导航路网数据改进模型及其组织方法

提出了一种支持高性能车辆导航的多尺度路网数据模型,该模型根据不同功能对导航数据内容与尺度的要求,将用于计算的路网拓扑数据与用于描述的路网几何数据分离,并分别在垂直方向进行分层抽象,在水平方向进行区域划分;几何数据以显式比例尺作为分层标准,通过多弧段来描述道路几何信息;拓扑数据以道路等级作为分层标准,通过节点-弧段结构来描述路网连通关系;参照动态分段思想设计了一种弧段编码体系,以描述模型上下层弧段之间、单弧段与多弧段之间的对应关系。结果表明:提出的模型能有效地支持导航应用中的多级地图显示与分层路径规划。     

公路工程施工资料的管理流程探讨

公路工程施工资料收集、整理、编制工作是贯穿于公路建设工程始终的一项重要工作，鉴于此，阐述公路工程施工资料收集、整理、编制的方法，对相关管理流程做了梳理，以促进公路工程施工资料管理。     

Using automated walking gait analysis for the identification of pedestrian attributes

Collecting microscopic pedestrian behavior and characteristics data is important for optimizing the design of pedestrian facilities for safety, efficiency, and comfortability. This paper provides a framework for the automated classification of pedestrian attributes such as age and gender based on information extracted from their walking gait behavior. The framework extends earlier work on the automated analysis of gait parameters to include analysis of the gait acceleration data which can enable the quantification of the variability, rhythmic pattern and stability of pedestrian’s gait. In this framework, computer vision techniques are used for the automatic detection and tracking of pedestrians in an open environment resulting in pedestrian trajectories and the speed and acceleration dynamic profiles. A collection of gait features are then derived from those dynamic profiles and used for the classification of pedestrian attributes. The gait features include conventional gait parameters such as gait length and frequency and dynamic parameters related to gait variations and stability measures. Two different techniques are used for the classification: a supervised k-Nearest Neighbors (k-NN) algorithm and a newly developed semi-supervised spectral clustering. The classification framework is demonstrated with two case studies from Vancouver, British Columbia and Oakland, California. The results show the superiority of features sets including gait variations and stability measures over features relying only on conventional gait parameters. For gender, correct classification rates (CCR) of 80% and 94% were achieved for the Vancouver and Oakland case studies, respectively. The classification accuracy for gender was higher in the Oakland case which only considered pedestrians walking alone. Pedestrian age classification resulted in a CCR of 90% for the Oakland case study.     

对地铁信号系统列车运行速度制约因素的探讨

信号系统是保障地铁运行安全及提高运行效率的重要设备,列车超速防护功能是信号系统一个非常关键的功能。信号系统防护下的列车运行速度由车辆、线路、轨道、限界及信号系统等条件共同决定。由于相关专业对信号系统安全制动模型不了解,在实际工程中易造成"速度浪费"现象。从信号系统安全制动模型的原理出发,对车辆、线路、轨道、限界等专业对列车运行速度的制约因素进行分析,提出建议。     

Efficient missing data imputing for traffic flow by considering temporal and spatial dependence

The missing data problem remains as a difficulty in a diverse variety of transportation applications, e.g. traffic flow prediction and traffic pattern recognition. To solve this problem, numerous algorithms had been proposed in the last decade to impute the missed data. However, few existing studies had fully used the traffic flow information of neighboring detecting points to improve imputing performance. In this paper, probabilistic principle component analysis (PPCA) based imputing method, which had been proven to be one of the most effective imputing methods without using temporal or spatial dependence, is extended to utilize the information of multiple points. We systematically examine the potential benefits of multi-point data fusion and study the possible influence of measurement time lags. Tests indicate that the hidden temporal–spatial dependence is nonlinear and could be better retrieved by kernel probabilistic principle component analysis (KPPCA) based method rather than PPCA method. Comparison proves that imputing errors can be notably reduced, if temporal–spatial dependence has been appropriately considered.     

基于优化模型及多重数据处理的舰船污损监测法

针对目前舰船污损监测受环境和航行状态限制而无法实现连续监测的问题,提出了一种基于优化模型并对数据进行多重处理的舰船污损监测法。首先对轴功率与航速关系监测模型进行优化,将现有一维模型提高到更大航速区间内成立的二维模型。然后采集相关数据,根据其采集条件进行数据筛选及数据修正的多重处理,提高监测的连续性。其次建立污损阀值,与计算结果对比分析得到监测结论。最后将实船应用的监测结论与船体污损情况对比,验证了该方法的可行性和有效性。     

语料记忆在英语教学中的价值辩护与实施策略

外语学习离不开记忆，记忆的形式有多种多样。本文从多角度为语料记忆作价值辩护，阐述它的实施策略及要注意的问题，旨在说明语料记忆是在外语学习环境下提高英语学习效率的重要途径。     

以数据为中心的舰载分布式系统

在分析传统的以处理为中心的舰载分布式系统存在的诸多瓶颈的基础上,研究了以数据为中心的设计方法。采用实时发布-订阅协议的数据分发服务,提供了1种以数据为中心的通信规范,定义了1个可扩展、与平台无关、与位置无关的基础服务模型。该模型在空间、时间、传输、功能方面都是松散耦合的。实时数据发布者和订阅者,通过设置和调整服务质量参数,可以实现不同的数据需求和传输方式。系统内的各种数据能轻松发送和接收,有利于系统灵活动态的扩展和升级,易于组建更大范围的应用系统。