On January 7, 2015 the project ＂Study on the technology formanufacture of high-spheroidicity FCC catalysts ＂undertakenby the SINOPEC Research Institute of Petroleum Processing（RIPP） has passed the technical apprai...On January 7, 2015 the project ＂Study on the technology formanufacture of high-spheroidicity FCC catalysts ＂undertakenby the SINOPEC Research Institute of Petroleum Processing（RIPP） has passed the technical appraisal organized by theScience and Technology Division of the Sinopec Corp.展开更多
The network integration provides users with a new network with long connection time and a high data rate when needed, but it also brings the defects of all the networks that integrate together into the integrated netw...The network integration provides users with a new network with long connection time and a high data rate when needed, but it also brings the defects of all the networks that integrate together into the integrated network. This will cause all kinds of existing and some new security problems in the operation of the integrated network. A complete protection based on recovery is proposed in the paper. It uses the public-key algorithm to authorize and private-key algorithm to encrypt the communicating data. This solution can provide the system with reliable security, and avoid Denial of Service (DoS) of the user. This solution has been proposed lately, and we should further identify the correct action of all the layers and figure out how to react when a legal node is framed by multiple malicious nodes.展开更多
Purpose:Social media users share their ideas,thoughts,and emotions with other users.However,it is not clear how online users would respond to new re search outcomes.This study aims to predict the nature of the emotion...Purpose:Social media users share their ideas,thoughts,and emotions with other users.However,it is not clear how online users would respond to new re search outcomes.This study aims to predict the nature of the emotions expressed by Twitter users toward scientific publications.Additionally,we investigate what features of the research articles help in such prediction.Identifying the sentiments of research articles on social media will help scientists gauge a new societal impact of their research articles.Design/methodology/appro ach:Several tools are used for sentiment analysis,so we applied five sentiment analysis tools to check which are suitable for capturing a tweet’s sentiment value and decided to use NLTK VADER and TextBlob.We segregated the sentiment value into negative,positive,and neutral.We measure the mean and median of tweets’sentiment value for research articles with more than one tweet.We next built machine learning models to predict the sentiments of tweets related to scientific publications and investigated the essential features that controlled the prediction models.Findings:We found that the most important feature in all the models was the sentiment of the research article title followed by the author count.We observed that the tree-based models performed better than other classification models,with Random Forest achieving 89%accuracy for binary clas sification and 73%accuracy for three-label clas sification.Research limitations:In this research,we used state-of-the-art sentiment analysis libraries.However,these libraries might vary at times in their sentiment prediction behavior.Tweet sentiment may be influenced by a multitude of circumstances and is not always immediately tied to the paper’s details.In the future,we intend to broaden the scope of our research by employing word2 vec models.Practical implications:Many studies have focused on understanding the impact of science on scientists or how science communicators can improve their outcomes.Research in this area has relied on fewer and more limited measures,such as citations and user studies with small datasets.There is currently a critical need to find novel methods to quantify and evaluate the broader impact of research.This study will help scientists better comprehend the emotional impact of their work.Additionally,the value of understanding the public’s interest and reactions helps science communicators identify effective ways to engage with the public and build positive connections between scientific communities and the public.Originality/value:This study will extend work on public engagement with science,sociology of science,and computational social science.It will enable researchers to identify areas in which there is a gap between public and expert understanding and provide strategies by which this gap can be bridged.展开更多
By studying the traditional spectral reflectance reconstruction method, spectral reflectance and the relative spectral power distribution of a lighting source are sparsely decomposed, and the orthogonal property of th...By studying the traditional spectral reflectance reconstruction method, spectral reflectance and the relative spectral power distribution of a lighting source are sparsely decomposed, and the orthogonal property of the principal component orthogonal basis is used to eliminate basis; then spectral reflectance data are obtained by solving a sparse coefficient. After theoretical analysis, the spectral reflectance reconstruction based on sparse prior knowledge of the principal component orthogonal basis by a single-pixel detector is carried out by software simulation and experiment. It can reduce the complexity and cost of the system, and has certain significance for the improvement of multispectral image acquisition technology.展开更多
文摘On January 7, 2015 the project ＂Study on the technology formanufacture of high-spheroidicity FCC catalysts ＂undertakenby the SINOPEC Research Institute of Petroleum Processing（RIPP） has passed the technical appraisal organized by theScience and Technology Division of the Sinopec Corp.
