High-quality,normalized differential vegetation index (NDVI) time-series data are fundamental for environmental remote sensing applications;however,their quality is often influenced by complicated factors such as atmo...High-quality,normalized differential vegetation index (NDVI) time-series data are fundamental for environmental remote sensing applications;however,their quality is often influenced by complicated factors such as atmospheric aerosols and cloud coverage. Hence,in the current study,a robust reconstruction method based on envelope detection and the Savitzky-Golay filter (ED-SG) was developed to reduce noise in the NDVI time-series. To verify the performance of ED-SG,simulation experiments were implemented and NDVI time-series samples were selected for different land cover types derived from MOD09GQ,Sentinel-2 and Landsat 8 OLI of Yangtze River Basin,between December 2018 and December 2019. The experimental results yielded an agreement coefficient and variance of 0.9599 and 0.0006,respectively on simulated time-series,Additionally,the smoothness metrics of evergreen broadleaf forests,evergreen needleleaf forests,deciduous broadleaf forests,herbaceous,and croplands were 0.0019,0.0017,0.0012,0.0012,and 0.0013,respectively. Ultimately,the reconstructed time-series metrics showed significant improvements in robustness and smoothness over conventional methods. Moreover,the simplistic mechanisms of the ED-SG model enabled it to run effectively in the Google Earth Engine over the NDVI time-series of the whole Yangtze River Basin.展开更多
This work proposes a computational algorithm to improve the determination of the timing of the respiratory phases.The algorithm was developed using a database of breathing sound signals acquired through properly posit...This work proposes a computational algorithm to improve the determination of the timing of the respiratory phases.The algorithm was developed using a database of breathing sound signals acquired through properly positioned face masks and electret microphones.Most of the proposed works use the frequency domain and decimation in time to detect the respiratory period and phases,as well as some specific pathology.In this work the processing applied is only in time without applying decimation,thus improving the detection of a greater number of respiratory periods.The segmentation is very important since it allows the isolation of phases of the signal to later detect some pathology or to estimate the volume of inspired and exhaled air.The proposed algorithm involves the extraction of signal envelopes with the use of high selectivity filters without decimation and adaptive normalization processes that aim to achieve an adequate detection.In the validation process,the algorithm detection results were compared with the timing of respiratory periods and phases marked by visual inspection.The results show a maximum error of 4.36%for the respiratory period and 3.23%and 3.09%for the expiration and inspiration times,respectively.展开更多
The tip vortex cavitation and its relevant noise has been the subject of extensive researches up to now. In most cases of experimental approaches, the accurate and objective decision of cavitation inception is primary...The tip vortex cavitation and its relevant noise has been the subject of extensive researches up to now. In most cases of experimental approaches, the accurate and objective decision of cavitation inception is primary, which is the main topic of this paper. Although the conventional power spectrum is normally adopted as a signal processing tool for the analysis of cavitation noise, a faithful exploration cannot be made especially for the cavitation inception. Alternatively, the periodic occurrence of bursting noise induced from tip vortex cavitation gives a diagnostic proof that the repeating frequency of the bursting contents can be exploited as an indication of the inception. This study, hence, employed the Short-Time Fourier Transform （STFT） analysis and the Detection of Envelope Modulation On Noise （DEMON） specmma analysis, both which are appropriate for finding such a repeating frequency. Through the acoustical measurement in a water tunnel, the two signal processing techniques show a satisfactory result in detecting the inception of tip vortex cavitation.展开更多
基金supported by the National Key Research and Development Program of China (grant number 2017YFC1500501).
文摘High-quality,normalized differential vegetation index (NDVI) time-series data are fundamental for environmental remote sensing applications;however,their quality is often influenced by complicated factors such as atmospheric aerosols and cloud coverage. Hence,in the current study,a robust reconstruction method based on envelope detection and the Savitzky-Golay filter (ED-SG) was developed to reduce noise in the NDVI time-series. To verify the performance of ED-SG,simulation experiments were implemented and NDVI time-series samples were selected for different land cover types derived from MOD09GQ,Sentinel-2 and Landsat 8 OLI of Yangtze River Basin,between December 2018 and December 2019. The experimental results yielded an agreement coefficient and variance of 0.9599 and 0.0006,respectively on simulated time-series,Additionally,the smoothness metrics of evergreen broadleaf forests,evergreen needleleaf forests,deciduous broadleaf forests,herbaceous,and croplands were 0.0019,0.0017,0.0012,0.0012,and 0.0013,respectively. Ultimately,the reconstructed time-series metrics showed significant improvements in robustness and smoothness over conventional methods. Moreover,the simplistic mechanisms of the ED-SG model enabled it to run effectively in the Google Earth Engine over the NDVI time-series of the whole Yangtze River Basin.
基金Dirección de Investigación of Universidad Peruana de Ciencias Aplicadas,Lima,Peru,for funding(No.UPC-DExpost-2021)and logistical support.
文摘This work proposes a computational algorithm to improve the determination of the timing of the respiratory phases.The algorithm was developed using a database of breathing sound signals acquired through properly positioned face masks and electret microphones.Most of the proposed works use the frequency domain and decimation in time to detect the respiratory period and phases,as well as some specific pathology.In this work the processing applied is only in time without applying decimation,thus improving the detection of a greater number of respiratory periods.The segmentation is very important since it allows the isolation of phases of the signal to later detect some pathology or to estimate the volume of inspired and exhaled air.The proposed algorithm involves the extraction of signal envelopes with the use of high selectivity filters without decimation and adaptive normalization processes that aim to achieve an adequate detection.In the validation process,the algorithm detection results were compared with the timing of respiratory periods and phases marked by visual inspection.The results show a maximum error of 4.36%for the respiratory period and 3.23%and 3.09%for the expiration and inspiration times,respectively.
文摘The tip vortex cavitation and its relevant noise has been the subject of extensive researches up to now. In most cases of experimental approaches, the accurate and objective decision of cavitation inception is primary, which is the main topic of this paper. Although the conventional power spectrum is normally adopted as a signal processing tool for the analysis of cavitation noise, a faithful exploration cannot be made especially for the cavitation inception. Alternatively, the periodic occurrence of bursting noise induced from tip vortex cavitation gives a diagnostic proof that the repeating frequency of the bursting contents can be exploited as an indication of the inception. This study, hence, employed the Short-Time Fourier Transform （STFT） analysis and the Detection of Envelope Modulation On Noise （DEMON） specmma analysis, both which are appropriate for finding such a repeating frequency. Through the acoustical measurement in a water tunnel, the two signal processing techniques show a satisfactory result in detecting the inception of tip vortex cavitation.
