一种消除阶梯效应的图像分解新模型

针对TV-L1分解模型在进行图像分解时所得到的结构部分有阶梯效应的问题,本文提出一种改进的图像分解模型即GJTV-L1模型。该模型首先得到结构部分的切向量场,由切向量场可得到结构部分的法向量场,然后拟合法向量场得到重构图像,即结构部分。通过仿真实验,验证了GJTV-L1模型和算法的合理性及有效性。     

Evaluation of tile–wall bonding integrity based on impact acoustics and support vector machine

It is well recognized that the impact-acoustic emissions contain information that can indicate the presence of the adhesive defects in the bonding structures. In our previous papers, artificial neural network (ANN) was adopted to assess the bonding integrity of the tile–walls with the feature extracted from the power spectral density (PSD) of the impact-acoustic signals acting as the input of classifier. However, in addition to the inconvenience posed by the general drawbacks such as long training time and large number of training samples needed, the performance of the classic ANN classifier is deteriorated by the similar spectral characteristics between different bonding status caused by abnormal impacts. In this paper our previous works was developed by the employment of the least-squares support vector machine (LS-SVM) classifier instead of the ANN to derive a bonding integrity recognition approach with better reliability and enhanced immunity to surface roughness. With the help of the specially designed artificial sample slabs, experiments results obtained with the proposed method are provided and compared with that using the ANN classifier, demonstrating the effectiveness of the present strategy.     

基于混沌系统和极化恒等式的数字图像加密算法

混沌系统具有初值敏感性,参数敏感性和类随机性等特性。将图像分成大小为8 8的图像子块,利用经典的Logistic方程产生的混沌序列并对其排序生成匹配模板来改变图像子块的位置,然后利用极化恒等式内积分解加密算法改变图像像素的值。因此,基于混沌系统和极化恒等式的数字图像加密算法使图像的像素的位置和值都发生了变化,实现了图像的混淆和扩散。仿真实验表明该方法进行图像加密具有可行性和安全性。     

模糊综合评判理论在研究性学习系统中的研究及应用

介绍了工程数学中的模糊综合评判理论以及相应树型向量推理算法,并将模糊综合推理机制运用到研究性学习系统中进行研究型应用。该系统中运用模糊综合评判对学习效果进行合理评判,得出综合成绩,以其作为改进研究性学习模式的参考评证,从而使研究性学习过程良性发展。     

SVPWM教学研究之重点解析

SVPWM是电力电子技术教学中的重要内容,本文对空间矢量调制的教学重点做了一个较为全面系统的梳理。重点阐述SVPWM的核心思想,特别是三相正弦交流电SVPWM的基本原理,严格证明了三相电压的空间矢量相等与线电压相等等价。同时,证明在SVPWM下,逆变器输出的最大圆为基本空间矢量构成的正六边形的内接圆、直流母线电压利用率提高了约15.4%。     

5种药用植物挥发油对仓库害虫生物活性的研究

研究了香薷、鹤虱等５种药用植物挥发油对仓虫的生物活性作用。结果表明,香薷挥发油的作用最为明显,它（剂量０２μＬ／ｇ）及其粗分离１＃～５＃样品（剂量００５μＬ／ｇ）均有效地抑制了试虫卵、幼虫及成虫的生长发育,从而减少了试虫Ｆ１代种群的发生,其中粗分离１＃样品作用尤为突出。香薷挥发油１＃～５＃样品的主要化学成分为４,５,６,７,８,８ａ－六氢－８ａ－甲基－２［１Ｈ］－奥酮（５２６４％）、百里香酚（３０５％）和一未定成分（２１９２％）。     

浅谈在艺术设计教育中加强中国传统文化学习的必要性

近年来,正当许多发达国家努力发展本土文化的时候,我国在很多方面特别是艺术设计教育领域却忽视了具有5000年历史的中国传统文化。传统文化在现代设计教育中缺失的问题,表面上是教育体系、教育方法的问题,实际是教育理念的问题。面对西方文化巨大冲击,完善我国现代设计教育体系,确保民族文化根脉的活力,是我们必须面对、也必须尽快解决的问题。     

中国传统造物艺术研究——中国古代建筑环境造物艺术的美学特征

美学是研究美、美感以及艺术美的学科,对于中国古代建筑环境造物艺术的美学特征,自古有之,它充分的体现了中国悠久的建筑的历史,同时表达了人们对生活的向往和热爱。本文就以中国古代建筑环境造物艺术的美学特征进行论述,从文中可以领会到中国古代建筑环境造物艺术的博大精深。     

Modeling wine preferences by data mining from physicochemical properties

We propose a data mining approach to predict human wine taste preferences that is based on easily available analytical tests at the certification step. A large dataset (when compared to other studies in this domain) is considered, with white and red vinho verde samples (from Portugal). Three regression techniques were applied, under a computationally efficient procedure that performs simultaneous variable and model selection. The support vector machine achieved promising results, outperforming the multiple regression and neural network methods. Such model is useful to support the oenologist wine tasting evaluations and improve wine production. Furthermore, similar techniques can help in target marketing by modeling consumer tastes from niche markets.