Publications

Journal Articles

A Classification Method for Bearing Surface Defects Based on Acoustic Emission Technology and the YOLO-V11 Algorithm

Published in International Journal of Advanced Engineering Research and Science (IJAERS), 2025

A bearing surface defect classification framework combining acoustic emission technology and YOLO-V11-based intelligent recognition.

Recommended citation: Xin-Yu Guo, Liu-Yi Yu, Yi Chen, and Yan-Zuo Chang, “A Classification Method for Bearing Surface Defects Based on Acoustic Emission Technology and the YOLO-V11 Algorithm,” International Journal of Advanced Engineering Research and Science, vol. 12, no. 12, pp. 48-53, 2025.
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A Design of Intelligent Range Hood Based on Arduino

Published in International Journal of Advanced Engineering Research and Science (IJAERS), 2024

An Arduino-based intelligent range hood system integrating gas sensing, environmental monitoring, and adaptive fan-speed control.

Recommended citation: Liu Yi Yu, Yan Zuo Chang, Lin Po Shang, Ze Feng Ling, Yi Chen, Yan Hai Li, Jian Bin Cai, and Young Shan Ou, “A Design of Intelligent Range Hood Based on Arduino,” International Journal of Advanced Engineering Research and Science, vol. 11, no. 12, pp. 90-97, 2024.
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Conference Papers

Damage Localization for Type IV Composite Pressure Vessels Based on YOLOv11 with Dynamic Convolution, EMA and AE Time-Frequency Analysis

Published in 2026 IEEE 8th International Conference on Communications, Information System and Computer Engineering (CISCE 2026), 2026

An acoustic emission damage localization framework integrating YOLOv11, dynamic convolution, EMA attention mechanisms, and time-frequency analysis.

Recommended citation: Xin-Yu Guo, Liu-Yi Yu, and Yan-Zuo Chang, “Damage Localization for Type IV Composite Pressure Vessels Based on YOLOv11 with Dynamic Convolution, EMA and AE Time-Frequency Analysis,” in Proc. IEEE CISCE 2026, Guangzhou, China, 2026.
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Face Detection Study Based on YOLOv11n Improved ViT with AKConv

Published in 2025 IEEE 7th International Conference on Communications, Information System and Computer Engineering (CISCE 2025), 2025

An improved YOLOv11n framework integrating AKConv and Vision Transformer modules for efficient multi-target face detection under complex environments.

Recommended citation: Liu-Yi Yu, Yan-Zuo Chang, Fu-Ping Guo, Lin-Po Shang, Yi Chen, Yu Liu, and Yi-Ling Pan, “Face Detection Study Based on YOLOv11n Improved ViT with AKConv,” in Proc. IEEE CISCE 2025, Guangzhou, China, 2025.
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LiuYi Yu