远程接入短信动态口令系统的阻塞攻击分析及其对策

动态口令是目前常用于替代静态口令的一种强身份鉴别技术,基于短信的动态口令又是动态口令系统中的一种低成本、易管理的实现模式。远程接入系统认证时常使用短信动态口令来加强对账号安全的保障,目前广泛使用的远程接入短信动态口令系统中,由于动态口令的触发产生机制简单无保护,易于形成阻塞攻击,论文详细分析了短信动态口令的触发机制,并提出一种改进方法,用于降低阻塞攻击对远程访问系统带来的风险。     

DSP Based Optimal Switching Pattern SVPWM Technique Study and Realization

This paper presents a DSP based optimal switching pattern SVPWM （Space vector pulse width modulation） technique. Under this switching mode, the inverter PWM period begins and ends with zero voltage vector, which can effectively avoid the voltage vector sharp change problem in the PWM period and inverter voltage sector. The optimal switching pattern SVPWM technique reduced the inverter switching depletion and smoothed vector change in the PWM period. The inverter output distortion was been reduced. To prove the equivalence of optimal switching pattern SVPWM and carrier-based PWM, the carrier-based PWM form and zero-sequence signal of the optimal switching pattern SVPWM has been deduced. Finally, experiment has been taken to prove those ideal analysed in this paper.     

Design and Development of New Digital Thermostat

The designed thermostat is based on the microcontroller featuring intelligence, programmable, environmental protection and power saving. The thermostat design is mainly composed of hardware and software design, the hardware includes the power supply circuit, temperature measurement circuit, humidity measurement circuit and backlight circuit; while the software design includes temperature measurement and compensation algorithm, moreover software flowchart is given as well. Finally the power supply circuit is simulated by the software of Pspice and the creative power stealing mode is verified by the simulation results. A target board is stuffed by hand with Pb-free electronic components and used to test hardware and debug software. Since the Pb-free components were used, power stealing mode is designed in hardware and temperature compensation algorithm is accomplished in software, and the thermostat is outstanding with its features of ＂green＂ and ＂power saving＂.     

氢脉泽中四极磁态选择器的设计及其应用

氢脉泽是一种中、长期稳定度最高的原子频率标准.其中原子磁态选择器的改进设计可以改善氢脉泽的工作参数及其体积与重量,从而改进氢脉泽的品质与工作寿命等,同时也可以改进氢脉泽的长期性能,并给出了磁态选择器的设计与实验结果.     

预警信息安全播出管理系统

用VB开发了一套预警信息安全播出管理系统,该系统第一时间向相关部门发布预警信息.让技术人员提前做好安全播出应急措施.通过该系统可以查询主要播出设备工作状态、接收信号质量.主要论述其功能特点、实现方案、系统组成、工作原理、硬件的配置及软件流程设计.     

含芳香基团的梳状聚合物型降凝剂与沥青质协同改善合成蜡油的流变性

采用流变学实验、 差示扫描量热(DSC)分析、 显微观察及沥青质沉淀实验研究了聚丙烯酸十八酯-马来酸酐(POM)、 聚丙烯酸十八酯-马来酸酐-苯胺(POMA)及聚丙烯酸十八酯-马来酸酐-萘胺(POMN)梳状聚合物对合成蜡油的流变性能的影响规律. 实验结果表明, 这3种梳状聚合物降凝剂均能在一定程度上改善不含沥青质合成蜡油(MO-1)的低温流变性, 其中POM对MO-1蜡油的流变性改善效果最佳. 添加500 mg/kg POM后, MO-1的凝点从29 ℃降至23 ℃, 屈服值从627.20 Pa降至83.35 Pa. 而POM, POMA和POMN可以显著改善含0.3%(质量分数)沥青质的合成蜡油(MO-2)的低温流变性, 且添加500 mg/kg POMA后MO-2蜡油的流变改善效果最佳: 凝点降至3 ℃, 屈服值降至1.27 Pa. 可见, 本文制备的梳状聚合物降凝剂均能与沥青质协同改善MO-2蜡油的流变性, 并且向POM中引入芳香基团能进一步促进沥青质与降凝剂分子的相互作用, 进而增强梳状聚合物降凝剂与沥青质的协同作用.     

