A new method of detecting abnormal sounding data based on LS-SVM is presented.The theorem proves that the trend surface filter is the especial result of LS-SVM.In order to depict the relationship of trend surface filt...A new method of detecting abnormal sounding data based on LS-SVM is presented.The theorem proves that the trend surface filter is the especial result of LS-SVM.In order to depict the relationship of trend surface filter and LS-SVM,a contrast is given.The example shows that abnormal sounding data could be detected effectively by LS-SVM when the training samples and kernel function are reasonable.展开更多
Continuous thunderstorm occurring at Qingdao Airport in China from August 7 to 13,2022 was analyzed based on sounding data.The weather was divided into thunderstorm gale,thunderstorm and heavy precipitation,and some p...Continuous thunderstorm occurring at Qingdao Airport in China from August 7 to 13,2022 was analyzed based on sounding data.The weather was divided into thunderstorm gale,thunderstorm and heavy precipitation,and some physical quantities and time variables which can effectively identify severe convective weather types were preliminarily obtained.The results show that CAPE was sensitive to different types of weather,but the uncertainty was relatively large.Convective temperature T_(CON),temperature difference between 500 and 850 hPa,and vertical wind shear can distinguish thunderstorm gale,thunderstorm and heavy precipitation weather obviously.Besides,K index,Showalter index,θ_(se) difference between 500 and 850 hPa were also important basis to distinguish thunderstorm and heavy precipitation weather.Thunderstorm gale can be distinguished by the 24-hour variations of K index,and the difference of dew point between 500 and 850 hPa.The 24-hour variations of(T-T_(d))_(500) and vertical wind shear can be used to distinguish between heavy precipitation and thunderstorm weather;the 24-hour variation of stratification stability Δθ_(se) can distinguish the three kinds of weather well.For the wind field,the existence of vertical wind shear was required for strong convective weather,and the 24-hour increment of thunderstorm gale and thunderstorm was larger than that of heavy precipitation.展开更多
Discriminating internal layers by radio echo sounding is important in analyzing the thickness and ice deposits in the Antarctic ice sheet.The signal processing method of synthesis aperture radar(SAR)has been widely us...Discriminating internal layers by radio echo sounding is important in analyzing the thickness and ice deposits in the Antarctic ice sheet.The signal processing method of synthesis aperture radar(SAR)has been widely used for improving the signal to noise ratio(SNR)and discriminating internal layers by radio echo sounding data of ice sheets.This method is not efficient when we use edge detection operators to obtain accurate information of the layers,especially the ice-bed interface.This paper presents a new image processing method via a combined robust principal component analysis-total variation(RPCA-TV)approach for discriminating internal layers of ice sheets by radio echo sounding data.The RPCA-based method is adopted to project the high-dimensional observations to low-dimensional subspace structure to accelerate the operation of the TV-based method,which is used to discriminate the internal layers.The efficiency of the presented method has been tested on simulation data and the dataset of the Institute of Electronics,Chinese Academy of Sciences,collected during CHINARE 28.The results show that the new method is more efficient than the previous method in discriminating internal layers of ice sheets by radio echo sounding data.展开更多
[Objective] The research aimed to discuss shallowly the application of L-band sounding seconds data in the artificial precipitation. [Method] The characteristics, getting manner and displaying method of L-band soundin...[Objective] The research aimed to discuss shallowly the application of L-band sounding seconds data in the artificial precipitation. [Method] The characteristics, getting manner and displaying method of L-band sounding seconds data were introduced briefly. Moreover, its application prospect in the artificial precipitation operation was analyzed initially. We aimed to improve its application rate in the artificial precipitation operation. [Result] L-band sounding seconds data had the great improvement in the time-space resolution and the space positioning accuracy aspects when compared with the previous sounding data, and the precision reached the second level. It could provide the high-precision data basis for the assimilation of artificial precipitation numerical model initial field, and improve the numerical model. Moreover, the sounding product could provide the accurate scientific basis for the selection of artificial precipitation operation tool, the determination of operation height and range, and guide the artificial precipitation operation, and improve the operation efficiency. [Conclusion] The research provided the analysis and reference basis for the command of artificial precipitation operation.展开更多
