Learning Multi Labels from Single Label——An Extreme Weak Label Learning Algorithm

This paper presents a novel algorithm for an extreme form of weak label learning, in which only one of all relevant labels is given for each training sample. Using genetic algorithm, all of the labels in the training set are optimally divided into several non-overlapping groups to maximize the label distinguishability in every group. Multiple classifiers are trained separately and ensembled for label predictions. Experimental results show significant improvement over previous weak label learning algorithms.     

基于曼哈顿距离构建非参数Q矩阵修正方法

将被试得分、理想反应距离和被试得分异常原理相结合,并加入属性计分下的被试得分特性,开发了用于多级评分情境下属性计分曼哈顿距离法(SA-MD),在不同条件下验证了SA-MD的稳定性和适宜性.通过模拟研究和实证研究表明:(i)从逻辑推导出SA-MD用于多级评分情境下Q矩阵修正更合理;(ii)在多种条件中,SA-MD 均有较优的修正效果,适用范围更广,稳定性更高;(iii)当小样本测验进行Q矩阵修正时,使用SA-MD方法可获得更优的效果.     

Post李超代数结构的性质

通过post李超代数的定义, 讨论post李超代数结构的基本性质, 给出post李超代数的一些存在性结果, 并利用post李超代数可构造LR超代数和左对称超代数, 给出交换post李超代数结构的相关结果.     

Synthesis and Largely Enhanced Nonlinear Refraction of Au@Cu_2O Core-Shell Nanorods

Au@Cu_2O core-shell nanorods with tunable thickness of Cu_2O shell were synthesized and their linear and nonlinear optical responses were investigated. Two transverse plasmon resonance peaks were observed when the Au nanorods were coated with Cu_2O shells, which were adjusted by the Cu_2O shell thickness. The nonlinear absorption of the Au@Cu_2O nanorods is enhanced by 5 times at the longitudinal plasmon resonance wavelength compared with that of bare Au nanorods. More intriguingly, largely enhanced nonlinear refraction and suppressed nonlinear absorption at the transverse plasmon resonance wavelength were observed in the Au@Cu_2O nanorods. Our findings indicate the existence of strong local field enhancement at the interface between the Au core and the Cu_2O shell, which would provide a promising strategy in designing plasmonic nonlinear nanodevices with good nonlinear figures of merit.     

可折叠集装箱接驳运输问题的建模与优化

对一类带时间窗的可折叠箱接驳运输问题进行了研究,其中使用可折叠箱在堆场与客户之间集散货物,一辆集卡可装载一个满箱或多个空箱,目标为集卡总工作时间的最小化.借鉴确定的活动在顶点上的图的思想,将该问题分解为满箱子问题和空箱子问题,其中满箱子问题类似于带时间窗的多旅行商问题,空箱子问题因客户的货物量可为负值而显著区别于车辆路径问题,且两个子问题之间存在访问时间耦合等关联.进而建立了问题的数学描述,设计了问题的主动禁忌搜索(reactive tabu search,RTS)求解算法,并基于随机生成的大量算例验证了算法的有效性.结果表明,相比于使用CPLEX等优化软件,RTS算法可以在更短的时间内求得问题的更优解;相比于使用标准箱的情形,使用可折叠箱可节省约13%的接驳成本.     

基于数据场联合PRI变换与聚类的雷达信号分选

基于脉冲描述字进行雷达信号分选时,传统聚类算法需要预先人工设定聚类中心和聚类数目。针对该问题,提出一种基于数据场理论联合脉冲重复间隔(pulse repetition interval,PRI)变换与聚类的雷达信号分选新方法。首先,依据数据场理论,基于势值大小实现干扰点剔除,而后利用PRI变换算法进行PRI估计,依据PRI估计值将归一化脉冲描述字数据预分类,进而以各类数据集中心间的欧氏距离小于辐射因子为准则进行类别合并,自动得到初始聚类中心和聚类数目,最后通过改进K-Means算法完成聚类分选。仿真实验表明:所提方法能够应对存在频率捷变,重频参差、抖动、参数交叠、局部脉冲丢失的复杂信号环境,分选正确率明显提升。     

彩虹黑弦的热力学性质

双重相对论(DSR)是描述平直时空中的量子引力的一个有效模型.当试图将该模型纳入到弯曲时空中考虑时,一种被称为"彩虹引力"的理论可帮助实现这一推广,此时背景时空依赖于探测粒子的能量.事实上受粒子能量影响的度规的形式依赖于正交系的选取.本文主要考虑了自由落体参考系下的彩虹静态柱对称黑洞(彩虹黑弦).得到了取一阶近似的彩虹黑弦的霍金温度和熵,这种修正来源于考虑的彩虹引力效应.     

A Method for Time-Series Location Data Publication Based on Differential Privacy

In the age of information sharing, logistics information sharing also faces the risk of privacy leakage. In regard to the privacy leakage of time-series location information in the field of logistics, this paper proposes a method based on differential privacy for time-series location data publication. Firstly, it constructs public region of interest(PROI) related to time by using clustering optimal algorithm. And it adopts the method of the centroid point to ensure the public interest point(PIP) representing the location of the public interest zone. Secondly, according to the PIP, we can construct location search tree(LST) that is a commonly used index structure of spatial data, in order to ensure the inherent relation among location data. Thirdly, we add Laplace noise to the node of LST, which means fewer times to add Laplace noise on the original data set and ensures the data availability. Finally, experiments show that this method not only ensures the security of sequential location data publishing, but also has better data availability than the general differential privacy method, which achieves a good balance between the security and availability of data.     

变化海流环境下AUV能量最优三维路径规划

为获取变化海流环境下自主水下航行器(autonomous underwater vehicle, AUV)的能量最优路径, 基于最优控制理论提出一种用于AUV的三维能量最优路径规划算法。首先, 为了有效抑制海流对路径规划的影响, 将海流向量加入到AUV运动学模型中。其次, 在已知俯仰角及AUV位置的情况下, 利用庞特里亚金极小值原理, 获得能量最优控制律。最后, 利用线性定常系统的状态空间理论, 计算得到初始艏向角、航速以及能量消耗。在仿真环节, 通过与负反馈控制策略相比较, 说明所提算法能够规划出三维能量最优路径, 而且可以有效降低AUV的能量消耗。     

考虑引入渠道竞争的双渠道信号传递策略

在一个存在高低两种类型制造商的供应链中,通过对制造商向零售商进行信号传递策略的研究,把制造商引入渠道竞争的动机解释为"渠道竞争"及"信息非对称"两种效应.把零售商努力纳入需求函数,建模分析了不完全信息条件下单(双)渠道供应链中制造商通过调整入场费和批发价进行信号传递的决策.并在此基础上通过两种渠道模式下供应链成员决策参数的对比,重点分析了渠道入侵对信号传递策略两种效应的综合影响.研究发现:两种模式下,制造商都需要通过向上扭曲批发价、降低支付给零售商的入场费来进行信号传递,同时零售商会减少附加值服务的提供;但当满足一定条件时,制造商可以通过引入线上直销渠道降低批发价向上扭曲的概率(即更容易实现自然分离),并减少信号传递成本;产品需求波动性、需求对零售商提供附加服务的敏感性以及渠道间竞争强度都将在一定程度上影响引入渠道竞争的效果.