Jove
Visualize
お問い合わせ
JoVE
x logofacebook logolinkedin logoyoutube logo
JoVEについて
概要リーダーシップブログJoVEヘルプセンター
著者向け
出版プロセス編集委員会範囲と方針査読よくある質問投稿
図書館員向け
推薦の声購読アクセスリソース図書館諮問委員会よくある質問
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experimentsアーカイブ
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教員リソースセンター教員サイト
利用規約
プライバシーポリシー
ポリシー

関連する概念動画

Maximum Power Transfer01:16

Maximum Power Transfer

396
Numerous practical applications within engineering disciplines, such as telecommunications, necessitate optimizing power delivery to a connected load. This pursuit, however, entails inherent internal losses, which can either equal or exceed the power supplied to the load. The Thevenin equivalent circuit is helpful in finding the maximum power a linear circuit can deliver to a load. It is assumed in this context that the load resistance can be adjusted.
By substituting the entire circuit with...
396
Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

178
The maximum power flow for lossy transmission lines is derived using ABCD parameters in phasor form. These parameters create a matrix relationship between the sending-end and receiving-end voltages and currents, allowing the determination of the receiving-end current. This relationship facilitates calculating the complex power delivered to the receiving end, from which real and reactive power components are derived.
178
Energy Budgets00:51

Energy Budgets

9.7K
Organisms must balance energy intake with the energy required for growth, maintenance and reproduction. These trade-offs result in a variety of survivorship and reproductive strategies, including semelparity and iteroparity. Semelparous species, like annual plants, have only one reproductive episode in their lifetimes and consequently have short lifespans. Iteroparous species, by contrast, have many reproductive events during their lifetimes but have relatively few offspring. These two...
9.7K
Energy to Drive Translocation01:37

Energy to Drive Translocation

2.1K
Mitochondrial protein import is powered by two distinct energy sources: ATP hydrolysis and electrochemical potential across the inner membrane. Newly synthesized precursors are bound by cytosolic chaperones of the Hsp70 family, which guide them to the import receptors on the mitochondrial surface. Utilizing the energy of ATP hydrolysis, Hsp70 chaperones transfer these precursors to the TOM receptors on the mitochondrial outer membrane.
Generally, polypeptides are unfolded by two distinct...
2.1K
Short-distance Transport of Resources02:12

Short-distance Transport of Resources

16.5K
Short-distance transport refers to transport that occurs over a distance of just 2-3 cells, crossing the plasma membrane in the process. Small uncharged molecules, such as oxygen, carbon dioxide, and water, can diffuse across the plasma membrane on their own. In contrast, ions and larger molecules require the assistance of transport proteins due to their charge or size. Transport across membranes also occurs within individual cells, playing a variety of essential roles for the plant as a whole.
16.5K
Energy Conservation and Bernoulli's Equation01:16

Energy Conservation and Bernoulli's Equation

9.4K
Applying the conservation of energy principle or the work-energy theorem to an incompressible, inviscid fluid in laminar, steady, irrotational flow leads to Bernoulli's equation. It states that the sum of the fluid pressure, potential, and kinetic energy per unit volume is constant along a streamline.
All the terms in the equation have the dimension of energy per unit volume. The kinetic energy per unit volume is called the kinetic energy density, and the potential energy per unit volume is...
9.4K

こちらも読む

関連記事

共著者、ジャーナル、引用グラフによってこの研究に関連する記事。

並び替え
Same author

Analysis of comorbidity patterns of pregnancy and delivery complications in the female population.

Frontiers in global women's health·2026
Same author

Correction: LncRNA SPINT1-AS1 enhances the Warburg effect and promotes the progression of osteosarcoma via the miR-135b-5p/PGAM1 axis.

Cancer cell international·2026
Same author

Chalcone-containing dual-targeting PD-L1/tubulin small molecules: a novel approach for cancer immunotherapy.

Frontiers in pharmacology·2026
Same author

Integrating multi-stage interventions for harmful algal blooms effective management.

Journal of environmental management·2026
Same author

Diagnostic Utility of Bronchoalveolar Lavage Metagenomic Next-Generation Sequencing for Pulmonary Mucormycosis: A Single-Center Retrospective Cohort Study.

Infection and drug resistance·2025
Same author

Design and mechanistic study of a D-π-a fluorescent probe for sensitive water detection in organic media.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy·2025

関連する実験動画

Updated: Sep 9, 2025

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

657

5G NRにおけるエネルギー最適化のためのMLベースのリソース割り当てスキーム

Xiao Yao1, Antonio Pérez Yuste1

  • 1ETSI Sistemas de Telecomunicación, Universidad Politécnica de Madrid, 28031 Madrid, Spain.

Sensors (Basel, Switzerland)
|August 28, 2025
PubMed
まとめ

この研究は,5G New Radioのエネルギー消費を最適化するための機械学習の枠組みを紹介しています. エネルギー消費を40%以上削減し,予測的な資源管理によりサービスの質を保証します.

科学分野:

  • 電気通信工学
  • コンピュータ科学
  • 人工知能

背景:

  • 5Gニューラジオ (5G NR) ネットワークはエネルギー需要の増加に直面しています.
  • 効率的なエネルギー管理は,持続可能なネットワークの運営に不可欠です.
  • エネルギー節約と並行してサービス品質を維持することは大きな課題です.

研究 の 目的:

  • 5G NRのための機械学習ベースのエネルギー最適化フレームワークを提案し,検証する.
  • 5G NR基地局のエネルギー消費を削減する.
  • エネルギー削減戦略がQoSの重要なパラメータを損なわないことを確保する.

主な方法:

  • 予測的な負荷予測のための分類と回帰ツリー (CART) アルゴリズムを使用する.
  • 予測されるネットワーク負荷に基づいてダイナミックなセルリソースの再構成を実行します.
  • バンド間NR-NRダブルコネクティビティ (DC) ネットワークのレイアウトを検証する.

主要な成果:

  • エネルギー消費量を42.3%削減しました
  • サービス品質 (QoS) パラメータは,第3世代パートナーシッププロジェクト (3GPP) 指定された値内で維持されます.
キーワード:
5G RANについてRRC についてエネルギー効率機械学習資源の配分

さらに関連する動画

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem
10:15

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem

Published on: February 3, 2021

3.9K
Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption
10:36

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption

Published on: November 3, 2023

1.7K

関連する実験動画

Last Updated: Sep 9, 2025

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

657
Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem
10:15

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem

Published on: February 3, 2021

3.9K
Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption
10:36

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption

Published on: November 3, 2023

1.7K
  • シミュレートされたネットワークのケーススタディを通じて提案されたモデルを定量的に検証した.

    • 結論:

    • 提案された機械学習の枠組みは,5G NRネットワークのエネルギー消費を効果的に最適化します.
    • 予測的負荷予測によるダイナミックなセル資源再構成は,エネルギー節約のための実行可能な戦略です.
    • CARTアルゴリズムは,ネットワークのパフォーマンスを犠牲にすることなく,大幅なエネルギー削減を達成するための堅実な方法を提供します.