The Chang＇e-3 （CE-3） mission is China＇s first exploration mission on the surface of the Moon that uses a lander and a rover. Eight instruments that form the scientific payloads have the following objectives： （1...The Chang＇e-3 （CE-3） mission is China＇s first exploration mission on the surface of the Moon that uses a lander and a rover. Eight instruments that form the scientific payloads have the following objectives： （1） investigate the morphological features and geological structures at the landing site; （2） integrated in-situ analysis of minerals and chemical compositions; （3） integrated exploration of the structure of the lunar interior; （4） exploration of the lunar-terrestrial space environment, lunar sur- face environment and acquire Moon-based ultraviolet astronomical observations. The Ground Research and Application System （GRAS） is in charge of data acquisition and pre-processing, management of the payload in orbit, and managing the data products and their applications. The Data Pre-processing Subsystem （DPS） is a part of GRAS. The task of DPS is the pre-processing of raw data from the eight instruments that are part of CE-3, including channel processing, unpacking, package sorting, calibration and correction, identification of geographical location, calculation of probe azimuth angle, probe zenith angle, solar azimuth angle, and solar zenith angle and so on, and conducting quality checks. These processes produce Level 0, Level 1 and Level 2 data. The computing platform of this subsystem is comprised of a high-performance computing cluster, including a real-time subsystem used for processing Level 0 data and a post-time subsystem for generating Level 1 and Level 2 data. This paper de- scribes the CE-3 data pre-processing method, the data pre-processing subsystem, data classification, data validity and data products that are used for scientific studies.展开更多
Debris flows are the one type of natural disaster that is most closely associated with hu- man activities. Debris flows are characterized as being widely distributed and frequently activated. Rainfall is an important ...Debris flows are the one type of natural disaster that is most closely associated with hu- man activities. Debris flows are characterized as being widely distributed and frequently activated. Rainfall is an important component of debris flows and is the most active factor when debris flows oc- cur. Rainfall also determines the temporal and spatial distribution characteristics of the hazards. A reasonable rainfall threshold target is essential to ensuring the accuracy of debris flow pre-warning. Such a threshold is important for the study of the mechanisms of debris flow formation, predicting the characteristics of future activities and the design of prevention and engineering control measures. Most mountainous areas have little data regarding rainfall and hazards, especially in debris flow forming re- gions. Therefore, both the traditional demonstration method and frequency calculated method cannot satisfy the debris flow pre-warning requirements. This study presents the characteristics of pre-warning regions, included the rainfall, hydrologic and topographic conditions. An analogous area with abundant data and the same conditions as the pre-warning region was selected, and the rainfall threshold was calculated by proxy. This method resolved the problem of debris flow pre-warning in ar- eas lacking data and provided a new approach for debris flow pre-warning in mountainous areas.展开更多
As the demand for wind energy continues to grow at exponential rate, reducing operation and maintenance (O & M) costs and improving reliability have become top priorities in wind turbine maintenance strategies. Pr...As the demand for wind energy continues to grow at exponential rate, reducing operation and maintenance (O & M) costs and improving reliability have become top priorities in wind turbine maintenance strategies. Prediction of wind turbine failures before they reach a catastrophic stage is critical to reduce the O & M cost due to unnecessary scheduled maintenance. A SCADA-data based condition monitoring system, which takes advantage of data already collected at the wind turbine controller, is a cost-effective way to monitor wind turbines for early warning of failures. This article proposes a methodology of fault prediction and automatically generating warning and alarm for wind turbine main bearings based on stored SCADA data using Artificial Neural Network (ANN). The ANN model of turbine main bearing normal behavior is established and then the deviation between estimated and actual values of the parameter is calculated. Furthermore, a method has been developed to generate early warning and alarm and avoid false warnings and alarms based on the deviation. In this way, wind farm operators are able to have enough time to plan maintenance, and thus, unanticipated downtime can be avoided and O & M costs can be reduced.展开更多
