Results 221 to 230 of about 35,453 (267)

Secondary Operation Risk Assessment Method Integrating Graph Convolutional Networks and Semantic Embeddings. [PDF]

Sensors (Basel)
Zhu P, Li Y, Xu P, Li P, Zhao Z, Li G.
europepmc   +1 more source

Orchestrating Green Transformation: How AI Adoption Enables Corporate Carbon Neutrality

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT As carbon neutrality has become a central goal of global climate governance, how firms achieve low‐carbon transformation has emerged as a critical research issue. However, prior studies have primarily focused on macro‐ or industry‐level analyses, offering limited and fragmented insights into how digital technologies—particularly AI—affect firm‐
Xiaonan Dong, Sungjin Son
wiley   +1 more source

Leveraging commonality across multiple tissue slices for enhanced whole slide image classification using graph convolutional networks. [PDF]

BMC Med Imaging
Noree S, Quinones Robles WR, Ko YS, Yi MY.   +3 more
europepmc   +1 more source

EventFlow: Real‐time neuromorphic event‐driven classification of two‐phase boiling flow regimes

Droplet, EarlyView.
We present a real‐time flow regime classification framework that integrates neuromorphic event‐driven sensing with deep recurrent neural networks. Unlike traditional frame‐based approaches, our system captures sparse event streams from an event‐based camera, representing only the dynamic brightness changes at the individual pixel level.
Sanghyeon Chang, Srikar Arani, Nishant Sai Nuthalapati, Youngjoon Suh, Nicholas Choi, Siavash Khodakarami, Md Rakibul Hasan Roni, Nenad Miljkovic, Aparna Chandramowlishwaran, Yoonjin Won   +9 more
wiley   +1 more source

A Dynamic Model for Early Prediction of Alzheimer's Disease by Leveraging Graph Convolutional Networks and Tensor Algebra. [PDF]

Pac Symp Biocomput
Ozdemir C, Olaimat MA, Bozdag S, Alzheimer’s Disease Neuroimaging Initiative.   +3 more
europepmc   +1 more source

Gaborlet‐guided sparse filtering: A novel intelligent method for lithology identification by vibration signals while drilling

Deep Underground Science and Engineering, EarlyView.
The flowchart illustrates rock specimen testing, vibration signal acquisition, and feature extraction with Gaborlet and sparse filtering for classification. Abstract Traditional lithology identification methods mainly rely on core sampling and well‐logging data.
Jian Hao, Danqi Zhang, Zhenqi Song, Jinrui Wang, Qi Wang, Heqing Liu   +5 more
wiley   +1 more source

Analyzing world city network by graph convolutional networks. [PDF]

Sci Rep
Tian L, Rao W, Zhao K, Vo HT.
europepmc   +1 more source

Advancing mine pillar design: Evaluating traditional methods and integrating AI for enhanced stability of pillars in the Great Dyke, Zimbabwe

Deep Underground Science and Engineering, EarlyView.
B1 is bord width 1, B2 is bord width 2, L is the pillar length, W is the pillar width, red color and letter A represent the pillars, and white color and number 1 represent excavated areas. Pstress is the average pillar stress; σv is the vertical component of the virgin stress, MPa; and e is the areal extraction ratio. e = B o B o + B P ${\rm{e}}=\frac{{
Tawanda Zvarivadza, Hendrik Grobler, Peter Apata Olubambi, Moshood Onifade, Manoj Khandelwal   +4 more
wiley   +1 more source

TGNet: tensor-based graph convolutional networks for multimodal brain network analysis. [PDF]

BioData Min
Kong Z, Zhou R, Luo X, Zhao S, Ragin AB, Leow AD, He L.   +6 more
europepmc   +1 more source

Dynamic geo‐hydrogeological monitoring‐driven situational awareness for real‐time floor water inrush risk prediction in deep mining

Deep Underground Science and Engineering, EarlyView.
The fused data extracted from the distributed monitoring system as the data basis, combined with dynamic geological data, are imported into a deep learning model. As the geological conditions of mining and excavation change, the risk of water inrush at the working face is retrieved in real time.
Yongjie Li, Huiyong Yin, Fangying Dong, Tao Wu, Chao Zhang   +4 more
wiley   +1 more source