我国高等教育进入普及化发展阶段,第一代大学生在校占比持续上升且受先赋性不利因素的影响,在学业、社交、校园生活等方面表现不足,部分教育收获较低。高校图书馆的适时介入与助推可显著减少高等教育对该群体的无效供给,有效改善其大学...我国高等教育进入普及化发展阶段,第一代大学生在校占比持续上升且受先赋性不利因素的影响,在学业、社交、校园生活等方面表现不足,部分教育收获较低。高校图书馆的适时介入与助推可显著减少高等教育对该群体的无效供给,有效改善其大学体验感和受教育经历。文章以美国研究型大学图书馆为研究对象,运用系统性文献研究方法,从Web of Science核心合集和中国知网(CNKI)检索文献中梳理美国图书馆学界参与校园支持的研究进展;运用网络调研方法,调查美国13所研究型大学图书馆的服务举措。立足我国第一代大学生非经济因素群体困境,借鉴国外图书馆的支持理念和服务经验,建议我国“211工程”和“985工程”高校图书馆从减少服务障碍、搭建同伴支持平台、尽早开展信息素养和财经素养教育以及合作组织高影响力教育活动5个途径开展支持服务,以融入大学“三全育人”体系,助力大学生成长成才、促进教育公平和高质量发展。展开更多
Due to the complicated background of objectives and speckle noise, it is almost impossible to extract roads directly from original synthetic aperture radar(SAR) images. A method is proposed for extraction of road netw...Due to the complicated background of objectives and speckle noise, it is almost impossible to extract roads directly from original synthetic aperture radar(SAR) images. A method is proposed for extraction of road network from high-resolution SAR image. Firstly, fuzzy C means is used to classify the filtered SAR image unsupervisedly, and the road pixels are isolated from the image to simplify the extraction of road network. Secondly, according to the features of roads and the membership of pixels to roads, a road model is constructed, which can reduce the extraction of road network to searching globally optimization continuous curves which pass some seed points. Finally, regarding the curves as individuals and coding a chromosome using integer code of variance relative to coordinates, the genetic operations are used to search global optimization roads. The experimental results show that the algorithm can effectively extract road network from high-resolution SAR images.展开更多
文摘我国高等教育进入普及化发展阶段,第一代大学生在校占比持续上升且受先赋性不利因素的影响,在学业、社交、校园生活等方面表现不足,部分教育收获较低。高校图书馆的适时介入与助推可显著减少高等教育对该群体的无效供给,有效改善其大学体验感和受教育经历。文章以美国研究型大学图书馆为研究对象,运用系统性文献研究方法,从Web of Science核心合集和中国知网(CNKI)检索文献中梳理美国图书馆学界参与校园支持的研究进展;运用网络调研方法,调查美国13所研究型大学图书馆的服务举措。立足我国第一代大学生非经济因素群体困境,借鉴国外图书馆的支持理念和服务经验,建议我国“211工程”和“985工程”高校图书馆从减少服务障碍、搭建同伴支持平台、尽早开展信息素养和财经素养教育以及合作组织高影响力教育活动5个途径开展支持服务,以融入大学“三全育人”体系,助力大学生成长成才、促进教育公平和高质量发展。
文摘Due to the complicated background of objectives and speckle noise, it is almost impossible to extract roads directly from original synthetic aperture radar(SAR) images. A method is proposed for extraction of road network from high-resolution SAR image. Firstly, fuzzy C means is used to classify the filtered SAR image unsupervisedly, and the road pixels are isolated from the image to simplify the extraction of road network. Secondly, according to the features of roads and the membership of pixels to roads, a road model is constructed, which can reduce the extraction of road network to searching globally optimization continuous curves which pass some seed points. Finally, regarding the curves as individuals and coding a chromosome using integer code of variance relative to coordinates, the genetic operations are used to search global optimization roads. The experimental results show that the algorithm can effectively extract road network from high-resolution SAR images.
