970 resultados para COMPARATIVE CALIBRATION MODELS


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This work deals with the determination of crack openings in 2D reinforced concrete structures using the Finite Element Method with a smeared rotating crack model or an embedded crack model In the smeared crack model, the strong discontinuity associated with the crack is spread throughout the finite element As is well known, the continuity of the displacement field assumed for these models is incompatible with the actual discontinuity However, this type of model has been used extensively due to the relative computational simplicity it provides by treating cracks in a continuum framework, as well as the reportedly good predictions of reinforced concrete members` structural behavior On the other hand, by enriching the displacement field within each finite element crossed by the crack path, the embedded crack model is able to describe the effects of actual discontinuities (cracks) This paper presents a comparative study of the abilities of these 2D models in predicting the mechanical behavior of reinforced concrete structures Structural responses are compared with experimental results from the literature, including crack patterns, crack openings and rebar stresses predicted by both models

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Recently, the development of industrial processes brought on the outbreak of technologically complex systems. This development generated the necessity of research relative to the mathematical techniques that have the capacity to deal with project complexities and validation. Fuzzy models have been receiving particular attention in the area of nonlinear systems identification and analysis due to it is capacity to approximate nonlinear behavior and deal with uncertainty. A fuzzy rule-based model suitable for the approximation of many systems and functions is the Takagi-Sugeno (TS) fuzzy model. IS fuzzy models are nonlinear systems described by a set of if then rules which gives local linear representations of an underlying system. Such models can approximate a wide class of nonlinear systems. In this paper a performance analysis of a system based on IS fuzzy inference system for the calibration of electronic compass devices is considered. The contribution of the evaluated IS fuzzy inference system is to reduce the error obtained in data acquisition from a digital electronic compass. For the reliable operation of the TS fuzzy inference system, adequate error measurements must be taken. The error noise must be filtered before the application of the IS fuzzy inference system. The proposed method demonstrated an effectiveness of 57% at reducing the total error based on considered tests. (C) 2011 Elsevier Ltd. All rights reserved.

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In the present study a fast, sensitive and robust validated method to quantify chlorpheniramine in human plasma using brompheniramine as internal standard (IS) is described. The analyte and the IS were extracted from plasma by LLE (diethyl ether-dichloromethane, 80:20, v/v) and analyzed by HPLC-ESI-MS/MS. Chromatographic separation was performed using a gradient of methanol from 35 to 90% with 2.5 mm NH(4)OH on a Gemini Phenomenex C(8) 5 mu m column (50 x 4.6 mm i.d.) in 5.0 min/run. The method fitted to a linear calibration curve (0.05-10 ng/mL, R > 0.9991). The precision (%CV) and accuracy ranged, respectively: intra-batch from 1.5 to 6.8% and 99.1 to 106.6%, and inter-batch from 2.4 to 9.0%, and 99.9 to 103.1%. The validated bioanalytical procedure was used to assess the comparative bioavailability in healthy volunteers of two dexchlorpheniramine 2.0 mg tablet formulations (test dexchlorpheniramine, Eurofarma, and reference Celestamine (R), Schering-Plough). The study was conducted using an open, randomized, two-period crossover design with a 2 week washout interval. Since the 90% confidence interval for C(max) and AUC ratios were all within the 80-125% interval proposed by ANVISA and FDA, it was concluded that test and reference formulations are bioequivalent concerning the rate and the extent of absorption. Copyright (C) 2009 John Wiley & Sons, Ltd.

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Polytomous Item Response Theory Models provides a unified, comprehensive introduction to the range of polytomous models available within item response theory (IRT). It begins by outlining the primary structural distinction between the two major types of polytomous IRT models. This focuses on the two types of response probability that are unique to polytomous models and their associated response functions, which are modeled differently by the different types of IRT model. It describes, both conceptually and mathematically, the major specific polytomous models, including the Nominal Response Model, the Partial Credit Model, the Rating Scale model, and the Graded Response Model. Important variations, such as the Generalized Partial Credit Model are also described as are less common variations, such as the Rating Scale version of the Graded Response Model. Relationships among the models are also investigated and the operation of measurement information is described for each major model. Practical examples of major models using real data are provided, as is a chapter on choosing an appropriate model. Figures are used throughout to illustrate important elements as they are described.

