水源涵养内涵及估算方法综述

水源涵养和生态系统过程与人类生产生活紧密相关,深入研究水源涵养对维持生态系统健康和人类社会可持续发展至关重要,对促进人与水和谐共生具有指导意义。随着对水源涵养研究与应用的深入,水源涵养内涵逐渐丰富,评估方法愈加多样,但以往的研究中水源涵养定义模糊,缺乏对各种评估方法的综合性对比分析,因此急需明确界定水源涵养内涵,分析各种估算方法的适用性。采用文献分析法系统梳理水源涵养研究历程,将其划分为认识与萌芽期、理论发展期、定量计算和模型综合评估等4个阶段;从定义、水量与功能等3个方面明确界定水源涵养内涵,从原理、时空尺度、适用范围及优缺点方面对已有水源涵养量估算方法进行对比和分析,并展望水源涵养研究的未来发展方向。     

黄河内蒙古段冰盖厚度模拟

基于原型观测数据对黄河内蒙古段的冰盖厚度进行模拟,通过引入Colburn类比法计算冰盖下的热通量,在热力学方程中引入河流流量、水流流速、水位河道坡降、冰盖糙率等因素,改进基于Stefan公式的度日法冰厚计算模型。采用巴彦高勒至头道拐河段4个测站的原型观测数据率定该冰厚计算模型的相关参数,并通过气温、水温数据进行冰厚计算。结果表明：改进后的冰厚计算模型在计算结果的精度上达到1.97％,相比于Stefan模型的14.99％、统一度日法模型的4.77％、动水冰厚辐射冰冻度日法模型的14.98％,精度上有所提升,冰厚变化趋势与现场原型观测趋势一致;根据累积气温值与气温序列特征分析2006—2017年的头道拐测站气温数据,提取冬季累积气温值最大的2009—2010年进行冰厚计算,模型计算结果精度为734％。[JP]改进模型在正常天气条件和极端天气条件下的冰厚计算结果均保持较高的精度,研究结果可为极端天气条件下研究区的冰厚计算提供理论依据。     

An implicit enthalpy scheme for one-phase Stefan problems

A compact finite-difference scheme to solve one-phase Stefan problems in one dimension is described. Numerical experiments indicate that the moving interface is obtained withO(t) accuracy when 3–4 iterations per time step are used to solve the nonlinear implicit scheme. The scheme can be adapted to ADI methods in higher dimensions.     

面向软件演化的可靠性分析代数方法

环境和需求的改变导致软件演化发生, 并通常会使软件架构(Software architecture, SA)产生变化.现有的结构化软件可靠性模型对评价软件初始结构设计有不错的效果, 但在软件演化时的实时分析方面有局限性.从软件结构建模出发, 通过使用代数方法将软件演化描述为原子操作序列, 并跟踪分析序列中每一步操作对可靠性的影响, 从而建立基于过程的可靠性分析方法.方法可分析演化关键环节及整体趋势, 用以进一步反馈和约束演化方案设计, 最终达到提高软件产品质量的目的.通过对2个实际算例的深入分析与讨论, 方法的有效性与易用性得到验证.     

A novel data-driven approach to support decision-making during production scale-up of assembly systems

In today's manufacturing settings, a sudden increase in the customer demand may enforce manufacturers to alter their manufacturing systems either by adding new resources or changing the layout within a restricted time frame. Without an appropriate strategy to handle this transition to higher volume, manufacturers risk losing their market competitiveness. The subjective experience-based ad-hoc procedures existing in the industrial domain are insufficient to support the transition to a higher volume, thereby necessitating a new approach where the scale-up can be realised in a timely, systematic manner. This research study aims to fulfill this gap by proposing a novel Data-Driven Scale-up Model, known as DDSM, that builds upon kinematic and Discrete-Event Simulation (DES) models. These models are further enhanced by historical production data and knowledge representation techniques. The DDSM approach identifies the near-optimal production system configurations that meet the new customer demand using an iterative design process across two distinct levels, namely the workstation and system levels. At the workstation level, a set of potential workstation configurations are identified by utilising the knowledge mapping between product, process, resource and resource attribute domains. Workstation design data of selected configurations are streamlined into a common data model that is accessed at the system level where DES software and a multi-objective Genetic Algorithm (GA) are used to support decision-making activities by identifying potential system configurations that provide optimum scale-up Key Performance Indicators (KPIs). For the optimisation study, two conflicting objectives: scale-up cost and production throughput are considered. The approach is employed in a battery module assembly pilot line that requires structural modifications to meet the surge in the demand of electric vehicle powertrains. The pilot line is located at the Warwick Manufacturing Group, University of Warwick, where the production data is captured to initiate and validate the workstation models. Conclusively, it is ascertained by experts that the approach is found useful to support the selection of suitable system configuration and design with significant savings in time, cost and effort.     

