Effects of coal rank and reaction conditions upon coprocessing coal with waste tyre

It is well known that the amount of waste tyre increases every year, and a numerous amount of waste tyre is landfilled or dumped all over the world, which causes environmental problems, such as destruction of natural places and the risk of fires. Coprocessing waste tyre and coal is considered as one of the effective processing methods of both materials. Upon coprocessing lower rank coal (Wyoming, C; 68%) with waste tyre, the synergistic effects to upgrading, such as the increase of oil yield and the decrease of residue yield, were appeared. However, the synergistic effects were not observed on coprocessing two kinds of higher rank coals with waste tyre. The reactions of coal with benzophenone were carried out to discuss the hydrogen donatability of coal. Conversion of benzophenone to diphenylmethane on the reaction with Wyoming coal was higher than those of higher rank coals. Accordingly, it was considered that the synergistic effects to upgrading upon coprocessing Wyoming coal with waste tyre were obtained owing to the enhancement of stabilization of radicals from tyre and Wyoming coal through the hydrogen donation from both tyre and Wyoming coal. The effects of reaction temperature and the amount of solvent upon coprocessing Wyoming coal with waste tyre were also discussed in this study.     

Beliefs about birth rank and their reflection in reality.

Beliefs about birth rank reflect what the society regards as social reality, and they may also influence that reality. Three studies found that people believe those with different birth ranks differ in their personalities, that higher birth ranks are likely to attain higher occupational prestige, and that the personality characteristics attributed to the various birth ranks favor the actual attainment of higher occupational prestige. In one example of such beliefs, firstborns were rated as most intelligent but least creative whereas the opposite was true of last-borns. The 4th study found that those with higher birth ranks in fact attain more prestigious occupations and actually do complete more years of schooling. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A note on iterative marginal optimization: a simple algorithm for maximum rank correlation estimation

The maximum rank correlation (MRC) estimator was originally studied by Han [1987. Nonparametric analysis of a generalized regression model. J. Econometrics 35, 303-316] and Sherman [1993. The limiting distribution of the maximum rank correlation estimator. Econometrica 61, 123-137] from the econometrics point of view, and most recently attracted much attention from the classification literature due to its close relationship with the receiver operating characteristics (ROC) curve [Baker, 2003. The central role of receiver operating characteristics (ROC) curves in evaluating tests for the early detection of cancer. J. Nat. Cancer Inst. 95, 511-515; Pepe, 2003. The Statistical Evaluation of Medical Tests for Classification and Prediction. Oxford University Press, Oxford; Pepe et al., 2004. Combining predictors for classification using the area under the ROC curve. University of Washington Biostatistics Working Paper Series]. Compared with its nice theoretical properties and successful applications, the MRC estimator's computational aspects are not trivial. This is because the MRC objective function is neither smooth nor continuous. Therefore, the traditional Newton-Raphson type algorithm cannot be used to find the MRC estimator. As an easy solution, we propose in this article a very simple fitting algorithm named iterative marginal optimization (IMO), which guarantees a monotone increasing of the MRC objective function at each iteration step in a very efficient manner. We show via extensive simulation that the proposed IMO algorithm is not only computationally stable but also reasonably fast. Moreover, real data about the China stock market are analyzed to further illustrate the usefulness of the proposed.     

Fast Implementation of Two-Dimensional APES and CAPON Spectral Estimators

The matched-filterbank spectral estimators APES and CAPON have recently received considerable attention in a number of applications. Unfortunately, their computational complexity tends to limit their usage in several cases – a problem that has previously been addressed by different authors. In this paper, we introduce a novel approach to the computation of the APES and CAPON spectra, which leads to a computational method that is considerably faster than all existing techniques. The new implementations of APES and CAPON are called fast APES and fast CAPON, respectively, and are developed for the two-dimensional case, with the one-dimensional case as a special case. Numerical examples are provided to demonstrate the application of APES to synthetic aperture radar (SAR) imaging, and to illustrate the reduction in computational complexity provided by our method.     

