Modeling of Temperature–Frequency Correlation Using Combined Principal Component Analysis and Support Vector Regression Technique

A good understanding of environmental effects on structural modal properties is essential for reliable performance of vibration-based damage diagnosis methods. In this paper, a method of combining principal component analysis (PCA) and support vector regression (SVR) technique is proposed for modeling temperature-caused variability of modal frequencies for structures instrumented with long-term monitoring systems. PCA is first applied to extract principal components from the measured temperatures for dimensionality reduction. The predominant feature vectors in conjunction with the measured modal frequencies are then fed into a support vector algorithm to formulate regression models that may take into account thermal inertia effect. The research is focused on proper selection of the hyperparameters to obtain SVR models with good generalization performance. A grid search method with cross validation and a heuristic method are utilized for determining the optimal values of SVR hyperparameters. The proposed method is compared with the method directly using measurement data to train SVR models and the multivariate linear regression (MLR) method through the use of long-term measurement data from a cable-stayed bridge. It is shown that PCA-compressed features make the training and validation of SVR models more efficient in both model accuracy and computational costs, and the formulated SVR model performs much better than the MLR model in generalization performance. When continuously measured data is available, the SVR model formulated taking into account thermal inertia effect can achieve more accurate prediction than that without considering thermal inertia effect.     

Multiple object semilinear motion planning

We present a method based on extended linear real quantifier elimination for multiple object semilinear motion planning, i.e. finding collision-free trajectories for several robots in a time dependent environment. For practical applicability the method is limited to polygonal objects and linear trajectories. It can, however, deal with situations involving even non-convex objects.     

VaR and ES for linear portfolios with mixture of elliptic distributions risk factors

In this paper, we generalize the Linear VaR method from portfolios with normally distributed risk factors to portfolios with mixture of elliptically distributed ones. We treat both the Expected Shortfall and the Value-at-Risk of such portfolios. Special attention is given to the particular case of a mixture of multivariate t-distributions. This is a part of J. SADEFO-KAMDEM PhD Thesis[12] of the Université de Reims, France . It has been presented at the workshop on modelling and computation in Financial Engineering at Bad Herrenalb, Germany May 6-8, 2003. The author is an associate professor at the Department of mathematics, université d’Evry Val d’Essonne.     

高能多脉冲超正压射孔技术

高能多脉冲超正压射孔技术是一项利用高能燃料的燃烧在目的层产生压力的超正压射孔或增产新技术。主要介绍了该技术的基本原理和装置的结构设计，并给出了该技术在国内一些油田的应用实例。实例说明，该技术是一项非常好的完井或增产新技术。     

Generation and selection of likely interpretations during plan recognition in task-oriented consultation systems

This paper presents a mechanism which infers a user's plans from his/her utterances by directing the inference process towards the more likely interpretations of a speaker's statements among many possible interpretations. Our mechanism uses Bayesian theory of probability to assess the likelihood of an interpretation, and it complements this assessment by taking into consideration two aspects of an interpretation: its coherence and its information content. The coherence of an interpretation is determined by the relationships between the different statements in the discourse. The information content of an interpretation is a measure of how well defined the interpretation is in terms of the actions to be performed on the basis of this interpretation. This measure is used to guide the inference process towards interpretations with higher information content. The information content of an interpretation depends on the specificity and the certainty of the inferences in it, where the certainty of an inference depends on the knowledge on which the inference is based. Our mechanism has been developed for use in task-oriented consultation systems. The particular domain that we have chosen for exploration is that of travel booking.     

线性八元树表示的三维客体群的连通分量标号和计数

本文提出二种算法分别标号和计数线性八元树表示的三维客体群的连通分量.这些操作典型地需要检查线性八元树中诸八分体在三个主方向上的面邻接对.根据这些邻接对,可以建造在计算机中用关联矩阵表示的邻接图.连通分量标号和计数是在关联矩阵上分别执行相应的操作而完成的.连通分量标号的执行时间是O(n+m·logm),而连通分量计数需要O(n)时间,其中m和n分别是线性八元树中八分体和邻接对的数目.     

Response level crossing rate of a linear system excited by a partially specified Gaussian load process

The problem of determining the maximum mean response level crossing rate of a linear system driven by a partially specified Gaussian load process has been considered. The partial specification of the load is given only in terms of its total average energy. The critical input power spectral (PSD) function, which maximizes the mean response level crossing rate, is obtained. The critical input PSD turns out to be highly narrow-banded which fails to capture the erratic nature of the excitation. Consequently, the trade-off curve between the maximum mean response level crossing rate and the maximum disorder in the input process, quantified in terms of its entropy rate, has been generated. The method of Pareto optimization is used to tackle the conflicting objectives of the simultaneous maximization of the mean response level crossing rate and the input entropy rate. The non-linear multi-objective optimization has been carried out using a recently developed multi-criteria genetic algorithm scheme. Illustrative example of determining the critical input of an axially vibrating rod, excited by a partially specified stationary Gaussian load process, has been considered.     

Makespan estimation and order acceptance in batch process industries when processing times are uncertain

Batch process industries are characterized by complex precedence relationships between operations, which renders the estimation of an acceptable workload very difficult. A detailed schedule based model can be used for this purpose, but for large problems this may require a prohibitive large amount of computation time. We propose a regression based model to estimate the makespan of a set of jobs. We extend earlier work based on deterministic processing times by considering Erlang-distributed processing times in our model. This regression-based model is used to support customer order acceptance. Three order acceptance policies are compared by means of simulation experiments: a scheduling policy, a workload policy and a regression policy. The results indicate that the performance of the regression policy can compete with the performance of the scheduling policy in situations with high variety in the job mix and high uncertainty in the processing times. Correspondence to: C.V. Ivanescu     

A NEW ALGORITHM FOR ADAPTIVE LATTICE FILTERAND ITS APPLICATION IN THE SPEECH LINEARPREDICTIVE SYNTHESIS

In this paper, an adaptive line spectral pair filter is derived from an adaptive lattice filter. A least-mean-square(LMS) type adaptive algorithm used to calculate directly the line spectral pair(LSP) coefficients on a stage-by-stage basis is presented. Experimental results show that the algorithm has higher convergence rate and lower misadjustment as compared with the other algorithms. The LSP coefficients calculated by the algorithm have been used to carry out speech linear predictive synthesis, resulting in better results than PARCOR coefficients.     

Numerical solution of the kinematic dynamo problem for Beltrami flows in a sphere

The article discusses computational aspects of the kinematic problem of magnetic field generation by a Beltrami flow in a sphere. Galerkin's method is applied with a functional basis consisting of Laplace operator eigenfunctions. Dominant eigenvalues of the magnetic induction operator and associated magnetic eigenmodes are obtained numerically for a certain Beltrami flow for magnetic Reynolds numbers up to 100. The eigenvalue problem is solved by a highly optimized iterative procedure, which is quite general and can be applied to numerical treatment of arbitrary linear stability problems.