战役战术导弹目标价值排序的模糊综合评判法

针对现代战争中战役战术导弹运用的特点，确定了战役战术导弹所打击目标价值的评判指标体系，并从分析目标价值的角度出发，用模糊综合评判法对战役战术导弹所打击目标进行价值分析，建立了打击先后顺序的评判模型．最后，用实例证明了，评判模型对战役战术导弹所打击目标进行价值排序的实用性和可行性。     

OCT-M 汽油选择加氢工艺工业应用

介绍了OCT-M汽油选择性加氢技术在汽油加氢装置的应用情况。对影响加氢汽油质量的主要因素进行了分析，提出了降低加氢过程汽油辛烷值损失、降低大分子硫醇生成的优化措施，并针对存在的问题提出了相应的改进建议。     

论包装的功能价值与商品附加值

文中从包装与包装的功能价值、商品附加值及其开发、包装与商品附加值等方面进行了论述。     

我国有线电视的网络媒体价值

阐述有线电视网络媒体的特点，有线电视网络媒体面临的困境及解决办法，最后展望有线电视网络媒体价值。     

渤中28－1（BZ28－1）油田N6H水平井动态分析

本文以渤中２８－１（ＢＺ２８－１）油田Ｎ６Ｈ水平井为例，从多方面对该井的动态和产能变化进行了系统分析，所用的方法对水平井动态分析有一定的指导意义。     

液态挤压在铝合金减震筒上的应用：液态挤压比压值对制件性能影响的分析

指出了压力铸造及热挤压工艺生产铝合金减震筒的缺点，阐述了液态挤压的特征，介绍了液态挤压在减震筒上的应用，分析了比压值对制件性能的影响。     

氨合成塔出口氨含量偏低原因分析及对策

阐述UHDE合成塔运行现状 ,分析氨净值达不到设计值的原因 ,提出相应的解决措施     

用分步沉积法去除Nb(OH)5/Ta(OH)5中Ti,Sb等金属杂质的工艺研究

从理论和实践应用方面，研究了在不同活性金属离子存在的条件下控制pH值，应用分步沉积的方法去除Nb(OH)5/Ta(OH)5中某些金属杂质。在一定温度下，可在不影响Nb(OH)5/Ta(OH)5沉积的条件下，达到有效去除Ti，Sb，Sn，Al，Fe等杂质元素的目的。     

关于正整数的k次根的整部

对于给定的自然数m，令口α（m)为m的是的次根的整部。即：α(m)=[m^1/k]。研究了α(m)的渐近性质，并给出了一个有趣的渐近公式。     

Application of the blind source separation method to feature extraction of machine sound signals

As the result of vibration emission in air, a machine sound signal carries important information about the working condition of machinery. But in practice, the sound signal is typically received with a very low signal-to-noise ratio. To obtain features of the original sound signal, uncorrelated sound signals must be removed and the wavelet coefficients related to fault condition must be retrieved. In this paper, the blind source separation technique is used to recover the wavelet coefficients of a monitored source from complex observed signals. Since in the proposed blind source separation (BSS) algorithms it is generally assumed that the number of sources is known, the Gerschgorin disk estimator method is introduced to determine the number of sound sources before applying the BSS method. This method can estimate the number of sound sources under non-Gaussian and non-white noise conditions. Then, the partial singular value analysis method is used to select these significant observations for BSS analysis. This method ensures that signals are separated with the smallest distortion. Afterwards, the time-frequency separation algorithm, converted to a suitable BSS algorithm for the separation of a non-stationary signal, is introduced. The transfer channel between observations and sources and the wavelet coefficients of the source signals can be blindly identified via this algorithm. The reconstructed wavelet coefficients can be used for diagnosis. Finally, the separation results obtained from the observed signals recorded in a semi-anechoic chamber demonstrate the effectiveness of the presented methods .