Second harmonic generation from a ferroelectric film

We derive an expression for transmittivity (T_SHG) of second harmonic generation (SHG) signals from a ferroelectric (FE) film. Intensities of up and down fields in the medium are investigated in relation to T_SHG. The derivations are made based on undepletion of input fields and nonlinear wave equation derived from the Maxwell equations. We present two cases: film without mirrors and with partial mirrors. Expressions for the newly derived nonlinear susceptibility coefficients of SHG for real crystal symmetry [J. Opt. Soc. Am. B 19 (2002) 2007] are used to get more realistic results. Variations in T_SHG with respect to film thickness are illustrated.     

A dual-mode bandpass filter with enhanced capacitive perturbation

A dual-mode ring bandpass filter with two pairs of capacitors has been designed. The capacitors are used to control the location of the even- and odd-mode frequencies independently, allowing weak coupling for narrow-band filter design with realizable capacitance values. Theoretical expressions have been derived for these frequencies. A 4% bandwidth bandpass filter centered at 1.9 GHz was designed and tested with good agreement between theoretical and measured results.     

An intelligent web-page classifier with fair feature-subset selection

The explosion of on-line information has given rise to many manually constructed topic hierarchies (such as Yahoo!!). But with the current growth rate in the amount of information, manual classification in topic hierarchies results in an immense information bottleneck. Therefore, developing an automatic classifier is an urgent need. However, classifiers suffer from enormous dimensionality, since the dimensionality is determined by the number of distinct keywords in a document corpus. More seriously, most classifiers are either working slowly or they are constructed subjectively without any learning ability. In this paper, we address these problems with a fair feature-subset selection (FFSS) algorithm and an adaptive fuzzy learning network (AFLN) for classification. The FFSS algorithm is used to reduce the enormous dimensionality. It not only gives fair treatment to each category but also has ability to identify useful features, including both positive and negative features. On the other hand, the AFLN provides extremely fast learning ability to model the uncertain behavior for classification so as to correct the fuzzy matrix automatically. Experimental results show that both FFSS algorithm and the AFLN lead to a significant improvement in document classification, compared to alternative approaches.     

大规模定制环境下 ERP 的发展

ERP─EnterpriseResourcePlanning企业资源计划系统 ,是指建立在信息技术基础上 ,以系统化的管理思想 ,为现代企业决策层及员工提供决策运行手段的管理平台。从竞争环境的角度出发 ,提出了大规模定制已经逐渐成熟并最终取代大规模生产成为新的生产经营模式的观点 ,同时 ,分析了在大规模定制下传统ERP的局限 ,从管理和技术的角度探讨新一代ERP的特点及发展。     

炼油厂成品油罐区调度优化问题研究

研究了以集合论为基础的调度优化模型。给出了该离散型优化问题的求解算法。根据优化结果，在G2实时智能平台上开发了包含监视子系统和调度子系统的调度支持系统。在中国石化股份有限公司长岭分公司的试用结果表明，该调度系统可以提高炼油厂的生产效率，从而提高炼油厂的经济效益。     

Numerical Study of Finite Element Method Based Solutions for Propagation of Wetting Fronts in Unsaturated Soil

The accurate prediction of the propagation of a wetting front in an unsaturated soil subjected to surficial infiltration is of practical importance to many geotechnical and geoenvironmental problems. The finite element method is the most common solution technique as the hydraulic soil properties are highly nonlinear. Two important issues are often found to create difficulties in such analyses. First, numerical oscillations are usually observed in the calculated pore pressures at the wetting front. Second, when a reasonable mesh size and time step are used, the elevation of the wetting front may be seriously overpredicted. This paper is focused on the second issue. The under-relaxation (UR) technique used in the iterative process within each time step is found to have a serious impact on rate of convergence with refinement in mesh size and time step. Two different techniques are typically used; the first evaluates the hydraulic conductivity using an average of heads calculated from the preceding time node and the most recent iteration of the current time node (UR1), and the second evaluates the hydraulic conductivity using the average of heads calculated from the two most recent iterations of the current time nodes (UR2). The study shows that UR1, which is adopted in programs such as SEEP/W, ensures that the solution converges rapidly to a stable solution within a time step, but may converge to the wrong wetting front at a given elapsed time unless a sufficiently refined mesh is used. UR2 converges much more slowly within a time step, but the error in the wetting front is smaller than that generated by UR1.     

2-乙基己酸的制备

研究了 2乙基己酸的制备 ,该反应是 2乙基己醇与氢氧化钠在催化剂存在下进行氧化、脱氢 ,生成产物2乙基己酸。通过实验找到了一种新型、高效、廉价的催化剂 ,以及最佳反应条件。通过对 2乙基己酸的分析测试 ,产品完全符合质量标准。     

A Neural Network Approach for Signal Detection in Digital Communications

In this paper, we propose a new approach for signal detection in wireless digital communications based on the neural network with transient chaos and time-varying gain (NNTCTG), and give a concrete model of the signal detector after appropriate transformations and mappings. It is well known that the problem of the maximum likelihood signal detection can be described as a complex optimization problem that has so many local optima that conventional Hopfield-type neural networks fail to solve. By refraining from the serious local optima problem of Hopfield-type neural networks, the NNTCTG makes use of the time-varying parameters of the recurrent neural network to control the evolving behavior of the network so that the network undergoes the transition from chaotic behavior to gradient convergence. It has richer and more flexible dynamics rather than conventional neural networks only with point attractors, so that it can be expected to have much ability to search for globally optimal or near-optimal solutions. After going through a transiently inverse-bifurcation process, the NNTCTG can approach the global optimum or the neighborhood of global optimum of our problem. Simulation experiments have been performed to show the effectiveness and validation of the proposed neural network based method for the signal detection in digital communications.     

任丘油田雾迷山油藏抽油机井系统效率初步探讨

总公司1996年对任丘雾迷山油藏抽油机井进行测试,系统效率高达51%~68%,其结果出乎意料。从影响抽油机系统效率的几大因素入手,分析出任丘雾迷山油藏抽油机井系统效率高的主要原因。任丘雾迷山油藏属裂缝性破酸盐岩油藏(即灰岩油战),由于其裂缝发育、渗透性好、油层厚度大、地层温度高、油气比小、饱和压力低等,使得抽油机井生产呈现如下特点:()大泵径,长冲程,低冲次大排量采油;(2)中浅京挂,小沉没度;(3)抽汲流体为液体单相,泵充满程度高;(4)部分井为连抽"带喷"状态,抽油系活塞底部受力大;(5)井液粘度低,油井不结蜡,摩阻损失小。由于这些特点以及近年来使用的新型节能抽油机,使得抽油机井系统效率大大高于其它油田抽油机井系统效率。