基于ICA模式空间的基因分类

ICA是应用于盲源信号分离的一种统计方法。利用ICA对基因微阵列表达谱数据进行分解获得由基因模型谱和对应系数构成的线性谱模型,并在此基础上进行基因分类。由于基于ICA的一个模型谱并不能完整地代表一个具有生物意义的类别,并且模型谱之间不具正交性,在此线性模型下不能有效的表示基因数据,为此提出基于ICA的模式表达空间的概念,并在该模式空间中重新构造了基因的数据表达形式,并利用此表达形式进行基因分类。实验结果表明,该分类方法比线性谱模型下的基因分类具有更高的正确率。

Determination of Melamine by Infrared Spectroscopy Based on Nonlinear Modeling

[Objective] The aim was to develop a nonlinear model of quantitative analysis of melamine content by infrared spectroscopy and provide theoretical basis for the nondestructive detection of melamine. [Method] According to dynamics,mathematical modeling and optimization theory,linear and nonlinear models were respectively set up by taking an absorption peak of 1 550 cm-1 as characteristic absorption peak. [Result] The correlation coefficient of nonlinear model was 0.922 7 and the recovery was 96%,which showed that the nonlinear model was more accurate than linearity model with correlation coefficient of 0.904 9 and recovery of 557%. [Conclusion] It is feasible to determine melamine content by using the nonlinear model quantitatively.

Improvement of Urban Impervious Surface Estimation in Shanghai Using Landsat7 ETM+ Data

This paper explores the potential to improve the impervious surface estimation accuracy using a multi-stage approach on the basis of vegetation-impervious surface-soil (V-I-S) model. In the first stage of Spectral Mixture Analysis (SMA) process, pixel purity index, a quantitative index for defining endmember quality, and a 3-dimensional endmember selection method were applied to refining endmembers. In the second stage, instead of obtaining impervious surface fraction by adding high and low albedo fractions directly, a linear regression model was built between impervious surface and high/low albedo using a random sampling method. The urban impervious surface distribution in the urban central area of Shanghai was predicted by the linear regression model. Estimation accuracy of spectral mixture analysis and impervious surface fraction were assessed using root mean square (RMS) and color aerial photography respectively. In comparison with three different research methods, this improved estimation method has a higher overall accuracy than traditional Linear Spectral Mixture Analysis (LSMA) method and the normalized SMA model both in root mean square error (RMSE) and standard error (SE). However, the model has a tendency to overestimate the impervious surface distribution.

On the Non-linear Motion of IGS Station

With the daily SINEX files of the IGS, the time series of IGS stations are obtained using an independently developed software under generalized network adjustment models with coordinate patterns. From the time series, non-linear motions are found. With spectral analysis method, the variation frequency （annual period and semi-annual period） of the site velocity is found. Moreover, the empirical model of the velocity variation of the station has been established by regression analysis method based on the weekly solution coordinate series of the station. With respect to the velocity of the IGS tracking station, it was better to model the variation periodically or to give a velocity periodically using a piece-wise linear function rather than a linear variable to estimate its bias.

Construction of lake bathymetry from MODIS satellite data and GIS from 2003 to 2011

In recent years, sedimentation conditions in Dongting Lake have varied greatly because of signifi cant changes in runoff and sediment load in the Changjiang(Yangtze) River following the construction of Three Gorges Dam. The topography of the lake bottom has changed rapidly because of the intense exchange of water and sediment between the lake and the Changjiang River. However, time series information on lake-bottom topographic change is lacking. In this study, we introduced a method that combines remote sensing data and in situ water level data to extract a record of Dongting Lake bottom topography from 2003 to 2011. Multi-temporal lake land/water boundaries were extracted from MODIS images using the linear spectral mixture model method. The elevation of water/land boundary points were calculated using water level data and spatial interpolation techniques. Digital elevation models of Dongting Lake bottom topography in different periods were then constructed with the multiple heighted waterlines. The mean root-mean-square error of the linear spectral mixture model was 0.036, and the mean predicted error for elevation interpolation was-0.19 m. Compared with fi eld measurement data and sediment load data, the method has proven to be most applicable. The results show that the topography of the bottom of Dongting Lake has exhibited uneven erosion and deposition in terms of time and space over the last nine years. Moreover, lake-bottom topography has undergone a slight erosion trend within this period, with 58.2% and 41.8% of the lake-bottom area being eroded and deposited, respectively.

Analysis and Modeling of k-regular and k-connected Protection Structure in Ultra-High Capacity Optical Networks

This paper proposes k-regular and k-connected(k&k) structure against multifaults in ultra-high capacity optical networks.Theoretical results show that pre-configured k&k structure can reach the lower bound on logical redundancy.The switching time of k&k protection structure is as quickly as ringbased protection in SDH network.It is the optimal protection structure in ultra-high capacity optical networks against multi-faults.We develop the linear programming model for k&k structure and propose a construction method for k&k structure design.Simulations are conducted for spare spectrum resources effi ciency of the pre-confi gured k&k structure under multi-faults on representative COST239 and NSFnet topologies.Numerical results show that the spare spectrum resources efficiency of k&k structure can reach the lower bound on logical redundancy in static networks.And it can largely improve spare spectrum resources effi ciency compared with p-cycles based protection structure without reducing protection effi ciency under dynamic traffi cs.

New Positive and Negative Hierarchies of Integrable Differential-Difference Equations and Conservation Laws

Two hierarchies of nonlinear integrable positive and negative lattice equations are derived from a discrete spectrak problem. The two lattice hierarchies are proved to have discrete zero curvature representations associated with a discrete spectral problem, which also shows that the positive and negative hierarchies correspond to positive and negative power expansions of Lax operators with respect to the spectral parameter, respectively. Moreover, the integrable lattice models in the positive hierarchy are of polynomial type, and the integrable lattice models in the negative hierarchy are of rational type. Further, we construct infinite conservation laws about the positive hierarchy.