三维网格模型水印技术研究

对三维模型水印技术的研究现状及评价标准进行了系统阐述。首先阐述了三维模型的特点、数字水印的嵌入和提取过程,然后详细分析了三维模型水印技术的研究现状、空间域和变换域两大类水印方法的发展以及三维模型水印技术的评价标准。最后,对三维模型水印技术的研究现状和未来发展方向进行了总结和展望。     

基于模糊综合评价法的实验教学示范中心示范效应评价

以库恩的范式理论和班杜拉的社会学习理论为基础,构建实验教学示范中心示范效应影响因素三维模型,据此设计用于评价实验教学示范中心示范效应的指标体系,包括榜样、认知、环境3个因素一级指标和先进性、创新性、可观察性、易模仿性、传播性和辐射性6个二级指标,并应用层次分析法确定了各指标权重。在此基础上,根据示范效应评价指标具有主观性、模糊性特点,本文应用模糊综合评价法建立了示范效应评价模型,并应用该指标体系和评价模型对管理学科省级实验教学示范中心进行了评价。     

关于提高桌面虚拟实验建模效率的思考

在桌面虚拟实验开发中,建模得到实验对象的三维模型是至关重要的一步。如果能提高三维模型的开发效率,将会加快整个虚拟实验开发的进度。该文基于大学物理光学衍射实验的开发实例,分析了虚拟实验三维模型开发中诸多细节因素,进而总结了提高建模效率的几种方法。     

闽江沿岸景观三维重现研究

以4D数据为基础,利用三维地理信息系统软件IMAGIS,通过数据预处理、三维建模、纹理映射、三维场景生成等过程,建立了福州滨江景观三维可视地理信息系统.该系统具有数据集成管理、信息查询分析、规划方案比较、规划方案三维预评价以及成果输出等功能.并提出系统建立过程中应注意的问题,如DEM格网大小设置、模型数据量控制、避免多面重合以及设置纹理存放路径等.     

学科核心素养导向下高校体育课过程性评价模型与体系构建

基于学科核心素养,在阐述高校体育课程过程性评价的价值意蕴的基础上,借鉴DNA双螺旋模型理论与实践经验,建构了高校体育课过程性评价的双螺旋支撑模型,促使教师的教学链和学生的学习链在过程性评价的助力作用下实现教学相长的螺旋协同化发展。基于双螺旋支撑模型,从评价目的、评价内容、评价主体及评价方式四个方面探讨了具体实施方案,最终建构了“三维双螺旋”的高校体育课过程性评价体系,以期创建新型的体育学业评价观,推进高校体育课程考核改革。     

神经网络在计算机网络安全评价中的应用研究

针对计算机网络安全评价当中的神经网络所表现出来的运用价值以及特点进行有效分析,并进一步对其发展历程进行概述,并结合计算机网络安全所具有的相关概念、影响因素以及计算机系统当中具有的脆弱性等予以分析,通过可行性的、独立性、系统性以及准确性的远侧,重现构建计算机网络安全评价模型,并对神经网络当中的BP神经网络及粒子群进行优化进行阐述,最终在计算机网络安全当中对输入层、隐含层、输出层进行详细的分解和构建,促进整个网络安全性的提高,降低由于不必要的安全进而导致的各种损失和不良因素,使得整个计算机网络安全评价在运用当中更具安全性和应用价值。     

黄瓜叶缘形态特征及生长过程的建模和可视化

叶片形态模拟是植物建模和可视化的重要组成部分,而叶缘是叶片的一个重要形态特征。本文以黄瓜叶片为例,集成应用角点检测、折线拟合、样条曲线拟合等方法对生长中黄瓜叶片的各种叶缘进行了几何建模,并在此基础上模拟了叶缘在整个生长过程中的变化情况。最后结合VC++和openGL重构出了黄瓜叶缘生长的三维模型,实验结果表明该模型具有较好的真实感。     

