LSTM model’s equations. حسب Songsong Wang (8088293)

"…The findings indicate that the LSTM model, when integrated with the watershed-internal KG and LLM, can effectively incorporate critical elements influencing water level changes, the accuracy of the LLM-KG-LSTM model is enhanced by 3% compared to the standard LSTM model, and the LSTM series outperforms both RNN and GRU models, Our method will guide future research from the perspective of focusing on forecasting algorithms to the perspective of focusing on the relationship between multi-dimensional disaster data and algorithm parallelism.…"

Parameter’s interpretation. حسب Songsong Wang (8088293)

"…The findings indicate that the LSTM model, when integrated with the watershed-internal KG and LLM, can effectively incorporate critical elements influencing water level changes, the accuracy of the LLM-KG-LSTM model is enhanced by 3% compared to the standard LSTM model, and the LSTM series outperforms both RNN and GRU models, Our method will guide future research from the perspective of focusing on forecasting algorithms to the perspective of focusing on the relationship between multi-dimensional disaster data and algorithm parallelism.…"

The models’ training parameters. حسب Songsong Wang (8088293)

"…The findings indicate that the LSTM model, when integrated with the watershed-internal KG and LLM, can effectively incorporate critical elements influencing water level changes, the accuracy of the LLM-KG-LSTM model is enhanced by 3% compared to the standard LSTM model, and the LSTM series outperforms both RNN and GRU models, Our method will guide future research from the perspective of focusing on forecasting algorithms to the perspective of focusing on the relationship between multi-dimensional disaster data and algorithm parallelism.…"

Association point and relationship. حسب Songsong Wang (8088293)

"…The findings indicate that the LSTM model, when integrated with the watershed-internal KG and LLM, can effectively incorporate critical elements influencing water level changes, the accuracy of the LLM-KG-LSTM model is enhanced by 3% compared to the standard LSTM model, and the LSTM series outperforms both RNN and GRU models, Our method will guide future research from the perspective of focusing on forecasting algorithms to the perspective of focusing on the relationship between multi-dimensional disaster data and algorithm parallelism.…"

Performance assessment of Cell2Spatial on real and simulated mouse brain spatial transcriptomics (ST) data. حسب Huamei Li (8815955)

Spatial characterization and cell-type-specific genes in mouse brain tissue. حسب Huamei Li (8815955)

Evaluation of spatial transcriptomics (ST) tools across various metrics and conditions. حسب Huamei Li (8815955)

BootCellNet2 gives clustering that comply more with CITE-seq results. حسب Yutaro Kumagai (481168)

Overall framework design. حسب Matthew Yit Hang Yeow (20721206)

"…Our approach uses cross-project code clone detection to establish the ground truth for software reuse, identifying code clones across popular GitHub projects as indicators of potential reuse candidates. …"

Gamma distribution of reuse. حسب Matthew Yit Hang Yeow (20721206)

"…Our approach uses cross-project code clone detection to establish the ground truth for software reuse, identifying code clones across popular GitHub projects as indicators of potential reuse candidates. …"

Top 5 correlated features based on reuse. حسب Matthew Yit Hang Yeow (20721206)

"…Our approach uses cross-project code clone detection to establish the ground truth for software reuse, identifying code clones across popular GitHub projects as indicators of potential reuse candidates. …"

Features with the top importance score. حسب Matthew Yit Hang Yeow (20721206)

"…Our approach uses cross-project code clone detection to establish the ground truth for software reuse, identifying code clones across popular GitHub projects as indicators of potential reuse candidates. …"

Heatmap of pre-post interview changes in system insights, health equity thinking, & healthy equity action. حسب Travis R. Moore (19532635)

<b>AI for imaging plant stress in invasive species </b>(dataset from the article https://doi.org/10.1093/aob/mcaf043) حسب Erola Fenollosa (20977421)

"…Machine learning regression algorithms were trained to predict betalain accumulation from digital images, outperforming classic spectroradiometer measurements. …"

S1 Graphical abstract - حسب José M. Rivera-Arbeláez (12418512)

"…The software uses a shape-detection algorithm to single out and track the movement of pillars’ tips for the most common shapes of EHT platforms. …"

The architecture of the SE-multi-input CNN model. حسب Bin Zheng (45359)

"…The fusion strategy combines feature maps via bicubic interpolation and element-wise summation to maintain spatial integrity. …"

Confusion matrix for the Multi-input CNN model. حسب Bin Zheng (45359)

"…The fusion strategy combines feature maps via bicubic interpolation and element-wise summation to maintain spatial integrity. …"

Confusion matrices for single-input CNN models. حسب Bin Zheng (45359)

"…The fusion strategy combines feature maps via bicubic interpolation and element-wise summation to maintain spatial integrity. …"

Confusion matrix for the Multi-input CNN model. حسب Bin Zheng (45359)

"…The fusion strategy combines feature maps via bicubic interpolation and element-wise summation to maintain spatial integrity. …"

Steps to the final sample. حسب Vittorio Nicoletta (21367878)

"…<div><p>One major obstacle to advancing research and treatment for major psychiatric disorders is their substantial within-diagnosis heterogeneity in patient lifetime trajectories. Adapted research methods such as cluster analysis to define subgroups of patients are currently used. …"