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. Data policies and procedures will help to prevent “disasters” caused by users.
Missing measurement data recovery methods in structural health ...
2024年5月31日 · The missing sensor data is treated as an unknown variable for data recovery, decoding vector y l, and determining the decoding measurement matrix Φ l according to the missing data case. The generated measurement matrix needs to ensure that the random matrix has sufficient sparsity and randomness to ensure the performance of the CS algorithm.
Data recovery in a case of fire-damaged Hard Disk Drives and …
2021年7月1日 · Fortunately, the owners of the drives reacted quickly. All the drives were referred to the data recovery service immediately after they had been recovered. Before any attempts to read the data, the drives were disassembled, and their electronic components were removed and thoroughly cleaned with 99,9% isopropyl alcohol (IPA).
Multi-dimensional imaging data recovery via minimizing the …
2020年7月1日 · 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].
Spatial-temporal traffic speed patterns discovery and incomplete …
2018年1月1日 · 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.
Social media use in disaster recovery: A systematic literature review
2022年2月15日 · The damage and performance issues associated with disaster impacts can be investigated and monitored with social media data. Community recovery from major disasters is often challenging without a clear understanding of the locations and extent of damage caused to key public infrastructure such as power/electricity, roads/transportation ...
Filling GRACE data gap using an innovative transformer-based …
2024年12月15日 · Integration of GRACE (Gravity Recovery and Climate Experiment) data with traditional data sets for a better understanding of the time-dependent water partitioning in African watersheds Geology , 39 ( 5 ) ( 2011 ) , pp. 479 - 482 , 10.1130/g31812.1
Assessing post-fire forest structure recovery by combining LiDAR …
2022年4月1日 · Post-fire forest recovery dynamics are highly complex due to their high variability and processes undergone in changing environmental conditions. LiDAR data in combination with Landsat imagery provides a unique opportunity to extrapolate information on forest structure over time for a comprehensive evaluation of forest resilience to fire.
A data-driven analysis of the aviation recovery from the COVID-19 ...
2023年6月1日 · The recovery time for the air transport sector based on historical aviation data and available epidemic data has been extensively discussed. EUROCONTROL issued a five-year (2020–2024) forecast of the European aviation at the end of 2020, mainly depending on the availability and effectiveness of COVID-19 vaccines, along with passenger ...
Artificial intelligence for cybersecurity: Literature review and future ...
2023年9月1日 · The main goal of data extraction is to break down each study into its constituent parts and describe the overall relationships and connections. The data extraction parameters (explained in Table 3) collect the qualitative and contextual data from the primary studies selected for the SLR. The qualitative data are collected to write a short ...