Robust3D: a robust 3D face reconstruction application

In the process of reconstructing a historical event such as a rock concert only from video, the reconstruction of faces and expressions of the musicians is obviously important. However, in the process of rebuilding appearance, because of the low quality of the video of the recorded concert, the result of the reconstruction may be far from the real appearance. In this paper, a robust 3D face reconstruction application is described that can be applied to a video recording. The application first uses DeblurGAN program to run anti-ambiguity calculation and removes the ambiguity in the concert video. Then, the super-resolution program is used to enlarge every frame of the concert video by four times, thus making every frame of the video clearer. Finally, the 3D faces are obtained after 3D reconstruction of the processed video frames via the 3DMM_CNN program.

     

半城子水库水生态健康评价

参照《水生态健康评价技术规范》中的评价方法及评价体系,对密云水库上游半城子水库水生态健康状况进行评价,评价结果显示:半城子水库水生态健康综合指数为83.79,处于评价水平中的健康等级.根据评价结果,从村庄生活污染控制、河道生态修复及库区水质改善等方面提出建议.通过对河湖生态系统的现状及存在的问题进行诊断,来评估北京市河湖水生态系统的健康状况,对加快推进水生态文明建设具有重要意义.     

基于Hessian矩阵跟踪算法在血管新生量化中的应用

血管新生与肿瘤的生长密切相关,CAM(鸡胚绒毛尿囊膜)是研究血管新生的常用载体,所以通常对CAM中特定区域的血管分割量化来衡量抗肿瘤药物对血管的抑制作用.本文提出一种CAM图像分割算法,首先利用Hessian矩阵下多尺度分析得到一个初始的CAM血管轮廓,在此基础上跟踪未知血管,得到的最终分割结果.最后,对分割出的CAM血管进行骨架提取、裁剪等处理,计算出图像中血管的密度、长度和分叉点个数等量化指标,综合评价血管的生长情况.在相同系列的CAM图像上和其他方法进行实验对比.结果显示基于Hessian矩阵跟踪算法可以为血管新生状况提供有效的分析,尤其对微小血管的检测比较优越,而且具有更高的准确率.     

金属有机框架复合材料的制备及其性能研究

通过气态扩散作用,合成了MIL-101(Cr)@[Fe(HB(pz)3)2]、NH2-MIL-101(Al)@[Fe(HB(pz)3)2]和MIL-100(Al)@[Fe(HB(pz)3)2]3种MOFs材料@([Fe(HB(pz)3)2])复合物。采用红外光谱仪、原子吸收光谱仪、X射线衍射仪、物理吸附仪对3种MOFs材料@[Fe(HB(pz)3)2]复合物的组成、结构和性能进行表征测试。测试结果表明:[Fe(HB(pz)3)2]成功进入MOFs材料的孔洞中,形成了MOFs材料@[Fe(HB(pz)3)2]的复合物;MOFs材料的孔洞结构使[Fe(HB(pz)3)2]形成了一层保护外壁,从而使复合物的热稳定性和化学稳定性。经原子吸收光谱测试,可知MIL-101(Cr)@[Fe(HB(pz)3)2]、NH2-MIL-101(Al)@[Fe(HB(pz)3)2]和MIL-100(Al)@[Fe(HB(pz)3)2]中分别含有质量分数为8.11%,7.42%和1.64%的[Fe(HB(pz)3)2]。最后,对比分析了MIL-101(Cr)@[Fe(HB(pz)3)2]、NH2-MIL-101(Al)@[Fe(HB(pz)3)2]与[Fe(HB(pz)3)2]经多次转变后的颜色变化情况,实验结果表明,MOFs材料@[Fe(HB(pz)3)2]的复合物可应用到防伪包装材料之中。     

Multimedia cloud transmission and storage system based on internet of things

For the issues of large space and storage security of multimedia files, we analyzed the impact of access control and cloud storage on multimedia file, and proposed a mixed security cloud storage framework based on Internet of Things. This paper introduced the concept of multimedia protection into the method based on role access control. Moreover, we also adopted a scheme based on the combination of multimedia data state and role access control. At the same time, all input and output devices were connected to this system. Internet of Things is used to judge whether circuits are connected and whether the devices are normally operated, so as to improve the access efficiency. On this basis, we also described in detail the complete process of registration, role assignment, multimedia file owner’s request for data encryption, and user login and access to multimedia file. According to the result, this scheme can be used to resist the known attacks. It guarantees security of multimedia files.     

