基于腔衰减相移光谱法的二氧化氮分析仪的设计与应用

基于腔衰减相移光谱法设计了一套二氧化氮在线分析仪,通过优化测量参数,该仪器可长期稳定运行,其时间分辨率为60 s,检出限为0.191 ppb,在0~300 ppb范围内,NO₂气体浓度与相位正切信号值具有较好的二次拟合关系,R²为0.9995.另外,该仪器在泰安站进行了长期外场观测,并与改装后的进口商品化仪器PKU-Thermo 42i-TL进行比对实验,结果表明,两者的测量结果一致性较好,R²=0.9811,表明其具有良好的运行稳定性和测定结果准确性,适用于环境大气二氧化氮浓度的在线监测.外场观测结果表明,春季泰安站二氧化氮浓度均值为12.39 ppb,有明显日变化规律.     

含弹内埋弹舱缩尺模型气动噪声特性研究

目的对含弹的内埋弹舱模型进行噪声仿真和试验研究。方法计算采用"CFD+CAA"的混合方法,采用DDES计算流场,基于M?hring声学类比方法得到测量点的噪声信息。采用该方法与空腔M219标准试验结果进行对比。内埋弹舱吹风试验在全消声室中进行,并采用传声器阵列识别主要噪声源。结果计算与试验得到的不同来流条件下,不同测量点的噪声频谱曲线基本一致。弹舱内最大声压级出现在中间弹翼附近的侧壁上,与声源识别的主要噪声源的位置一致。结论该研究可为内埋弹舱的设计提供参考和技术支持。     

A Variance Estimator for Constrained Estimates of Change in Relative Categorical Frequencies

Consistent estimators of change and state becomes an issue when sample data come from a mix of permanent and temporary observation units. A joint maximum likelihood estimator of state and change creates estimates of state that depend on antecedent viz. posterior survey results and may differ from estimates of state derived from a single-date analysis of the sample data. A constrained estimator of change in relative categorical frequencies that eliminates this potential inconsistency is proposed and a model based estimator of their sampling variance is developed. The performance of the constrained estimator is quantified against six criteria and a joint maximum likelihood estimator in simulated sampling from 15 populations with three combinations of permanent and temporary samples, four to six categorical class attributes, and constant size between sampling dates. Bias of the constrained estimators was negligible but larger than for joint maximum likelihood estimators. Mean absolute deviations and variances of constrained estimators were generally at par with the joint estimators. Constrained estimators of root mean square errors and achieved coverage of nominal confidence intervals of constrained estimators were occasionally better. A generalized variance function for the constrained estimates of change is provided as a computational shortcut.     

基于神经网络的碳排放预测及影响因素分析

基于新疆1995—2014年农业生产碳排放源,建立碳排放关系数据库。应用广义神经网络(generalized regression neural network,GRNN)构建了排放量预测模型,结合平均影响值(mean impact value,MIV)方法对碳排放影响因素进行量化。结果表明:1)GRNN模型预测碳排放的平均绝对百分误差和拟合优度分别为2.7860%和0.8720;2)新疆人口、人均GDP、农业贡献值、农机总动力和农户固定资产投资等因素对农业生产碳排放的影响程度分别为0.6210、0.2377、0.3698、0.8500和0.1000。该成果可为新疆碳排放总量分析和影响因素量化方面提供参考。     

带缝金属腔体内包含非线性组件的耦合效应分析

目的对带缝金属腔体内连接非线性组件的系统级耦合效应进行分析。方法在外界电磁激励源的作用下,采用全波混合算法解决腔体内部场强分布问题,并利用高阶FDTD方法求解线缆上的感应电压和电流,得到流入非线性组件的信号,然后建立非线性组件的频域黑箱模型,结合S-参数,得到非线性组件端口的功率响应,最后通过仿真实验验证方法的有效性。结果通过系统耦合效应分析建模,建立仿真模型,得到了非线性组件的响应曲线。结论该系统级的耦合效应分析方法可以分析得到非线性组件作为二端口或多端口时的输出功率响应,对系统级的耦合研究具有重要意义。     

Evaluation of adsorption capacities of humic acids extracted from Algerian soil on polyaniline for application to remove pollutants such as Cd(Ⅱ), Zn(Ⅱ) and Ni(Ⅱ) and characterization with cavity microelectrode