稀有原人参二醇型皂苷的人肠道菌群生物转化

利用高分离度液相色谱-四极杆飞行时间质谱(RRLC-Q-TOF MS)和超高效液相色谱-三重四极杆质谱(UPLC-QQQ MS)定性定量分析了稀有原人参二醇型皂苷Rd, F₂, Rg₃, CK和Rh₂在离体人肠道菌群中的生物转化过程. 并将上述二醇型皂苷与人肠道菌群在体外厌氧, 37 ℃下共温孵育, 采用电喷雾质谱在负离子模式进行检测, 鉴定代谢产物, 监测其含量变化, 拟合代谢路径. 结果表明, 人参皂苷Rd主要被代谢为F₂, Rg₃, CK, Rh₂和PPD; 人参皂苷F₂主要被代谢为CK和PPD; 人参皂苷Rg₃主要被代谢为Rh₂和PPD; 人参皂苷CK和Rh₂主要被代谢为PPD. 在离体条件下, 人参皂苷Rd, F₂和Rg₃会被肠道菌群完全转化为其代谢产物, 而人参皂苷CK和Rh₂则不能被肠道菌群完全转化为其代谢产物. 原人参二醇型皂苷在人肠道菌群中的主要转化为脱糖基反应, 单糖苷和苷元是稀有原人参二醇型皂苷在人体内发挥药效的物质基础.     

LaCoO3对H2S选择氧化性能的影响

使用溶胶-凝胶法制备了LaCoO₃催化剂,采用XRD、BET和XPS等方式对催化剂进行了表征,考察了该催化剂制备过程中煅烧温度、表面活性剂PEG-6000和PEG-20000含量对其H₂S选择氧化制硫磺反应催化活性的影响。结果表明,表面活性剂PEG-6000及PEG-20000的添加能明显提高LaCoO₃的催化活性。0.02 mol La（NO₃）₃+0.02mol Co（NO₃）₂溶液中添加0.30 g PEG-20000、煅烧温度为650℃时所制备的LaCoO₃催化活性最好;在最佳反应温度260℃下,H₂S的转化率达到96.10%,硫选择性为93.77%。     

油浆高温快速裂解过程的气固相产物研究

采用高频炉快速热解装置研究油浆的高温快速热解特性,考察了热解温度、氮气流量对气固相产物的组成和产率的影响。温度是影响气相产物产率的关键因素,气相产物主要为甲烷、氢气和乙烯,升高温度可提高甲烷和氢气的产率,而乙烯产率受高温下二次反应的影响在800℃到达最大值后逐渐降低,乙烷、丙烯产率较小且受二次反应的影响在700℃到达最大值后逐渐降低,温度高于800℃时会有少量乙炔生成且升温可提高乙炔产率。增加氮气流量可降低甲烷、氢气分压,缩短乙烯、丙烯等在高温区的停留时间,从而增加气相产物的产率。积炭产率随热解温度升高迅速增加,氮气流量的增加能够削弱二次反应从而降低积炭产率。     

Quantitative Analysis of Main Components of Natural Gas Based on Raman Spectroscopy

Natural gas is composed of methane, ethane, propane, carbon dioxide, nitrogen, hydrogen, carbon monoxide and unknown alkane components of C4 or more (denoted as C4⁺) after desulfurization and dehydration treatment. The concentrations of the first seven components account for more than 90% of natural gas. When analyzing the natural gas composition using Raman spectral analysis methods, a small amount of unknown alkane components C4⁺ will have a negative impact on the analytical precision. In this work, a novel method that consists of an automatic decomposition algorithm of Raman spectra and a model for quantitative analysis was developed for the analysis of components of natural gas. The Raman spectrum of a natural gas sample could be decomposed into the sum of the Raman spectra of pure constituents and several Lorentz peaks by a nonlinear least-square optimization algorithm based on a linear additivity of Raman spectra. The concentration of the unknown alkane component C4⁺ was determined according to the area of the C-H deformation vibration peak which was common for most alkane molecules. Some training samples were used to establish the model between Raman characteristic peak areas and corresponding concentrations for each component. Compared with the existing Raman analysis methods, the new method solved the problem of analyzing natural gas containing unknown alkane components with good stability and accuracy. The experiments showed that the maximum absolute errors of this algorithm for methane, ethane, propane, carbon dioxide, nitrogen, hydrogen, and carbon monoxide respectively reached 0.57%, 0.37%, 0.21%, 0.07%, 0.18%, 0.04%, 0.13%, and the correlation coefficient to gas chromatographic results also reached 0.997, 0.986, 0.991, 0.998, 0.993, 1.000, 0.995, 0.982, respectively.