The public has shown great interest in the data factor and data transactions,but the current attention is overly focused on personal behavioral data and transactions happening at Data Exchanges.To deliver a complete p...The public has shown great interest in the data factor and data transactions,but the current attention is overly focused on personal behavioral data and transactions happening at Data Exchanges.To deliver a complete picture of data flaw and transaction,this paper presents a systematic overview of the flow and transaction of personal,corporate and public data on the basis of data factor classification from various perspectives.By utilizing various sources of information,this paper estimates the volume of data generation&storage and the volume&trend of data market transactions for major economies in the world with the following findings:(i)Data classification is diverse due to a broad variety of applying scenarios,and data transaction and profit distribution are complex due to heterogenous entities,ownerships,information density and other attributes of different data types.(ii)Global data transaction has presented with the characteristics of productization,servitization and platform-based mode.(iii)For major economies,there is a commonly observed disequilibrium between data generation scale and storage scale,which is particularly striking for China.(i^v)The global data market is in a nascent stage of rapid development with a transaction volume of about 100 billion US dollars,and China s data market is even more underdeveloped and only accounts for some 10%of the world total.All sectors of the society should be flly aware of the diversity and complexity of data factor classification and data transactions,as well as the arduous and long-term nature of developing and improving relevant institutional systems.Adapting to such features,efforts should be made to improve data classification,enhance computing infrastructure development,foster professional data transaction and development institutions,and perfect the data governance system.展开更多
This study concerns a Ka-band solid-state transmitter cloud radar, made in China, which can operate in three different work modes, with different pulse widths, and coherent and incoherent integration numbers, to meet ...This study concerns a Ka-band solid-state transmitter cloud radar, made in China, which can operate in three different work modes, with different pulse widths, and coherent and incoherent integration numbers, to meet the requirements for cloud remote sensing over the Tibetan Plateau. Specifically, the design of the three operational modes of the radar（i.e., boundary mode M1, cirrus mode M2, and precipitation mode M3） is introduced. Also, a cloud radar data merging algorithm for the three modes is proposed. Using one month＇s continuous measurements during summertime at Naqu on the Tibetan Plateau,we analyzed the consistency between the cloud radar measurements of the three modes. The number of occurrences of radar detections of hydrometeors and the percentage contributions of the different modes＇ data to the merged data were estimated.The performance of the merging algorithm was evaluated. The results indicated that the minimum detectable reflectivity for each mode was consistent with theoretical results. Merged data provided measurements with a minimum reflectivity of -35 dBZ at the height of 5 km, and obtained information above the height of 0.2 km. Measurements of radial velocity by the three operational modes agreed very well, and systematic errors in measurements of reflectivity were less than 2 dB. However,large discrepancies existed in the measurements of the linear depolarization ratio taken from the different operational modes.The percentage of radar detections of hydrometeors in mid- and high-level clouds increased by 60% through application of pulse compression techniques. In conclusion, the merged data are appropriate for cloud and precipitation studies over the Tibetan Plateau.展开更多
Purpose The Follow-up X-ray Telescope(FXT)is a principal scientific payload onboard the Einstein Probe(EP).It is designed to be capable of localizing X-ray sources,measuring the energy spectra in X-ray band of 0.3-10 ...Purpose The Follow-up X-ray Telescope(FXT)is a principal scientific payload onboard the Einstein Probe(EP).It is designed to be capable of localizing X-ray sources,measuring the energy spectra in X-ray band of 0.3-10 keV,and in some cases,performing observations with high time resolution.The FXT consists of two X-ray mirror modules(FXTA and FXTB),each containing 54 nested Wolter-I paraboloid-hyperboloid mirror shells.Each module is equipped with a PN-CCD as the focal plane detector.In order to complement the capabilities of the FXT,the PN-CCD offers three readout modes,full field of view imaging with low time resolution mode(FF mode),partial window imaging with moderate time resolution mode(PW mode)and high time resolution mode(TM mode).These different modes require tools and algorithms for data reduction and analysis.Methods A software package is utilized to achieve the FXT data analysis processing and extract scientific products.In the data reduction,time correction,computation of the PI values,elimination of the events caused by particles,identification of anomalous pixels and columns,and event reconstruction will be provided.Generic tools from HEASOFT,such as Xselect and Xspec,can also be used to manipulate the data files of the FXT.Results The FXT data are distributed in FITS format files.Its software package was created by taking the FXT-specific tools and the generic tools,and re-packaging them as stand-alone application.And the FXT-specific tools are written in ftools style,and the run styles are fully compatible with the HEASOFT software.Conclusion This package can achieve the FXT data analysis processing for all three science modes and effectively meets the data analysis requirements of the FXT.展开更多
The accurate prediction of vehicle speed plays an important role in vehicle's real-time energy management and online optimization control. However, the current forecast methods are mostly based on traffic conditio...The accurate prediction of vehicle speed plays an important role in vehicle's real-time energy management and online optimization control. However, the current forecast methods are mostly based on traffic conditions to predict the speed, while ignoring the impact of the driver-vehicle-road system on the actual speed profile. In this paper, the correlation of velocity and its effect factors under various driving conditions were firstly analyzed based on driver-vehicle-road-traffic data records for a more accurate prediction model. With the modeling time and prediction time considered separately, the effectiveness and accuracy of several typical artificial-intelligence speed prediction algorithms were analyzed. The results show that the combination of niche immunegenetic algorithm-support vector machine(NIGA-SVM) prediction algorithm on the city roads with genetic algorithmsupport vector machine(GA-SVM) prediction algorithm on the suburb roads and on the freeway can sharply improve the accuracy and timeliness of vehicle speed forecasting. Afterwards, the optimized GA-SVM vehicle speed prediction model was established in accordance with the optimized GA-SVM prediction algorithm at different times. And the test results verified its validity and rationality of the prediction algorithm.展开更多
文摘The public has shown great interest in the data factor and data transactions,but the current attention is overly focused on personal behavioral data and transactions happening at Data Exchanges.To deliver a complete picture of data flaw and transaction,this paper presents a systematic overview of the flow and transaction of personal,corporate and public data on the basis of data factor classification from various perspectives.By utilizing various sources of information,this paper estimates the volume of data generation&storage and the volume&trend of data market transactions for major economies in the world with the following findings:(i)Data classification is diverse due to a broad variety of applying scenarios,and data transaction and profit distribution are complex due to heterogenous entities,ownerships,information density and other attributes of different data types.(ii)Global data transaction has presented with the characteristics of productization,servitization and platform-based mode.(iii)For major economies,there is a commonly observed disequilibrium between data generation scale and storage scale,which is particularly striking for China.(i^v)The global data market is in a nascent stage of rapid development with a transaction volume of about 100 billion US dollars,and China s data market is even more underdeveloped and only accounts for some 10%of the world total.All sectors of the society should be flly aware of the diversity and complexity of data factor classification and data transactions,as well as the arduous and long-term nature of developing and improving relevant institutional systems.Adapting to such features,efforts should be made to improve data classification,enhance computing infrastructure development,foster professional data transaction and development institutions,and perfect the data governance system.
