铯原子激光共振电离

用Ｎｄ：ＹＡＧ及其泵浦的染料激光进行铯原子三步共振电离。求解了非饱和共振过程速率方程，计算出基态和激发态共振吸收截面，给出电离效率分别与激发电离速率以及作用时间的变化关系，得到饱和激发电离的流量条件和通量条件。     

液体低温热导率的测试

介绍了非稳态法测试液体在低温下（－１００～５０℃）的热导率的测试原理、方法，测试了全氟三乙胺的低温热导率。为了提高测试的重复性，采用了相对比较法，并给出了测试装置及测试结果和误差分析。     

乙烯基三甲基硅烷等离子体聚合反应历程

应用色谱—质谱(GC-MS)及裂解色谱-质谱(PGC-MS)测定了乙烯基三甲基硅烷等离子体聚合反应中的气体冷凝物及聚合物,研究推导了等离子体聚合反应历程。单体在气相中被电子撞击,然后扩散到基底,在基底发生链增长和链终止反应。     

FEATURE SOLID MODELING TOOL SYSTEM:FSMTS

In conformity with the principle of Design for Manufacture,feature-based design strate-(?)es have been developed.As the“feature”is relevant to the“macro process plan”and“macro NCprograms”,obviously,“feature”is beyond the power of conventional solid modellers.Neverthe-less,substantial breakthrough has not been made in the solid modeling field,except“feature at-taching”or“feature recognizing”methods have been taken on.In this paper,the theory,concepts,system architecture,and algorithm principles of solid modeling tool system have beenrepresented.The practice of Feature Solid Modeling Tool System (FSMTS) developed atHuazhong University has proved that the tool may be a new foundation of Feature-Based Design.     

尿素熔融喷浆造粒工艺在复合肥生产过程中存在的问题及对策

介绍在团粒法工艺的基础上，将尿素熔融成尿液进行喷浆造粒生产复合肥的过程中，存在的问题，原因及解决的对策。     

叠后地震剖面的线性化波阻抗反演

本文提出了由井旁道出发逐道进行的叠后地震剖面的线性化波阻抗反演方法。每一道反演采用逐次线性化对波阻抗进行修正，反演的纵向分辨率为一个采样时间间隔，并以合成记录道与实际地震道的相似系数作为迭代收敛准则，已处理的地震道波阻抗作为下一道反演初始值。实际资料处理表明，该方法具有较高的分辨率和运算速度快的优点。     

挖掘机工作装置实验样本长度确定方法及程序系统

本文通过对某液压挖掘机工作装置实验样本长度的研究,详细讨论了样本长度的确定方法,重点分析了趋势曲线拟合法,提出了样本长度精度区间分析的方法,并在处理大量实验数据的基础上,从载荷分布及寿命估算的角度做了实际的验证.编制了应用程序,使样本长度确定至寿命估算整个过程程序化.     

ZG3Cr13钢经长期时效后组织及硬度的研究

研究了ZG3Cr13钢在550℃～600℃的工作温度区间经2500h长期时效后的硬度及组织的变化。结果表明，在时效1000h内，硬度有明显的下降，之后趋于稳定；组织变化与正常处理后的组织均匀化程度有关，原始组织越均匀组织稳定性和热强性越高。     

Measurement-based network monitoring and inference: scalability andmissing information

Using measurements collected at network monitors to infer network conditions is a promising approach for network-centric monitoring. In this context, an important question arises: given the number and locations of network monitors, how much network management resources (e.g., the number of measurements) are needed to obtain an accurate estimate of network states? We define the scalability of measurement-based network monitoring as the growth rate of the number of measurements required for accurate network monitoring/inference with respect to the size of a network. We develop a framework for investigating the scalability in the context of multicast inference with the monitors at the edges of a network. In such a framework, network monitoring/inference can be formulated as probability density estimation of network states. The growth rate is characterized through the sample complexity, which is the number of measurements needed to accurately estimate the density. The missing data framework is introduced to estimate the growth rate, where the missing data reflect unavailable measurements at the unobservable nodes without resident monitors, and the underlying nodal packet losses. We show that when the missing information is mainly due to the number of unobservable nodes, the number of measurements needed grows linearly with the size of the network, and the measurement-based inference approach is, thus, scalable. When the missing information is mainly due to the underlying nodal packet losses, the number of measurements needed grows faster than linear with the size of the network, and the measurement-based inference approach is, thus, not scalable. Our results provide guidelines for accessing feasibility of the measurement-based inference approach, and the number of probes required. We give numerical examples to illustrate some of our results