Measurement selection for parametric IC fault diagnosis

This article presents experimental results which show feedforward neural networks are well-suited for analog IC fault diagnosis. Boundary band data (BBD) measurement selection is used to reduce the computational overhead of the FFN training phase. We compare the diagnostic accuracy between traditional statistical classifiers and feedforward neural networks trained with various measurement selection criteria. The feedforward networks consistently perform as well as or better than the other classifiers in term of accuracy. Training using BBD consistently reduces the FFN training efforts without degrading the performance. Experimental results suggest that feedforward networks provide a cost efficient method for IC fault diagnosis in a large scale production testing environment.This work is supported by NSF-IUC CDADIC, Project 90-1.     

Manipulating Deformable Linear Objects: Fuzzy-Based Active Vibration Damping Skill

Human can handle a deformable object and damp its vibration with recognized skill. However, for an industrial robot, handling a deformable object with acute vibration is often a difficult task. This paper addresses the problem of active damping skill for handling deformable linear objects (DLOs) by using a strategy inspired from human manipulation skills. The strategy is illustrated by several rules, which are explained by a fuzzy and a P controller. A proportional-integral-derivative (PID) controller is also employed to explain the rules as a comparison. The interpretations from controllers are translated into high level commands in a robotic language V+. A standard industrial robot with a force/torque sensor mounted on the wrist was employed to demonstrate the skill. Experimental results showed the fuzzy based damping skill is quite effective and stable even without any previous acknowledge of the deformable linear objects.Category (5)     

参数强迫激励下非线性振子尖点型奇点的分叉

本文首先研究了不具有Z_2—对称性时的规范形理论和退化向量场的普适开折理论。然后利用这些理论研究了参数激励与强迫激励联合作用下非线性振动系统的尖点型奇点的余维2退化分叉。     

用介孔材料制备定向碳纳米管的研究进展

综述了近年来采用介孔材料制备定向碳纳米管的研究进展,包括介孔材料的合成及介孔材料在制备定向碳纳米管方面的应用。重点介绍了采用合成介孔材料的模板剂石墨化及介孔材料作为载体制备定向碳纳米管的方法,探讨了模板剂种类、催化剂的制备方法及反应温度和时间对定向碳纳米管生长的影响和定向碳纳米管生长的介孔限制机理,并提出了这一领域的研究方向。     

用参数泵分步结晶制取精萘的新工艺及放大

采用参数泵分步结晶工艺，开发了直立弹状流气泡管结晶器，由工业萘提纯制取精萘。实验室研究和放大试验的研究表明，产品纯度大于９９％，收率大于９２．５％。弹状气泡强化了传热和传质过程，流体的均布是放大过程的关键。     

助模板剂对MCM—41分子筛孔结构和性能的影响

在硅酸钠－硫酸铝－十六烷基三甲基氯化铵－水体系中，加入不同类型，如正庚烷、三甲基苯和十二胺的有机助模板剂（简称助剂）进行ＭＣＭ－４１分子筛的合成试验，并用ＸＲＤ、ＩＲ及Ｎ２吸附等方法考察了助剂对ＭＣＭ－４１分子筛孔径、热稳定性及酸性的影响。结果表明，十二胺助剂对ＭＣＭ－４１分子筛的孔径影响最大，但热稳定性较差，相比之下，三甲基苯助剂合成的ＭＣＭ－４１分子筛具有孔径大、热稳定性好和酸性特征较好的特点。     

天然高分子吸附剂研究Ⅱ．镍离子模板壳聚糖树脂的合成及特性

以镍离子为模板剂，合成了乙醇双环氧丙基醚交联的壳聚糖树脂，研究了其对Ｃｕ（Ⅱ）、Ｎｉ（Ⅱ）、Ｃｏ（Ⅱ）离子的吸附性能。结果表明，该法合成的树脂对Ｎｉ（Ⅱ）离子具有较强的“记忆”和“识别”能力，其对Ｃｕ（Ⅱ）、Ｎｉ（Ⅱ）、Ｃｏ（Ⅱ）的吸附量分别达２．２１、２．１３、１．４０ｍｍｏｌ／ｇ树脂。     

Nonlinear parametric identification based on the criterion of minimum probability of estimation error

The importance of studies of alternative (as compared to traditional) methods of nonlinear stochastic parametric identification is demonstrated. Synthesis of a procedure of identification of the parameter, “discrete observer,” with the use of the criterion, “minimum probability of estimation error,” is proposed for the first time. A model example that demonstrates the efficiency of the proposed approach is considered.     

基于色度分析的唇动特征提取与识别

本文提出了一种基于色度滤波的唇动特征提取与识别方法 ,它通过唇的色度滤波 ,得到增强的唇动图像 ,再利用可变模板 ,描述口型轮廓并提取特征参数 ,并用HMM模型进行唇运动序列图像识别 .该方法鲁棒性强 ,对光照没有苛刻的要求 ,且针对非特定人 ,适用于自然条件下的实用环境 ,解决了可变模板对目标边缘有较高分辨率的要求 ,使方法更实用化 .本文的实验是基于单纯的视觉信息 (没有声音信道的信息 )的唇动识别 ,不加语音信息 ,实验集合只限于单韵母 ,识别率可达 95 8% .     

Isometric Piecewise Polynomial Curves

The main preoccupations of research in computer-aided geometric design have been on shape-specification techniques for polynomial curves and surfaces, and on the continuity between segments or patches. When modelling with such techniques, curves and surfaces can be compressed or expanded arbitrarily. There has been relatively little work on interacting with direct spatial properties of curves and surfaces, such as their arc length or surface area. As a first step, we derive families of parametric piecewise polynomial curves that satisfy various positional and tangential constraints together with arc-length constraints. We call these curves isometric curves. A space curve is defined as a sequence of polynomial curve segments, each of which is defined by the familiar Hermite or Bézier constraints for cubic polynomials; as well, each segment is constrained to have a specified arc length. We demonstrate that this class of curves is attractive and stable. We also describe the numerical techniques used that are sufficient for achieving real time interaction with these curves on low-end workstations.