To quantitatively analyze main figure,field,agency and level of sponge city research in China,and clear research focus and hot spot in each year,by using the Full Text Database of Chinese Sci-tech Periodicals and othe...To quantitatively analyze main figure,field,agency and level of sponge city research in China,and clear research focus and hot spot in each year,by using the Full Text Database of Chinese Sci-tech Periodicals and other retrieval tools,the statistics and analysis of 3152 research literatures on sponge city published in domestic academic journals of 2004-2016 are conducted based on bibliometrics. It is found that since the concept of " sponge city" was firstly proposed in 2012,development research of sponge city involves 40 subject fields and is mainly published in 32 kinds of journals,which is dominated by natural science research( 1427 literatures). Researchers are mainly from each college and university,some design institutes and Chinese Academy of Sciences. The research could play certain guidance significance for further research and construction of ecological city construction in China.展开更多
Academic literature retrieval concerns about the selection of papers that are most likely to match a user's information needs. Most of the retrieval systems are limited to list-output models, in which the retrieva...Academic literature retrieval concerns about the selection of papers that are most likely to match a user's information needs. Most of the retrieval systems are limited to list-output models, in which the retrieval results are isolated from each other. In this paper, we aim to uncover the relationships between the retrieval results and propose a method to build structural retrieval results for academic literature, which we call a paper evolution graph(PEG).The PEG describes the evolution of diverse aspects of input queries through several evolution chains of papers. By using the author, citation, and content information, PEGs can uncover various underlying relationships among the papers and present the evolution of articles from multiple viewpoints. Our system supports three types of input queries: keyword query, single-paper query, and two-paper query. The construction of a PEG consists mainly of three steps. First, the papers are soft-clustered into communities via metagraph factorization, during which the topic distribution of each paper is obtained. Second, topically cohesive evolution chains are extracted from the communities that are relevant to the query. Each chain focuses on one aspect of the query. Finally, the extracted chains are combined to generate a PEG, which fully covers all the topics of the query. Experimental results on a real-world dataset demonstrate that the proposed method can construct meaningful PEGs.展开更多
Purpose-Extracting suitable features to represent an image based on its content is a very tedious task.Especially in remote sensing we have high-resolution images with a variety of objects on the Earth’s surface.Maha...Purpose-Extracting suitable features to represent an image based on its content is a very tedious task.Especially in remote sensing we have high-resolution images with a variety of objects on the Earth’s surface.Mahalanobis distance metric is used to measure the similarity between query and database images.The low distance obtained image is indexed at the top as high relevant information to the query.Design/methodology/approach-This paper aims to develop an automatic feature extraction system for remote sensing image data.Haralick texture features based on Contourlet transform are fused with statistical features extracted from the QuadTree(QT)decomposition are developed as feature set to represent the input data.The extracted features will retrieve similar images from the large image datasets using an image-based query through the web-based user interface.Findings-The developed retrieval system performance has been analyzed using precision and recall and F1 score.The proposed feature vector gives better performance with 0.69 precision for the top 50 relevant retrieved results over other existing multiscale-based feature extraction methods.Originality/value-The main contribution of this paper is developing a texture feature vector in a multiscale domain by combining the Haralick texture properties in the Contourlet domain and Statistical features using QT decomposition.The features required to represent the image is 207 which is very less dimension compare to other texture methods.The performance shows superior than the other state of art methods.展开更多
由于传统方法在图书馆文献信息智能检索中应用效果不佳,不仅平均正确率(Mean Average Precision,MAP)较低,而且衡量搜索引擎算法的指标(Discounted Cumulative Gain,DCG)具有较低的归一化止损值,为此提出应用数据挖掘的图书馆文献信息...由于传统方法在图书馆文献信息智能检索中应用效果不佳,不仅平均正确率(Mean Average Precision,MAP)较低,而且衡量搜索引擎算法的指标(Discounted Cumulative Gain,DCG)具有较低的归一化止损值,为此提出应用数据挖掘的图书馆文献信息智能检索方法。首先,利用数据挖掘技术估测出嵌入的检索词条与检索文本的相关性;其次,考虑用户反馈构建逻辑回归判断模型;最后,根据逻辑回归判断模型结合最佳权重实现信息检索。实验证明,设计方法MAP值为0.95~0.98,DCG归一化止损值在0.86以上,证明应用设计方法可更好地进行图书馆文献信息检索,应用效果更好。展开更多
Objective:This paper aims to evaluate the implementation effect of the diversified course assessment method reform.Methods:A diversified assessment method was implemented for 196 undergraduate nursing students.Student...Objective:This paper aims to evaluate the implementation effect of the diversified course assessment method reform.Methods:A diversified assessment method was implemented for 196 undergraduate nursing students.Students’mastery of key knowledge in“Nursing Research”was assessed through group reports on topic selection and literature retrieval,as well as the proposition level of the final examination.Results:81.6%of the students agreed with the course assessment method,and 97.9%believed studying“Nursing Research”would be helpful for future scientific research applications.Conclusion:Diversified assessment methods can help improve undergraduate nursing students’scientific research skills and comprehensive quality.展开更多
基金Supported by Science Research Fund of Yunnan Provincial Education Department(2017ZZX090)School-level Key Project of Kunming University(XJZD1602)"Study on Key Technology of Ecological Planting Mode of Balcony Vegetables"of Provincial-level"Quality Project"of Kunming University-Innovation and Entrepreneurship Training Program for College Students
文摘To quantitatively analyze main figure,field,agency and level of sponge city research in China,and clear research focus and hot spot in each year,by using the Full Text Database of Chinese Sci-tech Periodicals and other retrieval tools,the statistics and analysis of 3152 research literatures on sponge city published in domestic academic journals of 2004-2016 are conducted based on bibliometrics. It is found that since the concept of " sponge city" was firstly proposed in 2012,development research of sponge city involves 40 subject fields and is mainly published in 32 kinds of journals,which is dominated by natural science research( 1427 literatures). Researchers are mainly from each college and university,some design institutes and Chinese Academy of Sciences. The research could play certain guidance significance for further research and construction of ecological city construction in China.
