Results 91 to 100 of about 1,475 (247)

From Ship to Shore: A Review of Vessel‐To‐Grid Bidirectional Charging for Sustainable Maritime Transport

EcoEnergy, EarlyView.
As maritime transport electrifies, bidirectional charging (V2G) offers a dual‐purpose solution for energy resilience and economic viability. This work identifies key technological advancements and lifecycle challenges utilizing practical case studies to demonstrate how V2G systems can drive decarbonization and grid stability in the marine sector ...
Jonathan Bloor, Tamer Kamel, Sarah Fear, Lee J. Durndell   +3 more
wiley   +1 more source

Generative Models in Inorganic Crystals Discovery and Inverse Design

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
Generative inverse‐design samples from the vast inorganic crystal design space by starting from target properties such as band gap, stability, and ion transport. This Review examines the representations, generative models, and validation workflows needed to translate candidate structures into stable, potentially synthesizable materials for applications
Tao Li, Xiaolin Liu, Fei Wang, Yan Xiong, Yu Chen, Yan Zhao   +5 more
wiley   +1 more source

AI‐based localization of the epileptogenic zone using intracranial EEG

Epilepsia Open, EarlyView.
Abstract Artificial intelligence (AI) is rapidly transforming our lives. Machine learning (ML) enables computers to learn from data and make decisions without explicit instructions. Deep learning (DL), a subset of ML, uses multiple layers of neural networks to recognize complex patterns in large datasets through end‐to‐end learning.
Atsuro Daida, Yipeng Zhang, Sotaro Kanai, Richard Staba, Vwani Roychowdhury, Hiroki Nariai   +5 more
wiley   +1 more source

Empirical Model of Post‐Earthquake Restoration Time for Building Components Based on Data From the 2022 Fukushima‐ken Oki Earthquake in Japan

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT Estimation of the time required for damaged building components to return to their pre‐earthquake conditions through repair is a critical element in assessing the seismic resilience of buildings, and it requires consideration of uncertainty.
Tomoaki Nishino, Takeshi Morii, Rie Okazawa, Hiroaki Notake, Aya Hada, Takahiro Matsui   +5 more
wiley   +1 more source

Learning Rocking Dynamics From Sparse Shake‐Table Data With Interpretable Physics‐Informed Neural Networks

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT We present a hybrid interpretable Physics‐Informed Neural Network Long‐Short Term Memory (Hybrid PINN LSTM) framework for predicting the seismic response of rocking blocks. Existing analytical models rely on uncertain idealizations, while purely data‐driven and machine‐learning approaches lack physical consistency and interpretability.
Shirley Shen, Christian Málaga‐Chuquitaype   +1 more
wiley   +1 more source

Inter‐Material Transfer Learning for Accelerated Nanofluid Heat Transfer Prediction: A Machine Learning Approach for Energy Systems

Energy Science &Engineering, EarlyView.
This study presents an inter‐material transfer learning framework for nanofluid heat transfer prediction in energy systems. By leveraging knowledge from Al2O3‐water data, the model accurately predicts hybrid Al2O3‐TiO2 nanofluid performance with only 20 simulations, achieving R2 = 0.985 and reducing computational requirements by 78. ABSTRACT This paper
Soumaya Hadj Salah, Aymen Ochi, Sonia Bezi   +2 more
wiley   +1 more source

A Review of Energy Management Strategies for Hybrid Electric Vehicles

Energy Science &Engineering, EarlyView.
This review systematically categorizes energy management strategies (EMS) for hybrid electric vehicles, highlighting rule‐based, optimization‐based, learning‐based, and emerging algorithm‐mixing approaches. It provides a comprehensive roadmap for developing intelligent control systems to enhance energy efficiency and promote sustainable transportation.
Song Gao, Bingchan Zhou, Zhumu Fu, Zhaohui Jiang, Kaikai Zhang, Qihui Ma, Mingchong Dong, Fazhan Tao, Pengju Si, Xin Jin   +9 more
wiley   +1 more source

ChatGPT in Educational Research: A Case Study of Graduate Students' Use and Ethical Perceptions

Future in Educational Research, EarlyView.
ABSTRACT The rise of generative AI, particularly ChatGPT, has transformed academic research, raising both opportunities and ethical concerns. This study examines how graduate students in the education field utilize ChatGPT and their ethical perceptions regarding its use.
Eunseon Lim, Hyunwoong Lee, Yeoran Choi
wiley   +1 more source

Motive and Opportunity: Order Choice in a Limit Order Book With Dispersed Information

International Journal of Finance &Economics, EarlyView.
ABSTRACT We test predictions of market microstructure theory relating to the determinants of order choice in a limit order book where information is dispersed among traders. Using an experimental limit order book, with a large state space, we find that informed traders exhibit patience, compatible with the ‘waiting game’ behaviour described in Foster ...
James Steeley, Charles Schnitzlein, Patricia Chelley‐Steeley   +2 more
wiley   +1 more source

The Impact of Economic Growth on Insurance (Growth)

International Journal of Finance &Economics, EarlyView.
ABSTRACT This paper investigates the impact of economic growth on insurance (growth), focusing on the outflow side of the insurance activity, as captured by benefits (including commissions and expenses). The findings provide evidence that economic growth does exert a positive, statistically significant impact on the benefit side of insurance (growth ...
Nicholas Apergis, Thomas Poufinas, Panagiotis Kimpouropoulos   +2 more
wiley   +1 more source