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131.
132.
报告3例巨大斜坡肿瘤伴有球麻痹及不全高位截瘫,分别采用经颞枕底,经口咽,经额颅底斜坡入路施行全或次全切除肿瘤,效果良好,平均随访2.8年。如何根据每个病例选择好手术入路,是决定手术成功的关键。 相似文献
133.
本文介绍了一个以摄影测量光束法平差理论为基础的实用的联合平差程
序系统。该系统具有补偿系统误差、检测部分粗差和处理大地测量信息
的功能。文中简要说明了该系统所使用的基本理论、平差模型、方程解
法、程序结构和主要功能。利用HORDoRF试验场资料,对该程序系
统进行了试验计算。结果是令人满意的。 相似文献
134.
A GPS-based system for precise shipping guidance and control 总被引:2,自引:0,他引:2
Mami Ueno 《Journal of Marine Science and Technology》2000,5(1):9-15
This paper discusses the general concept of an automatic berthing system. The research considered the automatic berthing
of a large merchant ship. A global positioning system (GPS)-based system, which provides the necessary information on position,
velocity, attitude (roll, pitch, and heading), angular velocity, and time, was the principal sensor used. Field tests were
conducted on board a hydrographic sounding ship to assess the quality of information obtained from a GPS-based system. The
data were processed using the software with which the algorithms developed in this research were implemented. This paper also
discusses various aspects concerning a real-time GPS-based system in relation to an automatic berthing system, such as integration
of sensors, mathematical models, port infrastructure, and training of crews.
Received: October 22, 1999 / Accepted: June 30, 2000 相似文献
135.
锯齿形公交优先进口道的设置方法 总被引:9,自引:0,他引:9
为减少公交延误,发挥锯齿形公交优先进口道作用,分析了公交优先进口道的工作流程、车辆到达流量、通行能力、预信号区使用条件,提出了将锯齿形公交优先进口道车辆到达流量与通行能力匹配的优化模型与设置方法,建立了锯齿形公交优先进口道设置适宜的交通条件,提出了进口道主信号与预信号协调配时,与车辆流量适宜的候驶区长度确定的方法,计算了公交优先进口道设置前后公交车辆与社会车辆的延误。发现给定条件的城市主干道公交进口道优先可以使公交车的平均延误减少3.7S,社会车辆平均延误增加1.4S,所有乘客平均延误减少2.4S。 相似文献
136.
针对木京枢纽扩建船闸通航条件较为复杂的问题,对其上、下游引航道推荐方案的通航安全性进行试验论证研究。在水工模型试验的基础上,利用自航小尺度船模技术,观测分析船闸上、下游引航道在不同流量下的舵角、航速等通航参数。结果表明,在Q≥3 900 m~3/s时,上、下游引航道均有通航参数超过相应限值,难以保障通航安全。上、下游引航道的航行难点分别在于横流较大的转弯段和导墙末端,且均表现为进闸难度大于出闸难度。综合试验成果进行定量和定性分析,提出船闸最高限制通航流量为3 000 m~3/s,为工程优化设计及后期运行提供了科学可靠的数据基础。 相似文献
137.
138.
桥头搭板底脱空的病害会加剧搭板的损坏,采用注浆技术,填实搭板底的脱空处,会延长搭板的使用寿命及消除不利于行车的安全隐患。 相似文献
139.
In this paper the multi‐actor multi‐criteria analysis (MAMCA) method to evaluate transport projects is presented. This evaluation method specifically focuses on the inclusion of qualitative as well as quantitative criteria with their relative importance, defined by the multiple stakeholders, into one comprehensive evaluation process in order to facilitate the decision making process by the different stakeholders. The MAMCA methodology is introduced by an overview of other evaluation methods for transport projects in the past and is illustrated by means of two practical cases. The introduction will lead us to the theoretical conception of the MAMCA method where we draw the attention to the proven usefulness of the MAMCA for the evaluation of transport projects and the inclusion of different kinds of stakeholders, individuals as well as groups, into the evaluation process. 相似文献
140.
