Bootstrapping the Local Periodogram of Locally Stationary Processes

Abstract. Locally stationary processes are non‐stationary stochastic processes the second‐order structure of which varies smoothly over time. In this paper, we develop a method to bootstrap the local periodogram of a locally stationary process. Our method generates pseudo local periodogram ordinates by combining a parametric time and non‐parametric frequency domain bootstrap approach. We first fit locally a time varying autoregressive model so as to capture the essential characteristics of the underlying process. A locally calculated non‐parametric correction in the frequency domain is then used so as to improve upon the locally parametric autoregressive fit. As an application, we investigate theoretically the asymptotic properties of the bootstrap method proposed applied to the class of local spectral means, local ratio statistics and local spectral density estimators. Some simulations demonstrate the ability of our method to give accurate estimates of the quantities of interest in finite sample situations and an application to a real‐life data‐set is presented.     

3D velocity from 3D Doppler radial velocity

We present local least squares and regularization frameworks for computing 3D velocity (3D optical flow) from 3D radial velocity measured by a Doppler radar. We demonstrate the performance of our algorithms quantitatively on synthetic radial velocity data and qualitatively on real radial velocity data, obtained from the Doppler radar at Kurnell Radar station, Botany Bay, New South Wales, Australia. Radial velocity can be used to predict the future positions of storms in sequences of Doppler radar datasets.© 2005 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 15, 189–198, 2005     

Logistic Regression Analysis of Customer Satisfaction Data

Variation exists in all processes. Significant work has been done to identify and remove sources of variation in manufacturing processes resulting in large returns for companies. However, business process optimization is an area that has a large potential return for a company. Business processes can be difficult to optimize due to the nature of the output variables associated with them. Business processes tend to have output variables that are binary, nominal or ordinal. Examples of these types of output include whether a particular event occurred, a customer's color preference for a new product and survey questions that assess the extent of the survey respondent's agreement with a particular statement. Output variables that are binary, nominal or ordinal cannot be modeled using ordinary least‐squares regression. Logistic regression is a method used to model data where the output is binary, nominal or ordinal. This article provides a review of logistic regression and demonstrates its use in modeling data from a business process involving customer feedback. Copyright © 2006 John Wiley & Sons, Ltd.     

Prediction of spectral reflectance factor distribution of automotive paint finishes

It is necessary to determine the accurate reflectance of painted surfaces for the review of paint finishes by computer graphics (CG) before actual painting of the exterior color of automobiles, and for quality control during production and inspection processes. We have optimized a method for measuring reflectance by using a statistical technique. We have found that the reflectance of a painted surface is best measured at an incident angle of 60° and at five aspecular angles of 10°, 18°, 28°, 40°, and 90°. Our method makes it possible to accurately reproduce reflection characteristics of paint finishes containing special flake pigments, such as pearl mica. Also it was proved that our method can apply not only to solid and metallic coatings but to all painted surfaces. © 2005 Wiley Periodicals, Inc. Col Res Appl, 30, 275–282, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20125     

锌钾硼对甜菜产质量效应及最佳施肥措施的研究

本文利用最优回归设计“310”方案,研究了黑土地甜菜 Zn、K_2O、B的效果及合理施用问题。得出甜菜块根产量、含糖、产糖量、灰分 K 和有害 N 与 ZnK_2O、B 肥回归关系显著的回归模型,分析了 Zn、K_2O、B 对上述五个指标的效应,明确了 Zn 是影响各项指标的主要因子,并采用频率筛选法,提出了兼顾上述五项指标的优质高产施肥措施。     

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     

Oil yield and compressibility modeling during microscale expression: Criteria for linseed breeding

Seven linseed varieties were harvested at seven times before complete maturity. Microscale oilseed expressions were subsequently carried out on it. A pressure of 10 MPa was applied for 1 h under uniaxial stress. The results were characterized in terms of oil, water and mucilage content, harvest date and oil yield. The piston displacement versus time (creep curves) was described by a four‐Kelvin‐Voigt elements viscoelastic model. Parameters were derived from the model, such as the mechanical properties of seeds (compressibility moduli), showing that the viscoelastic model fits well the experimental data (R² ≈ 0.999). The modeling parameters were combined with some biochemical data in order to predict the kinetics of oil extraction.     

地方热电联产企业发展对策的探讨

介绍了泰州热电企业的运行情况，分析了各热电厂在技术改造、扩大热用户和强化内部考核管理方面的措施，探讨了地方热电企业应采取的对策和发展思路。     

The pulse distributed file system

A network of powerful personal computers, linked by a high-speed local area network, is being seen increasingly as an alternative to a traditional centralized time-sharing operating system. The PULSE project is investigating how such a system may be constructed to give the benefits of a self-sufficient personal computer to each user without losing the facilities for communication and sharing of data inherent in centralized systems. In particular, a distributed file system has been built which provides a single global UNIX

1 UNIX is a trademark of Bell Laboratories.

-like hierarchy, with a consistent appearance when accessed from any machine. Replicated copies of files are maintained to improve reliability, increase performance, and enable each machine to run stand-alone, albeit with reduced facilities.     

Change of the amorphous state by heat treatment below the glass transition temperature

This study was undertaken to elucidate the state of a polymer in the amorphous state through a change of motion of the molecular chain caused by heat treatment below the glass transition temperature. From dielectric measurements of amorphous poly(ethylene terephthalate) heat-treated below T_g, it was found that the average relaxation time, the distribution of relaxation time and the dielectric strength increase with increase of heat treatment. From these results, it was concluded that the amorphous state becomes more random by heat treatment.