Background:To summarize the concerted application and prescription rules of traditional Chinese medicine in the treatment of pre diabetes.Methods:Microsoft Excel 2010 was used to summarize the categories,nature,flavou...Background:To summarize the concerted application and prescription rules of traditional Chinese medicine in the treatment of pre diabetes.Methods:Microsoft Excel 2010 was used to summarize the categories,nature,flavour and channel tropism of drugs.The cluster analysis of high-frequency drugs was carried out by SPSS 22.0,and the association rules of high-frequency drugs were analyzed by Apriori algorithm provided by SPSS modeler 14.0.Results:One hundred and forty-six references were included,including 153 prescriptions and 131 drugs.Their frequency of use is listed in the following order.The top 3 categories of drugs were“Tonifying,Heat-Clearing”,diuresis and“Diffusing Dampness”drugs.The top 5 drugs were Huangqi(Astragali radix),Fuling(Poria),Huanglian(Coptidis rhizoma),Shanyao(Dioscoreae rhizoma),Gegen(Puerariae lobatae radix).The top 3 channel tropism of drugs were spleen,stomach and lung.The top 3 nature of drugs were cold,warm and calm.The top 3 flavour of drugs were sweet,bitter and pungent.The cluster analysis of high-frequency drugs showed that it could be classified into 4 categories:“Benefiting Qi”for promoting production of fluid,“Clearing Heat”and“Eliminating Dampness”,“Nourishing Yin”and“Clearing Heat”,and“Invigorating Spleen”for“Diffusing Dampness”.The results of association rule analysis showed that the combination with the highest degree of confidence and support was Poria-Chenpi(Citri reticulatae pericarpium)-Banxia(Pinelliae rhizoma)-Baizhu(Atractylodis macrocephalae rhizoma)and the combination with the highest frequency was Astragali radix-Puerariae lobatae radix.Conclusion:The pre diabetes is due to deficiency.The disease location is spleen and stomach and the pathological factor is phlegm-damp,that is why benefiting qi and invigorating spleen is regarded as the key link of clinical treatment.展开更多
In current cloud computing system, large amounts of sensitive data are shared to other cloud users. To keep these data confidentiality, data owners should encrypt their data before outsourcing. We choose proxy reencry...In current cloud computing system, large amounts of sensitive data are shared to other cloud users. To keep these data confidentiality, data owners should encrypt their data before outsourcing. We choose proxy reencryption （PRE） as the cloud data encryption technique. In a PRE system, a semi-trusted proxy can transform a ciphertext under one public key into a ciphertext of the same message under another public key, but the proxy cannot gain any information about the message. In this paper, we propose a certificateless PRE （CL-PRE） scheme without pairings. The security of the proposed scheme can be proved to be equivalent to the computational Dire- Hellman （CDH） problem in the random oracle model. Compared with other existing CL-PRE schemes, our scheme requires less computation cost and is significantly more efficient. The new scheme does not need the public key certificates to guarantee validity of public keys and solves the key escrow problem in identity-based public key cryptography.展开更多
Strainmeters have been used to detect earthquake precursory anomalies in many countries. An innovated four-component strainmeter with four sensing units set at 45 degrees intervals, named SKZ strainmeter, was develope...Strainmeters have been used to detect earthquake precursory anomalies in many countries. An innovated four-component strainmeter with four sensing units set at 45 degrees intervals, named SKZ strainmeter, was developed and used in China. The design, with a few unique features, allows high-sensitivity monitoring of the regime of the crustal strain field, as well as the self-consistencies of the instrument. One of the most difficult problems in the earthquake precursory investigation is to efficiently detect anomalies from large amount of data. Pattern recognition of waveforms is widely used, but it is time-consuming and relies more or less investigator’s experience and decision. In this study, the consistency factors of the paired components were firstly shown to be utilized to detect anomalies possibly related with imminent earthquakes. Here, rather than using the consistency factors, the correlation coefficients of the two orthogonal strain data were used to detect. SKZ strainmeters have been installed at more than ten sites in China, exhibited high efficiency and reliability in precursory monitoring since. Anomalous variations from a few stations during two recent earthquakes in south China were analyzed. During normal stages, diurnal earth tides could be clearly observed with very little urban noises. Though the consistency factors may have near constant bias, their correlation coefficients remain near 1.0, greater than 0.99. During the imminent preparatory stage of earthquake occurrence, non-planar strain may appear and the correlation coefficients drop noticeably. The analysis showed that the correlation coefficient between the two orthogonal components is a useful parameter in post-processing of the strain data to detect precursory anomalies. The resultant resolving power is shown to be some one-order larger compared with previous methods.展开更多
