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  • 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
  • Spatial-temporal traffic speed patterns discovery and incomplete data . . .
    Abstract Missing data is an inevitable and ubiquitous problem in data-driven intelligent transportation systems While there are several studies on the missing traffic data recovery in the last decade, it is still an open issue of making full use of spatial-temporal traffic patterns to improve recovery performance
  • 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
  • Grade-recovery curves: A new approach for analysis of and predicting . . .
    Abstract Flotation performance is most commonly represented using grade-recovery curves, with a shift upwards and to the right indicating an improvement in performance The problem with using grade recovery curves, especially on plant data, is that position and shape of the curve is strongly influenced by both the feed rate and grade to the
  • Resilience of Interdependent Urban Socio-Physical Systems using Large . . .
    Here, we study the socio-physical interdependencies in urban systems and their effects on disaster recovery and resilience, using large-scale mobility data collected from Puerto Rico during Hurricane Maria
  • Waste heat recovery from urban air cooled data centres to increase . . .
    Even though the primary energy reused in such installations can be above 50%, the economic analysis performed for a specific 1000 kW data centre located in Barcelona (Spain) demonstrates the non-viability of heat recovery integration in most of the conventional air-cooled data centres
  • Performance analysis of compression-assisted absorption refrigeration . . .
    This study proposes a compression-assisted absorption refrigeration-heating (CARH) system aimed at fulfilling efficient waste heat recovery in the liquid-cooling system of data center In this system the auxiliary compression process is regarded as a solution to the difficulty of waste heat recovery with efficiency attributed to its low
  • Abnormal data detection and recovery of sensors network based on . . .
    Abstract This paper proposes a novel deep-learning-enabled framework for abnormal data detection and recovery considering spatial-temporal correlation among sensors The wavelet scattering transform is adopted to replace the first layer of one-dimension convolutional neural network classification model
  • Agent-based modelling of post-disaster recovery with remote sensing data
    Increasingly, there is a need to understand and explore the impacts of different dimensions of recovery, including the behaviour of individual actors and their interactions with socio-economic institutions Computer-based simulations such as agent-based models (ABMs) permit to explore the dynamics of the recovery process from the bottom up
  • A review of data center cooling technology, operating conditions and . . .
    A number of currently available and developmental low-grade waste heat recovery techniques were reviewed in order to assess the suitability and effectiveness of each technology specifically for the reuse of low quality data center waste heat





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