Optimal Evasion from a Pursuer with Delayed Information

A class of prescribed duration pursuit–evasion problems with first-order acceleration dynamics and bounded controls is considered. In this class, the pursuer has delayed information on the lateral acceleration of the evader, but knows perfectly the other state variables. Moreover, the pursuer applies a strategy derived from the perfect information pursuit–evasion game solution. Assuming that the evader has perfect information on all the state variables as well as on the delay of the pursuer and its strategy, an optimal evasion problem is formulated. The necessary optimality conditions indicate that the evader optimal control has a bang–bang structure. Based on this result, two particular cases of the pursuer strategy (continuous and piecewise continuous in the state variables) are considered for the solution of the optimal evasion problem. In the case of the continuous pursuer strategy, the switch point of the optimal control can be obtained as a root of the switch function. However, in the case of the piecewise continuous (bang–bang) pursuer strategy, this method fails, because of the discontinuity of the switch function at this very point. In this case, a direct method for obtaining the switch point, based on the structure of the solution, is proposed. Numerical results illustrating the theoretical analysis are presented leading to a comparison of the two cases.     

A Planck-Like Problem for Quantum Charged Black Holes

Motivated by the parallelism existing between the puzzles of classical physics at the beginning of the XXth century and the current paradoxes in the search of a quantum theory of gravity, we give, in analogy with Planck's black body radiation problem, a solution for the exact Hawking flux of evaporating Reissner-Nordström black holes. Our results show that when back-reaction effects are fully taken into account the standard picture of black hole evaporation is significantly altered, thus implying a possible resolution of the information loss problem.     

Causality, relativity and quantum correlation experiments with moving reference frames

Entanglement, one of the most important features of quantum mechanics, is at the core of the famous Einstein-Bohr philosophical debate [1] and is the principal resource for quantum information processing [2]. We report on new experimental investigations of the properties of entangled photon pairs with emphasis on the tension between quantum mechanics and relativity [3,4]. Entangled photons are sent via an optical fiber network to two villages near Geneva, separated by more than 10 km where they are analyzed by interferometers [5]. The photon pair source is set as precisely as possible in the center so that the two photons arrive at the detectors within a time interval of less than 5 ps (corresponding to a path length difference of less than 1 mm). This sets a lower bound on the ‘speed of quantum information’ to 10⁷ times the speed of light. Next, one detector is set in motion [6] so that both detectors, each in its own inertial reference frame, are first to do the measurement! The data always reproduces the quantum correlations.     

信息披露质量影响公司风险承担:治理效应抑或声誉效应？

基于信息披露理论和公司治理理论,本文实证检验了信息披露质量对公司风险承担的影响。实证结果发现:较高的信息披露质量有助于提高公司风险承担水平,从而验证了信息披露的“治理效应”。进一步发现,管理层持股激励能够影响上市公司的信息披露行为,并提高公司风险承担水平,说明管理层持股能够加强信息披露质量与公司风险承担之间的正向关系,且这种影响关系在高管理层持股组中更显著。研究结论不仅丰富和拓展了信息披露和公司风险承担的相关研究,而且对管理层激励契约的设计和公司风险认知具有重要的启示作用和现实意义。     

基于在线评价信息的概率语言多属性变权决策方法

针对电子商务网站中涌现的大量在线评价信息,本文提出一种基于在线评价信息的概率语言多属性变权决策方法,指导消费者的购买决策。在本文方法中,首先利用概率语言描述在线评价信息,构建概率语言决策矩阵,并重新定义了区间概率语言的得分函数;其次,利用变权方法处理决策矩阵,得出不同方案的各属性权重;再次,依据得出的属性权重,基于后悔理论,考虑决策者风险规避系数,求出各方案的综合感知效用值,并据此排序。最后,利用汽车之家网站提供的顾客在线评价信息,以一个汽车选择的实例说明了本文所提方法的合理性与实用性。     

多因素干扰下的供应链最优定价与订货决策

在信息不对称条件下,市场需求、价格和风险厌恶等因素同时干扰时,构建数量折扣契约的供应链博弈模型,寻找其实现供应链协调的内在约束条件。根据显示原理,构建信息不对称条件下多因素干扰的CVaR模型并求解,然后用算例仿真,结果表明:供应商隐瞒生产成本信息会带来额外收益,但给零售商造成额外损失。价格随机与零售商厌恶风险的耦合作用是导致供应链上各决策变量发生分岔现象的内因,与信息是否对称无关。但信息不对称会损害供应链系统的稳定性。在分岔突变区域内供应链失调,在区域之外供应链协调。零售商风险中性的态度和提高信息透明度有利于提高整个供应链的绩效。     

Virtual age,is it real? ‐ Discussing virtual age in reliability context

Several settings, where the notion of virtual age is employed, are discussed. We argue that the age reduction imperfect repair modeling is often not sufficiently justified in practice, as it is not possible to execute repair in most of real situations that conforms with this model. On the other hand, a shock‐based virtual age model is suggested and justified via the probabilities of failures on shocks. The new notion of virtual age for degrading items is also introduced. We discuss how to recalculate virtual age after switching from one regime to another. Several examples illustrating different notions of virtual age are presented.     

