城市轨道交通智慧工地信息化集成管理系统研究与应用

为实现智慧工地平台在轨道交通工程项目管理中的应用,青岛地铁集团根据中国城市轨道交通协会发布的《中国城市轨道交通智慧城轨发展纲要》要求,开展了智慧工地信息化集成管理系统平台的研究与建设工作。通过建立一套完善的资产数据,对工程现场产生的海量信息数据进行汇总分析、挖掘利用;通过人脸识别、视频监控、自动化监测等设备,实时采集现场信息;通过物联网前端感知技术和“BIM+GIS”数字孪生技术,实时监管建设过程中“人、机、料、法、环”等要素。智慧工地平台的使用,可实现工程参建各方履约监管、安全、质量、计划、进度等各要素的信息化、标准化、数字化、可追溯化管控,有效解决信息不全面、不真实和传统方式人工统计量大、子系统间信息孤岛等问题,达到直观、动态、综合、统一的实施管控、智能分析和数据共享的目的,确保“远程可视化监管”理念的落地实施。     

基于GIS的长输管道信息管理系统

介绍了基于GIS的长输管道信息管理系统.阐述了系统的开发方法、系统结构、功能设计以及数据库的建设,从而实现了对长输管道信息方面的科学化管理.最后,限于GIS技术目前的发展水平,指出了实现该项技术的部分难点问题.     

城际铁路无砟轨道简支T梁设计研究

随着我国城市圈建设步伐的加快,城际铁路的建设日益加快,国家铁路局于2015年颁布了城际铁路设计规范,其标准简支梁设计研究也正开展。在此背景下,基于更好体现城际铁路建设经济性要求、充分利用T梁造价低与施工便捷等优点的目的,在借鉴珠三角、武汉城市圈城际等项目实践经验的基础上,研究时速200 km无砟轨道简支T梁的构造,并通过采用杆系有限元分析方法建立相应计算模型,对其强度、刚度进行验算,同时采用实体有限元模型进行验证。分析结果表明,无砟轨道简支T梁可以满足强度、刚度等相关规范要求,且能有效降低工程造价,可在城际铁路建设中推广。     

基于数据融合的城市轨道交通规划理论研究——BIM与GIS一体化研究综述

大数据与信息化给城市和轨道交通领域带来了更多机会和挑战,不同来源信息数据的整合需要跨尺度理论、综合化技术手段及跨平台分析方法。轨道交通领域需要跨部门、多专业协作,而数据融合技术为城市轨道交通与城市空间协同性差、相关专业之间存在技术壁垒等问题提供解决途径,并为城市轨道交通规划中二维信息向三维信息的转变搭建技术平台。针对当前轨道交通领域信息化趋势及信息集成的需求,通过建立比较框架,探讨在数据融合环境中,打通城市国土空间规划、城市轨道交通线网规划及车站建筑设计等阶段,建筑信息模型(buildinginformationmodeling,BIM)与地理信息系统(geographicinformationsystem,GIS)一体化平台在数据支撑规划设计中的应用。从CAD、GIS以及规划支持系统(planningsupportsystems,PSS)3个不同阶段综述规划信息平台的发展,探讨每个阶段针对轨道交通一体化的技术特征、进步和局限。通过对理论趋势、城市规划与城市轨道交通发展需求和相关技术现状等方面的研究,显示城市规划与城市轨道交通领域的技术平台和数据标准均呈现出整合化特征。针对城市轨道交通领域整合的发展趋势与数据融合需求,提出BIM和GIS软件平台及数据标准的集成,是城市轨道交通科学化、智慧化发展的技术关键,也是大数据时代实现轨道交通与城市协同发展的重要支撑。     

GIS技术在高速公路监控系统中的实践应用

本文介绍了GIS在高速公路系统中的基本应用,阐述了GIS技术应用于高速公路系统的基本功能、总体架构和相关的系统要求.     