基于最大秩距离码的两种Rao-Nam方案

基于最大秩距离码，提出两种新的Rao-Nam方案，讨论了它们的可行性及安全性，并证明了它们比基于纠错码的Rao-Nam方案更安全。     

西山煤田不同变质程度煤孔隙结构分形特征及影响因素研究

为研究煤的多孔介质属性及其分形特征,以山西沁水盆地西山煤田为研究对象,采用扫描电镜(SEM)分析了煤表面孔隙结构特征。基于SEM图片,通过盒维数法计算得到了不同煤样表面孔隙分形维数,并分析了其影响因素。研究结果表明:煤表面具有显著的分形特征,分形理论能够较好地描述煤孔隙结构复杂程度;在本测试煤样中,不同煤样分形维数值在1.33～1.92范围内变化;变质程度、水分、埋深、坚固性系数(f值)对煤孔隙分形维数有显著影响,随Ro和埋深的增加煤体表面孔隙趋于复杂化,分形维数值不断增大;而水分和灰分的存在使得煤体表面变得相对光滑,能够减小分形维数值。分形维数是衡量煤孔隙复杂程度的有效参数,在煤矿现场瓦斯防治中,对于具有高分形维数的煤体,应该引起重视。这类煤体往往破坏程度较高,具有强吸附性,孔隙连通性差,瓦斯抽采困难,在煤炭开采过程中,容易导致煤与瓦斯突出、瓦斯涌出等灾害。     

融合低秩和形态学的高光谱影像特征提取

高光谱遥感影像具有较高的光谱分辨率,能够精细刻画地物的反射光谱,具有很高的地物分类与识别能力. 但高维波段之间通常具有较高的相关性,冗余度高,为影像处理和分析带来负担. 针对高光谱影像特点的特征提取和选择为有效提取信息提供了保障. 提出一种融合低秩和形态学的特征提取方法(MSEMP),利用低秩来精简高光谱影像中的冗余信息,获取秩最小的光谱紧致表达,并在此基础上利用多形态多尺度结构元素提取形态学剖面,获取影像空间特征. 实验对AVIRIS和ROSIS传感器的两组数据进行测试,通过MSEMP提取特征后进行分类实验,可以获得较高的分类结果,证明了低秩和形态学相结合的特征提取方法的有效性.     

二连盆地吉尔嘎朗图凹陷低煤阶煤层气勘探

二连盆地群低煤阶煤层气资源丰富但勘探程度相对较低,煤层气富集和主控因素认识不足,制约了开发实践。以吉尔嘎朗图凹陷为重点,对二连盆地群的构造、沉积、水文、物性和含气量分布进行精细解剖,总结了煤层气富集成藏规律。二连盆地群具有断陷小湖盆和残留盆地的特点,分割性强。煤系主要发育中、下侏罗统阿拉坦合力群及下白垩统巴彦花群赛汉塔拉组两套含煤建造,以辫状河三角洲相为主,煤层层数多且与砂泥岩叠置发育,煤层倾角平缓。针对研究区"浅部低煤阶、平缓厚煤层、多层砂煤组"的特点,建立了符合吉尔嘎朗图"斜坡区正向构造带富集模式",提出在煤层气勘探中应注意优选埋深适中、相对高渗、高含气量的"甜点区",并需要规避断层,在向斜两翼、背斜和单斜地层中寻找高产区。优选部署的吉煤4井在埋深430~470 m煤层段获得大于2 000 m~3/d的产气量,证实中国低含气量、厚煤层的褐煤区煤层气可以获得高产工业气流,有助于推进低煤阶煤层气资源的勘探进程。     

联合低秩与稀疏先验的高光谱图像压缩感知重建

本文建立了一种新的高光谱图像压缩感知重建模型,编码端采用块对角的Noiselet测量矩阵对每一谱带进行独立采样,解码端首先建立高光谱图像低秩稀疏表示模型,分解为低秩与稀疏成分,并对低秩成分在空间维进行稀疏分解,进而构建联合谱间低秩性先验与谱内空间稀疏性先验的凸优化重建模型,并提出模型求解的增广拉格朗日乘子迭代算法,通过引入辅助变量与线性化技巧,使得每一子问题均存在解析解,降低了模型求解的复杂度。实验结果验证了本文模型及其算法的有效性。     

局部归一化融合EW-Gabor特征的光照变化人脸识别

针对光照变化人脸识别问题,提出了一种基于局部归一化融合熵加权Gabor特征方法。首先,计算类熵加权向量;然后,对图像进行局部归一化,并且计算输入图像的Borda计数,从而消除低值Gabor jet比较矩阵;最后,利用投票得分策略和k近邻分类器完成人脸识别。在扩展YaleB和AR人脸数据库上进行实验评估,在AR上的识别率可接近100%,相比其它几种较新的局部特征方法,本文方法取得了更高的识别精度,并且在一定程度上减少了计算开销。