Folklore research entails field trips, serve as secondary role. Writing of title, abstract and while textual study and circumstantial investigation merely keywords for folklore papers differs from that of other types ...Folklore research entails field trips, serve as secondary role. Writing of title, abstract and while textual study and circumstantial investigation merely keywords for folklore papers differs from that of other types of articles. Proceeding from writing strategies and linguistic features, the authors intend to share their experience with fellow researchers.展开更多
expressions like ＂socialism with Chinese character- istics＂ and ＂comprehensively deepening reform？＂ Then help is at hand with a program launched in December to enable foreigners understand politi- cal and cultura...expressions like ＂socialism with Chinese character- istics＂ and ＂comprehensively deepening reform？＂ Then help is at hand with a program launched in December to enable foreigners understand politi- cal and cultural phrases,展开更多
A proxy signature scheme with message recovery using self-certified public key is proposed, which withstands public key substitution attacks, active attacks, and forgery attacks. The proposed scheme accomplishes the t...A proxy signature scheme with message recovery using self-certified public key is proposed, which withstands public key substitution attacks, active attacks, and forgery attacks. The proposed scheme accomplishes the tasks of public key verification, proxy signature verification, and message recovery in a logically single step. In addition, the proposed scheme satisfies all properties of strong proxy signature and does not use secure channel in the communication between the original signer and the proxy signature signer.展开更多
In order to solve the problems of weak prediction stability and generalization ability of a neural network algorithm model in the yarn quality prediction research for small samples,a prediction model based on an AdaBo...In order to solve the problems of weak prediction stability and generalization ability of a neural network algorithm model in the yarn quality prediction research for small samples,a prediction model based on an AdaBoost algorithm(AdaBoost model) was established.A prediction model based on a linear regression algorithm(LR model) and a prediction model based on a multi-layer perceptron neural network algorithm(MLP model) were established for comparison.The prediction experiments of the yarn evenness and the yarn strength were implemented.Determination coefficients and prediction errors were used to evaluate the prediction accuracy of these models,and the K-fold cross validation was used to evaluate the generalization ability of these models.In the prediction experiments,the determination coefficient of the yarn evenness prediction result of the AdaBoost model is 76% and 87% higher than that of the LR model and the MLP model,respectively.The determination coefficient of the yarn strength prediction result of the AdaBoost model is slightly higher than that of the other two models.Considering that the yarn evenness dataset has a weaker linear relationship with the cotton dataset than that of the yarn strength dataset in this paper,the AdaBoost model has the best adaptability for the nonlinear dataset among the three models.In addition,the AdaBoost model shows generally better results in the cross-validation experiments and the series of prediction experiments at eight different training set sample sizes.It is proved that the AdaBoost model not only has good prediction accuracy but also has good prediction stability and generalization ability for small samples.展开更多
When conducting a literature review,medical authors typically search for relevant keywords in bibliographic databases or on search engines like Google.After selecting the most pertinent article based on the title’s r...When conducting a literature review,medical authors typically search for relevant keywords in bibliographic databases or on search engines like Google.After selecting the most pertinent article based on the title’s relevance and the abstract’s content,they download or purchase the article and cite it in their manuscript.Three major elements influence whether an article will be cited in future manuscripts:the keywords,the title,and the abstract.This indicates that these elements are the“key dissemination tools”for research papers.If these three elements are not determined judiciously by authors,it may adversely affect the manuscript’s retrievability,readability,and citation index,which can negatively impact both the author and the journal.In this article,we share our informed perspective on writing strategies to enhance the searchability and citation of medical articles.These strategies are adopted from the principles of search engine optimization,but they do not aim to cheat or manipulate the search engine.Instead,they adopt a reader-centric content writing methodology that targets well-researched keywords to the readers who are searching for them.Reputable journals,such as Nature and the British Medical Journal,emphasize“online searchability”in their author guidelines.We hope that this article will encourage medical authors to approach manuscript drafting from the perspective of“looking inside-out.”In other words,they should not only draft manuscripts around what they want to convey to fellow researchers but also integrate what the readers want to discover.It is a call-to-action to better understand and engage search engine algorithms,so they yield information in a desired and self-learning manner because the“Cloud”is the new stakeholder.展开更多
文摘Folklore research entails field trips, serve as secondary role. Writing of title, abstract and while textual study and circumstantial investigation merely keywords for folklore papers differs from that of other types of articles. Proceeding from writing strategies and linguistic features, the authors intend to share their experience with fellow researchers.
文摘expressions like ＂socialism with Chinese character- istics＂ and ＂comprehensively deepening reform？＂ Then help is at hand with a program launched in December to enable foreigners understand politi- cal and cultural phrases,
文摘A proxy signature scheme with message recovery using self-certified public key is proposed, which withstands public key substitution attacks, active attacks, and forgery attacks. The proposed scheme accomplishes the tasks of public key verification, proxy signature verification, and message recovery in a logically single step. In addition, the proposed scheme satisfies all properties of strong proxy signature and does not use secure channel in the communication between the original signer and the proxy signature signer.
文摘In order to solve the problems of weak prediction stability and generalization ability of a neural network algorithm model in the yarn quality prediction research for small samples,a prediction model based on an AdaBoost algorithm(AdaBoost model) was established.A prediction model based on a linear regression algorithm(LR model) and a prediction model based on a multi-layer perceptron neural network algorithm(MLP model) were established for comparison.The prediction experiments of the yarn evenness and the yarn strength were implemented.Determination coefficients and prediction errors were used to evaluate the prediction accuracy of these models,and the K-fold cross validation was used to evaluate the generalization ability of these models.In the prediction experiments,the determination coefficient of the yarn evenness prediction result of the AdaBoost model is 76% and 87% higher than that of the LR model and the MLP model,respectively.The determination coefficient of the yarn strength prediction result of the AdaBoost model is slightly higher than that of the other two models.Considering that the yarn evenness dataset has a weaker linear relationship with the cotton dataset than that of the yarn strength dataset in this paper,the AdaBoost model has the best adaptability for the nonlinear dataset among the three models.In addition,the AdaBoost model shows generally better results in the cross-validation experiments and the series of prediction experiments at eight different training set sample sizes.It is proved that the AdaBoost model not only has good prediction accuracy but also has good prediction stability and generalization ability for small samples.
文摘When conducting a literature review,medical authors typically search for relevant keywords in bibliographic databases or on search engines like Google.After selecting the most pertinent article based on the title’s relevance and the abstract’s content,they download or purchase the article and cite it in their manuscript.Three major elements influence whether an article will be cited in future manuscripts:the keywords,the title,and the abstract.This indicates that these elements are the“key dissemination tools”for research papers.If these three elements are not determined judiciously by authors,it may adversely affect the manuscript’s retrievability,readability,and citation index,which can negatively impact both the author and the journal.In this article,we share our informed perspective on writing strategies to enhance the searchability and citation of medical articles.These strategies are adopted from the principles of search engine optimization,but they do not aim to cheat or manipulate the search engine.Instead,they adopt a reader-centric content writing methodology that targets well-researched keywords to the readers who are searching for them.Reputable journals,such as Nature and the British Medical Journal,emphasize“online searchability”in their author guidelines.We hope that this article will encourage medical authors to approach manuscript drafting from the perspective of“looking inside-out.”In other words,they should not only draft manuscripts around what they want to convey to fellow researchers but also integrate what the readers want to discover.It is a call-to-action to better understand and engage search engine algorithms,so they yield information in a desired and self-learning manner because the“Cloud”is the new stakeholder.
