新时期公路工程建设中安全监理工作的探索与实践

介绍了新时期公路工程建设中安全监理工作的探索与实践,并对安全监理工作的经验与教训进行总结。     

基于骑乘安全性的摩托车色彩设计研究

色彩对摩托车安全性有着直接的影响。色彩设计不仅在视觉上美化了摩托车产品,影响人的心理和情感,还会影响骑乘者视觉的反应速度及准确性。与色彩相关联的摩托车安全性设计主要包括仪表设计、方向把操作按键面板设计、整车色彩设计及骑乘者的头盔及着装设计。     

拆船公约新导则出台后中国的履约策略研究

国际海事组织海上环境保护委员会第64届大会通过了《2009香港国际安全与无害环境拆船公约》的最后两个导则,即《2012船舶检验和发证导则》和《2012船舶检查导则》,65届大会又对有害物质的阈值进行了修订,加快了公约生效进程。通过对上述导则的分析研究,结合国内外拆船业发展现状,为我国就拆船公约的履约提出了相关策略。     

浅谈海运精矿粉的安全运输

文章从精矿粉的特性入手,分析了精矿粉运输的安全隐患,指出了精矿粉在装货前、装货时、运输途中及卸货时的一些安全对策,对精矿粉的安全运输具有较强的指导作用。     

威志V5全新上市以进取超越期待

市场对于轿车的消费需求逐渐向理想消费阶段发展,这就对汽车的设计和制造技术提出了新的要求,天津一汽推出了威志v5这款新车来积极应对当前经济型轿车竞争激烈的形势。威志V5导入了新的“智能双I”的设计理念;在造型和内饰的细节上做了很多人性化的设计和调整;配备了很多先进技术使轿车更加节能和安全;使用自主研发的新的CA4GA5发动机更节能和环保。完全由天津一汽独立研发设计的威志v5在安全、节能、环保和新技术应用方面都为经济型轿车树立了新标杆。     

“库尔斯克”号核潜艇事故的启迪与教训

本文阐述俄罗斯海军“库尔斯克”号核潜艇沉没事故对潜艇设计、运行和管理等方面的影响,并且从俄罗斯潜艇设计的指导思想、设计原则以及潜艇可靠性、抗沉性等方面对“库尔斯克”号核潜艇事故的教训和启发作了分析和探讨。     

地铁火灾人员逃生的模拟与分析

本文针对地铁火灾人员逃生这一问题,系统分析了地铁火灾与人员逃生过程与特点,在此基础上,提出了地铁火灾人员疏散时间计算模型。通过实验与软件,对地铁火灾的烟气的温度与扩散进行模拟,确定了地铁火灾人员疏散可用时间,总结了人员疏散所需时间的计算方法。结合了上海某地铁站的实例进行安全性分析,使得本文所提出地铁火灾疏散时间模型得以运用。     

一起船舶碰岸事故的教训

对于一起由于船员过失而导致的船舶触岸事故,分折导致该事故的原因和在此事故中各当事方的过失,并阐述在引航员操纵船舶时船长、驾驶员和其它当值船员的职责,以预防类似事故的发生。     

救生艇的安全操作

针对救生艇使用过程中容易出现的事故,结合教学与工作实践,阐述预防救生艇事故的注意事项,确保船员生命及财产安全。     

Fuzzy ontology-based sentiment analysis of transportation and city feature reviews for safe traveling

Traffic congestion is rapidly increasing in urban areas, particularly in mega cities. To date, there exist a few sensor network based systems to address this problem. However, these techniques are not suitable enough in terms of monitoring an entire transportation system and delivering emergency services when needed. These techniques require real-time data and intelligent ways to quickly determine traffic activity from useful information. In addition, these existing systems and websites on city transportation and travel rely on rating scores for different factors (e.g., safety, low crime rate, cleanliness, etc.). These rating scores are not efficient enough to deliver precise information, whereas reviews or tweets are significant, because they help travelers and transportation administrators to know about each aspect of the city. However, it is difficult for travelers to read, and for transportation systems to process, all reviews and tweets to obtain expressive sentiments regarding the needs of the city. The optimum solution for this kind of problem is analyzing the information available on social network platforms and performing sentiment analysis. On the other hand, crisp ontology-based frameworks cannot extract blurred information from tweets and reviews; therefore, they produce inadequate results. In this regard, this paper proposes fuzzy ontology-based sentiment analysis and semantic web rule language (SWRL) rule-based decision-making to monitor transportation activities (accidents, vehicles, street conditions, traffic volume, etc.) and to make a city-feature polarity map for travelers. This system retrieves reviews and tweets related to city features and transportation activities. The feature opinions are extracted from these retrieved data, and then fuzzy ontology is used to determine the transportation and city-feature polarity. A fuzzy ontology and an intelligent system prototype are developed by using Protégé web ontology language (OWL) and Java, respectively. The experimental results show satisfactory improvement in tweet and review analysis and opinion mining.