基金Project supported by the National Key R&D Program of China(No.2018YFB0505000)the National Natural Science Foundation of China(No.61571393)
文摘Academic literature retrieval concerns about the selection of papers that are most likely to match a user's information needs. Most of the retrieval systems are limited to list-output models, in which the retrieval results are isolated from each other. In this paper, we aim to uncover the relationships between the retrieval results and propose a method to build structural retrieval results for academic literature, which we call a paper evolution graph(PEG).The PEG describes the evolution of diverse aspects of input queries through several evolution chains of papers. By using the author, citation, and content information, PEGs can uncover various underlying relationships among the papers and present the evolution of articles from multiple viewpoints. Our system supports three types of input queries: keyword query, single-paper query, and two-paper query. The construction of a PEG consists mainly of three steps. First, the papers are soft-clustered into communities via metagraph factorization, during which the topic distribution of each paper is obtained. Second, topically cohesive evolution chains are extracted from the communities that are relevant to the query. Each chain focuses on one aspect of the query. Finally, the extracted chains are combined to generate a PEG, which fully covers all the topics of the query. Experimental results on a real-world dataset demonstrate that the proposed method can construct meaningful PEGs.
基金Satellite Application Centre partially funds this project,Indian Space Research Organization(ISRO)under the grant No:ISRO/RES/3/789/18-19.The authors are thankful to the agency for supporting this research.
文摘Purpose-Extracting suitable features to represent an image based on its content is a very tedious task.Especially in remote sensing we have high-resolution images with a variety of objects on the Earth’s surface.Mahalanobis distance metric is used to measure the similarity between query and database images.The low distance obtained image is indexed at the top as high relevant information to the query.Design/methodology/approach-This paper aims to develop an automatic feature extraction system for remote sensing image data.Haralick texture features based on Contourlet transform are fused with statistical features extracted from the QuadTree(QT)decomposition are developed as feature set to represent the input data.The extracted features will retrieve similar images from the large image datasets using an image-based query through the web-based user interface.Findings-The developed retrieval system performance has been analyzed using precision and recall and F1 score.The proposed feature vector gives better performance with 0.69 precision for the top 50 relevant retrieved results over other existing multiscale-based feature extraction methods.Originality/value-The main contribution of this paper is developing a texture feature vector in a multiscale domain by combining the Haralick texture properties in the Contourlet domain and Statistical features using QT decomposition.The features required to represent the image is 207 which is very less dimension compare to other texture methods.The performance shows superior than the other state of art methods.
文摘由于传统方法在图书馆文献信息智能检索中应用效果不佳,不仅平均正确率(Mean Average Precision,MAP)较低,而且衡量搜索引擎算法的指标(Discounted Cumulative Gain,DCG)具有较低的归一化止损值,为此提出应用数据挖掘的图书馆文献信息智能检索方法。首先,利用数据挖掘技术估测出嵌入的检索词条与检索文本的相关性;其次,考虑用户反馈构建逻辑回归判断模型;最后,根据逻辑回归判断模型结合最佳权重实现信息检索。实验证明,设计方法MAP值为0.95~0.98,DCG归一化止损值在0.86以上,证明应用设计方法可更好地进行图书馆文献信息检索,应用效果更好。
基金Nursing Research Outcome of the Pilot Project for Course Assessment Reform in Sanya University(Project number:SYJGKH2022138)。
文摘Objective:This paper aims to evaluate the implementation effect of the diversified course assessment method reform.Methods:A diversified assessment method was implemented for 196 undergraduate nursing students.Students’mastery of key knowledge in“Nursing Research”was assessed through group reports on topic selection and literature retrieval,as well as the proposition level of the final examination.Results:81.6%of the students agreed with the course assessment method,and 97.9%believed studying“Nursing Research”would be helpful for future scientific research applications.Conclusion:Diversified assessment methods can help improve undergraduate nursing students’scientific research skills and comprehensive quality.
