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Ming Jin

Researcher at Virginia Tech

Publications -  73
Citations -  2200

Ming Jin is an academic researcher from Virginia Tech. The author has contributed to research in topics: Computer science & Robustness (computer science). The author has an hindex of 22, co-authored 67 publications receiving 1455 citations. Previous affiliations of Ming Jin include University of California, Berkeley & Lawrence Berkeley National Laboratory.

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Personal thermal comfort models with wearable sensors

TL;DR: It is suggested that Cohen's kappa or AUC should be employed to assess the performance of personal thermal comfort models for imbalanced datasets due to the capacity to exclude random success.
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Microgrid to enable optimal distributed energy retail and end-user demand response

TL;DR: In this article, the authors investigated the pricing and operation strategy with demand response (DR) for a MG retailer in an integrated energy system (IES), based on co-optimizing retail rates and MG dispatch formulated as a mixed integer quadratic programming (MIQP) problem, devises a dynamic pricing scheme that reflects the cost of generation and promotes DR, in tandem with an optimal dispatch plan that exploits spark spread and facilitates the integration of renewables.
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WinIPS: WiFi-Based Non-Intrusive Indoor Positioning System With Online Radio Map Construction and Adaptation

TL;DR: WinIPS is proposed, a WiFi-based non-intrusive IPS that enables automatic online radio map construction and adaptation, aiming for calibration-free indoor localization.
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MOD-DR: Microgrid optimal dispatch with demand response

TL;DR: In this article, the authors developed a microgrid optimal dispatch with demand response (MOD-DR), which fills in the gap by coordinating both the demand and supply sides in a renewable-integrated, storage-augmented, DR-enabled MG to achieve economically viable and system-wide resilient solutions.
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Automated mobile sensing: Towards high-granularity agile indoor environmental quality monitoring

TL;DR: In this paper, an automated mobile sensing system that dispatches a sensor-rich navigation-capable robot to actively survey the indoor space is proposed to enable high-granularity indoor environmental quality monitoring with agile adaptation to the dynamic indoor environment.