas enzyme extracts from either pond or clear water-raised shrimp was further verified in terms of reproducibility and possible diet history effects upon in vitro outputs. Shrimps were previously acclimated and then maintained over 56 days (initial mean weight 3.28 g) on each diet in 500-L tanks at 114 ind m(-2), clear water closed system with continuous renewal and mechanical filtering (50 mu m), with four replicates per treatment. Feeds were offered four times daily (six days a week) delivered in trays at feeding rates ranging from 4.0% to 7.0% of stocked shrimp biomass. Feed was accessible to shrimp 4 h daily for 1-h feeding period after which uneaten feed was recovered. Growth and survival were determined every 14 days from a sample of 16 individuals per tank. Water quality was monitored daily (pH, temperature and salinity) and managed by water back flushing filter cleaning every 7-10 days. Feeds were analysed for crude protein, gross energy, amino acids and pepsin digestibility. In vitro pH-stat degree of protein hydrolysis (DH%) was determined for each feed using hepatopancreas enzyme extracts from experimental (clear water) or pond-raised shrimp. Feeds resulted in significant differences in shrimp performance (P < 0.05) as seen by the differences in growth rates (0.56-0.98 g week(-1)), final weight and feed conversion ratio (FCR). Shrimp performance and in vitro DH% with pond-raised shrimp enzymes showed significant correlation (P < 0.05) for yield (R-2 = 0.72), growth rates (R-2 = 0.72-0.80) and FCR (R-2 = -0.67). Other feed attributes (protein : energy ratio, amino acids, true protein, non-protein nitrogen contents and in vitro pepsin digestibility) showed none or limited correlation with shrimp culture performance. Additional correlations were found between growth rates and methionine (R-2 = 0.73), FCR and histidine (R-2 = -0.60), and DH% and methionine or methionine+cystine feed contents (R-2 = 0.67-0.92). pH-stat assays with shrimp enzymes generated reproducible DH% results with either pond (CV <= 6.5%) or clear water (CV <= 8.5%) hepatopancreas enzyme sources. Moreover, correlations between shrimp growth rates and feed DH% were significant regardless of the enzyme origin (pond or clear water-raised shrimp) and showed consistent R-2 values. Results suggest the feasibility of using standardized hepatopancreas enzyme extracts for in vitro protein digestibility.
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In this paper we propose a hybrid hazard regression model with threshold stress which includes the proportional hazards and the accelerated failure time models as particular cases. To express the behavior of lifetimes the generalized-gamma distribution is assumed and an inverse power law model with a threshold stress is considered. For parameter estimation we develop a sampling-based posterior inference procedure based on Markov Chain Monte Carlo techniques. We assume proper but vague priors for the parameters of interest. A simulation study investigates the frequentist properties of the proposed estimators obtained under the assumption of vague priors. Further, some discussions on model selection criteria are given. The methodology is illustrated on simulated and real lifetime data set.
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Vanadium oxide nanotubes (NTs) were synthesized by the sol-gel method followed by a long-term hydrothermal treatment. The obtained nanotubes have a multiwall structure, and 70% of vanadium ions are in the V4+ state. This percentage was derived by evaluating three components of the magnetic susceptibility; namely, (i) the paramagnetic Curie-Weiss behavior, (ii) antiferromagnetic dimers, and (iii) magnetic trimers. The as-made NTs were annealed in situ in the cavity of the electron paramagnetic resonance (EPR) spectrometer. The line shape changes irreversibly at 390 K, and the EPR susceptibility presents an anomaly at 425 K. These changes are interpreted as a partial oxidation of the V4+ ions and consequently a decrease in the concentration of the magnetic species. The quantification of the V4+ ions of the annealed NTs reveals a diminution to 39% of V4+, a weakening of the Curie-Weiss and antiferromagnetic dimers contributions, and the suppression of magnetic trimers. Vibrational studies confirm the decrease of V4+ amount. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4749417]
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The physical properties of small rhodium clusters, Rh-n, have been in debate due to the shortcomings of density functional theory (DFT). To help in the solution of those problems, we obtained a set of putative lowest energy structures for small Rh-n (n = 2-15) clusters employing hybrid-DFT and the generalized gradient approximation (GGA). For n = 2-6, both hybrid and GGA functionals yield similar ground-state structures (compact), however, hybrid favors compact structures for n = 7-15, while GGA favors open structures based on simple cubic motifs. Thus, experimental results are crucial to indicate the correct ground-state structures, however, we found that a unique set of structures (compact or open) is unable to explain all available experimental data. For example, the GGA structures (open) yield total magnetic moments in excellent agreement with experimental data, while hybrid structures (compact) have larger magnetic moments compared with experiments due to the increased localization of the 4d states. Thus, we would conclude that GGA provides a better description of the Rh-n clusters, however, a recent experimental-theoretical study [ Harding et al., J. Chem. Phys. 133, 214304 (2010)] found that only compact structures are able to explain experimental vibrational data, while open structures cannot. Therefore, it indicates that the study of Rh-n clusters is a challenging problem and further experimental studies are required to help in the solution of this conundrum, as well as a better description of the exchange and correlation effects on the Rh n clusters using theoretical methods such as the quantum Monte Carlo method.
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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.
