Predicting and interpreting identification errors in military vehicle training using multidimensional scaling

We compared methods for predicting and understanding the source of confusion errors during military vehicle identification training. Participants completed training to identify main battle tanks. They also completed card-sorting and similarity-rating tasks to express their mental representation of resemblance across the set of training items. We expected participants to selectively attend to a subset of vehicle features during these tasks, and we hypothesised that we could predict identification confusion errors based on the outcomes of the card-sort and similarity-rating tasks. Based on card-sorting results, we were able to predict about 45% of observed identification confusions. Based on multidimensional scaling of the similarity-rating data, we could predict more than 80% of identification confusions. These methods also enabled us to infer the dimensions receiving significant attention from each participant. This understanding of mental representation may be crucial in creating personalised training that directs attention to features that are critical for accurate identification.

Practitioner Summary: Participants completed military vehicle identification training and testing, along with card-sorting and similarity-rating tasks. The data enabled us to predict up to 84% of identification confusion errors and to understand the mental representation underlying these errors. These methods have potential to improve training and reduce identification errors leading to fratricide.     

基于Wiener结构的软测量模型及辨识算法

Wiener模型结构能有效地表征系统的动态和静态特性, 因此这里首先基于这一结构建立软测量模型, 利用动态与静态子模型分别建立辅助变量与主导变量间的动态与静态关系, 并说明该软测量模型的可行性, 给出模型具体表达式. 其次, 针对所提模型, 提出分步辨识方式获得最优模型参数, 说明其可行性. 再次, 为了减少计算和实现模型在线更新, 这里提出参数辨识递推算法, 并给出软测量模型参数的收敛性结论. 通过实例仿真, 可以看出本文提出模型的可行性, 以及分步辨识方式与递推算法的有效性.     

Semantic weak signal tracing

The weak signal concept according to Ansoff has the aim to advance strategic early warning. It enables to predict the appearance of events in advance that are relevant for an organization. An example is to predict the appearance of a new and relevant technology for a research organization. Existing approaches detect weak signals based on an environmental scanning procedure that considers textual information from the internet. This is because about 80% of all data in the internet are textual information. The texts are processed by a specific clustering approach where clusters that represent weak signals are identified. In contrast to these related approaches, we propose a new methodology that investigates a sequence of clusters measured at successive points in time. This enables to trace the development of weak signals over time and thus, it enables to identify relevant weak signal developments for organization’s decision making in strategic early warning environment.     

从假性紫罗兰酮合成β-紫罗兰酮中主要副产物(I)的分离鉴定

假性紫罗兰酮在浓硫酸及 - 2 0°C低温条件下反应 ,主要生成 β-紫罗兰酮 ,少量的 α-及 γ-紫罗兰酮 ,同时生成副产物 ( I)及 ( II)。用 IR、1H NMR及 MS光谱分析方法 ,对副产物 ( I)进行了结构鉴定 ,结构为 3,4,4a,5 ,8,8a-六氢 - 2 ,5 ,5 ,8a-四甲基 - 2 H - 1 -苯并吡喃     

CAE技术在模具设计过程中的并行应用

介绍CAE技术在模具设计并行工程中应用的基本思路、设计流程和主要特点，并应用Moldflow软件对空气取水机门盖进行CAE分析，以说明CAE技术的并行应用过程。实践证明，CAE技术的并行应用可以提高模具设计质量、缩短模具设计时间，为设计人员提供有效的技术支持，最大限度地发挥CAE的技术优势。     

Estimation of rheological parameters using velocity measurements

In the present investigation, we develop a method for estimating rheological parameters of viscoelastic fluids using velocity measurement in a square straight channel. It is believed that a somewhat complicated patterns of secondary flows due to the non-zero second normal stress difference are more useful than the simple viscometric flows traditionally adopted in the determination of rheological parameters. The inverse problem of determining the rheological parameters from a set of velocity measurements is solved using a conjugate gradient method. When applied to a general constitutive equation encompassing the UCM model, the Oldroyd-B model and the PTT model, the present method is found to yield a reasonably accurate estimation of five rheological parameters simultaneously even with noisy velocity measurements.     

