A Novel Platform of Autonomous Vehicle in Multi-Disciplinary Industry

Nguyen, Thanh Luan; Quang, Ha Pham; Ngo, Thinh; Nguyễn, Thanh Phương; Nguyen, Hung T.

doi:10.1109/icsse.2019.8823298

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Preliminary Analysis Of Sample Data1

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“…Figure 3 shows the capacitance detection results of water and alcohol without bubbles. The capacitance values of these two liquids are close, indicating that their dielectric constant differences are not significant 11 . Figure 4 shows the capacitance detection results of bubbles of different thicknesses.…”

Section: Preliminary Analysis Of Sample Datamentioning

confidence: 87%

Algorithm Research for Bubble Detection in Capacitive Liquid Level Sensor of Fully Automated Immunoassay Analyzer

Huang,

Zhang

2023

J. Phys.: Conf. Ser.

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Fully automated immunoassay analyzers are integral to clinical testing, with liquid-level detection crucial to mitigate false measurements and cross-contamination. This study introduces a bubble detection algorithm based on the Random Forest machine learning model to address bubble detection in analyzers using capacitive sensors. The algorithm processes collected capacitance data, accurately identifying bubbles and ensuring sampling accuracy. Data preprocessing, feature extraction, and classification enable precise bubble detection. Compared to the traditional CART decision tree algorithm, this algorithm demonstrates superior bubble detection performance, indicating its significant research value and potential for liquid-level detection in fully automated immunoassay analyzers.

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Section: Preliminary Analysis Of Sample Datamentioning

confidence: 87%