The adsorption capacities of new humic acids isolated from Yakouren forest (YHA) and Sahara (Tamenrasset: THA) soils (Algeria) and commercial humic acid (PFHA) on polyaniline emeraldine base (PEB) were studied at pH 6.6. Also the adsorption of heavy metals such as Cd2+, Zn2+ and Ni2+ on humic acid-polyaniline systems (HA-PEB) was investigated at the same conditions. HA-PEB compounds were characterized by scanning electron microscopy (SEM), infrared spectrometry and cavity microelectrode. In addition, batch adsorption and cavity microelectrode were used in the adsorption study of Cd2+, Zn2+ and Ni2+ on HA-PEB. To develop biocaptors of polluting metals using a cavity microelectrode modified by HA-PEB systems, the adsorption kinetic and adsorption capacity were investigated. The SEM analysis showed that the presence of humic acid affected the PEB surface and caused the formation of a granular morphology. The maximum adsorption capacities (qmax) of PFHA, THA and YHA determined by adsorption isotherms were 91.31, 132.1 and 151.0 mg/g, respectively. Batch adsorption results showed that qmax of Cd2+, Zn2+ and Ni2+ on HA-PEB followed the order: THA-PEB > YHA-PEB > PFHA-PEB. The voltammograms obtained with HA-PEB modified cavity microelectrode showed the appearance of new redox couples reflecting the adsorption of HA on PEB. Metal-humic acid-polyaniline voltammograms were characterized by appearance of oxidation-reduction couples or reduction wave corresponding to metal. Finally, the result may be exploited to develop a biocaptor based on the cavity microelectrode amended by THA-PEB and YHA-PEB.     

企业资源管理拓展问题评述

企业资源管理问题是关系到提升企业核心价值和保持企业持续竞争优势的重要问题，企业资源管理的拓展是企业管理理论和实践的共同需要。在文献综述的基础上，从企业广义资源环境划分、企业资源管理范畴拓展、企业资源形式和属性等几个不同角度，对企业资源管理拓展问题进行了讨论和分析。     

Evaluating Alternative Temporal Survey Designs for Monitoring Wetland Area and Detecting Changes Over Time in California

Evaluation of wetland extent and changes in extent is a foundation of many wetland monitoring and assessment programs. Probabilistic sampling and mapping provides a cost‐effective alternative to comprehensive mapping for large geographic areas. One unresolved challenge for probabilistic or design‐based approaches is how best to monitor both status (e.g., extent at a single point in time) and trends (e.g., changes in extent over time) within a single monitoring program. Existing wetland status and trends (S&T) monitoring programs employ fixed sampling locations; however, theoretical evaluation and limited implementation in other landscape monitoring areas suggest that alternative designs could increase statistical efficiency and overall accuracy. In particular, designs that employ both fixed and nonfixed sampling locations (alternately termed permanent and temporary samples), termed sampling with partial replacement (SPR), are considered to efficiently and effectively balance monitoring current status with detection of trends. This study utilized simulated sampling to assess the performance of fixed sampling locations, SPR, and strictly nonfixed designs for monitoring wetland S&T over time. Modeled changes in wetland density over time were used as inputs for sampling simulations. In contrast to previous evaluations of SPR, the results of this study support the use of a fixed sampling design and show that SPR may underestimate both S&T.     

基于前向神经网络的广义环境系统评价普适模型

为了建立由水环境、空气环境、生态环境、水资源环境、灾害环境、遥感环境、社会经济环境等不同环境系统组成的广义环境系统评价都能普适、通用的神经网络模型,针对BP神经网络因收敛速度慢、易于陷入局部极值而使实用性受限的缺陷,提出以双极性sigmoid函数作为网络隐层节点(神经元)的激活函数,而网络输出为所有隐层节点输出的线性求和的前向神经网络的广义环境系统评价模型.在设置广义环境系统指标参照值和指标值规范变换式,并对指标值进行规范变换的基础上,分别构建了适用于广义环境系统评价的任意2个指标规范值的前向神经网模型(NV-FNN(2)结构)和任意3个指标规范值的前向神经网模型(NV-FNN(3)结构).而对于指标较多的广义环境系统评价,只要将多指标分解为以上2个指标和3个指标的两种简单结构的前向神经网络的广义环境系统评价模型的组合表示即可.理论分析和实例检验结果表明:该模型对任意广义环境系统的规范指标值皆普适、通用,因而使不同环境系统的评价变得简洁、统一.规范变换和优化算法相结合的建模思想和方法对简化广义环境系统评价的多元回归、投影寻踪回归、回归支持向量机和径向基神经网络建模亦有借鉴和启迪作用.     

基于Copula函数的汉江中上游流域极端降雨洪水联合分布特征

选取汉江中上游流域作为研究对象,根据流域九个气象站点1969~2008年逐日降雨资料以及丹江口水库同时期日入库流量资料,采用年最大值法(AM)和百分位法两种选样方式选取1 d、3 d降雨和1 d、3 d洪量极值样本,分别运用广义极值分布(GEV)、广义帕累托分布(GPD)、伽玛分布(Gamma)3种极值统计模型对样本进行单变量边缘分布拟合,运用Gumbel、Clayton以及Frank Copula函数模型对样本进行多变量联合分布拟合,遴选出描述流域降雨和洪水联合分布规律的最优概率模型。结果显示:对于AM选样样本,边缘分布为GEV时降雨洪量的二维和三维联合分布Frank Copula函数拟合效果最优;对于百分位选样样本,边缘分布为GPD时降雨洪量的二维联合分布Gumbel Copula函数拟合效果最优,三维联合分布则是Frank Copula函数拟合效果最优;比较二维和三维Copula函数模拟结果,三维联合Copula函数推求的设计值更大,说明三维联合分布考虑了更多的变量和极值信息,能更全面地反映极端降雨洪水事件的真实特征,对工程设计更显安全。