Results 191 to 200 of about 9,360,077 (298)

Structure-aware diffusion model for molecule generation based on K-Nearest Neighbor and equivariant graph neural network. [PDF]

Future Med Chem
Zeng X, Feng PK, Li SJ, Meng PY, Du WF, Jiang B, Yang ZZ, Li Y.   +7 more
europepmc   +1 more source

Comparative analysis of proficiencies of various textures and geometric features in breast mass classification using k-nearest neighbor. [PDF]

Vis Comput Ind Biomed Art, 2022
Singh H, Sharma V, Singh D.
europepmc   +1 more source

A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys

Advanced Engineering Materials, EarlyView.
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin, Marta Campolucci, Nicolas de Andrade Ishiki, Nathan Mirgot, Nadir Zhamantay, Frédéric Kanoufi, Jennifer Peron, Jean Charlety, Emiliano Fonda, Valérie Briois, Marco Faustini, Maria‐Letizia De Marco, Christine Goyhenex, Ovidiu Ersen, Hervé Bulou   +14 more
wiley   +1 more source

A novel intelligent photonic design method enabled by metamaterials and k-nearest neighbor. [PDF]

Nanophotonics
Fan H, Pan J, Wang Y, Yuan Z, Cheng M, Yang Q, Liu D, Deng L.   +7 more
europepmc   +1 more source

Determination of Reactivity Ratios from Binary Copolymerization Using the k-Nearest Neighbor Non-Parametric Regression. [PDF]

Polymers (Basel), 2021
Fazakas-Anca IS, Modrea A, Vlase S.
europepmc   +1 more source

Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning

Advanced Engineering Materials, EarlyView.
Machine‐learning‐based screening enables automated identification of anomalous battery cells from complementary electrochemical tests. A curated battery database supports configuration‐aware comparison of rate‐capability and impedance data. Supervised classification of rate‐test data achieves 90% accuracy, while CNN‐VAE‐based impedance analysis reaches
Minu Rose, Sanxchep Sharma, Veit Königer, Vincent Nebel, Jonas Oehm, Christian Weisenberger, Laura Bies, Volker Knoblauch   +7 more
wiley   +1 more source

Experimental and Machine Learning Modelling of Ni(II) Ion Adsorption onto Guar Gum: Artificial Neural Network (ANN) and K-Nearest Neighbor (KNN) Comparative Study. [PDF]

Polymers (Basel)
Ali IH, Alqahtani MF, Eljack ND, Eltahir SB, Ahmed MH, Elkhaleefa A.   +5 more
europepmc   +1 more source

K-Nearest Neighbor and Random Forest-Based Prediction of Putative Tyrosinase Inhibitory Peptides of Abalone Haliotis diversicolor. [PDF]

Molecules, 2021
Kongsompong S, E-Kobon T, Chumnanpuen P.
europepmc   +1 more source

Thermal Cycle–Microstructure–Property Relationships in Rail Steel Heat‐Affected Zone Simulated by Gleeble

Advanced Engineering Materials, EarlyView.
Microstructural evolution of premium rail steel during flash butt welding (FBW), comparing physically simulated heat‐affected zones with actual weld regions. Thermal cycles induce phase transformations and microstructural heterogeneity that influence weld quality and mechanical performance. These findings provide insights into optimizing FBW parameters
Emmanoelle Cintra da Cunha Araújo, João Marcos da Silva Nunes, Marcelly Cristiny Nunes de Carvalho, Alex Rojas, Cristie Luis Kugelmeier, Cristhian Ricardo Loayza Loayza, João Carlos Ferreira, Maria Veronica Goncalves Rodrigues, Rute Sayuri Kano, Isaac Araújo Furtado, Jacyara Dalylla da Silva Nunes, Jhonatan Peres de Sousa, Marcos Natan da Silva Lima, Eden Santos Silva, Gedeon Silva Reis, Samuel Filgueiras Rodrigues   +15 more
wiley   +1 more source

Underwater Single-Photon 3D Reconstruction Algorithm Based on K-Nearest Neighbor. [PDF]

Sensors (Basel)
Wang H, Qiu S, Lu T, Kuang Y, Jin W.
europepmc   +1 more source