灾后救灾干部心理重建研究进展

灾后心理重建工作越来越受到人们的重视,目前已经被正式纳入灾后重建体系。近年来研究表明,灾后救灾干部心理健康水平低于正常人,存在不同程度的生理和心理健康问题,而且与多种影响因素有关。灾后心理重建包括物质干预和心理干预等措施。现就灾后救灾干部心理重建研究进行综述。     

基于小波能量谱的先天或风湿性心脏病异常心音分类算法研究

目的为解决先天性心脏病或风湿性心脏病异常心音分辨问题,应用离散小波频带能量对异常心音分类算法进行研究。方法采集22人的正常心音和116人的异常心音,对心音信号做离散小波变换,根据病理性心杂音在频域内的分布范围划分5层频带,计算得到各层频带的能量占比,根据单因素方差分析方法,提出了基于小波能量谱的心音分类指标。结果对正常心音和异常心音的4个听诊区域进行了分类,最优分类准确率为92%。区分动脉导管未闭和其余异常心音的最优分类准确率为81.9%。结论基于小波能量谱的心音分类算法无需对心音信号进行分割,提取特征值少,可准确有效地对心音信号进行分类,相较于传统的心音听诊,算法的引入能够在异常心音临床诊断中提供参考数据。     

Multi-Frequency Contrast Source Inversion for Reflection Seismic Data

In the contrast source inversion (CSI) method, the contrast sources (equivalent scattering sources) and the contrast (parameter perturbation) are iteratively reconstructed by an alternating optimization scheme. Traditionally integral equation CSI method is formulated for transmission tomography using analytic Green's function in homogeneous background. To extend the method to the case of reflection seismology, in this paper, we use WKBJ method to compute the Green's function of depth dependent background media and the solving method of equations to initialize the contrast source of different frequencies, resulting in an efficient method to invert multi-frequency reflection seismic data – multi-frequency contrast source inversion method (MFCSI). Numerical results for the Marmousi model show that MFCSI method can obtain good results even when low frequency data are missing, in which case the conventional FWI fails.