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IRTF: A new tensor factorization for irregular multidimensional data ...IRTF: A new tensor factorization for irregular multidimensional data ...
By integrating the proposed IRTF and TV-CST, we establish an irregular multidimensional data recovery model. From (d), we can observe that our method preserves the color and the edge of the spatial-irregular multidimensional data as compared with traditional tensor factorization with preprocessing.

Waste heat recoveries in data centers: A review - ScienceDirectWaste 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.

Localized anomaly detection and recovery of marine engine data to ...Localized anomaly detection and recovery of marine engine data to ...
In this research study SVD analysis is performed within data clusters for localized anomaly detection and missing data recovery. While localized models can effectively capture the nonlinear dynamics of the vessel, they are more straightforward to interpret and analyze the results compared to complex DL-based models.

Missing measurement data recovery methods in structural health ...Missing measurement data recovery methods in structural health ...
In order to demonstrate the practical application of missing measurement data recovery methods in SHM, this section focuses on the Hardanger Bridge in Norway, a kilometer-scale suspension bridge.

Analysis of false lock in Mueller-Muller clock and data recovery system ...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.

Tensor network decomposition for data recovery: Recent advancements and ...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.

Trustworthy data recovery for incomplete multi-view learningTrustworthy 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.

Impacts of flexible-cooling and waste-heat recovery from data centres ...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 ...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 …

Swimming in urban estuaries: understanding stormwater contamination ...Swimming in urban estuaries: understanding stormwater contamination ...
This study analysed historical bathing water compliance data and concurrent hydrometeorological records to characterise long and short-term contamination and recovery patterns at current and proposed bathing sites in Sydney’s Parramatta River estuary.







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