Study of Multistage Project Risk Identification-Assessment Process Based on Objective Orientation

Risk management of projects is about the real time ev aluation and making of decisions proactively in order to maximize the probabilit y of achieving or surpassing the targets set for project objectives. Project objective generally includes three elements: time, cost, quality. Risk occurrin g in the projects will affect these three factors to some various degrees in the end. There are different emphases in each stage and integrated balanced goals b etween the three factors. A large complex engineering project generally consists of several stages each of which has variable objective combinations leading to variable important risks. In order to achieve strategic goals on the schedule under the restriction of lim ited resources, the paper gives the analysis of the so-called risk identificati on-assessment process on the basis of objective orientation. In this paper the set of involved mostly hazards is presented in terms of given objective weight v ector, and so is the model of risk ranking .By reducing the range of risk factor s step by step, risk manager could pay more attention to important ventures and effectively control of them. According to different objective combination at different stages, primary risk f actor sets at different stages are given. With the probability and their various effects to project objectives, evaluation of these sets is made aiming to r educing of the scope of risks and providing decision maker with a better decisio ns support. Successful projects are those, which focus on the relevant business objectives t hroughout the whole process and seek to information integration across project l ife cycle. This paper also introduces the idea of real time process of risk iden tification-assessment and presents a flow chart as a demonstration.

An object tracking and global localization method using the cylindrical projection of omnidirectional image

We present an omnidirectional vision system we have implemented to provide our mobile robot with a fast tracking and robust localization capability. An algorithm is proposed to do reconstruction of the environment from the omnidirectional image and global localization of the robot in the context of the Middle Size League RoboCup field. This is accomplished by learning a set of visual landmarks such as the goals and the corner posts. Due to the dynamic changing environment and the partially observable landmarks, four localization cases are discussed in order to get robust localization performance. Localization is performed using a method that matches the observed landmarks, i.e. color blobs, which are extracted from the environment. The advantages of the cylindrical projection are discussed giving special consideration to the characteristics of the visual landmark and the meaning of the blob extraction. The analysis is established based on real time experiments with our omnidirectional vision system and the actual mobile robot. The comparative studies are presented and the feasibility of the method is shown.

Recovering the Shape of Planar Object Depicted by a Line Drawing under Axonometric Projection

A new approach is proposed for automatically creating B-rep models of a three-dimensional planar object from a line drawing depicting the object under orthographically axonometric projection. A new line parameterization that satisfies the uniqueness, boundedness and uniformness for representing lines in 2D and 3D space is given. According to the location relation between lines and planes of object depicted by the line drawing, some constraints about object’s 3D information are produced and a linear system based on those constraints is established. 3D information of a planar body can be obtained by solving the linear system. It is proved that, during the processing, there existed at least four degrees of freedom. It is more convenient to use information about lines and planes instead of points and planes for computer vision and intelligent CAD systems to interpret line drawings of planar objects.

The Impact of Project Portfolio Management on Enterprise Strategic Objectives

In today’s era,with the increase in the number of enterprise innovations,enterprises must adopt project portfolio management for various innovations,select alternative projects from the perspective of enterprise strategy.This paper primarily explores the use of project portfolio management in enterprise project management,hoping to improve the quality of enterprise project management and the utilization efficiency of project portfolio management in enterprise project management.

Low-order Wavefront Error Compensation for Multi-field of Lithography Projection Objective Based on Interior Point Method

Low-order wavefront error account for a large proportion of wave aberrations.A compensation method for low order aberration of projection lithography objective based on Interior Point Method is presented.Compensation model between wavefront error and degree of movable lens freedom is established.Converting over-determined system to underdetermined system,the compensation is solved by Interior Point Method(IPM).The presented method is compared with direct solve the over-determined system.Then,other algorithm GA,EA and PS is compared with IPM.Simulation and experimental results show that the presented compensation method can obtained compensation with less residuals compared with direct solve the over-determined system.Also,the presented compensation method can reduce computation time and obtain results with less residuals compare with AGA,EA and PS.Moreover,after compensation,RMS of wavefront error of the experimental lithography projection objective decrease from 56.05 nm to 17.88 nm.

