<i>hi</i>PRS algorithm process flow. حسب Michela C. Massi (14599915)

Hierarchical clustering to infer a binary tree with <i>K</i> = 4 sampled populations. حسب Tristan Mary-Huard (3864)

The detected blocks. حسب Xin Li (51274)

Symmetry test result. حسب Jiyong Moon (16819302)

Bayesian Spatial Binary Regression for Label Fusion in Structural Neuroimaging حسب D. Andrew Brown (6584837)

Application of ABC SMC to the fitting of the binary flip with cusp model. حسب Elena Camacho-Aguilar (10906327)

Parameter settings. حسب Yang Cao (53545)

"…Finally, the paper incorporates the sampling concept of elite individuals from the Estimation of Distribution Algorithm (EDA) to regenerate new solutions through the selection process in DE. …"

Thesis-RAMIS-Figs_Slides حسب Felipe Santibañez-Leal (10967991)

"…<br><br>Finally, although the developed concepts, ideas and algorithms have been developed for inverse problems in geostatistics, the results are applicable to a wide range of disciplines where similar sampling problems need to be faced, included but not limited to design of communication networks, optimal integration and communication of swarms of robots and drones, remote sensing.…"

Fig 12 - حسب Nisha Yadav (366131)

Supportive boundary lines and related results. حسب Xin Li (51274)

MCLP_quantum_annealer_V0.5 حسب Anonymous Anonymous (4854526)

"…This paper presents a quantum computing path for Transformation-to-Sampling-to-Verification of geospatial optimization problems, adaptable to the controlled qubit scale and coherence constraints under current NISQ conditions. …"

Processed dataset to train and test the WGAN-GP_IMOA_DA_Ensemble model حسب Ramya Chinnasamy (21633527)

Image_1_Validation of miRNA signatures for ovarian cancer earlier detection in the pre-diagnosis setting using machine learning approaches.pdf حسب Konrad Stawiski (4753380)

"…We employed the extreme gradient boosting (XGBoost) algorithm to train a binary classification model using 70% of the available data, while the model was tested on the remaining 30% of the dataset.…"

Supplementary Material 8 حسب Nishitha R Kumar (19750617)

"…</li><li><b>Adaboost: </b>A boosting algorithm that combines weak classifiers iteratively, refining predictions and improving the identification of antimicrobial resistance patterns.…"

DataSheet_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx حسب Massaine Bandeira e Sousa (7866242)

"…The accuracy of the optimal scenario for classifying samples with a cooking time of 30 minutes reached RCal2  = 0.86 and RVal2 = 0.84, with a Kappa value of 0.53. …"

Table_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx حسب Massaine Bandeira e Sousa (7866242)

"…The accuracy of the optimal scenario for classifying samples with a cooking time of 30 minutes reached RCal2  = 0.86 and RVal2 = 0.84, with a Kappa value of 0.53. …"