Passive acoustic monitoring(PAM)technology is increasingly becoming one of the mainstream methods for bird monitoring.However,detecting bird audio within complex natural acoustic environments using PAM devices remains...Passive acoustic monitoring(PAM)technology is increasingly becoming one of the mainstream methods for bird monitoring.However,detecting bird audio within complex natural acoustic environments using PAM devices remains a significant challenge.To enhance the accuracy(ACC)of bird audio detection(BAD)and reduce both false negatives and false positives,this study proposes a BAD method based on a Dual-Feature Enhancement Fusion Model(DFEFM).This method incorporates per-channel energy normalization(PCEN)to suppress noise in the input audio and utilizes mel-frequency cepstral coefficients(MFCC)and frequency correlation matrices(FCM)as input features.It achieves deep feature-level fusion of MFCC and FCM on the channel dimension through two independent multi-layer convolutional network branches,and further integrates Spatial and Channel Synergistic Attention(SCSA)and Multi-Head Attention(MHA)modules to enhance the fusion effect of the aforementioned two deep features.Experimental results on the DCASE2018 BAD dataset show that our proposed method achieved an ACC of 91.4%and an AUC value of 0.963,with false negative and false positive rates of 11.36%and 7.40%,respectively,surpassing existing methods.The method also demonstrated detection ACC above 92%and AUC values above 0.987 on datasets from three sites of different natural scenes in Beijing.Testing on the NVIDIA Jetson Nano indicated that the method achieved an ACC of 89.48%when processing an average of 10 s of audio,with a response time of only 0.557 s,showing excellent processing efficiency.This study provides an effective method for filtering non-bird vocalization audio in bird vocalization monitoring devices,which helps to save edge storage and information transmission costs,and has significant application value for wild bird monitoring and ecological research.展开更多
The characteristics of frequency correlation and group time delay of ambient noise and ship radiated-noise in the sea are studied. The theoretical and experimental results show that the frequency correlation of ship r...The characteristics of frequency correlation and group time delay of ambient noise and ship radiated-noise in the sea are studied. The theoretical and experimental results show that the frequency correlation of ship radiated-noise is much greater than that of ambient noise,and the frequency correlation of ship radiated-noise at long distance has obvious group time delay展开更多
Hypoxia represents one of the most extreme environmental conditions for both human beings and animals living at high al- titudes （Zhao et al., 2009）. Over the past few years, great attention has been focused on the ...Hypoxia represents one of the most extreme environmental conditions for both human beings and animals living at high al- titudes （Zhao et al., 2009）. Over the past few years, great attention has been focused on the genetic bases of adaption to high-altitude environments （Bigham et al., 2010; Simonson et al., 2010）. The domestic dog （Canisfamiliaris） is the first animal that developed an intimate relationship with human beings. Dogs migrated with human beings and have adapted to variety of ecological niches （Savolainen et al., 2002）. Our previous research revealed parallel evolution and convergent evolution in the adaptation of dogs and humans to the high-altitude environment of the Tibetan plateau （Wang et al., 2013, 2014）, suggesting that exploring the adaption of domestic dogs to high-altitude hypoxia is an interesting and important question.展开更多
Based on time correlation characteristic, width correlation characteristic and frequency correlation characteristic of detecting pulses, several methods are introduced to control random or periodic noise whose width i...Based on time correlation characteristic, width correlation characteristic and frequency correlation characteristic of detecting pulses, several methods are introduced to control random or periodic noise whose width is narrower than 1 ms or wider than 3 ms in Frequency Selection Detecting Radar System. The software flow chart and the results of the experiment are also given.展开更多
The complex resistivity of coal and related rocks contains abundant physical property information,which can be indirectly used to study the lithology and microstructure of these materials.These aspects are closely rel...The complex resistivity of coal and related rocks contains abundant physical property information,which can be indirectly used to study the lithology and microstructure of these materials.These aspects are closely related to the fluids inside the considered coal rocks,such as gas,water and coalbed methane.In the present analysis,considering different lithological structures,and using the Cole-Cole model,a forward simulation method is used to study different physical parameters such as the zero-frequency resistivity,the polarizability,the relaxation time,and the frequency correlation coefficient.Moreover,using a least square technique,a complex resistivity“inversion”algorithm is written.The comparison of the initial model parameters and those obtained after inversion is used to verify the stability and accuracy of such approach.The method is finally applied to primary-structure coal considered as the experimental sample for complex resistivity measurements.展开更多
