Details underlying our iterative forward sampling algorithm using MCTS. by Gwangho Lee (11027565)

“…<p>The process (third iteration in terms of total <i>N</i>) illustrates the internal process of our sampling algorithm. …”

Representative sample paths starting from the same initial state (<i>q</i>₀, <i>p</i>₀) = (0.26, 0.665) (magenta dot) and the same initial budget . by MingYi Wang (2807581)

GA-XGBoost optimization process diagram. by Ke Peng (2220973)

“…The results show that: (1) The applied SMOTEENN is more effective than SMOTE and ADASYN in dealing with the imbalance of banking data. (2) The F1 and AUC values of the model improved and optimized by XGBoost using genetic algorithm can reach 90% and 99%, respectively, which are optimal compared to other six machine learning models. …”

Bootstrap results for Case 1. by Muhammad Hamza (798822)

“…Regression models, on one side, optimize the prediction of the study variable’s non-sampled values while the classification algorithms, on the other side, look for the classification of non-sampled cases into different strata. …”

Flow diagram of DGCART. by Muhammad Hamza (798822)

“…Regression models, on one side, optimize the prediction of the study variable’s non-sampled values while the classification algorithms, on the other side, look for the classification of non-sampled cases into different strata. …”

Bootstrap results Case 2. by Muhammad Hamza (798822)

“…Regression models, on one side, optimize the prediction of the study variable’s non-sampled values while the classification algorithms, on the other side, look for the classification of non-sampled cases into different strata. …”

DataSheet1_Automatic in situ sensor based on K2S2O8 oxidation method for total phosphorus detection in marine water.docx by Yanmin Zhang (391964)

Performance of models by different algorithms. by Yong Zhang (5893)

datasheet1_Graph Neural Networks for Maximum Constraint Satisfaction.pdf by Jan Tönshoff (10192709)

Methodological steps. by Luan Carlos de Sena Monteiro Ozelim (16914117)

“…A study case is carried out to demonstrate the applicability of the new methodology. Overall, a total of 124 models were trained using a specific dataset: 40 Machine Learning models and 84 Polynomial Chaos Expansion models (which considered 3 types of base random variables, 7 least square algorithms for fitting the up to fourth order expansion’s coefficients). …”

Heatmap of weights. by Luan Carlos de Sena Monteiro Ozelim (16914117)

“…A study case is carried out to demonstrate the applicability of the new methodology. Overall, a total of 124 models were trained using a specific dataset: 40 Machine Learning models and 84 Polynomial Chaos Expansion models (which considered 3 types of base random variables, 7 least square algorithms for fitting the up to fourth order expansion’s coefficients). …”

Five types of Beta functions considered. by Luan Carlos de Sena Monteiro Ozelim (16914117)

“…A study case is carried out to demonstrate the applicability of the new methodology. Overall, a total of 124 models were trained using a specific dataset: 40 Machine Learning models and 84 Polynomial Chaos Expansion models (which considered 3 types of base random variables, 7 least square algorithms for fitting the up to fourth order expansion’s coefficients). …”

Dimensional variables of I-beam [87]. by Luan Carlos de Sena Monteiro Ozelim (16914117)

“…A study case is carried out to demonstrate the applicability of the new methodology. Overall, a total of 124 models were trained using a specific dataset: 40 Machine Learning models and 84 Polynomial Chaos Expansion models (which considered 3 types of base random variables, 7 least square algorithms for fitting the up to fourth order expansion’s coefficients). …”

Data Sheet 1_AutoRA: an innovative algorithm for automatic delineation of reference areas in support of smart soil sampling and digital soil twins.pdf by Hugo Rodrigues (5954366)

“…In this study, we introduce the autoRA algorithm, an innovative automated soil sampling design method that utilizes Gower’s Dissimilarity Index to delineate RAs automatically. …”

Performance comparison of neural UCB strategies based on the basal ganglia model against other UCB algorithms in different bandit tasks. by Yuhao Wang (196321)

An overview of the experimental paradigm. by Nienke E. R. van Bueren (11414330)

Triplet Matching for Estimating Causal Effects With Three Treatment Arms: A Comparative Study of Mortality by Trauma Center Level by Giovanni Nattino (561797)

“…Our algorithm outperforms the nearest neighbor algorithm and is shown to produce matched samples with total distance no larger than twice the optimal distance. …”

Table_1_Decision-tree-based ion-specific dosing algorithm for enhancing closed hydroponic efficiency and reducing carbon emissions.docx by Woo-Jae Cho (17661486)

“…In this study, a decision-tree-based dosing algorithm was developed to calculate the optimal volumes of individual nutrient stock solutions to be supplied for five major nutrient ions, i.e., NO₃, K, Ca, P, and Mg, based on the concentrations of NO₃, K, and Ca and remaining volume of the recycled nutrient solution. …”

Minimizing the Optical Illusion of Nanoparticles in Single Cells Using Four-Dimensional Cuboid Multiangle Illumination-Based Light-Sheet Super-Resolution Imaging by Yingying Cao (4777638)

“…Additionally, a 4D multiangle illumination-based algorithm was created to select the optimal illumination angle by combining three-dimensional super-resolution imaging with multiangle observation, even in the presence of obstacles. …”

Minimizing the Optical Illusion of Nanoparticles in Single Cells Using Four-Dimensional Cuboid Multiangle Illumination-Based Light-Sheet Super-Resolution Imaging by Yingying Cao (4777638)

“…Additionally, a 4D multiangle illumination-based algorithm was created to select the optimal illumination angle by combining three-dimensional super-resolution imaging with multiangle observation, even in the presence of obstacles. …”