A robot hand-eye calibration method of line laser sensor based on 3D reconstruction

In the robotic eye-in-hand measurement system, a hand-eye calibration method is essential. From the perspective of 3D reconstruction, this paper first analyzes the influence of the line laser sensor hand-eye calibration error on the 3D reconstructed point clouds error. Based on this, considering the influence of line laser sensor measurement errors and the need for high efficiency and convenience in robotic manufacturing systems, this paper proposes a 3D reconstruction-based robot line laser hand-eye calibration method. In this method, combined with the point cloud registration technique, the newly defined error-index more intuitively reflects the calibration result than traditional methods. To raise the performance of the calibration algorithm, a Particle Swarm Optimization - Gaussian Process (PSO-GP) method is adopted to improve the efficiency of the calibration. The experiments show that the Root Mean Square Error (RMSE) of the reconstructed point cloud can reach 0.1256 mm when using the proposed method, and the reprojection error is superior to those using traditional hand-eye calibration methods.     

一种自适应运动目标检测算法及其应用

针对ViBe算法在动态背景下存在鬼影消除时间长、算法适应性差、前景检测噪声多的问题,本文提出一种基于ViBe算法框架的改进算法.该算法采用鬼影检测法标记第1帧中的鬼影区域,并向位于鬼影区域的背景模型中强制引入背景样本,从而快速抑制鬼影;在像素分类过程中,引入自适应分类阈值,解决全局阈值易受动态噪声干扰的问题;在背景模型更新中,根据像素分类的匹配值来动态决定更新因子,提高算法适应场景变化的能力.定性与定量的对比实验结果表明,本文算法相较于ViBe算法能够有效地检测动态背景下的运动目标,应用于河流漂浮物检测场景中也有较好的效果.     

混合高斯模型结合五帧差分的运动目标检测

在复杂背景下,光照变化、目标短暂遮挡以及背景运动等因素会导致运动目标检测精度较低.提出一种结合改进混合高斯模型和改进五帧差分的运动目标检测算法,首先在混合高斯模型中加入自适应学习率以及背景学习速率更新策略有效解决传统背景更新速率恒定而出现的残影现象;然后利用改进的五帧差分法克服运动目标短暂遮挡问题,并加入光照阈值判别因素,有效减弱光照变化带来的影响;最后对两者结果进行或运算进而得到最终检测结果.实验结果表明,该融合算法在复杂环境下具有一定的抗干扰能力,运动目标检测精度较高.     

某商品大集人员疏散的仿真模拟研究

目前,在各地均有商贸活动开展,且参与人员众多,如果公安机关事先未做好预案,一旦发生突发性事件,人员疏散不到位,极易造成群死群伤事件。文章以商品大集为例,构建参与人员的流动模型,利用计算机技术实现流量和流动状况的模拟仿真,获得接近实际的流动的时间和动态过程．利于事先对类似活动拥堵情况进行准确评估。     

数据库安全性测试研究

随着数据库在系统软件开发中的比重越来越高,数据的安全成为了软件系统中的重中之重。根据数据库安全的定义,针对数据库安全的设计,给出数据库身份认证、访问控制、数据访问机密性、数据完整性、审计能力、可用性的安全性测试方法。