Techniques of Image Processing Based on Artificial Neural Networks

This paper presented an online quality inspection system based on artificial neural networks. Chromatism classification and edge detection are two difficult problems in glass steel surface quality inspection. Two artificial neural networks were made and the two problems were solved. The one solved chromatism classification. Hue, saturation and their probability of three colors, whose appearing probabilities were maximum in color histogram, were selected as input parameters, and the number of output node could be adjusted with the change of requirement. The other solved edge detection. In this neutral network, edge detection of gray scale image was able to be tested with trained neural networks for a binary image. It prevent the difficulty that the number of needed training samples was too large if gray scale images were directly regarded as training samples. This system is able to be applied to not only glass steel fault inspection but also other product online quality inspection and classification.     

Using of the surface plasmon resonance cytosensor for real-time and non-invasive monitoring of cellular effects in living C6 cells induced by PMA

By cell and molecular biology, the traditional life science research has been improved into modern ex-perimental science. Because cell is the basic structural and functional unit of the mysterious life, the study of life phenomena will be ultimately embodied into the study of cell biology. How to acquire a dynamic knowledge of the intricate biomolecular reactivity and process in living cells has become one of the hotspots in recent biological researches. For the complexity of cellular effects,…     

Insecticidal activity of residual Bt protein at the second trophic level

Since the first commercial release of transgenic crop expressing genes from Bacillus thuringiensis (Bt), there have been concerns about its potential impact on the environment. Research has focused on the ecological effects from second exposure to Bt prot…     

基于形态学的图像融合算法

提出一种基于边缘连接强度的图像融合算法。利用形态学梯度算子得到图像的边缘信息。以图像灰度的边缘连接强度加权为判据,进行图像融合。实验结果表明,该图像融合方法在保留TM多光谱图像光谱分辨率的同时,通过融合SPOT全色图像提高了空间分辨率,丰富了图像细节信息。     

柔性形态边缘检测算法在菌类显微图像中的应用

在灰度图像的柔性形态学概念及特性的基础上,根据菌类显微图像的边缘特点,提出了均衡化的柔性形态边缘检测方法.以霉菌图像为例,通过实验结果和传统的canny算子、LOG算子边缘提取结果进行对比,证明了算法的有效性,为菌类识别打下了良好的基础.     

三色Ramsey数尺（Cm1，Cm2，Cm3）研究

用r种颜色对图G的所有边着色，记着第i色的边构成的子图为G1,如果存在一种着色方法使得对所有的1≤i≤r都满足Hi￠Gi，则称图G对于（H1，H1，…．Hr）可r着色．Ramsey数尺（H1，H2，…，Hr）是使得完全图Kn对于（H1．H2，…，Hr）不可r着色的最小正整数n，令m1〉m2≥m3，Erdoes等给出了当m1足够大时R（Cm1，Cm2，Cm3）的值．通过对m1不是足够大的情况进行研究，证明了当m≥5时，R（Cm，C3m,C3）=5m=4；并给出了当m1≤7时R（Cm1，Cm2，Cm3）的值．     

中国股市交易量的周内效应

研究了中国股市交易量在一周里面的变化规律,采样时间跨度是从1990-12-19到2002-12-31。以市场换手率度量交易量,采用自回归广义自回归条件异方差(AR-GARCH)模型研究了中国股市交易量的时间系列。研究结果显示沪市和深市的日市场换手率不服从正态分布并且存在着自相关性和ARCH效应;AR-GARCH模型很好地拟合了日市场换手率时间系列,估计出来的参数十分显著;周一到周五的日市场换手率存在显著差异并且周一的市场换手率达到了一周的最大值。利用混合分布假说进行了解释,非交易日的信息积累可能是周一高换手率的原因。结果指出:在该研究的样本范围内,中国股市交易量存在着周内效应。     

全球气候变化对中国自然灾害的可能影响

随着人口增多和社会经济的发展，全球CO2、CH4、N2O等气体的排放增加所引起的温室效应，预期本世纪的全球变暖较20世纪更为强烈．讨论了全球气候变化及其对中国自然灾害的可能影响．结果表明，本世纪全球气候进一步变暖将可能导致我国北方干旱趋势仍将延续．南方雨量增加特别是暴雨和台风的增加，会使洪涝灾害扩大加剧．沿海地区由于海平面上升，海岸带灾害主要是风暴潮呈现加剧趋势、农林病虫害、滑坡与泥石流、水土流失与土壤侵蚀灾害也将发展，唯寒冻灾害可能大幅度减轻．面对全球气候变化，我国政府及科学界应加强科学研究，积极参与国际合作，采取减轻、防范和适应措施，以减少经济损失．     

A New Edge-directed Subpixel Edge Localization Method

IntroductionComparedtotraditionalindustry ,microelectronicfab ricationhasthreecharacteristics :highcomplexity ,highprecisionandhighautomatization .Tomeettheprecision ,speedandreliabilityrequirements,machinevisiontech niques,suchasvisionaidedinspectionandregistration ,havebeenintroducedineveryworkingprocedureofinte grated circuitfabricationandsurfacemounttechnology(SMT) .Inspectionandregistrationprecisionmustbecon stantlyincreasedasthesizeofthecomponentbecomessmallerandsmaller .Therefore ,the…     

基于逆向学习改进算法的汽车边缘提取

根据智能交通系统中车型识别的特点提出了使用逆向学习改进算法提取汽车边缘的新方法，这种方法的优点在于可以充分利用车型识别系统的特点和汽车历史轨迹的先验知识得到较好的提取精度，并有效地解决了车型识别中，因使用黑白图象而使基于色彩的汽车边缘提取失效的问题。