Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Aekyeung Moon"'
Publikováno v:
2022 IEEE International Conference on Big Data (Big Data).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f0df7521f1e7a159b29d4fd5d707d648
https://doi.org/10.1109/bigdata55660.2022.10020381
https://doi.org/10.1109/bigdata55660.2022.10020381
Publikováno v:
2022 IEEE International Conference on Big Data (Big Data).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4f6daf93a084ee7c39e2378dcd2da7e5
https://doi.org/10.1109/bigdata55660.2022.10020345
https://doi.org/10.1109/bigdata55660.2022.10020345
Publikováno v:
2022 IEEE/ACM 8th International Workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f2256eb632d2859c6fd326bf9e98e772
https://doi.org/10.1109/drbsd56682.2022.00013
https://doi.org/10.1109/drbsd56682.2022.00013
Publikováno v:
2021 IEEE International Conference on Big Data (Big Data).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b6fa1f4068f5a96e017354b62d2cb702
https://doi.org/10.1109/bigdata52589.2021.9671364
https://doi.org/10.1109/bigdata52589.2021.9671364
Publikováno v:
CLUSTER
Lossy compression on scientific data is coming into prominence as the scientific workflow is hampered significantly by large amounts of data produced by high-performance computing (HPC) applications. State-of-the-art lossy compressors, such as SZ and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::499ffd5e115ef0668624b39c8dab61ab
https://doi.org/10.1109/cluster48925.2021.00056
https://doi.org/10.1109/cluster48925.2021.00056
Publikováno v:
IEEE BigData
The growing demand for recording longer ECG signals to improve the effectiveness of IoT-enabled remote clinical healthcare is contributing large amounts of ECG data. While lossy compression techniques have shown potential in significantly lowering th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::00e50c3d9ea9888dbb2f253abcbbcb8d
https://doi.org/10.1109/bigdata50022.2020.9378343
https://doi.org/10.1109/bigdata50022.2020.9378343
Publikováno v:
HPEC
Scientific simulations run by high-performance computing (HPC) systems produce a large amount of data, which causes an extreme I/O bottleneck and a huge storage burden. Applying compression techniques can mitigate such overheads through reducing the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::802008e897947778070e893b3622c7f1
https://doi.org/10.1109/hpec43674.2020.9286177
https://doi.org/10.1109/hpec43674.2020.9286177
Publikováno v:
Computers and Electronics in Agriculture. 154:304-313
As the volume of data collected by various IoT sensors used in smart farm applications increases, the storing and processing of big data for agricultural applications become a huge challenge. The insight of this paper is that lossy compression can un
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6589806c154961622288ff5ba25268a0
https://doi.org/10.1016/j.compag.2018.08.045
https://doi.org/10.1016/j.compag.2018.08.045
Publikováno v:
IEEE BigData
With recent technological advances in sensor nodes, IoT enabled applications have great potential in many domains. However, sensing data may be inaccurate due to not only faults or failures in the sensor and network but also the limited resources and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a859015485053dfdb76d204a444d5cb7
https://doi.org/10.1109/bigdata47090.2019.9005533
https://doi.org/10.1109/bigdata47090.2019.9005533
Publikováno v:
HPEC
As the size and amount of data produced by high-performance computing (HPC) applications grow exponentially, an effective data reduction technique is becoming critical to mitigating time and space burden. Lossy compression techniques, which have been
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::adf1b221d407bbb36c079ea854840841
https://doi.org/10.1109/hpec.2019.8916286
https://doi.org/10.1109/hpec.2019.8916286