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相关概念视频

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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Transformers with Off-Nominal Turns Ratios01:25

Transformers with Off-Nominal Turns Ratios

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In scenarios involving parallel transformers with disparate ratings, developing per-unit models requires accommodating off-nominal turns ratios. This situation arises when the selected base voltages are not proportional to the transformer’s voltage ratings. Consider a transformer where the rated voltages are related by the term a. If the chosen voltage bases satisfy a relationship involving term b, term c is defined as the ratio of these bases. This ratio is then substituted into the...
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Transformers in Distribution System01:27

Transformers in Distribution System

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Transformers in distribution systems can be broadly categorized into distribution substation transformers and other distribution transformers. They are crucial for stepping down high transmission voltages to levels suitable for distribution and end-user applications.
Distribution substation transformers come in various ratings and typically use mineral oil for insulation and cooling. To prevent moisture and air from entering the oil, some transformers use an inert gas like nitrogen to fill the...
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Energy Losses in Transformers01:21

Energy Losses in Transformers

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In an ideal transformer, it is assumed that there are no energy losses, and, hence, all the power at the primary winding is transferred to the secondary winding. However, in reality,  the transformers always have some energy losses, and, hence, the output power obtained at the secondary winding is less than the input power at the primary winding due to energy losses.
There are four main reasons for energy losses in transformers.
The first cause can be  the high resistance of the...
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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
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The Ideal Transformer01:26

The Ideal Transformer

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In single-phase two-winding transformers, two windings are coiled around a magnetic core characterized by cross-sectional area A and magnetic permeability μ. A phasor current i1 enters the left winding while i2 exits the right winding, establishing the fundamental working of the transformer through electromagnetic principles.
Ampere's Law forms the basis of understanding the magnetic field within the transformer. It states that the integral of the magnetic field intensity's...
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相关实验视频

Updated: May 13, 2025

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
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用预训练过的变压器进行快速准确的贝叶斯优化,用于受约束的工程问题.

Rosen Ting-Ying Yu1, Cyril Picard2, Faez Ahmed2,1

  • 1Center for Computational Science and Engineering, Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA USA.

Structural and multidisciplinary optimization : journal of the International Society for Structural and Multidisciplinary Optimization
|April 14, 2025
PubMed
概括

本研究介绍了一种新的贝叶斯优化 (BO) 框架,使用先前数据拟合网络 (PFN) 来实现更快的工程设计. PFN模型有效地处理约束,在找到最佳解决方案方面实现了显著的加快速度.

关键词:
贝叶斯优化是贝叶斯的优化.工程设计优化工程设计优化机器学习 机器学习基于替代品的优化

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科学领域:

  • 工程设计优化工程设计优化
  • 机器学习 机器学习
  • 人工智能的人工智能

背景情况:

  • 贝叶斯优化 (BO) 对于复杂的工程设计具有昂贵的黑子功能至关重要.
  • 现有的方法经常与多个约束作斗争,每一个都需要单独的模型.

研究的目的:

  • 引入使用先前数据拟合网络 (PFN) 的BO新型约束处理框架.
  • 允许在单个模型通行证中同时评估目标和约束.

主要方法:

  • 杆PFN,一个基础变压器模型,用于集成目标和约束处理.
  • 为了有效的评估,雇员在语境学习.
  • 在15个不同的工程设计问题中进行了基准测试.

主要成果:

  • 与传统的基于高斯过程 (GP) 的方法相比,实现了数量级的加速.
  • 保持或改善溶液质量.
  • 在快速找到可行的,工程问题的最佳解决方案方面表现出特别的有效性.

结论:

  • 基于PFN的BO框架为高效的工程设计优化提供了显著的进步.
  • 这种方法可以加速在复杂的设计空间中发现可行和最佳的解决方案.