With the spread and development of new epidemics,it is of great reference value to identify the changing trends of epidemics in public emotions.We designed and implemented the COVID-19 public opinion monitoring system...With the spread and development of new epidemics,it is of great reference value to identify the changing trends of epidemics in public emotions.We designed and implemented the COVID-19 public opinion monitoring system based on time series thermal new word mining.A new word structure discovery scheme based on the timing explosion of network topics and a Chinese sentiment analysis method for the COVID-19 public opinion environment are proposed.Establish a“Scrapy-Redis-Bloomfilter”distributed crawler framework to collect data.The system can judge the positive and negative emotions of the reviewer based on the comments,and can also reflect the depth of the seven emotions such as Hopeful,Happy,and Depressed.Finally,we improved the sentiment discriminant model of this system and compared the sentiment discriminant error of COVID-19 related comments with the Jiagu deep learning model.The results show that our model has better generalization ability and smaller discriminant error.We designed a large data visualization screen,which can clearly show the trend of public emotions,the proportion of various emotion categories,keywords,hot topics,etc.,and fully and intuitively reflect the development of public opinion.展开更多
The performance and reliability of structural components are greatly influenced by the presence of any abnormality in them.To this purpose,structural health monitoring(SHM)is recognized as a necessary tool to ensure t...The performance and reliability of structural components are greatly influenced by the presence of any abnormality in them.To this purpose,structural health monitoring(SHM)is recognized as a necessary tool to ensure the safety precautions and efficiency of both mechanical and civil infrastructures.Till now,most of the previous work has emphasized the functioning of several SHM techniques and systematic changes in SHM execution.However,there exist insufficient data in the literature regarding the patent-based technological developments in the SHM research domain which might be a useful source of detailed information for worldwide research institutes.To address this research gap,a method based on the Co-Operative Patent Classification(CPC)codes is proposed in the current study.The proposed method includes the patent analysis of SHM in terms of its global publication trend and technology-based applications.This analysis is performed using patent database search tools,namely,IncoPat and Espacenet.The period ranging from 2005 to 2019 is selected to retrieve the required patent documents.A new approach termed as Patents’value is utilized to investigate the technological impact of a patent in the form of forward citations,technical stability,and scope of protection.The identification of emerging SHM techniques and forecasting of vacant technology is also part of current research work.The research results have revealed the increasing trend in the number of published patents each year related to various SHM technologies.In this regard,China,the United States,and South Korea are notified as to the major depositor countries,respectively.Hence,mapping of patent data in this research is an effort to illustrate the effectiveness of the proposed method to demonstrate the development trends and dynamic inventions over the time in SHM research domain to achieve the optimal damage inspections of various mechanical components.展开更多
基金This work was supported by the Hainan Provincial Natural Science Foundation of China[2019RC041,2019RC098]National Natural Science Foundation of China[61762033]+3 种基金Hainan University Doctor Start Fund Project[kyqd1328]Hainan University Youth Fund Project[qnjj1444]Ministry of education humanities and social sciences research program fund project(19YJA710010)The Opening Project of Shanghai Trusted Industrial Control Platform(Grant No.TICPSH202003005-ZC).
文摘With the spread and development of new epidemics,it is of great reference value to identify the changing trends of epidemics in public emotions.We designed and implemented the COVID-19 public opinion monitoring system based on time series thermal new word mining.A new word structure discovery scheme based on the timing explosion of network topics and a Chinese sentiment analysis method for the COVID-19 public opinion environment are proposed.Establish a“Scrapy-Redis-Bloomfilter”distributed crawler framework to collect data.The system can judge the positive and negative emotions of the reviewer based on the comments,and can also reflect the depth of the seven emotions such as Hopeful,Happy,and Depressed.Finally,we improved the sentiment discriminant model of this system and compared the sentiment discriminant error of COVID-19 related comments with the Jiagu deep learning model.The results show that our model has better generalization ability and smaller discriminant error.We designed a large data visualization screen,which can clearly show the trend of public emotions,the proportion of various emotion categories,keywords,hot topics,etc.,and fully and intuitively reflect the development of public opinion.
文摘The performance and reliability of structural components are greatly influenced by the presence of any abnormality in them.To this purpose,structural health monitoring(SHM)is recognized as a necessary tool to ensure the safety precautions and efficiency of both mechanical and civil infrastructures.Till now,most of the previous work has emphasized the functioning of several SHM techniques and systematic changes in SHM execution.However,there exist insufficient data in the literature regarding the patent-based technological developments in the SHM research domain which might be a useful source of detailed information for worldwide research institutes.To address this research gap,a method based on the Co-Operative Patent Classification(CPC)codes is proposed in the current study.The proposed method includes the patent analysis of SHM in terms of its global publication trend and technology-based applications.This analysis is performed using patent database search tools,namely,IncoPat and Espacenet.The period ranging from 2005 to 2019 is selected to retrieve the required patent documents.A new approach termed as Patents’value is utilized to investigate the technological impact of a patent in the form of forward citations,technical stability,and scope of protection.The identification of emerging SHM techniques and forecasting of vacant technology is also part of current research work.The research results have revealed the increasing trend in the number of published patents each year related to various SHM technologies.In this regard,China,the United States,and South Korea are notified as to the major depositor countries,respectively.Hence,mapping of patent data in this research is an effort to illustrate the effectiveness of the proposed method to demonstrate the development trends and dynamic inventions over the time in SHM research domain to achieve the optimal damage inspections of various mechanical components.
