Use of a neural network to link AFM etch patterns to plasma parameters

Plasmas play a critical role in depositing thin films or etching fine patterns while manufacturing integrated circuits. A new model for plasma diagnosis is presented. This was accomplished by linking atomic force microscopy (AFM) to plasma parameters using a neural network. Experimental AFM data were collected during the etching of silicon oxynitride films in C₂F₆ inductively coupled plasma. Surface roughness of etched patterns was characterized by means of discrete wavelet transformation. This led to the construction of three vertical (type I), diagonal (type II), and horizontal (type III) wavelet coefficient-based models. The performance of diagnosis models was evaluated in terms of the prediction and recognition accuracies. Both accuracies were optimized as a function of the number of hidden neurons. Comparisons revealed that the type I model yielded the largest recognition and the smallest prediction error. This was demonstrated even under stricter monitoring conditions. More improved diagnosis is expected by enhancing AFM resolution.     

模糊数学在电视机故障诊断中的应用

本文介绍了应用模糊数学方法进行计算机辅助诊断电视机的故障原因,这种方法有效性在于建立模型的因果关系正确性和自动搜索范围及速度。     

Current basis for the ultrastructural clinical diagnosis of tumors: A review

The ultrastructural diagnosis of tumors requires a careful analysis that should be done in an orderly fashion. It requires precise planning from the time of specimen collection to the selection of the area to be examined. Pictures must be taken systematically and every micrograph should allow to answer whether the number of cells photographed is adequate; whether mitoses are present, what is the pattern of the tumor; what is the appearance of the cell membrane; whether the cells are joined by junctional complexes; whether free surfaces possess microvilli or cilia; what organelles are present and how they are distributed; whether there are secretory granules, melanosomes, or other cytoplasmic elements. Nuclear and nucleolar size and shape have to be taken into consideration. The composition of the interstitial extracellular matrix is important in certain types of tumors. Although these questions are not the only ones to be addressed, their use in a logical fashion is helpful when it concerns the ultrastructural diagnosis.     

输血后丙型肝炎病毒NS4区抗体的动态变化及其诊断意义

利用重组NS4抗原及合成肽5－11抗原分别检测5例输血后丙型肝炎患者的系列血清136份，并与HCV总抗体及HCVRNA检测结果比较，发现抗NS4抗体的动态变化虽然有两种模式，但在多数情况下为一种模式，即抗体阳转后很少转阴，并且其动态变化基本与总抗体相似。同时发现2例病人抗NS4抗体阳转时间早于总抗体，因此，推测HCV检测试剂中增加NS4抗原可能对提高HCV诊断试剂的灵敏度有一定意义。     

一种汽车用液压电磁阀控制电路设计

液压电磁阀是现代汽车液压控制系统的重要部件,通过对电磁阀的精确驱动控制,全面的故障诊断,确保液压系统的安全可靠运行。本电路设计具有灵活性、安全性、可扩展性等特点,可以方便实现对不同类型、不同电气参数、不同数量的液压电磁阀的控制,对推动机电液一体化技术在汽车上的应用具有积极意义。     

Ellipsoidal neighbourhood outlier factor for distributed anomaly detection in resource constrained networks

Anomaly detection in resource constrained wireless networks is an important challenge for tasks such as intrusion detection, quality assurance and event monitoring applications. The challenge is to detect these interesting events or anomalies in a timely manner, while minimising energy consumption in the network. We propose a distributed anomaly detection architecture, which uses multiple hyperellipsoidal clusters to model the data at each sensor node, and identify global and local anomalies in the network. In particular, a novel anomaly scoring method is proposed to provide a score for each hyperellipsoidal model, based on how remote the ellipsoid is relative to their neighbours. We demonstrate using several synthetic and real datasets that our proposed scheme achieves a higher detection performance with a significant reduction in communication overhead in the network compared to centralised and existing schemes.     

2D12型往复式压缩机气阀故障诊断的时频分析方法

分析了 2D12型往复式压缩机气阀的工作过程 ,针对气阀工作特点提取吸气阀与排气阀均关闭时刻的压缩阶段的局域声音信号 ,应用广义双线性时频法诊断气阀故障 ,给出了正常气阀和故障气阀的时频分析图     

高分辨力地震是提高中国南方碳酸盐岩地震勘探效能的基础——一个由失败到成功的史例

南方碳酸盐岩复杂地区的地震工作经历了长期艰难曲折的道路,其中异常判别的经验教训极为深刻。本文从地震异常分析入手,揭示其实质,寻求问题的关键,探讨解决的办法,介绍高分辨率地震方法技术,展示高分辨率地震新成果,以得出有意义的结论和建议。