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相关概念视频

Group Polarization01:01

Group Polarization

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Group polarization is the strengthening of an original group attitude following the discussion of views within a group (Teger & Pruitt, 1967). That is, if a group initially favors a viewpoint, after discussion the group consensus is likely a stronger endorsement of the viewpoint. Conversely, if the group was initially opposed to a viewpoint, group discussion would likely lead to stronger opposition.
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Types of Aggregate Grading01:15

Types of Aggregate Grading

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Aggregate grading is crucial in economically obtaining a concrete mix with adequate strength, reasonable workability, and minimal segregation. There are four types of aggregate gradation: well-graded, uniformly (or one-sized) graded, gap-graded, and open-graded.
Well-graded aggregates include a complete range of necessary size fractions that fit together to create a dense matrix with minimal voids, represented by a smooth, continuous gradation curve. This type of grading ensures good...
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Decision Making: P-value Method01:09

Decision Making: P-value Method

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The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can...
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Bonferroni Test01:10

Bonferroni Test

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The Bonferroni test is a statistical test named after Carlo Emilio Bonferroni, an Italian mathematician best known for Bonferroni inequalities. This statistical test is a type of multiple comparison test to determine which means are different than the rest. Bonferroni test can minimize the Type 1 error by reducing the significance level alpha, which otherwise increases with sample pairs.
The means of different samples are first paired in all possible combinations.
The null hypothesis of the...
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Sieve Analysis and Grading Curves01:19

Sieve Analysis and Grading Curves

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Sieve analysis is a method used to determine the particle size distribution of aggregate materials. This process involves the following steps:
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Confidence Coefficient01:24

Confidence Coefficient

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The confidence coefficient is also known as the confidence level or degree of confidence. It is the percent expression for the probability, 1-α, that the confidence interval contains the true population parameter assuming that the confidence interval is obtained after sufficient unbiased sampling; for example, if the CL = 90%, then in 90 out of 100 samples the interval estimate will enclose the true population parameter. Here α is the area under the curve, distributed equally under...
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相关实验视频

Updated: Jul 19, 2025

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
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A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

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一个改进的PBFT共识算法,基于分组和信用评级.

Shannan Liu1, Ronghua Zhang2, Changzheng Liu3

  • 1College of Information Science and Technology, Shihezi University, Shihezi, 832000, Xinjiang, China.

Scientific reports
|August 10, 2023
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种基于信用的拜占庭式容错共识算法 (CBFT),用于增强区块链网络. 与现有方法相比,CBFT显著改善吞吐量,减少延迟和通信开销,并增加故障容忍度.

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相关实验视频

Last Updated: Jul 19, 2025

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
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A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Published on: December 10, 2012

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科学领域:

  • 区块链技术 区块链技术
  • 分布式系统 分布式系统
  • 计算机科学 计算机科学

背景情况:

  • 实用拜占庭式故障宽容 (PBFT) 存在高通讯开销和有限的网络可扩展性问题.
  • 现有的共识算法难以平衡效率,安全性和网络大小.

研究的目的:

  • 提出一个增强的拜占庭式容错共识算法 (CBFT),解决PBFT的局限性.
  • 为了提高通信效率,网络尺寸支持和区块链共识中的安全性.

主要方法:

  • 开发了一种新的基于信用的拜占庭式容错 (CBFT) 共识算法.
  • 实施了一个分组模型,将节点按响应速度划分,以获得分离的集团内部和集团内部共识.
  • 整合了一个信用模型,为节点类型分配不同的责任,降低恶意主节点的概率.

主要成果:

  • 与PBFT相比,CBFT的吞吐量是PBFT的3.1倍,与52个节点相比,GPBFT的1.5倍.
  • 延迟时间减少到PBFT的7.4%,GPBFT的38.8%.
  • 通讯开支减少到PBFT的6.4%,GPBFT的87.3%.
  • 通过300个节点,拜占庭式故障耐受性提高了59.3%,随着网络规模的增加,收益增加了.

结论:

  • 拟议的CBFT算法显著提高了区块链共识的效率和可扩展性.
  • CBFT提供了比传统的PBFT更安全,更高性能的替代方案,特别是在大型网络中.
  • 集团和信用模型有效地减少了通信开销,并减轻了与恶意节点相关的风险.