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This paper discusses a multi-layer feedforward (MLF) neural network incident detection model that was developed and evaluated using field data. In contrast to published neural network incident detection models which relied on simulated or limited field data for model development and testing, the model described in this paper was trained and tested on a real-world data set of 100 incidents. The model uses speed, flow and occupancy data measured at dual stations, averaged across all lanes and only from time interval t. The off-line performance of the model is reported under both incident and non-incident conditions. The incident detection performance of the model is reported based on a validation-test data set of 40 incidents that were independent of the 60 incidents used for training. The false alarm rates of the model are evaluated based on non-incident data that were collected from a freeway section which was video-taped for a period of 33 days. A comparative evaluation between the neural network model and the incident detection model in operation on Melbourne's freeways is also presented. The results of the comparative performance evaluation clearly demonstrate the substantial improvement in incident detection performance obtained by the neural network model. The paper also presents additional results that demonstrate how improvements in model performance can be achieved using variable decision thresholds. Finally, the model's fault-tolerance under conditions of corrupt or missing data is investigated and the impact of loop detector failure/malfunction on the performance of the trained model is evaluated and discussed. The results presented in this paper provide a comprehensive evaluation of the developed model and confirm that neural network models can provide fast and reliable incident detection on freeways. (C) 1997 Elsevier Science Ltd. All rights reserved.

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The use of computational fluid dynamics simulations for calibrating a flush air data system is described, In particular, the flush air data system of the HYFLEX hypersonic vehicle is used as a case study. The HYFLEX air data system consists of nine pressure ports located flush with the vehicle nose surface, connected to onboard pressure transducers, After appropriate processing, surface pressure measurements can he converted into useful air data parameters. The processing algorithm requires an accurate pressure model, which relates air data parameters to the measured pressures. In the past, such pressure models have been calibrated using combinations of flight data, ground-based experimental results, and numerical simulation. We perform a calibration of the HYFLEX flush air data system using computational fluid dynamics simulations exclusively, The simulations are used to build an empirical pressure model that accurately describes the HYFLEX nose pressure distribution ol cr a range of flight conditions. We believe that computational fluid dynamics provides a quick and inexpensive way to calibrate the air data system and is applicable to a broad range of flight conditions, When tested with HYFLEX flight data, the calibrated system is found to work well. It predicts vehicle angle of attack and angle of sideslip to accuracy levels that generally satisfy flight control requirements. Dynamic pressure is predicted to within the resolution of the onboard inertial measurement unit. We find that wind-tunnel experiments and flight data are not necessary to accurately calibrate the HYFLEX flush air data system for hypersonic flight.

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Background: A variety of methods for prediction of peptide binding to major histocompatibility complex (MHC) have been proposed. These methods are based on binding motifs, binding matrices, hidden Markov models (HMM), or artificial neural networks (ANN). There has been little prior work on the comparative analysis of these methods. Materials and Methods: We performed a comparison of the performance of six methods applied to the prediction of two human MHC class I molecules, including binding matrices and motifs, ANNs, and HMMs. Results: The selection of the optimal prediction method depends on the amount of available data (the number of peptides of known binding affinity to the MHC molecule of interest), the biases in the data set and the intended purpose of the prediction (screening of a single protein versus mass screening). When little or no peptide data are available, binding motifs are the most useful alternative to random guessing or use of a complete overlapping set of peptides for selection of candidate binders. As the number of known peptide binders increases, binding matrices and HMM become more useful predictors. ANN and HMM are the predictive methods of choice for MHC alleles with more than 100 known binding peptides. Conclusion: The ability of bioinformatic methods to reliably predict MHC binding peptides, and thereby potential T-cell epitopes, has major implications for clinical immunology, particularly in the area of vaccine design.

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The applicability of image calibration to like-values in mapping water quality parameters from multitemporal images is explored, Six sets of water samples were collected at satellite overpasses over Moreton Bay, Brisbane, Australia. Analysis of these samples reveals that waters in this shallow bay are mostly TSS-dominated, even though they are occasionally dominated by chlorophyll as well. Three of the images were calibrated to a reference image based on invariant targets. Predictive models constructed from the reference image were applied to estimating total suspended sediment (TSS) and Secchi depth from another image at a discrepancy of around 35 percent. Application of the predictive model for TSS concentration to another image acquired at a time of different water types resulted in a discrepancy of 152 percent. Therefore, image calibration to like-values could be used to reliably map certain water quality parameters from multitemporal TM images so long as the water type under study remains unchanged. This method is limited in that the mapped results could be rather inaccurate if the water type under study has changed considerably. Thus, the approach needs to be refined in shallow water from multitemporal satellite imagery.

