Comparison of soil moisture at different depths for drought monitoring based on improved soil moisture anomaly percentage index

To better understand the characteristics and mechanisms of droughts at different drought stages, this study selected the Xiangjiang River Basin in China as the study area, and evaluated soil moisture (SM) at different depths for drought monitoring, through SM data simulated with the variable infiltration capacity (VIC) model. To solve the problem of unreasonable drought/wetness classifications based on the soil moisture anomaly percentage index (SMAPI), an improved soil moisture anomaly percentage index (ISMAPI) was developed by introducing the Box–Cox transformation. The drought/wetness frequency generated by ISMAPI demonstrated preferable spatial comparability in comparison with those from SMAPI. The lag time of ISMAPI relative to the standardized precipitation evapotranspiration index was closely related to soil depth, and was characterized by a fast response in shallow soil layers and a relatively slow response in deep soil layers. SM in shallow soil layers provided a measure for monitoring short-term droughts, whereas SM in deep soil layers provided a better measure for long-term persistent drought events. Furthermore, the occurrence and mitigation time of drought events identified by SM in deep soil layers usually lagged behind that identified by SM in shallow soil layers. Compared with deep SM, SM in shallow soil layers responded faster to meteorological anomalies, thereby resulting in shorter periods of SM persistence in shallow soil layers than in deep soil layers. This can explain the differences of SM at different depths in drought monitoring.     

Multiperson interaction recognition in images: A body keypoint based feature image analysis

Most interaction recognition approaches have been limited to single‐person action classification in videos. However, for still images where motion information is not available, the task becomes more complex. Aiming to this point, we propose an approach for multiperson human interaction recognition in images with keypoint‐based feature image analysis. Proposed method is a three‐stage framework. In the first stage, we propose feature‐based neural network (FCNN) for action recognition trained with feature images. Feature images are body features, that is, effective distances between a set of body part pairs and angular relation between body part triplets, rearranged in 2D gray‐scale image to learn effective representation of complex actions. In the later stage, we propose a voting‐based method for direction encoding to anticipate probable motion in steady images. Finally, our multiperson interaction recognition algorithm identifies which human pairs are interacting with each other using an interaction parameter. We evaluate our approach on two real‐world data sets, that is, UT‐interaction and SBU kinect interaction. The empirical experiments show that results are better than the state‐of‐the‐art methods with recognition accuracy of 95.83% on UT‐I set 1, 92.5% on UT‐I set 2, and 94.28% on SBU clean data set.     

核电厂重要人员动作分析与人因工程相结合研究

人因工程(HFE)是人机接口的复杂的系统工程。在核电厂(NPP)中,重要人员动作分析和人因工程管理之间具有紧密联系。人因工程/人机接口(HSI)活动能够为重要人员动作分析提供输人,用于识别电厂关键人员动作和风险重要人员动作。重要人员动作分析能够确定对电厂安全和可靠性至关重要的电厂情景、人员操作等,为人因工程/人机接口设计提供参考。对人因工程和重要人员动作分析相结合过程进行研究,基于NUREC-0711建立一套二者相结合的方法体系,详细阐述二者结合要点及实施流程。最后结合实际电厂给出工程应用实例,并通过概率安全评价(PSA)定量评价方法给出分析结果。该方法能够为核电厂重要人员动作识别及人因工程设计优化提供参考,提高电厂安全性和可靠性。     

Prediction of scouring around an arch-shaped bed sill using Neuro-Fuzzy model

In this study, Adaptive Neuro-Fuzzy Inference System (ANFIS) has been used to model local scouring depth and pattern scouring around concave and convex arch shaped circular bed sills. The experimental part of this research study includes seven sets of laboratory test cases which were performed in an experimental flume under different flow conditions. A data set consists of 2754 data points of scouring depth were collected to use in the ANFIS model. The ratio of arch diameter, D, to flume width, W, is used as a non dimensional variables in all test cases. The results from ANFIS model were compared with the results of ANN model obtained by Homayoon et al. [24] and previously presented models. The results indicated that for D/W equal to 1 and 1.2, the ANFIS models produced a good performance for convex and concave bed sills. As a result, the ANFIS models can be used as an alternative to ANN for estimation of scour depth and scour pattern around a concave bed sill installed with a bridge pier.     

