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Your search keyword '"Guo, Lianbo"' showing total 469 results
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469 results on '"Guo, Lianbo"'

30. Laser-Induced Breakdown Spectroscopy–Visible and Near-Infrared Spectroscopy Fusion Based on Deep Learning Network for Identification of Adulterated Polygonati Rhizoma.

Author

Chen, Feng, Zhang, Mengsheng, Huang, Weihua, Sattar, Harse, and Guo, Lianbo

Subjects
MACHINE learning, OPTICAL spectroscopy, NEAR infrared spectroscopy, FOOD safety, PRICES, ADULTERATIONS, DEEP learning
Abstract

The geographical origin of foods greatly influences their quality and price, leading to adulteration between high-priced and low-priced regions in the market. The rapid detection of such adulteration is crucial for food safety and fair competition. To detect the adulteration of Polygonati Rhizoma from different regions, we proposed LIBS-VNIR fusion based on the deep learning network (LVDLNet), which combines laser-induced breakdown spectroscopy (LIBS) containing element information with visible and near-infrared spectroscopy (VNIR) containing molecular information. The LVDLNet model achieved accuracy of 98.75%, macro-F measure of 98.50%, macro-precision of 98.78%, and macro-recall of 98.75%. The model, which increased these metrics from about 87% for LIBS and about 93% for VNIR to more than 98%, significantly improved the identification ability. Furthermore, tests on different adulterated source samples confirmed the model's robustness, with all metrics improving from about 87% for LIBS and 86% for VNIR to above 96%. Compared to conventional machine learning algorithms, LVDLNet also demonstrated its superior performance. The results indicated that the LVDLNet model can effectively integrate element information and molecular information to identify the adulterated Polygonati Rhizoma. This work shows that the scheme is a potent tool for food identification applications. [ABSTRACT FROM AUTHOR]

Published
2024
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48. Best impedance matching seeking of single-frequency capacitively coupled plasmas by numerical simulations.

Author

Yu, Shimin, Chen, Zili, Wu, Hao, Guo, Lianbo, Wang, Zhijiang, Jiang, Wei, and Zhang, Ya

Subjects
IMPEDANCE matching, COMPUTER simulation, REFLECTANCE, POLITICAL succession, ELECTRIC inductance
Abstract

Impedance matching can maximize the absorbed power transferred to the plasma load and minimize the reflected power, making it critical and indispensable for capacitively coupled plasmas (CCPs). The external circuit usually interacts with the plasma nonlinearly, so the global simulation of the external circuit and plasma and the matching design is very challenging. In this work, an a priori model was proposed to match the plasma impedance and the external circuit impedance for single-frequency CCPs. By calculating the plasma impedance and the matching network, the matching parameters were iteratively updated to find the best matching parameters. By adjusting the capacitance and the inductance of the circuit by numerical simulations, the reflection coefficient can be significantly reduced. At the same time, the plasma power absorption efficiency will be significantly improved. The universality of the method was demonstrated by choosing different initial circuit, discharge, and plasma parameters. The proposed method provides an effective matching design reference for CCPs. [ABSTRACT FROM AUTHOR]

Published
2022
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