The Advanced Radiative Transfer Modeling System(ARMS),a computationally efficient satellite observation operator,has been successfully integrated into the YinHe four-dimensional variational data assimilation(YH4DVAR)s...The Advanced Radiative Transfer Modeling System(ARMS),a computationally efficient satellite observation operator,has been successfully integrated into the YinHe four-dimensional variational data assimilation(YH4DVAR)system.This study investigates the impacts of assimilating Advanced Microwave Sounding Unit-A(AMSU-A)observations from the Meteorological Operational Satellite-C(MetOp-C)on the performance of YH4DVAR.Through a month-long global statistical analysis and a case study of Typhoon Hinnamnor,we evaluate the benefits of AMSUA data assimilation under clear sky conditions.Key findings are as follows.(1)ARMS achieves simulation accuracy comparable to RTTOV(Radiative Transfer for the Television and InfraRed Observation Satellite Operational Vertical sounder)version 11.2,demonstrating only a 0.5%discrepancy in data retention after quality control.(2)Implementation of ARMS as an operator in YH4DVAR enhances forecast accuracy for the 850-hPa temperature and 500-hPa geopotential height in the tropical region.(3)Compared to RTTOV,ARMS has improved the intensity forecast of Typhoon Hinnamnor and reduced mean wind speed errors by approximately 2%and central pressure errors by approximately1%.ARMS has now been operationally adopted as an alternative observational operator within YH4DVAR,demonstrating exceptional numerical stability,computational efficiency,and promising potential for future satellite data assimilation applications.展开更多
To achieve accurate positioning of autonomous underwater vehicles, an appropriate underwater terrain database storage format for underwater terrain-matching positioning is established using multi-beam data as underwat...To achieve accurate positioning of autonomous underwater vehicles, an appropriate underwater terrain database storage format for underwater terrain-matching positioning is established using multi-beam data as underwater terrainmatching data. An underwater terrain interpolation error compensation method based on fractional Brownian motion is proposed for defects of normal terrain interpolation, and an underwater terrain-matching positioning method based on least squares estimation（LSE） is proposed for correlation analysis of topographic features. The Fisher method is introduced as a secondary criterion for pseudo localization appearing in a topographic features flat area, effectively reducing the impact of pseudo positioning points on matching accuracy and improving the positioning accuracy of terrain flat areas. Simulation experiments based on electronic chart and multi-beam sea trial data show that drift errors of an inertial navigation system can be corrected effectively using the proposed method. The positioning accuracy and practicality are high, satisfying the requirement of underwater accurate positioning.展开更多
Together,the heart and lung sound comprise the thoracic cavity sound,which provides informative details that reflect patient conditions,particularly heart failure(HF)patients.However,due to the limitations of human he...Together,the heart and lung sound comprise the thoracic cavity sound,which provides informative details that reflect patient conditions,particularly heart failure(HF)patients.However,due to the limitations of human hearing,a limited amount of information can be auscultated from thoracic cavity sounds.With the aid of artificial intelligence–machine learning,these features can be analyzed and aid in the care of HF patients.Machine learning of thoracic cavity sound data involves sound data pre-processing by denoising,resampling,segmentation,and normalization.Afterwards,the most crucial step is feature extraction and se-lection where relevant features are selected to train the model.The next step is classification and model performance evaluation.This review summarizes the currently available studies that utilized different machine learning models,different feature extraction and selection methods,and different classifiers to generate the desired output.Most studies have analyzed the heart sound component of thoracic cavity sound to distinguish between normal and HF patients.Additionally,some studies have aimed to classify HF patients based on thoracic cavity sounds in their entirety,while others have focused on risk strati-fication and prognostic evaluation of HF patients using thoracic cavity sounds.Overall,the results from these studies demonstrate a promisingly high level of accuracy.Therefore,future prospective studies should incorporate these machine learning models to expedite their integration into daily clinical practice for managing HF patients.展开更多
Conventional information of Micaps, NCEP reanalysis data, and data from regional automatic weather stations were used to analyze the causes of rainstorm in southern mountains of Zhongwei City on July 21,2012. The resu...Conventional information of Micaps, NCEP reanalysis data, and data from regional automatic weather stations were used to analyze the causes of rainstorm in southern mountains of Zhongwei City on July 21,2012. The results showed that the favorable circulation situation ＂ high in east and low in west＂ to rainfall in Nlngxia formed at 500 hPa before the precipitation appeared, and the heavy rainfall generated when cold air over Lake Baikal moved eastward and joined with warm and wet airflow on the northwest side of 584 line in Hetao region. Ground frontal surface and shear lines at 700 and 500 hPa were main influencing systems of heavy rainfall. Positive vorticity area at low levels, water vapor convergence, as- cending motion and stratification instability provided thermal, dynamic and energy conditions for the formation of the rainstorm. The rainstorm area was situated in wind direction convergence zone where southwest airflow changed into easterly airflow at 700 hPa. Sounding data show that temper- ature and humidity were high in the lower atmosphere which was nearly saturated, and atmospheric convection was unstable before the rainstorm appeared. After the rainstorm occurred, energy in the atmosphere released rapidly, and each index reduced fast, so that the precipitation ended.展开更多
