Categorical Bias in Line Angle Judgments: Sex Differences and the Use of Multiple Categories

According to the Category Adjustment (CA) model, spatial estimates (e.g., of location) involve Bayesian combination across multiple, hierarchical pieces information, each weighted by its relative certainty. Recent work, though, has shown that men and women differ in terms of their certainty regarding fine-grained and categorical information in location memory. Here we demonstrate that this reflects a more general sex difference in visuospatial processing by examining bias patterns in a line angle judgment task (JLAP-15). In addition, the data suggest that multiple, hierarchical levels of categorical information influenced spatial judgments. These results imply that the hierarchical combination outlined by the CA model extends beyond two levels, and that men and women apply differential weighting to these representations.     

IDS contribution to ITRF2008

For the first time, the International DORIS Service (IDS) has produced a technique level combination based on the contributions of seven analysis centers (ACs), including the European Space Operations Center (ESOC), Geodetic Observatory Pecny (GOP), Geoscience Australia (GAU), the NASA Goddard Space Flight Center (GSFC), the Institut Géographique National (IGN), the Institute of Astronomy, Russian Academy of Sciences (INASAN, named as INA), and CNES/CLS (named as LCA). The ACs used five different software packages to process the DORIS data from 1992 to 2008, including NAPEOS (ESA), Bernese (GOP), GEODYN (GAU, GSC), GIPSY/OASIS (INA), and GINS (LCA). The data from seven DORIS satellites, TOPEX/Poseidon, SPOT-2, SPOT-3, SPOT-4, SPOT-5, Envisat and Jason-1 were processed and all the analysis centers produced weekly SINEX files in either variance–covariance or normal equation format. The processing by the analysis centers used the latest GRACE-derived gravity models, forward modelling of atmospheric gravity, updates to the radiation pressure modelling to improve the DORIS geocenter solutions, denser parameterization of empirically determined drag coefficients to improve station and EOP solutions, especially near the solar maximum in 2001–2002, updated troposphere mapping functions, and an ITRF2005-derived station set for orbit determination, DPOD2005. The CATREF software was used to process the weekly AC solutions, and produce three iterations of an IDS global weekly combination. Between the development of the initial solution IDS-1, and the final solution, IDS-3, the ACs improved their analysis strategies and submitted updated solutions to eliminate troposphere-derived biases in the solution scale, to reduce drag-related degradations in station positioning, and to refine the estimation strategy to improve the combination geocenter solution. An analysis of the frequency content of the individual AC geocenter and scale solutions was used as the basis to define the scale and geocenter of the IDS-3 combination. The final IDS-3 combination has an internal position consistency (WRMS) that is 15 to 20 mm before 2002 and 8 to 10 mm after 2002, when 4 or 5 satellites contribute to the weekly solutions. The final IDS-3 combination includes solutions for 130 DORIS stations on 67 different sites of which 35 have occupations over 16 years (1993.0–2009.0). The EOPs from the IDS-3 combination were compared with the IERS 05 C04 time series and the RMS agreement was 0.24 mas and 0.35 mas for the X and Y components of polar motion. The comparison to ITRF2005 in station position shows an agreement of 6 to 8 mm RMS in horizontal and 10.3 mm in height. The RMS comparison to ITRF2005 in station velocity is at 1.8 mm/year on the East component, to 1.2 mm/year in North component and 1.6 mm/year in height.     

指数分布可靠性增长分析的Bayesian整体推断方法

本文引入服从广义逆Gamma分布的折合因子,得到一种指数可靠性增长下失效率的Bayes整体推断技术,并采用Laguerre-Gauss积分方法得到了折合因子分布参数的精确数值解,通过典型示例与其它确定分布参数的方法进行比较,可知这种方法更加接近工程实际。     

经营多角化的结合效应与度量

经营多角化多年来一直是产业经济学家和政策制定者关注的焦点之一。本文对如何取得多角化经营的结合效应作了分析,并给出了经营多角化的度量方法。     

基于动态贝叶斯的反舰导弹弹型识别

使用反舰导弹对舰艇进行饱和攻击是当前对舰攻击的主要方式。首先,提出了动态贝叶斯网络(DBN)的理论及算法;其次,根据反舰导弹的高度、速度、过载、机动方式等弹道特性和RCS、雷达频率等导弹自身特性,建立了对反舰导弹进行弹型识别的DBN模型;最后,通过仿真算例验证了DBN模型的有效性,这为实际解决反舰导弹进行弹型识别的问题,提供了一种思路。     

