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相关概念视频

Extraction: Advanced Methods00:56

Extraction: Advanced Methods

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Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is...
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Stereotype Content Model02:16

Stereotype Content Model

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The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
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Improving Translational Accuracy02:07

Improving Translational Accuracy

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Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
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Introduction to z Scores01:06

Introduction to z Scores

9.0K
A z score (or standardized value) is measured in units of the standard deviation. It tells you how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a zero z score. It is important to note that the mean of the z scores is zero, and the standard deviation is one.
z scores...
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Heuristics01:21

Heuristics

74
Heuristics are problem-solving strategies that use mental shortcuts to simplify decision-making. Unlike algorithms, which must be followed precisely to achieve a correct result, heuristics offer a general problem-solving framework. They save time and energy but can sometimes lead to less rational decisions.
People often rely on heuristics when faced with an overload of information, limited time, low importance of the decision, limited information, or when a heuristic readily comes to mind. For...
74
Empirical Method to Interpret Standard Deviation01:09

Empirical Method to Interpret Standard Deviation

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The empirical rule, also known as the three-sigma rule, allows a statistician to interpret the standard deviation in a normally distributed dataset. The rule states that 68% of the data lies within one standard deviation from the mean, 95% lies within two standard deviations from the mean, and 99.7% lies within three standard deviations from the mean. Additionally, this rule is also called the 68-95-99.7 rule.
This rule is used widely in statistics to calculate the proportion of data values...
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相关实验视频

Updated: Jun 5, 2025

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody
09:09

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody

Published on: September 27, 2024

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对于现实世界的专家编程人员来说,造型测量:一种零射击方法.

Andrea Gurioli1, Maurizio Gabbrielli1, Stefano Zacchiroli2

  • 1Department of Computer Science and Engineering, University of Bologna, Bologna, Italy.

PeerJ. Computer science
|December 9, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了代码造型测量的新方法,即使它们不在培训数据中,也可以准确识别软件作者. 这有助于提升抄袭检测和代码审计技术.

关键词:
代码作者的归属 代码作者的归属这是一个代码片段.代码造型仪表的代码造型仪表数据挖掘是一种数据挖掘.深度学习是一种深度学习.机器学习 机器学习计量学学习的学习方法源代码 源代码 源代码零射击 零射击 零射击 零射击

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Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
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Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

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Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment
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Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

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相关实验视频

Last Updated: Jun 5, 2025

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody
09:09

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody

Published on: September 27, 2024

402
Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
05:48

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Published on: August 9, 2024

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Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment
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科学领域:

  • 计算机科学 计算机科学
  • 软件工程 软件工程 软件工程
  • 数字法医学数字法医学

背景情况:

  • 代码造型测量识别软件作者使用风格特征.
  • 现有的方法通常使用有限的,人工数据集,并与未知作者作斗争.
  • 应用包括抄袭检测,代码审计和分配验证.

研究的目的:

  • 通过使用现实世界的开源代码来挑战现有的代码样式测量假设.
  • 开发一种识别培训数据中不存在的作者 (外发作者) 的方法.
  • 创建和利用一个新的,大规模的数据集,用于代码造型测量.

主要方法:

  • 汇集了来自104位作者的114,400个代码片段的新数据集.
  • 在这个数据集上开发和训练了一个K-最近邻居 (k-NN) 分类器.
  • 对在发行和在发行之外的作者进行评估的表现.

主要成果:

  • 在发行版作者中达到69%的准确性,超过了20%以上的最先进状态.
  • 保持了与外发行作者的高性能,达到71%的准确性.
  • 证明了k-NN分类器在现实世界代码数据上的有效性.

结论:

  • 开发的方法成功地从现实世界的开源项目中识别出作者.
  • 该方法在识别初始培训组之外的作者方面非常强大.
  • 这项工作为实际应用显著推进了代码造型测量.