数字化虚拟中国人体多模式三维影像融合研究

在中国数字化虚拟人体(CVHP)数据集的支持下,首次完成了数字化虚拟中国人体多模式三维医学影像(包括人体组织解剖切片数码影像数据、同期同一人体CT、MRI体层影像)融合技术,并给出相应图例。     

数字化可视人体的构建技术与应用研究

数字化可视人体，或称虚拟可视人体，是根据人体解剖学研究的全部数据综合构成的一系列数字化三维图像，而且可以虚拟地进行人体的一切生理活动。这种数字化可视人体可用于进行医学教学、模拟临床手术和放射治疗等，效果显著。本文阐述了制作方法和主要用途。     

在企业量值溯源系统中推行方针目标管理

1997年初，自贡硬质合金厂计控处将量值溯源系统的工作纳入计控处方针目标管理中，层层展开，逐级分解，一直落实到班组和职能人员。并建立了方针目标展开图，采用实施动态管理图、方针目标管理月报表、班组方针目标管理卡、职能人员方针目标管理卡和方针目标管理卡完成情况表，由专职计量管理员统一协调，落实各项措施的实施，开展日常管理工作；通过每周进行重点检查，每月通报方针目标（包括量值溯源系统工作）完成情况，加强了进度的管理与控制，实现了动态管理；计控处还通过召开诊断会，进行逐条分析、总结，找出在实现方针目标中存在…     

人体测量技术的现状与发展趋势

章介绍了人体测量的内容，讨论了其相关技术和软件，重点分析了非接触式三维数字化人体测量技术，并指出了人体测量技术的应用领域和发展趋势，对我国人体测量的研究具有重要的参考价值     

数字化图书馆管理系统设计

图书馆管理系统设计的核心应该是针对书籍的快速查找与分类,应该在注重读者的个人阅读隐私的同时,通过对大数据的合理分析完成对读者阅读喜好的分析。此外,数字化图书馆相较于传统图书馆拥有更快速、更精准以及更全面的馆藏查询系统,设计该系统应该注重用户使用习惯并结合图书馆馆藏需求,值得一提的是,该文设计的数字化图书馆管理系统有别于数字图书馆,依然需要与线下实体图书馆及其馆藏进行一一对应。     

人体测量及数字化人体模型技术的应用及进展

文章论述了人体测量学的发展历程并介绍了先进人体测量系统。重点介绍了数字化三维人体模型这一最新技术，实例论述了人体模型在各个领域的应用，并展望了人体模型的发展前景。     

PACS在中小型医院的应用前瞻性分析

目的：探讨PACS在中小型医院的应用价值和软硬件设备的合理配置。材料和方法；对大多数中小型医院的影像设备现状进行调查分析。结果：提出完成PACS设置必需的影像设备配置并对其数字化途径进行详细地解析。结论：在中小型医院根据实际情况按照总体规划，阶段实施，分期到位的原则，发展适合自己的PACS是切实可行的。     

误差综合测量的数字化码检仪

介绍了码检仪采用模拟量测量方式的原理、组成及存在的问题；提出了码检仪的数字化途径，原理和所有光栅检测参数的数字化测量，并对数字化测量进行了误差分析。通过对两种测量方式的比较，对数字化测量存在的问题提出了解决办法。     

美国Access IT第二阶段数字影院发展计划开始启动

Access IT曾与美国科视公司合作完成了4000块银幕的第一期数字影院发展计划；不久前Access IT又宣布制定了第二阶段数字影院发展计划，计划在3年内完成多达1万块银幕的数字化改造。     

浅析对部分DR进行检测的问题

DR系统，即直接数字化X射线摄影，由探测器、影像处理器、系统控制器等组成。X射线球管发射X射线，穿透人体后被探测器收集获取，直接形成数字信号，经计算机处理并成像．然后可进行一系列后期临床处理并打印成胶片。     