This paper mainly elaborates the studies of channel estimation and downlink data transmission in Massive MIMO. As there are different types of interference in single-cell and multi-cell systems, this paper establishes...This paper mainly elaborates the studies of channel estimation and downlink data transmission in Massive MIMO. As there are different types of interference in single-cell and multi-cell systems, this paper establishes different models for them separately. In terms of uplink training, for getting channel state information, we introduce LS and MMSE channel estimation algorithms and make a comparison between them. At the same time, the problem of pilot contamination is solved by cell classification and pilot identification. Next, this paper defines mathematical models for downlink data transmission. We use pre-coding methods (including Zero-forcing and Maximal Ratio Combining schemes) and optimize power distribution to improve channel capacity and transmission rate. Furthermore, this paper provides numerical results to show the simulation performance in both single-cell and multi-cell systems and extends to prospects in the future.展开更多
Poverty threatens human development especially for developing countries,so ending poverty has become one of the most important United Nations Sustainable Development Goals(SDGs).This study aims to explore China’s pro...Poverty threatens human development especially for developing countries,so ending poverty has become one of the most important United Nations Sustainable Development Goals(SDGs).This study aims to explore China’s progress in poverty reduction from 2016 to 2019 through time-series multi-source geospatial data and a deep learning model.The poverty reduction efficiency(PRE)is measured by the difference in the out-of-poverty rates(which measures the probability of being not poor)of 2016 and 2019.The study shows that the probability of poverty in all regions of China has shown an overall decreasing trend(PRE=0.264),which indicates that the progress in poverty reduction during this period is significant.The Hu Huanyong Line(Hu Line)shows an uneven geographical pattern of out-of-poverty rate between Southeast and Northwest China.From 2016 to 2019,the centroid of China’s out-of-poverty rate moved 105.786 km to the northeast while the standard deviation ellipse of the out-of-poverty rate moved 3 degrees away from the Hu Line,indicating that the regions with high out-of-poverty rates are more concentrated on the east side of the Hu Line from 2016 to 2019.The results imply that the government’s future poverty reduction policies should pay attention to the infrastructure construction in poor areas and appropriately increase the population density in poor areas.This study fills the gap in the research on poverty reduction under multiple scales and provides useful implications for the government’s poverty reduction policy.展开更多
文摘The Chang＇e-3 （CE-3） mission is China＇s first exploration mission on the surface of the Moon that uses a lander and a rover. Eight instruments that form the scientific payloads have the following objectives： （1） investigate the morphological features and geological structures at the landing site; （2） integrated in-situ analysis of minerals and chemical compositions; （3） integrated exploration of the structure of the lunar interior; （4） exploration of the lunar-terrestrial space environment, lunar sur- face environment and acquire Moon-based ultraviolet astronomical observations. The Ground Research and Application System （GRAS） is in charge of data acquisition and pre-processing, management of the payload in orbit, and managing the data products and their applications. The Data Pre-processing Subsystem （DPS） is a part of GRAS. The task of DPS is the pre-processing of raw data from the eight instruments that are part of CE-3, including channel processing, unpacking, package sorting, calibration and correction, identification of geographical location, calculation of probe azimuth angle, probe zenith angle, solar azimuth angle, and solar zenith angle and so on, and conducting quality checks. These processes produce Level 0, Level 1 and Level 2 data. The computing platform of this subsystem is comprised of a high-performance computing cluster, including a real-time subsystem used for processing Level 0 data and a post-time subsystem for generating Level 1 and Level 2 data. This paper de- scribes the CE-3 data pre-processing method, the data pre-processing subsystem, data classification, data validity and data products that are used for scientific studies.
