Results 201 to 210 of about 33,486 (254)

Detection of focal impaired awareness seizures using a biometric shirt

Epilepsia Open, EarlyView.
Abstract Objective In recent years, seizure detection using wearable technology has gained significant attention in research. Most studies, however, have focused on detecting generalized or focal to bilateral tonic–clonic seizures. This study evaluates the feasibility of using a biometric shirt to detect focal impaired awareness seizures (FIAS) by ...
Jérôme St‐Jean, Oumayma Gharbi, Dènahin Hinnoutondji Toffa, Thi Phuoc Yen Tran, Manon Robert, Dang Khoa Nguyen, Elie Bou Assi   +6 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

Graph Neural Network‐Based Prediction of Building Energy Consumption

Energy Science &Engineering, EarlyView.
A graph neural network that encodes a multi‐zone building as a graph accurately predicts hourly cooling and heating loads across three distinct climates, outperforming Random Forest and XGBoost baselines and serving as a fast surrogate to EnergyPlus simulations for scalable building energy management.
Ali Maboudi Reveshti, Jamal Dabbagh, Jhila Nasiri Reveshti, Karim Farajeyan Bonab, Farid Hosseini Mansoub   +4 more
wiley   +1 more source

Hybrid Simulation–Machine Learning Surrogates for Coordinate‐Based Solar and Wind Energy Yield Assessment in Iraq: A Streamlit Decision‐Support Tool

Energy Science &Engineering, EarlyView.
This study integrates climatic simulations with machine learning to predict solar and wind energy across Iraq. Results show Random Forest excels for solar (R2 = 0.98) and neural networks for wind (R2 = 0.97), enabling a practical web tool for renewable energy planning. ABSTRACT Driven by the global shift away from fossil fuels, solar and wind resources
Bassam Musheer Kareem, Abdolsalam Ebrahimpour, Jafar Ghafouri, Roghayyeh Motallebzadeh   +3 more
wiley   +1 more source

Variance‐Empirical Mode Decomposition Method for Fault Detection in MMC‐HVDC Transmission Lines

Energy Science &Engineering, EarlyView.
A variance‐embedded empirical mode decomposition (VEMD) method is proposed for fast and accurate fault detection in MMC‐HVDC transmission lines. By combining variance analysis with EMD, the method reliably detects various faults without communication links and remains robust to noise and non‐fault transients.
Seyed Amir Hosseini, Behrooz Taheri
wiley   +1 more source

Predicting Solar Photovoltaic Power Output in Saudi Arabia's Jazan Region: Performance Comparison of Machine Learning Models

Energy Science &Engineering, EarlyView.
Workflow of the PV power estimation and ML forecasting methodology. ABSTRACT Accurate prediction of solar panel energy output is vital for managing power systems effectively and maintaining a stable electrical grid. This is especially important in regions that rely heavily on renewable sources. This research provides a direct comparison of five machine
Abdoalateef Alzhrani, Abdullahi Abubakar Mas'ud, Mohd Khairul Amri Kamarudin, Firdaus Muhammad‐Sukki, Abdullahi Mohammad   +4 more
wiley   +1 more source

Predicting EU Emissions Allowance Prices Using Macroeconomic Indicators and Hybrid AI Models

Journal of Forecasting, EarlyView.
ABSTRACT Predicting carbon allowance prices has grown more crucial in relation to carbon market regulation, financial strategy, and environmental policy development. This study examines a hybrid forecasting system that combines deep learning with ensemble machine learning models to forecast the price fluctuations of EU Emissions Allowance (EUAs) within
Saptarshi Ganguly, Pooja Sengupta, Divya Aggarwal   +2 more
wiley   +1 more source

Research progress on the use of the optical coherence tomography system for the diagnosis and treatment of central nervous system tumors

Ibrain, Volume 11, Issue 1, Page 3-18, Spring 2025.
With the advantages of high‐resolution imaging, efficient image acquisition, intraoperative real‐time detection, and radiation‐free and noninvasive characteristics, optical coherence tomography (OCT) provides accurate diagnosis and effective intraoperative guidance for the minimally invasive diagnosis and treatment of central nervous system (CNS ...
Jiuhong Li, Ziba Ayi, Gonggong Lu, Haibo Rao, Feilong Yang, Jing Li, Jiachen Sun, Junlin Lu, Xulin Hu, Si Zhang, Xuhui Hui   +10 more
wiley   +1 more source

Development of CQ prediction based on XGBoost Algorithm

Journal of the Korea Institute of Information and Communication Engineering
Seungyeop Baek, Hyunbin Han, Yoon-Soo Seo, Keun-Young Lee, Donghyun Kim, Jihoon Park, Gwanghyun Jo   +6 more
openaire   +1 more source

Microbiome and aging: Trajectories of microbiome age across human ecosystems and their systemic effects

iMeta, EarlyView.
Microbiome age (MA) has emerged as an innovative biomarker of biological aging, reflecting host aging trajectories through dynamic alterations in microbial composition, function, and host–microbe interactions across multiple body ecosystems. Diverse computational strategies—including traditional machine learning, deep learning, and multi‐omics ...
Zhexin Ni, Jiaojiao Xie, Zhichun Zhang, Keming Zhang, Jie Ding, Mingyang Chang, Ying Su, Yunan Zhang, Mingfei Yao, Chengyuan Wang, Yan Yan, Wenjie Fang, Hainv Gao, Xuecong Tian, Yangshuo Li, Xinlin Zhu, Wen Zhang, Wanqing Liao, Gaoyuan Xu, Guojing Chen, Xiaoyi Lv, Chaoqin Yu, Weihua Pan, Vadim Molodtsov, Lanjuan Li, Yue Gao, Wei Zhou   +26 more
wiley   +1 more source