947 resultados para Hierarchical Bayesian Methods


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The aim of the present study was to compare and correlate training impulse (TRIMP) estimates proposed by Banister (TRIMP(Banister)), Stagno (TRIMP(Stagno)) and Manzi (TRIMP(Manzi)). The subjects were submitted to an incremental test on cycle ergometer with heart rate and blood lactate concentration measurements. In the second occasion, they performed 30 min. of exercise at the intensity corresponding to maximal lactate steady state, and TRIMP(Banister), TRIMP(Stagno) and TRIMP(Manzi) were calculated. The mean values of TRIMP(Banister) (56.5 +/- 8.2 u.a.) and TRIMP(Stagno) (51.2 +/- 12.4 u.a.) were not different (P > 0.05) and were highly correlated (r = 0.90). Besides this, they presented a good agreement level, which means low bias and relatively narrow limits of agreement. On the other hand, despite highly correlated (r = 0.93), TRIMP(Stagno) and TRIMP(Manzi) (73.4 +/- 17.6 u.a.) were different (P < 0.05), with low agreement level. The TRIMP(Banister) e TRIMP(Manzi) estimates were not different (P = 0.06) and were highly correlated (r = 0.82), but showed low agreement level. Thus, we concluded that the investigated TRIMP methods are not equivalent. In practical terms, it seems prudent monitor the training process assuming only one of the estimates.

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Molybdenum and tungsten bimetallic oxides were synthetized according to the following methods: Pechini, coprecipitation and solid state reaction (SSR). After the characterization, those solids were carbureted at programmed temperature. The carburation process was monitored by checking the consumption of carburant hydrocarbon and CO produced. The monitoring process permits to avoid or to diminish the formation of pirolytic carbon.

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Understanding the product`s `end-of-life` is important to reduce the environmental impact of the products` final disposal. When the initial stages of product development consider end-of-life aspects, which can be established by ecodesign (a proactive approach of environmental management that aims to reduce the total environmental impact of products), it becomes easier to close the loop of materials. The `end-of-life` ecodesign methods generally include more than one `end-of-life` strategy. Since product complexity varies substantially, some components, systems or sub-systems are easier to be recycled, reused or remanufactured than others. Remanufacture is an effective way to maintain products in a closed-loop, reducing both environmental impacts and costs of the manufacturing processes. This paper presents some ecodesign methods focused on the integration of different `end-of-life` strategies, with special attention to remanufacturing, given its increasing importance in the international scenario to reduce the life cycle impacts of products. (C) 2009 Elsevier Ltd. All rights reserved.

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We assess the performance of three unconditionally stable finite-difference time-domain (FDTD) methods for the modeling of doubly dispersive metamaterials: 1) locally one-dimensional FDTD; 2) locally one-dimensional FDTD with Strang splitting; and (3) alternating direction implicit FDTD. We use both double-negative media and zero-index media as benchmarks.

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This paper describes the modeling of a weed infestation risk inference system that implements a collaborative inference scheme based on rules extracted from two Bayesian network classifiers. The first Bayesian classifier infers a categorical variable value for the weed-crop competitiveness using as input categorical variables for the total density of weeds and corresponding proportions of narrow and broad-leaved weeds. The inferred categorical variable values for the weed-crop competitiveness along with three other categorical variables extracted from estimated maps for the weed seed production and weed coverage are then used as input for a second Bayesian network classifier to infer categorical variables values for the risk of infestation. Weed biomass and yield loss data samples are used to learn the probability relationship among the nodes of the first and second Bayesian classifiers in a supervised fashion, respectively. For comparison purposes, two types of Bayesian network structures are considered, namely an expert-based Bayesian classifier and a naive Bayes classifier. The inference system focused on the knowledge interpretation by translating a Bayesian classifier into a set of classification rules. The results obtained for the risk inference in a corn-crop field are presented and discussed. (C) 2009 Elsevier Ltd. All rights reserved.

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The airflow velocities and pressures are calculated from a three-dimensional model of the human larynx by using the finite element method. The laryngeal airflow is assumed to be incompressible, isothermal, steady, and created by fixed pressure drops. The influence of different laryngeal profiles (convergent, parallel, and divergent), glottal area, and dimensions of false vocal folds in the airflow are investigated. The results indicate that vertical and horizontal phase differences in the laryngeal tissue movements are influenced by the nonlinear pressure distribution across the glottal channel, and the glottal entrance shape influences the air pressure distribution inside the glottis. Additionally, the false vocal folds increase the glottal duct pressure drop by creating a new constricted channel in the larynx, and alter the airflow vortexes formed after the true vocal folds. (C) 2007 Elsevier Ltd. All rights reserved.

