Approach to Generate Radiometric Images

A new technique to generate radiometric images from the optical images is introduced in this paper. This technique can be applied in generating the source images for purpose of image-matching navigation. For comparison, two radiometric images are presents, one is imaged by a 8mm ground-based radiometer and the other is generated by this technique.     

FY-3A气象卫星紫外臭氧垂直探测仪

研制成FY-3A气象卫星紫外臭氧垂直探测仪,于2008年5月发射.它是一台小型化、高精度、紫外-真卒紫外光谱辐射计,用于测量大气太阳后向散射光谱辐亮度和太阳光谱辐照度,通过数据反演得剑大气臭氧总量的垂直分布.在轨道高度830 km处获得160～400 nm太阳连续光谱和250～340 nm间12个特征波长的太阳分立光谱及太阳后向散射谱,在轨测试结果表明:FY-3A气象卫星紫外臭氧年直探测仪全部功能正常,性能稳定.     

Application of a Bayesian Approach to the Tomographic Analysis of Hopper Flow

This paper presents a new approach to the analysis of data on powder flow from electrical capacitance tomography (ECT) using probability modelling and Bayesian statistics. The methodology is illustrated for powder flow in a hopper. The purpose, and special features, of this approach is that ‘high‐level’ statistical Bayesian modelling combined with a Markov chain Monte Carlo (MCMC) sampling algorithm allows direct estimation of control parameters of industrial processes in contrast to usually applied ‘low‐level’, pixel‐based methods of data analysis. This enables reliable recognition of key process features in a quantitative manner. The main difficulty when investigating hopper flow with ECT is due to the need to measure small differences in particle packing density. The MCMC protocol enables more robust identification of the responses of such complex systems. This paper demonstrates the feasibility of the approach for a simple case of particulate material flow during discharging of a hopper. It is concluded that these approaches can offer significant advantages for the analysis and control of some industrial powder and other multi‐phase flow processes.     

纳秒激光冲击加载的全过程诊断

 与传统的冲击加载方式相比,激光驱动试样具有微尺寸（直径小于1 mm,厚度约10 μm）、超短作用过程（纳秒量级）等特点,但其速度变化历史的实时诊断颇为困难,因此发展适用于激光驱动的高时空分辨率的实时测试技术是十分重要和有价值的。采用桌面式脉冲Nd:YAG激光器作为加载平台,发展了激光加载下的小焦点多普勒光纤探针测量系统（焦斑直径约200 μm,时间分辨力约50 ps）,成功实现了从激光脉冲驱动微尺寸飞片飞行直至撞击Z-切石英试样的全过程实时诊断。实验结果显示,将6 μm 厚Al箔飞片驱动至2.48 km/s时,撞击Z-切石英试样的粒子速度为1.27 km/s,与Hugoniot理论计算结果相符,表明该测试技术是可靠、有效的;多层薄膜靶结构设计（基底/烧蚀层/硅油/Al箔）可提升激光与靶物质的能量耦合效率,使飞片保持更好的宏观完整性。为开展超短脉冲激光加载下材料动态特性研究提供了一种有效的技术途径。     

A Bayesian Entropy Approach to Sectoral Systemic Risk Modeling

We investigate the dynamics of systemic risk of European companies using an approach that merges paradigmatic risk measures such as Marginal Expected Shortfall, CoVaR, and Delta CoVaR, with a Bayesian entropy estimation method. Our purpose is to bring to light potential spillover effects of the entropy indicator for the systemic risk measures computed on the 24 sectors that compose the STOXX 600 index. Our results show that several sectors have a high proclivity for generating spillovers. In general, the largest influences are delivered by Capital Goods, Banks, Diversified Financials, Insurance, and Real Estate. We also bring detailed evidence on the sectors that are the most pregnable to spillovers and on those that represent the main contributors of spillovers.     

