A topical review on AI-interlinked biodomain sensors for multi-purpose applications

R Thapa, S Poudel, K Krukiewicz, A Kunwar - Measurement, 2024 - Elsevier
Based on their construction or working principles, biosensors, biomimetic sensors, and
bioapplicable sensors may have been understood differently, but everyone acknowledges …

[HTML][HTML] Hybrid nanogenerator for self-powered object recognition

J Jo, S Panda, N Kim, S Hajra, S Hwang, H Song… - Journal of Science …, 2024 - Elsevier
Energy harvesting systems, including piezoelectric (PENG), triboelectric (TENG), and
pyroelectric (PYNG) nanogenerator technologies, have emerged as one of the major future …

Establishing operator trust in machine learning for enhanced reliability and safety in nuclear Power Plants

M Najar, H Wang - Progress in Nuclear Energy, 2024 - Elsevier
The advancement of safety and reliability in Nuclear Power Plants (NPP) is essential for
ensuring the protection of human life, the environment, and the sustainable use of clean …

Enhancing Radiological Risk Evaluation Through AI and HotSpot Code Integration: A Comparative Study of LOCA and SGTR

M Najar, NNM Maglas, H Wang, Z Qiang… - Radiation Physics and …, 2025 - Elsevier
This study assesses and compares the radiological risks posed by two nuclear accident
scenarios: Loss of Coolant Accident (LOCA) and Steam Generator Tube Rupture (SGTR) …

Safety evaluation of Multiple Steam Generator Tube rupture accident using the best estimate plus uncertainty approach

S Dzień, A Diab - Nuclear Engineering and Design, 2024 - Elsevier
Following the disaster in Fukushima Nuclear Power Plant (NPP) in 2011, the awareness of
securing the safety of NPP under extreme events has been raised. For this purpose, the …

[HTML][HTML] A New Frontier in Wind Shear Intensity Forecasting: Stacked Temporal Convolutional Networks and Tree-Based Models Framework

A Khattak, J Zhang, P Chan, F Chen, A H. Almaliki - Atmosphere, 2024 - mdpi.com
Wind shear presents a considerable hazard to aviation safety, especially during the critical
phases of takeoff and landing. Accurate forecasting of wind shear events is essential to …

Comparative Study of Deep Learning Models for Accidents Classification in NPP: Emphasizing Transparency and Performance

M Najar, H Wang - International Conference on …, 2024 - asmedigitalcollection.asme.org
The nuclear power plant (NPP) plays a crucial role in providing clean energy, significantly
contributing to mitigating global warming. However, this advantage is accompanied by …

[HTML][HTML] AI-Assisted Forecasting of a Mitigated Multiple Steam Generator Tube Rupture Scenario in a Typical Nuclear Power Plant

S Spisak, A Diab - Energies, 2025 - mdpi.com
This study is focused on developing a machine learning (ML) meta-model to predict the
progression of a multiple steam generator tube rupture (MSGTR) accident in the APR1400 …

Assessing the Effectiveness of Machine Learning Models in Predicting Stock Price Movements During Energy Crisis: Insights from Shell's Market Dynamics

MK Rahman, HM Dalim, SA Reza… - Journal of Business …, 2025 - al-kindipublishers.org
The global energy crisis has presented an unprecedented degree of volatility and
uncertainty in financial markets, specifically impacting the stock prices of energy sector …

Research on the hydraulic response characteristics during the water conveyance process of water diversion projects

H Hu, G Liu, L Tao - Journal of Physics: Conference Series, 2024 - iopscience.iop.org
During the initial trial period, the Hanjiang-to-Weihe River Valley Water Diversion Project
(HWRVWD) sourced water from the Sanhekou water conservancy junction. It then …