Publications

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  FedQV: Leveraging Quadratic Voting in Federated Learning

  Tianyue Chu, Nikolaos Laoutaris

  ACM SIGMETRICS. Venice, Italy. June 2024

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  Securing Federated Sensitive Topic Classification against Poisoning Attacks

  Tianyue Chu, Álvaro García-Recuero, Costas Iordanou, Georgios Smaragdakis, Nikolaos Laoutaris

  Usenix Network and Distributed System Security Symposium. San Diego, California. February 2023

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  Pre-impact alarm system for fall detection using MEMS sensors and HMM-based SVM classifiercall_made

  Shengyun Liang, Tianyue Chu, Dan Lin, Yunkun Ning, Huiqi Li, Guoru Zhao.

  Accidental fall can cause physical injury, fracture and other health complications, especially for elderly people living alone. Aimed to provide timely assistance after the occurrence of falling down, a pre-fall alarm system was proposed. In order to test the reliability of the pre-fall alarm system, eighteen subjects who wore this device on the waist were required to participate in a series of experiments. The acceleration and angular velocity time series extracted from human motion processes were used to describe human motion features. HMM-based SVM classifier was used to determine the maximum separation boundary between falls and Activities of Daily Living (ADLs). The fall detection results showed 94.91% accuracy, 97.22% Sensitivity and 93.75% Specificity. The proposed device can accurately recognize fall events, achieve additional functions, and have the advantages of small size and low power consumption. Based on the findings, this pre-impact fall alarm system with a detection algorithm could potentially be useful for monitoring the state of physical function in elderly population.