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Published in 2017 at "Fusion Engineering and Design"
DOI: 10.1016/j.fusengdes.2017.03.168
Abstract: Abstract The next generation of tokamaks, e.g. ITER, will have extremely large data collection rates significantly larger than those experienced today in present tokamaks, with consequential new challenges in data management, data analysis and integrated…
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Keywords:
distribution infrastructure;
preemptive data;
data distribution;
analysis ... See more keywords
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Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2946484
Abstract: The current data distribution method of vehicular network cannot satisfy the strict spatiotemporal constraints on the transmission of massive service data. Neither can the 5th generation mobile network (5G) meet the massive data demand of…
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Keywords:
vehicular network;
data distribution;
network;
distribution method ... See more keywords
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Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3222715
Abstract: Deep Learning based Intrusion Detection Systems (IDSs) have received significant attention from the research community for their capability to handle modern-day security systems in large-scale networks. Despite their considerable improvement in performance over machine learning-based…
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Keywords:
intrusion detection;
continual learning;
learning models;
learning ... See more keywords
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Published in 2023 at "IEEE Transactions on Computers"
DOI: 10.1109/tc.2022.3223302
Abstract: The exponential growth of data in many science and engineering domains poses significant challenges to storage systems. Data distribution is a critical component in large-scale distributed storage systems and plays a vital role in placing…
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Keywords:
systems data;
heterogeneous storage;
storage systems;
data distribution ... See more keywords
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Published in 2020 at "IEEE Transactions on Cybernetics"
DOI: 10.1109/tcyb.2018.2869476
Abstract: In this paper, a robust online multilabel learning method dealing with dynamically changing multilabel data streams is proposed. The proposed method has three advantages: 1) higher accuracy due to a newly defined objective function based…
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Keywords:
multilabel;
robust online;
online multilabel;
data distribution ... See more keywords
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Published in 2019 at "IEEE Transactions on Fuzzy Systems"
DOI: 10.1109/tfuzz.2019.2898371
Abstract: Fuzzy support vector machine (FSVM) has been combined with class imbalance learning (CIL) strategies to address the problem of classifying skewed data. However, the existing approaches hold several inherent drawbacks, causing the inaccurate prior data…
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Keywords:
data distribution;
relative density;
density;
density information ... See more keywords
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Published in 2022 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2021.3118701
Abstract: The distribution of large-size data block in the Internet of Vehicles (IoV), especially in the urban IoV with dense vehicles, is still a challenge issue. Though the methods based on 5G-cellular network commonly can efficiently…
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Keywords:
network;
large size;
size data;
data distribution ... See more keywords
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Published in 2017 at "IEEE Transactions on Mobile Computing"
DOI: 10.1109/tmc.2017.2687931
Abstract: Though the electronic technologies have undergone fast developments in recent years, mobile devices such as smartphones are still comparatively weak in contrast to desktops in terms of computational capability, storage, etc., and are not able…
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Keywords:
cloud computing;
data distribution;
secure;
mobile cloud ... See more keywords
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Published in 2023 at "IEEE Transactions on Network Science and Engineering"
DOI: 10.1109/tnse.2022.3185672
Abstract: Recently academia and industry has growing interest in the sixth generation network, which aims to support a rich range of applications with higher capacity and greater coverage than existing 5G connections. One of such promising…
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Keywords:
data distribution;
federated learning;
decentralised federated;
energy efficient ... See more keywords
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Published in 2022 at "IEEE Transactions on Pattern Analysis and Machine Intelligence"
DOI: 10.1109/tpami.2022.3166894
Abstract: Graph-based semi-supervised learning methods have been used in a wide range of real-world applications, e.g., from social relationship mining to multimedia classification and retrieval. However, existing methods are limited along with high computational complexity or…
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Keywords:
scale data;
graph;
data distribution;
distribution ... See more keywords
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Published in 2021 at "IEEE Transactions on Parallel and Distributed Systems"
DOI: 10.1109/tpds.2020.3010521
Abstract: Edge computing, as an extension of cloud computing, distributes computing and storage resources from centralized cloud to distributed edge servers, to power a variety of applications demanding low latency, e.g., IoT services, virtual reality, real-time…
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Keywords:
mml;
math;
app;
data distribution ... See more keywords