改进的蚁群算法在溶质运移参数识别问题中的应用

非饱和土壤水分和溶质运移参数(扩散率、导水率和水动力弥散系数)取值范围较大,往往跨越几个数量级。采用传统离散化蚁群算法求解此类问题,所需节点较多,这会造成算法收敛时间较长。该文在传统蚁群算法基础上,对蚂蚁搜索路径进行改进,改进后的蚁群算法寻优路径由参数精度位数(整数位和小数位)、参数个数以及0–9十个数字构成,并将路径解码公式修改为具有判别参数正负功能的解码公式。采用改进的连续蚁群算法对非饱和溶质运移参数识别优化模型进行求解。数值模拟表明相同迭代次数下改进的蚁群算法比传统蚁群算法耗时少,算法计算时间与迭代次数满足线性关系,含水率和溶质浓度实测值与计算值吻合较好、相关性较高。     

低(等)压合成氨的最佳H2/N2与催化活性的关系

采用高压催化剂性能评价实验装置，在压力分别为7.0,10.0和15.0MPa，温度分别为350,400和450℃条件下，在H2／N2为1.6-3.0范围内研究了H2／N2对A301，ZA－5和A110－2型催化剂的活性和合成塔出口氨浓度的影响。在压力和空速一定的条件下，最佳H2／N2随反应温度而异。在350，400和450℃下，最佳H2／N2分别为1.8-2.2,2.2-2.5和2.5-3.0。由此可见，合成氨反应的速率达到最大值时的最佳H2／N2值与反应的进程有关。为此提出了催化剂效率K（Catalysis efficiency)的概念来表征在催化剂作用下反应器出口氨浓度趋近平衡的程度，即K＝CNH3／C^*NH3。根据实验结果，得到了最佳H2／N2与催化剂效率的定量关系：（H2／N2）m=1.5(1 CNH3/C^*NH3)=1.5(1 K)。由此可以根据催化剂在不同反应条件下的催化剂效率来确定最佳H2／N2。凡是会降低催化剂效率的因素，都会使最佳H2／N2降低。各种影响因素对最佳H2／N2的影响中，反应温度的影响最大，其次是空速和催化剂的活性，而压力和惰性气体含量的影响相对较小。在低温（低压）下合成氨，宜采用较低的H2／N2。     

PRIVACY LEAKAGE IN HEALTH SOCIAL NETWORKS

Members of health social networks may be susceptible to privacy leaks by the amount of information they leave behind. The threat to privacy increases when members of these networks reuse their pseudonyms in other social networks. The risk of re‐identifying users from such networks requires quantitative estimates to evaluate its magnitude. The estimates will enable managers and members of health social communities to take corrective measures. We introduce a new re‐identification attack, the social network attack, that takes advantage of the fact that users reuse their pseudonyms. To demonstrate the attack, we establish links between MedHelp and Twitter (two popular social networks) based on matching pseudonyms. We used Bayesian networks to model the re‐identification risk and used stylometric techniques to identify the strength of the links. On the basis of our model 7‐11. 8% of the MedHelp members in the sample population who reused their pseudonyms in Twitter were re‐identifiable compared with 1% who did not. The risk estimates were measured at the 5% risk threshold. Our model was able to re‐identify users with a sensitivity of 41% and specificity of 96%. The potential for re‐identification increases as more data is accumulated from these profiles, which makes the threat of re‐identification more serious.     

13C-NMR分析技术在改性聚苯醚剖析中的应用

应用^13C核磁共振分析技术，参照Sadtler标准^13C核磁共振谱图，对国外公司的五种改性聚苯醚样品进行了剖析。结果表明，有两种改性聚苯醚样品系由聚苯醚、聚苯乙烯和磷酸三苯酯组成，该类材料具有优良的阻燃性能；有两种系由聚苯醚、聚苯乙烯和聚顺丁二烯共混而成，具有较强的冲击性能；有一种系由聚苯醚、聚苯乙烯和聚乙烯构成，具有突出的润滑性能和耐磨性能。