Results 101 to 110 of about 2,281,992 (231)

Explainable Deep Learning for Hyperparameter Optimization-Based Prediction of Solar Radiation Intensity Classification

Vietnam Journal of Computer Science
Due to the intermittent solar presence, forecasting Solar radiation, is crucial to balancing energy generation and demand, which is critical for the whole grid system.
Mohammed Chachan Younis, Ramadan Mahmood Ramo, Baydaa Sulaiman Bahnam   +2 more
doaj   +1 more source

Targeted Restoration of the Microbial Tryptophan Oxidative Pathway Ameliorates Autism‐Like Behavioral and Synaptic Deficits

Advanced Science, EarlyView.
ABSTRACT Autism Spectrum Disorder (ASD) is associated with gut microbiota dysbiosis, yet the contribution of specific microbial metabolic pathways remains unclear. Reanalysis of a public ASD cohort revealed reduced functional potential in microbial tryptophan oxidative metabolism.
Rui Guo, Caian He, Xiao Xiao, Jingmeng Li, Zilong Zhang, Ying He, Chuanchuan Wang, Jiale Zhao, Jun Gong, Jiarui Liang, Tian Yuan, Haiting Sun, Xuebo Liu, Chao Gao, Zhigang Liu   +14 more
wiley   +1 more source

Forecasting Sales of Slow and Fast Moving Inventories. [PDF]

Adaptations of simple exponential smoothing are presented that aim to unify the task of forecasting demand for both slow and fast moving inventories.
Snyder, R.
core  

Longitudinal Morphomolecular Monitoring of Head and Neck Carcinogenesis

Advanced Science, EarlyView.
A miniaturized endoscopic probe that integrates Raman spectroscopy and optical coherence tomography, enabling simultaneous molecular and structural imaging of living tissue, was developed. Applied longitudinally in a mouse model of head and neck cancer, the system tracks disease progression from precancerous lesions to invasive cancer.
Jianrong Qiu, Priyanka G. Bhosale, Vishal Kumar, Jeyrroy Gabriel, Shiyue Liu, Ciro Chiappini, Richard J. Cook, Mads S. Bergholt   +7 more
wiley   +1 more source

Precision forecasting for hybrid energy systems using five deep learning algorithms for meteorological parameter prediction

International Journal of Electrical Power & Energy Systems
The intermittent nature of renewable energy sources necessitates accurate power production forecasting to ensure system sustainability and balance between energy supply and demand.
Ceren Ceylan, Zehra Yumurtacı
doaj   +1 more source

Data‐Driven Modeling of Composition–Processing–Microstructure Relations for Recycled Aluminum Cast Alloys

Advanced Science, EarlyView.
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang, Waleed Mohammed, Dierk Raabe   +2 more
wiley   +1 more source

Role of Machine Learning in Improving Grid Resilience in Africa: A Comprehensive Review

Engineering Proceedings
Electricity grids in Africa are encountering challenges due to rapid urbanization, variable renewable energy integration, aging infrastructure, and limited financial investments, leading to deterioration of grid resilience. This paper reviews how Machine
Allen Manyere, Sunetra Chowdhury
doaj   +1 more source

A Worm‐Inspired Origami Robot with Multimodal Locomotion for Adaptive Mobility in Complex Pipeline Environments

Advanced Science, EarlyView.
An origami worm‐inspired robot achieves multimodal locomotion in confined pipelines through mechatronic integration that embeds actuation, control, and communication within each origami module. Large, reversible configuration and dimensional changes enable 25 gaits synthesized by a unified framework across peristaltic, inchworm, and wheel‐rolling modes
Qiwei Zhang, Kangning Tan, Zihan He, Hongsen Pang, Yanjie Wang, Hongbin Fang, Jian Xu   +6 more
wiley   +1 more source

Machine Learning‐Assisted KCl‐CaCl2‐LiCl Electrolyte Design for Low‐Temperature, High‐Performance Calcium‐Based Liquid Metal Batteries

Advanced Science, EarlyView.
A machine learning‐assisted framework optimizes the KCl‐CaCl2‐LiCl ternary electrolyte. The optimized 13:35:52 mol% composition enables Ca‐based liquid metal batteries to operate stably at 480 °C, with >99.5% coulombic efficiency, ultralow self‐discharge, and excellent cycling stability, advancing low‐temperature large‐scale energy storage.
Xinglin Zhou, Lei Huang, Yan Zhou, Xiaohui Ning   +3 more
wiley   +1 more source

Recent Advances in Carbon Cathode Materials toward High‐Performing Zinc‐Ion Hybrid Supercapacitors

Advanced Science, EarlyView.
Aqueous zinc‐ion hybrid supercapacitors (ZHSCs) have emerged as promising next‐generation electrochemical energy‐storage devices. Porous carbon materials have been extensively studied as cathodes, with advances in tailoring pore structures and material properties to enhance performance.
Take Hirooka, Zhaolin Liu, Ivan P. Parkin, Guanjie He   +3 more
wiley   +1 more source