Inference for pth‐order random coefficient integer‐valued autoregressive processes

Abstract. A pth‐order random coefficient integer‐valued autoregressive [RCINAR(p)] model is proposed for count data. Stationarity and ergodicity properties are established. Maximum likelihood, conditional least squares, modified quasi‐likelihood and generalized method of moments are used to estimate the model parameters. Asymptotic properties of the estimators are derived. Simulation results on the comparison of the estimators are reported. The models are applied to two real data sets.     

Complex system reliability modelling with Dynamic Object Oriented Bayesian Networks (DOOBN)

Nowadays, the complex manufacturing processes have to be dynamically modelled and controlled to optimise the diagnosis and the maintenance policies. This article presents a methodology that will help developing Dynamic Object Oriented Bayesian Networks (DOOBNs) to formalise such complex dynamic models. The goal is to have a general reliability evaluation of a manufacturing process, from its implementation to its operating phase. The added value of this formalisation methodology consists in using the a priori knowledge of both the system's functioning and malfunctioning. Networks are built on principles of adaptability and integrate uncertainties on the relationships between causes and effects. Thus, the purpose is to evaluate, in terms of reliability, the impact of several decisions on the maintenance of the system. This methodology has been tested, in an industrial context, to model the reliability of a water (immersion) heater system.     

Simultaneous HPLC quantification of total cholesterol,tocopherols and β-carotene in Barrosã-PDO veal

A simple, rapid and sensitive procedure for the simultaneous determination of total cholesterol, tocopherols and β-carotene in meat is described. The method involves a direct saponification of the meat, a single n-hexane extraction and the analysis of the extracted compounds by normal-phase HPLC, using fluorescence (tocopherols) and UV–Vis photodiode array (cholesterol and β-carotene) detections in tandem. Rates of recovery of spiked meat samples were 93% for cholesterol, 83–86% for (α-, β- and -γ) tocopherols and 89% for β-carotene. Repeatabilities were high (CV < 6%) for all determined compounds, except for δ-tocopherol. This tocopherol, which is not usually present in meat, showed a much lower recovery percentage (73%) and repeatability (12.8%). This methodology was applied for the quantification of total cholesterol, tocopherols and β-carotene in three muscles (longissimus thoracis, longissimus lumborum and semitendinosus) of the Portuguese traditional Barrosã-PDO veal, obtained from autochthonous calves fed extensively during summer (with the least abundant green pastures) and slaughtered in early autumn (October). Barrosã-PDO veal showed median contents of total cholesterol (0.50–0.56 mg/g) and, depending on the analysed muscle, moderate to high contents of α-tocopherol (3.3–3.9 μg/g) and β-carotene (0.07–0.09 μg/g), suggesting an high sensorial and hygienic quality.     

Runout analysis in fatigue investigation

Those individual tests in a series of experiments that are not completed or must be suspended are known as “censored points,” or “runouts”. Inclusion of runouts in data analysis can be problematic, and such ad hoc approaches as ignoring the runout observation or treating it as a failure can significantly affect estimation. The methodology offered here alleviates the handling of runouts and censored data by using the maximum likelihood estimation (MLE) method to incorporate the censored data properly. The methodology is illustrated with an example problem using actual data and the affects of ad hoc approaches are illustrated.     

高层建筑结构设计的分析判断与优化

对高层建筑设计而言,设计前期的初步结构方案需通过结构软件的计算分析,判断该方案是否正确与合理,从而对其进行有针对性的修改和优化。文章结合具体实例,介绍了分析判断计算结果的主要几项内容及可采取的相应优化措施,从而可以提高设计的准确性和工作效率。     

轮式工程机械轮边减速器优化模型与方法

论述了重构轮式工程机械轮边减速器优化设计数学模型的必要性,给出了精确化的目标函数,全面化和准确化的设计变量、基于并行设计的约束条件;介绍了对优化解适用性评价的方法和手段。巧妙地解决了优化解中离散变量的圆整问题,提供了基于MATLAB的求解反渐开线函数的M文件。     

Assumptions and Consequences of Treating Providers in Therapy Studies as Fixed Versus Random Effects: Reply to Crits-Christoph, Tu, and Gallop (2003) and Serlin, Wampold, and Levin (2003).