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On-line leak detection is a main concern for the safe operation of pipelines. Acoustic and mass balance are the most important and extensively applied technologies in field problems. The objective of this work is to compare these leak detection methods with respect to a given reference situation, i.e., the same pipeline and monitoring signals acquired at the inlet and outlet ends. Experimental tests were conducted in a 749 m long laboratory pipeline transporting water as the working fluid. The instrumentation included pressure transducers and electromagnetic flowmeters. Leaks were simulated by opening solenoid valves placed at known positions and previously calibrated to produce known average leak flow rates. Results have clearly shown the limitations and advantages of each method. It is also quite clear that acoustics and mass balance technologies are, in fact, complementary. In general, an acoustic leak detection system sends out an alarm more rapidly and locates the leak more precisely, provided that the rupture of the pipeline occurs abruptly enough. On the other hand, a mass balance leak detection method is capable of quantifying the leak flow rate very accurately and of detecting progressive leaks.

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This paper analyses the presence of financial constraint in the investment decisions of 367 Brazilian firms from 1997 to 2004, using a Bayesian econometric model with group-varying parameters. The motivation for this paper is the use of clustering techniques to group firms in a totally endogenous form. In order to classify the firms we used a hybrid clustering method, that is, hierarchical and non-hierarchical clustering techniques jointly. To estimate the parameters a Bayesian approach was considered. Prior distributions were assumed for the parameters, classifying the model in random or fixed effects. Ordinate predictive density criterion was used to select the model providing a better prediction. We tested thirty models and the better prediction considers the presence of 2 groups in the sample, assuming the fixed effect model with a Student t distribution with 20 degrees of freedom for the error. The results indicate robustness in the identification of financial constraint when the firms are classified by the clustering techniques. (C) 2010 Elsevier B.V. All rights reserved.

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Neodymium doped and undoped aluminum oxide samples were obtained using two different techniques: Pechini and sol-gel. Fine grained powders were produced using both procedures, which were analyzed using Scanning Electron Microscopy (SEM) and Thermo-Stimulated Luminescence (TSL). Results showed that neodymium ions incorporation is responsible for the creation of two new TSL peaks (125 and 265 degrees C) and, also, for the enhancement of the intrinsic TSL peak at 190 degrees C. An explanation was proposed for these observations. SEM gave the dimensions of the clusters produced by each method, showing that those obtained by Pechini are smaller than the ones produced by sol-gel; it can also explain the higher emission supplied by the first one. (C) 2010 Elsevier B.V. All rights reserved.

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This paper deals with the use of simplified methods to predict methane generation in tropical landfills. Methane recovery data obtained on site as part of a research program being carried Out at the Metropolitan Landfill, Salvador, Brazil, is analyzed and used to obtain field methane generation over time. Laboratory data from MSW samples of different ages are presented and discussed: and simplified procedures to estimate the methane generation potential, L(o), and the constant related to the biodegradation rate, k are applied. The first order decay method is used to fit field and laboratory results. It is demonstrated that despite the assumptions and the simplicity of the adopted laboratory procedures, the values L(o) and k obtained are very close to those measured in the field, thus making this kind of analysis very attractive for first approach purposes. (C) 2008 Elsevier Ltd. All rights reserved.

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An updated flow pattern map was developed for CO2 on the basis of the previous Cheng-Ribatski-Wojtan-Thome CO2 flow pattern map [1,2] to extend the flow pattern map to a wider range of conditions. A new annular flow to dryout transition (A-D) and a new dryout to mist flow transition (D-M) were proposed here. In addition, a bubbly flow region which generally occurs at high mass velocities and low vapor qualities was added to the updated flow pattern map. The updated flow pattern map is applicable to a much wider range of conditions: tube diameters from 0.6 to 10 mm, mass velocities from 50 to 1500 kg/m(2) s, heat fluxes from 1.8 to 46 kW/m(2) and saturation temperatures from -28 to +25 degrees C (reduced pressures from 0.21 to 0.87). The updated flow pattern map was compared to independent experimental data of flow patterns for CO2 in the literature and it predicts the flow patterns well. Then, a database of CO2 two-phase flow pressure drop results from the literature was set up and the database was compared to the leading empirical pressure drop models: the correlations by Chisholm [3], Friedel [4], Gronnerud [5] and Muller-Steinhagen and Heck [6], a modified Chisholm correlation by Yoon et al. [7] and the flow pattern based model of Moreno Quiben and Thome [8-10]. None of these models was able to predict the CO2 pressure drop data well. Therefore, a new flow pattern based phenomenological model of two-phase flow frictional pressure drop for CO2 was developed by modifying the model of Moreno Quiben and Thome using the updated flow pattern map in this study and it predicts the CO2 pressure drop database quite well overall. (C) 2007 Elsevier Ltd. All rights reserved.

