Supporting data for “The role of forest composition heterogeneity on temperate ecosystem carbon dynamic under climate change" by Ziyu Lin (9151064)

“…The process includes (1) harmonizing Landsat 5, 7, 8, and Sentinel-2 data using the HLS algorithm, and (2) filling temporal gaps with an optimized object-based STARFM fusion algorithm. …”

Data Sheet 1_Machine learning based assessment of hoarseness severity: a multi-sensor approach centered on high-speed videoendoscopy.docx by Tobias Schraut (21488108)

Data used to drive the Double Layer Carbon Model in the Qinling Mountains. by Huiwen Li (17705280)

“…It also incorporates climate change responses, adjust decomposition rates based on climate and environmental changes, and lead to robust estimates under different climatic scenarios. The simulation process of the DLCM involves initializing SOC stocks with spatially detailed baseline data, adding organic matter inputs based on vegetation production, and simulating microbial decomposition while adjusting for climate variables such as temperature and soil moisture. …”

Data Sheet 1_Durable response of primary cardiac lymphoma after autologous stem cell transplantation and sequential CAR-T therapy: a case report and literature review.pdf by Ge Wang (56838)

Proposed method approach. by Muhammad Usman Tariq (11022141)

“…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”

LSTM model performance. by Muhammad Usman Tariq (11022141)

“…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”

Descriptive statistics. by Muhammad Usman Tariq (11022141)

“…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”

CNN-LSTM Model performance. by Muhammad Usman Tariq (11022141)

“…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”

MLP Model performance. by Muhammad Usman Tariq (11022141)

“…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”

RNN Model performance. by Muhammad Usman Tariq (11022141)

“…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”

CNN Model performance. by Muhammad Usman Tariq (11022141)

“…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”

Bi-directional LSTM Model performance. by Muhammad Usman Tariq (11022141)

“…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”

Early Parkinson’s disease identification via hybrid feature selection from multi-feature subsets and optimized CatBoost with SMOTE by Subhashree Mohapatra (17387852)

“…The proposed framework leverages a strong categorical boosting (CatBoost) algorithm optimized using Grid Search Optimization (GSO). …”

Minimal Dateset. by Hongwei Yue (574068)

“…To address this issue, this paper proposes a novel hybrid algorithm—PSO-KM—that integrates Particle Swarm Optimization with K-means to improve both accuracy and computational efficiency in clustering resident profile data. …”

Loss Function Comparison. by Hongwei Yue (574068)

“…To address this issue, this paper proposes a novel hybrid algorithm—PSO-KM—that integrates Particle Swarm Optimization with K-means to improve both accuracy and computational efficiency in clustering resident profile data. …”

Comparative Results of Different Models. by Hongwei Yue (574068)

“…To address this issue, this paper proposes a novel hybrid algorithm—PSO-KM—that integrates Particle Swarm Optimization with K-means to improve both accuracy and computational efficiency in clustering resident profile data. …”

Loss Function Comparison. by Hongwei Yue (574068)

“…To address this issue, this paper proposes a novel hybrid algorithm—PSO-KM—that integrates Particle Swarm Optimization with K-means to improve both accuracy and computational efficiency in clustering resident profile data. …”

Overall Framework of the PSO-KM Model. by Hongwei Yue (574068)

“…To address this issue, this paper proposes a novel hybrid algorithm—PSO-KM—that integrates Particle Swarm Optimization with K-means to improve both accuracy and computational efficiency in clustering resident profile data. …”

Overall Framework of the PSO-KM Model. by Hongwei Yue (574068)

“…To address this issue, this paper proposes a novel hybrid algorithm—PSO-KM—that integrates Particle Swarm Optimization with K-means to improve both accuracy and computational efficiency in clustering resident profile data. …”

Data_Sheet_1_Machine Learning Prediction Model for Acute Renal Failure After Acute Aortic Syndrome Surgery.docx by Jinzhang Li (9221930)