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Xiaodao Chen
Researcher at China University of Geosciences (Wuhan)
Publications - 47
Citations - 1102
Xiaodao Chen is an academic researcher from China University of Geosciences (Wuhan). The author has contributed to research in topics: Scheduling (computing) & Very-large-scale integration. The author has an hindex of 12, co-authored 43 publications receiving 803 citations. Previous affiliations of Xiaodao Chen include Michigan Technological University.
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Uncertainty-Aware Household Appliance Scheduling Considering Dynamic Electricity Pricing in Smart Home
TL;DR: A new demand side management technique, namely, a new energy efficient scheduling algorithm, is proposed to arrange the household appliances for operation such that the monetary expense of a customer is minimized based on the time-varying pricing model.
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A time-series classification approach based on change detection for rapid land cover mapping
TL;DR: A Time-Series Classification approach based on Change Detection (TSCCD) for rapid LULC mapping that uses the Prophet algorithm to detect the ground-cover change-points and perform time-series segmentation in a time dimension and the DTW algorithm to classify the sub-time series.
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Thermal-aware correlated two-level scheduling of real-time tasks with reduced processor energy on heterogeneous MPSoCs
Junlong Zhou,Junlong Zhou,Jianming Yan,Kun Cao,Yanchao Tan,Tongquan Wei,Mingsong Chen,Gongxuan Zhang,Xiaodao Chen,Shiyan Hu +9 more
TL;DR: A two-level thermal-aware energy-efficient scheduling algorithm for real-time tasks on DVFS-enabled heterogeneous MPSoC systems is developed considering the constraints of task deadlines, task precedences, and chip peak temperature limit.
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A Multi-Order Distributed HOSVD with Its Incremental Computing for Big Services in Cyber-Physical-Social Systems
Xiaokang Wang,Laurence T. Yang,Xingyu Chen,Lizhe Wang,Rajiv Ranjan,Xiaodao Chen,M. Jamal Deen +6 more
TL;DR: The proposed MDHOSVD method speeds up data processing, scales with data volume, improves the adaptability and extensibility over data diversity and converts low-level data into actionable knowledge.
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A Dynamic Programming Algorithm for Leveraging Probabilistic Detection of Energy Theft in Smart Home
TL;DR: A new dynamic programming algorithm is proposed that inserts the minimum number of FRTUs satisfying the detection rate constraint and can perform FRTU insertion for a large scale power system.