基金supported by the National Natural Science Foundation of China(Nos.40830742 and 40901007)
文摘Debris flows are the one type of natural disaster that is most closely associated with hu- man activities. Debris flows are characterized as being widely distributed and frequently activated. Rainfall is an important component of debris flows and is the most active factor when debris flows oc- cur. Rainfall also determines the temporal and spatial distribution characteristics of the hazards. A reasonable rainfall threshold target is essential to ensuring the accuracy of debris flow pre-warning. Such a threshold is important for the study of the mechanisms of debris flow formation, predicting the characteristics of future activities and the design of prevention and engineering control measures. Most mountainous areas have little data regarding rainfall and hazards, especially in debris flow forming re- gions. Therefore, both the traditional demonstration method and frequency calculated method cannot satisfy the debris flow pre-warning requirements. This study presents the characteristics of pre-warning regions, included the rainfall, hydrologic and topographic conditions. An analogous area with abundant data and the same conditions as the pre-warning region was selected, and the rainfall threshold was calculated by proxy. This method resolved the problem of debris flow pre-warning in ar- eas lacking data and provided a new approach for debris flow pre-warning in mountainous areas.
文摘As the demand for wind energy continues to grow at exponential rate, reducing operation and maintenance (O & M) costs and improving reliability have become top priorities in wind turbine maintenance strategies. Prediction of wind turbine failures before they reach a catastrophic stage is critical to reduce the O & M cost due to unnecessary scheduled maintenance. A SCADA-data based condition monitoring system, which takes advantage of data already collected at the wind turbine controller, is a cost-effective way to monitor wind turbines for early warning of failures. This article proposes a methodology of fault prediction and automatically generating warning and alarm for wind turbine main bearings based on stored SCADA data using Artificial Neural Network (ANN). The ANN model of turbine main bearing normal behavior is established and then the deviation between estimated and actual values of the parameter is calculated. Furthermore, a method has been developed to generate early warning and alarm and avoid false warnings and alarms based on the deviation. In this way, wind farm operators are able to have enough time to plan maintenance, and thus, unanticipated downtime can be avoided and O & M costs can be reduced.
文摘Background:To summarize the concerted application and prescription rules of traditional Chinese medicine in the treatment of pre diabetes.Methods:Microsoft Excel 2010 was used to summarize the categories,nature,flavour and channel tropism of drugs.The cluster analysis of high-frequency drugs was carried out by SPSS 22.0,and the association rules of high-frequency drugs were analyzed by Apriori algorithm provided by SPSS modeler 14.0.Results:One hundred and forty-six references were included,including 153 prescriptions and 131 drugs.Their frequency of use is listed in the following order.The top 3 categories of drugs were“Tonifying,Heat-Clearing”,diuresis and“Diffusing Dampness”drugs.The top 5 drugs were Huangqi(Astragali radix),Fuling(Poria),Huanglian(Coptidis rhizoma),Shanyao(Dioscoreae rhizoma),Gegen(Puerariae lobatae radix).The top 3 channel tropism of drugs were spleen,stomach and lung.The top 3 nature of drugs were cold,warm and calm.The top 3 flavour of drugs were sweet,bitter and pungent.The cluster analysis of high-frequency drugs showed that it could be classified into 4 categories:“Benefiting Qi”for promoting production of fluid,“Clearing Heat”and“Eliminating Dampness”,“Nourishing Yin”and“Clearing Heat”,and“Invigorating Spleen”for“Diffusing Dampness”.The results of association rule analysis showed that the combination with the highest degree of confidence and support was Poria-Chenpi(Citri reticulatae pericarpium)-Banxia(Pinelliae rhizoma)-Baizhu(Atractylodis macrocephalae rhizoma)and the combination with the highest frequency was Astragali radix-Puerariae lobatae radix.Conclusion:The pre diabetes is due to deficiency.The disease location is spleen and stomach and the pathological factor is phlegm-damp,that is why benefiting qi and invigorating spleen is regarded as the key link of clinical treatment.
