Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

50
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...
50
Alternative Sets of Equilibrium Equations01:31

Alternative Sets of Equilibrium Equations

389
When analyzing the behavior of structures, engineers often rely on the concept of equilibrium. This refers to the state where all forces and moments acting on a system balance each other, resulting in no net movement or rotation. In many cases, equilibrium can be described by a set of standard equations. However, in some situations, alternative sets of equilibrium equations must be used to describe the system's behavior accurately.
One example of such a situation can be observed in a...
389
Overview of Cell-Matrix Interactions01:24

Overview of Cell-Matrix Interactions

7.2K
The extracellular matrix or ECM holds cells together to form a tissue and allows the cells within the tissue to communicate. ECM comprises proteins such as fibronectin, collagen, laminin, etc. The most abundant protein in this space is collagen. Collagen fibers are interwoven with carbohydrate-containing protein molecules called proteoglycans. ECM allows cell migration and provides a structural scaffold at cell adhesion that anchors the cell when the extracellular matrix proteins interact with...
7.2K
MO Theory and Covalent Bonding02:40

MO Theory and Covalent Bonding

10.5K
The molecular orbital theory describes the distribution of electrons in molecules in a manner similar to the distribution of electrons in atomic orbitals. The region of space in which a valence electron in a molecule is likely to be found is called a molecular orbital. Mathematically, the linear combination of atomic orbitals (LCAO) generates molecular orbitals. Combinations of in-phase atomic orbital wave functions result in regions with a high probability of electron density, while...
10.5K
Cell-matrix's Response to Mechanical Forces01:13

Cell-matrix's Response to Mechanical Forces

2.6K
In animal cells, the extracellular matrix allows cells within tissues to withstand external stresses and transmits signals from the outside of the cell to the inside. The extracellular matrix is extensive, and its composition varies between different types of tissues. For example, the reticular fibers and ground substance make up the ECM in loose connective tissue, while collagen and bone minerals make up the ECM of bone tissue. 
Anchoring junctions mechanically attach a cell to the...
2.6K
¹H NMR Signal Multiplicity: Splitting Patterns01:13

¹H NMR Signal Multiplicity: Splitting Patterns

5.1K
When protons A and X are coupled, their nuclear spin energy levels are slightly modified. This is because the energy required to excite proton A to a spin state parallel to proton X is slightly different from the energy required for it to become anti-parallel to spin X. Consequently, there are two possible excitation frequencies for A (A1 and A2), depending on the spin state of X, and vice versa. The mutual nature of coupling implies that the difference between frequencies A1 and A2, indicated...
5.1K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Optimizing Distributions for Associated Entropic Vectors via Generative Convolutional Neural Networks.

Entropy (Basel, Switzerland)·2024
Same author

Fundamental Limits of Coded Caching in Request-Robust D2D Communication Networks.

Entropy (Basel, Switzerland)·2024
Same author

A Numerical Study on the Capacity Region of a Three-Layer Wiretap Network.

Entropy (Basel, Switzerland)·2023
Same author

On the Asymptotic Capacity of Information-Theoretic Privacy-Preserving Epidemiological Data Collection.

Entropy (Basel, Switzerland)·2023

相关实验视频

Updated: Jun 25, 2025

2D and 3D Matrices to Study Linear Invadosome Formation and Activity
12:25

2D and 3D Matrices to Study Linear Invadosome Formation and Activity

Published on: June 2, 2017

10.0K

在任意勾结模式下最小化双边安全分布式矩阵乘法计算和通信成本.

Jin Li1, Nan Liu1, Wei Kang2

  • 1National Mobile Communications Research Laboratory, Southeast University, Nanjing 211189, China.

Entropy (Basel, Switzerland)
|May 24, 2024
PubMed
概括

这项研究通过优化矩阵分割和随机矩阵使用来最大限度地降低安全分布式矩阵乘法 (SDMM) 的成本. 一种新的零依赖策略和交替优化显著提高了效率和安全性.

关键词:
随意的勾结模式的任意勾结模式.整数几何编程的整数几何编程整数线性编程的整数线性编程安全的分布式矩阵乘法.

更多相关视频

Quadruple-Checkerboard: A Modification of the Three-Dimensional Checkerboard for Studying Drug Combinations
11:15

Quadruple-Checkerboard: A Modification of the Three-Dimensional Checkerboard for Studying Drug Combinations

Published on: July 24, 2021

4.6K
Preparation of Complaint Matrices for Quantifying Cellular Contraction
11:38

Preparation of Complaint Matrices for Quantifying Cellular Contraction

Published on: December 14, 2010

17.8K

相关实验视频

Last Updated: Jun 25, 2025

2D and 3D Matrices to Study Linear Invadosome Formation and Activity
12:25

2D and 3D Matrices to Study Linear Invadosome Formation and Activity

Published on: June 2, 2017

10.0K
Quadruple-Checkerboard: A Modification of the Three-Dimensional Checkerboard for Studying Drug Combinations
11:15

Quadruple-Checkerboard: A Modification of the Three-Dimensional Checkerboard for Studying Drug Combinations

Published on: July 24, 2021

4.6K
Preparation of Complaint Matrices for Quantifying Cellular Contraction
11:38

Preparation of Complaint Matrices for Quantifying Cellular Contraction

Published on: December 14, 2010

17.8K

科学领域:

  • 分布式计算 分布式计算
  • 信息安全信息安全.
  • 矩阵计算矩阵计算

背景情况:

  • 安全分布式矩阵乘法 (SDMM) 对于保护隐私的计算至关重要.
  • 现有的SDMM方案面临着在任意勾结下最大限度地降低联合计算和通信成本的挑战.
  • 矩阵分割和存储约束中的可分割性问题也会影响系统效率.

研究的目的:

  • 在双面SDMM系统中最大限度地降低总成本 (计算和通信).
  • 为了优化矩阵分割因子,随机矩阵数量和分布向量.
  • 在任意勾结下满足安全性,解码性,存储和延迟约束.

主要方法:

  • 引入了将零添加到输入矩阵的策略,以解决矩阵分割的可分割性问题.
  • 交替优化 (AO) 用于将主要问题分成两个可解决的子问题.
  • 分析包括推导出问题可行性的必要条件.

主要成果:

  • 拟议的方案,包括零附加和AO,为SDMM成本最小化提供了可行的解决方案.
  • 模拟结果验证了拟议方法的优越性,而不是缺乏零附加或AO的方案.
  • 优化的方案有效地平衡了安全性,解码性,存储和延迟约束.

结论:

  • 新的零依赖策略和基于AO的优化有效地降低了双面SDMM的总成本.
  • 拟议的方法提高了SDMM的效率和安全性,特别是在任意勾结模式下.
  • 这项工作为实用和安全的分布式矩阵乘法提供了一个强大的框架.