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Waste heat recoveries in data centers: A review - ScienceDirect
Waste heat recovery technology is considered as a promising approach to improve energy efficiency, achieve energy and energy cost savings, and mitigate environmental impacts (caused by both carbon emission and waste heat discharge) at the same time.

Distributed neural tensor completion for network monitoring data recovery
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 methods have attracted recent attentions with their capability of capturing complex interactions among data for more accurate recovery.

Tensor network decomposition for data recovery: Recent advancements and ...
Tensor network (TN) decomposition stands as a pivotal technique for characterizing the essential features of high-dimensional data, attracting significant interest and achieving notable success in high-dimensional data recovery.

A neural tensor decomposition model for high-order sparse data recovery ...
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 the low rankness and the model performance may be hindered by the multi-linear hypothesis in the decomposition, making it fail to capture the nonlinear features [21].

A graph and diffusion theory-based approach for localization and ...
The proposed data recovery framework, comprised of the FDIA localization model and data recovery model, offers a notable improvement in accuracy, providing a more robust defense against cyberattacks and enhancing grid security.

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 locations.

Innovative approaches for deep decarbonization of data centers and ...
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 utilization in district heating networks or buildings, and those relying solely on heat exchangers.

Analysis of false lock in Mueller-Muller clock and data recovery system ...
Another view suggests that data correlation is the key contributor [ [9], [10]]. In this work, we provide a comprehensive analysis of MMPD false lock and introduce an enhanced mitigation strategy, validated via simulations. Section 2 investigates the false-lock mechanism and presents an improved phase detection strategy.

Lost data recovery for structural vibration data based on improved U ...
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 domains. Different missing ratios are set, a mask matrix is used to construct random lost data, and the proposed model is used to reconstruct the lost data.

A novel tensor decomposition-based approach for internet traffic data ...
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 have favorable performance than some state-of-the-art tensor/matrix based approaches.

 

 

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