本文件构成涵盖2015年至2019年的智能交通系统战略计划;它以2010-2014计划的进展为基础,提出了广泛的技术,政策,机构和组织概念。它提供了一个全面的视角,该视角基于包容性,协作性,互动性和迭代过程,以及各种各样的利益相关方参与机会,从而确保战略计划能够反映全国多方位ITS社区的愿望。这一新计划:确定了一个愿景——“转变社会运动方式”,以及ITS JPO的相关使命 ——推进跨越所有地面模式的研究;概述技术生命周期阶段和战略主题,阐明定义六个计划类别的成果和绩效目标;描述了“实现连接车辆实施”和“推进自动化”作为目前未来ITS工作跨越多个部门的主要技术驱动因素;以及将企业数据,互操作性,ITS部署支持和新兴的ITS能力作为额外的计划类别进行展示,这些额外的计划类别是对实现计划愿景至关重要的补充和相互依存的活动。该计划进一步确定了与技术生命周期每个阶段中的每个计划类别相一致的研究问题,以及与计划类别相关的跨部门组织和业务学科。
2021-02-26 09:54:18 4.32MB its战略计划
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In the process of eye tracking , a subject may focus on a point for a longer time, we call it fixation points, theprocess between fixation points is a saccade. Here, we investigate into the correlation between eye-tracking data andEEG(Electroencep
2021-02-22 14:05:47 347KB Eye Tracking; EEG Rthyms;
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Anatase TiO2 film with 3D network nanoporous structure consisted of 1D nanowires is obtained on SnO2:F (FTO) glass substrate by in-situ hydrothermal synthesis and applied in mesoporous perovskite (CH3NH3PbI3) solar cell. A thin Ti film is deposited on FTO substrate by magnetron sputtering before the
2021-02-22 14:05:46 2.62MB Perovskite solar cell; TiO2
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A finite-time convergent Zhang neural network and its application to real-time matrix square root finding
2021-02-22 09:07:54 488KB 研究论文
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We present the generation of the nanosecond cylindrical vector beams (CVBs) in a two-mode fiber (TMF) and its applications of stimulated Raman scattering. The nanosecond (1064 nm, 10 ns, 10 Hz) CVBs have been directly produced with mode conversion efficiency of ~18 dB (98.4%) via an acoustically ind
2021-02-21 19:10:00 1.48MB
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its-nedum.github.io:我的投资组合网站
2021-02-18 11:06:24 7.41MB CSS
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ITS-ICT_微服务 实验室 作业 附录
2021-02-13 11:05:30 9.33MB Java
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Adaptive Control of a Gyroscopically Stabilized Pendulum and Its Application to a Single-Wheel Pendulum Robot
2021-02-11 09:07:02 256KB 研究论文
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Grammar learning has been a bottleneck problem for a long time. In this paper, we propose a method of semantic separator learning, a special case of grammar learning. The method is based on the hypothesis that some classes of words, called semantic separators, split a sentence into several constituents. The semantic separators are represented by words together with their part-of-speech tags and other information so that rich semantic information can be involved. In the method, we first identify t
2021-02-09 18:05:56 509KB semantic separator; separator learning;
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2008Jaw-chuck stiffness and its influence on dynamic clamping force during high-speed turning
2021-01-28 04:39:16 563KB 12
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