小径管焊缝射线照相标准的实践与问题研讨

通过分析小径管焊缝射线检验中存在问题，对X射线检测标准作了进一步探讨。     

不等厚板过渡削薄对接焊缝的超声波探伤

不等厚板经过渡削薄处理后的对接焊缝,由于厚度的不均匀,射线穿透时的衰减不一样,对射线检测带来很大的麻烦。常用的超声波探伤方法在定位和定级方面比较困难,本文给出利用现在先进的数字式超声波探伤仪进行准确探伤的方法。     

SOME PROPERTIES OF THE MAXIMUM LIKELIHOOD ESTIMATOR IN THE SIMULTANEOUS SWITCHING AUTOREGRESSIVE MODEL

Abstract. The simultaneous switching autoregressive (SSAR) model proposed by Kunitomo and Sato (A non-linearity in economic time series and disequilibrium econometric models. In Theory and Application of Mathematical Statistics (ed. A. Takemura). Tokyo:University of Tokyo Press (in Japanese), 1994; Asymmetry in economic time series and simultaneous switching autoregressive model. Struct. Change Econ. Dyn. , forthcoming (1994).) is a Markovian non-linear time series model. We investigate the finite sample as well as the asymptotic properties of the least squares estimator and the maximum likelihood (ML) estimator. Due to a specific simultaneity involved in the SSAR model, the least squares estimator is badly biased. However, the ML estimator under the assumption of Gaussian disturbances gives reasonable estimates.     

基于FPGA实现AES的侧信道碰撞攻击

为了解决攻击点在能量迹中具体位置的识别问题,在对侧信道碰撞攻击技术研究的基础上,提出了通过计算能量迹中每个采样点的方差来识别攻击点的方差检查技术。并利用基于相关系数的碰撞检测方法,对一种AES的FPGA实现实施了攻击。实验结果表明,方差检查技术可以有效地识别攻击点在能量迹中的具体位置。     

出口磷铁的检验方法研究

介绍我省出口磷铁所采用的精确、快速的检验方法及其分析研究。     

Decision support in machine vision system for monitoring of TFT-LCD glass substrates manufacturing

This study addresses classification methodology for the automatic inspection of a range of defects on the surface of glass substrates in thin film transistor liquid crystal display glass substrate manufacturing. The proposed methodology consisted of four stages: (1) feature extraction by calculating the wavelet co-occurrence signature from the substrate images, (2) handling of imbalanced dataset using the Synthetic Minority Over-sampling TEchnique (SMOTE), (3) reduction of the feature's dimension by principal component analysis, and (4) finally choosing the best classifier between three different methods: Classification And Regression Tree (CART), Multi-Layer Perceptron (MLP) and Support Vector Machine (SVM). In training the SVM and MLP classifiers, the simulated annealing algorithm was used to obtain the optimal tuning parameters for the classifiers. From the industrial case study, the proposed feature extraction algorithm could remove the defect-irrelevant image features and SMOTE increased the accuracy of all three methods. Furthermore, the optimized SVM and MLP models were more accurate than the CART model whereas a higher accuracy of 89.5% was observed for the proposed SVM model.     

基于改进K-Means聚类的煤炭交易者信誉度划分

针对目前煤炭销售中存在的煤炭质量信息分散性与质量计价政策对其质量精确性要求的矛盾,提出了采用对初始聚类中心优化选取的K-Means聚类算法,对大型煤炭企业及其联盟客户煤炭质量检验数据进行系统分析和挖掘,获得双方质量检验行为统计规律,进行交易双方信誉度等级划分,将不确定性的质量指标转化为确定性的交易者质量检验行为评价。该研究一方面可为煤炭企业在发生交易者质量纠纷情况下合理划分质量检验责任提供参考,监督和指导矿井和客户的质检管理工作;另一方面可以为煤炭企业提供销售决策辅助支持。     

便携心电传感器的心房肥大诊断研究

基于便携式传感器的模式识别在心电(ECG)监护领域具有广泛的应用前景,并且在心律不齐、心肌梗塞、心室肥大等心电的识别算法上都已有大量的研究与应用,但在心房肥大诊断上却未有模式识别相关的研究成果。心房肥大病症的心电数据量不足给研究造成重大障碍,部分分类器无法适应小样本训练下的分类。针对小样本训练进行研究,对比了不同分类方法,显示了基于统计模式识别的支持向量机(SVM)应用于心房肥大的应用潜力。另外,由于不同个体的心房肥大心电存在差异,在实际应用环境中,SVM存在无法良好泛化的问题,存在类别错分的医学风险。针对类别错分情况,采用分类器融合的方法改进分类器,提出了在SVM分类器输出端增加了拒绝域的分类器(SVM-R)的方法。实验结果表明:SVMR有较高的分类准确率与诊断可信度。     

基于幂图的属性约简

针对粗糙集理论中基于差别矩阵的属性约简方法存在的不足,提出一种基于幂图的属性约简算法.首先通过修改样本决策属性值将不相容决策表转化为简化的相容决策表;然后将样本对概念与幂图概念相结合,将基于修正差别矩阵的不相容决策表的属性约简转化为幂图的搜索问题;最后通过实例和实验验证了所提出算法的有效性.