Results 91 to 100 of about 212,881 (293)
Advanced Materials, EarlyView.Magnetic tunnel junctions (MTJs) using MgO tunnel barriers face challenges of high resistance‐area product and low tunnel magnetoresistance (TMR). To discover alternative materials, Literature Enhanced Ab initio Discovery (LEAD) is developed. The LEAD‐predicted materials are theoretically evaluated, showing that MTJs with dusting of ScN or TiN on ...
Sabiq Islam +6 more
wiley +1 more source
A Combinatorial Approach to Hyperparameter Optimization
2024 IEEE/ACM 3rd International Conference on AI Engineering – Software Engineering for AI (CAIN)In machine learning, hyperparameter optimization (HPO) is essential for effective model training and significantly impacts model performance. Hyperparameters are predefined model settings which fine-tune the model’s behavior and are critical to modeling ...
Krishna Khadka +4 more
semanticscholar +1 more source
Comprehensive Performance Assessment of Multi-Neural Ensemble Model for Mortality Prediction in ICU
IEEE AccessThe development of models to estimate the mortality rate of critically ill patients in the intensive care unit(ICU) is significantly enhanced by technologies based on artificial intelligence.
M. Fathima Begum, Subhashini Narayan
doaj +1 more source
Advanced Materials Interfaces, EarlyView.SAA significantly enhanced Al/PU bonding, increasing SLSS by up to 920% and fracture energy by 15 100% through optimized micro‐nano porous surfaces. RSM identified the optimal anodizing conditions, while ML confirmed sulfuric acid concentration and roughness as dominant predictors of strength.
Umut Bakhbergen +6 more
wiley +1 more source
Revista de TeledetecciónThe development of efficient classifiers for land cover remains challenging due to the presence of hyperparameters in the model. Conventional approaches rely on manual tuning, which is both time-consuming and impractical, often leading to suboptimal ...
Abdelhak El Kharki +6 more
doaj +1 more source
Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets
, 2017 Bayesian optimization has become a successful tool for hyperparameter optimization of machine learning algorithms, such as support vector machines or deep neural networks.
Bartels, Simon +4 more
core
Advanced Materials Technologies, EarlyView.This study explores how machine learning models, trained on small experimental datasets obtained via Phase Doppler Anemometry (PDA), can accurately predict droplet size (D32) in ultrasonic spray coating (USSC). By capturing the influence of ink complexity (solvent, polymer, nanoparticles), power, and flow rate, the model enables precise droplet control
Pieter Verding +5 more
wiley +1 more source
Reducing Personalization Time and Energy Cost While Walking Outdoors with a Portable Exosuit
Advanced Robotics Research, EarlyView.Rapid Real‐World Optimization! An AF‐based human‐in‐the‐loop optimization strategy rapidly personalizes a portable hip extension exosuit for incline walking. Real‐time Bayesian optimization of assistive force significantly reduces metabolic energy—up to 16.2%—while converging in just 3 min 24 s.
Kimoon Nam +7 more
wiley +1 more source
Liquid Metal Sensors for Soft Robots
Advanced Robotics Research, EarlyView.This review thoroughly reviews liquid metal sensors in soft robots. Their unique material properties like high conductivity and good biocompatibility are analyzed. Working principles are classified, and applications in environmental perception, motion detection, and human—robot interaction are introduced.
Qi Zhang +7 more
wiley +1 more source
IEEE AccessAlzheimer’s disease is a neurodegenerative disorder prevalent in older adults, and early diagnosis is crucial for effective treatment. A deep learning model can automatically classify Alzheimer’s disease from magnetic resonance imaging to ...
Mahir Kaya, Yasemin Cetin-Kaya
doaj +1 more source