对变压器真实油温的智能化监测

本文中作者通过FLUENT温度场解析和变压器实物温升试验,找出了变压器油温最热的真实位置,从而提出智能化监测的解决方案,为真实反映油温升提供可靠的依据.     

如何在C语言教学中帮助学生树立信心

该文对C语言教学中两种不同的教学思路做了举例、分析和比较,偏重算法的教学有助于培养学生研究算法编制程序的能力,但对初学者培养兴趣、树立信心方面没有益处,在这方面偏重语法的教学更有效率,建议在教学实践中注重两者的结合。     

Robust image hashing using non-uniform sampling in discrete Fourier domain

This paper proposes a robust image hashing method in discrete Fourier domain that can be applied in such fields as image authentication and retrieval. In the pre-processing stage, image resizing and total variation based filtering are first used to regularize the input image. Then the secondary image is obtained by the rotation projection, and the robust frequency feature is extracted from the secondary image after discrete Fourier transform. More sampling points are chosen from the low- and middle-frequency component to represent the salient content of the image effectively, which is achieved by the non-uniform sampling. Finally, the intermediate sampling feature vectors are scrambled and quantized to produce the resulting binary hash securely. The security of the method depends entirely on the secret key. Experiments are conducted to show that the present method has satisfactory robustness against perceptual content-preserving manipulations and has also very low probability for collision of the hashes of distinct images.     

Epsilon-near-zero or mu-near-zero materials composed of dielectric photonic crystals

We theoretically demonstrate that at certain frequencies two-dimensional dielectric photonic crystals （PCs） may be regarded as either epsilon-near-zero or mu-near-zero materials. We show that the transmission through a slab of such materials upon normal incidence is normally non-unity and decays with slab thickness. However, when the incident angle increases slightly, the transmittance experiences a dramatic increase due to the Brewster effect. The combination of the tunneling and resonance effects makes such materials good candidates for almost perfect bending waveguides and cloaking in waveguides. The zero index also enables applications of focusing and directive emission. At last, the distinction between the single-zero and double-zero media is discussed. In all of the above results, the numerical simulations perfectly match with theoretical predictions from the effective medium analysis.     

运用多媒体改革经济数学教学存在的问题与对策

如何将多媒体技术有效地应用于经济数学课堂教学中,是目前经济数学教学改革值得注意的问题。结合教学实践,分析当前经济数学多媒体教学存在的问题,提出经济数学课程使用多媒体教学必须结合课程的特点,教学的需要以及学生的实际情况,将传统黑板教学与多媒体教学优势互补,以实现最佳教学效果。     

A scalable kernel-based semisupervised metric learning algorithm with out-of-sample generalization ability

In recent years, metric learning in the semisupervised setting has aroused a lot of research interest. One type of semisupervised metric learning utilizes supervisory information in the form of pairwise similarity or dissimilarity constraints. However, most methods proposed so far are either limited to linear metric learning or unable to scale well with the data set size. In this letter, we propose a nonlinear metric learning method based on the kernel approach. By applying low-rank approximation to the kernel matrix, our method can handle significantly larger data sets. Moreover, our low-rank approximation scheme can naturally lead to out-of-sample generalization. Experiments performed on both artificial and real-world data show very promising results.