用RAFA方法定量解析芳烃混合物的EEM

本文介绍了降秩因子分析(RAFA)方法,它是从一个多组分混合物中直接定量计算其中某一组分,而不必知道其它组分的物种及含量的一种定量分析的数学方法。它适用于双线性的数据。本实验首先将荧光分光光度计与外接计算机相连,以获得样品的激发-发射矩阵(EEM),再用RAFA方法对蒽、萘、菲、芘、芴、(艹屈)六种标样的一至五组分的混合物进行定量分析,获得满意的结果。     

Comments on “Equivalence of characterizations of fixed models”

In this note we present a proof to the conjecture given in the above paper, and therefore establish the equivalence of characterizations of fixed modes for the general case.     

F_q上矩阵秩的概率分布及其渐近性质

本文给出了Ｆｑ（ｑ为素数）上ｋ×ｎ随机矩阵秩的概率分布，并详细讨论了方阵和高矩阵这两类特别重要的矩阵的秩分布，揭示了这两类矩阵秩分布的渐近性质。     

西江流域压咸风险调度及其时空传递规律研究

枯水期珠江河口咸潮情势日益加重,径流不确定加剧了压咸风险,严重威胁沿线的供水安全。本文基于概率密度分布描述径流不确定性,构建了单源风险调度基本框架。以西江流域五座水库为研究对象,量化了预报误差与压咸风险的响应关系;揭示了压咸风险的时空传递规律;将压咸风险划分为3个等级;确定出各级风险越级传递的临界阈值。研究表明：随预报误差的增大,压咸风险提前且持续天数增加、风险率增大;压咸风险呈逐时段累积和从上游向下游、从支流向干流的时空传递规律;当预报误差超过±16%、±21%时,压咸风险从轻险越级至中险、中险越级至重险。研究成果对于西江流域压咸风险的调控和粤港澳大湾区的供水安全具有重要的应用价值。     

Squaring down of general MIMO systems to invertible uniform rank systems via pre- and/or post-compensators

Pre- and/or post-compensators are designed to square down a general MIMO system to a uniform rank system, the structure of which is almost similar to a SISO system. The method of squaring down either does not change the finite zero structure of the given MIMO system or simply adds additional finite zeros in the left half s-plane. The significance of such a squaring down lies in the simplicity of the structure of a uniform rank system lending itself for easy analysis and control design.     

Uncooperative gait recognition by learning to rank

Gait is a useful biometric because it can operate from a distance and without subject cooperation. However, it is affected by changes in covariate conditions (carrying, clothing, view angle, etc.). Existing methods suffer from lack of training samples, can only cope with changes in a subset of conditions with limited success, and implicitly assume subject cooperation. We propose a novel approach which casts gait recognition as a bipartite ranking problem and leverages training samples from different people and even from different datasets. By exploiting learning to rank, the problem of model over-fitting caused by under-sampled training data is effectively addressed. This makes our approach suitable under a genuine uncooperative setting and robust against changes in any covariate conditions. Extensive experiments demonstrate that our approach drastically outperforms existing methods, achieving up to 14-fold increase in recognition rate under the most difficult uncooperative settings.     

Fisher discrimination based low rank matrix recovery for face recognition

In this paper, we consider the issue of computing low rank (LR) recovery of matrices with sparse errors. Based on the success of low rank matrix recovery in statistical learning, computer vision and signal processing, a novel low rank matrix recovery algorithm with Fisher discrimination regularization (FDLR) is proposed. Standard low rank matrix recovery algorithm decomposes the original matrix into a set of representative basis with a corresponding sparse error for modeling the raw data. Motivated by the Fisher criterion, the proposed FDLR executes low rank matrix recovery in a supervised manner, i.e., taking the with-class scatter and between-class scatter into account when the whole label information are available. The paper shows that the formulated model can be solved by the augmented Lagrange multipliers and provides additional discriminating power over the standard low rank recovery models. The representative bases learned by the proposed method are encouraged to be closer within the same class, and as far as possible between different classes. Meanwhile, the sparse error recovered by FDLR is not discarded as usual, but treated as a feedback in the following classification tasks. Numerical simulations demonstrate that the proposed algorithm achieves the state of the art results.     

基于路由标记的分布式信息检索

文章对分布式信息检索中通常采用的洪泛策略进行分析,发现其容易重复转发相同消息,导致产生大量冗余通信,造成网络拥塞等问题。提出采用基于路由标记的分布式信息检索策略,以减少冗余消息的产生并避免网络拥塞,最后以实例进行两种策略的对比分析,并通过理论推导证明了后者的有效性。     

Maceral and rank influences on the morphology of coal char

Concentrates of vitrinite and inertinite macerals have been pyrolysed in a flame under conditions representative of the initial stages of pulverized coal combustion. Char was distinguished from soot by size analysis and the char yield correlated with the proximate analysis. The char morphology was studied by optical microscopy and quantitative measurements of porosity and pore size were made using image analysis. Vitrinite and inertinite produce chars of characteristic morphology. The softening behaviour of inertinite varies with coal rank and can be related to the optical reflectance. The porosity of vitrinite chars approaches that of inertinite chars at high rank.     

基于未确知数学理论的建筑结构可靠性分析

本文结合结构可靠性评估特点,应用未确知测度、置信度的概念,建立了基于未确知测度的工程结构可靠性评估模型,并结合工程实例,验证该模型在处理大量不确定性影响因素时丢失信息少,得到的评估结果能够客观全面地反映结构可靠性。该评价方法操作相对简单,满足工程需要,更加实用。