高效液相色谱法测定氨基酸口服液中L-色氨酸的不确定度评定

采用高效液相色谱法测定氨基酸口服液中L-色氨酸的含量,对测量结果的不确定度进行评定。结果表明,标准曲线校准和测量重复性是测量过程中不确定度的主要来源,其中标准曲线校准对合成不确定度的影响最大。当氨基酸口服液中L-色氨酸的测定结果为8.8μg/mL时,其扩展不确定度为1.1μg/mL。     

植物油中邻苯二甲酸酯含量测定结果的不确定度评定

依据GB/T 21911–2008《食品中邻苯二甲酸酯的测定》,采用GPC净化在线浓缩、气相色谱–质谱法测定植物油中的邻苯二甲酸酯类增塑剂。参照JJF1059–1999《测量不确定度的评定与表示》,以测定花生油中邻苯二甲酸二(2-乙基)己酯(DEHP)为例,对整个测量过程中不确定度的来源进行了分析,并对不确定度各个分量进行了评定和合成,取包含因子k=2(约95%置信概率),花生油中DEHP含量为11.8 mg/kg时,扩展不确定度U=1.2 mg/kg。结果表明,随机效应和曲线拟合是影响邻苯二甲酸酯检测过程中的主要因素。     

气相色谱法测定果汁饮料中甜蜜素含量的不确定度评定

采用气相色谱法测定果汁饮料中甜蜜素的含量,对测定结果的不确定度进行了分析,对各不确定度分量进行了评定和量化,计算了合成标准不确定度和扩展不确定度。不确定度主要来自量器校准和标准曲线引入的不确定度。果汁饮料中甜蜜素的含量结果表示为（0．350±0．023）g／kg,k=2。     

石墨炉原子吸收光谱法测定虾粉中镉含量的不确定度评定

对石墨炉原子吸收光谱法测定虾粉中镉含量进行了不确定度评价。分析了整个测试过程中不确定度的来源,并对各不确定度分量进行了计算,当虾粉中镉的含量为0．389mg／kg时,扩展不确定度为0．008mg／kg（k=2）。     

原子荧光法测定土壤中总汞不确定度的评定

评定了原子荧光法测定土壤中总汞的不确定度.分析了样品从制备到测试的整个过程中各环节对测定结果不确定度的影响,结果表明,影响测定结果相对标准不确定度的最大因素是样品制备过程,其次是重复性条件下的标准偏差,标准物质引入的不确定度最小.在规定条件下,测定结果为(0.146±0.012) mg/kg(k=2).     

不确定二阶多智能体系统的鲁棒最优一致

针对不确定二阶多智能体系统,研究了其鲁棒最优一致性问题.首先,基于每个智能体所获得的邻居信息,设计了一个使多智能体系统达到一致的控制协议.其次,研究了多智能体系统的最优一致性问题,给出了系统在满足一定性能指标下达到一致的条件.再次,基于该条件,利用Schur补引理和线性矩阵不等式技术,给出了不确定系统达到鲁棒最优一致的条件.最后,通过仿真验证了所得结果的可行性.     

具时变时滞和 Markovian转换的不确定奇异随机系统的鲁棒 H_∞ 滤波(英文)

本文处理了一类具与模式有关的时变时滞和 Markovian转换的不确定奇异随机系统的鲁棒H∞滤波问题.所考虑的系统包含参数不确定性,Markovian参数,随机扰动和与模式有关的时变时滞.本文的目的是设计一个滤波器以保证滤波错误系统是正则的、无脉冲的、鲁棒指数均方稳定的和可达到一个给定的 H∞扰动衰减水平.文章首先得到所求鲁棒指数H∞滤波器存在的充分条件,然后给出所求滤波器参数的显示表示.     

A Bayesian approach to vectorization of object boundaries from digital images and to geometrical uncertainty assessment

A new Bayesian approach is presented for extracting 2D object boundaries with measures of uncertainty. The boundaries are described by minimal closed sequences of segments and arcs, called mixed polygons. The sequence is minimal in the sense that it is able to describe all the geometrical properties of the boundary without being redundant. Based on geometrical measures evaluated on the object boundary model, a prior distribution is introduced in order to favor a mixed polygon with good geometrical properties, avoiding short sides, collinearity between segments, and so on. The estimation process is based on a two‐stage procedure that combines reversible‐jump MCMC (RJMCMC) and classic MCMC methods. The RJMCMC method is viewed as a model selection technique, and it is used to estimate the correct number of sides of the mixed polygon. The MCMC algorithm provides a sample of mixed polygons through which to evaluate the mixed polygon that best approximates the object boundary and its geometrical uncertainty. A convergence criterion for the RJMCMC method is provided. Copyright © 2011 John Wiley & Sons, Ltd.     

Growth mechanism of thermally processed Cu(In,Ga)S2 precursors for printed Cu(In,Ga)(S,Se)2 solar cells

We investigate a process used for the selenisation of particle‐based precursors to prepare low‐cost Cu(In,Ga)(S,Se)₂ (CIGS) solar cells. It is suitable for high throughput with a short optimum selenisation duration of 3–5 min and employs a rapid thermal annealing system with elemental selenium vapour. Homogeneous crack‐free Cu(In,Ga)S₂ precursor films of up to 1 µm are obtained via doctor blading. The high selenium vapour pressure in the selenisation reaction chamber results in the formation of a compact Cu(In,Ga)(S,Se)₂ layer on top of a carbon‐rich underlayer. In order to investigate the phase development in the film, the selenisation process was interrupted at different stages and the samples were monitored via XRD and surface‐sensitive Raman measurements. We find the formation of a polycrystalline Cu(In,Ga)Se₂ phase already after 1 s at the target temperature of 550 °C. Furthermore, the effect of initial precursor thickness on solar cell parameters is discussed. Complete solar cells are prepared by conventional methods, leading to conversion efficiencies well above 8%. (© 2012 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Distance-Based Knowledge Measure for Intuitionistic Fuzzy Sets with Its Application in Decision Making

Much attention has been paid to construct an applicable knowledge measure or uncertainty measure for Atanassov’s intuitionistic fuzzy set (AIFS). However, many of these measures were developed from intuitionistic fuzzy entropy, which cannot really reflect the knowledge amount associated with an AIFS well. Some knowledge measures were constructed based on the distinction between an AIFS and its complementary set, which may lead to information loss in decision making. In this paper, knowledge amount of an AIFS is quantified by calculating the distance from an AIFS to the AIFS with maximum uncertainty. Axiomatic properties for the definition of knowledge measure are extended to a more general level. Then the new knowledge measure is developed based on an intuitionistic fuzzy distance measure. The properties of the proposed distance-based knowledge measure are investigated based on mathematical analysis and numerical examples. The proposed knowledge measure is finally applied to solve the multi-attribute group decision-making (MAGDM) problem with intuitionistic fuzzy information. The new MAGDM method is used to evaluate the threat level of malicious code. Experimental results in malicious code threat evaluation demonstrate the effectiveness and validity of proposed method.