Data centers waste heat recovery technologies: Review and …
Apr 15, 2025 · With a growing focus on energy-saving and emission-reduction efforts in data centers, waste heat recovery technology is urgently needed because of the…
Distributed neural tensor completion for network monitoring data …
Mar 1, 2024 · Abstract Network monitoring data is usually incomplete, accurate and fast recovery of missing data is of great significance for practical applications. The tensor-based nonlinear …
Waste heat recoveries in data centers: A review - ScienceDirect
Dec 1, 2023 · Waste heat recovery technology is considered as a promising approach to improve energy efficiency, achieve energy and energy cost savings, and mitigate environmental …
A novel tensor decomposition-based approach for internet traffic …
A series of numerical experiments about the recovery of structurally missing traffic data and the traffic data prediction on the widely used real-world datasets demonstrate that our approach …
Data Recovery - an overview | ScienceDirect Topics
Data recovery strategies include hot sites, spare or underutilized servers, the use of noncritical servers, duplicate data centers, replacement agreements, and transferring operations to other …
Air quality index prediction through TimeGAN data recovery and …
Feb 1, 2025 · TimeGAN is employed to learn the structure and distribution of air quality data, facilitating the generation of synthetic data through adversarial networks. Subsequently, the …
Demonstration of all-digital burst clock and data recovery for ...
Aug 1, 2022 · We experimentally demonstrated all-digital burst clock and data recovery (BCDR) for symmetrical single-wavelength 50 Gb/s four-level amplitude modulat…
False data injection attacks data recovery in smart grids: A graph ...
Jun 26, 2025 · False data injection (FDI) attacks, one of the most classical cyber attacks, have increasingly posed a significant threat to the security and reliability of power systems [5]. Such …
Dual-domain low-rank tensor completion for traffic data recovery
However, due to the malfunctions in sensing devices or communication networks, missing data phenomena are ubiquitous in the real world and thus pose formidable challenges to network …
Transfer entropy and LSTM deep learning-based faulty sensor data ...
Dec 1, 2024 · The faulty sensor data recovery method consists of a TE-based fault feature variable extraction module, a UPCA-based sensor fault diagnosis module, and a GW-LSTM …