基金supported by the Beijing Natural Science Foundation(5252014)the National Natural Science Foundation of China(62303063)。
文摘Passive acoustic monitoring(PAM)technology is increasingly becoming one of the mainstream methods for bird monitoring.However,detecting bird audio within complex natural acoustic environments using PAM devices remains a significant challenge.To enhance the accuracy(ACC)of bird audio detection(BAD)and reduce both false negatives and false positives,this study proposes a BAD method based on a Dual-Feature Enhancement Fusion Model(DFEFM).This method incorporates per-channel energy normalization(PCEN)to suppress noise in the input audio and utilizes mel-frequency cepstral coefficients(MFCC)and frequency correlation matrices(FCM)as input features.It achieves deep feature-level fusion of MFCC and FCM on the channel dimension through two independent multi-layer convolutional network branches,and further integrates Spatial and Channel Synergistic Attention(SCSA)and Multi-Head Attention(MHA)modules to enhance the fusion effect of the aforementioned two deep features.Experimental results on the DCASE2018 BAD dataset show that our proposed method achieved an ACC of 91.4%and an AUC value of 0.963,with false negative and false positive rates of 11.36%and 7.40%,respectively,surpassing existing methods.The method also demonstrated detection ACC above 92%and AUC values above 0.987 on datasets from three sites of different natural scenes in Beijing.Testing on the NVIDIA Jetson Nano indicated that the method achieved an ACC of 89.48%when processing an average of 10 s of audio,with a response time of only 0.557 s,showing excellent processing efficiency.This study provides an effective method for filtering non-bird vocalization audio in bird vocalization monitoring devices,which helps to save edge storage and information transmission costs,and has significant application value for wild bird monitoring and ecological research.
文摘The characteristics of frequency correlation and group time delay of ambient noise and ship radiated-noise in the sea are studied. The theoretical and experimental results show that the frequency correlation of ship radiated-noise is much greater than that of ambient noise,and the frequency correlation of ship radiated-noise at long distance has obvious group time delay
基金supported by the National Natural Science Foundation of China(No.91231108)the Breakthrough Project of Strategic Priority Program of the Chinese Academy of Sciences(No.XDB13000000)+1 种基金the Key Research Program of the Chinese Academy of Sciencesthe Youth Innovation Promotion Association,Chinese Academy of Sciences(to GDW)
文摘Hypoxia represents one of the most extreme environmental conditions for both human beings and animals living at high al- titudes （Zhao et al., 2009）. Over the past few years, great attention has been focused on the genetic bases of adaption to high-altitude environments （Bigham et al., 2010; Simonson et al., 2010）. The domestic dog （Canisfamiliaris） is the first animal that developed an intimate relationship with human beings. Dogs migrated with human beings and have adapted to variety of ecological niches （Savolainen et al., 2002）. Our previous research revealed parallel evolution and convergent evolution in the adaptation of dogs and humans to the high-altitude environment of the Tibetan plateau （Wang et al., 2013, 2014）, suggesting that exploring the adaption of domestic dogs to high-altitude hypoxia is an interesting and important question.
基金Supported by the 86 3High Technology Project of China( 86 3-8180 2 )
文摘Based on time correlation characteristic, width correlation characteristic and frequency correlation characteristic of detecting pulses, several methods are introduced to control random or periodic noise whose width is narrower than 1 ms or wider than 3 ms in Frequency Selection Detecting Radar System. The software flow chart and the results of the experiment are also given.
基金This research was funded by the National Natural Science Foundation under Grant No.[41974151]by the Jiangsu Province Natural Science Foundation under Grant No.[BK20181360]+1 种基金by the Major Scientific and Technological Innovation Project of Shandong Province of China under Grant No.[2019JZZY010820]by the Shaanxi Province Science and Technology Innovation Guidance Special No.[2020CGHJ-005].
文摘The complex resistivity of coal and related rocks contains abundant physical property information,which can be indirectly used to study the lithology and microstructure of these materials.These aspects are closely related to the fluids inside the considered coal rocks,such as gas,water and coalbed methane.In the present analysis,considering different lithological structures,and using the Cole-Cole model,a forward simulation method is used to study different physical parameters such as the zero-frequency resistivity,the polarizability,the relaxation time,and the frequency correlation coefficient.Moreover,using a least square technique,a complex resistivity“inversion”algorithm is written.The comparison of the initial model parameters and those obtained after inversion is used to verify the stability and accuracy of such approach.The method is finally applied to primary-structure coal considered as the experimental sample for complex resistivity measurements.
