医院级CT辐射剂量及诊断剂量水平研究

探讨医院级各部位CT扫描辐射剂量及成人CT检查诊断剂量水平。采集2018年2月—2019年1月本院在GE Light Speed 16 CT设备上进行诊断性CT检查的全部成年人共15 440例的CT检查数据,按照检查部位进行分类,统计各部位的容积剂量指数(CTDI_vol)、剂量长度乘积(DLP)。使用SPSS 19统计软件分析CTDI_vol、DLP的四分位数并计算有效剂量(ED)。结果表明,各部位CTDI_vol的诊断剂量参考水平(DRL)值为:颅脑87.75 mGy、肺部8.09 mGy、上下腹15.82 mGy、上下腹盆腔15.79 mGy;各部位DLP的诊断剂量参考水平(DRL)值为:颅脑1 053.03 mGy·cm、肺部245.19 mGy·cm、上下腹269.96 mGy·cm、上下腹盆腔835.20 mGy·cm。研究中发现肺部CTDI_vol、DLP的DRL值(分别为8.09 mGy、245.19 mGy·cm)低于我国其他地区和其他国家的DRL值;60岁以下患者肺部CT检查CTDI_vol、DLP的DRL值低于8.09 mGy、245.19 mGy·cm,60岁以上患者肺部CT检查CTDI_vol、DLP的DRL值高于8.09 mGy、245.19 mGy·cm。通过研究可以确定医院级各部位CT检查辐射剂量及成人CT检查诊断剂量水平,能为优化CT检查扫描技术和监测辐射剂量提供基础。     

Learning a Deep Predictive Coding Network for a Semi-Supervised 3D-Hand Pose Estimation

In this paper we present a CNN based approach for a real time 3D-hand pose estimation from the depth sequence. Prior discriminative approaches have achieved remarkable success but are facing two main challenges: Firstly, the methods are fully supervised hence require large numbers of annotated training data to extract the dynamic information from a hand representation. Secondly, unreliable hand detectors based on strong assumptions or a weak detector which often fail in several situations like complex environment and multiple hands. In contrast to these methods, this paper presents an approach that can be considered as semi-supervised by performing predictive coding of image sequences of hand poses in order to capture latent features underlying a given image without supervision. The hand is modelled using a novel latent tree dependency model (LDTM) which transforms internal joint location to an explicit representation. Then the modeled hand topology is integrated with the pose estimator using data dependent method to jointly learn latent variables of the posterior pose appearance and the pose configuration respectively. Finally, an unsupervised error term which is a part of the recurrent architecture ensures smooth estimations of the final pose. Experiments on three challenging public datasets, ICVL, MSRA, and NYU demonstrate the significant performance of the proposed method which is comparable or better than state-of-the-art approaches.      

Automated classification of simulated wind field patterns from multiphysics ensemble forecasts

In this study, we have proposed an automated classification approach to identify meaningful patterns in wind field data. Utilizing an extensive simulated wind database, we have demonstrated that the proposed approach can identify low‐level jets, near‐uniform profiles, and other patterns in a reliable manner. We have studied the dependence of these wind profile patterns on locations (eg, offshore vs onshore), seasons, and diurnal cycles. Furthermore, we have found that the probability distributions of some of the patterns depend on the underlying planetary boundary layer schemes in a significant way. The future potential of the proposed approach in wind resource assessment and, more generally, in mesoscale model parameterization improvement is touched upon in this paper.     

Two-dimensional temperature distribution estimation for a cross-flow planar solid oxide fuel cell stack

The uniform temperature distribution of a cross-flow planar solid oxide fuel cell (SOFC) stack plays an essential role in stack thermal safety and electrical property. However, because of the strict requirements in stack sealing struture, it is hard to acquire the temperature inside the stack using thermal detection devices within an acceptable cost. Therefore, accurately estimating the two-dimensional (2-D) temperature distribution of the cross-flow stack is crucial for its thermal management. In this paper, Firstly, a 2-D mechanism model of a cross-flow planar SOFC stack is established. The stack is divided into 5*5 nodes along the gas flow directions, which can reflect the stack states with moderate computational burden. Then, experimental test data is utilized to modify and validate the stack model, guaranteeing the model accuracy as well as the reliability of model-based state estimator design. Finally, easily-measured stack inputs and outputs are selected, and a temperature distribution estimator combined with unscented kalman filter (UFK) approach is developed to achieve accurate and fast temperature distribution estimation of a cross-flow SOFC stack. Simulation results demonstrate that the UKF-based temperature distribution estimator can precisely and quickly achieve the temperature distribution estimation of the cross-flow stack under both static state and dynamic state changes and is applicable to cross-flow stacks with different size or cell number as well, the maximum estimated absolute error is less than 0.15 K with an absolute error rate of 0.015%, which indicates the developed estimator has good estimation performances.     