Detecting ground control points via convolutional neural network for stereo matching

In this paper, we present a novel approach to detect ground control points (GCPs) for stereo matching problem. First of all, we train a convolutional neural network (CNN) on a large stereo set, and compute the matching confidence of each pixel by using the trained CNN model. Secondly, we present a ground control points selection scheme according to the maximum matching confidence of each pixel. Finally, the selected GCPs are used to refine the matching costs, then we apply the new matching costs to perform optimization with semi-global matching algorithm for improving the final disparity maps. We evaluate our approach on the KITTI 2012 stereo benchmark dataset. Our experiments show that the proposed approach significantly improves the accuracy of disparity maps.     

Iterative quadtree decomposition based automatic selection of the seed point for ultrasound breast tumor images

Based on seed region growing method, lesion segmentation for ultrasound breast tumor images often requires manual selection of the seed point, which is both time-consuming and laborious. To overcome this limit, this paper attempts to explore an automatic method for finding the seed point inside the tumor. Two criteria combining iterative quadtree decomposition (QTD) and the gray characteristics of the lesion are thus designed to locate the seed point. One is to seek the biggest homogenous region and the other is to select the seed region where the seed point is found. Furthermore, this study validates the proposed algorithm through 110 ultrasonic breast tumor images (including 58 malignant tumor images and 52 benign tumor images). According to the needs of the seed region growing algorithm, if the seed point is found inside the tumor, it means the proposed method is correct. Otherwise, it means that the method is a failure. As the quantitative experiment results show, the proposed method in this paper can automatically find the seed point inside the tumor with an accuracy rate of 97.27 %.     

部队武器装备管理机制概念解析

以国内外相关理论为参考,系统梳理了部队武器装备管理机制的概念,得出其定义为:在部队武器装备管理系统内各个要素之间相互作用的方式和机理。围绕定义,进一步阐明了部队武器装备系统管理要素构成,并分析了诸要素之间的作用机理和模拟了要素作用图,认为诸要素之间需通过5种稳定有序的组合方式相互联系、相互作用来实现部队武器装备管理系统的有序运动。     

基于疲劳理论的汽车空气悬架结构件的弯曲强度计算

针对某种型号客车的空气悬架，应用ANSYS软件对弹簧支架进行了有限元分析，计算了弹簧支架的应力、变形特性，在此基础上计算了弹簧支架的疲劳强度。     

A Bayesian approach for sleep and wake classification based on dynamic time warping method

Sleep plays a significant role in human’ smental and physical health. Recently, the associations between lack of sleep and weight gain, development of cancer and many other health problems have been recognized. Then monitoring the sleep and wake state all night is becoming a hotspot issue. Traditionally it classified by a PSG recording which is very costly and uncomfortable. Nowadays, with the advance of internet of things, many convenient wearable devices are being used for medical use, like measuring the heart rate (HR), blood pressure and other signals. With the sleep quality monitor problem, the key question is how to discriminate the sleep and weak stage from these signals. This paper proposed a Bayesian approach based on dynamic time warping (DTW) method for sleep and wake classification. It used HR and surplus pulse O2 (SPO2) signals to analyze the sleep states and the occurrence of some sleep-related problems. DTW is an algorithm that searches an optimal alignment between time series with scaling and shifting and Bayesian methods have been successfully used for object classification in many study. In this paper, a three-step process is used for sleep and wake classification. In the first step, the DTW is used to extract features of the original HR and SPO2 signals. Then a probabilistic model is introduced for using the Bayesian classification for uncertain data. And in the classification step, the DTW features are used as the training dataset in the Bayesian approach for sleep and wake classification. Finally, a case study form a real-word applications, collected from the website of the Sleep Heart Health Study, is presented to shown the feasibility and advantages of the DTW-based Bayesian approach.