Animal models are crucial for the study of severe infectious diseases,which is essential for determining their pathogenesis and the development of vaccines and drugs.Animal experiments involving risk grade 3 agents su...Animal models are crucial for the study of severe infectious diseases,which is essential for determining their pathogenesis and the development of vaccines and drugs.Animal experiments involving risk grade 3 agents such as SARS CoV,HIV,M.tb,H7N9,and Brucella must be conducted in an Animal Biosafety Level 3(ABSL-3)facility.Because of the in vivo work,the biosafety risk in ABSL-3 facilities is higher than that in BSL-3 facilities.Undoubtedly,management practices must be strengthened to ensure biosafety in the ABSL-3 facility.Meanwhile,we cannot ignore the reliable scientific results obtained from animal experiments conducted in ABSL-3 laboratories.It is of great practical significance to study the overall biosafety concepts that can increase the scientific data quality.Based on the management of animal experiments in the ABSL-3 Laboratory of Wuhan University,combined with relevant international and domestic literature,we indicate the main safety issues and factors affecting animal experiment results at ABSL-3 facilities.Based on these issues,management practices regarding animal experiments in ABSL-3 facilities are proposed,which take into account both biosafety and scientifically sound data.展开更多
A wireless acoustic sensor network was realized using wireless sensor nodes equipped with microphone condensers,in which its sensor nodes were configured to capture poultry sound data and transmit it via the network t...A wireless acoustic sensor network was realized using wireless sensor nodes equipped with microphone condensers,in which its sensor nodes were configured to capture poultry sound data and transmit it via the network to a collection point.A high performance computer can process these large volumes of animal audio signals under different behaviors.By performing data signal processing and analyzing the audio signal,poultry sound can be achieved and then transformed into their corresponding behavioral modes for welfare assessment.In this study,compressive sensing algorithm was developed in consideration of the balance between the power saving from compression ratio and the computational cost,and a low power consumption as well as an inexpensive sensor node was designed as the elementary unit of poultry acoustic data collecting and transmission.Then,a Zigbee-based wireless acoustic sensor network was developed to meet the challenges of short transmission range and limited resources of storage and energy.Experimental results demonstrate that the compressive sensing algorithm can improve the communication performances of the wireless acoustic sensor network with high reliability,low packet loss rate and low energy consumption.展开更多
基金The National High-Tech Research and Development Program of China (863 Program) under contract No.2007AA12Z326the National Natural Science Foundation of China under contract Nos 40974010 and 40971306
文摘A new method of detecting abnormal sounding data based on LS-SVM is presented.The theorem proves that the trend surface filter is the especial result of LS-SVM.In order to depict the relationship of trend surface filter and LS-SVM,a contrast is given.The example shows that abnormal sounding data could be detected effectively by LS-SVM when the training samples and kernel function are reasonable.
文摘Continuous thunderstorm occurring at Qingdao Airport in China from August 7 to 13,2022 was analyzed based on sounding data.The weather was divided into thunderstorm gale,thunderstorm and heavy precipitation,and some physical quantities and time variables which can effectively identify severe convective weather types were preliminarily obtained.The results show that CAPE was sensitive to different types of weather,but the uncertainty was relatively large.Convective temperature T_(CON),temperature difference between 500 and 850 hPa,and vertical wind shear can distinguish thunderstorm gale,thunderstorm and heavy precipitation weather obviously.Besides,K index,Showalter index,θ_(se) difference between 500 and 850 hPa were also important basis to distinguish thunderstorm and heavy precipitation weather.Thunderstorm gale can be distinguished by the 24-hour variations of K index,and the difference of dew point between 500 and 850 hPa.The 24-hour variations of(T-T_(d))_(500) and vertical wind shear can be used to distinguish between heavy precipitation and thunderstorm weather;the 24-hour variation of stratification stability Δθ_(se) can distinguish the three kinds of weather well.For the wind field,the existence of vertical wind shear was required for strong convective weather,and the 24-hour increment of thunderstorm gale and thunderstorm was larger than that of heavy precipitation.
