终身体育视野下的学校体育自主学习教学模式的构建

学校体育应以终身体育思想作为指导,依据建构主义理论、认知学习理论、自主学习理论,结合兴趣、习惯、实际出发、主体性、灵活性原则,构建终身体育视野下的学校体育自主学习教学模式,注重教学情境设置,激发学生学习兴趣,引导学生开展自主学习和探究,采取较为全面的评价,以评促教,培养学生自主学习能力和终身体育的意识、习惯,使之受益一...     

Fine-grained legal entity annotation: A case study on the Brazilian Supreme Court

The exploration of legal documents in the Brazilian Judiciary context lacks reliable annotated corpus to support the development of new Natural Language Process (NLP) applications. Therefore, this paper presents a step toward exploring legal decisions with Named Entity Recognition (NER) in the Brazilian Supreme Court (STF) context. We aim to present a case study on the fine-grained annotation task of legal decisions, performed by law students as annotators where two levels of nested legal entities were annotated. Nested entities mapped in a preliminary study composed of four coarser legal named entities and twenty-four nested ones (fine-grained). The final result is a corpus of 594 decisions published by the STF annotated by the 76 law students, those with the highest average inter-annotator agreement score. We also present two baselines for NER based on Conditional Random Fields (CRFs) and Bidirectional Long-Short Term Memory Networks (BiLSTMs). This corpus is the first of its kind, the most extensive corpus known in Portuguese dedicated for legal named entity recognition, open and available to better support further research studies in a similar context.     

论桂林市文化创意产业集群模式选择

本文首先对桂林文化创意产业现状进行分析,之后提出三种不同集群发展模式所对应的具体发展方式,例如历史文化主题公园建设的纵向关联发展方式、文化产业园区建设的横向关联发展方式、大型演艺项目发展方式等等。利用模糊三角权定量分析方法结合桂林自然资源、历史文化资源的优势以及现在文化创意产业发展的情况,综合评价桂林现在文化创意产业发展态势,并且提出发展建议。     

Application of automated image analysis to the identification and extraction of recyclable plastic bottles

An experimental machine vision apparatus was used to identify and extract recyclable plastic bottles out of a conveyor belt. Color images were taken with a commercially available Webcam, and the recognition was performed by our homemade software, based on the shape and dimensions of object images. The software was able to manage multiple bottles in a single image and was additionally extended to cases involving touching bottles. The identification was fulfilled by comparing the set of measured features with an existing database and meanwhile integrating various recognition techniques such as minimum distance in the feature space, self-organized maps, and neural networks. The recognition system was tested on a set of 50 different bottles and provided so far an accuracy of about 97% on bottle identification. The extraction of the bottles was performed by means of a pneumatic arm, which was activated according to the plastic type; polyethylene-terephthalate （PET） bottles were left on the conveyor belt, while non-PET bottles were extracted. The software was designed to provide the best compromise between reliability and speed for real-time applications in view of the commercialization of the system at existing recycling plants.     

面向开放学习成果的微认证：概念理解与运作体系

传统证书在知识经济时代的资质认证与交流功能日显不足,对无处不在的开放学习进行灵活认证、在线验证与交流成为教育培训领域面临的重大挑战,而微认证实践就是其中最典型的有益探索。研究通过文献综述法,在分析国内外微认证现象的基础上,对微认证进行概念分析、要素解剖与理解辨析,重点对微认证的运作机制和体系进行了系统化阐述。研究认为微认证具有知识模块化、开发敏捷化、证据绩效化、记录可验证、结果可堆叠、凭证可移植等运作机制;开放徽章是微认证的典型流通凭证,是适合开放学习的后现代证书;微认证运作体系涵盖发行者、学习者、认可者和托管机构等四个互连的关键角色,以及生产、认证与消费微证书等三个相互支撑的子系统。微认证满足了开放学习结果的认证需求,有利于丰富新的人才资质交流话语体系,弥合教育培训供给与市场精准需求之间的鸿沟。     

科技创新影响区域绿色化的机理——基于绿色经济效率和空间计量的研究

运用数理统计和地理学空间分析方法对中国科技创新与绿色化的时空演变进行刻画并对科技创新对绿色化的影响机制进行验证,得出以下结论,(1)2000—2014年中国科技创新能力和绿色化水平逐年提升,二者的时序演变具有显著相似性;(2)科技创新和绿色化在空间分布上均由"大差距低水平"逐渐向"小差距高水平"的特点转变;(3)科技创新通过资源利用效应、投入产出效应、知识外溢效应以及人力资本效应对区域绿色化起到显著正向影响。     

学术机构引证中的中介关系

本文研究学术机构引证网络中的中介关系,识别和分析以中间人作为纽带的中介路径以及中介模式。选取信息计量领域机构数据,依据P(Top 10%)指数将学术机构划分为“强”“中”“弱”三个学术实力等级,结合中间人中介关系分析,得出三条主要知识交流路径,按照显著程度,依次为“中→弱”“弱→弱”和“强→弱”。中介模式方面,“强”等级中间人机构发挥主导中介作用。显著路径末端的机构与对应的始端机构具有潜在的知识交流需求,双方可在重合的研究主题和研究方向上推进交流合作。图6。表8。参考文献26。     

DCT-BP神经网络在表情识别中的应用

人脸表情识别作为智能化人机交互技术中的一个重要组成部分,近年来得到了广泛关注。本文提出了一种用DCT-BP神经网络算法来识别面部表情,先对图像进行灰度均衡和图像平滑的预处理,然后利用离散余弦变换获取图像的表情特征参数,最后利用前向反馈算法进行识别。     

Incremental cue phrase learning and bootstrapping method for causality extraction using cue phrase and word pair probabilities

This work aims to extract possible causal relations that exist between noun phrases. Some causal relations are manifested by lexical patterns like causal verbs and their sub-categorization. We use lexical patterns as a filter to find causality candidates and we transfer the causality extraction problem to the binary classification. To solve the problem, we introduce probabilities for word pair and concept pair that could be part of causal noun phrase pairs. We also use the cue phrase probability that could be a causality pattern. These probabilities are learned from the raw corpus in an unsupervised manner. With this probabilistic model, we increase both precision and recall. Our causality extraction shows an F-score of 77.37%, which is an improvement of 21.14 percentage points over the baseline model. The long distance causal relation is extracted with the binary tree-styled cue phrase. We propose an incremental cue phrase learning method based on the cue phrase confidence score that was measured after each causal classifier learning step. A better recall of 15.37 percentage points is acquired after the cue phrase learning.     

高校经济效益审计目标与模式刍议

“评建”已经成为全国普通高等学校的热点话题,并被社会所关注。从去年开始,教育部在评估中心网站上,向社会每年公布一次高等学校教学基本状态数据,同时公布迎评高校的自评报告、专家组进校考察评估意见、学校最终评估结论。从国家宏观管理、指导和高校建立健全教育教学质量保证长效机制的层面上看,开展对高校经济效益审计将呼之欲出。