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Corresponding to the updated flow pattern map presented in Part I of this study, an updated general flow pattern based flow boiling heat transfer model was developed for CO2 using the Cheng-Ribatski-Wojtan-Thome [L. Cheng, G. Ribatski, L. Wojtan, J.R. Thome, New flow boiling heat transfer model and flow pattern map for carbon dioxide evaporating inside horizontal tubes, Int. J. Heat Mass Transfer 49 (2006) 4082-4094; L. Cheng, G. Ribatski, L. Wojtan, J.R. Thome, Erratum to: ""New flow boiling heat transfer model and flow pattern map for carbon dioxide evaporating inside tubes"" [Heat Mass Transfer 49 (21-22) (2006) 4082-4094], Int. J. Heat Mass Transfer 50 (2007) 391] flow boiling heat transfer model as the starting basis. The flow boiling heat transfer correlation in the dryout region was updated. In addition, a new mist flow heat transfer correlation for CO2 was developed based on the CO2 data and a heat transfer method for bubbly flow was proposed for completeness sake. The updated general flow boiling heat transfer model for CO2 covers all flow regimes and is applicable to a wider range of conditions for horizontal tubes: tube diameters from 0.6 to 10 mm, mass velocities from 50 to 1500 kg/m(2) s, heat fluxes from 1.8 to 46 kW/m(2) and saturation temperatures from -28 to 25 degrees C (reduced pressures from 0.21 to 0.87). The updated general flow boiling heat transfer model was compared to a new experimental database which contains 1124 data points (790 more than that in the previous model [Cheng et al., 2006, 2007]) in this study. Good agreement between the predicted and experimental data was found in general with 71.4% of the entire database and 83.2% of the database without the dryout and mist flow data predicted within +/-30%. However, the predictions for the dryout and mist flow regions were less satisfactory due to the limited number of data points, the higher inaccuracy in such data, scatter in some data sets ranging up to 40%, significant discrepancies from one experimental study to another and the difficulties associated with predicting the inception and completion of dryout around the perimeter of the horizontal tubes. (C) 2007 Elsevier Ltd. All rights reserved.

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This work shows the application of the analytic hierarchy process (AHP) in the full cost accounting (FCA) within the integrated resource planning (IRP) process. For this purpose, a pioneer case was developed and different energy solutions of supply and demand for a metropolitan airport (Congonhas) were considered [Moreira, E.M., 2005. Modelamento energetico para o desenvolvimento limpo de aeroporto metropolitano baseado na filosofia do PIR-O caso da metropole de Sao Paulo. Dissertacao de mestrado, GEPEA/USP]. These solutions were compared and analyzed utilizing the software solution ""Decision Lens"" that implements the AHP. The final part of this work has a classification of resources that can be considered to be the initial target as energy resources, thus facilitating the restraints of the IRP of the airport and setting parameters aiming at sustainable development. (C) 2007 Elsevier Ltd. All rights reserved.

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One of the most important recent improvements in cardiology is the use of ventricular assist devices (VADs) to help patients with severe heart diseases, especially when they are indicated to heart transplantation. The Institute Dante Pazzanese of Cardiology has been developing an implantable centrifugal blood pump that will be able to help a sick human heart to keep blood flow and pressure at physiological levels. This device will be used as a totally or partially implantable VAD. Therefore, an improvement on device performance is important for the betterment of the level of interaction with patient`s behavior or conditions. But some failures may occur if the device`s pumping control does not follow the changes in patient`s behavior or conditions. The VAD control system must consider tolerance to faults and have a dynamic adaptation according to patient`s cardiovascular system changes, and also must attend to changes in patient conditions, behavior, or comportments. This work proposes an application of the mechatronic approach to this class of devices based on advanced techniques for control, instrumentation, and automation to define a method for developing a hierarchical supervisory control system that is able to perform VAD control dynamically, automatically, and securely. For this methodology, we used concepts based on Bayesian network for patients` diagnoses, Petri nets to generate a VAD control algorithm, and Safety Instrumented Systems to ensure VAD system security. Applying these concepts, a VAD control system is being built for method effectiveness confirmation.

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Safety Instrumented Systems (SIS) are designed to prevent and / or mitigate accidents, avoiding undesirable high potential risk scenarios, assuring protection of people`s health, protecting the environment and saving costs of industrial equipment. The design of these systems require formal methods for ensuring the safety requirements, but according material published in this area, has not identified a consolidated procedure to match the task. This sense, this article introduces a formal method for diagnosis and treatment of critical faults based on Bayesian network (BN) and Petri net (PN). This approach considers diagnosis and treatment for each safety instrumented function (SIF) including hazard and operability (HAZOP) study in the equipment or system under control. It also uses BN and Behavioral Petri net (BPN) for diagnoses and decision-making and the PN for the synthesis, modeling and control to be implemented by Safety Programmable Logic Controller (PLC). An application example considering the diagnosis and treatment of critical faults is presented and illustrates the methodology proposed.