In their comments on the authors' article (see record 2003-10163-009), R. C. Serlin, B. E. Wampold, and J. R. Levin (see record 2003-10163-011) and P. Crits-Christoph, X. Tu, and R. Gallop (see record 2003-10163-010) took issue with the authors' suggestion to evaluate therapy studies with nested providers with a fixed model approach. In this rejoinder, the authors' comment on Serlin et al's critique by showing that their arguments do not apply, are based on misconceptions about the purpose and nature of statistical inference, or are based on flawed reasoning. The authors also comment on Crits-Christoph et al's critique by showing that the proposed approach is very similar to, but less inclusive than, their own suggestion. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Development of calibration models for quality control in the production of ethylene/propylene copolymers by FTIR spectroscopy,multivariate statistical tools,and artificial neural networks

Principal component regression (PCR), partial least squares (PLS), StepWise ordinary least squares regression (OLS), and back‐propagation artificial neural network (BP‐ANN) are applied here for the determination of the propylene concentration of a set of 83 production samples of ethylene–propylene copolymers from their infrared spectra. The set of available samples was split into (a) a training set, for models calculation; (b) a test set, for selecting the correct number of latent variables in PCR and PLS and the end point of the training phase of BP‐ANN; (c) a production set, for evaluating the predictive ability of the models. The predictive ability of the models is thus evaluated by genuine predictions. The model obtained by StepWise OLS turned out to be the best one, both in fitting and prediction. The study of the breakdown number of samples to be included in the training set showed that at least 52 experiments are necessary to build a reliable and predictive calibration model. It can be concluded that FTIR spectroscopy and OLS can be properly employed for monitoring the synthesis or the final product of ethylene–propylene copolymers, by predicting the concentration of propylene directly along the process line. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Motion compensated film restoration

Motion picture films are susceptible to local degradations such as dust spots. Other deteriorations are global such as intensity and spatial jitter. It is obvious that motion needs to be compensated for before the detection/correction of such local and dynamic defects. Therefore, we propose a hierarchical motion estimation method ideally suited for high resolution film sequences. This recursive block-based motion estimator relies on an adaptive search strategy and Radon projections to improve processing speed. The localization of dust particles then becomes straightforward. Thus, it is achieved by simple inter-frame differences between the current image and motion compensated successive and preceding frames. However, the detection of spatial and intensity jitter requires a specific process taking advantage of the high temporal correlation in the image sequence. In this paper, we present our motion compensation-based algorithms for removing dust spots, spatial and intensity jitter in degraded motion pictures. Experimental results are presented showing the usefulness of our motion estimator for film restoration at reasonable computational costs. Received: 9 July 2000 / Accepted: 13 January 2002 Correspondence to:S. Boukir     

Multiplicative Operator Splittings in Nonlinear Diffusion: From Spatial Splitting to Multiple Timesteps

Operator splitting is a powerful concept used in many diversed fields of applied mathematics for the design of effective numerical schemes. Following the success of the additive operator splitting (AOS) in performing an efficient nonlinear diffusion filtering on digital images, we analyze the possibility of using multiplicative operator splittings to process images from different perspectives.We start by examining the potential of using fractional step methods to design a multiplicative operator splitting as an alternative to AOS schemes. By means of a Strang splitting, we attempt to use numerical schemes that are known to be more accurate in linear diffusion processes and apply them on images. Initially we implement the Crank-Nicolson and DuFort-Frankel schemes to diffuse noisy signals in one dimension and devise a simple extrapolation that enables the Crank-Nicolson to be used with high accuracy on these signals. We then combine the Crank-Nicolson in 1D with various multiplicative operator splittings to process images. Based on these ideas we obtain some interesting results. However, from the practical standpoint, due to the computational expenses associated with these schemes and the questionable benefits in applying them to perform nonlinear diffusion filtering when using long timesteps, we conclude that AOS schemes are simple and efficient compared to these alternatives.We then examine the potential utility of using multiple timestep methods combined with AOS schemes, as means to expedite the diffusion process. These methods were developed for molecular dynamics applications and are used efficiently in biomolecular simulations. The idea is to split the forces exerted on atoms into different classes according to their behavior in time, and assign longer timesteps to nonlocal, slowly-varying forces such as the Coulomb and van der Waals interactions, whereas the local forces like bond and angle are treated with smaller timesteps. Multiple timestep integrators can be derived from the Trotter factorization, a decomposition that bears a strong resemblance to a Strang splitting. Both formulations decompose the time propagator into trilateral products to construct multiplicative operator splittings which are second order in time, with the possibility of extending the factorization to higher order expansions. While a Strang splitting is a decomposition across spatial dimensions, where each dimension is subsequently treated with a fractional step, the multiple timestep method is a decomposition across scales. Thus, multiple timestep methods are a realization of the multiplicative operator splitting idea. For certain nonlinear diffusion coefficients with favorable properties, we show that a simple multiple timestep method can improve the diffusion process.