Huakun Que¹, Guolong Lin², Wenchong Guo¹, Xiaofeng Feng¹, Zetao Jiang¹, Yunfei Cao^2,*, Jinmin Fan², Zhixian Ni³

Energy Engineering, Vol.119, No.4, pp. 1453-1466, 2022, DOI:10.32604/ee.2022.018448

Abstract In order to solve the failure of electricity anti-stealing detection device triggered by the noise mixed in high-frequency electricity stealing signals, a denoising method based on variational mode decomposition (VMD) and wavelet threshold denoising (WTD) was applied to extract the effective high-frequency electricity stealing signals. First, the signal polluted by noise was pre-decomposed using the VMD algorithm, the instantaneous frequency means of each pre-decomposed components was analyzed, so as to determine the optimal K value. The optimal K value was used to decompose the polluted signal into K intrinsic mode components, and the sensitive mode components were determined through the… More > Graphic Abstract

B.J. Yang¹, K.J. Cho¹, G.M. Kim¹, H.K. Lee^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.103, No.5, pp. 343-365, 2014, DOI:10.3970/cmes.2014.103.343

Abstract The addition of carbon nanotubes (CNTs) to a matrix material is expected to lead to an increase in the effective electrical properties of nanocomposites. However, a CNT entanglement caused by the matrix viscosity and the high aspect ratio of the nanotubes often inhibits the formation of a conductive network. In the present study, the micromechanics-based model is utilized to investigate the effect of CNT agglomeration on the electrical conductivity and percolation threshold of nanocomposites. A series of parametric studies considering various shapes and curviness distributions of CNTs are carried out to examine the effects of entanglement on the electrical performance… More >

Jun Shi¹, Zhujun Zhang², Yangyang Li^1,*, Rui Wang¹, Hao Shi¹, Xile Li³

CMC-Computers, Materials & Continua, Vol.57, No.1, pp. 69-80, 2018, DOI:10.32604/cmc.2018.03688

Abstract The electromagnetic waves emitted from devices can be a source of information leakage and can cause electromagnetic compatibility (EMC) problems. Electromagnetic radiation signals from computer displays can be a security risk if they are intercepted and reconstructed. In addition, the leaks may reveal the hardware information of the computer, which is more important for some attackers, protectors and security inspection workers. In this paper, we propose a statistical distribution based algorithm (SD algorithm) to extracted eigenvalues from electromagnetic radiate video signals, and then classified computers by using classifier based on Bayesian and SVM. We can identify computers automatically and accurately… More >