Results 61 to 70 of about 302,002 (276)

Comparative Evaluation of Statistical, Machine‐Learning, and Deep‐Learning Models for Construction Sand and Gravel Price Forecasting: A Synthetic‐Data, Simulation‐Based Benchmark

Engineering Reports
Forecasting construction sand and gravel prices is critical for infrastructure cost control, yet reliable comparisons among model families in the small‐sample, multidriver setting typical of regional markets are lacking.
You Wu, Peng Li, Jing Zhang, Fengsheng Guo, Danshu Hu, Wei He, Zhi Wang   +6 more
doaj   +1 more source

Neutrosophic Exponential Ratio-Type Estimator for Finite Population Mean [PDF]

Neutrosophic Sets and Systems
This paper proposes a neutrosophic exponential-type estimator for finite population mean estimation using auxiliary variables. Traditional statistical estimators often fall short when handling vague or uncertain data.
Anisha Taneja, Sachin Malik, Prem Shankar Jha   +2 more
doaj   +1 more source

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Advanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source

Forecasting renewable energy for microgrids using machine learning

Discover Applied Sciences
Microgrids, comprised of interconnected loads and distributed energy resources, function as single controllable entities with respect to the main grid. However, the inherent variability of distributed wind and solar generation within microgrids presents ...
Piyumi Sudasinghe, Damayanthi Herath, Isiwara Karunarathne, Hansani Weeratunge, Lahiru Jayasuriya   +4 more
doaj   +1 more source

Transferable Deep Reinforcement Learning With Edge‐Contour‐Depth Fusion for Autonomous Wireless Capsule Endoscopy Navigation

Advanced Science, EarlyView.
This study presents an anatomical landmark‐guided DRL framework for autonomous wireless capsule endoscopy navigation. Using a lightweight edge‐contour‐depth fusion module, it achieves over 97% coverage across diverse gastric anatomies. To ensure reliability, a two‐stage sim‐to‐real pipeline with an adaptive dynamic programming controller mitigates ...
Haoxuan Wu, Haitao Gao, Qingyang Liu, Sishen Yuan, Haiyang Fang, Mingwu Su, Baijia Liang, Yongzun Yang, Long Bai, Wenzhen Dong, Dihong Xie, Shijian Su, Jiewen Lai, Shing Shin Cheng, Zhen Li, Xiuli Zuo, Hongliang Ren   +16 more
wiley   +1 more source

Native AI-based hybrid deep learning for wireless link quality prediction in NTN waterside scenarios

ICT Express
Predicting link quality before establishing communication between transmitter and receiver enhances channel selection. With the advancements in artificial intelligence, prediction is now possible for complex environments such as riverside, maritime and ...
Shrutika Sinha, G. Pradeep Reddy, Sea-Moon Kim, Soo-Hyun Park   +3 more
doaj   +1 more source

stMixer for Scalable Mosaic Integration and Label Transfer in Spatial Histology and Multi‐Omics

Advanced Science, EarlyView.
stMixer is an unsupervised framework for scalable integration and label transfer across spatial histology and multi‐slide multi‐omics data with incomplete modality overlap. It combines self‐looped cross‐attention, multimodal metric learning, and graph‐guided cluster voting to align heterogeneous sections, correct batch effects, and propagate ...
Qixing Yang, Yan Wang, Luonan Chen, Chunman Zuo   +3 more
wiley   +1 more source

De Novo Design of Membrane‐Targeting Antimicrobial Peptides Against Gram‐Negative Bacteria Using a Generative Artificial Intelligence Framework

Advanced Science, EarlyView.
Antimicrobial resistance caused by Gram‐negative bacteria remains difficult to overcome due to the protective outer membrane. To address this challenge, a multi‐condition constrained generative AI framework, GenMTAMP is proposed for de novo membrane‐targeting antimicrobial peptide design by integrating physicochemical and spatial structure descriptors.
Jingxiao Yu, Da‐Wen Sun, QingYi Wei, Yibing Zhang, Jidong Tang, Hongbin Pu   +5 more
wiley   +1 more source

Performance of the Machine Learning Algorithm in Stature Estimation Using Scapula Measurements from Post-Mortem Computed Tomography in a Thai Male Population

Journal of Health Science and Medical Research (JHSMR)
Objective: This study attempted to investigate the performance of stature prediction models from scapular dimensions based on post-mortem computed tomography (PMCT) using machine learning algorithms within the male population of Southern Thailand ...
Thutchai Opaburanakul, Tawachai Monum, Komet Kosawiwat, Chanathip Kawin, Wirachai Samai   +4 more
doaj   +1 more source

A Foundation Model Based CT Biomarker for Non‐Invasive Prediction of Response to Neoadjuvant Immunochemotherapy in Non‐Small Cell Lung Cancer

Advanced Science, EarlyView.
This study introduces a foundation model‐based biomarker for risk stratification of pathological response in non‐small cell lung cancer. A Vision Mamba super‐resolution model standardizes heterogeneous CT images. A multi‐task Swin Transformer then fine‐tunes a pre‐trained lung foundation model to jointly optimize tumor segmentation and response ...
Yanglan Xu, Shuchang Zhou, Qin Peng, Xiao Bao, Xiaodan Ye, Ahmet Görkem Er, Tong Tong, Mirabela Rusu, Yajia Gu, Mailin Chen, Jing Gong   +10 more
wiley   +1 more source