中央控制远程印刷文件云服务系统的研究

设计和构建了由中央控制服务器和企业文件服务器群构成的一种印刷文件云服务系统,实现了客户直接递交文件到企业印刷文件服务云,通过云端文件复制或转移,使企业实现了本地化管理远程数字文件资源,实现了自动化印刷工作流程控制。实验对云端服务器间相互确认、动态版面形成及自动文件转移等进行了测试。中央控制远程印刷文件云服务系统改变了远程印刷服务过程中的文件管理模式,为印刷企业实现云印刷服务和自动化数字印刷流程提供支持。     

Research on Electronic Document Management System Based on Cloud Computing

With the development of information technology, cloud computing technology has brought many conveniences to all aspects of work and life. With the continuous promotion, popularization and vigorous development of e-government and e-commerce, the number of documents in electronic form is getting larger and larger. Electronic document is an indispensable main tool and real record of e-government and business activities. How to scientifically and effectively manage electronic documents? This is an important issue faced by governments and enterprises in improving management efficiency, protecting state secrets or business secrets, and reducing management costs. This paper discusses the application of cloud computing technology in the construction of electronic file management system, proposes an architecture of electronic file management system based on cloud computing, and makes a more detailed discussion on key technologies and implementation. The electronic file management system is built on the cloud architecture to enable users to upload, download, share, set security roles, audit, and retrieve files based on multiple modes. An electronic file management system based on cloud computing can make full use of cloud storage, cloud security, and cloud computing technologies to achieve unified, reliable, and secure management of electronic files.     

融合配准的多站室外大场景激光点云分割

针对室外场景范围广、分割难度大、识别效果不显著等问题,提出了一种融合多站点云配准的室外大场景分割方法.首先,根据室外场景视野大、点云数据量庞大特点,选取多个视角下重叠区域较多的建筑场景点集,结合SAC-IA和ICP方法进行点云自动配准,从而构建出点云密度相对均匀的室外大场景完整结构;然后,选用公共数据集Semantic...     

采用激光跟踪仪测量飞机外形

利用激光跟踪仪测量空间点坐标的原理,通过“转站”建立飞机坐标系,采集飞机外形坐标点云,处理数据并建立数学模型。     

Determination of trace bismuth in human serum by cloud point extraction coupled flow injection inductively coupled plasma optical emission spectrometry

A cloud point extraction method for the preconcentration of ultra-trace bismuth in human serum prior to its determination by inductively coupled plasma optical emission spectrometry had been developed in this paper. The cloud point extraction method was based on the complex of Bi(III) with 8-hydroxyquinoline and Triton X-114 was used as non-ionic surfactant. The main factors affecting cloud point extraction efficiency, such as pH of solution, concentration of complexing agent, concentration of non-ionic surfactant, equilibration temperature and time were investigated in detail. An enrichment factor of 81 was obtained for the preconcentration of Bi(III) with 25 mL solution. Under the optimal conditions, the detection limit of Bi(III) is 0.12 μg L⁻¹. The relative standard deviation (n = 7) of determination was 2.3%, values of recovery of bismuth were from 92.3% to 94.7% for three samples. This method is simple, accurate, sensitive and can be applied to the determination trace bismuth in human serum.     

激光点云中散乱电子元器件分割方法

目的 针对散乱电子元器件计数过程中电子元器件分割困难的问题,提出一种基于点云簇平均法线夹角、平均点云密度边缘提取和区域生长阈值自适应的散乱电子元器件分割方法。方法 通过体素化处理、RANSAC算法和统计离群滤波算法对原始点云数据进行预处理,去除大量无关点云;使用欧式聚类算法对预处理结果粗分割得到电子元器件点云簇,以点云簇为阈值设置单元,避免阈值设置不合理的情况;通常边缘点较非边缘点法线夹角更大、邻域点更少,提出通过点云簇平均法线夹角和平均点云密度自适应约束来去除点云簇中边缘点的方法;对去边缘点后的点云簇细分割,根据细分割后点云簇的平均法线夹角进行区域生长阈值的自适应选择,通过改进的区域生长算法将每个电子元器件从点云簇中分割出来。结果 实验结果证明,文中方法分割正确率达97%以上,每10个目标分割耗时约345 ms。结论 提出的方法具有良好的准确性和实用性,分割效果优于传统分割算法,能够准确地将每个电子元器件从复杂场景中分割出来。     

