渠首水位实时调控模型——以船行灌区一支渠为例

很多大中型灌区在输配水过程中存在水位衔接不当的问题,加之田面高程存在起伏,使得灌溉时往往存在部分田面不能上水或受淹等问题。本文提出了空间灌溉率的概念,并利用GIS的三维分析功能研究了其与渠道渠首水位之间的关系。分析表明,空间灌溉率与渠首水位之间的关系符合Logistic曲线;针对船行灌区一支渠,得到该Logistic曲线的参数,并确定了一支渠渠首和干渠渠首不同空间灌溉率所需的水位,为灌区水位实时调控提供基础数据。     

Augment low-field intra-operative MRI with preoperative MRI using a hybrid non-rigid registration method

Background

Preoperatively acquired diffusion tensor image (DTI) and blood oxygen level dependent (BOLD) have been proved to be effective in providing more anatomical and functional information; however, the brain deformation induced by brain shift and tumor resection severely impairs the correspondence between the image space and the patient space in image-guided neurosurgery.

Method

To address the brain deformation, we developed a hybrid non-rigid registration method to register high-field preoperative MRI with low-field intra-operative MRI in order to recover the deformation induced by brain shift and tumor resection. The registered DTI and BOLD are fused with low-field intra-operative MRI for image-guided neurosurgery.

Results

The proposed hybrid registration method was evaluated by comparing the landmarks predicted by the hybrid registration method with the landmarks identified in the low-field intra-operative MRI for 10 patients. The prediction error of the hybrid method is 1.92 ± 0.54 mm, and the compensation accuracy is 74.3 ± 5.0%. Compared to the landmarks far from the resection region, those near the resection region demonstrated a higher compensation accuracy (P-value = .003) although these landmarks had larger initial displacements.

Conclusions

The proposed hybrid registration method is able to bring preoperatively acquired BOLD and DTI into the operating room and compensate for the deformation to augment low-field intra-operative MRI with rich anatomical and functional information.     

煤中吡啶型氮热解机理的量子化学研究

用密度泛函 ( DFT)方法 ,在 UB3LYP/6- 31 G( d)水平上研究了煤中吡啶型氮的热解机理 ,对热解过程中由于官能团周围环境的不同而形成的三类吡啶自由基进行了量子化学计算 ,通过对键的 Mulliken布居数等计算结果的分析 ,分别得到了这三类自由基的热解途径 .并优化得到了反应物、中间体和产物的几何构型 .计算结果表明 ,吡啶型氮主要是以 HCN的形式释放出来的 .NH3 是 HCN二次反应的产物 .     

基于不确定决策树分类算法在滑坡危险性预测的应用

滑坡灾害预测受多种因素影响,其中降雨等不确定因素存在难以获取数据及有效处理等难题,为提高滑坡危险性预测的准确率,根据滑坡灾害发生相关理论及决策树分类原理,提出了基于不确定决策树算法在滑坡危险性预测的方法.该方法引入不确定因子降雨,并将不确定因子和其余评价因子一起,根据不确定决策树算法理论构建出不确定决策树,建立滑坡危险性等级预测模型,并用延安市宝塔区的实例进行验证.实验结果表明,该预测方法取得了较高的总体精度和有效精度,达到了滑坡预测的精度标准,且两项预测精度均高于传统C4.5决策树方法.     

超声波传感器在沙子料位检测中的应用

为提高混凝土的质量,配比很重要,其中沙子精确计量是关键因素之一。提出并设计了超声波系统测量沙子料位;为保证测量精度,采取自动增益控制电路和温度补偿。经实验证明:该方法简单、可行,为沙子质量的检测提供了一种新的参考方法。     

Reliability analysis of a repairable duplex system

We analyse the survival time of a repairable duplex system characterised by cold standby and by a pre-emptive priority rule. We allow general probability distributions for failure and repair. Moreover, an important realistic feature of the system is the general assumption that the non-priority unit has a memory. This combination of features has not been analysed in the previous literature. Our (new) methodology is based on a concatenation of a Cauchy-type integral representation of the modified Heaviside unit-step function and a two-sided stochastic inequality. Finally, we introduce a security interval related to a security level and a suitable risk-criterion based on the survival function of the system. As a practical application, we analyse some particular cases of the survival function jointly with the security interval corresponding to a security level of 90.     

Continuous Levels‐of‐Detail and Visual Abstraction for Seamless Molecular Visualization

Molecular visualization is often challenged with rendering of large molecular structures in real time. We introduce a novel approach that enables us to show even large protein complexes. Our method is based on the level‐of‐detail concept, where we exploit three different abstractions combined in one visualization. Firstly, molecular surface abstraction exploits three different surfaces, solvent‐excluded surface (SES), Gaussian kernels and van der Waals spheres, combined as one surface by linear interpolation. Secondly, we introduce three shading abstraction levels and a method for creating seamless transitions between these representations. The SES representation with full shading and added contours stands in focus while on the other side a sphere representation of a cluster of atoms with constant shading and without contours provide the context. Thirdly, we propose a hierarchical abstraction based on a set of clusters formed on molecular atoms. All three abstraction models are driven by one importance function classifying the scene into the near‐, mid‐ and far‐field. Moreover, we introduce a methodology to render the entire molecule directly using the A‐buffer technique, which further improves the performance. The rendering performance is evaluated on series of molecules of varying atom counts.     

库水升降速率对老蛇窝滑坡稳定性影响分析

通过监测资料分析和滑坡稳定性数值计算,探讨了三峡库水位在不同升降速率下对老蛇窝滑坡稳定性的影响规律。研究结果表明,理论上库水位上升有利于老蛇窝滑坡的稳定,但实际运行中库水位上升是不利于滑坡稳定的,因为库水浸泡会使滑坡前缘塌岸;老蛇窝滑坡为动水压力型滑坡,最主要诱发因素为库水位的下(骤)降;老蛇窝滑坡稳定性的临界库水位调度速率为0.9 m/d,即当库水位下降速率大于0.9 m/d时,滑坡K值小于1。     

基于MultiLayer水平集的脑MRI图像分割框架

提出了一种新的自动初始化水平集的方法和基于MultiLayer水平集的活动轮廓模型。该模型同时进行偏移场去除和图像分割,因此可以有效地克服灰度不均匀性的影响。最后利用了大脑皮层的距离信息,在框架中增加了厚度约束项。实验结果显示,相比著名的LBF模型,该框架不但可以获得更高的分割精度,而且分割时间也大大减少。     

一种基于混合量子粒子群的快速运动目标跟踪算法研究

量子粒子群算法在优化过程中需要权衡局部探索性和全局开拓性,进化后期由于全局开拓能力的丧失使得种群多样性减少,设计了一种基于欧式距离的混合量子粒子群算法,通过计算粒子的种群多样性,当种群多样性低于阈值范围时加入基于欧式距离的种群划分策略划分子种群,从而保证获得全局最优解。利用标准测试函数验证提出的混合量子群算法有效性。提出了基于混合量子粒子群的Mean Shift算法(HQPSO Mean Shift)完成目标快速跟踪,克服传统Mean Shift算法的在跟踪快速移动目标时出现"跟丢"的问题。