珊溪水力发电厂220kV开关站防误系统改造

通过对珊溪水力发电厂220 kV开关站的"五防"系统的现状分析,提出对"五防"系统全面的改造方案。微机"五防"装置凭借技术先进、功能齐全、运行可靠、维护方便等优点,成为目前电厂的首选配置。图3幅,表1个。     

石头口门水库洪水调度系统效益分析

石头口门水库洪水调度系统提高了洪水预报精度,增强了水库的安全性,提高了水库的综合效益。通过定性分析和定量计算,分析了石头口门水库洪水调度系统所创造的防洪效益、兴利效益用及社会效益。并根据水库工程现状,提出如何最大限度的发挥石头口门洪水调度系统的综合效益。     

网络攻击的防范策略

近年来计算机网络受到攻击及瘫痪的现象频频发生,给企业和社会造成极大的经济损失,在社会上影响极坏。因此,除了传统的预防方法之外,为改变这种被动受攻击的局面,本文对网络攻击的防范策略进行了探讨。     

基于单片机的地震仪器采集站控制优化

地震仪器是一种重要的油气勘探设备。在地震仪器中,由电源站为采集站提供电能,采集站的控制方案影响电源站的带道数量。为了提高电源站的带道数量,减少勘探成本,本文根据对地震仪器供电模型的分析,针对采集站启动状态对电源站带道数量的影响,提出了一套采集站单片机控制的优化方案,并进行了实验验证。实验结果表明,在55米道距时,电源站带道数量可提高至40道,优化方案切实、有效。     

基于变异的紧凑遗传算法

紧凑遗传算法(CGA)具有存储成本低的优点,但是其容易出现早熟。该文提出一种基于变异的紧凑遗传算法(MBCGA)。MBCGA在CGA的基础上,引进变异算子,完整地体现生态进化中的选择、遗传和变异,提高了局部寻优以及算法克服早熟的能力。试验结果表明,MBCGA保留存储成本低的优点,具有较快的收敛速度。变异算子的局部寻优作用明显。     

软PLC控制系统实现

以Visual C 6.0作为开发工具,介绍了软PLC控制系统的软、硬件结构,详细叙述了其具体实施方案,并给出实际运用,验证了它的正确性.     

不同功能单体对分子印迹聚合物识别性能的模拟

以槲皮素为模板分子,以甲基丙烯酸(MAA)、三氟甲基丙烯酸(TFMAA)、丙烯酰胺(AM)、N-乙烯基吡咯烷酮(NVP)、2-乙烯基吡啶(2-VP)、4-乙烯基吡啶(4-VP)六种物质分别作为功能单体,运用量子化学方法模拟模板分子与不同功能单体的分子印迹聚合物预组装体系的构型、能量及复合反应的结合能△E,以讨论不同功能单体对分子印迹聚合物识别性能的影响,结果4-VP的印迹效应最好.通过模拟,有助于解释实验现象以及选择印迹效应更好的功能单体.     

Improved Results on Passivity Analysis of Uncertain Neural Networks with Time-Varying Discrete and Distributed Delays

In this paper, the passivity analysis problem is investigated for uncertain neural networks with time-varying discrete and distributed delays. Based on direct delay decomposition idea and free-weighting matrix approach, several new delay-dependent passive criterions are derived in terms of linear matrix inequalities (LMIs), which can be easily checked by the Matlab LMI toolbox. Numerical examples show that the obtained results improve some existing ones.     

A DR algorithm based on artificial potential field method

Considering player entity’s motion regularity into DR (Dead Reckoning) algorithm can improve its prediction accuracy in MMOG (Massively Multiplayer Online Games), a novel DR algorithm was proposed to solve this problem in this paper. First the artificial potential field model of player entities is created, and then the acceleration of player entities is weighted with the acceleration produced by the potential field force and the acceleration reckoned by the traditional DR algorithm. In order to calculate the weight, Q-Learning algorithm is used. The experiments show that the method can improve prediction accuracy and reduce the network traffic.     

Boosting Piezo-Catalytic Activity of KNN-Based Materials with Phase Boundary and Defect Engineering

Although the piezo-catalysis is promising for the environmental remediation and biomedicine, the piezo-catalytic properties of various piezoelectric materials are limited by low carrier concentrations and mobility, and rapid electron-hole pair recombination, and reported regulating strategies are quite complex and difficult. Herein, a new and simple strategy, integrating phase boundary engineering and defect engineering, to boost the piezo-catalytic activity of potassium sodium niobate ((K, Na)NbO₃, KNN) based materials is innovatively proposed. Tur strategy is validated by exampling 0.96(K_0.48Na_0.52)Nb_0.955Sb_0.045O₃-0.04(Bi_xNa_4-3x)_0.5ZrO₃-0.3%Fe₂O₃ material having phase boundary engineering and conducted the defect engineering via the high-energy sand-grinding. A high reaction rate constant k of 92.49 × 10⁻³ min⁻¹ in the sand-grinding sample is obtained, which is 2.40 times than that of non-sand-grinding one and superior to those of other representative lead-free perovskite piezoelectric materials. Meanwhile, the sand-grinding sample has remarkable bactericidal properties against Escherichia coli and Staphylococcus aureus. Superior piezo-catalytic activities originate from the enhanced electron-hole pair separation and the increased carrier concentration. This study provides a novel method for improving the piezo-catalytic activities of lead-free piezoelectric materials and holds great promise for harnessing natural energy and disease treatment.