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)

"…The methodology incorporates key features of the symmetric eNRTL-SAC model structure to reduce the number of parameters and uses a hybrid of global search algorithms for parameter estimation. …"

MCLP_quantum_annealer_V0.5 حسب Anonymous Anonymous (4854526)

"…These problems often involve inequality-constrained discrete optimization, such as the maximum coverage location problem. …"

Spontaneous ERG-based random forest model discriminates control and disease cases in rodent models of obesity and type 1 diabetes and predicts disease evolution in the type 1 diabe... حسب Ramsés Noguez Imm (6658637)

Image2_Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing.TIF حسب Sizhuo Yu (11429743)

Generalized Tensor Decomposition With Features on Multiple Modes حسب Jiaxin Hu (1327875)

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

"…<br><br>Although the presented work was focused on 2-D binary channelized structures (geological facies), the applied principles are general and it can be extended to the characterization and recovery of other geological signals with spatial structure in under sampling contexts. …"

Flowchart of software workflow. حسب Gavrielle R. Untracht (11820311)

Active Learning Accelerated Discovery of Stable Iridium Oxide Polymorphs for the Oxygen Evolution Reaction حسب Raul A. Flores (2910539)

"…Subsequent Pourbaix Ir–H₂O analysis shows that α-IrO₃ is the globally stable solid phase under acidic OER conditions and supersedes the stability of rutile IrO₂. …"

GSE96058 information. حسب Sepideh Zununi Vahed (9861298)

"…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …"

The performance of classifiers. حسب Sepideh Zununi Vahed (9861298)

"…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …"