作为服务的不确定性计算:集成基于云的微服务,用于增强校准和DCC生成
Anil Cetinkaya1,2, M Cagri Kaya3, Erkan Danaci4
1Department of Computer Engineering, Middle East Technical University, 06800 Ankara, Türkiye.
Sensors (Basel, Switzerland)
|September 14, 2024
概括
这项研究增强了微服务云架构的校准,改善了复杂设备和流程的管理. 更新后的系统简化了数据流,以便进行准确的测量和生成数字证书.
科学领域:
- 计量学和测量科学 计量学和测量科学
- 云计算和分布式系统
背景情况:
- 校准行业面临各种设备和复杂工艺的挑战.
- 快速的技术进步需要创新的管理解决方案.
研究的目的:
- 增强现有的基于微服务的云架构,以管理校准复杂性.
- 将各种设备和通信技术集成到一个统一的系统中.
主要方法:
- 实现基于微服务的云架构.
- 整合各种设备类型和通信协议.
- 开发模块来计算不确定性和生成数字校准证书 (DCC).
主要成果:
- 增强的架构成功地集成了各种校准设备和流程.
- 证明了从测量到DCC生成的高效数据流.
- 一个关于射频功率测量的案例研究验证了该系统的实际应用和好处.
结论:
- 增强的微服务架构为管理复杂的校准流程提供了强大的解决方案.
- 该系统促进了准确的不确定性计算和数字证书生成.
- 灵活的设计支持未来扩展到多种测量类型和计量学的进步.
相关概念视频
Uncertainty: Overview
529
In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
529
Propagation of Uncertainty from Systematic Error
490
The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
490
Uncertainty: Confidence Intervals
3.1K
The confidence interval is the range of values around the mean that contains the true mean. It is expressed as a probability percentage. The interpretation of a 95% confidence interval, for instance, is that the statistician is 95% confident that the true mean falls within the interval. The upper and lower limits of this range are known as confidence limits. The confidence limits for the true mean are estimated from the sample's mean, the standard deviation, and the statistical factor...
3.1K
Propagation of Uncertainty from Random Error
656
An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
656
Distributed Loads: Problem Solving
636
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
636
Distribution Reliability and Automation
107
Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
107