基金funded by the National Sciences Foundation of China(Grant No.91337103)the China Meteorological Administration Special Public Welfare Research Fund(Grant No.GYHY201406001)
文摘This study concerns a Ka-band solid-state transmitter cloud radar, made in China, which can operate in three different work modes, with different pulse widths, and coherent and incoherent integration numbers, to meet the requirements for cloud remote sensing over the Tibetan Plateau. Specifically, the design of the three operational modes of the radar（i.e., boundary mode M1, cirrus mode M2, and precipitation mode M3） is introduced. Also, a cloud radar data merging algorithm for the three modes is proposed. Using one month＇s continuous measurements during summertime at Naqu on the Tibetan Plateau,we analyzed the consistency between the cloud radar measurements of the three modes. The number of occurrences of radar detections of hydrometeors and the percentage contributions of the different modes＇ data to the merged data were estimated.The performance of the merging algorithm was evaluated. The results indicated that the minimum detectable reflectivity for each mode was consistent with theoretical results. Merged data provided measurements with a minimum reflectivity of -35 dBZ at the height of 5 km, and obtained information above the height of 0.2 km. Measurements of radial velocity by the three operational modes agreed very well, and systematic errors in measurements of reflectivity were less than 2 dB. However,large discrepancies existed in the measurements of the linear depolarization ratio taken from the different operational modes.The percentage of radar detections of hydrometeors in mid- and high-level clouds increased by 60% through application of pulse compression techniques. In conclusion, the merged data are appropriate for cloud and precipitation studies over the Tibetan Plateau.
基金supported by the Einstein Probe(EP)Program which is funded by the Strategic Priority Research Program of the Chinese Academy of Sciences Grant No.XDA15310000the National Natural Science Foundation of China under Grant No.U1938102.
文摘Purpose The Follow-up X-ray Telescope(FXT)is a principal scientific payload onboard the Einstein Probe(EP).It is designed to be capable of localizing X-ray sources,measuring the energy spectra in X-ray band of 0.3-10 keV,and in some cases,performing observations with high time resolution.The FXT consists of two X-ray mirror modules(FXTA and FXTB),each containing 54 nested Wolter-I paraboloid-hyperboloid mirror shells.Each module is equipped with a PN-CCD as the focal plane detector.In order to complement the capabilities of the FXT,the PN-CCD offers three readout modes,full field of view imaging with low time resolution mode(FF mode),partial window imaging with moderate time resolution mode(PW mode)and high time resolution mode(TM mode).These different modes require tools and algorithms for data reduction and analysis.Methods A software package is utilized to achieve the FXT data analysis processing and extract scientific products.In the data reduction,time correction,computation of the PI values,elimination of the events caused by particles,identification of anomalous pixels and columns,and event reconstruction will be provided.Generic tools from HEASOFT,such as Xselect and Xspec,can also be used to manipulate the data files of the FXT.Results The FXT data are distributed in FITS format files.Its software package was created by taking the FXT-specific tools and the generic tools,and re-packaging them as stand-alone application.And the FXT-specific tools are written in ftools style,and the run styles are fully compatible with the HEASOFT software.Conclusion This package can achieve the FXT data analysis processing for all three science modes and effectively meets the data analysis requirements of the FXT.
基金supported by the Nanjing University of Aeronautics and Astronautics Research Funding(Grant No.NS2015028)
文摘The accurate prediction of vehicle speed plays an important role in vehicle's real-time energy management and online optimization control. However, the current forecast methods are mostly based on traffic conditions to predict the speed, while ignoring the impact of the driver-vehicle-road system on the actual speed profile. In this paper, the correlation of velocity and its effect factors under various driving conditions were firstly analyzed based on driver-vehicle-road-traffic data records for a more accurate prediction model. With the modeling time and prediction time considered separately, the effectiveness and accuracy of several typical artificial-intelligence speed prediction algorithms were analyzed. The results show that the combination of niche immunegenetic algorithm-support vector machine(NIGA-SVM) prediction algorithm on the city roads with genetic algorithmsupport vector machine(GA-SVM) prediction algorithm on the suburb roads and on the freeway can sharply improve the accuracy and timeliness of vehicle speed forecasting. Afterwards, the optimized GA-SVM vehicle speed prediction model was established in accordance with the optimized GA-SVM prediction algorithm at different times. And the test results verified its validity and rationality of the prediction algorithm.