基于改进信息融合的航空发动机状态评估方法

针对航空发动机状态监测数据的模糊性和随机性,结合贝叶斯粗糙集和D-S证据理论,提出一种改进信息融合的状态评估方法。首先对样本数据进行离散化处理,通过基于区分矩阵的属性约简算法对影响发动机性能的特征参数进行提取,生成最佳决策表。然后根据置信增益函数重新定义了贝叶斯粗糙集,利用贝叶斯粗糙集的支持度和置信增益函数作为证据的支持程度,得到各准则下的证据基本信任分配。最后利用证据合成法则对多个证据进行合成,得到评估结果。通过实例计算,验证了改进方法应用在航空器发动机状态评估中的有效性以及在处理不完备信息问题时的优越性。     

基于云贝叶斯网络的运输飞机超轮速风险评估

起飞超轮速严重威胁飞行安全,为了有效评估运输飞机起飞时在不确定性因素影响下的超轮速风险水平,提出一种基于云模型和贝叶斯网络的评估模型。选取抬轮速度、总重、低压转子转速、抬轮率、抬轮时机、升降舵控制量、风的分量、总温8个指标,建立超轮速风险指标体系;运用基于启发式高斯云变换算法和正向高斯云算法的云模型,实现超轮速风险等级...     

基于改进FCM的北斗三频组合观测值选取

以北斗卫星导航系统三频双差为基础探讨了组合观测值及误差,针对以往采用聚类方法在研究GPS三频组合数据过程中的不足,提出了基于距离修正的增量模糊C均值算法.通过调节因子有效地修正了样本中心与聚类中心的距离,获得合理的隶属度,从而得到正确的分类;构造了基于距离修正的聚类有效性指标,自动获取最佳聚类数,避免了人为确定聚类数的不合理性;在此基础上引入增量的思想,数据增加时以原有的数据集为基础,根据阈值进行归类,不需要重新进行初始计算.通过矩阵变换法及实例验证了该方法的可行性和可靠性.     

目的论视角下服装品牌的翻译

随着全球化飞速发展,海内外服装贸易竞争日益激烈,服装品牌的译名日益显示出其重要性。以服装类品牌为研究对象,旨在探讨目的论下的服装品牌的翻译策略。目的论认为,目的原则是翻译中的首要原则。经分析发现,为使译名达到传达信息、传递美感或呼唤消费的目的,译者在翻译时应灵活运用音译、直译、意译、音意译几种译法,创造出达意传神、刺激消费的译名。     

Bayesian network-based extraction of lunar impact craters from optical images and DEM data

Impact craters are among the most noticeable geomorphological features on the planetary surface and yield significant information about terrain evolution and the history of the solar system. Thus, the recognition of impact craters is an important branch of modern planetary studies. Aiming at addressing problems associated with the insufficient and inaccurate detection of lunar impact craters, a decision fusion method within the Bayesian network (BN) framework is developed in this paper to handle multi-source information from both optical images and associated digital elevation model (DEM) data. First, we implement the edge-based method for efficiently searching crater candidates which are the image patches that can potentially contain impact craters. Secondly, the multi-source representations of an impact crater derived from both optical images and DEM data are proposed and constructed to quantitatively describe the two-dimensional (2D) and three-dimensional (3D) morphology, consisting of Histogram of Oriented Gradient (HOG), Histogram of Multi-scale Slope (HMS) and Histogram of Multi-scale Aspect (HMA). Finally, a BN-based framework integrates the multi-source representations of impact craters, which can provide reductant and complementary information, for distinguishing craters from non-craters. To evaluate the effectiveness and robustness of the proposed method, experiments were conducted on three lunar scenes using both orthoimages from the Lunar Reconnaissance Orbiter (LRO) and DEM data acquired by the Lunar Orbiter Laser Altimeter (LOLA). Experimental results demonstrate that integrating optical images with DEM data significantly decreases the number of false positives compared with using optical images alone, with F₁-score of 84.8% on average. Moreover, compared with other existing fusion methods, our proposed method was quite advantageous especially for the detection of small-scale craters with diameters less than 1000 m.