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 …
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 …
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…
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 …
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 …
Innovative approaches for deep decarbonization of data centers …
Mar 1, 2024 · The data center heat recovery systems discussed in the studies above fall into two primary categories: those utilizing heat pumps to recover waste heat from data centers for …
Tensor network decomposition for data recovery: Recent …
Nov 1, 2025 · Tensor network (TN) decomposition stands as a pivotal technique for characterizing the essential features of high-dimensional data, attracting significant interest and achieving …
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…
Lost data recovery for structural vibration data based on improved …
Jun 1, 2025 · Verification was conducted on single-channel and multi-channel data from practical engineering of large-span bridges by comparing the recovery levels in the time and frequency …
A neural tensor decomposition model for high-order sparse data …
Feb 1, 2024 · When faced with high missing ratios or sparse observed sets, the recovery results become less ideal [20]. More importantly, the nonlinear information in the data may obscure …