基于深度学习的人体姿态估计方法综述

基于深度学习的人体姿态估计方法旨在通过构建合适的神经网络，直接从二维的图像特征中回归出人体姿态信息。主要按照2D人体姿态估计到3D人体姿态估计的顺序，并从单人检测与多人检测、稀疏的关节点检测与密集的模型构建等方面，对近年来基于深度学习的人体姿态估计方法进行系统介绍，从而初步了解如何通过深度学习的方法得到人体姿态的各个要素，包括肢体部件的相对朝向和比例尺度、骨骼关节点的位置坐标和连接关系，甚至更为复杂的人体蒙皮模型信息。最后,对当前研究面临的挑战以及未来的热点动向进行概述，清晰地呈现出该领域的发展脉络。     

潮流能水平轴水轮机在剪切来流下的水动力分析

采用基于计算流体力学方法的全尺度数值模拟计算,建立了适用于潮流能水轮机模拟的剪切来流环境,通过数值计算结果,对潮流能水轮机随时间变化的宏观力和流场特征进行了系统分析,探索水轮机在复杂工况下的水动力特性规律。结果表明,水轮机整个叶轮的总体平均受力在剪切流工况中未受到明显影响; 单个叶片的瞬态轴向力系数和瞬态轴向扭矩系数在旋转周期内出现了明显的周期性变化,且周期性变化幅值随转速增大而增大; 非定常的瞬时轴向扭矩和力的周期性振荡容易引起单个叶片的结构性振动,可能对水轮机的机械结构造成影响。     

甘草黄酮的提取工艺优化、含量测定及体外抗氧化活性研究

以95%乙醇为提取溶剂提取甘草黄酮,以提取率为评价指标,采用响应面法优化提取工艺;以芦丁为对照品,采用亚硝酸钠-硝酸铝-氢氧化钠比色法测定不同产地甘草黄酮含量;通过DPPH自由基清除反应,比较不同产地甘草黄酮的体外抗氧化活性。结果表明,醇提法提取甘草黄酮的最优工艺条件为:提取温度86.7℃、提取时间4.0 h、液料比80.0∶1.0(mL∶g);在此工艺条件下,甘肃、新疆、内蒙古的甘草黄酮含量分别为18.22 mg·g~(-1)、17.75 mg·g~(-1)、16.82 mg·g~(-1),其对DPPH自由基的清除率分别为63.82%、62.74%、51.41%;3个产地的甘草黄酮的含量及体外抗氧化活性大小顺序均为:甘肃新疆内蒙古。该结论可作为甘草原产地鉴别及质量评价的参考依据之一,为甘草药材的开发利用提供帮助。     

基于热电效应的高效环控系统

部分空间科学实验对环境温度有较高的要求，环境温度高于或低于空间科学系统能够提供的热沉温度，需要有可靠有效的加温降温处理措施。使用可靠性强的热电制冷片作为制冷制热方式和气液换热器二次换热来实现环境温度控制的需求，并对不同流体温度制冷制热效果进行分析，结果表明流体温度和目标温度差越小，热电制冷制热的效果越好。在环境温度制冷工况中，热电单元数量随电流增加先减少后增加，在制热工况中则单调递减，设计中需按照制冷工况进行热电单元数量的确定。当流体温度接近制冷制热的目标温度时，会出现整个系统总效率优于热电系统效率的区间。通过对热电单元和气液换热器的组合系统的性能计算，提供一种适于热电环控系统的计算方法和部件选型思路，对空间站环控系统的设计有重要参考意义。     

基于深度学习的视频跟踪研究进展综述

近年来深度学习迅猛发展，颠覆了语音识别、图像分类、文本理解等领域的算法设计思路。深度学习因其具备强大的特征提取能力，在图像识别领域的成绩尤为突出。然而深度学习与视频监控领域的结合并不多，由于深度模型具有多层网络结构，算法复杂度大，训练和更新模型时比较耗时，很难满足实时性要求。回顾了深度学习的发展史，介绍了最近10年来国内外深度学习主要模型，论述了基于深度学习的目标跟踪算法，指出了各算法的优缺点，最后对当前该领域存在的问题和发展前景进行了总结和展望。     

Headspace fingerprinting approach to identify the major pathway influencing volatile patterns of vinasse-cured duck processed by high pressure,as well as its impact on physicochemical and sensory attributes

As a decisive attribute, flavour could be influenced by HP treatments through multiple physical and chemical pathways within the high pressure (HP)-assisted meat curing process. This investigation aimed to identify the major pathway influencing volatile flavour patterns of two representative vinasse-cured duck (VCD) products with HP treatments (150–300 MPa/15 min), including wet and dry types, by employing headspace fingerprinting as an untargeted approach. Results suggested that HP treatments greatly lowered moisture contents and increased Warner-Bratzler shear force and thiobarbituric acid reactive substances of the cured samples. According to multivariate models, the volatile flavour patterns of the HP-processed VCD could be clearly separated from the unprocessed samples, but the VCD pressurised at different intensities represented similar volatile fingerprinting, which was validated by e-nose analysis. The discriminant analysis (OPLS-DA) model outlined vinasse-derived ethanol, acetic acid, 3-methyl-1-butanol, 2-methyl-1-butanol, phenethyl alcohol and 2-methyl-3-octanone as the major discriminant aromas across the unpressurised and pressurised samples.     

掺铒单模光纤飞秒脉冲激光器和放大器

为了获得一种被动锁模掺铒光纤振荡器及功率放大器，数值模拟出超短脉冲在光纤中的传输和演化过程，并基于此搭建了一种被动锁模掺铒光纤飞秒振荡器及功率放大器。实验获得了中心波长1560 nm、重复频率100 MHz、输出功率30 mW、脉冲宽度85 fs超短脉冲。通过采用PPLN晶体进行倍频，进一步获得了输出功率5 mW，中心波长780 nm的飞秒脉冲。该光纤激光器为全保偏光纤结构，具有体积小巧、可靠性高、稳定性好的特点。     

液压支架让缩性能试验特性分析与探讨

分析研究国家标准中液压支架让缩性能试验的技术要求,设计开发让缩性能试验系统,以双伸缩立柱液压支架为研究对象进行让缩性能试验分析与研究,为让缩性能试验的开展提供了试验条件,为液压支架国标的实施提供基础。     

On Cost Aware Cloudlet Placement for Mobile Edge Computing

As accessing computing resources from the remote cloud inherently incurs high end-to-end (E2E) delay for mobile users, cloudlets, which are deployed at the edge of a network, can potentially mitigate this problem. Although some research works focus on allocating workloads among cloudlets, the cloudlet placement aiming to minimize the deployment cost (i.e., consisting of both the cloudlet cost and average E2E delay cost) has not been addressed effectively so far. The locations and number of cloudlets have a crucial impact on both the cloudlet cost in the network and average E2E delay of users. Therefore, in this paper, we propose the Cost Aware cloudlet PlAcement in moBiLe Edge computing (CAPABLE) strategy, where both the cloudlet cost and average E2E delay are considered in the cloudlet placement. To solve this problem, a Lagrangian heuristic algorithm is developed to achieve the suboptimal solution. After cloudlets are placed in the network, we also design a workload allocation scheme to minimize the E2E delay between users and their cloudlets by considering the user mobility. The performance of CAPABLE has been validated by extensive simulations.