With the development of the transportation industry, the effective guidance of aircraft in an emergency to prevent catastrophic accidents remains one of the top safety concerns. Undoubtedly, operational status data of...With the development of the transportation industry, the effective guidance of aircraft in an emergency to prevent catastrophic accidents remains one of the top safety concerns. Undoubtedly, operational status data of the aircraft play an important role in the judgment and command of the Operational Control Center(OCC). However, how to transmit various operational status data from abnormal aircraft back to the OCC in an emergency is still an open problem. In this paper, we propose a novel Telemetry, Tracking,and Command(TT&C) architecture named Collaborative TT&C(CoTT&C) based on mega-constellation to solve such a problem. CoTT&C allows each satellite to help the abnormal aircraft by sharing TT&C resources when needed, realizing real-time and reliable aeronautical communication in an emergency. Specifically, we design a dynamic resource sharing mechanism for CoTT&C and model the mechanism as a single-leader-multi-follower Stackelberg game. Further, we give an unique Nash Equilibrium(NE) of the game as a closed form. Simulation results demonstrate that the proposed resource sharing mechanism is effective, incentive compatible, fair, and reciprocal. We hope that our findings can shed some light for future research on aeronautical communications in an emergency.展开更多
Considering the problem that the scattering echo images of airborne Doppler weather radar are often reduced by ground clutters,the accuracy and confidence of meteorology target detection are reduced.In this paper,a de...Considering the problem that the scattering echo images of airborne Doppler weather radar are often reduced by ground clutters,the accuracy and confidence of meteorology target detection are reduced.In this paper,a deep convolutional neural network(DCNN)is proposed for meteorology target detection and ground clutter suppression with a large collection of airborne weather radar images as network input.For each weather radar image,the corresponding digital elevation model(DEM)image is extracted on basis of the radar antenna scan-ning parameters and plane position,and is further fed to the net-work as a supplement for ground clutter suppression.The fea-tures of actual meteorology targets are learned in each bottle-neck module of the proposed network and convolved into deeper iterations in the forward propagation process.Then the network parameters are updated by the back propagation itera-tion of the training error.Experimental results on the real mea-sured images show that our proposed DCNN outperforms the counterparts in terms of six evaluation factors.Meanwhile,the network outputs are in good agreement with the expected mete-orology detection results(labels).It is demonstrated that the pro-posed network would have a promising meteorology observa-tion application with minimal effort on network variables or parameter changes.展开更多
1.Overview August 2022 marked the 17th Workshop on Antarctic Meteorology and Climate(WAMC)which was held in a hybrid format at the Pyle Center at the University of Wisconsin-Madison(UW-Madison)in Madison,WI,USA.The wo...1.Overview August 2022 marked the 17th Workshop on Antarctic Meteorology and Climate(WAMC)which was held in a hybrid format at the Pyle Center at the University of Wisconsin-Madison(UW-Madison)in Madison,WI,USA.The workshop is the first partial in-person gathering since the 14th WAMC(Lazzara et al.,2018)as the 15th WAMC was canceled due to the COVID-19 pandemic,and the 16th WAMC(Bromwich et al.,2022)was purely online.Global members of the Antarctic meteorological community gathered at this meeting to present and discuss weather-related topics encompassing scientific research and support operations within Antarctic meteorology and climate.These conversations aimed to share and discuss results,future developments,and build collaborative plans.展开更多
It is imperative to prioritize the development of agriculture and rural areas and improve the efficiency of smart meteorological services for agricultural products under the strategy of rural revitalization. In this a...It is imperative to prioritize the development of agriculture and rural areas and improve the efficiency of smart meteorological services for agricultural products under the strategy of rural revitalization. In this article, we take Mingshan tea, one of the characteristic industries in Sichuan Province, as an example to explore the related issues of smart meteorology serving agriculture. The status, value, and demand of tea smart meteorological services have been analyzed in this article. In addition, in response to the increasing demand for meteorological services in agricultural production, we have proposed to solve problem of tea meteorological service by strengthening talent, technology, product refinement, and dissemination. We have also proposed specific measures for tea intelligent meteorology to serve agriculture, in order to provide reference for future service practices. We need to continuously improve the methods and content of meteorological services, and improve the level of meteorological services. At the same time, utilizing smart meteorological service methods provides strong support for rural revitalization. This not only increases the income of tea farmers, but also maximizes the technical support role of meteorology in disaster prevention and reduction.展开更多
