Jiannong Cao
Hong Kong Polytechnic University
992 Papers
6.5K Citations
Jiannong Cao is an academic researcher from Hong Kong Polytechnic University. The author has contributed to research in topics: Computer science & Wireless sensor network. The author has an hindex of 58, co-authored 898 publications. Previous affiliations of Jiannong Cao include Nanjing University & Nanjing Agricultural University.
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Papers
Fast Tensor Factorization for Accurate Internet Anomaly Detection
TL;DR: TensorDet can achieve significantly lower false positive rate and higher true positive rate, and benefiting from the well designed algorithm to reduce the computation cost of tensor factorization, the tensorFactorization process in TensorDet is 5 (Abilene) and 13 (GÈANT) times faster than that of the traditional Tucker decomposition solution.
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CPS-Based Smart Warehouse for Industry 4.0: A Survey of the Underlying Technologies
TL;DR: This paper discusses how the state-of-the-art techniques in cyber-physical systems facilitate building smart warehouses to achieve the promising vision of industry 4.0 and focuses on four significant issues when applying CPS techniques in smart warehouses.
105
On-Line Anomaly Detection With High Accuracy
TL;DR: This paper directly models the monitoring data in each time slot as a 2-D matrix, and detects anomalies in the new time slot based on bilateral principal component analysis (B-PCA), the first work that exploits 2- D PCA for anomaly detection.
104
Adaptive Traffic Light Control of Multiple Intersections in WSN-Based ITS
Binbin Zhou,Jiannong Cao,Hejun Wu +2 more
- 15 May 2011
TL;DR: Simulation results demonstrate that the proposed adaptive traffic light control scheme produces much higher throughput, lower average waiting time and fewer number of stops, compared with three control approaches: the optimal fixed-time control, an actuated control and an adaptive control.
96
Accurate and Efficient Object Tracking Based on Passive RFID
TL;DR: This paper proposes a hybrid method which combines PF with Weighted Centroid Localization (WCL) to achieve high accuracy and low computational cost and evaluates the performance of the method through extensive simulations and experiments in two real world applications.
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