A spatio-temporal fusion method for remote sensing data Using a linear injection model and local neighbourhood information

This paper presents a spatio-temporal fusion method for remote sensing images by using a linear injection model and local neighbourhood information. In this method, the linear injection model is first introduced to generate an initial fused image, the spatial details are extracted from the fine-resolution image at the base date, and are weighted by a proper injection gains. Then, the spatial details and the relative spectral information from the coarse-resolution images are blended to generate the fusion result. To further enhance its robustness to the noise, the local neighbourhood information, derived from the fine-resolution image and the fused result simultaneously, is introduced to refine the initial fused image to obtain a more accurate prediction result. The algorithm can effectively capture phenology change or land-cover-type change with minimum input data. Simulated data and two types of real satellite images with seasonal changes and land-cover-type changes are employed to test the performance of the proposed method. Compared with a spatial and temporal adaptive reflectance fusion model (STARFM) and a flexible spatio-temporal fusion algorithm (FSDAF), results show that the proposed approach improves the accuracy of fused images in phenology change area and effectively captures land-cover-type reflectance changes.     

Citation recommendation based on citation tendency

Scientometrics - Due to the development of academic, more and more attentions are paid to citation recommendation. To solve the citation recommendation problem, researchers begin to focus on the...     

Wearing prediction of stellite alloys based on opposite degree algorithm

In order to predict the wearing of stellite alloys,the related methods of rare metals data processing were discussed. The method of opposite degree(OD) algorithm was put forward to predict the wearing of stellite alloys.OD algorithm is based on prior numerical data, posterior numerical data and the opposite degree between numerical forecast data. To compare the performance of predicted results based on different algorithms, the back propagation(BP) and radial basis function(RBF) neural network methods were introduced. Predicted results show that the relative error of OD algorithm is smaller than those of BP and RBF neural network methods. OD algorithm is an effective method to predict the wearing of stellite alloys and it can be applied in practice.     

Regulation of sensory nerve conduction velocity of human bodies responding to annual temperature variations in natural environments

The extensive research interests in environmental temperature can be linked to human productivity / performance as well as comfort and health; while the mechanisms of physiological indices responding to temperature variations remain incompletely understood. This study adopted a physiological sensory nerve conduction velocity (SCV) as a temperature‐sensitive biomarker to explore the thermoregulatory mechanisms of human responding to annual temperatures. The measurements of subjects’ SCV (over 600 samples) were conducted in a naturally ventilated environment over all four seasons. The results showed a positive correlation between SCV and annual temperatures and a Boltzmann model was adopted to depict the S‐shaped trend of SCV with operative temperatures from 5°C to 40°C. The SCV increased linearly with operative temperatures from 14.28°C to 20.5°C and responded sensitively for 10.19°C‐24.59°C, while tended to be stable beyond that. The subjects’ thermal sensations were linearly related to SCV, elaborating the relation between human physiological regulations and subjective thermal perception variations. The findings reveal the body SCV regulatory characteristics in different operative temperature intervals, thereby giving a deeper insight into human autonomic thermoregulation and benefiting for built environment designs, meantime minimizing the temperature‐invoked risks to human health and well‐being.     

丙烷脱沥青装置调合前沥青的综合利用

在丙烷脱沥青装置加热炉试烧装置自产调合前沥青,通过观察油枪雾化沥青的能力、火嘴的燃烧情况以及燃烧后的烟尘状况,筛选出适合沥青燃烧的油枪,最终实现调合前沥青直接做加热炉燃料、减少重油出厂量的目的。     

Optimal Spectral-Galerkin Methods Using Generalized Jacobi Polynomials

We extend the definition of the classical Jacobi polynomials withindexes α, β>−1 to allow α and/or β to be negative integers. We show that the generalized Jacobi polynomials, with indexes corresponding to the number of boundary conditions in a given partial differential equation, are the natural basis functions for the spectral approximation of this partial differential equation. Moreover, the use of generalized Jacobi polynomials leads to much simplified analysis, more precise error estimates and well conditioned algorithms.Mathematics subject classification 1991. 65N35, 65N22, 65F05, 35J05     

冲突检测中的主动规则技术

提出主动数据库技术的一个新应用——主动规则应用于虚拟装配中的冲突检测，使虚拟装配具有了主动能力；论述分析了虚拟装配过程中冲突检测的主动功能需求；分析了虚拟装配环境的事件、每件、动作；提出了规则模型；对规则进行了描述。     

新版《建筑抗震设计规范》的主要改进

作者通过新旧抗震设计规范几个方面的对比，简要介绍了抗震设计新规范的主要改进情况，对结构设计人员学习抗震设计新规范有一定的指导作用。     

Recovery of gold cyanide using inherently conducting polymers

Removal of gold from basic solutions containing [Au(CN)₂]^? has been demonstrated using the inherently conducting polymer polypyrrole. Polymers containing sulfonated aromatic dopants have been found to display a significant ability to remove gold from such solutions. Experiments performed in solutions containing both gold and copper cyanide complexes indicate that the recovery process is not highly selective. However, the polypyrroles used display significantly faster rates of gold recovery than activated carbon. © 2003 Society of Chemical Industry