Data acquisition in the EUDET project

The goal of the EUDET project is the development and construction of infrastructure to permit detector R&D for the international linear collider (ILC) with larger scale prototypes. It encompasses major detector components: the vertex detector, the tracker and the calorimeters. We describe here the status and plans of the project with emphasis on issues related to data acquisition for future test beam experiments.      

On stochastic parameter estimation using data assimilation

Data assimilation-based parameter estimation can be used to deterministically tune forecast models. This work demonstrates that it can also be used to provide parameter distributions for use by stochastic parameterization schemes. While parameter estimation is (theoretically) straightforward to perform, it is not clear how one should physically interpret the parameter values obtained. Structural model inadequacy implies that one should not search for a deterministic “best” set of parameter values, but rather allow the parameter values to change as a function of state; different parameter values will be needed to compensate for the state-dependent variations of realistic model inadequacy. Over time, a distribution of parameter values will be generated and this distribution can be sampled during forecasts. The current work addresses the ability of ensemble-based parameter estimation techniques utilizing a deterministic model to estimate the moments of stochastic parameters. It is shown that when the system of interest is stochastic the expected variability of a stochastic parameter is biased when a deterministic model is employed for parameter estimation. However, this bias is ameliorated through application of the Central Limit Theorem, and good estimates of both the first and second moments of the stochastic parameter can be obtained. It is also shown that the biased variability information can be utilized to construct a hybrid stochastic/deterministic integration scheme that is able to accurately approximate the evolution of the true stochastic system.     

Adaptive modeling, adaptive data assimilation and adaptive sampling

For efficient progress, model properties and measurement needs can adapt to oceanic events and interactions as they occur. The combination of models and data via data assimilation can also be adaptive. These adaptive concepts are discussed and exemplified within the context of comprehensive real-time ocean observing and prediction systems. Novel adaptive modeling approaches based on simplified maximum likelihood principles are developed and applied to physical and physical–biogeochemical dynamics. In the regional examples shown, they allow the joint calibration of parameter values and model structures. Adaptable components of the Error Subspace Statistical Estimation (ESSE) system are reviewed and illustrated. Results indicate that error estimates, ensemble sizes, error subspace ranks, covariance tapering parameters and stochastic error models can be calibrated by such quantitative adaptation. New adaptive sampling approaches and schemes are outlined. Illustrations suggest that these adaptive schemes can be used in real time with the potential for most efficient sampling.     

The k-means range algorithm for personalized data clustering in e-commerce

This paper describes the k-means range algorithm, a combination of the partitional k-means clustering algorithm with a well known spatial data structure, namely the range tree, which allows fast range searches. It offers a real-time solution for the development of distributed interactive decision aids in e-commerce since it allows the consumer to model his preferences along multiple dimensions, search for product information, and then produce the data clusters of the products retrieved to enhance his purchase decisions. This paper also discusses the implications and advantages of this approach in the development of on-line shopping environments and consumer decision aids in traditional and mobile e-commerce applications.     

时域压缩合成孔径超分辨水声成像算法

提出一种针对水下稀疏目标的时域压缩合成孔径声呐成像方法(TC-SAS),实现了水声目标高分辨实时成像。通过多子阵的孔径合成,在时域上构造出成像网格格点到有效孔径内逐帧阵列的格林函数,并给出成像区域散射强度到数据域的映射矩阵;然后利用该区域空域稀疏的先验知识,通过正交匹配追踪的稀疏重构方式,解算出成像区域散射系数矩阵,实现了稀疏目标高分辨成像.同时,针对线性调频信号提出数据缩减的方法,通过对观测数据和字典矩阵同时脉压后截取,减小了数据规模;进一步结合二维矩阵数表查表的方法,以空间换时间,实现了区块实时成像。数值仿真以及湖试试验表明,所提算法能分辨出传统的时延求和算法难以分辨的目标,并且在图像清晰度指标上平均提升4.9 dB.改善了合成孔径声呐的成像质量.     

A statistical study of the analysis of congested spectra by total spectrum fitting

Heavily overlapped, or congested spectra often display much structure but few individual “lines.” Methods have been devised for analyzing such spectra through nonlinear least-squares fitting of the intensity as a function of wavelength or wavenumber. Such total spectrum fitting (TSF) methods are examined statistically for a simple diatomic model and compared with the standard “measure-assign-fit” (MAF) approach in use since the dawn of spectroscopy. Monte Carlo computations on typically 1000 synthetic spectra at a time verify that the predictions of the variance-covariance matrix are reliable under many circumstances. However in regions where the P and R branches double up, the predicted standard errors in the key spectroscopic constants rise sharply and greatly exceed estimates from the Monte Carlo ensemble statistics. In the same regions, the MAF method actually gives better precision. However, for imperfectly overlapped R and P branches, the MAF standard errors are typically three times larger than the TSF values; moreover, the MAF statistical errors are dwarfed by bias. The TSF approach, while clearly superior in these tests, has a practical drawback: it, too, can give significant bias if the spectra are analyzed with an incorrect model, as illustrated here through calculations employing the wrong function to describe the spectral lineshape.     

