Results 101 to 110 of about 36,835 (256)

Machine Learning‐Assisted KCl‐CaCl2‐LiCl Electrolyte Design for Low‐Temperature, High‐Performance Calcium‐Based Liquid Metal Batteries

Advanced Science, EarlyView.
A machine learning‐assisted framework optimizes the KCl‐CaCl2‐LiCl ternary electrolyte. The optimized 13:35:52 mol% composition enables Ca‐based liquid metal batteries to operate stably at 480 °C, with >99.5% coulombic efficiency, ultralow self‐discharge, and excellent cycling stability, advancing low‐temperature large‐scale energy storage.
Xinglin Zhou, Lei Huang, Yan Zhou, Xiaohui Ning   +3 more
wiley   +1 more source

Data driven state of charge estimation for lithium ion batteries: Evaluating the influence of averaged input features using machine learning

Next Materials
For electric car batteries to operate safely and dependably, a highly accurate State of Charge (SOC) is essential. While machine learning (ML) techniques have demonstrated superior performance over traditional methods, their effectiveness heavily depends
Mohamed Abdul Basith Mydeen Pitchai
doaj   +1 more source

Circulating Amino Acid Network Remodeling Reveals Systemic Metabolic Reprogramming Predictive of Colorectal Cancer Recurrence and Metastasis

Advanced Science, EarlyView.
Blood‐based amino acid patterns measured by 19F NMR reveal hidden metabolic changes in colorectal cancer. By analyzing how these amino acids interact as a network, machine learning models identify patients at higher risk of recurrence and metastasis.
Ji‐Yeon Lee, Jumi Kim, Taehan Yoon, So Hyun Kwon, Su Chan Park, Dohyun Chun, Dohyeong Kim, Eun Jung Park, Hyunwoo Kim, Ji Min Lee   +9 more
wiley   +1 more source

A Unified Framework for Tuning Hyperparameters in Clustering Problems

Statistica Sinica
Selecting hyperparameters for unsupervised learning problems is challenging in general due to the lack of ground truth for validation. Despite the prevalence of this issue in statistics and machine learning, especially in clustering problems, there are not many methods for tuning these hyperparameters with theoretical guarantees.
Xinjie Fan, Yuguang Yue, Purnamrita Sarkar, Y. X. Rachel Wang   +3 more
openaire   +3 more sources

Congruent Learning for Self-Regulated Federated Learning in 6G

IEEE Transactions on Machine Learning in Communications and Networking
Future 6G networks are expected to be AI-native with distributed machine learning functionalities responsible for improving and automating a variety of network- and service-management tasks. To enable a privacy-preserving approach to distributed learning,
Jalil Taghia, Farnaz Moradi, Hannes Larsson, Xiaoyu Lan, Adam Orucu, Masoumeh Ebrahimi, Andreas Johnsson   +6 more
doaj   +1 more source

A Versatile‐Designable Framework for Active and Programmable Shape‐Morphing Soft Matter Systems: From Inverse Design to Closed‐Loop Control

Advanced Science, EarlyView.
A versatile framework integrates addressable electrothermal actuation and strain‐constraint mechanisms to construct programmable shape‐morphing soft matter systems. By combining an analytical inverse design strategy for high‐fidelity 3D surface reconstruction with deep learning‐based closed‐loop control, this approach enables zero‐energy shape locking,
Kai Liu, Peiling Xie, Ruitong Song, Banghan Liu, Rui Guo, Jiu‐an Lv   +5 more
wiley   +1 more source

The Implementation of Bayesian Optimization for Automatic Parameter Selection in Convolutional Neural Network for Lung Nodule Classification

Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI)
Lung cancer's high mortality rate makes early detection crucial. Machine learning techniques, especially convolutional neural networks (CNN), play a very important role in lung nodule detection.
Kadek Eka Sapta Wijaya, Gede Angga Pradipta, Dadang Hermawan   +2 more
doaj   +1 more source

Real‐Time and Non‐Invasive Detection of Respiratory Viral Infections Using an Intelligent Odor Monitoring System (IOMS)

Advanced Science, EarlyView.
An intelligent odor monitoring system integrates an IVC animal model, gas sensor array, real‐time resistance readout, and machine‐learning analysis to continuously monitor infection‐associated odor changes. The platform captures longitudinal sensor responses, distinguishes infected from healthy states, and supports early‐stage respiratory viral ...
Yajie Shen, Weifeng Yuan, Long Li, Yucheng Zheng, Kenan Liu, Hegeng Li, Hua‐Yao Li, Yongliang Zhao, Binzhou Ying, Lanpeng Guo, Wenjian Zhang, Shu‐Ming Kuo, Zirui Zhang, Yufan Deng, Bohan Yin, Zhaocheng Luo, Ke Xu, Huan Liu   +17 more
wiley   +1 more source

Optimizing Machine Learning Models for Graduation on Time Prediction: A Comparative Study with Resampling and Hyperparameter Tuning

JOIN: Jurnal Online Informatika
Timely graduation prediction is a crucial issue in higher education, especially when academic, demographic, and behavioral factors interact in complex ways.
Rizal Bakri, Syamsu Alam, Niken Probondani Astuti, Muhammad Ilham Bakhtiar   +3 more
doaj   +1 more source

Ovarian Cancer Diagnosis and Chemoresistance Prediction Model Based on cfRNA Molecular Signature

Advanced Science, EarlyView.
A deep learning model analyzes cfRNA profiles extracted from the blood of OVCA patients. This innovative approach distinguishes OVCA from healthy controls with high accuracy. Crucially, it reliably predicts patient response to chemotherapy (sensitive versus resistant subgroups).
Qinhao Guo, Yangyang Zhang, Yongcheng Jin, Siwei Deng, Yongqi Chen, Zheng Feng, Hao Wen, Liu Wang, Yilin Li, Fanghong Ou, Yong Shen, Haiming Li, Tianyao Zhou, Xingzhu Ju, Xiaohua Wu   +14 more
wiley   +1 more source