Descriptive statistical analysis of data. حسب Xiangjuan Liu (618000)

"…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …"

The MAE value of the model under raw data. حسب Xiangjuan Liu (618000)

"…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …"

Three error values under raw data. حسب Xiangjuan Liu (618000)

"…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …"

Decomposition of time scries plot. حسب Xiangjuan Liu (618000)

"…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …"

Data Sheet 1_Global burden and trends of occupational noise-induced hearing loss (1990–2021) and projection to 2040.pdf حسب Xin Gong (592328)

"…By 2040, ONIHL DALYs are predicted to increase, whereas the ASDR is projected to decrease; however, the disease burden among females will rise significantly.…"

Mean ± SD values of unipedal stance parameters evaluated at the different time points of the postural training session. حسب Cristina Dolciotti (16317330)

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Mean ± SD of the different parameters relative to bipedal stance on soft support with the eyes open recorded in the Chewing and Hand Grip groups. حسب Cristina Dolciotti (16317330)

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Time course of Path Length, LFS and Velocity during postural training. حسب Cristina Dolciotti (16317330)

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Relation of the changes in Y Sway Amplitude and LFS induced by postural training with those in 95% Area. حسب Cristina Dolciotti (16317330)

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Training-induced changes in bipedal stance. حسب Cristina Dolciotti (16317330)

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Between-group differences in 95% Area, Y Sway Amplitude and LFS during postural training. حسب Cristina Dolciotti (16317330)

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Relation between training-related changes in unipedal and bipedal stance. حسب Cristina Dolciotti (16317330)

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Consolidation of training-induced changes in unipedal stance: 95% Area, Y Sway Amplitude and LFS. حسب Cristina Dolciotti (16317330)

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Consolidation of training-induced changes in unipedal stance: Path Length, X Sway Amplitude and Velocity. حسب Cristina Dolciotti (16317330)

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Time course of 95% Area, X and Y Amplitude Sway during postural training. حسب Cristina Dolciotti (16317330)

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Correlations between unipedal and bipedal stance parameters recorded at the beginning of the training and of the control session. حسب Cristina Dolciotti (16317330)

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Flow diagram. حسب Cristina Dolciotti (16317330)

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Ignition delay process shot by high-speed camera. حسب Lei Bai (631944)

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Data disclosure (Bai - manuscript). حسب Lei Bai (631944)

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Experimental bench and corresponding facility. حسب Lei Bai (631944)

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