On September 27th,the Energy-Meteorology Synergy Development Thematic Forum of the2023 Global Energy Interconnection Conference was held in Beijing.This forum,co-hosted by Global Energy Interconnection Development and...On September 27th,the Energy-Meteorology Synergy Development Thematic Forum of the2023 Global Energy Interconnection Conference was held in Beijing.This forum,co-hosted by Global Energy Interconnection Development and Cooperation Organisation,World Meteorological Organisation and National Climate Centre.展开更多
Objective:To explore the effects of daily mean temperature(°C),average daily air pressure(hPa),humidity(%),wind speed(m/s),particulate matter(PM)2.5(μg/m3)and PM10(μg/m3)on the admission rate of chronic kidney ...Objective:To explore the effects of daily mean temperature(°C),average daily air pressure(hPa),humidity(%),wind speed(m/s),particulate matter(PM)2.5(μg/m3)and PM10(μg/m3)on the admission rate of chronic kidney disease(CKD)patients admitted to the Second Affiliated Hospital of Harbin Medical University in Harbin and to identify the indexes and lag days that impose the most critical influence.Methods:The R language Distributed Lag Nonlinear Model(DLNM),Excel,and SPSS were used to analyze the disease and meteorological data of Harbin from 01 January 2010 to 31 December 2019 according to the inclusion and exclusion criteria.Results:Meteorological factors and air pollution influence the number of hospitalizations of CKD to vary degrees in cold regions,and differ in persistence or delay.Non-optimal temperature increases the risk of admission of CKD,high temperature increases the risk of obstructive kidney disease,and low temperature increases the risk of other major types of chronic kidney disease.The greater the temperature difference is,the higher its contribution is to the risk.The non-optimal wind speed and non-optimal atmospheric pressure are associated with increased hospital admissions.PM2.5 concentrations above 40μg/m3 have a negative impact on the results.Conclusion:Cold region meteorology and specific environment do have an impact on the number of hospital admissions for chronic kidney disease,and we can apply DLMN to describe the analysis.展开更多
基金supported by the National Natural Science Foundation of China under Grant 62131012/61971261。
文摘With the development of the transportation industry, the effective guidance of aircraft in an emergency to prevent catastrophic accidents remains one of the top safety concerns. Undoubtedly, operational status data of the aircraft play an important role in the judgment and command of the Operational Control Center(OCC). However, how to transmit various operational status data from abnormal aircraft back to the OCC in an emergency is still an open problem. In this paper, we propose a novel Telemetry, Tracking,and Command(TT&C) architecture named Collaborative TT&C(CoTT&C) based on mega-constellation to solve such a problem. CoTT&C allows each satellite to help the abnormal aircraft by sharing TT&C resources when needed, realizing real-time and reliable aeronautical communication in an emergency. Specifically, we design a dynamic resource sharing mechanism for CoTT&C and model the mechanism as a single-leader-multi-follower Stackelberg game. Further, we give an unique Nash Equilibrium(NE) of the game as a closed form. Simulation results demonstrate that the proposed resource sharing mechanism is effective, incentive compatible, fair, and reciprocal. We hope that our findings can shed some light for future research on aeronautical communications in an emergency.
基金This work was supported by the National Key R&D Program of China[grant number 2022YFC370110]the National Natural Science Foundation of China[grant numbers 42077194,42061134008,and 42377098]+1 种基金the Shanghai International Science and Technology Partnership Project[grant number 21230780200]the Shanghai General Project[grant number 23ZR1406100].
基金supported by the China Ministry of Industry and Information Technology Foundation and Aeronautical Science Foundation of China(ASFC-201920007002)the National Key Research and Development Plan(2021YFB1600603)the Open Fund of Key Laboratory of Civil Aircraft Airworthiness Technology,Civil Aviation University of China.
