• Publications
  • Influence
An Improved Photovoltaic Power Forecasting Model With the Assistance of Aerosol Index Data
Due to the intermittency and randomness of solar photovoltaic (PV) power, it is difficult for system operators to dispatch PV power stations. In order to find a precise expectation for day-ahead PVExpand
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Distributionally Robust Chance-Constrained Approximate AC-OPF With Wasserstein Metric
TLDR
In the presence of VRE uncertainties, this paper discusses a distributionally robust chance constrained approximate AC-OPF formulation that minimizes the expectation of the quadratic cost function w.r.t. the worst-case probability distribution. Expand
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End-to-End Inference of Loss Nature in a Hybrid Wired/Wireless Environment
TLDR
End-to-End differentiation between wireless and conges- tion loss can equip TCP control so it operates effectively in a hybrid wired/wireless environment. Expand
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Android Malware Familial Classification and Representative Sample Selection via Frequent Subgraph Analysis
  • Ming Fan, J. Liu, +4 authors Ting Liu
  • Computer Science
  • IEEE Transactions on Information Forensics and…
  • 16 February 2018
TLDR
We propose a novel approach that constructs frequent subgraphs (fregraphs) to represent the common behaviors of malware samples that belong to the same family. Expand
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MASSETOGNATHUS (CYNODONTIA, TRAVERSODONTIDAE) FROM THE SANTA MARIA FORMATION OF BRAZIL
Based on a new examination of published specimens and some unstudied specimens from Brazil, Massetognathus ochagaviae is re-evaluated and the diagnosis revised. One distinguished character of thisExpand
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Aerosol and monsoon climate interactions over Asia
The increasing severity of droughts/floods and worsening air quality from increasing aerosols in Asia monsoon regions are the two gravest threats facing over 60% of the world population living inExpand
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Data-Driven Affinely Adjustable Distributionally Robust Unit Commitment
TLDR
We propose a data-driven affinely adjustable distributionally robust method for unit commitment considering uncertain load and renewable generation forecasting errors. Expand
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A Deep Multi-Modal CNN for Multi-Instance Multi-Label Image Classification
TLDR
We propose a deep multi-modal CNN for multi-instance multi-label image classification, called MMCNN-MIML. Expand
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DAPASA: Detecting Android Piggybacked Apps Through Sensitive Subgraph Analysis
TLDR
We propose DAPASA, an approach to detect Android piggybacked apps through sensitive subgraph analysis. Expand
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Performance Analysis of Adaptive Detectors for Point Targets in Subspace Interference and Gaussian Noise
TLDR
This paper investigates the statistical performance of three adaptive detectors in the presence of subspace interference and Gaussian noise, where the actual signal does not completely lie in the presumed signal subspace. Expand
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