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

Tandem Mass Spectrometry01:21

Tandem Mass Spectrometry

927
Tandem mass spectrometry is a technique that uses multiple mass analyzers in series to obtain a higher selectivity and signal-to-noise ratio for the analyte. Instruments with multiple analyzers separated by an interaction cell enable secondary fragmentation and selected study of the fragment ions.
Secondary fragmentations occur in the interaction cell and can be induced by various factors. Fragmentation induced by collision with inert gases, such as N2, Ar, He, etc., is called collision-induced...
927
Gas Chromatography–Mass Spectrometry (GC–MS)01:14

Gas Chromatography–Mass Spectrometry (GC–MS)

4.0K
Gas chromatography–mass spectrometry (GC–MS) is the combination of analytical techniques of gas chromatography and mass spectrometry in a single instrument for analyzing a mixture of compounds. The gas chromatograph separates the compounds in the mixture, and the mass spectrometer analyzes each compound separately to determine the molecular masses and molecular structures.
A gas chromatograph consists of a long, narrow capillary column with a polysiloxane coating on the inner wall....
4.0K

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

Departure Process of Actively Managed Queue with Dependent Job Sizes.

Entropy (Basel, Switzerland)·2026
Same author

Workload of Queueing Systems with Autocorrelated Service Times.

Entropy (Basel, Switzerland)·2025
Same author

On the Influence of AQM on Serialization of Packet Losses.

Sensors (Basel, Switzerland)·2023
Same author

Non-Stationary Characteristics of AQM Based on the Queue Length.

Sensors (Basel, Switzerland)·2023
Same author

Impact of the Dropping Function on Clustering of Packet Losses.

Sensors (Basel, Switzerland)·2022
Same author

Burst ratio for a versatile traffic model.

PloS one·2022

相关实验视频

Updated: Jun 12, 2025

High-throughput and Comprehensive Drug Surveillance Using Multisegment Injection-Capillary Electrophoresis-Mass Spectrometry
10:17

High-throughput and Comprehensive Drug Surveillance Using Multisegment Injection-Capillary Electrophoresis-Mass Spectrometry

Published on: April 23, 2019

9.6K

暂时的GI/MSP/1/N队列

Andrzej Chydzinski1

  • 1Department of Computer Networks and Systems, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland.

Entropy (Basel, Switzerland)
|September 27, 2024
PubMed
概括
此摘要是机器生成的。

本研究分析了使用马科维服务过程 (MSP) 相关服务时间的系统中的队列长度. 我们为队列长度分布和随时间推移的平均队列长度提供定理和示例.

关键词:
在GI/MSP/1/N队列中马尔科维亚服务流程相关的服务时间与服务时间相关.排队的平均长度是队列长度分布 队列长度分布单个服务器排队过渡性分析是一种过渡性分析.

更多相关视频

Using a Cyclic Ion Mobility Spectrometer for Tandem Ion Mobility Experiments
08:40

Using a Cyclic Ion Mobility Spectrometer for Tandem Ion Mobility Experiments

Published on: January 20, 2022

4.2K
15N CPMG Relaxation Dispersion for the Investigation of Protein Conformational Dynamics on the µs-ms Timescale
08:09

15N CPMG Relaxation Dispersion for the Investigation of Protein Conformational Dynamics on the µs-ms Timescale

Published on: April 19, 2021

5.1K

相关实验视频

Last Updated: Jun 12, 2025

High-throughput and Comprehensive Drug Surveillance Using Multisegment Injection-Capillary Electrophoresis-Mass Spectrometry
10:17

High-throughput and Comprehensive Drug Surveillance Using Multisegment Injection-Capillary Electrophoresis-Mass Spectrometry

Published on: April 23, 2019

9.6K
Using a Cyclic Ion Mobility Spectrometer for Tandem Ion Mobility Experiments
08:40

Using a Cyclic Ion Mobility Spectrometer for Tandem Ion Mobility Experiments

Published on: January 20, 2022

4.2K
15N CPMG Relaxation Dispersion for the Investigation of Protein Conformational Dynamics on the µs-ms Timescale
08:09

15N CPMG Relaxation Dispersion for the Investigation of Protein Conformational Dynamics on the µs-ms Timescale

Published on: April 19, 2021

5.1K

科学领域:

  • 运营研究 运营研究
  • 应用概率学 应用概率学

背景情况:

  • 现实世界排队系统通常在服务时间中表现出非零的相关性.
  • 马科维服务过程 (MSP) 是一种可操作的模型,用于关联的服务时间,提供强大的装配能力.

研究的目的:

  • 在排队模型中对队列长度进行过渡性分析,使用MSP服务和一般到达间隔时间.
  • 证明有关队列长度分布和在任意时间t.的平均队列长度的定理.
  • 为了说明在不同条件下队列长度指标的动态行为.

主要方法:

  • 开发结合马科维亚服务流程的排队模型.
  • 对队列长度分布和平均队列长度的定理的分析推导.
  • 数字模拟来证明短暂的队列长度行为.

主要成果:

  • 建立了两个定理:一个用于时间 t 的队列长度分布,另一个用于时间 t 的平均队列长度.
  • 数字示例展示了平均队列长度,标准偏差和完整分布的演变.
  • 服务相关性强度,初始条件和到达间时间差异对队列动态的影响得到说明.

结论:

  • 该研究提供了理论框架和对与服务时间相关联的排队系统的实际见解.
  • 这些发现适用于优化各种排队场景中的性能,其服务时间非指数.
  • 马科夫服务过程证明有效地分析了短暂的队列长度动态.