Results 141 to 150 of about 442,254 (313)

High-dynamic-range 3D measurement for E-beam fusion additive manufacturing based on SVM intelligent fringe projection system [PDF]

, 2021
Yue Liu, Liam Blunt, Feng Gao, Xiangqian Jiang   +3 more
openalex   +1 more source

A Machine Learning Perspective on the Brønsted–Evans–Polanyi Relation in Water‐Gas Shift Catalysis on MXenes

Advanced Intelligent Discovery, EarlyView.
Machine learning predicts activation energies for key steps in the water‐gas shift reaction on 92 MXenes. Random Forest is identified as the most accurate model. Reaction energy and reactant LogP emerge as key descriptors. The approach provides a predictive framework for catalyst design, grounded in density functional theory data and validated through ...
Kais Iben Nassar, Tiago L. P. Galvão, José D. Gouveia, José R. B. Gomes   +3 more
wiley   +1 more source

Symbolic computing of LS-SVM based models

, 2011
Siamak Mehrkanoon, Li Jiang, Carlos Alzate   +2 more
openalex   +1 more source

SVM-OD: SVM Method to Detect Outliers1 [PDF]

, 2005
Jiaqi Wang, Chengqi Zhang, Xindong Wu, Hongwei Qi, Jue Wang   +4 more
openaire   +1 more source

Piezoelectric Origami Metamaterials for Enhanced Handwriting Recognition and Trajectory Tracking

Advanced Intelligent Discovery, EarlyView.
This study introduces origami metamaterials inspired by Kresling piezoelectric generators to enhance biometric authentication and handwriting trajectory recognition. Overcoming sensor limitations in conventional devices, the design enables multichannel data acquisition with fewer sensors, utilizing machine learning to accurately identify content ...
Yinzhi Jin, Ting Tan, Zhimiao Yan
wiley   +1 more source

Perbandingan Algoritma Naïve Bayes dan Algoritma Support Vector Machine (SVM) Untuk Melihat Potensi Kepatuhan Peserta BPJS Dalam Membayar Tagihan [PDF]

Rika Lestari, Raissa Amanda Putri
openalex   +1 more source

Sparse Representation and SVM Diagnosis Method for Inter-Turn Short-Circuit Fault in PMSM [PDF]

, 2019
Siyuan Liang, Yong Chen, Hong Liang, Xu Li   +3 more
openalex   +1 more source

Macrophage Phenotype Detection Methodology on Textured Surfaces via Nuclear Morphology Using Machine Learning

Advanced Intelligent Discovery, EarlyView.
A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi, Kateryna Andriienkova, Tetyana Goldanova, Ezgi Antmen, Thibaut Soubrie, Nihal Engin Vrana   +5 more
wiley   +1 more source

Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

Advanced Intelligent Discovery, EarlyView.
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia, Giovanna Pappalardo, Aldo R. Boccaccini, Liliana Liverani   +3 more
wiley   +1 more source

Artificial Intelligence for Bone: Theory, Methods, and Applications

Advanced Intelligent Discovery, EarlyView.
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan, Haicang Zhang, Liping Tong, Di Chen   +3 more
wiley   +1 more source