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Adaptive Multivariate Data Compression in Smart Metering Internet of Things
IEEE Transactions on Industrial Informatics, 2021Recent advances in electric metering infrastructure have given rise to the generation of gigantic chunks of data. Transmission of all of these data certainly poses a significant challenge in bandwidth and storage constrained Internet of Things (IoT ...
M. R. Chowdhury, Sharda Tripathi, S. De
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Data compression and histograms [PDF]
Probability Theory and Related Fields, 1992 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Terence P. Speed, Bin Yu
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Data Compression Accelerator on IBM POWER9 and z15 Processors : Industrial Product
International Symposium on Computer Architecture, 2020Lossless data compression is highly desirable in enterprise and cloud environments for storage and memory cost savings and improved utilization I/O and network.
B. Abali +11 more
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Comparison of Lossless Data Compression Techniques
International Congress on Information and Communication Technology, 2020The transmission of humongous data from the monitoring field to the central unit for further processing is a highly challenging task for the hardware, especially when the communication bandwidth is limited.
Athira Gopinath, M. Ravisankar
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Proceedings of SPE/IADC Drilling Conference, 1999
Abstract Measurement-While-Drilling (MWD) services efficiently support drilling decisions, therefore these tools are becoming a de-facto standard on well sites. Currently, the main drawback of MWD equipment is the absence of a high bit-rate telemetry system to enable real-time activities. This problem may be solved by employing either an
G Bernasconi +3 more
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Abstract Measurement-While-Drilling (MWD) services efficiently support drilling decisions, therefore these tools are becoming a de-facto standard on well sites. Currently, the main drawback of MWD equipment is the absence of a high bit-rate telemetry system to enable real-time activities. This problem may be solved by employing either an
G Bernasconi +3 more
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Two-Level Data Compression using Machine Learning in Time Series Database
IEEE International Conference on Data Engineering, 2020The explosion of time series advances the development of time series databases. To reduce storage overhead in these systems, data compression is widely adopted.
Xinyang Yu +6 more
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IEEE Transactions on Information Theory, 1994
In a frequent practical situation one possesses inconsistent fragmentary data concerning some industrial process or natural phenomenon. It is an interesting and reasonable task to assess what the most concise way to store or transmit them would be.
KORNER, JANOS, Mario Lucertini
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In a frequent practical situation one possesses inconsistent fragmentary data concerning some industrial process or natural phenomenon. It is an interesting and reasonable task to assess what the most concise way to store or transmit them would be.
KORNER, JANOS, Mario Lucertini
openaire +4 more sources
High-Ratio Lossy Compression: Exploring the Autoencoder to Compress Scientific Data
IEEE Transactions on Big Data, 2023Scientific simulations on high-performance computing (HPC) systems can generate large amounts of floating-point data per run. To mitigate the data storage bottleneck and lower the data volume, it is common for floating-point compressors to be employed ...
Tong Liu +5 more
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Deep learning for data anomaly detection and data compression of a long‐span suspension bridge
Comput. Aided Civ. Infrastructure Eng., 2019As intelligent sensing and sensor network systems have made progress and low‐cost online structural health monitoring has become possible and widely implemented, large quantities of highly heterogeneous data can be acquired during the monitoring.
FuTao Ni, Jian Zhang, Mohammad Noori
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2004
Publisher Summary This chapter discusses the problem of data compression, i.e., different ways of minimizing the amount of digital data symbols, e.g. bits, need to represent a given amount of information in, for instance, a computer file. Removing redundancy is mainly what data compression is all about i.e., information that could be deducted from ...
William Walker, Dag Stranneby
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Publisher Summary This chapter discusses the problem of data compression, i.e., different ways of minimizing the amount of digital data symbols, e.g. bits, need to represent a given amount of information in, for instance, a computer file. Removing redundancy is mainly what data compression is all about i.e., information that could be deducted from ...
William Walker, Dag Stranneby
openaire +4 more sources