竞赛试题对物理科学方法的考察

新课程标准强调三维目标,对过程和方法提出了明确的要求,让学生通过参与科学探究活动,初步认识科学研究方法的重要性,学习信息处理方法,有对信息有效性做出判断的意识。在科学探究能力目标中提出尝试考虑影响问题的主要因素,有控制变量的初步意识。可以说物理科学方法伴随着学习物理的整个过程,在初中阶段主要应用的物理科学方法有类比法、控制变量法、理想模型法等。     

基于Hopfield神经网络的高校评估模型构建

高校评估是一个复杂的过程,针对高校评估的很多不确定性因素,建立高校评估的Hopfield神经网络模型。网络模型以专家打分作为神经网络输入,以评价等级为输出,对已有评价体系中的主观性因素进行量化,自动建立输入和输出之间映射关系。该模型较已有的评价体系具有更高的准确率,评价结果更加合理公正。     

教学过程设计因素对教学总体评价的影响分析——以食品类专业选修课为例

保持学生在教学课堂上的注意力和学习动力长期以来都是一个挑战。为了探究本专业特色课程食品类选修课教学过程设计中各因素与学生对课程总体评价之间的关系,文章采用开放式的SEEQ问卷调查方法进行数据采集,并利用SPSS进行统计分析。结果显示,学生对课程的总体评价是满意,人口学变量对教学各因素均不存在显著差异（p>0.05）。由此构建多元线性回归模型,且回归模型的拟合度良好。由模型可知,在后期的教学设计持续改进时,必须将课堂教学各因素放在首位,重视雨课堂融进整个教学过程,最后适当的结合学生的兴趣及未来就业的规划。     

Real-time grouting monitoring and visualization analysis system for dam foundation curtain grouting

A real-time monitoring and 3D visualization analysis system is proposed for dam foundation curtain grouting. Based on the real-time control technology, the optimization method and the set theory, a mathematical model of the system is established. The real-time collection and transmission technology of the grouting data provides a data foundation for the system. The real-time grouting monitoring and dynamic alarming method helps the system control the grouting quality during the grouting process, thus, the abnormalities of grouting, such as jacking and hydraulic uplift, can be effectively controlled. In addition, the 3D grouting visualization analysis technology is proposed to establish the grouting information model (GIM). The GIM provides a platform to visualize and analyze the grouting process and results. The system has been applied to a hydraulic project of China as a case study, and the application results indicate that the real-time grouting monitoring and 3D visualization analysis for the grouting process can help engineers control the grouting quality more efficiently.     

Developing rigid constraint for the estimation of pose and structure from a single image

INTRODUCTION Pose and structural parameters analysis of 2Dimages sets find application in many areas such asobject recognition, motion estimation, navigationplanning, and structural analysis of 3D objects(Huang and Netravali, 1994), image communica-tion, and image coding (Mitiche and Aggarwal,1986). Normally, given one set of 3D object pointdata and their corresponding 2D projective imagepoint data, the 3D-2D calibration problem is re-ferred to as the estimation of the camera par…     

Developing rigid constraint for the estimation of pose and structure from a single image

Pose and structure estimation from a single image is a fundamental problem in machine vision and multiple sensor fusion and integration.In this paper we propose using rigid constraints described in different coordinate frames to iteratively estimate structural and camera pose parameters.Using geometric properties of reflected correspondences we put forward a new concept,the reflected pole of a rigid transformation.The reflected pole represents a general analysis of transformations that can be applied to both 2D and 3D transformations.We demonstrate how the concept is applied to calibration by proposing an iterative method to estimate the structural parameters of objects.The method is based on a coarse-to-fine strategy in which initial estimation is obtained through a classical linear algorithm which is then refined by iteration.For a comparative study of performance,we also implemented an extended motion estimation algorithm(from 2D-2D to 3D-2D case)based on epipolar geometry.     

