Results 231 to 240 of about 333,902 (325)

Towards Decoding the Intricate Connection Between Hosting The MSEs and Advancing Digital Infrastructure and Capabilities with Machine Learning

Napitiporn Manoli, Masakazu Takahashi, Yoshiyuki Matsuura   +2 more
openalex   +1 more source

Application of Neural Networks for Advanced Ir Spectroscopy Characterization of Ceria Catalysts Surfaces

Advanced Intelligent Discovery, EarlyView.
A novel convolutional neural network architecture enables rapid, unsupervised analysis of IR spectroscopic data from DRIFTS and IRRAS. By combining synthetic data generation with parallel convolutional layers and advanced regularization, the model accurately resolves spectral features of adsorbed CO, offering real‐time insights into ceria surface ...
Mehrdad Jalali, Lachlan Caulfield, Eric Sauter, Alexei Nefedov, Chengwu Yang, Christof Wöll   +5 more
wiley   +1 more source

Accurate prediction of geometrical parameters of an ultra-broadband metamaterial absorber using machine learning. [PDF]

Sci Rep
Ahmed MR, Jyoti O, Sarkar PP, Motin MA, Habib MS, Habib MS.   +5 more
europepmc   +1 more source

Challenges and Strategies in Halal Supply Chain Management for MSEs in West Sumatra: A Participatory Action Research Study

Roni Andespa, Yurni Yurni, Aldiyanto Aldiyanto, Gus Efendi   +3 more
openalex   +2 more sources

Bayesian Optimization Guiding the Experimental Mapping of the Pareto Front of Mechanical and Flame‐Retardant Properties in Polyamide Nanocomposites

Advanced Intelligent Discovery, EarlyView.
Bayesian optimization enabled the design of PA56 system with just 8 wt% additives, achieving limiting oxygen index 30.5%, tensile strength 80.9 MPa, and UL‐94 V‐0 rating. Without prior knowledge, the algorithm uncovered synergistic effects between aluminum diethyl‐phosphinate and nanoclay.
Burcu Ozdemir, Miguel Hernández‐del‐Valle, Christina Schenk, De‐Yi Wang, Maciej Haranczyk   +4 more
wiley   +1 more source

Three-Dimensional Evaluation of Midfacial Changes After Maxillary Skeletal Expander Application: A Retrospective Study. [PDF]

Turk J Orthod
Vural F, Kaya Y, Alkan Ö.
europepmc   +1 more source

A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

Advanced Intelligent Discovery, EarlyView.
A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas, Panagiotis Krokidas, Vasileios Vavourakis, Clara Essmann, George Giannakopoulos   +4 more
wiley   +1 more source

Theoretical aspects and simulation with the application of a new two parameter distribution. [PDF]

Sci Rep
Ghouar A, Bashiru SO, Zeghdoudi H, Alshangiti AM, Bakr ME, Balogun OS, Habineza A, Hussam E, Gemeay AM.   +8 more
europepmc   +1 more source

MSE superiority of Bayes and empirical Bayes estimators in two generalized seemingly unrelated regressions

, 2007
Li‐Chun Wang, Noël Veraverbeke
openalex   +2 more sources

Taguchi–Bayesian Sampling: A Roadmap for Polymer Database Construction Toward Small Representative Machine Learning

Advanced Intelligent Discovery, EarlyView.
This article establishes a Taguchi–Bayesian sampling strategy to reconstruct polymer processing–property landscape at minimal sampling cost, generically building the roadmap for materials database construction from sampling their vast design space. This sampling strategy is featured by an alternating lesson between uniformity and representativeness ...
Han Liu, Liantang Li
wiley   +1 more source