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。     

Prediction of rock mass P wave velocity using blasthole drilling information

In this paper, the development of the models for the prediction of rock mass P wave velocity is presented. For model development, the database of 53 cases including widely used and recorded drilling parameters and P wave velocity was constructed from the field studies conducted in 13 open pit lignite mines. Both conventional linear, non-linear multiple regression and Adaptive Neuro Fuzzy Inference System (ANFIS) were used for model development. Prediction performance indicators showed that ANFIS model presented the best performance and it can successfully be used for the preliminary prediction of P wave velocities of rock masses.     

膨胀剂对约束条件下UHPC早期抗裂性能影响的试验研究

超高性能混凝土(UHPC)在钢桥面铺装结构中由于铺装材料受到钢板、栓钉等的约束,加上材料本身水胶比小,更易收缩,早期容易承受拉应力导致开裂。通过在拌和过程中添加膨胀剂可以起到减小收缩的作用,但该方法对于约束条件下的UHPC铺装的早期抗裂性能提升是否有促进作用,仍需通过更多试验进行合理评估和深入研究。通过圆环法对3组不同配方的UHPC在均匀约束条件下的早期抗裂性能进行定量测试,并将试验数据进行回归分析和计算,得到了各组的平均应力发展速率,进而评估了各组的开裂风险等级。试验结果表明,通过在UHPC中加入适量膨胀剂,可使其最终收缩应力减小,并可降低其收缩应力发展速率,进一步降低其在约束条件下的开裂风险。     

复杂土坝的渗流安全分析评价

根据福华山土坝的渗流观测资料,建立了测压管水位的回归统计模型,定量分析了各影响量(水位分量、时效分量)对测压管水位的影响效应。在此基础上,结合观测资料,采用有限元法反演了大坝各填筑区的渗透系数,并综合评价了大坝的渗流性态。     

基于保护分散式抽象方法的可扩展操作系统设计

为了提供高性能和柔性，操作系统内核应该只保留最小的功能，今天的操作系统大而低效，更缺乏柔性，我们提出了保护分散式操作系统抽象方法，集成了分散式操作系统抽象和保护抽象的方法，这种新的安全方式在分散式抽象系统里共享用户级的抽象，能够使非特权，不信任的任务在运行时定义并安全的共享生成的抽象，它在对相同的抽象重复调用时，通过消除上下文切换的需求和对通常情况进行优化，可获得较好的柔性，保护分散式抽象的设计强调简单并正确性证明，易于理解和使用，文章介绍了保护分散式操作系统抽象方法，并运用该方法开发了一个基于共享库的原型操作系统－ExLinux/LibOS.     

Effects of modeling means on properties of monitoring models of spot welding quality

Analyzing and modeling the relation between monitoring information during welding and quality information of the joints is the foundation of monitoring resistance spot welding quality. According to the means of modeling, the known models can be divided into three large categories: single linear regression models, multiple linear regression models and multiple non-linear models. By modeling the relations between dynamic resistance information and welding quality parameters with different means, this paper analyzes effects of modeling means on performances of monitoring models of resistance spot welding quality. From the test results, the following conclusions can be drawn: By comparison with two other kinds of models, artificial neural network (ANN) model can describe non-linear and high coupling relationship between monitoring information and quality information more reasonably, improve performance of monitoring model remarkably, and make the estimated values of welding quality parameters more accurate and reliable.     

Semiparametric Estimation in Time‐Series Regression with Long‐Range Dependence

Abstract. We consider semiparametric estimation in time‐series regression in the presence of long‐range dependence in both the errors and the stochastic regressors. A central limit theorem is established for a class of semiparametric frequency domain‐weighted least squares estimates, which includes both narrow‐band ordinary least squares and narrow‐band generalized least squares as special cases. The estimates are semiparametric in the sense that focus is on the neighbourhood of the origin, and only periodogram ordinates in a degenerating band around the origin are used. This setting differs from earlier studies on time‐series regression with long‐range dependence, where a fully parametric approach has been employed. The generalized least squares estimate is infeasible when the degree of long‐range dependence is unknown and must be estimated in an initial step. In that case, we show that a feasible estimate which has the same asymptotic properties as the infeasible estimate, exists. By Monte Carlo simulation, we evaluate the finite‐sample performance of the generalized least squares estimate and the feasible estimate.     

Simultaneous Spectrophotometric Determination of Three Components Including Deoxyschizandrin by Partial Least Squares Regression

1IntroductionWuweizi is a traditional Chinese herb,usually usedto cure cough,asthma,neurasthenic,hepatitisetc.Theactive ingredients in wuweizi are5%-22%lignan,themain components of which include deoxyschizandrin,schizandrin andγ-Schizandrin.Forthe purpos…     

均匀设计法分析制备过程对钴钼硫化物催化剂机械强度的影响

建立了CoMoP/Al2O3加氢精制催化剂机械强度及其可靠性在制备过程中的数学模型,采用均匀设计考察了浸渍、干燥、煅烧、硫化4个制备过程中,浸渍时间、干燥温度、干燥时间、煅烧温度、煅烧时间、硫化温度和硫化升温速率7个实验因子对催化剂强度均值、Weibull模量的影响,同时考察了这些因素对颗粒密度的影响。方差分析表明所有模型都是充足的。实验结果表明,硫化过程是影响催化剂强度均值的主要过程。在实验范围内提高硫化温度、降低硫化时的升温速率有利于提高催化剂的强度。影响催化剂Weibull模量的因素主要为各个制备过程的交互效应。要提高催化剂强度的可靠性就必须全面考虑催化剂制备的各个过程,特别是各个制备过程的交互效应。