新文科背景下项目管理学课程思政教学探索与实践

新文科建设如火如荼地开展,为管理类课程发展带来了新的发展机遇。新文科建设背景下,管理类课程的教学应重新审视课程定位、培养目标与教学模式,突出并强调课程的价值引领作用。该文探究和分析了项目管理学的课程教学目标及思政育人目标,进而挖掘了课程建设与思政特色,并提出课程思政教学内容设计和教学方法,希望提升教师思政教学能力,助力学生全面发展,努力开创我国高等教育事业发展新局面。

“实验设计与数据处理”教学设计与实践

基于成果导向教育理念,依据“实验设计与数据处理”课程所支撑的毕业要求观测点,反向设计课程目标。围绕课程目标整合教学内容和教学资源、设计教学过程、组织教学活动、评价学习成效,并基于评价结果持续改进,形成“实施-评价-反馈-改进”闭环。教学过程引入“工艺优化驱动教学”的项目式教学法,与“专业综合实验”“科研实践”等实践环节形成跨课程教学联动,以实践环节中的实验方案设计和数据处理的实际需求推动“实验设计与数据处理”课程的理论教学和课下实践,将零散的知识体系化,碎片化的应用系统化,着力提升学生实验方案设计、实验结果统计分析和模拟预测以及方案优化能力。

基于目标与活动风险的关键链项目缓冲监控周期确定方法

经典研究假设随时能够得到缓冲的消耗状态,但在项目实际执行的过程中很难实现,且监控次数过多会导致项目偏离计划。为保证每一次缓冲监控都能够有利于项目实施,本文提出了一种基于项目目标和活动风险确定监控周期的方法。不同项目对工期、成本、质量的侧重点不同,利用工期与成本、工期与质量之间的关系,根据不同的侧重点确定合适的监控频次。再根据每项活动的风险大小分配监控次数,活动的风险越大需分配到的监控次数越多,从而确定每项活动的监控周期,使项目在有限次的缓冲监控下实现效益最优。最后利用Matlab进行蒙特卡洛模拟实验,结果表明,与对比方法相比,所提方法能在满足项目质量要求的前提下,缩短项目工期并降低成本。

基于CDIO-OBE的发酵工程实验教学改革

针对传统教学出现的问题,以工程教育认证为契机,开展了基于CDIO-OBE理念的发酵工程实验课程教学改革探索。设定了明确的课程目标,将项目构思、设计、实现和运作融入到教学全过程,并采用多元化考核评价体系,采用观测点统计法对课程目标达成情况进行了评价。结果表明,三个课程分目标达成度分别为0.81、0.80和0.76,总目标达成度为0.79,说明大多数学生能够完成课程目标设定的学习任务,并达到对应毕业要求观测点的学生能力培养要求。

基于文本挖掘的水电工程施工物体打击事故致因分析

为探明水电工程施工过程中物体打击事故的致因及作用关系,提出针对性的事故预防措施,从源头遏制事故发生。遴选水电工程施工物体打击事故调查报告,运用文本挖掘从人、机、环、管4个方面提取14项事故致因。融合关联规则、决策试验和评价实验室(DEMATEL)方法,厘清致因因素间的关联关系,构建重要度分析模型,确定事故近端致因因素。结果表明:水电工程物体打击事故各致因间联系紧密,其中,安全监督检查不到位、违章作业、安全防护措施不完备、安全意识淡薄等致因因素对事故发生具有直接影响作用。现场清理不彻底、安全技术交底不到位、安全教育培训不到位等是诱发事故的深层影响因素,且安全意识淡薄的中心度排名第一,对事故致因系统的影响较大,在实际施工中应着重考虑上述致因因素。

