five

Beach profile data for the Elwha River Delta, 2013-04-01

收藏
Mendeley Data2023-02-23 更新2024-06-27 收录
下载链接:
https://doi.pangaea.de/10.1594/PANGAEA.901537
下载链接
链接失效反馈
资源简介:
Data were collected using GNSS survey methods, with a differential GPS operating in Real Time Kinematic (RTK) mode. Data from prior to 2013 were typically collected with a Magellan ProMark 3 traditional RKT-DGPS system (i.e. local base station and rover), with the base station sited on survey control markers installed in 1996, with survey control coordinates referenced to NAD83(CORS91). Starting in 2013 survey data were typically collected with an AshTech ProMark 200 RTK-DGPS system connected to the Washington State Reference Network. Survey data collected between January and November 2013 are referenced to NAD83(CORS96), and after November 2013 to NAD83(2011). Vertical data for surveys in 2012 and 2013 are referenced to NAVD88, presumably using Geoid96 (the survey control documentation does not specific a geoid). For all subsequent surveys the vertical data are referenced to NAVD88(Geoid09). No conversion were applied to these data to account for variations in horizontal or vertical coordinate system adjustments through time, but an error analysis suggests a standard deviation for the elevation data of between 0.03 and 0.05 m across the entire sampling period (2011-2018). All survey data were collected with the GNSS system mounted on a 2.05 m rover pole, held level as a transect line was traced in a cross-shore orientation on the beach. The associated text files include the horizontal (HRMS) and vertical (VRMS) root-mean-square errors estimated by the GNSS system, as well as the RTK-DGPS status reported by the GNSS system at the time each point was collected. Times are referenced to local Pacific time (either PST or PDT).
创建时间:
2022-01-24
用户留言
有没有相关的论文或文献参考?
这个数据集是基于什么背景创建的?
数据集的作者是谁?
能帮我联系到这个数据集的作者吗?
这个数据集如何下载?
点击留言
数据主题
具身智能
数据集  4099个
机构  8个
大模型
数据集  439个
机构  10个
无人机
数据集  37个
机构  6个
指令微调
数据集  36个
机构  6个
蛋白质结构
数据集  50个
机构  8个
空间智能
数据集  21个
机构  5个
5,000+
优质数据集
54 个
任务类型
进入经典数据集
热门数据集

PAN-X

该数据集是Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME)基准的一部分,名为WikiANN或PAN-X。它包含多种语言的维基百科文章,特别是瑞士四种最常用语言:德语、法语、意大利语和英语。每篇文章都使用LOC(位置)、PER(人物)和ORG(组织)标签在‘inside-outside-beginning’(IOB2)格式下进行了标注。

github 收录

Simulation of rear wheel steering in a vehicle towing a single axle trailer with variable load distribution

This is the dataset for a publication on the stability of automotive vehicles when towing single axle trailers. The loading of the trailer is critical for stability, if the load distribution is too far back, then the trailer will begin to sway uncontrollably, dictating the track of the vehicle.In this research, small proportional control of the rear wheel steering of a larger towing vehicle is shown to be able to further stabilize the system easily, thus improving the safety margin. This is based on control measurements of the yaw angle, either directly measured or inferred from rear camera / parking sensor measurements.The simulation environment is Simulink and all scripts are included to initialise and plot the results. The work is based on the built in example "Two axle vehicle towing one axle trailer" with modifications to enable control algorithms for rear wheel steering control and variable load distribution. Reference for the original model is available at:T. M. Inc., Vehicle dynamics blockset version: 2.0 (r2023a) (2022). https://www.mathworks.comT. M. Inc., Trailer body 3dof documentation (2020). https://uk.mathworks.com/help/vdynblks/ref/trailerbody3dof.html<br>

DataCite Commons 收录

suno

该数据集包含由人工智能生成的659,788首歌曲的元数据,这些歌曲由suno.com平台生成。数据集是多语言的,主要语言为英语,但也包含日语和其他语言的歌词和标题。每个歌曲的元数据包括唯一标识符、视频和音频URL、封面图像URL、AI模型版本、生成状态、创作者信息等。数据集根据CC0许可证公开,允许任何用途的使用、修改和分发。

huggingface 收录

China Health and Retirement Longitudinal Study

中国健康与养老追踪调查(China Health and Retirement Longitudinal Study, CHARLS)是一个全国性的、具有代表性的老年人调查项目,旨在收集有关中国45岁及以上人群的健康、经济和社会状况的数据。该数据集包括个人和家庭层面的信息,涵盖健康状况、医疗使用、经济状况、社会支持等多个方面。

charls.pku.edu.cn 收录

中国交通事故深度调查(CIDAS)数据集

交通事故深度调查数据通过采用科学系统方法现场调查中国道路上实际发生交通事故相关的道路环境、道路交通行为、车辆损坏、人员损伤信息,以探究碰撞事故中车损和人伤机理。目前已积累深度调查事故10000余例,单个案例信息包含人、车 、路和环境多维信息组成的3000多个字段。该数据集可作为深入分析中国道路交通事故工况特征,探索事故预防和损伤防护措施的关键数据源,为制定汽车安全法规和标准、完善汽车测评试验规程、

北方大数据交易中心 收录