用于新一代高密度可录光盘的有机材料研究进展

本文在总结近几年来国内外文献和专利报道的最新研究成果基础上,简要阐述了新一代高密度可录光盘的数据存储机理以及激光器工作波长与有机材料薄膜最大吸收波长相匹配的要求,介绍了在蓝(紫)光波段内(350～400nm)具有显著吸收的有机材料研究概况,并讨论了这些有机材料作为新一代高密度可录光盘数据存储介质的可能性。最后,对有机材料用于新一代高密度可录光盘数据存储介质的研究重点以及今后的发展前景进行简要讨论和展望。     

基于SMAA和公共权重的决策单元效率评价与排序

在数据包络分析(DEA)中,公共权重模型是决策单元效率评价与排序的常用方法之一。与传统DEA模型相比,公共权重模型用一组公共的投入产出权重评价所有决策单元,评价结果往往更具有区分度且更为客观。本文考虑决策单元对排序位置的满意程度,提出了基于最大化最小满意度和最大化平均满意度两类新的公共权重模型。首先,基于随机多准则可接受度分析(SMAA)方法,计算出每个决策单元处于各个排名位置的可接受度;然后,通过逆权重空间分析,分别求得使最小满意度和平均满意度最大化的一组公共权重;最后,利用所求的公共权重,计算各决策单元的效率值及相应的排序。算例分析验证了本文提出的基于SMAA的公共权重模型用于决策单元效率评价与排序的可行性。     

Data fusion methodologies for food and beverage authentication and quality assessment – A review

The ever increasing interest of consumers for safety, authenticity and quality of food commodities has driven the attention towards the analytical techniques used for analyzing these commodities. In recent years, rapid and reliable sensor, spectroscopic and chromatographic techniques have emerged that, together with multivariate and multiway chemometrics, have improved the whole control process by reducing the time of analysis and providing more informative results. In this progression of more and better information, the combination (fusion) of outputs of different instrumental techniques has emerged as a means for increasing the reliability of classification or prediction of foodstuff specifications as compared to using a single analytical technique. Although promising results have been obtained in food and beverage authentication and quality assessment, the combination of data from several techniques is not straightforward and represents an important challenge for chemometricians. This review provides a general overview of data fusion strategies that have been used in the field of food and beverage authentication and quality assessment.     

不同部位矿质元素与红外光谱数据融合对美味牛肝菌产地溯源研究

野生食用菌产地溯源研究中,采用单一有机成分或矿质元素指纹存在一定局限性。利用不同指纹分析技术的互补性与协同性,将不同部位与类型的化学信息进行融合,探讨此方法对野生食用菌产地溯源的可行性,以期为野生食用菌溯源提供新的思路与科学依据。通过测定云南7个产地、124个美味牛肝菌(菌柄、菌盖)中15种矿质元素的含量,以及子实体傅里叶变换红外光谱(FTIR)。标准正态变换(SNV)、二阶导数(2D)等算法对原始光谱进行预处理。基于低级与中级数据融合策略,将预处理后的FTIR光谱与菌柄、菌盖矿质元素数据进行融合,结合支持向量机(SVM)分别建立菌柄、菌盖、FTIR、低级数据融合(菌柄+菌盖,菌柄+菌盖+FTIR)与中级数据融合(菌柄+菌盖+FTIR)判别模型;分析比较模型参数,确定快速甄别美味牛肝菌产地的可靠方法。结果显示：(1)菌盖中Cd,Cr,Cu,Li,Mg,Na,P和Zn元素平均含量高于菌柄,Ba,Ca,Co,Ni,Rb,Sr和V元素在菌柄中平均含量高于菌盖。美味牛肝菌中人体必需矿质元素Ca,Cu,Mg,P和Zn平均含量远高于小麦、水稻干品和新鲜蔬菜,与动物干制品含量相似;(2)FTIR光谱数据最佳预处理方法为3D+SNV,其Q2和R2Y分别为76.64%,88.91%;(3)菌柄、菌盖、FTIR、低级数据融合与中级数据融合SVM模型,c值分别为8 192,4 096,1.414 2,11.313 7,1和0.7071 1,菌柄和菌盖模型c值较大,表明采用单一菌柄或菌盖矿质元素含量数据,SVM训练存在过拟合风险,判别效果较差;(4)FTIR、低级数据融合和中级数据融合SVM模型,样品分类错误总数分别为7,9,7和0,中级数据融合(菌柄+菌盖+FTIR)模型样品分类正确率最高。表明基于中级融合策略将不同部位矿物元素和子实体FTIR光谱数据融合,可作为野生食用菌产地溯源的一种有效方法。