基金supported by the National Hi-Tech Research and Development Program of China("863"Project)(Grant No.2011AA040202)the National Natural Science Foundation of China(Grant No.40976114)
文摘Discriminating internal layers by radio echo sounding is important in analyzing the thickness and ice deposits in the Antarctic ice sheet.The signal processing method of synthesis aperture radar(SAR)has been widely used for improving the signal to noise ratio(SNR)and discriminating internal layers by radio echo sounding data of ice sheets.This method is not efficient when we use edge detection operators to obtain accurate information of the layers,especially the ice-bed interface.This paper presents a new image processing method via a combined robust principal component analysis-total variation(RPCA-TV)approach for discriminating internal layers of ice sheets by radio echo sounding data.The RPCA-based method is adopted to project the high-dimensional observations to low-dimensional subspace structure to accelerate the operation of the TV-based method,which is used to discriminate the internal layers.The efficiency of the presented method has been tested on simulation data and the dataset of the Institute of Electronics,Chinese Academy of Sciences,collected during CHINARE 28.The results show that the new method is more efficient than the previous method in discriminating internal layers of ice sheets by radio echo sounding data.
文摘[Objective] The research aimed to discuss shallowly the application of L-band sounding seconds data in the artificial precipitation. [Method] The characteristics, getting manner and displaying method of L-band sounding seconds data were introduced briefly. Moreover, its application prospect in the artificial precipitation operation was analyzed initially. We aimed to improve its application rate in the artificial precipitation operation. [Result] L-band sounding seconds data had the great improvement in the time-space resolution and the space positioning accuracy aspects when compared with the previous sounding data, and the precision reached the second level. It could provide the high-precision data basis for the assimilation of artificial precipitation numerical model initial field, and improve the numerical model. Moreover, the sounding product could provide the accurate scientific basis for the selection of artificial precipitation operation tool, the determination of operation height and range, and guide the artificial precipitation operation, and improve the operation efficiency. [Conclusion] The research provided the analysis and reference basis for the command of artificial precipitation operation.
基金Supported by the National Key Research and Development Program of China(2021YFC3101500)National Natural Science Foundation of China(42075149,42375155,and 62372460)Natural Science Foundation of Hunan Province of China(2023JJ40667)。
文摘The Advanced Radiative Transfer Modeling System(ARMS),a computationally efficient satellite observation operator,has been successfully integrated into the YinHe four-dimensional variational data assimilation(YH4DVAR)system.This study investigates the impacts of assimilating Advanced Microwave Sounding Unit-A(AMSU-A)observations from the Meteorological Operational Satellite-C(MetOp-C)on the performance of YH4DVAR.Through a month-long global statistical analysis and a case study of Typhoon Hinnamnor,we evaluate the benefits of AMSUA data assimilation under clear sky conditions.Key findings are as follows.(1)ARMS achieves simulation accuracy comparable to RTTOV(Radiative Transfer for the Television and InfraRed Observation Satellite Operational Vertical sounder)version 11.2,demonstrating only a 0.5%discrepancy in data retention after quality control.(2)Implementation of ARMS as an operator in YH4DVAR enhances forecast accuracy for the 850-hPa temperature and 500-hPa geopotential height in the tropical region.(3)Compared to RTTOV,ARMS has improved the intensity forecast of Typhoon Hinnamnor and reduced mean wind speed errors by approximately 2%and central pressure errors by approximately1%.ARMS has now been operationally adopted as an alternative observational operator within YH4DVAR,demonstrating exceptional numerical stability,computational efficiency,and promising potential for future satellite data assimilation applications.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.51179035 and 51279221)the Natural Science Foundation of Heilongjiang Province(Grant No.E201121)
文摘To achieve accurate positioning of autonomous underwater vehicles, an appropriate underwater terrain database storage format for underwater terrain-matching positioning is established using multi-beam data as underwater terrainmatching data. An underwater terrain interpolation error compensation method based on fractional Brownian motion is proposed for defects of normal terrain interpolation, and an underwater terrain-matching positioning method based on least squares estimation（LSE） is proposed for correlation analysis of topographic features. The Fisher method is introduced as a secondary criterion for pseudo localization appearing in a topographic features flat area, effectively reducing the impact of pseudo positioning points on matching accuracy and improving the positioning accuracy of terrain flat areas. Simulation experiments based on electronic chart and multi-beam sea trial data show that drift errors of an inertial navigation system can be corrected effectively using the proposed method. The positioning accuracy and practicality are high, satisfying the requirement of underwater accurate positioning.
