Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Sampling Methods: Overview01:06

Sampling Methods: Overview

535
A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling. 
In analytical chemistry, the choice of...
535
Sampling Continuous Time Signal01:11

Sampling Continuous Time Signal

357
In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
In the...
357
Aliasing01:18

Aliasing

238
Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
238
Cluster Sampling Method01:20

Cluster Sampling Method

12.8K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
12.8K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Endoscopic ultrasound-guided Hartmann reversal procedure.

Endoscopy·2026
Same author

Pancreatic cystic lesions in hereditary syndromes: Diagnostic role of endoscopic ultrasound.

Best practice & research. Clinical gastroenterology·2026
Same author

Endoscopic ultrasound-guided transgastric drainage of pancreaticopleural fistulas.

Endoscopy international open·2026
Same author

Pulmonary Dynamics of the Bronchodilator Response in Volume-Responsive Asthma and COPD.

Chest·2026
Same author

The Use of Direct Endoscopic Necrosectomy During Endoscopic Drainage of Walled-Off Pancreatic Necrosis.

Journal of clinical medicine·2026
Same author

Percutaneous Endoscopic Necrosectomy of Walled-Off Pancreatic and Peripancreatic Necrosis.

Journal of clinical medicine·2026
Same journal

Correction: A method for supervoxel-wise association studies of age and other non-imaging variables from coronary computed tomography angiograms.

Scientific reports·2026
Same journal

Poly(bromophenol blue)/CoSn(OH)<sub>6</sub> cubic particles modified pencil graphite electrode for electrochemical determination of diphenhydramine.

Scientific reports·2026
Same journal

Dietary Chlorella, Spirulina, and acidifier modulate jejunal cytokine-related gene expression in broiler chickens.

Scientific reports·2026
Same journal

Perceived physical activity barriers in university students: associations with fatigue and eating behaviours.

Scientific reports·2026
Same journal

Refuge limitation structures habitat use in agricultural landscapes: evidence from Sunda pangolins.

Scientific reports·2026
Same journal

Lightweight stateless transaction verification with outsourced witness updates for UTXO blockchains.

Scientific reports·2026
查看所有相关文章

相关实验视频

Updated: Sep 17, 2025

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
07:59

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

Published on: June 9, 2023

1.5K

一个轻量级的算法,用于使用时间样本对齐进行同步多式联运数据采集.

Jacek Piatkowski1, Lukasz Karbowiak2, Filip Depta1

  • 1Faculty of Computer Science and Artificial Intelligence, Czestochowa University of Technology, Czestochowa, 42-201, Poland.

Scientific reports
|July 2, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种同步数据采集系统 (SDAS),用于无的传感器数据融合. 该系统使用边缘控制协议 (ECP) 和时间样本对齐 (TSA) 算法确保同步数据收集.

关键词:
调整算法对齐的算法数据同步数据同步.多传感器数据融合技术同步数据采集和数据采集.

更多相关视频

Author Spotlight: Automated Deep Brain Stimulation for Parkinson's Disease - Exploring the Possibilities and Challenges of Home Monitoring
06:32

Author Spotlight: Automated Deep Brain Stimulation for Parkinson's Disease - Exploring the Possibilities and Challenges of Home Monitoring

Published on: July 14, 2023

1.4K
Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
07:13

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

Published on: October 27, 2023

1.4K

相关实验视频

Last Updated: Sep 17, 2025

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
07:59

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

Published on: June 9, 2023

1.5K
Author Spotlight: Automated Deep Brain Stimulation for Parkinson's Disease - Exploring the Possibilities and Challenges of Home Monitoring
06:32

Author Spotlight: Automated Deep Brain Stimulation for Parkinson's Disease - Exploring the Possibilities and Challenges of Home Monitoring

Published on: July 14, 2023

1.4K
Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
07:13

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

Published on: October 27, 2023

1.4K

科学领域:

  • 计算机科学 计算机科学
  • 数据工程数据工程
  • 传感器网络 传感器网络

背景情况:

  • 多传感器数据采集增强了现象的表现.
  • 数据同步和融合在多传感器系统中构成重大挑战.

研究的目的:

  • 开发一种轻量级和灵活的系统,用于从多种传感器同步获取数据.
  • 为了解决数据同步和融合的复杂性.

主要方法:

  • 开发同步数据采集系统 (SDAS).
  • 实施边缘控制协议 (ECP) 用于数据采集.
  • 利用时间样本对齐 (TSA) 算法进行基于软件的同步.

主要成果:

  • SDAS确保了所有连接的传感器的同步数据收集.
  • 时间样本对齐 (TSA) 算法有效地同步传感器数据.
  • 验证试验证实了该溶液的有效性.

结论:

  • 开发的SDAS为传感器数据同步提供了有效的基于软件的解决方案.
  • ECP和TSA使得多传感器数据集成具有稳定性和灵活性.
  • 该系统经过验证,并已准备好用于实际应用.