Group properties of generalized quasi-linear wave equations

In this paper, complete group classification of a class of (1+1)-dimensional generalized quasi-linear wave equations is performed by using the Lie-Ovsiannikov method, additional equivalent transformation and furcate split method. Lie reductions of some truly ‘variable coefficient’ wave equations which are singled out from the classification results are investigated. Some classes of exact solutions of these ‘variable coefficient’ wave equations are constructed by means of both the reductions and the additional equivalent transformations. The nonclassical symmetries to the generalized quasi-linear wave equation are also studied. This enabled to obtain some exact solutions of the wave equations which are invariant under certain conditional symmetries.     

Comment on “Group analysis of KdV equation with time dependent coefficients”

We show that the group classification results of the article entitled “Group analysis of KdV equation with time dependent coefficients” which appeared in [A.G. Johnpillai, M.C. Khalique, Group analysis of KdV equation with time dependent coefficients, Appl. Math. Comput. 216 (2010) 3761-3771] can be obtained from those of a more general class by a change of variables.     

An improvement to multiple criteria ABC inventory classification

In this paper we presented an extended version of the Ng-modelg [W.L. Ng, A simple classifier for multiple criteria ABC analysis, European Journal of Operational Research 177 (2007) 344–353] for multi-criteria inventory classification. The proposed model is a nonlinear programming model which determines a common set of weights for all the items. Our model not only incorporates multiple criteria for ABC classification, but also maintains the effects of weights in the final solution, an improvement over the model proposed by Ng. An illustrative example is presented to compare our model and the Ng-model.     

Boson fock representations of stochastic processes

A classification theory of quantum stationary processes similar to the corresponding theory for classical stationary processes is presented. Our main result is the classification of those pairs of classical stationary processes that admit a joint boson Fock canonical representation. Translated fromMatematicheskie Zametki, Vol. 67, No. 1, pp. 3–14, January, 2000.     

Magnitude Estimations for Line Bisection Under Lateral Visuo-Spatial Neglect

Human subjects can bisect a line, with error, even when they have neglect on one side. How this skill, even though inefficient, can be represented in nonlinear psychophysical theory is explored here. A problem for previous theoretical explanations of lateral neglect bisection, where the errors of bisection are reversed in sign for brain-damaged subjects, when very short lines are used as stimuli, is shown not in fact to be a problem for N(onlinear) P(sychophysical) D(ynamics) theory at all, but is exactly what is expected to arise when sensitivities are biassed on one side. It is suggested that an imbalance in channel inputs in a nonlinear system representation has results which do not follow from a more conventional connectionist approach.     

Resonant dynamics in a rotordynamic system with nonlinear inertial coupling and shaft anisotropy

The response of a nonlinear, damped Jeffcott rotor with anisotropic stiffness is considered in the presence of an imbalance. For sufficiently small external torque or large imbalance, resonance capture or rotordynamic stall can occur, whereby the rotational velocity of the shaft is unable to increase beyond the fundamental resonance between the rotational and translational motion. This phenomena provides a mechanism for energy transfer from the rotational to the translational mode. Using the method of averaging a reduced-order model is developed, valid near the resonance, that describes this resonant behavior. The equilibrium points of these averaged equations, which correspond to stationary solutions of the original equations and rotordynamic stall, are described as the applied torque, damping, and anisotropy vary. As the anisotropy increases, assumed to arise from increasing shaft cracks, the torque required to eliminate the possibility of stall increases. However, when the system is started with zero initial conditions, the minimum torque required to pass through the resonance is approximately constant as the anisotropy increases. The predictions from the reduced-order model are verified against numerical simulations of the original equations of motion.     

技术市场聚类和预测

本依据1993～2000年全国及各省、市、自治区技术市场成交额，用聚类分析的方法分析了我国技术市场的发展状况，进而利用最小二乘法建立了我国技术市场的预测模型。实例计算表明模型是有效的。     

Feature selection algorithm in classification learning using support vector machines

An algorithm for selecting features in the classification learning problem is considered. The algorithm is based on a modification of the standard criterion used in the support vector machine method. The new criterion adds to the standard criterion a penalty function that depends on the selected features. The solution of the problem is reduced to finding the minimax of a convex-concave function. As a result, the initial set of features is decomposed into three classes—unconditionally selected, weighted selected, and eliminated features. Original Russian Text Yu.V. Goncharov, I.B. Muchnik, L.V. Shvartser @, 2008, published in Zhurnal Vychislitel’noi Matematiki i Matematicheskoi Fiziki, 2008, Vol. 48, No. 7, pp. 1318–1336.     

两类重要p-群及其自同构群的阶

In the paper we obtain two infinite classes of p-groups,calculate the orders of their automorphism groups and correct a mistake(perhaps misprinted)of Rodney James'paper in 1980.     

PLS: A versatile tool for industrial process improvement and optimization

Modern industrial processes are characterized by acquiring massive amounts of highly collinear data. In this context, partial least‐squares (PLS) regression, if wisely used, can become a strategic tool for process improvement and optimization. In this paper we illustrate the versatility of this technique through several real case studies that basically differ in the structure of the X matrix (process variables) and Y matrix (response parameters). By using the PLS approach, the results show that it is possible to build predictive models (soft sensors) for monitoring the performance of a wastewater treatment plant, to help in the diagnosis of a complex batch polymerization process, to develop an automatic classifier based on image data, or to assist in the empirical model building of a continuous polymerization process. Copyright © 2008 John Wiley & Sons, Ltd.