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相关概念视频

Difference from Background: Limit of Detection01:05

Difference from Background: Limit of Detection

6.4K
The limit of detection (LOD) is the smallest amount of analyte that can be distinguished from the background noise. The LOD value corresponds to the concentration at which the analyte signal is three times larger than the standard deviation of the blank signal. Below this value, the analyte signal cannot be differentiated from the background noise. It is calculated by dividing the calibration slope by 3 times the standard deviation of the blank signals.
The LOD indicates the presence or absence...
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BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

399
System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....
399
Boundary Conditions: Lossless Lines01:21

Boundary Conditions: Lossless Lines

97
Consider a single-phase, two-wire, lossless transmission line terminated by an impedance at the receiving end and a source with Thevenin voltage and impedance at the sending end. The line, with length, has a surge impedance and wave velocity determined by the line's inductance and capacitance.
At the receiving end, the boundary condition states that the voltage equals the product of the receiving-end impedance and current. This relationship is expressed as a function of the incident and...
97

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相关实验视频

Updated: Jul 8, 2025

Design and Analysis for Fall Detection System Simplification
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Design and Analysis for Fall Detection System Simplification

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自动黑盒边界值检测自动化黑盒边界值检测

Felix Dobslaw1, Robert Feldt2, Francisco Gomes de Oliveira Neto3

  • 1Department of Communication, Quality Management and Information Systems, Mid Sweden University, Östersund, Jämtland, Sweden.

PeerJ. Computer science
|December 11, 2023
PubMed
概括

本研究介绍了一种用于软件测试中的边界值分析的自动化方法. 自动BVA方法识别了关键输入边界,而不需要软件规范,提高了软件质量.

关键词:
边界价值分析的分析方法边界值检测检测 边界值检测边界价值勘探 边界价值勘探 边界价值勘探程序衍生工具 程序衍生工具软件测试 软件测试 软件测试

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High-precision Electromagnetic Flowmeter with Empty Pipe Detection via Complex Programmable Logic Device-based Waveform Recognition
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Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking
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Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking

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相关实验视频

Last Updated: Jul 8, 2025

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Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking
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科学领域:

  • 软件工程 软件工程 软件工程
  • 计算机科学 计算机科学
  • 软件测试 软件测试 软件测试

背景情况:

  • 边界值分析对于软件质量至关重要,但通常是抽象的,需要规范.
  • 现有的边界值分析方法因需要软件模型或规范而受到限制.

研究的目的:

  • 提出一种自动化的黑子方法来检测软件系统中的边界值.
  • 支持软件测试人员在不依赖规范的情况下进行系统的边界值分析.

主要方法:

  • 开发了一种名为AutoBVA的自动黑盒边界值检测方法.
  • 使用"程序衍生"度量来量化测试输入的边界性.
  • 将程序衍生度量与搜索算法结合起来,以识别具有远程输出的输入对.

主要成果:

  • 在示例程序和613个Julia语言函数上对AutoBVA进行了评估.
  • 在70%以上的研究系统中成功识别了边界候选.
  • 证明程序衍生度量有效地找到有趣的边界候选者.

结论:

  • 自动边界值检测方法 (AutoBVA) 对各种软件系统有效.
  • 该方法可以扩展到更复杂的系统和数据类型.
  • 在软件测试中,AutoBVA增强了系统的边界值分析.