网络空间安全实训设计

为保障网络空间安全,需要加强网络空间安全人才队伍建设,实训是把学生培养成为高素质复合型人才的重要手段。通过分析我国网络空间安全人才队伍建设现状,构建实训课程体系和实训平台,设计实训大纲和实训竞赛平台,形成了校企合作、教学与竞赛相结合的实训体系。实践证明,此网络空间安全实训设计能有效提高学生的网络空间安全技术能力,具有一定的推广价值,为高校培养应用型、复合型人才提供了新思路。     

A small samples training framework for deep Learning-based automatic information extraction: Case study of construction accident news reports analysis

Knowledge management is crucial for construction safety management. Widely collected and well-organized safety-related documents are recognized to be significant in raising the workers' security awareness and then to prevent hazards and accidents. To improve document processing efficiency, automatic information extraction plays an important role. However, currently, automatic information extraction modeling requires large scale training datasets. It is a big challenge for the engineering industry, especially for the fields which heavily rely on the experts’ knowledge. Limited data sources, and high time and labor costs make it not practical to establish a large-scale dataset. This work proposed a natural language data augmentation-based small samples training framework for automatic information extraction modeling. With the designed cross combination-based text data augmentation algorithm, the deep neural network can be employed to build up automatic information extraction models without large-scale raw data and manual annotations. Characters semantic coding is employed to avoid word segmentation and make sure that the framework can be utilized in different writing language systems. The BiLSTM-CRF model is adopted as the detection core to conduct character classification. Through a case study of two independent accident news report datasets analysis, the proposed framework has been validated. A reliable and robust automatic information extraction model can be established, even though with small samples training.     

对抗样本三元组约束的度量学习算法

针对已有三元组约束的度量学习算法大多利用先验知识构建约束,一定程度上制约了度量学习算法性能的问题,本文借鉴对抗训练中样本扰动的思想,在原始样本附近学习对抗样本以构造对抗三元组约束,基于对抗三元组和原始三元组约束构建了度量学习模型,提出了对抗样本三元组约束的度量学习算法(metric learning algorithm with adversarial sample triples constraints,ASTCML)。实验结果表明,提出的算法既克服了已有固定约束方法受先验知识影响大的问题,也提高了分类精度,说明区分更加难以区分的三元组约束能够提升算法的性能。     

“顶岗置换”模式培养高师准幼儿教师的探讨

＂顶岗置换＂模式不仅促进了一线学前教师的职后培训,更有利于高师准幼儿教师的培养;同时,＂顶岗置换＂对高师准幼儿教师的培养提出了相应的挑战：顶岗对学生的高要求——能否从学生变为教师,顶岗对学生的低回报——能否从教中学。提出相应策略,促进＂顶岗置换＂模式下准幼儿教师的培养。     

A case study of developing ICT-supported pedagogy through a collegial practice transfer process

A collegial practice transfer process between more- and less-experienced teachers was examined in two cases that sought to encourage teachers to use information and communication technology (ICT) in a pedagogically meaningful way. Collegial practice transfer aims to offer new models for in-service teacher training. The process included guiding sessions, training materials presenting authentic pedagogical examples, and try-outs in the classroom. The success of practice transfer was examined through comparing the classroom practices of more- and less-experienced teachers applying the Pedagogical Infrastructure Framework, and through analyzing the tutored teachers' self-reported experiences in interviews. The process provided flexible support and gave self-confidence to the less-experienced teachers. Technology use was successful, but the tutored teachers designed less coherent tasks and weaker support for pupils' collaboration, knowledge construction and metacognition than their more-experienced colleagues. When tutoring, underlying educational ideologies and reasons should be explicated in addition to practical issues of classroom orchestration and technology use.     

基于Gabor小波自适应判别的单样本人脸识别

提出一种基于Gabor小波和LDA的人脸识别算法,借助通用训练集估计类内散布矩阵,使才传统LDA算法在单样本问题中可行。最后,在FERET人脸数据库上对所提方法进行了实验,结果表明该方法在单样本问题上取得了较好的结果。     

虚拟仿真技术的三维LNG培训系统

将虚拟三维仿真技术引入到LNG加注站员工培训系统中, 不仅提高了新员工的工作效率, 还能保证LNG加注站的安全运行. 文章系统的介绍了仿真系统的组成, 各子模块的设计模型, NURBS软件建模的方法, 演示了仿真系统的人机交互功能. 该仿真系统可用于专业教学与实习、新上岗员工操作技能培训以及在岗人员事故演练与轮训. 由于其逼真、生动、感染性好, 可更好的调动学员积极性, 提高员工培训效率和质量, 为LNG加注站的安全运行提供一定的技术保障. 集先进性、科学性、灵活性于一体的LNG仿真培训系统, 能更好的应用于LNG加注站相关教学与培训, 是一种有效的提高人员技术水平的手段.     

交会对接仿真电视图像TMO算法主观评价

通过对实时渲染仿真交会对接电视图像的主观评价,指出调和映射处理(TMO)算法的修正是提高仿真场景逼真度的方法.基于交会对接仿真电视图像TMO算法应用,分别针对S-curve算法、自适应对数算法和Reinhard算法设计了基于静态图像对比的亮度调和因子评价实验和基于动态场景对比的算法应用距离段评价实验,并对实验结果的均值、标准差以及HSD值进行了计算与分析;上述3种算法亮度调和因子分别为6.0,0.6和2.2,依次应用于远距离,中、近距离和靠拢距离时仿真电视图像有最佳评价和显示效果.实验结果表明,采用同种TMO算法处理的交会对接仿真图像动态场景真实感效果优于静态图像;在交会对接不同距离段内,仿真场景需要采用不同的TMO渲染方法.     

柬教官计算机专业外训教学探索

近年来,我室承担了柬埔寨教官计算机专业培训的外训教学任务,由于没有外训经验,教学过程中面临许多新问题,任务艰巨。如何有效实施计算机专业外训教学,提升外训教学水平是当前迫切需要探索的课题。从柬教官的特点和计算机专业的特点出发,对外训教学的规范化问题提出了几点看法,以期为提高教学效果提供借鉴。     

两种面向推荐系统的数据压缩方法

今日头条的服务器每天都会产生规模庞大的训练数据,为方便进行训练,这些数据都具有特定的格式和分布特征。使用不同类型的通用压缩算法(字典类型及非字典类型)进行测试,发现单独任何一种算法都无法在满足业务需求(速率需求和CPU占比等)的同时获得较为可观的压缩比。针对今日头条的训练数据,提出了分段聚类压缩和Hash recoding压缩两种策略。实验结果表明,分段聚类压缩方式在更好地保证了压缩率的同时提高了压缩速率的目的;Hash recoding压缩方式则更好地达到了以少量压缩速率的损失换取更可观的压缩率的目的。分段聚类方式搭配Gzip压缩算法的组合能使压缩速率提高300%以上;Hash recoding方式匹配Snappy压缩算法能使压缩率缩小50%以上。根据实际需求,不论选择哪种策略,对于降低今日头条的运营成本,提升业务处理的效率,提供更好的用户体验,都有一定意义。