文摘Together,the heart and lung sound comprise the thoracic cavity sound,which provides informative details that reflect patient conditions,particularly heart failure(HF)patients.However,due to the limitations of human hearing,a limited amount of information can be auscultated from thoracic cavity sounds.With the aid of artificial intelligence–machine learning,these features can be analyzed and aid in the care of HF patients.Machine learning of thoracic cavity sound data involves sound data pre-processing by denoising,resampling,segmentation,and normalization.Afterwards,the most crucial step is feature extraction and se-lection where relevant features are selected to train the model.The next step is classification and model performance evaluation.This review summarizes the currently available studies that utilized different machine learning models,different feature extraction and selection methods,and different classifiers to generate the desired output.Most studies have analyzed the heart sound component of thoracic cavity sound to distinguish between normal and HF patients.Additionally,some studies have aimed to classify HF patients based on thoracic cavity sounds in their entirety,while others have focused on risk strati-fication and prognostic evaluation of HF patients using thoracic cavity sounds.Overall,the results from these studies demonstrate a promisingly high level of accuracy.Therefore,future prospective studies should incorporate these machine learning models to expedite their integration into daily clinical practice for managing HF patients.
基金Supported by the Scientific and Technological Research Project of Ningxia Meteorological Bureau,China
文摘Conventional information of Micaps, NCEP reanalysis data, and data from regional automatic weather stations were used to analyze the causes of rainstorm in southern mountains of Zhongwei City on July 21,2012. The results showed that the favorable circulation situation ＂ high in east and low in west＂ to rainfall in Nlngxia formed at 500 hPa before the precipitation appeared, and the heavy rainfall generated when cold air over Lake Baikal moved eastward and joined with warm and wet airflow on the northwest side of 584 line in Hetao region. Ground frontal surface and shear lines at 700 and 500 hPa were main influencing systems of heavy rainfall. Positive vorticity area at low levels, water vapor convergence, as- cending motion and stratification instability provided thermal, dynamic and energy conditions for the formation of the rainstorm. The rainstorm area was situated in wind direction convergence zone where southwest airflow changed into easterly airflow at 700 hPa. Sounding data show that temper- ature and humidity were high in the lower atmosphere which was nearly saturated, and atmospheric convection was unstable before the rainstorm appeared. After the rainstorm occurred, energy in the atmosphere released rapidly, and each index reduced fast, so that the precipitation ended.
基金We are grateful for the funding from the National Key Research and Development Program of China(grant No.:2016YFC1202203).
文摘Animal models are crucial for the study of severe infectious diseases,which is essential for determining their pathogenesis and the development of vaccines and drugs.Animal experiments involving risk grade 3 agents such as SARS CoV,HIV,M.tb,H7N9,and Brucella must be conducted in an Animal Biosafety Level 3(ABSL-3)facility.Because of the in vivo work,the biosafety risk in ABSL-3 facilities is higher than that in BSL-3 facilities.Undoubtedly,management practices must be strengthened to ensure biosafety in the ABSL-3 facility.Meanwhile,we cannot ignore the reliable scientific results obtained from animal experiments conducted in ABSL-3 laboratories.It is of great practical significance to study the overall biosafety concepts that can increase the scientific data quality.Based on the management of animal experiments in the ABSL-3 Laboratory of Wuhan University,combined with relevant international and domestic literature,we indicate the main safety issues and factors affecting animal experiment results at ABSL-3 facilities.Based on these issues,management practices regarding animal experiments in ABSL-3 facilities are proposed,which take into account both biosafety and scientifically sound data.
基金the General Program of National Natural Science Foundation of China(No.11364029,No.61461042)Key Projects of National Science and Technology Ministry of China(No.2014BAD08B05)“Prairie talent”Industrial Innovation Team project of Inner Mongolia(No.2014-27).
文摘A wireless acoustic sensor network was realized using wireless sensor nodes equipped with microphone condensers,in which its sensor nodes were configured to capture poultry sound data and transmit it via the network to a collection point.A high performance computer can process these large volumes of animal audio signals under different behaviors.By performing data signal processing and analyzing the audio signal,poultry sound can be achieved and then transformed into their corresponding behavioral modes for welfare assessment.In this study,compressive sensing algorithm was developed in consideration of the balance between the power saving from compression ratio and the computational cost,and a low power consumption as well as an inexpensive sensor node was designed as the elementary unit of poultry acoustic data collecting and transmission.Then,a Zigbee-based wireless acoustic sensor network was developed to meet the challenges of short transmission range and limited resources of storage and energy.Experimental results demonstrate that the compressive sensing algorithm can improve the communication performances of the wireless acoustic sensor network with high reliability,low packet loss rate and low energy consumption.