Erika Spissu Abdul Rawoof Pinjari Ram M. Pendyala Chandra R. Bhat 《Transportation》2009,36(4):403-422
In this paper, a joint model of vehicle type choice and utilization is formulated and estimated on a data set of vehicles
drawn from the 2000 San Francisco Bay Area Travel Survey. The joint discrete–continuous model system formulated in this study
explicitly accounts for common unobserved factors that may affect the choice and utilization of a certain vehicle type (i.e.,
self-selection effects). A new copula-based methodology is adopted to facilitate model estimation without imposing restrictive
distribution assumptions on the dependency structures between the errors in the discrete and continuous choice components.
The copula-based methodology is found to provide statistically superior goodness-of-fit when compared with previous estimation
approaches for joint discrete–continuous model systems. The model system, when applied to simulate the impacts of a doubling
in fuel price, shows that individuals are more likely to shift vehicle type choices than vehicle usage patterns.
Erika Spissu is currently a Research Fellow at the University of Cagliari (Italy). She received her Ph.D. from the University of Palermo and University of Cagliari (Italy) in Transport techniques and economics. She spent the past 2 years at The University of Texas at Austin as a Research Scholar focusing primarily in activity-based travel behavior modeling, time use analysis, and travel demand forecasting. Abdul Pinjari is an Assistant Professor in the Department of Civil and Environmental Engineering at the University of South Florida, Tampa. His research interests include time-use and travel-behavior analysis, and activity-based approaches to travel-demand forecasting. He has his Ph.D. from The University of Texas at Austin. Ram M. Pendyala is a Professor of Transportation Systems in the Department of Civil, Environmental, and Sustainable Engineering at Arizona State University. He teaches and conducts research in travel behavior analysis, travel demand modeling and forecasting, activity-based microsimulation approaches, and time use. He specializes in integrated land use-transport models, transport policy formulation, and public transit planning and design. He is currently the Vice-Chair of the International Association for Travel Behavior Research and is the immediate past chair of the Transportation Research Board Committee on Traveler Behavior and Values. He has his PhD from the University of California at Davis. Chandra R. Bhat is a Professor in Transportation at The University of Texas at Austin. He has contributed toward the development of advanced econometric techniques for travel behavior analysis, in recognition of which he received the 2004 Walter L. Huber Award and the 2005 James Laurie Prize from the American Society of Civil Engineers (ASCE), and the 2008 Wilbur S. Smith Distinguished Transportation Educator Award from the Institute of Transportation Engineers (ITE). He is the immediate past chair of the Transportation Research Board Committee on Transportation Demand Forecasting and the International Association for Travel Behaviour Research. 相似文献
Chandra R. Bhat (Corresponding author)Email: |
Erika Spissu is currently a Research Fellow at the University of Cagliari (Italy). She received her Ph.D. from the University of Palermo and University of Cagliari (Italy) in Transport techniques and economics. She spent the past 2 years at The University of Texas at Austin as a Research Scholar focusing primarily in activity-based travel behavior modeling, time use analysis, and travel demand forecasting. Abdul Pinjari is an Assistant Professor in the Department of Civil and Environmental Engineering at the University of South Florida, Tampa. His research interests include time-use and travel-behavior analysis, and activity-based approaches to travel-demand forecasting. He has his Ph.D. from The University of Texas at Austin. Ram M. Pendyala is a Professor of Transportation Systems in the Department of Civil, Environmental, and Sustainable Engineering at Arizona State University. He teaches and conducts research in travel behavior analysis, travel demand modeling and forecasting, activity-based microsimulation approaches, and time use. He specializes in integrated land use-transport models, transport policy formulation, and public transit planning and design. He is currently the Vice-Chair of the International Association for Travel Behavior Research and is the immediate past chair of the Transportation Research Board Committee on Traveler Behavior and Values. He has his PhD from the University of California at Davis. Chandra R. Bhat is a Professor in Transportation at The University of Texas at Austin. He has contributed toward the development of advanced econometric techniques for travel behavior analysis, in recognition of which he received the 2004 Walter L. Huber Award and the 2005 James Laurie Prize from the American Society of Civil Engineers (ASCE), and the 2008 Wilbur S. Smith Distinguished Transportation Educator Award from the Institute of Transportation Engineers (ITE). He is the immediate past chair of the Transportation Research Board Committee on Transportation Demand Forecasting and the International Association for Travel Behaviour Research. 相似文献