Airborne hyperspectral imaging for estimating acorn yield based on the PLS B-matrix calibration technique

Alternate bearing of acorn is a well-marked yield variability phenomenon in forest production. In Japan, this phenomenon is also related to wildlife management (e.g. of animals such as wild pigs, that rely on acorn as their major feed source). Effective management of animals dependent on acorn will require accurate estimation of acorn yield at an early stage. In this paper, we proposed a way to estimate acorn yield from the canopy reflectance values of individual trees. Using an Airborne Imaging Spectrometer for Application (AISA) Eagle System, hyperspectral images in 72 visible and near-infrared wavelengths (407–898 nm) were acquired over an acorn forest in Japan 10 times over three consecutive years (2003–2005) during the early acorn growing season. The canopy spectral reflectance values for individual trees at each wavelength were extracted from the images, and important wavelengths were determined as estimating factors by the B-matrix technique based on partial least squares (PLS) analysis. Yield-estimating models were then developed by multiple linear regression (MLR). Three models obtained from images acquired on June 27 in 2003, July 13 in 2004 and June 21 in 2005 estimated acorn yield well in comparison with ground truth, indicating that the procedure has considerable potential. The study also demonstrated the B-matrix technique based on PLS analysis to be reliable and efficient in identifying important wavelengths for determining suitable estimating factors that best contribute to the estimation model.     

Gene expression data classification using consensus independent component analysis

We propose a new method for tumor classification from gene expression data, which mainly contains three steps. Firstly, the original DNA microarray gene expression data are modeled by independent component analysis （ICA）. Secondly, the most discriminant eigenassays extracted by ICA are selected by the sequential floating forward selection technique. Finally, support vector machine is used to classify the modeling data. To show the validity of the proposed method, we applied it to classify three DNA microarray datasets involving various human normal and tumor tissue samples. The experimental results show that the method is efficient and feasible.     

环青海湖地区天然草地时序光谱特征参量分析

获取了环青海湖地区4类主要天然草地2003年5~10月共16个时相的地面高分辨率光谱数据,并利用植被指数技术、导数光谱技术、植被光谱维特征提取模型及包络线归一化技术提取了多个光谱特征参量,通过对各参量在生育期内分布规律的分析,给出了能较好地表征草地生长发育规律时序特征参量的具体分布;最后计算了4类天然草地各时序特征参量的平均散度,结果表明黄边位置λY、红边位置λV、红边斜率SV、绿峰半高宽wλG、红谷半高宽wλR、去包络红谷净面积AR'和归一化植被指数NDV I对于天然草地分类更有效。     

适于癌基因表达数据集的新特征提取标准NFEC及其分类新算法研究

癌基因表达数据集具有小样本、高维数之特点,一般的机器学习机难以对其有效分类。因此,通常需要采用某些特征提取度量标准来进行降维处理。可是常用的一些特征提取度量标准亦会导致分类效果欠佳之问题。依据微分容量控制学习机DCCM,提出了一个新的特征提取度量标准NFEC,然后依据NFEC和DCCM,提出了适于癌基因表达数据集的特征提取算法DCCFE。实验表明,新的度量NFEC和新的特征提取算法DCCFE较之现有方法对癌基因表达数据集分类时更为有效。本文的工作意义在于:(1)提出了一个新的更有意义的特征提取度量标准;(2)DCCM可以采用比核函数更为一般的一阶可微函数,因而提出的新的特征提取算法更具普遍应用意义。     

Technical note: standardized and semiautomated Harris lines detection

Arrest in long bone growth and the subsequent resumption of growth may be visible as radiopaque transverse lines in radiographs (Harris lines, HL; Harris, HA. 1933. Bone growth in health and disease. London: Oxford University Press). The assessment of individual age at occurrence of such lines, as part of paleopathological skeletal studies, is time-consuming and shows large intra- and interobserver variability. Thus, a standardized, automated detection algorithm would help to increase the validity of such paleopathological research. We present an image analysis application facilitating automatic detection of HL. On the basis of established age calculation methods, the individual age-at-formation can be automatically assessed with the tool presented. Additional user input to confirm the automatic result is possible via an intuitive graphical user interface. Automated detection of HL from digital radiographs of a sample of late Medieval Swiss tibiae was compared to the consensus of manual assessment by two blinded expert observers. The intra- and interobserver variability was high. The quality of the observer result improved when standardized detection criteria were defined and applied. The newly developed algorithm detected two-thirds of the HL that were identified as consensus lines between the observers. It was, however, necessary to validate the last one-third by manual editing. The lack of a large test series must be noted. The application is freely available for further testing by any interested researcher.     

豌豆根瘤脂质体的分布及形态特征

豌豆根瘤中有大量的脂质体,广泛分布于非侵染细胞和侵染细胞内,它既可以存在细胞质中,也可位于液泡里面。有时单个存在,有时又多个聚集在一起。非侵染细胞与侵染细胞相比,前者中的脂质体明显多于后者。这些脂质体近似圆形或椭圆形,表面无膜,电子密度较高,内部无固定的结构,常有一些细胞器位于它的附近。讨论了脂质体的细胞发育及细胞种类的关系。     

On Model-Choice in Discrimination with Categorical Variables

An algorithm for model selection in discrimination with categorical variables is presented. It is based on four models applied hierarchically and linked with a build-up procedure of feature-selection. The choice of models and features is ensured by a consequent cross-validation. Results of an application in medical diagnostics are described.     

Behavioral signatures of structured feature detection during courtship in Drosophila

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基于间隔二肽组分和递归特征消除法的DNA结合蛋白的鉴定

DNA结合蛋白(DNA-binding proteins,DBPs)的鉴定在原核和真核生物的基因和蛋白质功能注释研究中具有十分重要的意义.本研究首次运用间隔二肽组分(gapped-dipeptide composition,Gap DPC)结合递归特征消除法(recursive feature elimination,RFE)鉴定DBPs.首先获得待测蛋白质氨基酸序列的位置特异性得分矩阵(position specific scoring matrix,PSSM),在此基础上提取蛋白质的Gap DPC特征,通过RFE法选择最优特征,然后利用支持向量机(support vector machine,SVM)作为分类器,在蛋白质序列数据集PDB396和LB1068中进行夹克刀交叉验证(jackknife cross validation test).研究结果显示,基于PDB396和LB1068数据集,DBPs预测的准确率、Matthews相关系数、敏感性和特异性分别达到93.43%、0.86、89.04%和96.00%,以及86.33%、0.73、86.49%和86.18%,明显优于文献报道中的相关方法,为DBPs的鉴定提供了新的模型.