Ahmed Silik^1,2,7, Xiaodong Wang³, Chenyue Mei³, Xiaolei Jin³, Xudong Zhou⁴, Wei Zhou⁴, Congning Chen⁴, Weixing Hong^1,2, Jiawei Li^1,2, Mingjie Mao^1,2, Yuhan Liu^1,2, Mohammad Noori^5,6,*, Wael A. Altabey^8,*

Structural Durability & Health Monitoring, Vol.17, No.4, pp. 257-281, 2023, DOI:10.32604/sdhm.2023.023617 - 02 August 2023

Abstract Damage detection is an important area with growing interest in mechanical and structural engineering. One of the critical issues in damage detection is how to determine indices sensitive to the structural damage and insensitive to the surrounding environmental variations. Current damage identification indices commonly focus on structural dynamic characteristics such as natural frequencies, mode shapes, and frequency responses. This study aimed at developing a technique based on energy Curvature Difference, power spectrum density, correlation-based index, load distribution factor, and neutral axis shift to assess the bridge deck condition. In addition to tracking energy and frequency More > Graphic Abstract

Junbiao Liu^{1, 6}, Duanpo Wu^{2, 3}, Zimeng Wang², Xinyu Jin^{1, *}, Fang Dong⁴, Lurong Jiang⁵, Chenyi Cai⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.123, No.1, pp. 401-426, 2020, DOI:10.32604/cmes.2020.08731 - 01 April 2020

Abstract In the field of medical informatics, sleep staging is a challenging and timeconsuming task undertaken by sleep experts. According to the new standard of the American Academy of Sleep Medicine (AASM), the stages of sleep are divided into wakefulness (W), rapid eye movement (REM) and non-rapid eye movement (NREM) which includes three sleep stages (N1, N2 and N3) that describe the depth of sleep. This study aims to establish an automatic sleep staging algorithm based on the improved weighted random forest (WRF) and Hidden Markov Model (HMM) using only the features extracted from double-channel EEG… More >

Qing-Hua He^a, Bin Yu^b, Xin Hong^a, Bo Lv^a, Tao Liu^b, Jian Ran^b, Yu-Tian Bi^a

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 223-230, 2018, DOI:10.1080/10798587.2016.1261957

Abstract Lung abnormalities and respiratory diseases increase with the development of urban life. Lung sound analysis provides vital information of the present condition of the pulmonary. But lung sounds are easily interfered by noises in the transmission and record process, then it cannot be used for diagnosis of diseases. So the noised sound should be processed to reduce noises and to enhance the quality of signals received. On the basis of analyzing wavelet packet transform theory and the characteristics of traditional wavelet threshold de-noising method, we proposed a modified threshold selection method based on Particle Swarm More >

Yong Huang¹, Hui Li¹, Jinping Ou^1,2

The International Conference on Computational & Experimental Engineering and Sciences, Vol.12, No.2, pp. 53-64, 2009, DOI:10.3970/icces.2009.012.053

Abstract A new damage identification method based on Fractal theory and wavelet packet transform is presented in the paper. The damage identification method utilize frequency-based domain message, time-based domain message and space based domain message effectively. NeXT method were first employed to reduce loading effect of random vibration measured from structures and then the vibration sinal were decomposed into the certain level wavelet packet components. For every time array of wavelet packet component then need to calculate the mean FD values as the ultimated FD values to reduce noise effect. The location of damage in the… More >