核诱导距离度量的鲁棒典型相关分析

典型相关分析(canonical correlation analysis,CCA)是寻找同一对象两组变量间线性相关性的一种常用的多元统计分析方法,其采用的欧氏距离度量方式导致了算法的非鲁棒性。核诱导的距离度量不仅在理论上被证明是鲁棒的,而且在(聚类)应用上获得了有效验证。将其进一步应用于CCA,发展出了核诱导距离度量的鲁棒CCA(CCA based on kernel-induced measure,KI-CCA)。该算法不仅克服了CCA非鲁棒的不足,而且使现有基于最大相关熵的鲁棒主成分分析(half-quadratic principal component analysis,HQ-PCA)成为特例,且具有非线性相关分析的能力。一方面,核的多样性使得KI-CCA也具有多样性,从而使其成为一般性的分析算法。另一方面,与CCA刻画上的相似性,使其求解可归结为广义特征值问题。在人工数据、多特征手写体数据库(multiple feature database,MFD)和人脸数据集(Yale、AR、ORL)上的实验验证了该算法的有效性。     

氧化铝对水体中重金属离子吸附去除研究

以木材防腐剂CCA中的重金属铬、砷和铜为研究对象,评价了氧化铝对3种重金属的同时吸附去除效果,并对3种重金属在氧化铝上相互作用机理进行了探讨.结果表明,铬对氧化铝去除砷和铜均无显著影响;砷显著抑制氧化铝对铬的去除,但促进铜的去除;铜促进氧化铝对铬和砷的去除;铬主要通过外层作用(静电吸附,离子交换等方式)吸附在氧化铝的表面上;而砷主要通过内层吸附(专性吸附)在氧化铝的表面上,因而引起氧化铝的等电点朝较低的pH移动;铜主要通过专性吸附和沉淀作用得以去除.总体上,在中性环境下,氧化铝对3种重金属可同时具有较好的去除效果.     

Formation of metal agglomerates during carbonisation of chromated copper arsenate (CCA) treated wood waste: Comparison between a lab scale and an industrial plant

This paper compares the results obtained by scanning electron microscopy coupled to X-ray analysis (SEM-EDXA) of the solid product after carbonisation of treated wood waste in a lab scale and in an industrial installation. These setups (lab scale and industrial) are characterized by different operating conditions of the carbonisation process. Moreover, the wood waste input to the processes differs significantly. From this study, it is clear that some similarities but also some differences exist between the lab scale study and the study with the industrial Chartherm plant. In both reactors, a metal (and mineral) agglomeration process takes place, even in the case of untreated wood. The agglomerates initially present in the wood input may serve as a seed for the metal agglomeration process during "chartherisation". The industrial setup leads to a broader range of agglomerates' size (0.1-50 microm) and composition (all possible combinations of Cu, Cr, As and wood minerals). Some agglomerates contain the three metals but the major part is a combination of wood minerals and one or two of the three preservative metals, while all agglomerates analysed in the lab scale product contain the three metals. The separate influence of wood input characteristics and process conditions cannot be derived from these experiments, but the observations suggest that the higher the CCA retention in the wood input is, the easier is the metal agglomeration process during chartherisation of CCA treated wood waste. From the analyses performed in this study it seems that copper behaves differently in the sense that it agglomerates easily, but the resulting particles are small (<1 microm).     

柳河大米产地环境及其矿物元素分布特征的典范对应分析

为筛选稳定可靠的柳河大米产地确证元素,通过2 次典范对应分析研究影响吉林省柳河大米采样点分布的环境因子,分析大米产地确证元素在区域尺度内的影响关系及其稳定性。典范对应分析结果表明,2 个环境梯度轴分别解释大米矿物元素含量总方差的17.3%和23.4%,柳河大米矿物元素含量和环境变量之间存在较强的空间相关性,受产地环境变量影响最大的为Se元素,Ca、Zn、Mg含量受其影响最小,Mg、Ca、Na、Mn、Zn具有较好的稳定性和空间代表性,可作为柳河大米产地确证的指标元素。研究结果为建立柳河大米确证模型提供有效的理论依据。     

基于多视图典型相关分析的垃圾网页检测

首先将垃圾网页特征分为两个不同的视图, 即基于内容特征的视图和基于链接特征的视图, 利用典型相关分析及其相关改进方法进行特征提取, 生成两组新的特征; 再对新生成的两视图特征采用不同组合方式产生单视图数据, 并用这组数据作为训练数据构建分类算法。实验结果表明, 将垃圾网页看成两视图数据, 并应用多视图典型相关分析技术, 可有效提高垃圾网页的识别精度。     

Cu, Cr and As distribution in soils adjacent to CCA-treated utility poles in Eastern Blacksea Region of Turkey

In this study, the main objective was to asses the distribution of Cu, Cr, and As in soils adjacent to CCA-treated utility poles in Eastern Blacksea Region of Turkey (Trabzon, Rize and Artvin ) and determine the influence of soil composition.

