Latent state estimations for experimental data with interruptions for subject 21. حسب Samiul Alam (18563323)

Latent state estimations for experimental data with interruptions for subject 5. حسب Samiul Alam (18563323)

Latent state estimations for experimental data with interruptions for subject 9. حسب Samiul Alam (18563323)

Latent state estimations for experimental data with interruptions for subject 19. حسب Samiul Alam (18563323)

Latent state estimations for experimental data with interruptions for subject 3. حسب Samiul Alam (18563323)

Latent state estimations for experimental data with interruptions for subject 2. حسب Samiul Alam (18563323)

Latent state estimations for experimental data with interruptions for subject 16. حسب Samiul Alam (18563323)

Latent state estimations for experimental data with interruptions for subject 17. حسب Samiul Alam (18563323)

Latent state estimations for experimental data with interruptions for subject 6. حسب Samiul Alam (18563323)

Latent state estimations for experimental data with interruptions for subject 8. حسب Samiul Alam (18563323)

Latent state estimations for experimental data with interruptions for subject 22. حسب Samiul Alam (18563323)

Latent state estimations for experimental data with interruptions for subject 1. حسب Samiul Alam (18563323)

Latent state estimations for experimental data with interruptions for subject 4. حسب Samiul Alam (18563323)

Latent state estimations for experimental data with interruptions for subject 10. حسب Samiul Alam (18563323)

Latent state estimations for experimental data with interruptions for subject 12. حسب Samiul Alam (18563323)

Latent state estimations for experimental data with interruptions for subject 20. حسب Samiul Alam (18563323)

Segmentation, trace denoising and spike extraction framework. حسب Changjia Cai (10647521)

Solubility Prediction of Different Forms of Pharmaceuticals in Single and Mixed Solvents Using Symmetric Electrolyte Nonrandom Two-Liquid Segment Activity Coefficient Model حسب Getachew S. Molla (6416744)

"…Because of the semipredictive nature of the symmetric eNRTL-SAC model, the segment parameter regression is a critical step for solubility prediction accuracy. A particle swarm optimization algorithm is incorporated to preregress conceptual segment parameters of solutes. …"

PathOlOgics_RBCs Python Scripts.zip حسب Ahmed Elsafty (16943883)

"…This process generated a ground-truth binary semantic segmentation mask and determined the bounding box coordinates (XYWH) for each cell. …"

Identification and quantitation of clinically relevant microbes in patient samples: Comparison of three k-mer based classifiers for speed, accuracy, and sensitivity حسب George S. Watts (7962206)

"…We tested the accuracy, sensitivity, and resource requirements of three top metagenomic taxonomic classifiers that use fast k-mer based algorithms: Centrifuge, CLARK, and KrakenUniq. Binary mixtures of bacteria showed all three reliably identified organisms down to 1% relative abundance, while only the relative abundance estimates of Centrifuge and CLARK were accurate. …"