Results 221 to 230 of about 53,796 (278)

New Opportunities For the Integration of Artificial Intelligence With Materials Science: From Large Language Models to Embodied Large Models

Materials Genome Engineering Advances, EarlyView.
This review first introduces the diversified applications of large language models in materials discovery. Subsequently, the evolution of autonomous experimentation platforms empowered by large language models is analyzed. Finally, four key future research interests are proposed to develop embodied large models for driving autonomous experimentation ...
Zhen Song, Yishuai Cai, Yadong Yu, Pan Xiang, Minglong Li, Zhe Liu, Mengyan Dai   +6 more
wiley   +1 more source

Automated Rice Seedling Segmentation and Unsupervised Health Assessment Using Segment Anything Model with Multi-Modal Feature Analysis. [PDF]

Sensors (Basel)
Rezvan H, Valadan Zoej MJ, Youssefi F, Ghaderpour E.   +3 more
europepmc   +1 more source

TopoMAS: Large Language Model Driven Topological Materials Multi‐Agent System

Materials Genome Engineering Advances, EarlyView.
TopoMAS is an interactive multi‐agent framework that revolutionizes topological materials discovery through human–AI collaborative intelligence. The system integrates natural language processing, knowledge retrieval from literature and databases, crystal structure generation, and automated first‐principles calculations within a unified workflow.
Baohua Zhang, Xin Li, Huangchao Xu, Zhong Jin, Quansheng Wu, Ce Li   +5 more
wiley   +1 more source

Fast highway abandoned object detection via block-based multi-group foreground extraction. [PDF]

Sci Rep
Liu D, Wang H, Zhang X, Zhang X, Liu Y.
europepmc   +1 more source

On the analyzing of bifurcation properties of the one‐dimensional Mackey–Glass model by using a generalized approach

Mathematical Methods in the Applied Sciences, EarlyView.
The goal of this work is to look at how a nonlinear model describes hematopoiesis and its complexities utilizing commonly used techniques with historical and material links. Based on time delay, the Mackey–Glass model is explored in two instances. To offer a range, the relevance of the parameter impacting stability (bifurcation) is recorded.
Shuai Zhang, Yaya Wang, Hongyin Geng, Wei Gao, Esin Ilhan, Haci Mehmet Baskonus   +5 more
wiley   +1 more source

Lessons Learned From Using Simple Supervised Learning Tools on Small‐Ensemble Data—Applicability to Tunnel Design and Monitoring

International Journal for Numerical and Analytical Methods in Geomechanics, EarlyView.
ABSTRACT Integrating interdisciplinary strategies with artificial intelligence (AI), particularly machine learning (ML), is an effective way of addressing urgent engineering challenges. Therefore, a thorough evaluation of existing methodologies is essential, taking into account their respective strengths, limitations and opportunities.
Lina‐María Guayacán‐Carrillo, Jean‐Michel Pereira, Jean Sulem   +2 more
wiley   +1 more source

An adaptive, energy-efficient and secure routing protocol for zone-related mobile Ad-hoc networks using reinforcement learning. [PDF]

Sci Rep
Singh SB, Rizvi MA, Saxena K, Gupta R, Tripathi AN, Dewangan NK.   +5 more
europepmc   +1 more source

Implications of heterogeneous embankment conditions for geoelectrical investigations on dams: A case study at Mactaquac Dam, Canada

Near Surface Geophysics, EarlyView.
Abstract Electrical resistivity tomography (ERT) has been shown to be effective for surveying and monitoring dams, due to the method's sensitivity to moisture content and relevant physical properties (e.g., porosity). Automated ERT systems, capable of time‐lapse monitoring, can be used to detect variations in ground conditions.
John S. Ball, Karl E. Butler, Jonathan E. Chambers, Paul B. Wilkinson, Andrew Binley   +4 more
wiley   +1 more source

Research on Ground Point Cloud Segmentation Algorithm Based on Local Density Plane Fitting in Road Scene. [PDF]

Sensors (Basel)
Wang T, Fu Y, Zhang Z, Cheng X, Li L, He Z, Wang H, Gong K.   +7 more
europepmc   +1 more source

Matching habitat choice could be brightness‐based instead of hue‐based in green‐brown polymorphic grasshoppers

Oikos, EarlyView.
Some prey species have evolved background matching, that is they resemble their surrounding environment in terms of colour and/or brightness. When prey populations inhabit patchy environments, they may even have evolved specialised phenotypes: each phenotype matching a specific subset of patches.
Lilian Cabon, Holger Schielzeth
wiley   +1 more source