Investigation of Mechanical and Corrosion Behavior of ECAP Processed AA7075 Through ML, ANNW, RSM, and SA Methodologies by Majed Alinizzi, W. H. El‐Garaihy, A. I. Alateyah, Samar El‐Sanabary, Fahad Nasser Alsunaydih, Mansour Alturki, H. Abd El‐Hafez, Mohamed S. El‐Asfoury, Eman M. Zayed, Hanan Kouta

“…ABSTRACT This study employs a multi‐perspective modeling approach combining Response Surface Methodology (RSM), Machine Learning (ML), Artificial Neural Networks (ANNW), and Simulated Annealing (SA) to optimize Equal Channel Angular Pressing (ECAP) parameters for improving the mechanical and corrosion properties of AA7075 alloy. …”
Get full text

Soft actor-critic algorithm and improved GNN model in secure access control of disaggregated optical networks by Zhenqian Zhao, Yuhe Wang

“…GESAC is built on spatiotemporal modeling of evolving topologies and leverages a cross-layer spatiotemporal Graph Neural Network (GNN) to capture causal dependencies between optical path switching and access requests. …”
Get full text

Species-independent analysis and identification of emotional animal vocalizations by Stavros Ntalampiras

“…This paper proposes a deep neural network architecture for analysing and recognizing vocalizations representing positive and negative emotional states. …”
Get full text

Cotton transposon-related variome reveals roles of transposon-related variations in modern cotton cultivation by Shang Liu, Hailiang Cheng, Youping Zhang, Man He, Dongyun Zuo, Qiaolian Wang, Limin Lv, Zhongxv Lin, Ji Liu, Guoli Song

“…In addition, a convolutional neural network (CNN) model was constructed to evaluate epigenomic effects of transposon-related variations. …”
Get full text

A Deep Learning-Based Echo Extrapolation Method by Fusing Radar Mosaic and RMAPS-NOW Data by Shanhao Wang, Zhiqun Hu, Fuzeng Wang, Ruiting Liu, Lirong Wang, Jiexin Chen

“…To address the algorithmic limitations of deep learning-based echo extrapolation models, this study introduces three major improvements: (1) A Deep Convolutional Generative Adversarial Network (DCGAN) is integrated into the ConvLSTM-based extrapolation model to construct a DCGAN-enhanced architecture, significantly improving the quality of radar echo extrapolation; (2) Considering that the evolution of radar echoes is closely related to the surrounding meteorological environment, the study incorporates specific physical variable products from the initial zero-hour field of RMAPS-NOW (the Rapid-update Multiscale Analysis and Prediction System—NOWcasting subsystem), developed by the Institute of Urban Meteorology, China. …”
Get full text