基于随机活动工期的装配式项目鲁棒性调度优化

将装配式项目的生产阶段、运输阶段和装配阶段作为一个整体进行研究,考虑了各阶段的调度性质及相互牵制特性,提出了分种类分批次的调度策略。针对随机活动工期的装配式项目调度问题,采用鲁棒性调度方法,建立了以项目鲁棒值和成本值为优化目标的生产-运输-装配一体化建造鲁棒性调度模型。依据调度性质设计了集成精英策略的非支配性遗传算法(Non-dominated Sorting Genetic Algorithms-II,NSGA-II)并对其进行了求解。最后选取装配式项目实际案例,验证了算法的有效性并对实验结果进行了分析。研究结果表明,通过改变活动时差的不同分布状态,可在提高项目鲁棒性的同时保证项目成本最低。

基于NSGA-Ⅱ的面曝光3D打印工艺参数多目标优化

为改善面曝光3D打印制件的打印质量差、效率低等问题,采用非支配排序遗传算法(NSGA-Ⅱ)对工艺参数进行优化。选择温度、分层厚度、曝光时间、回合等待时间为优化变量,成型试样的变形率、表面硬度、时间为优化目标,通过单因素实验确定优化变量约束范围。根据Box-Behnken实验方案,建立各优化目标的预测模型,使用NSGA-Ⅱ算法进行多目标优化,规定优先精度、优先硬度、优先速度原则,按照不同优化原则分析帕累托前沿得到对应的最优工艺参数,并进行打印验证。结果表明,优先精度原则下,变形率最小值为0.508%,与优化前相比,降低了9.290%;优先硬度原则下,表面硬度最高达到95.3 HD,与优化前相比,提高了0.316%;在优先速度原则下,打印时间与优化前相比缩短了17.220%,优化效果显著。

基于拔尖人才培养的可视化实训平台构建研究

基于现代网络信息技术搭建的可视化实践实训平台,是一种以实际操作为学习任务,集“教学+实践技能培养+评核”多功能性新方式,是提升教学质量与教学效果的有效途径。南京医科大学药学院以药学拔尖创新人才培养为教学目标,进行以生药学课程为例的可视化实训平台体系化构建以及“贯通性”实践项目的教、培、评相结合教学探索,促进学生“三专协调”发展,强化综合技能与素质教育,调动学生主观积极能动性,提高学生创新思辨能力和拔尖人才培养效果。

基于NSGA-Ⅱ的南水北调东线一期北延应急工程水资源多目标优化配置

为推进南水北调工程高质量发展,以南水北调东线一期北延应急供水工程为研究对象,开展北延应急供水工程水资源多目标优化配置研究。以缺水量最小、调水成本最低为目标,构建北延应急供水工程受水区水量多目标优化配置模型,基于非支配排序遗传算法(NSGA-Ⅱ)进行模型求解。确定各受水区在经济最大化和缺水总量最小化条件下的供水量,制定符合农业、生态和城市应急等需求的精准调配方案。结果表明:平水年满足按需分配条件,做到满足最大需水量的同时也满足供水成本最低的目标;枯水年年供水保证率分别为57%、56%、55%、54%、53%、49%、46%、36%、34%和21%情况下的10组最优解作为水量优化配置方案,其中7个优化配置方案供水保证率大于规划调水量的供水保证率值38%。在水资源多目标优化配置方案下可高效完成受水区供需水任务的同时,有效提高供水保证率,同时保证调水成本的经济性。

“中国法律史”本科课程教学改革片思

“中国法律史”虽然一直是法学本科核心课程之一,但由于教学内容、教学组织与形式等方面的缺陷,往往被学生们视为不得不学,又略感抵触的必修课。为了摆脱此种困境,教学改革实为必需,或可从课程教学整体方案之改进及课堂教学质量之提升两个方向上展开。其最终目标则是使“中国法律史”成为教学内容兼顾基础性和启发性、教学手段灵活多样的优质本科课程。

