Results 241 to 250 of about 9,437,008 (290)

An Intelligent Microfluidics Enabled by Data‐Driven Deep Learning‐Based Microrobot‐Assisted Flow Manipulation

Advanced Intelligent Systems, EarlyView.
An AI‐enabled micromixing framework is developed by integrating cGAN with Bayesian optimization for predictive control of microrobot‐driven flow manipulation. Through this framework, the spatiotemporal evolution of micromixing is learned directly from experimental images, while rapid identification of optimized microrobot actuation strategies is ...
Dineshkumar Loganathan, Chia‐Yuan Chen
wiley   +1 more source

Using Digital Phenotyping for Depression Screening in Community-Dwelling Older Adults: Bayesian Multilevel Hurdle Model Machine Learning Approach. [PDF]

JMIR AI
Chung MK, Lim HS, Lee SY, Baek HS, Lee J, Lee KJ, Shin T, Kim MH, Hwang S, Urtnasan E, Park JY, Kwon DH, Lee JK.   +12 more
europepmc   +1 more source

A Generalizable Framework for Building Executable Domain‐Specific Large Language Models Under Data Scarcity: Demonstration on Semiconductor Technology Computer‐Aided Design Simulation

Advanced Intelligent Systems, EarlyView.
A schema‐first alignment framework builds compact, executable domain‐specific language models under data scarcity. Large‐scale synthetic question‐answer generation instills domain knowledge, and a code‐centric IR‐to‐DPO pipeline aligns generation with tool‐executable syntax.
Di Wang, Zhenhua Wu, Yu Liu, Kai Chang, Shaohua Wu   +4 more
wiley   +1 more source

A Variational Bayesian Constrained EKF for Sonar-Based Underwater Target Tracking in Shallow Water. [PDF]

Sensors (Basel)
Zhou H, Ding Y, Gao H, Wang G, Ge T, Zhang Y.   +5 more
europepmc   +1 more source

Cross‐Sectoral AI Integration Is Essential to Tackling Food Waste and Food Insecurity: A Roadmap for Developing Resilient Food Systems

Advanced Intelligent Systems, EarlyView.
As food insecurity and global food demands surge, artificial intelligence (AI)‐based technologies offer promising opportunities to reduce food loss and waste. In this perspective, current AI adoption across the food supply chain is assessed using various academic, industry, and policy sources.
Akansha Prasad, Hannah Mann, Lubna Najm, Shadman Khan, Carlos D. M. Filipe, Tohid F. Didar   +5 more
wiley   +1 more source

A Novel Unsupervised Learning Model with Bayesian Hyperparameter Optimization for Predicting Substrates of Promiscuous Enzymes. [PDF]

ACS Omega
Gao R, Duan C, Qin N, Liu Y, Liu K, Tsuboi T, Chen Z.   +6 more
europepmc   +1 more source

Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy

Advanced Intelligent Systems, EarlyView.
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne, Haodong Yao, Liyuan Wu, Yihe Pang, Fazhi Qi, Lina Zhao   +5 more
wiley   +1 more source

Machine Learning and Deep Learning for Earthquake Monitoring: A Systematic Review of Distributed Acoustic Sensing Applications. [PDF]

Sensors (Basel)
Iqbal N, Aziz IBA, Hakimi HSB, Raza MF, Rashid A.   +4 more
europepmc   +1 more source

Engineering Intelligent iPSC Biomanufacturing: Integrating Robotic Automation, AI, and Process Control

Advanced Intelligent Systems, EarlyView.
This review highlights recent advances in automated iPSC culture systems integrating robotics, advanced imaging, artificial intelligence, and process control. These technologies improve reproducibility, scalability, and quality in cell expansion, differentiation, and real‐time monitoring, while emerging AI‐enabled and closed‐loop approaches offer new ...
Hyoryong Lee, Roma Desai, Byunggik Kim, Deok‐Ho Kim   +3 more
wiley   +1 more source

Dictionary Learning Methods for Brain Activity Mapping with MEG Data. [PDF]

Brain Topogr
Calvetti D, Somersalo E.
europepmc   +1 more source