Results 101 to 110 of about 1,681,604 (218)

Predictive modeling of antenna performance using machine learning for IoT applications

Scientific Reports
The Internet of Things (IoT) is driving the demand for compact, energy-efficient antennas capable of supporting massive, low-power wireless connectivity.
Nitin Panuganti, Pinku Ranjan, Rachit Jain, Anupam Shukla   +3 more
doaj   +1 more source

Network Analysis in Central Disorders of Hypersomnolence: Insight Into Relationships Between Symptoms, Mental Health, and Quality of Life

Journal of Sleep Research, EarlyView.
Network Analysis in Central Disorders of Hypersomnolence: Insight Into Relationships Between Symptoms, Mental Health, and Quality of Life. ABSTRACT In the central disorders of hypersomnolence (CDH) narcolepsy types 1 and 2 (NT1, NT2) and idiopathic hypersomnia (IH), mental health problems are highly prevalent, and quality of life is decreased.
Denise Bijlenga, Tessa F. Blanken, Josephine J. de Boer, Rolf Fronczek, Gert Jan Lammers   +4 more
wiley   +1 more source

Sparse Causal Dynamic Linear Regression

Journal of Time Series Analysis, EarlyView.
ABSTRACT We develop a sparse causal dynamic regression framework for long multivariate time series. With very long time series, the potentially large number of lags and leads in a dynamic regression model often makes time‐domain estimation numerically unstable or intractable.
Rui Huang, Kung‐Sik Chan
wiley   +1 more source

Growing-season NDVI responses to climate change in China’s three major marsh wetland regions

Ecological Indicators
The dynamics of marsh wetland vegetation (MWV) play a vital role in the carbon cycle of marsh wetlands under the background global climate change. However, it is still unclear the response of MWV to climate change in China.
Yue Deng, Shujing Gao, Lulu Liu, Weiguo Jiang   +3 more
doaj   +1 more source

Enhancing Predictive Ability of Agronomic and Quality Traits in Ethiopian Malting Barley (Hordeum vulgare L.) Using Spectral Variable Selection Methods

Plant Breeding, EarlyView.
ABSTRACT Phenomic selection (PS) offers a cost‐effective, breeder‐friendly approach for public breeding programmes with limited access to genotyping or restricted financial resources for laboratory infrastructure. Since PS relies on high‐throughput phenotyping data, which is often derived from near‐infrared spectroscopy (NIRS) of harvested seeds ...
Tigist Tadesse, Peer Wilde, Wondimu Ejerso, Dorothea Borchardt, Patrick Thorwarth, Thomas Miedaner   +5 more
wiley   +1 more source

Machine learning-based methods for estimating evapotranspiration of winter wheat field in the regions of Nanjing

Guan'gai paishui xuebao
【Objective】Accurate estimation of crop evapotranspiration (ETc) is essential for improving irrigation and water resource management. This study aimed to reduce the uncertainty in ETc estimation for winter wheat in the region of Nanjing and improve the ...
LU Lifang, LIU Chunwei, ZHANG Baozhong, WANG Ranghui, ZHANG Pei, QIU Rangjian   +5 more
doaj   +1 more source

Periodontitis and metabolic dysfunction‐associated steatotic liver disease

Periodontology 2000, EarlyView.
Abstract Objective Periodontitis is a chronic inflammatory disease with systemic effects that extend beyond the oral cavity and contribute to systemic immune and metabolic dysregulation. Chronic liver diseases, particularly metabolic dysfunction‐associated steatotic liver disease (MASLD) and its progressive phenotypes, have emerged as major global ...
Rafael Scaf de Molon, Erica Dorigatti de Avila, Davi da Silva Barbirato, Mariana Fampa Fogacci, Jamil Awad Shibli, Anton Sculean, Alpdogan Kantarci   +6 more
wiley   +1 more source

A Stacking Ensemble Machine Learning Model for Predicting Vitamin D Deficiency in Bangladeshi Infants

Vector: The Journal of Engineering, Volume 2027, Issue 1, January/December 2027.
This study uses machine learning to predict vitamin D levels in Bangladeshi infants aged 12–24 months, addressing deficiency despite abundant sunlight. A stacking ensemble model combining Gaussian regressor, extra trees and XGBoost achieved the highest accuracy (R2$R^2$: 0.933, RMSE: 3.312).
Sadia Nasrin Tuly, Shatabdi Majumder, Koushik Roy, Md. Easin, Saha Reno, Golam Moktader Nayeem, Ahosan Habib, Atoshi Chowdhury   +7 more
wiley   +1 more source

Big Data in Cancer Genomics: Computational Foundations and Emerging Pathways for Precision Oncology

Computational and Systems Oncology, Volume 6, Issue 1, December 2026.
ABSTRACT This review aims to explore the computational foundations of big data in cancer genomics and examine emerging pathways that support precision oncology and personalized cancer care. A narrative review approach was adopted to synthesize evidence from PubMed, Scopus, Web of Science, and IEEE Xplore.
Nur Vanu, Nur Mohammad, Fahad Ahmed, Towsif Alam, Koushik Saha, Durga Shahi, Adib Hossain, Mia Md. Tofayel Gonee Manik, Mst. Rina Parvin   +8 more
wiley   +1 more source

Bayesian doubly adaptive elastic-net Lasso for VAR Shrinkage [PDF]

, 2013
We develop a novel Bayesian doubly adaptive elastic-net Lasso (DAELasso) approach for VAR shrinkage. DAELasso achieves variable selection and coefficient shrinkage in a data-based manner.
Gefang, Deborah, Deborah Gefang (7591397)   +1 more
core   +1 more source