基于无人机巡检与深度学习的河道整治施工进度图像识别

长线性小流域治理工程中的河道衬砌、生态护岸等距离长、范围广、布置分散,且工区交通不便,人工巡检费时费力,难以及时掌握工程的整体施工进度形象面貌。提出了基于无人机巡检与深度学习的河道整治施工进度智能图像识别方法,通过定位施工节点(施工区域起点和终点)的位置计算施工进度。首先,建立了施工区域目标检测模型,针对无人机航拍影像进行河道衬砌护岸施工区域的识别以及施工节点的定位;然后,利用尺度不变特征变换(scale-invariant feature transform,SIFT)算法对不同视频帧中的施工节点进行匹配,并基于单目视觉的运动视差法,计算施工节点的实际工区坐标;最后,计算当前衬砌护岸施工进度,并分析进度偏差。结果表明:该方法得到的施工节点定位平均误差为1.026 m,平均相对误差为0.74%,该方法能够较为准确地从航拍图像中识别得到当前衬砌护岸的施工进程,从而实现长线性工区快速巡检,及时掌控现场施工进度,提高工程管理的智能化水平。

广东省流域控制性水利工程管理体制优化研究

针对流域控制性水利工程存在管理主体多样、政府职能“缺位”、流域管理机构统筹监管能力不足等问题,为理顺流域控制性水利工程管理体制,在文献调研基础上提出了流域控制性水利工程定义,梳理确定了广东省流域控制性水利工程名录,提出了省级流域控制性水利工程的5项条件,并结合国内外流域控制性水利工程管理体制建立的经验,提出了优化广东省流域控制性水利工程管理体制的具体措施。研究结果表明:广东省有新丰江水库等流域控制性水利工程22宗,其中应纳入省级管理的省级流域控制性水利工程有15宗,流域控制性水利工程应按照提出的分级管理、统筹调度、协同运维的管理模式加强管理。

Fast global motion estimation and moving object extraction algorithm in image sequences

A novel and effective approach to global motion estimation and moving object extraction is proposed. First, the translational motion model is used because of the fact that complex motion can be decomposed as a sum of translational components. Then in this application, the edge gray horizontal and vertical projections are used as the block matching feature for the motion vectors estimation. The proposed algorithm reduces the motion estimation computations by calculating the onedimensional vectors rather than the two-dimensional ones. Once the global motion is robustly estimated, relatively stationary background can be almost completely eliminated through the inter-frame difference method. To achieve an accurate object extraction result, the higher-order statistics （HOS） algorithm is used to discriminate backgrounds and moving objects. Experimental results validate that the proposed method is an effective way for global motion estimation and object extraction.

全景视频中多运动对象检测与跟踪方法

全景视频多运动对象检测与跟踪技术的通用解决方案是通过投影变换将360°视频转为二维视频后进行检测和跟踪。然而固定球面投影变换会导致全景视频中存在空间上不连续的投影边界,当运动对象处于投影边界时,常规球面投影方法可能将其切分为多个部分,从而导致该运动对象的漏检或误检。针对该问题,提出了融合等距柱状形投影(equi-rectangular projection,ERP)和立方体投影(cube map projection,CMP)的全景视频多运动对象检测与跟踪方法,利用合适的CMP拼接帧减少ERP两极区域失真并弥补其边界不连续性,解决了处于投影边界和两极扭曲的对象检测问题。进一步,通过感知哈希、球面质心和运动方向等多重特征融合来解决全景视频多运动对象跟踪问题。实验结果表明,提出的方案可以有效减少投影边界不连续导致的误检,且能有效应对遮挡、穿梭帧边界和两极扭曲的对象跟踪问题。

基于三通道并行的高反光物体三维形貌测量

传统条纹投影技术测量高反光物体时因过度曝光导致相机失真,而常用的多重曝光时间法采集图像数量过多、耗时过长,为此提出了一种基于三通道并行的条纹投影强度预测与图像融合的方法。该方法根据被测物体的光强直方图分布计算条纹最佳投影光强比例关系,投影对应的红绿蓝条纹。利用彩色相机在多光通道下对投影条纹的不同响应,分离对应条纹图像并选择其中不饱和并且调制度最大的像素生成各自通道的图像掩膜,根据三通道下的掩膜图像和条纹图像合成高动态范围条纹图。通过相位解算与系统标定,最终恢复出高反光金属平面与球面零件的三维形貌。实验结果表明,该方法测量误差减小至传统方法的61.2%,同样采集12张条纹图像,仅增加1张预投影图像,提高系统适应性的同时也提升了测量精度。