RFID标签用缝隙天线分析与设计

分析了缝隙弯折次数、高度、位置、宽度和缝隙平片大小对缝隙天线谐振特性的影响.仿真结果显示,缝隙的弯折次数和高度对其谐振频率影响显著.最后,提出了一款UHF射频识别标签用的缝隙天线,制作了相应的实物天线.仿真与测试结果说明所设计的天线基本满足RFID标签应用要求.     

色噪声环境下系统记忆性对分数阶布朗马达合作输运特性的影响

本文引入分数阶微积运算,建立色噪声环境下分数阶布朗马达在闪烁棘齿势中的合作输运模型,通过数值模拟讨论分析了系统记忆性对合作定向输运性质的影响.本文的研究表明,系统记忆性可通过分数阶阶数和色噪声关联时间描述,且分数阶对输运特性的影响远大于色噪声;改变系统阶数不仅可影响粒子链定向输运速度的大小,还可改变其运动方向,使系统出现与整数阶方向相反的定向流,且出现振荡与广义随机共振现象;色噪声关联时间改变输运速度的大小,但不改变定向流的方向.     

陕北柠条的光合特性

用Licor-6400便携式光合作用测定系统测定了陕北吴旗县柠条在年生长季内叶片净光合速率随光照度和CO2浓度的变化规律,并测定了柠条叶片的蒸腾速率(Tr)和水分利用率(WUE)随光照度的变化规律.结果表明:在年生长季内,柠条叶片光补偿点(LCP)的变动范围为37.4～70.92 μmol/(m2·s),光饱和点(LSP)为1 324.07～1 626.04 μmol/(m2·s),表观光量子效率(φ)为0.008 99～0.014 76 μmol/mol;柠条叶片的CO2补偿点(CCP)为56.76～126.80 μmol/mol,CO2饱和点(CSP)为1 154.60～1 828.86 μmol/mol.说明柠条为C3植物,不耐荫,应栽植在阳光充足的地方.柠条在年生长季内蒸腾速率(Tr)的大小排序为:Tr9月＞Tr8月＞Tr6月＞Tr7月＞Tr5月;水分利用率(WUE)高低排序为:WUE5月＞WUE7月＞WUE8月＞WUE6月＞WUE9月.     

急倾斜煤层煤岩变形局部化特征现场监测

急倾斜煤层开挖扰动区煤体动态变形具有明显局部化特征,易诱致动力学破坏。以大洪沟矿巷道动压防治为目标,通过煤岩局部化变形指标分析,室内测试、现场光学观测和表面变形监测等方法,定量分析了动压巷道两帮和顶板不同深度的侧向与垂直变形及演化特征。结果表明:巷道局部化变形差异性显著,在两巷交汇区域,B3巷道最大侧向变形达0.5 m,顶板最大垂直变形达0.6 m.确定动压破坏严重区域范围为15.0～20.0 m.这为现场灾害预测和调控提供判据。     

急斜煤层水平分段综放开采围岩失稳特征分析

针对急斜煤层水平分段综放开采围岩失稳特征,通过对围岩力学模型分析,研究围岩结构的失稳过程和演化途径.根据急斜煤层围岩的非对称分布特点,所产生的非对称作用极易使围岩发生局部变形.局部变形的不断扩展进而将导致围岩发生失稳,这种动力学失稳极易演化为灾害.为了控制这种灾害的发生,借助声发射和钻孔窥视实时监测围岩"损伤-破裂-失稳"的全过程,将为工作面开采扰动区围岩失稳与控制提供了值得借鉴的依据.     

铝电解TiB2/C复合阴极用煤沥青的无机改性

采用无机粒子改性法在200℃下对煤沥青进行改性,分析无机粒子(Al2O3粒子或TiB2粒子)对改性煤沥青结构与性能以及改性沥青基TiB2/C复合阴极性能的影响。研究结果表明:改性煤沥青的结焦值和软化点比未改性煤沥青均有较大提高。无机粒子的添加进一步提高改性煤沥青的结焦能力,但降低改性煤沥青的软化点,与对比改性煤沥青相比,Al2O3粒子和TiB2粒子改性煤沥青的软化点分别降低4.5℃和2.0℃,结焦值分别提高4.85%和5.35%。经过1 000℃炭化,其残炭率相对于对比试样分别增加3.01%和5.87%。与对比复合阴极相比,Al2O3粒子和TiB2粒子改性煤沥青基复合阴极的密度分别增大0.45%和1.79%,开孔率分别降低5.08%和5.78%,电阻率从52.93μΩ·m分别降低到48.86μΩ·m和49.95μΩ·m,抗压强度从24.21 MPa分别增加到28.78 MPa和28.06 MPa,电解膨胀率分别降低0.10%和0.16%。无机改性粒子均匀地分布于粘结剂煤沥青炭中。     

自由曲面数字化的自适应规划

针对数学模型已知的自由曲面,依据质心定理推导出基于形状的采样算法,提出在给定采样精度下的自适应采样方法;针对数学模型未知的自由曲面,引入平面数字化曲线有界性概念,建立测量参数与采样步长的内在联系,提出了基于曲率和曲面切线斜率的自适应规划方法．计算机仿真结果表明,所提出的规划方法可显著提高数字化采样效率．     

考虑悬架几何特性及作动器延时的整车模糊控制

利用ADAMS软件建立了整车悬架及转向机械模型,考虑了悬架的几,阿特性,结合变论城模糊控制方法,设计了主动悬架变论域模糊控制器,同时考虑了作动器的延时特性,通过matlab/simulink联合仿真,并与被动悬架模型进行了对比,得出所设计的模糊控制器对汽车的平顺性有较大改善.     

Interval Time Series Analysis with an Application to the Sterling-Dollar Exchange Rate

Traditional econometrics has long employed ＂points＂ to measure time series data. In real life situations, however, it suffers the loss of volatility information, since many variables are bounded by intervals in a given period. To address this issue, this paper provides a new methodology for interval time series analysis. The concept of ＂interval stochastic process＂ is formally defined as a counterpart of ＂stochastic process＂ in point-based econometrics. The authors introduce the concepts of interval stationarity, interval statistics （including interval mean, interval variance, etc.） and propose an interval linear model to investigate the dynamic relationships between interval processes. A new interval-based optimization approach for estimation is proposed, and corresponding evaluation criteria are derived. To demonstrate that the new interval method provides valid results, an empirical example on the sterling-dollar exchange rate is presented.     

Designing a Hybrid Intelligent Mining System for Credit Risk Evaluation

In this study, a novel hybrid intelligent mining system integrating rough sets theory and support vector machines is developed to extract efficiently association rules from original information table for credit risk evaluation and analysis. In the proposed hybrid intelligent system, support vector machines are used as a tool to extract typical features and filter its noise, which are different from the previous studies where rough sets were only used as a preprocessor for support vector machines. Such an approach could reduce the information table and generate the final knowledge from the reduced information table by rough sets. Therefore, the proposed hybrid intelligent system overcomes the difficulty of extracting rules from a trained support vector machine classifier and possesses the robustness which is lacking for rough-set-based approaches. In addition, the effectiveness of the proposed hybrid intelligent system is illustrated with two real-world credit datasets.