基于Hough变换识别单周期正弦曲线图像的算法及实现

手工识别成像测井中的裂缝具有一定的主观性，不同的人可能会有不同的解释结果．作者介绍利用Hough变换自动识别裂缝的原理及其算法，并通过实例分析了其应用效果，结果表明，这种算法计算裂缝参数不仅精度可靠，还保证了裂缝参数拾取的唯一性，对实现井壁裂缝参数的完全自动解释有重要意义．     

一种大规模体数据压缩体绘制策略

针对基于GPU的大规模体数据直接体绘制过程中遇到的显存不足的问题，提出了一种大规模体数据的压缩绘制策略.该策略结合小波变换和分类矢量量化进行数据压缩，采用基于GPU的光线投射算法进行绘制，在绘制时，只解压变换当前绘制所需要的极少数数据，并结合多分辨率绘制，实现实时交互.基于CUDA的实验表明：该压缩绘制策略有效解决了显存不足问题，并且在保证交互绘制帧率的前提下获得了较好的成像质量.     

龙须菜细胞壁多糖对硼的吸附性能研究

为研究龙须菜(Gracilaria lemaneiformis)细胞壁多糖对硼的吸附作用机制及官能团之间的交互作用,本试验分别采用电感耦合等离子发射光谱(ICP-OES)和傅里叶变换红外光谱(FTIR)技术对其细胞壁多糖组分在吸附试验中进行硼的测定和表征。结果表明,细胞壁去琼胶后,硼吸附量减少50.13%,半纤维素去除后,硼吸附量减少21.20%,故可得纤维素吸附量占细胞壁总硼吸附量的28.67%。同时,通过细胞壁不同组分脱硼及硼胁迫后的红外光谱表征结果可知,龙须菜细胞壁及多糖在吸附硼的过程中,羟基、羧基、多糖碳链C-C为硼离子的主要结合位点,其中,琼胶、半纤维素中起主要作用的官能团为羟基、羧基,纤维素中起主要作用的官能团为多糖碳链C-C。本研究结果为进一步探究龙须菜多糖组分与硼的内在结合机制提供了基础依据。     

不同合成树脂工艺对改性材性能影响研究

为研究树脂对改性材性能的影响，采用2种不同工艺合成三聚氰胺-脲醛树脂（MUF），测试了树脂的相关性能。结果表明，不同合成工艺路线下制备的 MUF 树脂在固体含量、粘度、固化时间、游离甲醛含量间存在显著差异。最终树脂的分子结构类型相似性极高，但相同结构组分在不同树脂中所占比例各有差异。羟甲基基团在MUF2中所占比例高，而亚甲基桥键及醚键在MUF1中含量高。MUF1改性材的增重率（weight percent gain，WPG）值更大，但MUF2改性材的抗溶胀性（anti-swelling efficiency，ASE）和体积膨胀率（bulking rates，B）更高，MUF2改性材的尺寸稳定性更好。     

基于HHT变换的PSO-LSSVM耦合模型估算气象资料短缺地区ET_0

为准确估算气象资料短缺地区参考作物腾发量,构建了一种基于HHT变换的PSO-LSSVM耦合模型,并利用新疆和田气象站2000—2009年单日数据做训练、双日数据做验证。结果表明,该模型估算ET0方法明显优于常规的PSO-LSSVM和GRNN,预测精度较二者分别提高了15.7%~85.6%和15.8%~93.7%;该方法预测ET0的气象要素重要性为RsTmaxTminRHWn,利用该方法对气象要素组合为Tmax/Tmin/RH/Wn、Tmax/RH/Wn、Tmin/Wn、Wn条件下的ET0预测,MSE分别为0.407、0.185、0.149、0.135,说明该方法可以很好地估算资料缺失地区ET0。     

基于小波变换模态参数识别原理的共振拆除法理论研究

提出了一种经济、安全的建筑物拆除法-共振拆除法。依据小波变换模态参数辨识原理,求得建筑物理论固有频率及模态参数;建立楼房数学模型,模拟安装多台激振器,遥控激振器发出与建筑物固有频率相同频率激励,使楼房共振。建筑物激烈振动而坍塌,实现安全拆除建筑物的目的。     

Filtering Construct of Adaptive Filter Grou Pwith Multi-scale Decomposition

The principle and method of the adaptive filter and the filtering with wavelet transform were analyzed, and the model and method of adaptive filtering with wavelet transforms for the transient signal was established. The separated noise of signal by the multi-scale decomposition of wavelet transforms, was the input signal of adaptive filter, and accordingly the optimal filtering method of signal-noise decomposition was realized. By the adaptive filter grou Pbased on the wavelet transform, the optimal filtering to the multi-noise of signal is achieved at the same time, and the method presented in this paper has the excellent filtering capability. Examples of application demonstrate that this method presented is excellent to realize the optimal estimate to the valuable signal and noise of the transient signal in the same frequency segment.     

Wavelet Edge Detection Method Based-on Multi-scale Fuzzy Logic

A novel edge detection algorithm is proposed by implementing fuzzy image enhancement at different scales.The implement of this algorithm can reduce the negative influence bring from the non-maximum suppression algorithm which select only one threshold.The success of the approach depends on the selection of a general fuzzy operator(GFO) for the enhancement of contrast of region after smoothing of image at different scales.Consequently,it is more obvious that coarse intensity changes are obtained at a large scale whereas the fine details of intensity changes are obtained at a small scale.A pretty performance is obtained by used this work.     

Application of Wavelet Transform to De-noising Method

The wavelet transform is a new subject developed quickly in the past ten years. Compared with the Fourier transform, the wavelet transform is a part of time-frequency transform. The most important character is that it can be used to transform a signal into basic units at different scales and location, each unit represents a component of original signal difference from others. The wavelet transform has been proven to be a powerful and efficient tool for processing signal due to this character. This paper introduces the de-noising principles of the wavelet transform. It is proved to be an effective method by the simulating analysis.     

A Medical Image Quantization Method Suited for PACS

Image compression is very important in picture archiving and communication system(PACS). The author studied the statistical distribution of image wavelet subimage coefficients and concluded that the distribution of wavelet subimage coefficients is similar to that of Laplasian distribution. On the other hand, in image reconstruction, the coefficient with different amplitude owns different weight, and different accuracy can be applied to different coefficients according to their different weight. Then, the author has designed a image quantization encoding scheme for PACS. In this scheme, they selected the sample-standard-deviation of coefficients in every subimage as the quantization threshold, and accurately encoded those coefficients with higher weight. Also, this algorithm utilized the visual character of human. The test has proved that the main advantages of this method are the simplicity in computing and predictable encoded coefficients, and a high compression efficiency can obtain too.