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The aims of this study were to characterize the spatial distribution of neurodegeneration after status epilepticus (SE) induced by either systemic (S) or intrahippocampal (H) injection of pilocarpine (PILO), two models of temporal lobe epilepsy (TLE), using FluoroJade (FJ) histochemistry, and to evaluate the kinetics of FJ staining in the H-PILO model. Therefore, we measured the severity of behavioral seizures during both types of SE and also evaluated the FJ staining pattern at 12, 24, and 168 h (7 days) after the H-PILO insult. We found that the amount of FJ-positive (FJ+) area was greater in SE induced by S-PILO as compared to SE induced by H-PILO. After SE induced by H-PILO, we found more FJ+ cells in the hilus of the dentate gyrus (DG) at 12 h, in CA3 at 24 h, and in CA1 at 168 h. We found also no correlation between seizure severity and the number of FJ+ cells in the hippocampus. Co-localization studies of FJ+ cells with either neuronal-specific nuclear protein (NeuN) or glial fibrillary acidic protein (GFAP) labeling 24 h after H-PILO demonstrated spatially selective neurodegeneration. Double labeling with FJ and parvalbumin (PV) showed both FJ+/PV+ and FJ+/PV- cells in hippocampus and entorhinal cortex, among other areas. The current data indicate that FJ+ areas are differentially distributed in the two TLE models and that these areas are greater in the S-PILO than in the H-PILO model. There is also a selective kinetics of FJ+ cells in the hippocampus after SE induced by H-PILO, with no association with the severity of seizures, probably as a consequence of the extra-hippocampal damage. These data point to SE induced by H-PILO as a low-mortality model of TLE, with regional spatial and temporal patterns of FJ staining. (C) 2010 Elsevier B.V. All rights reserved.

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The objective of this study was to compare, on study models and initial cephalograms, the efficiency of Class II malocclusion treatment with the pendulum appliance, and with two maxillary premolar extraction protocol. The sample consisted of 48 treated Class II malocclusion patients: group 1 comprised 22 patients (7 males, 15 females) treated with the pendulum appliance, with an initial mean age of 14.44 years and group 2, 26 patients (14 males, 12 females) treated with two maxillary premolar extractions at an initial mean age of 13.66 years. To compare the efficiency of each treatment protocol, the occlusal outcomes were evaluated on dental casts using the Peer Assessment Rating (PAR) Index and the treatment time (TT) of each group was calculated on clinical charts. The degree of treatment efficiency was calculated as the ratio between the percentage of occlusal improvement, evaluated through the PAR index, and TT. Statistical analysis was undertaken by means of t-tests. The findings demonstrated that the two maxillary premolar extraction protocol provided the occlusal outcomes in a shorter time (group 1: 45.7 months, group 2: 23.01 months) and, therefore, demonstrated greater treatment efficiency than the pendulum appliance.

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In a previous study (Jones and Smith, 1999) we established that much the same core pattern of national identity characterizes many developed countries. Using the national identity module from the 1995 International Social Survey Programme, we identified two dimensions of national identity: an ascriptive dimension resembling the concept of ethnic identity described in the historical and theoretical literature, and a voluntarist dimension closer to the notion of civic identity. Some writers view these dimensions in terms of a historical sequence but we find that both constructs coexist in the minds of individual respondents in the nations we examine (we exclude Bulgaria and the Philippines from the present but not the earlier analysis). The dataset used for the multilevel analyses reported here consists of 28 589 respondents in the remaining 21 countries included in the national identity database for the 1995 round of surveys. The macrosociological literature on national identity does not offer well-defined predictions about what precise patterns of national identification we might expect to find among the masses of the developed countries. There are, however, recurring themes from which one can construct plausible hypotheses about how countries might differ according to their level of development, broadly conceived. Thus, we hypothesize that forces such as post-industrialism and globalization tend to favour the more open voluntaristic form of national identity over the more restrictive ascribed form. We develop different multi-level models in order to evaluate specific hypotheses pertaining to such issues, by simultaneously relating individual and societal characteristics to the relative strength of individual commitment to these different types of national identity.