Parametric study of the electrical to thermal power conversion in an inductively coupledrf plasma torch

An inductively coupled (ic) radio-frequency (rf) stabilized argon plasma was generated in a quartz tube using a 7 MHzrf generator. The electrical and thermal powers were measured and the efficiency of energy conversion was computed. The results indicate that for a constant power input, there is an optimum argon flow rate for which maximum energy conversion efficiency occurs.     

海水中VLF传播特性分析

本文以电磁波反射定律与折射定律为基础,建立了电磁波在两种介质分界面处的传播模型,研究了甚低频电磁波在导电媒质中的传播特性,推导了甚低频波在海面及海水中传播的电场表达式,分析了导电媒质对不同频率的电磁波所产生的影响,分析结果表明,甚低频电磁波在海水中的穿透深度较大,能够满足水下通信要求。     

激光焊接对接拼缝测量的微景深方法

对于复杂微细、错边量小的激光焊接拼缝测量,现有的视觉传感器方法不能稳定、可靠地提取出拼缝的中心位置、拼缝宽度等信息。为此,提出了基于微景深的激光焊接对接拼缝测量方法,该方法采用高倍光学放大镜头、工业CCD(Charge Coupled Device)/CMOS(Complementary Metal-Oxide-Semiconductor Transistor)相机和LED(Light-Emitting Diode)外部照明装置,以光学成像光轴与被测表面法矢呈45°的方式,组成的对接拼缝的非接触测量系统,既解决了显微放大时景深很小、测量范围小的问题,又解决了狭窄拼缝高光学放大倍数拼缝检测的难题。实验结果表明,该系统可快速准确地提取出拼缝中心坐标、拼缝宽度以及拼缝局部表面法矢。拼缝宽度测量精度优于5 μm,拼缝中心测量精度优于6 μm,可识别的最小拼缝宽度为0.02 mm,完全满足激光焊接对接狭窄拼缝的检测与自动跟踪的要求。     

基于单幅图像景深和大气散射模型的去雾方法

为恢复雾天图像对比度和颜色,更好地提取图像中的信息,根据海上开阔海域的特点,利用3维到2维透视投影模型,推导了海上图像任意像素点景深的计算公式,并结合暗原色先验知识,有效解决基准景深点的选取和天空亮度的选取问题,最后基于相对景深模型和大气散射模型,对单幅雾天图像进行清晰化处理。通过大量雾天降质图像的实验验证,该算法的去雾效果优于基于暗原色先验统计方法的效果。     

铍材应力常数的X射线法测试

在X2001应力分析仪上采用悬臂梁加载法测试了可以用于铍的X射线应力测试的5个衍射晶面的应力常数。结果表明,铍的5个衍射晶面的应力常数差异较大，在进行X射线应力分析时．应采用相应衍射晶面的应力常数，才能获得准确的应力分析结果。由于X射线对铍有较大的穿透深度，必须考虑X射线穿透深度对应力常数标定的影响。     

基于深度特性的帧间预测快速算法

高效视频编码(High Efficiency Video Coding, HEVC)的帧间预测部分存在很高的计算复杂度, 为了降低编码时间复杂度, 提出了一种基于深度特性的帧间预测快速算法。首先, 对帧间PU(Prediction Unit, PU)模式进行分类为规则和不规则块; 然后运用本文的方式定义当前CTU(Coding Tree Unit, CTU)的内容复杂程度; 最后对编码深度进行分区为SD(Small Depth, SD)、HD(High Depth, HD)区域, 位于SD区只进行规则的划分方式, 位于HD区根据当前CTU的复杂程度, 对复杂块进行不规则划分方式的遍历, 对简单块只进行规则划分, 从而实现快速编码算法。结果表明, 与HM16.9相比, 本文提出的算法在低时延和随机接入配置下分别降低了28.6%和23.8%的编码时间, 且编码性能不受影响。