文摘Considering the problem that the scattering echo images of airborne Doppler weather radar are often reduced by ground clutters,the accuracy and confidence of meteorology target detection are reduced.In this paper,a deep convolutional neural network(DCNN)is proposed for meteorology target detection and ground clutter suppression with a large collection of airborne weather radar images as network input.For each weather radar image,the corresponding digital elevation model(DEM)image is extracted on basis of the radar antenna scan-ning parameters and plane position,and is further fed to the net-work as a supplement for ground clutter suppression.The fea-tures of actual meteorology targets are learned in each bottle-neck module of the proposed network and convolved into deeper iterations in the forward propagation process.Then the network parameters are updated by the back propagation itera-tion of the training error.Experimental results on the real mea-sured images show that our proposed DCNN outperforms the counterparts in terms of six evaluation factors.Meanwhile,the network outputs are in good agreement with the expected mete-orology detection results(labels).It is demonstrated that the pro-posed network would have a promising meteorology observa-tion application with minimal effort on network variables or parameter changes.
基金Financial Support from the Office of Polar Programs, National Science Foundation (Grant Nos. NSF 1924730, 1951720, and 1951603)
文摘1.Overview August 2022 marked the 17th Workshop on Antarctic Meteorology and Climate(WAMC)which was held in a hybrid format at the Pyle Center at the University of Wisconsin-Madison(UW-Madison)in Madison,WI,USA.The workshop is the first partial in-person gathering since the 14th WAMC(Lazzara et al.,2018)as the 15th WAMC was canceled due to the COVID-19 pandemic,and the 16th WAMC(Bromwich et al.,2022)was purely online.Global members of the Antarctic meteorological community gathered at this meeting to present and discuss weather-related topics encompassing scientific research and support operations within Antarctic meteorology and climate.These conversations aimed to share and discuss results,future developments,and build collaborative plans.
文摘It is imperative to prioritize the development of agriculture and rural areas and improve the efficiency of smart meteorological services for agricultural products under the strategy of rural revitalization. In this article, we take Mingshan tea, one of the characteristic industries in Sichuan Province, as an example to explore the related issues of smart meteorology serving agriculture. The status, value, and demand of tea smart meteorological services have been analyzed in this article. In addition, in response to the increasing demand for meteorological services in agricultural production, we have proposed to solve problem of tea meteorological service by strengthening talent, technology, product refinement, and dissemination. We have also proposed specific measures for tea intelligent meteorology to serve agriculture, in order to provide reference for future service practices. We need to continuously improve the methods and content of meteorological services, and improve the level of meteorological services. At the same time, utilizing smart meteorological service methods provides strong support for rural revitalization. This not only increases the income of tea farmers, but also maximizes the technical support role of meteorology in disaster prevention and reduction.
文摘On September 27th,the Energy-Meteorology Synergy Development Thematic Forum of the2023 Global Energy Interconnection Conference was held in Beijing.This forum,co-hosted by Global Energy Interconnection Development and Cooperation Organisation,World Meteorological Organisation and National Climate Centre.
文摘Objective:To explore the effects of daily mean temperature(°C),average daily air pressure(hPa),humidity(%),wind speed(m/s),particulate matter(PM)2.5(μg/m3)and PM10(μg/m3)on the admission rate of chronic kidney disease(CKD)patients admitted to the Second Affiliated Hospital of Harbin Medical University in Harbin and to identify the indexes and lag days that impose the most critical influence.Methods:The R language Distributed Lag Nonlinear Model(DLNM),Excel,and SPSS were used to analyze the disease and meteorological data of Harbin from 01 January 2010 to 31 December 2019 according to the inclusion and exclusion criteria.Results:Meteorological factors and air pollution influence the number of hospitalizations of CKD to vary degrees in cold regions,and differ in persistence or delay.Non-optimal temperature increases the risk of admission of CKD,high temperature increases the risk of obstructive kidney disease,and low temperature increases the risk of other major types of chronic kidney disease.The greater the temperature difference is,the higher its contribution is to the risk.The non-optimal wind speed and non-optimal atmospheric pressure are associated with increased hospital admissions.PM2.5 concentrations above 40μg/m3 have a negative impact on the results.Conclusion:Cold region meteorology and specific environment do have an impact on the number of hospital admissions for chronic kidney disease,and we can apply DLMN to describe the analysis.