平原地区城市湖泊防洪与景观功能协调研究——以枝江市金湖为例

为了使城市湖泊尽可能滞蓄雨洪、发挥景观功能、打造良好的居民"亲水空间",以枝江市金湖为例,根据金湖主要泄洪渠道的实际情况,利用Mike 21模型模拟计算汛限水位值,按照景观水位确定大、小洪水工况下合理的水位。在此基础上,提出传统的静态景观水位与改进的动态景观水位两种方案。结果表明:以50年一遇、30年一遇为代表的大洪水工况下合理景观水位为40.7 m,以20年一遇、10年一遇为代表的小洪水工况合理景观水位为41.3 m;静态方案采用50年一遇洪水计算结果为标准执行,将40.7 m作为金湖固定的景观水位;动态方案水位可在41.3~40.7 m之间波动;金湖适宜采用动态景观水位运行方案,水位可在40.7~41.3 m之间波动;根据短期预报及历史监测资料分析后合理调度,将41.3 m作为金湖常水位,确定预测洪水大小后调整水位迎战洪水。据此,可在充分利用水资源的同时有效协调景观高水位需求与防洪之间的矛盾。     

消声元件安装位置对消声效果的影响

分别以消声量和管口阶次噪声作为评价指标,研究消声元件安装位置对消声效果的影响规律,设计在直管不同位置安放四分之一波长管的消声量测量试验对消声量评价。结果表明:设计频率声模态下,在反节点处安装波长管消声量最大,与理论分析完全吻合;进一步对消声量进行仿真计算,结果与试验完全相符。对于管口噪声指标评价,设计频率为267 Hz的谐振腔解决某发动机4000 r/min时进气管口存在4阶噪声引起的噪声峰值问题,对比谐振腔安装在进气管路该频率附近的声模态反节点和节点位置的管口4阶噪声,可知谐振腔布置在反节点位置比节点位置噪音降低了24 dB。两个案例充分证明声学系统模态反节点位置是消声元件的最佳布置位置。     

水位骤降对下伏隧道堤防安全影响研究

建立了考虑水位骤降条件下的下伏隧道堤防模型,依托湘江某下伏隧道堤防工程,基于堤防边坡渗流原理,结合有限元应力计算,探讨了不同水位骤降速率下的浸润线情况,计算了堤防安全系数。研究结果表明:湘江水位骤降速率越快,浸润线变化范围越大,浸润线变化范围与水位降落速率成正比;湘江水位骤降速度在3 m/d^4 m/d,水位降到28.8 m时,堤岸失去稳定;水位骤降并非整个过程中堤岸均处于失稳状态,而是水位降至某高度后堤岸失稳,骤降速率增快对堤防安全系数有一定负面作用。研究结果对隧道下穿堤防建设具有一定指导意义。     

基于改进交叉熵算法的电力系统随机生产模拟

蒙特卡洛模拟的计算效率与系统的可靠性密切相关，在其用于高可靠性系统的随机模拟时存在计算效率偏低的问题。为此，提出了一种基于多层交叉熵与对偶变数抽样技术相结合的随机模拟算法。首先使用多层交叉熵构造零方差概率密度函数的近似函数，提高小概率失效事件的抽取概率；其次基于已构造的近似概率函数，采用对偶变数抽样法进行抽样，进一步提高抽样的收敛速度。以IEEE RTS修改系统为例进行了算例分析，算例结果验证了所提出的基于改进交叉熵的电力系统随机生产模拟算法的有效性。     

自适应SA-PSO优化的威布尔混合分布参数估计方法及应用

针对采用传统参数估计方法得到的模型拟合误差较大的问题，建立多重威布尔混合分布参数估计的非线性最小二乘模型，并提出基于模拟退火（SA）思想的自适应粒子群（PSO）算法进行求解。在PSO算法优化过程中，采用自适应方法调整惯性权重和加速因子，加快其收敛速度；引入模拟退火机制，根据Metropolis准则确定最优粒子的取舍，改善其全局搜索能力。将该方法应用到某型柴油机喷油器失效分布的参数估计中，并与图解法、基于Levenberg-Marquardt的非线性最小二乘法、标准PSO算法、自适应PSO算法求解的结果进行比较，分析所提方法的优化性能及精度。结果表明，该方法能够有效提高多重威布尔混合分布模型参数估计的精度和效率。     

综采放顶煤工作面高位巷抽采关键技术研究

为了保证九里山矿1508工作面采空区瓦斯治理效果，通过现场数据测定、实验考察和理论分析，研究了推进度、抽采负压、抽采管网等高位巷抽采关键参数。研究结果表明，工作面煤层越厚、推进度越快，瓦斯涌出量越大；孔抽期间理想抽采负压为25～30 kPa、巷抽期间理想抽采负压为5～10 kPa，高位巷并联支路及管路阻力会影响高位巷的抽采效果。