Extrapolation of fuzzy values from incomplete data bases

This paper presents different approaches which enable a data base management system to obtain a plausible fuzzy estimate for an attribute value of an item for which the information is not explicitly stored in the data base. This can be made either by a kind of analogical reasoning from information about particular items or by means of expert rules which specify the (fuzzy) sets of possible values of the attribute under consideration, for various classes of items. Another kind of expert rules enables the system to compute an estimate from the attribute value of another item provided that, in other respects, this latter item sufficiently resembles the item, the value of which we are interested in; then these expert rules are used either for controlling the analogical reasoning process or for enlarging the scope of application of the first kind of expert rules. The different approaches are discussed in the framework of possibility theory.     

Passivity‐based sliding mode control for nonlinear systems

Passivity with sliding mode control for a class of nonlinear systems with and without unknown parameters is considered in this paper. In fact, a method for deriving a nonlinear system with external disturbances to a passive system is considered. Then a passive sliding mode control is designed corresponding to a given storage function. The passivity property guarantees the system stability while sliding mode control techniques assures the robustness of the proposed controller. When the system includes unknown parameters, an appropriate updated law is obtained so that the new transformed system is passive. The passivation property of linear systems with sliding mode is also analysed. The linear and nonlinear theories are applied to a simple pendulum model and the gravity‐flow/pipeline system, respectively. Copyright © 2008 John Wiley & Sons, Ltd.     

Understanding and Modeling the Effect of Surfactants in Enhanced Particle Removal from Surfaces in Aqueous Media

The removal of particulate contamination is a critical issue for many manufacturing processes. It is particularly critical to the electronics industry in which small pieces of microscopic debris remaining after chemical mechanical planarization (cmp) using submicron polishing particles can cause device failure. One way to enhance particle removal following the cmp process is to utilize surfactants. Recent research has shown ways to model the effect of surfactants on enhanced particle removal. However, previous research has not demonstrated the effect of ionic strength on enhanced particle removal associated with surfactant use. Past research has also not shown the combined effects of ionic strength and surfactant concentration on enhanced particle removal using surfactants. This article summarizes the parameters affecting particle removal, and it provides data and analysis on the effect of ionic strength as well as the combined effects of ionic strength and surfactant concentration on particle removal following cmp processing.     

含V、N无缝钢管表面外折缺陷产生原因的分析

通过对鞍钢生产的部分批号V、N微合金强化无缝钢管及生产该钢管的原料连铸坯和连轧管坯的表面缺陷进行研究，分析了含V、N钢管表面外折缺陷的成因，提出了改善钢管表面质量的方法。采用改进后工艺生产的无缝管，其表面外折废品量大幅度降低。     

The As-prepared surfaces of C-axis-oriented Nd1Ba2Cu3Oy thin films characterized using scanning probe microscopes

Recently, superconducting Nd₁Ba₂Cu₃O_y (Ndl23) thin films with high superconducting transition temperature (T _c) have been successfully fabricated at our institute employing the standard laser ablation method. In this paper, we report the results of surface characterization of the Nd123 thin films using an ultrahigh vacuum scanning tunneling microscope/spectroscopy (UHV-STM/STS) and an atomic force microscope (AFM) system operated in air. Clear spiral pattern is observed on the surfaces of Nd123 thin films by STM and AFM, suggesting that films are formed by two-dimensional island growth mode. Contour plots of the spirals show that the step heights of the spirals are not always the integer or half-integer number of thec-axis parameter of the structure. This implies that the surface natural termination layer of the films may not be unique. This result is supported byI-V STS measurements. The surface morphology of the Nd123 thin films is compared with that of thec-axis-oriented Y₁Ba₂Cu₃S_y thin films. Surface atomic images of the as-prepared Nd123 thin films are obtained employing both STM and AFM. STS measurements show that most of the surfaces are semiconductive. The results of STS measurements together with the fact that we are able to see the surface atomic images using scanning probe microscopes suggest that exposure to air does not cause serious degradation to the as-prepared surfaces of Nd123 thin films.     

A genetic‐based neuro‐fuzzy controller for blind equalization of time‐varying channels

This paper presents a neuro‐fuzzy network (NFN) where all its parameters can be tuned simultaneously using genetic algorithms (GAs). The approach combines the merits of fuzzy logic theory, neural networks and GAs. The proposed NFN does not require a priori knowledge about the system and eliminates the need for complicated design steps such as manual tuning of input–output membership functions, and selection of fuzzy rule base. Although, only conventional GAs have been used, convergence results are very encouraging. A well‐known numerical example derived from literature is used to evaluate and compare the performance of the network with other equalizing approaches. Simulation results show that the proposed neuro‐fuzzy controller, all parameters of which have been tuned simultaneously using GAs, offers advantages over existing equalizers and has improved performance. From the perspective of application and implementation, this paper is very interesting as it provides a new method for performing blind equalization. The main contribution of this paper is the use of learning algorithms to train a feed‐forward neural network for M‐ary QAM and PSK signals. This paper also provides a platform for researchers of the area for further development. Copyright © 2008 John Wiley & Sons, Ltd.     

Data mining of resilience indicators

In recent years, the Asia-Pacific region has experienced several financial setbacks, including speculative attacks in 1998 and the SARS outbreak in 2003. Financial stresses of this nature are unanticipated, and not all of the dangers can be predicted by the examination of market information and macroeconomic indicators. The Early Warning System (EWS) that has been adopted by the International Monetary Fund may not be able to predict future financial crises for all possible scenarios, because shocks come in many different forms. To supplement the EWS, this paper proposes a data mining framework to measure the resilience of an economy. The resilience framework does not predict a crisis, but rather assesses the current state of health of an economy and its ability to withstand a financial shock should one occur. The framework is based on a feedback system consisting of two stages. The first stage assigns a resilience score to each economy based on a fuzzy logic scoring scheme that is built on the ambiguous reasoning of experts. The second stage uses the classification tree approach to estimate thresholds for each economic indicator, and examines the quality of the fuzzy score. The result from the second stage is then passed back to the first stage as feedback. The final result is obtained when the feedback system reaches its equilibrium state. The proposed resilience framework is applied to the external-sector and the public-sector economies of several countries to illustrate its applicability.     

Possibilities and extension of XRD material response analysis in failure research for the advanced evaluation of the damage level of Hertzian loaded components

Due to clearly distinguishable damage symptoms, it is differentiated between the surface and sub‐surface failure mode of rolling bearings. Material states red out by X‐ray diffraction (XRD) residual stress measurements point to a variety of loading conditions especially at raceway surfaces that are associated with several competing failure mechanisms. The corresponding lifetime reduction can range from the lower fatigue strength region to material ratcheting in extreme cases. Relevant position of the microstructural changes and nature of the failure mechanisms are characterized. The time alteration of the XRD material parameters measured at or near the surface and at the depth of the maximum equivalent stress correlates, in a different manner, with the statistical parameter of the 10 % bearing life. Both failure modes are illustrated by concrete examples. Contaminated lubricant and boundary lubrication, which represent practically important surface‐induced failures, are discussed in more detail. Gray staining, i.e. shallow pitting, often occurs without distinct indication of global material aging by means of XRD characteristics. Here, scanning electron microscopy observations and electron microprobe analyses point to corrosion fatigue as acting surface failure mechanism. The interaction between material and lubricant under complex loading regimes particularly of mixed friction and corrosion opens further failure research areas in the field of tribology.