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In protein databases there is a substantial number of proteins structurally determined but without function annotation. Understanding the relationship between function and structure can be useful to predict function on a large scale. We have analyzed the similarities in global physicochemical parameters for a set of enzymes which were classified according to the four Enzyme Commission (EC) hierarchical levels. Using relevance theory we introduced a distance between proteins in the space of physicochemical characteristics. This was done by minimizing a cost function of the metric tensor built to reflect the EC classification system. Using an unsupervised clustering method on a set of 1025 enzymes, we obtained no relevant clustering formation compatible with EC classification. The distance distributions between enzymes from the same EC group and from different EC groups were compared by histograms. Such analysis was also performed using sequence alignment similarity as a distance. Our results suggest that global structure parameters are not sufficient to segregate enzymes according to EC hierarchy. This indicates that features essential for function are rather local than global. Consequently, methods for predicting function based on global attributes should not obtain high accuracy in main EC classes prediction without relying on similarities between enzymes from training and validation datasets. Furthermore, these results are consistent with a substantial number of studies suggesting that function evolves fundamentally by recruitment, i.e., a same protein motif or fold can be used to perform different enzymatic functions and a few specific amino acids (AAs) are actually responsible for enzyme activity. These essential amino acids should belong to active sites and an effective method for predicting function should be able to recognize them. (C) 2012 Elsevier Ltd. All rights reserved.
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Boiling points (T-B) of acyclic alkynes are predicted from their boiling point numbers (Y-BP) with the relationship T-B(K) = -16.802Y(BP)(2/3) + 337.377Y(BP)(1/3) - 437.883. In turn, Y-BP values are calculated from structure using the equation Y-BP = 1.726 + A(i) + 2.779C + 1.716M(3) + 1.564M + 4.204E(3) + 3.905E + 5.007P - 0.329D + 0.241G + 0.479V + 0.967T + 0.574S. Here A(i) depends on the substitution pattern of the alkyne and the remainder of the equation is the same as that reported earlier for alkanes. For a data set consisting of 76 acyclic alkynes, the correlation of predicted and literature T-B values had an average absolute deviation of 1.46 K, and the R-2 of the correlation was 0.999. In addition, the calculated Y-BP values can be used to predict the flash points of alkynes.
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Objective To determine variables that predict the rate of decline in fetal hemoglobin levels in alloimmune disease. Method Retrospective review of singleton pregnancies that underwent first and second intrauterine transfusions for treatment of fetal anemia because of maternal Rh alloimmunization in a tertiary referral center. Results Forty-one first intrauterine transfusions were performed at 26.1?weeks (standard deviation, SD, 4.6), mean volume of blood transfused was 44.4?mL (SD 23.5) and estimated feto-placental volume expansion was 51.3% (SD 14.5%). Between first and second transfusion, hemoglobin levels reduced on average 0.40?g/dl/day (SD 0.25). Stepwise multiple regression analysis demonstrated that this rate significantly correlated with hemoglobin levels after the first transfusion, the interval between both procedures, and middle cerebral artery systolic velocity before the second transfusion. Conclusion The rate of decline in fetal hemoglobin levels between first and second transfusions in alloimmune disease can be predicted by a combination of hemoglobin levels after the first transfusion, interval between both procedures, and middle cerebral artery systolic velocity before the second transfusion. (C) 2012 John Wiley & Sons, Ltd.
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This paper discusses the power allocation with fixed rate constraint problem in multi-carrier code division multiple access (MC-CDMA) networks, that has been solved through game theoretic perspective by the use of an iterative water-filling algorithm (IWFA). The problem is analyzed under various interference density configurations, and its reliability is studied in terms of solution existence and uniqueness. Moreover, numerical results reveal the approach shortcoming, thus a new method combining swarm intelligence and IWFA is proposed to make practicable the use of game theoretic approaches in realistic MC-CDMA systems scenarios. The contribution of this paper is twofold: (i) provide a complete analysis for the existence and uniqueness of the game solution, from simple to more realist and complex interference scenarios; (ii) propose a hybrid power allocation optimization method combining swarm intelligence, game theory and IWFA. To corroborate the effectiveness of the proposed method, an outage probability analysis in realistic interference scenarios, and a complexity comparison with the classical IWFA are presented. (C) 2011 Elsevier B.V. All rights reserved.
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Triple-gate devices are considered a promising solution for sub-20 nm era. Strain engineering has also been recognized as an alternative due to the increase in the carriers mobility it propitiates. The simulation of strained devices has the major drawback of the stress non-uniformity, which cannot be easily considered in a device TCAD simulation without the coupled process simulation that is time consuming and cumbersome task. However, it is mandatory to have accurate device simulation, with good correlation with experimental results of strained devices, allowing for in-depth physical insight as well as prediction on the stress impact on the device electrical characteristics. This work proposes the use of an analytic function, based on the literature, to describe accurately the strain dependence on both channel length and fin width in order to simulate adequately strained triple-gate devices. The maximum transconductance and the threshold voltage are used as the key parameters to compare simulated and experimental data. The results show the agreement of the proposed analytic function with the experimental results. Also, an analysis on the threshold voltage variation is carried out, showing that the stress affects the dependence of the threshold voltage on the temperature. (C) 2011 Elsevier Ltd. All rights reserved.