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11.
The subsolidus phase relationships in Si3N4–AlN–rare-earth oxide (Me2O3 where Me=Nd, Sm, Gd, Dy, Er, and Yb) systems were studied. Solid-solution regions with the α-Si3N4 structure were delineated along the Si3N4–"Me2O3:9AIN" joins for all of the rare-earth oxide systems studied. The solubility limits of these solid solutions increased with decreasing size of the rare-earth ions.  相似文献   
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Micron‐sized polymer particles were coated with layers of nickel compounds by plating electrolessly in the presence of aqueous solutions of nickel chloride, sodium hypophosphite, sodium citrate, and ammonium chloride at elevated temperature. The uniform functional polymer particle could be obtained by seeded polymerization. To investigate the effect of surface functionality on the conditions for nickel deposition, the polymer particle was functionalized with the thiol group. From morphological observation, it was found that the mode of nickel deposition was greatly dependent on the surface functionality of the polymer particle. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 87: 420–424, 2003  相似文献   
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Petroleum pitch (Ashland A240) has been subjected to thermal treatment and solvent fractionation to produce refined pitches to be evaluated as impregnants for C-C composites. The solvent fractions were obtained by sequential Soxhlet extraction with solvents such as hexane, benzene, and pyridine. Thermal treatment to 408 °C produced a mesophase pitch (≈50% mesophase); an appreciable portion of the mesophase was soluble in strong solvents. There were substantial differences in chemical composition and in pyrolysis behaviour of the fractions. As the depth of fraction increased, the pyrolysis yield and bloating increased, and the microstructure of the coke became finer until glassy microconstituents were formed in the deepest fractions.  相似文献   
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Including: Neural Networks Pioneer Vladimir Vapnik, NEC Research, Inc., USA. Fuzzy Systems Pioneer Hideo Tanaka, Hiroshima International University, JAPAN. Evolutionary Computation Pioneer David E. Goldberg, University of Illinois at Urbana Champaign, USA and John Grefenstette, George Mason University, USA. Meritorious Services James M. Keller, University of Missouri, USA. IEEE Transactions on Fuzzy Systems Outstanding Paper, IEEE Transactions on Evolutionary Computation Outstanding Paper, Outstanding Chapter, Outstanding Ph.D. Dissertation. Also past CIS Neural Networks Pioneer Awardees, Fuzzy Systems Pioneer Awardees, Evolutionary Computation Pioneer Awardees and Meritorious Service Awardees.  相似文献   
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In this paper, an automatic diagnosis system for diabetes on Linear Discriminant Analysis (LDA) and Morlet Wavelet Support Vector Machine Classifier: LDA–MWSVM is introduced. The structure of this automatic system based on LDA-MWSVM for the diagnosis of diabetes is composed of three stages: The feature extraction and feature reduction stage by using the Linear Discriminant Analysis (LDA) method and the classification stage by using Morlet Wavelet Support Vector Machine (MWSVM) classifier stage. The Linear Discriminant Analysis (LDA) is used to separate features variables between healthy and patient (diabetes) data in the first stage. The healthy and patient (diabetes) features obtained in the first stage are given to inputs of the MWSVM classifier in the second stage. Finally, in the third stage, the correct diagnosis performance of this automatic system based on LDA–MWSVM for the diagnosis of diabetes is calculated by using sensitivity and specificity analysis, classification accuracy, and confusion matrix, respectively. The classification accuracy of this system was obtained at about 89.74%.  相似文献   
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This paper deals with the stability radii of implicit dynamic equations on time scales when the structured perturbations act on both the coefficient of derivative and the right-hand side. Formulas of the stability radii are derived as a unification and generalization of some previous results. A special case where the real stability radius and the complex stability radius are equal is studied. Examples are derived to illustrate results.  相似文献   
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In the modern age of Internet connectivity, advanced information systems have accumulated huge volumes of data. Such fast growing, tremendous amount of data, collected and stored in large databases has far exceeded our human ability to comprehend without proper tools. There has been a great deal of research conducted to explore the potential applications of Machine Learning technologies in Security Informatics. This article studies the Network Security Detection problems in which predictive models are constructed to detect network security breaches such as spamming. Due to overwhelming volume of data, complexity and dynamics of computer networks and evolving cyber threats, current security systems suffer limited performance with low detection accuracy and high number of false alarms. To address such performance issues, a novel Machine Learning algorithm, namely Boosted Subspace Probabilistic Neural Network (BSPNN), has been proposed which combines a Radial Basis Function Neural Network with an innovative diversity-based ensemble learning framework. Extensive empirical analyses suggested that BSPNN achieved high detection accuracy with relatively small computational complexity compared with other conventional detection methods.  相似文献   
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