Results 121 to 130 of about 44,463 (307)

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Advanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou, Lin Pang, Arunachalam Ramanathan, Libin Yang, Xianyan Chen, Yuval Golan, Xiaoming Zhai, Hongyue Sun, Kenan Song, Xianqiao Wang   +12 more
wiley   +1 more source

Quantitative color fundus photography parameters as potential biomarkers of axial length progression: evidence from a machine learning cohort study

Frontiers in Cell and Developmental Biology
PurposeEarly identification of children at risk for accelerated axial elongation is essential for implementing timely myopia control strategies. Quantitative parameters derived from color fundus photography (CFP) may capture subtle structural and ...
Zixun Wang, Feifei Han, Xiaoling Zhang, Xiaoling Zhang, Jingjie Ding, Jingtao Yu, Xueshuo Xie, Zhiqing Li, Bei Du, Ruihua Wei   +9 more
doaj   +1 more source

Interpretable Machine Learning for Solvent‐Dependent Carrier Mobility in Solution‐Processed Organic Thin Films

Advanced Intelligent Discovery, EarlyView.
This work establishes a correlation between solvent properties and the charge transport performance of solution‐processed organic thin films through interpretable machine learning. Strong dispersion interactions (δD), moderate hydrogen bonding (δH), closely matching and compatible with the solute (quadruple thiophene), and a small molar volume (MolVol)
Tianhao Tan, Lian Duan, Dong Wang
wiley   +1 more source

Forest Fire Hazard Assessment using Remote Sensing Data and Machine Learning, Case Study of Jijel, Algeria

Ekológia (Bratislava)
Climate change, particularly in vulnerable areas such as the Mediterranean hotspot, exacerbates the risk of wildfires, turning these regions into true danger zones.
Matougui Zakaria, Zouidi Mohamed
doaj   +1 more source

Explainable DDoS Detection with a CNN-LSTM Hybrid Model and SHAP Interpretation

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
The rising frequency and complexity of Distributed Denial of Service (DDoS) attacks pose a severe threat to network security. This study aims to develop an effective and interpretable DDoS detection framework using a hybrid deep learning approach.
Amali Amali, Anggi Muhammad Rifa'i, Edy Widodo, Ahmad Turmudi Zy, Dhani Ariatmanto   +4 more
doaj   +1 more source

SHAP analysis on eANN output.

A SHAP values for an examplary excitatory (E) connection (top panel) and an inhibitory (I) connection (bottom panel), ranked according to their importance.
Manuel Schröter (14378109), Guillaume Obozinski (51054), Taehoon Kim (79056), Philipp Hornauer (14378106), Andreas Hierlemann (697177), Damian Roqueiro (187645), Julian Bartram (13896582), Christian Donner (3663007)   +7 more
core   +1 more source

Deep Learning‐Assisted Design of Mechanical Metamaterials

Advanced Intelligent Discovery, EarlyView.
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong, Pu Wen, Zhiping Chai, Dunxuan Wu, Han Ding, Zhigang Wu   +5 more
wiley   +1 more source

Traditional architectural styles in Northwest Henan: a machine learning analysis of influencing factors

Journal of Asian Architecture and Building Engineering
As a significant component of traditional Chinese architectural culture, the architectural styles of northwest Henan embody profound historical, cultural, and artistic values.
Tianxi Lu, Siti Sarah Herman, Nor Atiah Ismail   +2 more
doaj   +1 more source

Early Type 2 diabetes risk prediction using explainable machine learning in a two-stage approach

Frontiers in Digital Health
BackgroundDiabetes is a chronic disease characterized by elevated blood glucose levels. Without early detection and proper management, it can lead to serious complications and increase healthcare costs.
Silas Majyambere, Silas Majyambere, Tony Lindgren, Celestin Twizere, Isaac Ntakirutimana   +4 more
doaj   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source