DATA RECOVERY Web Results

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.

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.

Dynamic performance of an integrated heat pump system coupled free ... Recovering and reusing this waste heat for district heating is an effective strategy to enhance energy efficiency in data centers. To align data center waste heat recovery with heat consumer demand and improve energy utilization, a transient mathematical model of a data center-integrated heat pump district heating system was developed and ...

Trustworthy data recovery for incomplete multi-view learning Therefore, in this paper, we aim to develop a trustworthy data recovery framework for incomplete multi-view learning (TDR-IML), which ensures reliable imputed data with an uncertainty-aware scheme.

Long-term missing wind data recovery using free access databases and ... The conventional interpolation techniques hardly achieve the desired data recovery. Therefore, a framework was proposed for long-term missing wind data recovery based on a deep neural network (DNN) utilizing a free access database (European Center for Medium-Range Weather Forecasts, ECMWF).

Kernel Bayesian tensor ring decomposition for multiway data recovery With the aid of side information, the recovery performance of the methods above is improved. However, all matrix-based methods with side information encounter difficulties when dealing with high-order data because they cannot incorporate specific side information enhancements.

Impacts of flexible-cooling and waste-heat recovery from data centres ... This paper quantifies the economic and environmental gains from data centre's cooling-based flexibility and waste-heat recovery in energy systems with significant data centre demand, high penetration of variable renewable sources, and well-established district heating networks.

GRACE Follow-On accelerometer data recovery by high-precision ... The Gravity Recovery and Climate Experiment Follow-On (GRACE-FO) satellites are equipped with high-precision three-axis accelerometers to measure all …

Multi-dimensional imaging data recovery via minimizing the partial sum ... The tensor, a multi-dimensional extension of the matrix, is an important data format and has been applied in lots of real-world applications, for example, the video data recovery [1], the hyperspectral data recovery and fusion [2], [3], the personalized web search [4], and seismic data reconstruction [5]. Among these applications, how to accurately characterize and rationally utilize the inner ...