Surface (0–5 cm) and subsurface soil samples (30–40 cm) were collected near CCA-treated utility poles and control soil samples away from CCA-treated utility poles were also collected. Water holding capacity, pH and mechanical properties of soil samples were determined for both depth levels.

Results showed that Cu, Cr and As concentration in soil samples taken from all three cities in 0–5 cm depth was higher than soil samples taken from 30–40 cm depth. Cu, Cr and As concentrations were much higher in soil samples taken from city of Rize     

Metal contamination at a wood preservation site: characterisation and experimental studies on remediation

The aim of this investigation was to determine the occurrence of As, Cu, Cr and Zn in the soil at an abandoned wood preservation unit and to examine some possible extractants for the contaminants in the soil. The mean As content of the contaminated surface soils (0-10 cm) was 186 mg kg(-1), where as the mean concentrations of Cu, Cr and Zn in soils from the contaminated area were 26, 29 and 91 mg kg(-1), respectively. The elevated As content in the mineral soils is related to adsorption of inorganic As phases in the fine grained fractions, which are characterised by large surface area and high positive surface charge under the current acidic conditions. Cu and Cr were found to be rather mobile, which is reflected in their lower abundance in soils and significant accumulation in sediments in the drainage leaving the area. The fine fraction of the soil (<0.125 mm) has an average metal content increased by nearly 34% as compared to the <2-mm fraction conventionally used for the analysis and assessment of soil contamination. The <2-mm fraction constitutes approximately 65% of the total weight while the fine fraction (<0.125 mm) constitutes approximately 10%. These facts, taken together, are essential for the choice of remediation measures. Oxalate solutions have been tested as extractants for soil remediation. Dark acid oxalate extraction dissolves the amorphous Al- and Fe-oxides and hydroxides and mobilises the adsorbed inorganic As species. Oxalate also acts as a ligand for the cationic heavy metals, releasing them from exchangeable sites. With a three-step sequential leaching, up to 98-99% of the metals could be removed. At lower concentrations and higher pH, the leaching decreased to approximately 70%.     

Low grade thermal energy sources and uses from the process industry in the UK

Thermal energy loss in the process industry is a significant issue due to the high temperatures and multiple heat intensive processes involved. High-grade thermal energy is typically recovered within processes. However, lower grade heat is often rejected to the environment.The benefits of capturing and utilising low grade thermal energy are highly dependent on the qualities and properties of the heat in the waste streams. The temperature of the low grade heat stream is the most important parameter, as the effective use of the residual heat or the efficiency of energy recovery from the low grade heat sources will mainly depend on the temperature difference between the source and a suitable sink, e.g. another process or space heating/cooling. In general, the temperatures of these waste heat sources are too low to produce electricity and direct heat use will depend on whether potential user can be found.This paper presents past and current drivers for heat recovery studies. High and low grade heat sources are defined according to the viability of recovery within the processes. Firstly, high grade heat capture within the processes is reviewed. Then, the focus is on the potential for low grade heat capture outside of the original plant. The paper addresses the potential for low grade heat recovery with regard to new incentives and technological advances. Finally, different aspects which influence the decision making for low grade heat recovery in the process industry are discussed. It is concluded that organisational, financial and economic barriers might be overcome and benefits from a holistic vision could be gained with stronger governmental policy and regulation incentives.     

多彩色空间相关分析的人脸识别算法

人脸识别是当前人工智能和模式识别的研究热点,得到了广泛的关注.基于对不同色彩空间数据的分析,论文提出了多彩色空间典型相关分析的人脸识别方法.文中对2维的Contourlet变换特性进行了分析和讨论,利用Contourlet的多尺度,方向性和各向异性等特点,提出了一种基于Contourlet变换的彩色人脸识别算法.算法对原图进行Contourlet分解,对分解得到的低频和高频图像进行cca分析.典型相关分析是一种有效的分析方法,其实际应用十分广泛.低频系数反映图像的轮廓信息,高频系数反映图像的细节信息,使用cca充分利用不同频率的信息,使不同色彩空间的不同分辨率图形的相关性达到最大,得到投影系数,最后,采用决策级最近邻分类器完成人脸识别.在对彩色人脸数据库AR的识别实验中,该算法识别率达到98％以上,与传统算法相比,该算法不仅既有良好的识别结果,而且具有很快的运算速度.     

日地空间信息分布式协同高性能计算框架

以日地系统活动规律研究为背景,基于美国新近提出的应用于大规模科学计算领域的组件规范CCA（Common Component Architecture）,设计提出了日地空间信息分布式协同高性能计算框架DCHF-SI,它集物理模型组件化封装、模拟应用的构建和管理、模型互操作、分布式容错和计算驾驭可视化等服务于一体,能够充分利用网络集成大量的分布式高性能计算资源和空间物理模型资源来构建多物理松耦合模拟应用,支持日地空间信息的分布式协同高性能计算,解决了多物理耦合模拟的复杂性问题,最终为空间天气预报服务系统提供支持。