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Evaluation of the performance of the APACHE III (Acute Physiology and Chronic Health Evaluation) ICU (intensive care unit) and hospital mortality models at the Princess Alexandra Hospital, Brisbane is reported. Prospective collection of demographic, diagnostic, physiological, laboratory, admission and discharge data of 5681 consecutive eligible admissions (1 January 1995 to 1 January 2000) was conducted at the Princess Alexandra Hospital, a metropolitan Australian tertiary referral medical/surgical adult ICU. ROC (receiver operating characteristic) curve areas for the APACHE III ICU mortality and hospital mortality models demonstrated excellent discrimination. Observed ICU mortality (9.1%) was significantly overestimated by the APACHE III model adjusted for hospital characteristics (10.1%), but did not significantly differ from the prediction of the generic APACHE III model (8.6%). In contrast, observed hospital mortality (14.8%) agreed well with the prediction of the APACHE III model adjusted for hospital characteristics (14.6%), but was significantly underestimated by the unadjusted APACHE III model (13.2%). Calibration curves and goodness-of-fit analysis using Hosmer-Lemeshow statistics, demonstrated that calibration was good with the unadjusted APACHE III ICU mortality model, and the APACHE III hospital mortality model adjusted for hospital characteristics. Post hoc analysis revealed a declining annual SMR (standardized mortality rate) during the study period. This trend was present in each of the non-surgical, emergency and elective surgical diagnostic groups, and the change was temporally related to increased specialist staffing levels. This study demonstrates that the APACHE III model performs well on independent assessment in an Australian hospital. Changes observed in annual SMR using such a validated model support an hypothesis of improved survival outcomes 1995-1999.

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The use of a fitted parameter watershed model to address water quantity and quality management issues requires that it be calibrated under a wide range of hydrologic conditions. However, rarely does model calibration result in a unique parameter set. Parameter nonuniqueness can lead to predictive nonuniqueness. The extent of model predictive uncertainty should be investigated if management decisions are to be based on model projections. Using models built for four neighboring watersheds in the Neuse River Basin of North Carolina, the application of the automated parameter optimization software PEST in conjunction with the Hydrologic Simulation Program Fortran (HSPF) is demonstrated. Parameter nonuniqueness is illustrated, and a method is presented for calculating many different sets of parameters, all of which acceptably calibrate a watershed model. A regularization methodology is discussed in which models for similar watersheds can be calibrated simultaneously. Using this method, parameter differences between watershed models can be minimized while maintaining fit between model outputs and field observations. In recognition of the fact that parameter nonuniqueness and predictive uncertainty are inherent to the modeling process, PEST's nonlinear predictive analysis functionality is then used to explore the extent of model predictive uncertainty.

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In cameras with radial distortion, straight lines in space are in general mapped to curves in the image. Although epipolar geometry also gets distorted, there is a set of special epipolar lines that remain straight, namely those that go through the distortion center. By finding these straight epipolar lines in camera pairs we can obtain constraints on the distortion center(s) without any calibration object or plumbline assumptions in the scene. Although this holds for all radial distortion models we conceptually prove this idea using the division distortion model and the radial fundamental matrix which allow for a very simple closed form solution of the distortion center from two views (same distortion) or three views (different distortions). The non-iterative nature of our approach makes it immune to local minima and allows finding the distortion center also for cropped images or those where no good prior exists. Besides this, we give comprehensive relations between different undistortion models and discuss advantages and drawbacks.

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ABSTRACT Earlier studies of cross-national differences in consumer behavior in different consumption sectors have verified that cultural differences have a strong influence on consumers. Despite the importance of cross-national analysis, no studies in the literature examine the moderating effects of nationality on the construction of behavioral intentions and their antecedents among cruise line passengers. This study investigates the moderating effects of nationality on the relationships between perceived value, satisfaction, trust and behavioral intentions among Spanish and (U.S.) American passengers of cruise lines that use Barcelona as home port and port-of-call. A theoretical model was tested with a total of 968 surveys. Structural equation models (SEMs) were used, by means of a multigroup analysis. Results of this study indicated that Spaniards showed stronger relationships between trust and behavioral intentions, and between emotional value and satisfaction. Americans presented stronger relationships between service quality and satisfaction, and between service quality and behavioral intentions.