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相关概念视频

Bernoulli's Principle: Applications01:17

Bernoulli's Principle: Applications

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There are many devices and situations in which fluid flows at a constant height and so can be analyzed using Bernoulli's principle. These devices include, but are not limited to, entrainment devices and fluid flow measuring devices.
Entrainment devices use a high fluid speed to create low pressures and, thus, entrain one fluid into another. Some examples of these devices are given below:
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Design Example: Application of Archimedes' Principle01:11

Design Example: Application of Archimedes' Principle

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Archimedes' principle is fundamental in analyzing the buoyant force and stability of floating bodies. In this example, a wooden block with a rectangular section floats in seawater. Based on the block's dimensions, its specific gravity and the specific weight of seawater are used to find the volume of water displaced and the center of buoyancy.
The volume of seawater displaced by the block is determined by first calculating the block's weight. This is done by multiplying the...
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The Uncertainty Principle04:08

The Uncertainty Principle

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Werner Heisenberg considered the limits of how accurately one can measure properties of an electron or other microscopic particles. He determined that there is a fundamental limit to how accurately one can measure both a particle’s position and its momentum simultaneously. The more accurate the measurement of the momentum of a particle is known, the less accurate the position at that time is known and vice versa. This is what is now called the Heisenberg uncertainty principle. He...
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Hardy-Weinberg Principle01:49

Hardy-Weinberg Principle

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Diploid organisms have two alleles of each gene, one from each parent, in their somatic cells. Therefore, each individual contributes two alleles to the gene pool of the population. The gene pool of a population is the sum of every allele of all genes within that population and has some degree of variation. Genetic variation is typically expressed as a relative frequency, which is the percentage of the total population that has a given allele, genotype or phenotype.
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The Pauli Exclusion Principle03:06

The Pauli Exclusion Principle

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The arrangement of electrons in the orbitals of an atom is called its electron configuration. We describe an electron configuration with a symbol that contains three pieces of information:
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The Aufbau Principle and Hund's Rule03:02

The Aufbau Principle and Hund's Rule

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To determine the electron configuration for any particular atom, we can build the structures in the order of atomic numbers. Beginning with hydrogen, and continuing across the periods of the periodic table, we add one proton at a time to the nucleus and one electron to the proper subshell until we have described the electron configurations of all the elements. This procedure is called the aufbau principle, from the German word aufbau (“to build up”). Each added electron occupies the...
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相关实验视频

Updated: Jan 23, 2026

Constructing and Visualizing Models using Mime-based Machine-learning Framework
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基于机器学习的肉类新鲜度评估:原则,管道和应用.

Yahong Han1, Xiaoxue Jia2, Lei Yu3

  • 1Hubei Key Laboratory for Processing and Transformation of Agricultural Products, College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan, China.

Critical reviews in food science and nutrition
|January 22, 2026
PubMed
概括
此摘要是机器生成的。

机器学习 (ML) 提供了一种快速,非破坏性的方法来检查肉的新鲜度,提高食品安全. 本综述探讨了ML算法和实时肉质评估的管道,克服了传统的局限性.

关键词:
在美国,CNN是CNN.在SVM中,SVM是SVM.机器学习是机器学习.肉的新鲜度评估 肉的新鲜度评估

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科学领域:

  • 食品科学 食品科学 食品科学
  • 计算机科学 计算机科学
  • 人工智能的人工智能

背景情况:

  • 传统的肉类新鲜度评估方法是缓慢的,昂贵的和破坏性的.
  • 机器学习 (ML) 为实时,非破坏性肉质评估提供了一个可行的替代方案.
  • 准确的肉类新鲜度监测对于食品安全和消费者信心至关重要.

研究的目的:

  • 审查 ML 在肉类新鲜度评估中的原则和应用.
  • 详细介绍基于ML的检测管道,从数据采集到模型微调.
  • 突出肉类质量评估的ML的进步和挑战.

主要方法:

  • 关键的ML算法的审查:主要组件回归 (PCR),部分最小平方 (PLS),支持向量机 (SVM),K-最近邻居 (KNN) 和神经网络.
  • 检查ML管道阶段:数据采集,预处理,模型选择和微调.
  • 专注于先进的ML技术,如卷积神经网络 (CNN) 和合体学习.

主要成果:

  • ML算法在实时,非破坏性肉类新鲜度检测方面表现出有效性.
  • 像CNN和合奏方法这样的先进模型在解决腐烂和复杂的肉类组成方面表现有前途.
  • 该审查概述了一个基于ML的全面检测框架.

结论:

  • ML为监测肉类新鲜度提供了强大,高效的解决方案,提高了食品安全.
  • 需要进一步的研究来解决诸如数据集质量和模型可解释性等挑战,以便更广泛地采用.
  • 成功实施ML将为消费者带来更安全,更高质量的肉类产品.