通过传感器信号分析进气门是否积炭

进气门积炭影响行驶性能和排放,能否通过观察发动机传感器的数据来判断进气门是否有积炭呢?     

Is generalised cost justified in travel demand analysis?

Transportation - Generalised cost (GC) has long been widely used as a measure of the attractiveness of travel alternatives. We argue that its limitations have been forgotten, overlooked or not...     

描述有效的原料药

尽管癌症治疗在过去的十多年取得了显著进展，但肿瘤学仍属于目前最不能满足临床需要的学科领域。在过去十多年里，临床药理学的进步和研发活动方面的巨大投资使得“癌症治疗”发展为“治疗过程研究”的数量急剧增加。但事实上，癌症和其他慢性疾病一样，治疗效果都很差，由此很多大型医药公司和生物制药公司都比以往更大力度的投入资金，用于肿瘤学和其他强效候选药物的研发上。[第一段]     

诊断发动机故障的利器——诊断脉冲传感器

每次看到一台精密的基于示波器技术的现代检测工具．我们都会想到老一辈的汽修技师们，感叹他们当时是怎样利用简陋的检测工具和不太靠得住的简单的故障诊断测试方法进行工作的。同样地．当他们了解了一些新的检测工具后．肯定也会感叹融入新技术的检测工具给汽车维修工作带来的巨大便利。[编者按]     

驱动性能试验园地--MAP测试

OBD Ⅱ系统一直依赖于各种基本传感器所提供的信号输入,但是现在氧传感器在燃油控制与供给方面起到了更为突出的作用。     

利用OBDⅡ系统进行排放检测

OBD Ⅱ系统很快将取代标准排气管检测排放污染。在美国己制订了相应的法规,马克·沃伦先生在本文中解释这项法规涉及的内容以及与排气管检测的区别。通过本文,读者可了解排放检测的最新技术。     

我依然是局外人——宝马车手库比卡专访

踏入F1的第3年，23岁的Robert Kubica就拿下个人的首胜，而且他并非是待在传统强队之中，一度成为积分的暂时领先者，跃升为祖国波兰的超级明星人物，然而他依然保持低调的风格，凡事都有着超龄的成熟度，赛季迈入一半，让他来谈谈挤进Ferrari及Mclaren的争冠集团的感想。     

Condition monitoring of wooden railway sleepers

Wooden railway sleeper inspections in Sweden are currently performed manually by a human operator; such inspections are to large extent based on visual analysis. In this paper a machine vision based approach has been considered to emulate the visual abilities of the human operator to enable automation of the process. Digital images from either ends (left and right) of the sleepers have been acquired. A pattern recognition approach has been adopted to classify the condition of the sleeper into classes (good or bad) and thereby achieve automation. Appropriate image analysis techniques were applied and relevant features such as the number of cracks on a sleeper, average length and width of the crack and the condition of the metal plate were determined. Feature fusion has been proposed in order to integrate the features obtained from each end for the classification task which follows. The effect of using classifiers like multi-layer perceptron and support vector machines has been tested and compared. Results obtained from the experiments show that multi-layer perceptron and support vector machines have achieved encouraging results, with a classification accuracy of 90%; thereby exhibiting a competitive performance when compared to a human operator.