DATA RECOVERY Web Results

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.

A novel tensor decomposition-based approach for internet traffic data ... In this paper, we proposed a novel tensor-based approach for the recovery and forecast of internet network traffic data from incomplete observed data. The proposed model is based upon the newly introduced higher-order tensor decomposition form called tubal tensor train (TTT) decomposition, which fully fuses the data information inside each ...

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.

Tensor completion via joint reweighted tensor Tensor, as a generalization of vector and matrix, is a powerful tool for processing multi-dimensional data and plays a critical role in different fields of scientific computing, like color image and video inpainting [1], [2], [3], hyperspectral data recovery and classification [4], [5], [6], [7], and seismic data reconstruction [8].

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.

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.

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.

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.

Nonconvex 3D array image data recovery and pattern recognition under ... In this paper, we present a weighted tensor Schatten-p quasi-norm (0