Edge learning for 6G-enabled Internet of Things: A comprehensive survey of vulnerabilities, datasets, and defenses
The deployment of the fifth-generation (5G) wireless networks in Internet of Everything (IoE)
applications and future networks (eg, sixth-generation (6G) networks) has raised a number …
applications and future networks (eg, sixth-generation (6G) networks) has raised a number …
[HTML][HTML] Imprecise bayesian optimization
J Rodemann, T Augustin - Knowledge-Based Systems, 2024 - Elsevier
Bayesian optimization (BO) with Gaussian processes (GPs) surrogate models is widely used
to optimize analytically unknown and expensive-to-evaluate functions. In this paper, we …
to optimize analytically unknown and expensive-to-evaluate functions. In this paper, we …
Application of machine learning for material prediction and design in the environmental remediation
Y Zheng, S Sun, J Liu, Q Zhao, H Zhang, J Zhang… - Chinese Chemical …, 2024 - Elsevier
To develop more efficient catalysts and discover new materials to work towards efficient
solutions to the growing environmental problems, machine learning (ML) offers viable new …
solutions to the growing environmental problems, machine learning (ML) offers viable new …
Peak strength, coalescence and failure processes of rock-like materials containing preexisting joints and circular holes under uniaxial compression: experimental and …
M Wang, Z Lu, Y Zhao, W Wan - Theoretical and Applied Fracture …, 2023 - Elsevier
The stability of rock masses is greatly influenced by the voids and joints present in rock
masses; therefore, the peak strength, coalescence and failure process of rock masses with …
masses; therefore, the peak strength, coalescence and failure process of rock masses with …
A framework based on heterogeneous ensemble models for liquid steel temperature prediction in LF refining process
C Chen, N Wang, M Chen, X Yan - Applied Soft Computing, 2022 - Elsevier
The precise control of liquid steel temperature in the ladle furnace (LF) refining process is
vital for stabilizing and improving the quality of liquid steel, necessitating a capable …
vital for stabilizing and improving the quality of liquid steel, necessitating a capable …
Control of existing tunnel deformation caused by shield adjacent undercrossing construction using interpretable machine learning and multiobjective optimization
A hybrid intelligent framework is proposed in this paper to reduce the existing tunnel
deformation caused by shield adjacent undercrossing construction (SAUC). A Bayesian …
deformation caused by shield adjacent undercrossing construction (SAUC). A Bayesian …
Calibrating microparameters of DEM models by using CEM, DE, EFO, MFO, SSO algorithms and the optimal hyperparameters
M Wang, Z Lu, Y Zhao, W Wan - Computational Particle Mechanics, 2024 - Springer
Abstract The Particle Flow Code is a typical DEM numerical software; however, the
microparameters of DEM models need to be calibrated before numerical simulation. In most …
microparameters of DEM models need to be calibrated before numerical simulation. In most …
Adaptive watermarking with self-mutual check parameters in deep neural networks
Artificial Intelligence has found wide application, but also poses risks due to unintentional or
malicious tampering during deployment. Regular checks are therefore necessary to detect …
malicious tampering during deployment. Regular checks are therefore necessary to detect …
Privacy-preserving and verifiable convolution neural network inference and training in cloud computing
W Cao, W Shen, J Qin, H Lin - Future Generation Computer Systems, 2025 - Elsevier
With the rapid development of cloud computing, outsourcing massive data and complex
deep learning model to cloud servers (CSs) has become a popular trend, which also brings …
deep learning model to cloud servers (CSs) has become a popular trend, which also brings …
Soft integrity authentication for neural network models
Neural network models are widely used in various fields, eg, face recognition, and
autonomous driving, owing to their excellent performance. During training, distribution and …
autonomous driving, owing to their excellent performance. During training, distribution and …