FABEMD和改进局部能量窗口的红外中波和长波图像融合

针对探测波段为3.7～4.8 μm的中波红外图像和探测波段为8～14 μm长波红外图像融合过程中存在场景对比度低,显著性目标不够凸出,伪影引入严重的问题,采用快速自适应二维经验模态分解（FABEMD)对红外中波和长波图像进行多尺度分解以得到二维内蕴模函数(BIMFs)和残余分量(Residual)。对于每一层内蕴模函数选用改进的局部能量窗口融合规则,首先配置好加权算子以增加区域窗口中心像素的能量占比;选用不同的加权算子,经实验验证能有效突出红外中波和长波图像的能量特征信息;其次充分利用内蕴模函数的相位信息,当相位相反时,采用能量加权平均的方式,以解决融合系数的正负符号极性难以确定的问题;当相位相同时,判断二者的能量差距并依据差距大小选择设定的融合规则,融合规则基于红外中波和长波图像的灰度差异特性设定。对于残余分量则利用红外中波图像和改进区域能量窗口的最大对称环绕显著性权重图指导基础层系数的融合,自适应的局部环绕窗口充分利用了低频显著性信息,对无用背景的抑制效果也相当出色,能够在复杂背景图像中突出显著性对象,最终得到细节信息丰富,对比度明显的指导图像。最后通过FABEMD的逆变化重构过程得到融合图像,对4组不同背景、不同大小的红外中长波图像进行主观和客观性能评价,4组图像均来自多波段红外采集系统且都经过严格配准并和7种相关算法进行对比实验,在主观性能上显著性对象突出、清晰度度高;客观性能上在平均梯度和空间频率这两个评价指标上性能优异,验证了该算法的有效性。     

不同分辨率无人机数码影像的马铃薯地上生物量估算研究

地上生物量（AGB）是表征作物生命活动的重要参数,对作物长势监测和产量预测尤为关键。因此,快速准确地获取AGB信息,对于监测作物生长状况、指导农业管理和提高产量具有重要的意义。以无人机为平台搭载数码相机传感器,因机动性强、价格低、空间分辨率高的优势,能够及时准确的估算作物AGB,已成为遥感估算研究的热点之一。由于无人机不同飞行高度及其对应不同分辨率数码影像的AGB估算模型精度不同,因此,尝试在马铃薯的块茎增长期,通过设置10,20,30,40和50 m共5种无人机飞行高度,获取不同分辨率的数码影像,探究其对以光谱信息、纹理特征和光谱信息+纹理特征构建AGB模型精度的影响。首先,基于无人机数码影像,分别提取光谱信息和纹理特征,通过光谱信息构建的植被指数和纹理特征,分别结合地面试验获取的实测地上部生物量数据进行相关性分析,分别筛选了相关系数绝对值较大的前10个影像指数和前8个纹理特征。然后,分别以3种输入变量整合方差膨胀因子（VIF）进行主成分分析（PCA）降维处理,获得最佳主成分后以多元线性回归（MLR）构建AGB估算模型。最后,对比不同分辨率的数码影像以3种变量和同种分辨率下以同种变量构建的AGB估测模型效果。结果发现：（1）获得的影像分辨率在0.43~2.05 cm之间变化时,纹理特征与马铃薯AGB相关性弱于植被指数,但都达到极显著相关水平（p<0.01）,随着数码影像分辨率降低,二者相关性差异明显。（2）同种分辨率影像下,光谱信息+纹理特征估算AGB的效果最优,其次为单一纹理特征模型,而单一光谱模型表现效果最差。（3）随着数码影像分辨率提高,光谱信息、纹理信息以及光谱+纹理信息估算AGB的精度逐渐变好。     

光谱数据解析中的变量筛选方法

如何从海量或高维数据中“提纯”出有用的信息,这是当前数据分析面临的一个巨大的挑战,也是当前研究的一个热点。变量筛选技术能够从众多、复杂的量测数据中提取出特征信息变量,达到简化多元模型乃至提高模型预测性能等目的。在光谱分析中,来自噪声等诸多因素的影响,量测数据会不可避免地包含干扰和无关信息变量,以及变量间存在的多重共线性,这些都会影响模型的稳健性和预测能力。近年来变量（波长）筛选方法在光谱解析领域的研究与应用中取得了较大的进展。结合国内外相关研究文献和作者的研究体会,不仅仅综述了近红外光谱,还综述了中红外光谱、拉曼光谱等众多筛选变量的方法的提出、特点、发展、类别、比较和近五年来在不同领域的应用进展。其中,评价变量重要性的参数及其标准或阈值的选择、搜索变量的策略和途径是变量筛选方法的关键。而且每种方法都具有各自的优势和局限性,实际使用中要根据方法自身特点结合目标体系的特征选择合适的方法。重点内容：（1）对比了光谱数据分析中常用的波长筛选和波段筛选方法;（2）对比了基于PLS模型参数的不同变量筛选方法的原理和特点;（3）根据搜索和筛选变量策略的不同将变量筛选方法进行分类评述。最后,围绕在解析实际复杂体系中变量筛选方法出现的过拟合、不稳定等问题进行了讨论并提出相应的解决措施,同时对变量筛选方法的研究趋势、发展前景和应用方向进行了展望。其中,新的评价变量重要性的判据和搜索变量的策略等工作仍需要展开深入地研究。期望本综述能够对光谱变量筛选的后续研究及应用起到积极的推动作用。