功率电子器件用AlN陶瓷基板的研制

阐述了AlN陶瓷的烧结原理 ,分析了烧结工艺参数对大面积AlN基板性能的影响 ,成功研制出了高热导率(190W /m·K)、大面积 (14 0mm× 90mm)、翘曲度为 2 0 μm/5 0mm的AlN陶瓷基板。     

硼酸铝晶须增强环氧树脂和双马来酰亚胺树脂体系的研究

本文以硼酸铝晶须为增强剂，以4，5-环氧环己烷-1，2-二甲酸二缩水甘油酯(TDE-85)，甲基纳狄克酸酐(MNA)、N，N’-二胺基二苯甲烷型双马来酰亚胺(BMI)/O，O′-二烯丙基双酚A(BA)体系分别作为基体制备晶须增强复合材料。研究了晶须对树脂的尺寸、表面处理方法、含量对树脂体系力学性能和热性能的影响；通过扫描电子显微镜(SEM)分析了浇注体的弯曲、冲击断口，研究晶须的增强机理。     

Influence of inhibitor addition on the corrosion protection performance of sol–gel coatings on AA2024

Sol–gel films are actively investigated during the last decade as possible candidates for environmentally friendly pre-treatments. However, the important drawback in this case is the lack of active corrosion protection and self-healing ability.     

A new iterative order reduction (IOR) method for eigensolutions of large structures

Order reduction is a computationally efficient method to estimate some lowest eigenvalues and the corresponding eigenvectors of large structural systems by reducing the order of the original model to a smaller one. But its accuracy is limited to a small range of frequencies that depends on the selection of the retained degrees of freedom. This paper proposes a new iterative order reduction (IOR) technique to obtain accurately the eigensolutions of large structural systems. The technique retains all the inertia terms associated with the removed degrees of freedom. This hence leads to the reduced mass matrix being in an iterated form and the reduced stiffness matrix constant. From these mass and stiffness matrices, the eigensolutions of the reduced system can be obtained iteratively. On convergence the reduced system reproduces the eigensolutions of the original structure. A proof of the convergence property is also presented. Applications of the method to a practical GARTEUR structure as well as a plate have demonstrated that the proposed method is comparable to the commonly used Subspace Iteration method in terms of numerical accuracy. Moreover, it has been found that the proposed method is computationally more efficient than the Subspace Iteration method. Copyright © 2003 John Wiley & Sons, Ltd.     

Transmittance and cathodoluminescence of AlN ceramics sintered with Ca3Al2O6 as sintering additive

Aluminum nitride ceramics were prepared by sintering with 0–4.8 mass% of Ca₃Al₂O₆ (C₃A) as a sintering additive. The transmittance in the range of 260–550 nm increased with increasing amount of C₃A. The cathodoluminescence intensity attributed to oxygen-induced defects decreased with increasing amount of C₃A. From the results, the increase of the transmittance in the range of 260–550 nm was considered to be related to the decrease of the oxygen-induced defect density.     

Elimination of organic matter present in wastewaters from the cork industry by membrane filtration

BACKGROUND: The first stage of the cork industrial process generates great volumes of wastewater with moderate to high organic pollutant content that must be purified using different procedures, such as filtration by membranes. RESULTS: The tangential filtration of these wastewaters was studied using two different laboratory equipments. In the first one, three ultrafiltration (UF) membranes were tested, with molecular weight cut‐off (MWCO) 100 kDa and 30 kDa, and two operating modes were used: total recycling of permeate and retentate streams, and in continuous mode, without recycling both streams. In the total recycling UF experiments, the influence of the operating variables on the permeate flux was first established. The effectiveness of the different membranes was determined by evaluating the rejection coefficients for several parameters that measure the global pollutant content of the effluent. The values found for these rejection coefficients were in the following order: ellagic acid and color > absorbance at 254 nm > tannic content > COD (chemical oxygen demand). In the continuous mode experiments, the fouling mechanism for each membrane was established by fitting the experimental data to various filtration fouling models given in the literature. The operating mode in the second equipment was batch concentration, and additional experiments were carried out with an UF membrane (2 kDa), and with a NF membrane (with MWCO in the range 150–300 Da). CONCLUSIONS: The three operating modes tested provided different rejection levels of organic matter; among them, the most effective procedure tested was batch concentration mode using a NF membrane. Copyright © 2007 Society of Chemical Industry     

Solving the small sample size problem in face recognition using generalized discriminant analysis

The goal of face recognition is to distinguish persons via their facial images. Each person's images form a cluster, and a new image is recognized by assigning it to the correct cluster. Since the images are very high-dimensional, it is necessary to reduce their dimension. Linear discriminant analysis (LDA) has been shown to be effective at dimension reduction while preserving the cluster structure of the data. It is classically defined as an optimization problem involving covariance matrices that represent the scatter within and between clusters. The requirement that one of these matrices be nonsingular restricts its application to datasets in which the dimension of the data does not exceed the sample size. For face recognition, however, the dimension typically exceeds the number of images in the database, resulting in what is referred to as the small sample size problem. Recently, the applicability of LDA has been extended by using the generalized singular value decomposition (GSVD) to circumvent the nonsingularity requirement, thus making LDA directly applicable to face recognition data. Our experiments confirm that LDA/GSVD solves the small sample size problem very effectively as compared with other current methods.     

High training set size reduction by space partitioning and prototype abstraction

Instance-based learning methods like the nearest neighbour classifier generally suffer from the indiscriminate storage of all training instances, resulting in large memory requirements and slow execution speed. In this paper, new training set size reduction methods based on prototype generation and space partitioning are proposed. Experimental results show that the new algorithms achieve a very high reduction rate with still an important classification accuracy.     

钛精矿回转窑直接还原过程结圈可能性的探讨

通过煤种，入窑球冷态强度和还原过程强度，以及钛精矿与煤灰混合物的软化温度等分析探讨了钛精矿预热球团回转窑直接还原产生结圈的可能性，获得了可以避免结圈的结论。     

A Theoretical Framework for Core Material Properties Identification in Cellular Solids using Novelty Detection

Abstract:  This paper presents a novelty detection-based technique to identify core material properties of honeycombs and cellular structures. A numerical model (finite element) representing full scale and/or reduced size of the cellular solid is used to generate transmissibilities between topological homologous points at cells in different locations. In order to make the procedure robust against noise, these transmissibilities are artificially corrupted. This step is representative of a series of experimentally obtained measurements which automatically return information relating to the size and shape of data noise along with the mean measurement. The next stage, both in this paper and in the proposal for the experimental approach, is to generate several further sets of transmissibilities from the finite element model; the only difference being that the core material properties are altered from the original values. A novelty detection framework is then adopted to find a similarity measure between each of these 'test' transmissibilities and the original set thereby identifying the material properties. Although this work is concerned with identifying only one material property, the methodology extends to identifying several properties.