T梁的横向连接与横向分布系数

通过对T梁不同类型的横向连接的结构验算和相应静载试验的实测数据的比较和分析，初步得出T梁桥的横向连接及附属设施等对横向分布影响线值有影响，建议对横隔梁进行重点考虑。     

State-of-the-practice assessment of climate change adaptation practices across metropolitan planning organizations pre- and post-Hurricane Sandy

Metropolitan Planning Organizations (MPOs) throughout the United States are identifying goals and implementation strategies to reduce the impacts of climate change through transportation adaptation initiatives. Using vulnerability assessments as well as adaptation practices that support mitigation, MPOs are beginning to integrate climate change planning into the long range planning process. Evaluating the state-of-the-practice of adaptation planning and adaptation in support of mitigation is useful in that it helps identify gaps and areas of improvement. Therefore, this research investigates the state-of-the-practice of MPO adaptation planning using the Mid-Atlantic region as a case study. Surveys, administered in 2012 and 2014, are used to identify the level of progress of MPOs with regard to climate change adaptation practices as well as barriers before and after Hurricane Sandy. A cross-sectional analysis using GIS (Geographic Information Systems) maps the results of the surveys and spatially compares regional trends. The results of the case study suggest growing interest in adaptation efforts such as floodplain area designations and efforts to enhance coordination and collaboration as transportation jurisdictions respond to the potential climate change impacts. In addition, MPOs with dense, smaller geographic areas prioritize inter-jurisdictional collaboration as high, suggesting that they are more reliant on other agencies to maintain inter-connectivity of transportation networks and further implement adaptation planning practices.     

联合化疗加山莨菪碱治疗复治肺结核疗效观察

对33例复治肺结核患者以HRZS／HRE或HRZE方案加山莨菪碱进行治疗,观察其疗效。结果表明疗程结束时山莨菪碱治疗组痰菌阴转率、病灶吸收率、空洞闭合率分别达到92．6％、81．8％和81．6％,均明显高于对照组(P＜0．05)。认为此方法对经不规则化疗的复治肺结核疗效满意,尤其对慢性纤维空洞患者空洞闭合率高。并就山莨菪碱治疗肺结核增强疗效的可能机制进行了探讨。     

GPS/DR/GIS技术在基于GSM-R列车监控系统中应用

列车监控系统是IRS(智能铁路系统 )的主要组成部分。阐述了列车监控系统的基本组成。着重介绍了GPS/DR组合定位以及GIS在列车定位和监控中的作用 ,并探讨了用GSM R移动通信网实现GPS定位数据传输的有效性     

Pedestrian detection for traffic safety based on Accumulate Binary Haar features and improved deep belief network algorithm

ABSTRACT

In order to improve traffic safety and protect pedestrians, an improved and efficient pedestrian detection method for auto driver assistance systems is proposed. Firstly, an improved Accumulate Binary Haar (ABH) feature extraction algorithm is proposed. In this novel feature, Haar features keep only the ordinal relationship named by binary Haar features. Then, the feature brings in the idea of a Local Binary Pattern (LBP), assembling several neighboring binary Haar features to improve discriminating power and reduce the effect of illumination. Next, a pedestrian classification method based on an improved deep belief network (DBN) classification algorithm is proposed. An improved method of input is constructed using a Restricted Bolzmann Machine (RBM) with T distribution function visible layer nodes, which can convert information on pedestrian features to a Bernoulli distribution, and the Bernoulli distribution can then be used for recognition. In addition, a middle layer of the RBM structure is created, which achieves data transfer between the hidden layer structure and keeps the key information. Finally, the cost-sensitive Support Vector Machine (SVM) classifier is used for the output of the classifier, which could address the class-imbalance problem. Extensive experiments show that the improved DBN pedestrian detection method is better than other shallow classic algorithms, and the proposed method is effective and sufficiently feasible for pedestrian detection in complex urban environments.