Estimation of break location and size for loss of coolant accidents using neural networks

In this work, a probabilistic neural network (PNN) that has been applied well to the classification problems is used in order to identify the break locations of loss of coolant accidents (LOCA) such as hot-leg, cold-leg and steam generator tubes. Also, a fuzzy neural network (FNN) is designed to estimate the break size. The inputs to PNN and FNN are time-integrated values obtained by integrating measurement signals during a short time interval after reactor scram. An automatic structure constructor for the fuzzy neural network automatically selects the input variables from the time-integrated values of many measured signals, and optimizes the number of rules and its related parameters. It is verified that the proposed algorithm identifies very well the break locations of LOCAs and also, estimate their break size accurately.     

Induced ordered weighted geometric operators and their use in the aggregation of multiplicative preference relations

In this article, we introduce the induced ordered weighted geometric (IOWG) operator and its properties. This is a more general type of OWG operator, which is based on the induced ordered weighted averaging (IOWA) operator. We provide some IOWG operators to aggregate multiplicative preference relations in group decision‐making (GDM) problems. In particular, we present the importance IOWG (I‐IOWG) operator, which induces the ordering of the argument values based on the importance of the information sources; the consistency IOWG (C‐IOWG) operator, which induces the ordering of the argument values based on the consistency of the information sources; and the preference IOWG (P‐IOWG) operator, which induces the ordering of the argument values based on the relative preference values associated with each one of them. We also provide a procedure to deal with “ties” regarding the ordering induced by the application of one of these IOWG operators. This procedure consists of a sequential application of the aforementioned IOWG operators. Finally, we analyze the reciprocity and consistency properties of the collective multiplicative preference relations obtained using IOWG operators. © 2004 Wiley Periodicals, Inc.     

Performance comparison between the training method and the numerical method of the orthogonal neural network in function approximation

The orthogonal neural network is a recently developed neural network based on the properties of orthogonal functions. It can avoid the drawbacks of traditional feedforward neural networks such as initial values of weights, number of processing elements, and slow convergence speed. Nevertheless, it needs many processing elements if a small training error is desired. Therefore, numerous data sets are required to train the orthogonal neural network. In the article, a least‐squares method is proposed to determine the exact weights by applying limited data sets. By using the Lagrange interpolation method, the desired data sets required to solve for the exact weights can be calculated. An experiment in approximating typical continuous and discrete functions is given. The Chebyshev polynomial is chosen to generate the processing elements of the orthogonal neural network. The experimental results show that the numerical method in determining the weights gives as good performance in approximation error as the known training method and the former has less convergence time. © 2004 Wiley Periodicals, Inc. Int J Int Syst 19: 1257–1275, 2004.     

A ReScUE XML/EDI model

Since electronic data interchange (EDI) is one of the most important components in electronic commerce and since Extensible Markup Language (XML) provides Internet developers with a powerful vehicle for exchanging messages, XML/EDI has received much attention from almost all well‐known international enterprises and is believed to be the next generation EDI. However, since XML allows developers to design their own elements and attributes, it is almost certain businesses will receive XML documents with unknown elements. Generally, human intervention is required to solve the problem. Therefore, it is indispensable to design an efficient scheme to resolve the unknown elements. In this paper, we propose a ReScUE XML/EDI model such that transformation templates will be generated automatically for documents with unknown elements, and the documents will be converted into expected format. This model increases the flexibility of XML/EDI systems and reduces human intervention. Copyright © 2003 John Wiley & Sons, Ltd.     

Implementation of a TMO‐structured real‐time airplane‐landing simulator on a distributed computing environment

In real‐time simulation, the simulated system should display the same (or very close) timing behavior as the target system. The simulation accuracy is increased as the simulation time unit is decreased. Although there are several models for such systems, the TMO model is particularly appropriate due to its natural support for real‐time distributed object‐oriented programming. This paper discusses the results of the implementation of a real‐time airplane‐landing simulator on a distributed computing environment using the TMO model. Copyright © 2004 John Wiley & Sons, Ltd.     

Kinematic optimal design of a paramill: A multi‐SP device

In this paper, a manipulability analysis of a new parallel‐type rolling mill, named “paramill,” in its conceptual design stage is investigated. The paramill considered uses two Stewart platforms (SPs) in opposite directions for the generation of 6 degree‐of‐freedom motions of individual work‐rolls. The objective of this new approach is to pursue an integrated control of the strip thickness, strip shape, pair‐crossing angle, uniform wear of the rolls, and tension of the strip. The forward/inverse kinematics problems are formulated. Two main kinematic parameters, the size of the base and the acute angle made by two neighboring joints for a given size of the work‐roll, have been determined in the way that the force and moment transmission from the actuators to the work‐rolls is maximized. © 2004 Wiley Periodicals, Inc.     

Modeling and control for a Gough‐Stewart platform CNC machine

In this paper, a complete dynamic model on task space for a 6 degrees of freedom (DOF) Gough‐Stewart platform‐type computer numerical control (CNC) machine is derived. The rotation terms of the legs are included for those inertia effects cannot be negligible in the machine tool applications. The formulation derived by means of the Euler‐Lagrange method is convenient for designing the adaptive control law. Also, the average‐type force model for end milling process is derived and included in the dynamic model and control. A composite adaptive control scheme is developed by use of filtering dynamics technique. An appropriate estimator gain is designed in the parameter adaptation law that is useful for estimating the selected important cutting parameters. Experimental results verify the proposed adaptive control scheme can achieve good tracking performance. © 2004 Wiley Periodicals, Inc.     

Text information extraction in images and video: a survey

Text data present in images and video contain useful information for automatic annotation, indexing, and structuring of images. Extraction of this information involves detection, localization, tracking, extraction, enhancement, and recognition of the text from a given image. However, variations of text due to differences in size, style, orientation, and alignment, as well as low image contrast and complex background make the problem of automatic text extraction extremely challenging. While comprehensive surveys of related problems such as face detection, document analysis, and image & video indexing can be found, the problem of text information extraction is not well surveyed. A large number of techniques have been proposed to address this problem, and the purpose of this paper is to classify and review these algorithms, discuss benchmark data and performance evaluation, and to point out promising directions for future research.     

ULTRA‐FINE TRACKING CONTROL ON PIEZOELECTRIC ACTUATED MOTION STAGE USING PIEZOELECTRIC HYSTERETIC MODEL

The tracking control accuracy of the piezoelectric actuator (PEA) is limited due to its inherent hysteresis nonlinearity. A new piezoelectric‐actuator model is synthesized based on two first‐order transfer systems in parallel with two tuned parameters determined from one experiment. Two open‐loop tracking controllers are implemented with the proposed model to compensate the hysteresis of linear positioning. Numerical simulations and experimental tests on the tracking of sinusoidal and triangular waveforms with signal frequencies ranging from 1Hz to 30 Hz are revisited and compared with the conventional Bouc‐Wen and Duhem models. Experimental results reveal that the RMS tracking error can be reduced to less than 2% of the maximum traveling distance without any feedback sensor. When a piezoelectric actuated on a two Degree‐Of‐Freedom (DOF) monolithic motion stage was employed, the RMS tracking error was 50 nm within the measured sensor accuracy.