State-of-the-art CNN optimizer for brain tumor segmentation in magnetic resonance images

M Yaqub, J Feng, MS Zia, K Arshid, K Jia, ZU Rehman… - Brain sciences, 2020 - mdpi.com
Brain tumors have become a leading cause of death around the globe. The main reason for
this epidemic is the difficulty conducting a timely diagnosis of the tumor. Fortunately …

Uncertainty quantification for additive manufacturing process improvement: Recent advances

S Mahadevan, P Nath, Z Hu - … -ASME Journal of …, 2022 - asmedigitalcollection.asme.org
This paper reviews the state of the art in applying uncertainty quantification (UQ) methods to
additive manufacturing (AM). Physics-based as well as data-driven models are increasingly …

Improved compact cuckoo search algorithm applied to location of drone logistics hub

JS Pan, PC Song, SC Chu, YJ Peng - Mathematics, 2020 - mdpi.com
Drone logistics can play an important role in logistics at the end of the supply chain and
special environmental logistics. At present, drone logistics is in the initial development stage …

Bayesian optimization objective-based experimental design

M Imani, SF Ghoreishi - 2020 American control conference …, 2020 - ieeexplore.ieee.org
Design has become a salient part of most of the scientific and engineering tasks, embracing
a wide range of domains including real experimental settings (eg, material discovery or drug …

Graph-based Bayesian optimization for large-scale objective-based experimental design

M Imani, SF Ghoreishi - IEEE transactions on neural networks …, 2021 - ieeexplore.ieee.org
Design is an inseparable part of most scientific and engineering tasks, including real and
simulation-based experimental design processes and parameter/hyperparameter …

A novel active learning reliability method combining adaptive Kriging and spherical decomposition-MCS (AK-SDMCS) for small failure probabilities

M Su, G Xue, D Wang, Y Zhang, Y Zhu - Structural and Multidisciplinary …, 2020 - Springer
Structural reliability analysis for small failure probabilities remains a challenging task,
despite the significant progress made by the active learning reliability methods (ALRMs) …

Multi-model Bayesian optimization for simulation-based design

S Tao, A Van Beek, DW Apley… - Journal of …, 2021 - asmedigitalcollection.asme.org
We enhance the Bayesian optimization (BO) approach for simulation-based design of
engineering systems consisting of multiple interconnected expensive simulation models …

Bayesian surrogate learning for uncertainty analysis of coupled multidisciplinary systems

SF Ghoreishi, M Imani - Journal of Computing and …, 2021 - asmedigitalcollection.asme.org
Engineering systems are often composed of many subsystems that interact with each other.
These subsystems, referred to as disciplines, contain many types of uncertainty and in many …

Optimal Joint Defense and Monitoring for Networks Security under Uncertainty: A POMDP‐Based Approach

A Kazeminajafabadi, M Imani - IET Information Security, 2024 - Wiley Online Library
The increasing interconnectivity in our infrastructure poses a significant security challenge,
with external threats having the potential to penetrate and propagate throughout the …

Bearing health monitoring using relief-F-based feature relevance analysis and HMM

JA Hernández-Muriel, JB Bermeo-Ulloa… - Applied Sciences, 2020 - mdpi.com
Nowadays, bearings installed in industrial electric motors are constituted as the primary
mode of a failure affecting the global energy consumption. Since industries' energy demand …