基金the National Natural Science Foundation of China(No.61133014)
文摘In current cloud computing system, large amounts of sensitive data are shared to other cloud users. To keep these data confidentiality, data owners should encrypt their data before outsourcing. We choose proxy reencryption （PRE） as the cloud data encryption technique. In a PRE system, a semi-trusted proxy can transform a ciphertext under one public key into a ciphertext of the same message under another public key, but the proxy cannot gain any information about the message. In this paper, we propose a certificateless PRE （CL-PRE） scheme without pairings. The security of the proposed scheme can be proved to be equivalent to the computational Dire- Hellman （CDH） problem in the random oracle model. Compared with other existing CL-PRE schemes, our scheme requires less computation cost and is significantly more efficient. The new scheme does not need the public key certificates to guarantee validity of public keys and solves the key escrow problem in identity-based public key cryptography.
文摘Strainmeters have been used to detect earthquake precursory anomalies in many countries. An innovated four-component strainmeter with four sensing units set at 45 degrees intervals, named SKZ strainmeter, was developed and used in China. The design, with a few unique features, allows high-sensitivity monitoring of the regime of the crustal strain field, as well as the self-consistencies of the instrument. One of the most difficult problems in the earthquake precursory investigation is to efficiently detect anomalies from large amount of data. Pattern recognition of waveforms is widely used, but it is time-consuming and relies more or less investigator’s experience and decision. In this study, the consistency factors of the paired components were firstly shown to be utilized to detect anomalies possibly related with imminent earthquakes. Here, rather than using the consistency factors, the correlation coefficients of the two orthogonal strain data were used to detect. SKZ strainmeters have been installed at more than ten sites in China, exhibited high efficiency and reliability in precursory monitoring since. Anomalous variations from a few stations during two recent earthquakes in south China were analyzed. During normal stages, diurnal earth tides could be clearly observed with very little urban noises. Though the consistency factors may have near constant bias, their correlation coefficients remain near 1.0, greater than 0.99. During the imminent preparatory stage of earthquake occurrence, non-planar strain may appear and the correlation coefficients drop noticeably. The analysis showed that the correlation coefficient between the two orthogonal components is a useful parameter in post-processing of the strain data to detect precursory anomalies. The resultant resolving power is shown to be some one-order larger compared with previous methods.
文摘This paper mainly elaborates the studies of channel estimation and downlink data transmission in Massive MIMO. As there are different types of interference in single-cell and multi-cell systems, this paper establishes different models for them separately. In terms of uplink training, for getting channel state information, we introduce LS and MMSE channel estimation algorithms and make a comparison between them. At the same time, the problem of pilot contamination is solved by cell classification and pilot identification. Next, this paper defines mathematical models for downlink data transmission. We use pre-coding methods (including Zero-forcing and Maximal Ratio Combining schemes) and optimize power distribution to improve channel capacity and transmission rate. Furthermore, this paper provides numerical results to show the simulation performance in both single-cell and multi-cell systems and extends to prospects in the future.
基金supported by the National Key Research and Development Program of China[grant number 2019YFB2102903]the National Natural Science Foundation of China[grant number 41801306]+1 种基金the“CUG Scholar”Scientific Research Funds at China University of Geosciences(Wuhan)[grant number 2022034]a grant from State Key Laboratory of Resources and Environmental Information System.
文摘Poverty threatens human development especially for developing countries,so ending poverty has become one of the most important United Nations Sustainable Development Goals(SDGs).This study aims to explore China’s progress in poverty reduction from 2016 to 2019 through time-series multi-source geospatial data and a deep learning model.The poverty reduction efficiency(PRE)is measured by the difference in the out-of-poverty rates(which measures the probability of being not poor)of 2016 and 2019.The study shows that the probability of poverty in all regions of China has shown an overall decreasing trend(PRE=0.264),which indicates that the progress in poverty reduction during this period is significant.The Hu Huanyong Line(Hu Line)shows an uneven geographical pattern of out-of-poverty rate between Southeast and Northwest China.From 2016 to 2019,the centroid of China’s out-of-poverty rate moved 105.786 km to the northeast while the standard deviation ellipse of the out-of-poverty rate moved 3 degrees away from the Hu Line,indicating that the regions with high out-of-poverty rates are more concentrated on the east side of the Hu Line from 2016 to 2019.The results imply that the government’s future poverty reduction policies should pay attention to the infrastructure construction in poor areas and appropriately increase the population density in poor areas.This study fills the gap in the research on poverty reduction under multiple scales and provides useful implications for the government’s poverty reduction policy.