双层CNN三维刚性与非刚性模型相似性分析

三维模型相似性分析是计算机视觉中的重点问题,如何构建其形状特征和对比函数是难点。随着深度学习出现,通过神经网络自动提取模型特征成为研究热点。构建了双层CNN网络,首先利用热核特征函数分别构建带有颜色的刚性和非刚性训练集与测试集,其次将数据集通过双层CNN网络进行模型训练,第一层实现类别初步判定,第二层实现同一模型刚性与非刚性形变区分。为了提高分类准确度,对初步分类错误的模型引入阈值判定,将其直接排除。通过实验分析,双层CNN网络刚性与非刚性的判别准确率达到99%。实验证明,该方法在模型相似性分析上是鲁棒的,且提取的特征不受人工干扰。     

基于人脸特征点和线性回归的3D人脸姿态估计方法

改进传统的活动形状模型法,准确地提取人脸特征点后,利用人脸特征点初步估计人脸姿态,以初步估计值为初始值,通过线性回归迭代算法,精确估计3D人脸空间姿态。实验结果表明,本文提出的新方法不仅可以获得稳定和唯一的3D人脸空间姿态．而且与同类方法比较具有较好的姿态估计精确度。     

Assessment for Learning of Design Teamwork Skills

This article seeks to contribute to the reflection around the training of future designers regarding teamwork. Collaboration, teamwork and negotiations are common everyday interactions that are now known to contribute positively to the design process. This article builds on a theoretical model that was initially proposed as a Ph.D. thesis contribution: the zone of proximal development for learning teamwork skills. The objective of this article is to share the first implementation of the model in a real educational situation and seize this opportunity to develop it further. The framework of assessment for learning and the concept of the zone of proximal development guide this research. The data collection is based on the observations of teamwork during a design seminar. The analysis is structured around the theoretical definitions of the model's components and in situ observations of the participants. This process guides us to share indicators allowing to confirm if a level or set of skills are achieved by a student. Plus, we propose a set of related teaching guidance to use when skills are identified as underdeveloped or to develop. Through this work, we wish to discuss how design students can be better equipped to enter the profession and play a significant role as team players.     

Self‐report Case‐studies: an experiment in own classroom data collection by teachers

The capacity of Bayesian methods in estimating complex statistical models is undeniable. Bayesian data analysis is seen as having a range of advantages, such as an intuitive probabilistic interpretation of the parameters of interest, the efficient incorporation of prior information to empirical data analysis, model averaging and model selection. As a simplified demonstration, we illustrate (1) how Bayesians test and compare two non‐nested growth curve models using Bayesian estimation with non‐informative prior; (2) how Bayesians model and handle missing outcomes in the context of missing values; and (3) how Bayesians incorporate data‐based evidence from a previous data set, construct informative priors and treat them as extra information while conducting an up‐to‐date analogy analysis.     

基于知识图谱的高校教学实验室综合改革模型分析

基于BP神经网络的高校教学实验室综合改革模型分析方法,缺乏可视化分析过程,存在分析结果误差大的弊端,为此提出基于知识图谱的高校教学实验室综合改革模型分析方法。该方法以中文论文数据库为样本,采用知识图谱技术和Citespace可视化软件,通过定量化、可视化已有文献的研究热点,绘制高校教学实验室综合改革模型的系列知识图谱,获取高校教学实验室综合改革模型数据。在此基础上采用基于信息归纳的概率粗糙集挖掘算法SRII,将原始数据集映射到一个便于粗糙集处理的数据空间,计算各个属性集合的近似统计值,实现对实验室综合改革模型数据的有效挖掘和分析。实验结果表明,所提方法能有效分析高校教学实验室综合改革模型,呈现出了改革模型未来改革热点的直观分析结果,为深化实验室综合改革提供有力条件。     

Multi-level spherical moments based 3D model retrieval

INTRODUCTION Recently, the development of 3D modelling and digitizing technologies has made the model generating process much easier. Also, through the Internet, users can download a large number of free 3D models from all over the world. All these lead to the necessity of a 3D model retrieval system. Content-based 3D shape retrieval for broad domains like World Wide Web has recently gained considerable attention in the Com- puter Graphics community (Zhang et al., 2001; Pat- rick, 20…     

稀疏过程在一类相依多险种风险模型中的应用

将汽车保险中的一类相依两险种风险模型扩展到相依三险种风险模型，用对齐次poisson过程的稀疏与分解将该模型转化为古典风险模型，并证明了转化的合理性，进而给出破产概率的一般表达式及其一个上界估计．这种转化的方法对类似的多险种相依情形同样适用．