文摘The network integration provides users with a new network with long connection time and a high data rate when needed, but it also brings the defects of all the networks that integrate together into the integrated network. This will cause all kinds of existing and some new security problems in the operation of the integrated network. A complete protection based on recovery is proposed in the paper. It uses the public-key algorithm to authorize and private-key algorithm to encrypt the communicating data. This solution can provide the system with reliable security, and avoid Denial of Service (DoS) of the user. This solution has been proposed lately, and we should further identify the correct action of all the layers and figure out how to react when a legal node is framed by multiple malicious nodes.
文摘Purpose:Social media users share their ideas,thoughts,and emotions with other users.However,it is not clear how online users would respond to new re search outcomes.This study aims to predict the nature of the emotions expressed by Twitter users toward scientific publications.Additionally,we investigate what features of the research articles help in such prediction.Identifying the sentiments of research articles on social media will help scientists gauge a new societal impact of their research articles.Design/methodology/appro ach:Several tools are used for sentiment analysis,so we applied five sentiment analysis tools to check which are suitable for capturing a tweet’s sentiment value and decided to use NLTK VADER and TextBlob.We segregated the sentiment value into negative,positive,and neutral.We measure the mean and median of tweets’sentiment value for research articles with more than one tweet.We next built machine learning models to predict the sentiments of tweets related to scientific publications and investigated the essential features that controlled the prediction models.Findings:We found that the most important feature in all the models was the sentiment of the research article title followed by the author count.We observed that the tree-based models performed better than other classification models,with Random Forest achieving 89%accuracy for binary clas sification and 73%accuracy for three-label clas sification.Research limitations:In this research,we used state-of-the-art sentiment analysis libraries.However,these libraries might vary at times in their sentiment prediction behavior.Tweet sentiment may be influenced by a multitude of circumstances and is not always immediately tied to the paper’s details.In the future,we intend to broaden the scope of our research by employing word2 vec models.Practical implications:Many studies have focused on understanding the impact of science on scientists or how science communicators can improve their outcomes.Research in this area has relied on fewer and more limited measures,such as citations and user studies with small datasets.There is currently a critical need to find novel methods to quantify and evaluate the broader impact of research.This study will help scientists better comprehend the emotional impact of their work.Additionally,the value of understanding the public’s interest and reactions helps science communicators identify effective ways to engage with the public and build positive connections between scientific communities and the public.Originality/value:This study will extend work on public engagement with science,sociology of science,and computational social science.It will enable researchers to identify areas in which there is a gap between public and expert understanding and provide strategies by which this gap can be bridged.
基金supported by the National Natural Science Foundation of China (Grant No.61405115)the Natural Science Foundation of Shanghai (Grant No.14ZR1428400)+1 种基金the Innovation Project of Shanghai Municipal Education Commission (Grant No.14YZ099)National Basic Research Program of China (973 Program) (Grant No.2015CB352004)
文摘By studying the traditional spectral reflectance reconstruction method, spectral reflectance and the relative spectral power distribution of a lighting source are sparsely decomposed, and the orthogonal property of the principal component orthogonal basis is used to eliminate basis; then spectral reflectance data are obtained by solving a sparse coefficient. After theoretical analysis, the spectral reflectance reconstruction based on sparse prior knowledge of the principal component orthogonal basis by a single-pixel detector is carried out by software simulation and experiment. It can reduce the complexity and cost of the system, and has certain significance for the improvement of multispectral image acquisition technology.