基于GA-BP神经网络的散乱点云孔洞自动修补

点云孔洞修补作为点云数据处理中的关键技术,直接影响点云的质量和完整性。利用遗传算法（genetic algorithm,GA）优化的BP（back propagation,反向传播）神经网络（简称GA-BP神经网络）是一种修补效果较好的散乱点云孔洞修补方法。但基于GA-BP神经网络的散乱点云孔洞传统修补方法的多个步骤需借助逆向软件通过人机交互的方式完成,导致修补过程繁琐且耗时较长。为此,提出了一种基于GA-BP神经网络的散乱点云孔洞自动修补方法。通过计算机编程将孔洞识别、孔洞区域插值和孔洞修补相结合,实现从残缺点云模型直接到完整点云模型的自动修补,无须进行复杂的人机交互和数据转换。实验结果表明,所提出的方法可有效避免因数据转换而造成的数据失真,减少了人机交互工作量,方便而高效地修补了散乱点云的孔洞,且得到的修补点云密度均匀,这对提高点云孔洞修补效率和质量具有重要意义。     

A Proxy Re-Encryption with Keyword Search Scheme in Cloud Computing

With the widespread use of cloud computing technology, more and more users and enterprises decide to store their data in a cloud server by outsourcing. However, these huge amounts of data may contain personal privacy, business secrets and other sensitive information of the users and enterprises. Thus, at present, how to protect, retrieve, and legally use the sensitive information while preventing illegal accesses are security challenges of data storage in the cloud environment. A new proxy re-encryption with keyword search scheme is proposed in this paper in order to solve the problem of the low retrieval efficiency of the encrypted data in the cloud server. In this scheme, the user data are divided into files, file indexes and the keyword corresponding to the files, which are respectively encrypted to store. The improved scheme does not need to re-encrypt partial file cipher-text as in traditional schemes, but re-encrypt the cipher-text of keywords corresponding to the files. Therefore the scheme can improve the computational efficiency as well as resist chosen keyword attack. And the scheme is proven to be indistinguishable under Hash Diffie-Hellman assumption. Furthermore, the scheme does not need to use any secure channels, making it more effective in the cloud environment.     

基于三维点云聚类的坡度估计方法

为了提高火星探测器着陆时对坡度的估计精度,研究了一种基于三维点云数据聚类与随机搜索最优拟合平面的坡度估计方法。将通过激光雷达测量获得的三维点云数据进行稀疏表示,利用稀疏系数对数据点进行聚类与分割,划分子空间;对子空间中的数据点进行平面拟合,随机搜索最优拟合平面;根据最优拟合平面计算平面法向量之间夹角,其在数值上等于坡度角,从而完成坡度估计。实验表明:该方法可以对坡度进行较为准确的估计;与常用的坡度估计方法相比,相对误差较小。     

A hybrid point cloud alignment method combining particle swarm optimization and iterative closest point method

3D quality inspection is widely applied in many industrial fields including mould design, automotive and blade manufacturing, etc. A commonly used method is to obtain the point cloud of the inspected object and make a comparison between the point cloud and the corresponding CAD model or template. Thus, it is important to align the point cloud with the template first and foremost. Moreover,for the purpose of automatization of quality inspection, this alignment process is expected to be completed without manual interference. In this paper, we propose to combine the particle swarm optimization(PSO) with iterative closest point(ICP) algorithm to achieve the automated point cloud alignment. The combination of the two algorithms can achieve a balance between the alignment speed and accuracy, and avoid the local optimal caused by bad initial position of the point cloud.