View makes a difference: Presenting human figures from the back or front affects mental spatial transformations of children and adults

Previous research suggested that performance in spatial judgments involving rotated human figures is poorer if these figures are presented from the front than from the back. We further investigated this effect, controlling for visible facial information in front and back view by presenting figures' faces as profile. Children's and adults' judgments were still faster and less error prone if figures were presented from the back. Moreover, reaction times indicated that participants did not mentally rotate figures in front view. Children performed overall more poorly than adults, but there were also qualitative differences suggesting that children are more susceptible to embodiment effects than adults. This study underlines that embodiment may have differential effects in spatial transformation tasks, enhancing or impairing performance.     

Proposed strategies for optical observations in a future European Space Surveillance network

Two ESA-funded feasibility studies that aimed to develop observation strategies, to propose suitable sensor architectures, and to assess the expected performance of an independent European Space Surveillance System were carried out during the last years. The French company ONERA led two study teams comprising a number of European companies.     

基于Bayes方法的某武器系统可靠性综合评估

根据武器系统现场可靠性试验数据少而研制过程中分系统可靠性试验数据较易得的情况,提出了一种基于Bayes方法对某武器系统进行可靠性评估的方法。将研制过程中分系统的可靠性试验数据融合为系统可靠性评估的先验信息,以提高用于评估的信息量。方法对复杂大系统以及高可靠性系统的可靠性评估有一定的参考价值。     

基于树形马氏链模型的可靠性分析方法

复杂系统的极限状态函数非线性程度较高，在进行可靠性分析时，易导致失效概率的计算误差大、效率低，针对上述问题，提出了树形马氏链（TMC）算法和基于该算法的可靠性分析方法。树形马氏链是对原始马尔可夫链的改进，其状态转移过程更加灵活，具备局部多链并行和自适应探索失效域边界的特性。树形马氏链通过多候选状态点扩大对失效域信息的收集，生成能充分反映失效分布特征的样本，对该样本进行自适应核密度估计得到近似最优的重要抽样分布密度函数，从而提高计算结果的准确度。文末的数值算例和工程算例验证了算法性能，计算结果表明算法对设计点、抽样起点的位置不敏感，处理强非线性及复杂串联系统问题时，能在少样本量下得到相对高准确度的计算结果，且在样本量改变时，计算结果相对稳定可靠；工程算例给出了所提方法在实际问题下的效率，体现了所提方法的工程应用价值。     

Non-linear methods in remotely sensed multispectral data classification

The aim of this research is to develop an effective approach being able to deal with the stochastic nature of remote sensing data. In order to achieve this objective it is necessary to structure the methodological knowledge in the area of data mining and reveal the most suitable methods for the prediction and decision support based on large amounts of multispectral data. The idea is to establish a framework by decomposing the task into functionality objectives and to allow the end-user to experiment with a set of classification methods and select the best methods for specific applications. As a first step, we compare our results from Bayesian classification based on non-parametric probability density estimates of the data to the results obtained from other classification methods. Tree scenarios are considered, making use of a small benchmark dataset, a larger dataset from Corine land cover project for Bulgaria and analyzing different features and feature selection methods. We show that the theoretically optimal Bayesian classification can also achieve optimal classification in practice and provides a realistic interpretation of the world where land cover classes intergrade gradually.     

Synthesis,chemistry and photochemistry of cyanobutadiyne (HCCCCCN)

Cyanobutadiyne has been synthesized starting from the mono or bistributylstannyl derivative of 1,3-butadiyne and p-toluenesulfonyl cyanide. The UV spectrum of HC₅N and the ¹³C NMR spectrum of the deuterocyanobutadiyne DC₅N have been recorded for the first time. Cyanobutadiyne has been detected in the photolysis of mixtures of gases observed on Titan. Its formation starting from cyanoacetylene and acetylene also occurs in the presence of huge amounts of dinitrogen, the major constituent of the Titan’s atmosphere. The application of these findings to the atmosphere of Titan is discussed. The chemistry and photochemistry of cyanobutadiyne have been investigated. A photoadduct has been observed in the photolysis of cyanoacetylene and ethanethiol and, a univocal synthesis of this compound was performed by a nucleophilic addition reaction.     

冲击噪声环境下基于任意阵列流形的空时二维DOA估计方法

 针对冲击噪声环境中信号源的高分辨二维波达方向(DOA)估计问题,提出了一种适合任意阵形的基于联合对角化分数低阶空时(ST)相关矩阵的二维DOA估计方法。该方法先对分数低阶空时矩进行采样构建伪快拍数据矩阵,然后对两个时延分数低阶空时矩阵进行联合对角化处理。其无需二维谱峰搜索和参数配对,在低信噪比下对强冲击噪声具有更好的抑制作用,适合存在一维角度兼并的情况。仿真结果证明了该方法的有效性。     

基于EMD及PNN的航天器振动环境分析

针对航天器非平稳随机振动信号模态频率密集的特点,提出了基于经验模式分解EMD (Empirical Mode Decomposition)的多分量过程神经网络PNN(Process Neural Network)自回归模型.通过EMD对原始时间序列进行分解, 使之成为一组不同尺度的局部正交本征模函数IMF(Intrinsic Mode Functions),利用PNN对每个IMF分别进行时变参数分析并以此确定其时变自功率谱密度,对所有分量的时变自功率谱密度通过叠加进行重构, 以此得到原始信号的时变自功率谱密度.仿真结果和实例分析表明:和传统的时频分析法相比,该方法直接使用信号数据,避免了相关估计计算,减小了计算工作量;无交叉干扰项,提高了信号的时频分布特性,具有较高的时频分辨率;对各工况下航天器的振动信号能有效的进行分析,具有较强的信号特征提取能力.      

光纤陀螺中分形噪声的参数估计和去除

光纤陀螺零漂信号中主要存在分形噪声和高斯白噪声,采用传统的时间序列分析法很难去除这类混合噪声.基于小波分析,提出一种分步估计加性白噪声强度和分形随机过程参数的新方法.先通过拟合自相关函数,估计出白噪声的强度;再在小波变换域估计分形噪声参数,并选取适当软阈值对测量值滤波.实验结果表明该估计和降噪方法有效地去除了光纤陀螺中的混合噪声,且不需要噪声的先验知识,具有很好的适应性.      

基于半参数回归模型的批处理确定卫星轨道方法

由于卫星轨道观测数据中含有非线性影响因素,必然会降低定轨精度。在半参数 回归模型的基础上,应用小波阈值去噪算法估计并消除观测数据中存在的非线性影响因素, 提出了基于半参数回归模型的批处理确定卫星轨道的方法,以提高定轨精度;然后,在理论 上证明了在测量数据存在非线性影响因素的情形下,基于半参数回归模型的批处理确定卫星 轨道方法的定轨精度高于经典的批处理定轨精度;最后,对中低轨卫星应用批处理定轨进行 了仿真。结果表明：基于半参数回归模型的批处理确定卫星轨道方法分离出观测数据中的 白噪声和非线性影响因素,从而可以在观测数据中消除非线性影响因素,提高定轨的精度。