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相关概念视频

Random Error01:04

Random Error

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Random or indeterminate errors originate from various uncontrollable variables, such as variations in environmental conditions, instrument imperfections, or the inherent variability of the phenomena being measured. Usually, these errors cannot be predicted, estimated, or characterized because their direction and magnitude often vary in magnitude and direction even during consecutive measurements. As a result, they are difficult to eliminate. However, the aggregate effect of these errors can be...
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State Function, Exact and Inexact Differentials01:27

State Function, Exact and Inexact Differentials

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A state function is a thermodynamic property that depends solely on the current state of a system, irrespective of its history or how it arrived at that state. These functions are represented by capital letters, such as U, H, and S, which stand for internal energy, enthalpy, and entropy, respectively.For instance, the value of internal energy depends on the system's state variables and remains unaffected by the process path. This means that whether the system underwent a linear process or a...
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Distribution Reliability and Automation01:25

Distribution Reliability and Automation

557
Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
557
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

799
The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
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Differential Relays01:20

Differential Relays

878
Differential relays are used to protect generators, buses, and transformers by comparing electrical quantities at different points. When a fault occurs, the difference in current between the two points triggers the relay to operate, opening the circuit breaker. Under normal conditions, the current entering (i1) and leaving (i2) a generator are equal. When a fault occurs, however, these currents become unequal, and the difference current flows in the relay operating coil, causing the relay to...
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Censoring Survival Data01:09

Censoring Survival Data

626
Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different...
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相关实验视频

Updated: Jun 18, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

智能电网中的高效数据聚合:个性化的局部差分隐私计划

Haina Song1, Jinhang Sun1, Mengyao Wang1

  • 1Hubei Key Laboratory for High-Efficiency Utilization of Solar Energy and Operation Control of Energy Storage System, Hubei University of Technology, Wuhan 430068, China.

Sensors (Basel, Switzerland)
|March 14, 2026
PubMed
概括

这项研究引入了智能电网的高效数据聚合方案,使电力数据的个性化隐私保护成为可能. 该方法平衡了用户隐私需求与准确的网格分析,优于现有方法.

关键词:
数据聚合,数据聚合.当地差异性隐私 地方差异性隐私个性化隐私保护 个人隐私保护智能电网是一个智能电网.

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Bringing the Clinic Home: An At-Home Multi-Modal Data Collection Ecosystem to Support Adaptive Deep Brain Stimulation
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相关实验视频

Last Updated: Jun 18, 2026

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Bringing the Clinic Home: An At-Home Multi-Modal Data Collection Ecosystem to Support Adaptive Deep Brain Stimulation
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科学领域:

  • 计算机科学 计算机科学
  • 电气工程 电气工程
  • 网络安全 网络安全

背景情况:

  • 智能电网提高了效率,但也引发了用户电力数据隐私方面的担忧.
  • 现有的隐私方法无法满足个人需求,并降低数据的准确性.
  • 在个性化隐私和精确的网格分析之间存在冲突.

研究的目的:

  • 提出基于个性化局部差异隐私 (EDAS-PLDP) 的智能电网高效数据聚合方案.
  • 解决个性化隐私保护和高精度网格数据分析之间的权衡问题.
  • 为了使用户能够为他们的电力消耗数据选择自定义的隐私级别.

主要方法:

  • 开发了基于个性化局部差异隐私 (EDAS-PLDP) 的高效数据聚合方案.
  • 实施了基于平均平方误差的加权聚合策略,以减轻准确性损失.
  • 评估了来自不同隐私偏好组的数据质量,以优化全球平均值估计.

主要成果:

  • 与现有的方案相比,EDAS-PLDP在各种隐私偏好,用户规模和数据细节性方面实现了更高的估计准确性.
  • 拟议的方案显示了较低的时间消耗,适用于资源有限的智能电网.
  • 对于虚假数据注入攻击,EDAS-PLDP表现出极好的稳定性.

结论:

  • 对于智能电网,EDAS-PLDP提供了一个平衡且高效的解决方案.
  • 该计划有效地将个性化的隐私保护与高精度数据实用性相协调.
  • 它为增强智能电网中的隐私和数据分析提供了一种实用方法.