Browsing by Author "Huang Z"

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    An in-depth survey on Deep Learning-based Motor Imagery Electroencephalogram (EEG) classification
    (Elsevier BV, Netherlands, 2024-01) Wang X; Liesaputra V; Liu Z; Wang Y; Huang Z
    Electroencephalogram (EEG)-based Brain–Computer Interfaces (BCIs) build a communication path between human brain and external devices. Among EEG-based BCI paradigms, the most commonly used one is motor imagery (MI). As a hot research topic, MI EEG-based BCI has largely contributed to medical fields and smart home industry. However, because of the low signal-to-noise ratio (SNR) and the non-stationary characteristic of EEG data, it is difficult to correctly classify different types of MI-EEG signals. Recently, the advances in Deep Learning (DL) significantly facilitate the development of MI EEG-based BCIs. In this paper, we provide a systematic survey of DL-based MI-EEG classification methods. Specifically, we first comprehensively discuss several important aspects of DL-based MI-EEG classification, covering input formulations, network architectures, public datasets, etc. Then, we summarize problems in model performance comparison and give guidelines to future studies for fair performance comparison. Next, we fairly evaluate the representative DL-based models using source code released by the authors and meticulously analyse the evaluation results. By performing ablation study on the network architecture, we found that (1) effective feature fusion is indispensable for multi-stream CNN-based models. (2) LSTM should be combined with spatial feature extraction techniques to obtain good classification performance. (3) the use of dropout contributes little to improving the model performance, and that (4) adding fully connected layers to the models significantly increases their parameters but it might not improve their performance. Finally, we raise several open issues in MI-EEG classification and provide possible future research directions.
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    Biochar and soil properties limit the phytoavailability of lead and cadmium by Brassica chinensis L. in contaminated soils
    (Springer Nature on behalf of the Shenyang Agricultural University, 2022-12) Houssou AA; Jeyakumar P; Niazi NK; Van Zwieten L; Li X; Huang L; Wei L; Zheng X; Huang Q; Huang Y; Huang X; Wang H; Liu Z; Huang Z
    The current study investigated the effect of biochars derived from cinnamomum woodchip, garden waste and mulberry woodchip on soil phytoavailable lead (Pb), cadmium (Cd) pools, and their uptake by Chinese cabbage (Brassica chinensis L.). The biochars were produced at 450 °C of pyrolysis temperature. The contaminated soils were collected from Yunfu (classified as Udept), Jiyuan (Ustalf) and Shaoguan (Udult) cities in China at the depth of 0–20 cm and amended with biochars at the rate of 3% w/w. After mixing the soil with biochar for 14 days, the Chinese cabbage was planted in the amended soils. Then, it was harvested on the 48th day after sowing period. In Udult soil, Chinese cabbage died 18 days after sowing period in control and soils amended with cinnamomum and mulberry biochars. Although only plants grown with the garden waste biochar treatment survived in Udult soil, amendment of garden waste or mulberry biochars at 3% w/w (450 °C) to Udult soil significantly increased (4.95–6.25) soil pH compared to other biochar treatments. In Udept and Ustalf soils, the application of garden waste and mulberry biochars significantly improved plant biomass compared to control, albeit it was dependent on both biochar and soil properties. Garden waste biochar significantly decreased soil Cd phytoavailable concentration by 26% in the Udult soil, while a decrease of soil Cd phytoavailable concentration by 16% and 9% was observed in Ustalf and Udept soils, respectively. The available phosphorus in biochar and soil pH were important factors controlling toxic metal phytouptake by the plant. Thus, the amendment of soil with biochar at 3% can effectively reduce the mobility of Cd and Pb in soil and plant uptake. However, biochar and soil properties should be well-known before being used for soil toxic metal immobilization.