被动多轴差分吸收光谱技术监测大气NO_2垂直廓线研究

痕量气体垂直廓线的监测,对大气污染研究具有重要意义。介绍了被动多轴差分吸收光谱(MAX-DOAS)技术监测痕量气体垂直廓线的光学遥感方法。研究中MAX-DOAS测量多个角度的斜柱浓度、结合大气辐射传输模型,利用最优估算法反演出痕量气体垂直廓线,并对最优估算法参数选取和反演评估进行了详细描述。将该技术应用于合肥地区NO2垂直廓线的监测:通过与长光程差分吸收光谱仪的测量结果对比,相关系数达到0.80。该技术为大气环境立体监测提供了一种简便的方法。     

Gradient Profile Estimation Using Exponential Cubic Spline Smoothing in a Bayesian Framework

Attaining reliable gradient profiles is of utmost relevance for many physical systems. In many situations, the estimation of the gradient is inaccurate due to noise. It is common practice to first estimate the underlying system and then compute the gradient profile by taking the subsequent analytic derivative of the estimated system. The underlying system is often estimated by fitting or smoothing the data using other techniques. Taking the subsequent analytic derivative of an estimated function can be ill-posed. This becomes worse as the noise in the system increases. As a result, the uncertainty generated in the gradient estimate increases. In this paper, a theoretical framework for a method to estimate the gradient profile of discrete noisy data is presented. The method was developed within a Bayesian framework. Comprehensive numerical experiments were conducted on synthetic data at different levels of noise. The accuracy of the proposed method was quantified. Our findings suggest that the proposed gradient profile estimation method outperforms the state-of-the-art methods.     

Qubit-Based Clock Synchronization for QKD Systems Using a Bayesian Approach

Quantum key distribution (QKD) systems provide a method for two users to exchange a provably secure key. Synchronizing the users’ clocks is an essential step before a secure key can be distilled. Qubit-based synchronization protocols directly use the transmitted quantum states to achieve synchronization and thus avoid the need for additional classical synchronization hardware. Previous qubit-based synchronization protocols sacrifice secure key either directly or indirectly, and all known qubit-based synchronization protocols do not efficiently use all publicly available information published by the users. Here, we introduce a Bayesian probabilistic algorithm that incorporates all published information to efficiently find the clock offset without sacrificing any secure key. Additionally, the output of the algorithm is a probability, which allows us to quantify our confidence in the synchronization. For demonstration purposes, we present a model system with accompanying simulations of an efficient three-state BB84 prepare-and-measure protocol with decoy states. We use our algorithm to exploit the correlations between Alice’s published basis and mean photon number choices and Bob’s measurement outcomes to probabilistically determine the most likely clock offset. We find that we can achieve a 95 percent synchronization confidence in only 4140 communication bin widths, meaning we can tolerate clock drift approaching 1 part in 4140 in this example when simulating this system with a dark count probability per communication bin width of 8×10−4 and a received mean photon number of 0.01.     

基于多层感知器网络的FTIR高光谱数据温度和发射率光谱同步反演

文章以土壤为例,首先指出了典型的温度反射率分离算法由高光谱FTIR数据反演温度和发射率的局限; 当地物出射能量的真值和地物真实温度对应的黑体辐射在数值上的差别与仪器的噪声等效光谱辐射亮度在相同的数量级上时,产生奇异发射率的概率很大, 野外测量时这种现象在714和1 250 cm-1附近经常发生。针对这个局限,构建了一个三层的感知器(MLP)网络,利用ASTER光谱库中的土壤发射率光谱生成训练样本,MODIS光谱库中的土壤发射率光谱生成测试样本,对网络进行训练和测试,取得了比较好的结果。同时利用光谱平滑迭代算法(ISSTES)由测试样本反演土壤的温度和发射率,并与MLP方法的结果进行比较,MLP方法反演的土壤发射率精度在可接受的范围之内,略低于ISSTES算法,MLP方法的优点在于,它能够克服典型的温度发射率算法的局限,可以作为典型的温度发射率分离算法有益的补充。     

Thickness and Surface Profile Measurement by a Sinusoidal Wavelength-Scanning Interferometer

We propose a sinusoidal wavelength-scanning interferometer for measuring thickness and surface profile of a thin film. The interference signal contains phase modulation amplitude Z and phase $aL which are related to the positions and profiles of the reflecting surfaces, respectively. By reducing the difference between the detected signal and the estimated signal using the multidimensional nonlinear least-squares algorithm, we estimate values of Z and $aL. Experimental results show that the front and rear surfaces of a silica glass plate of 20 $mUm-thickness could be measured with an error less than 10 nm.     

