基于XML的UML模型向AADL模型的自动转换

UML已经成为复杂系统建模的工业标准,并可借助代码自动生成工具实现从分析到编码的开发过程自动化;AADL具有精确的语义和严格的语法规范,可用于描述嵌入式实时系统的软、硬件体系结构,并能分析系统的功能及非功能属性。 UML和AADL模型的基本元对象有相互对应关系,并且两种模型的表示都能够采用标准的XML的交换格式。为充分发挥两种语言的优势,文中研究了UML模型向AADL模型的自动转换,以XML为媒介实现两种模型的元对象的对应转换,最终达到两种模型的转换,使用户在设计阶段能够结合运用AADL、UML工具的优点对系统进行分析。     

色谱顶空法测活度系数及对三元极性体系液液平衡预测

用气相色谱顶空分析法测定 18组部分互溶三元极性体系在完全互溶区的 3个组分活度系数 ,由此拟合出 U NIQU AC过量自由焓模型参数 ,再用 U NIQUAC方程预测液液平衡。这一方法曾很好地用在水-正烷烃 -醇体系。将此法拓展到含醇、酮、酯 ,醚、卤烷烃和水等多种极性组分的三元体系液液平衡的预测 ,其结果与文献的液液平衡数据比较 ,平均均方根误差 1.4 1% ,表明本法对含极性组分的体系仍然可行     

An ultrahigh-resolution image encryption algorithm using random super-pixel strategy

Multimedia Tools and Applications - Almost all existing image encryption algorithms are only suitable for low-resolution images in the standard image library. When they are used to encrypt...     

侵入物高速撞击下铰链式动车组的安全性

为探究侵入物高速撞击下铰链式动车组的安全性,在实物三维扫描重构的基础上,构建一种新的活体三维有限元层叠模型,并在LS-DYNA中进行摆锤侧面碰撞分析验证;通过铰链式动车组与活体在110 km/h速度下的碰撞仿真计算,讨论动车组运行的安全性以及吸能装置的可靠性.结果 显示:活体的有限元层叠模型既能保证计算精度,又能提高计算效率;在110 km/h的碰撞速度下,车体加速度为0.117g,轮对抬升量为0.238 mm,车钩每5 m长度的压缩量最大约为1.89 mm.各项指标都低于EN 15227标准,动车组行车安全性没有受到影响,吸能装置也能可靠工作.     

基于区域结构特征的城区LiDAR数据快速分类

机载激光雷达能够及时准确地获取大量具有精确三维位置信息的三维点云数据,在数字城市、森林防火、智能交通等领域有着广泛的应用。城市中心区域的三维点云数据往往会因为高大树木或植被的遮挡,造成建筑物等人造目标识别特别困难。本文通过直接的二次多项式拟合方式提取高大树木等植被与建筑物目标典型局部区域的区域信息,构建区域目标敏感的结构特征,进而,通过模糊逻辑即可完成三维点云数据的建筑物目标敏感的分类任务。实验结果表明,该方法能够快速有效地实现较大尺度范围内LiDAR点云数据的分类,具有较好的应用前景和推广能力。     

A Performance Evaluation of Classic Convolutional Neural Networks for 2D and 3D Palmprint and Palm Vein Recognition

Palmprint recognition and palm vein recognition are two emerging biometrics technologies. In the past two decades, many traditional methods have been proposed for palmprint recognition and palm vein recognition, and have achieved impressive results. However, the research on deep learning-based palmprint recognition and palm vein recognition is still very preliminary. In this paper, in order to investigate the problem of deep learning based 2D and 3D palmprint recognition and palm vein recognition in-depth, we conduct performance evaluation of seventeen representative and classic convolutional neural networks (CNNs) on one 3D palmprint database, five 2D palmprint databases and two palm vein databases. A lot of experiments have been carried out in the conditions of different network structures, different learning rates, and different numbers of network layers. We have also conducted experiments on both separate data mode and mixed data mode. Experimental results show that these classic CNNs can achieve promising recognition results, and the recognition performance of recently proposed CNNs is better. Particularly, among classic CNNs, one of the recently proposed classic CNNs, i.e., EfficientNet achieves the best recognition accuracy. However, the recognition performance of classic CNNs is still slightly worse than that of some traditional recognition methods.

     

深度学习在主动脉中膜变性病理图像分类中的应用

胸主动脉瘤和夹层（TAAD）是严重的心血管疾病之一,而中膜变性（MD）的组织学改变对疾病的诊断及早期干预具有重要的临床意义。针对病理图像的高度复杂性使得MD的诊断过程耗时费力且一致性差的问题,提出了一种基于深度学习的病理图像分类方法,并将其应用于四种MD病变类型以进行性能验证。该方法使用了一种改进的基于GoogLeNet的卷积神经网络模型,首先采用迁移学习来将先验知识应用于TAAD病理图像的表达,然后使用Focal loss和L2正则化来解决数据不平衡问题,从而进一步优化模型性能。实验结果表明,所提模型的平均四分类准确率达到98.78%,表现出较好的泛化性能。可见所提方法可以有效地提升病理学家的诊断效率。     

Ethereum smart contract security research: survey and future research opportunities

Blockchain has recently emerged as a research trend, with potential applications in a broad range of industries and context. One particular successful Blockchain technology is smart contract, which is widely used in commercial settings (e.g., high value financial transactions). This, however, has security implications due to the potential to financially benefit froma security incident (e.g., identification and exploitation of a vulnerability in the smart contract or its implementation). Among, Ethereum is the most active and arresting. Hence, in this paper, we systematically review existing research efforts on Ethereum smart contract security, published between 2015 and 2019. Specifically, we focus on how smart contracts can be maliciously exploited and targeted, such as security issues of contract program model, vulnerabilities in the program and safety consideration introduced by program execution environment. We also identify potential research opportunities and future research agenda.     

D550R系列焊条的焊接电参数分析

采用汉诺威焊接质量分析系统对D550R系列堆焊焊条的焊接电参数进行了精确的统计分析.研究结果表明,可以通过Suw,Siw,∑n(Us),∑n(Is),∑(T1),T3 mean,TC mean等判据来评价焊条与电参数直接相关的工艺性能.为科学分析这类焊条的电参数提供了一种全新的方法.     

基于垂直平分线的无线传感器网络定位改进算法

针对传统基于垂直平分线的区域定位算法定位精度低、迭代次数多等缺点,提出一种改进的垂直平分线算法IMBLA。根据未知节点接收到的两锚节点接收信号强度指示( RSSI)值的比值,移动两锚点的垂直平分线,再确定待定位节点与垂直平分线的位置关系。该算法应用基于参考锚节点的高斯校正模型进行RSSI测距,包括有障碍物时的模型,不但适合各种环境,还能有效防止恶意攻击。仿真结果表明,与MBLA和IPAIT算法相比,IMBLA算法的定位精度和网络覆盖率较高。