DATA RECOVERY Web Results

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.

IRTF: A new tensor factorization for irregular multidimensional data ... Consequently, data recovery techniques are required to enhance the quality of these observed data for subsequent tasks. Real-world multidimensional data can be mathematically represented by the tensor [7], [8]. In this paper, we specifically focus on third-order tensors.

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.

Air quality index prediction through TimeGAN data recovery and PSO ... TimeGAN is employed to learn the structure and distribution of air quality data, facilitating the generation of synthetic data through adversarial networks. Subsequently, the missing values in the real data are replaced with the generated data.

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.

Missing measurement data recovery methods in structural health ... A data recovery method based on the OMP algorithm is used in the missing response recovery for aviation anti-rust aluminum plates [32]. Li et al. [6] studied an approach that uses convex optimization theory and OMP algorithm to achieve CS-based electromechanical admittance data recovery.

Analysis of false lock in Mueller-Muller clock and data recovery system ... Within high-speed serial data communication systems, the Clock and Data Recovery (CDR) circuit serves as the core module. For SerDes, it is crucial to extract the clock signals at the receiver correctly for clock synchronization and optimal data sampling.

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.

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.

Advances in direct liquid cooling technology and waste heat recovery ... The escalating demand for computational power and data storage has led to a substantial increase in the number and scale of data centers (DCs) worldwide. Due to characteristics of high heat flux and reliable operational security, there is an urgent need for innovative solutions to solve the problem of DC cooling and waste heat recovery.