热红外遥感图像中云覆盖像元地表温度估算研究进展

地表温度是描述陆表过程和反映地表特征的重要参数。及时掌握区域和全球尺度上的地表温度时空分布是许多地表过程研究和热红外遥感应用的必需。热红外遥感是地表温度快捷获取的最佳手段,但仅局限于天空晴朗无云情形。云覆盖致使热红外遥感不能直接获取云覆盖像元地表温度,其反演结果为云顶温度或附加了云辐射强迫效应后的地表温度。如何精准获取热红外遥感图像中云覆盖像元地表温度信息,成为热红外遥感地表温度反演和应用亟待完善的难题。文章系统详细回顾了国内外热红外遥感图像中云覆盖像元地表温度估算方法,评述了各方法的特性,并指出今后应加强加深热红外遥感与被动微波遥感融合技术、数据同化技术、尺度效应和算法参数化中普适性假定等四方面研究。     

Retrieving angular distributions of high-order harmonic generation from a single molecule

We present a novel method to retrieve angular distributions of high-order harmonic generation from a single molecule. This technique uses an iterative procedure based only on experimental results of time and angle-dependent harmonic signals, and no actual shape of molecular orbital is assumed. The molecular axis distribution in a target gas can simultaneously be deduced in this procedure. The angle-dependent signal retrieved for a single N2 and O2 molecule is demonstrated to reflect the highest occupied molecular orbital, excluding the ambiguity due to the imperfect alignment.     

Using a Millimeter-Wave Meteoradar for Measurement of the Atmospheric Temperature Profile

We consider a method of radio-acoustic sounding of the atmosphere using millimeter-wave radars based on powerful masers (gyrotrons) operated in the regime of intrapulse chirp modulation. The proposed method makes it possible to measure the atmospheric temperature profile without any modification of the meteoradar transceiving system and to improve significantly the capabilities of remote monitoring of the atmosphere.     

An Entropy-Based Approach to Measurement of Stock Market Depth

The aim of this study is to investigate market depth as a stock market liquidity dimension. A new methodology for market depth measurement exactly based on Shannon information entropy for high-frequency data is introduced and utilized. The proposed entropy-based market depth indicator is supported by an algorithm inferring the initiator of a trade. This new indicator seems to be a promising liquidity measure. Both market entropy and market liquidity can be directly measured by the new indicator. The findings of empirical experiments for real-data with a time stamp rounded to the nearest second from the Warsaw Stock Exchange (WSE) confirm that the new proxy enables us to effectively compare market depth and liquidity for different equities. Robustness tests and statistical analyses are conducted. Furthermore, an intra-day seasonality assessment is provided. Results indicate that the entropy-based approach can be considered as an auspicious market depth and liquidity proxy with an intuitive base for both theoretical and empirical analyses in financial markets.     

A Two-Stage Approach for Bayesian Joint Models of Longitudinal and Survival Data: Correcting Bias with Informative Prior

Joint models of longitudinal and survival outcomes have gained much popularity in recent years, both in applications and in methodological development. This type of modelling is usually characterised by two submodels, one longitudinal (e.g., mixed-effects model) and one survival (e.g., Cox model), which are connected by some common term. Naturally, sharing information makes the inferential process highly time-consuming. In particular, the Bayesian framework requires even more time for Markov chains to reach stationarity. Hence, in order to reduce the modelling complexity while maintaining the accuracy of the estimates, we propose a two-stage strategy that first fits the longitudinal submodel and then plug the shared information into the survival submodel. Unlike a standard two-stage approach, we apply a correction by incorporating an individual and multiplicative fixed-effect with informative prior into the survival submodel. Based on simulation studies and sensitivity analyses, we empirically compare our proposal with joint specification and standard two-stage approaches. The results show that our methodology is very promising, since it reduces the estimation bias compared to the other two-stage method and requires less processing time than the joint specification approach.     

Profile of a fiber from backscattering measurements

The angular positions of the light-scattering minima obtained from structures placed on flat substrates are closely related to the geometry of the scattering object. We show how the profile of a fiber can be determined, and possible irregularities located, by measurement of the backscattering patterns. An approximate double-interaction model is used to fit the results.     

逐差方法处理数据的误差计算

以杨氏模量实验为例阐述2种不同的数据逐差法的误差计算方法。