Recursive algorithms of adaptive lattice filters adjustment by D. I. Lekhovytskiy, V. P. Riabukha, D. S. Rachkov, A. V. Semeniaka

Get full text

Cross‐Domain Foundation Model Adaptation: Pioneering Computer Vision Models for Geophysical Data Analysis by Zhixiang Guo, Xinming Wu, Luming Liang, Hanlin Sheng, Nuo Chen, Zhengfa Bi

“…FMs, which are large neural networks trained on massive data sets, excel in diverse tasks with remarkable adaptability and generality. …”
Get full text

General Framework for Georeferencing and Interpretation of Multi-Resolution LiDAR Data for Fine-Scale Forest Inventory by H. Hanafy, S.-Y. Shin, A. M. Eissa, Y. Hany, S. Park, S. Fei, A. Habib

Get full text

Design of multi-innovation hierarchical fractional adaptive algorithm for generalized bilinear-in-parameter system using the key term separation principle by Yancheng Zhu, Huaiyu Wu, Zhihuan Chen, Zhenhua Zhu, Yang Chen, Xiujuan Zheng

Get full text

Development of a customised data management system for a COVID-19-adapted colorectal cancer pathway by Malcolm G Dunlop, Yasuko Maeda, Janice Miller, Frances Gunn, Farhat VN Din

Get full text

Climate adaptive energy efficiency modeling using a generalized additive approach to optimize building performance across Chinese climate zones by Jian Yang, Mu He, Xingzhu Zhang, Qimeng Ning, Yu Chen, Maryam Alsadat Ziaei Mazinan

Get full text

Generalized domain prompt learning for accessible scientific vision-language models by Qinglong Cao, Yuntian Chen, Lu Lu, Hao Sun, Zhengzhong Zeng, Xiaokang Yang, Dongxiao Zhang

“…While large-scale VLMs have transformed natural vision tasks, their use in specialized domains like remote sensing and medical imagery remains constrained due to resource limitations. By introducing generalized domain prompt learning (GDPL), the study enables smaller research groups to adapt powerful VLMs for specialized domains like remote sensing, medical imaging, and geology, fostering inclusivity and innovation. …”
Get full text

Unsupervised Domain Adaptation via Contrastive Learning and Complementary Region-Class Mixing by Xiaojing Li, Wei Zhou, Mingjian Jiang

“…In semantic segmentation, current deep convolutional neural networks rely heavily on extensive data to achieve superior segmentation results. However, these deep models have poor generalization ability across different domain datasets. …”
Get full text

Analyzing risk factors and handling imbalanced data for predicting stroke risk using machine learning by Adiwijaya Adiwijaya, Nur Ghaniaviyanto Ramadhan

“…Effective preventive measures are crucial to minimize stroke risk, and using predictive methods based on data analysis from the clinical examination dataset over the last three years (2019-2021), known as the general checkup (GCU) dataset, presents an innovative approach. …”
Get full text

A Generalized Convolutional Neural Network Model Trained on Simulated Data for Fault Diagnosis in a Wide Range of Bearing Designs by Amirmasoud Kiakojouri, Ling Wang

“…However, existing DL models struggle with data availability, generalization, and domain adaptation, making industrial applications challenging. …”
Get full text

A Multi-Source Domain Adaptation Method for Bearing Fault Diagnosis with Dynamically Similarity Guidance on Incomplete Data by Juan Tian, Shun Zhang, Gang Xie, Hui Shi

“…To address these issues, the Dynamic Similarity-guided Multi-source Domain Adaptation Network (DS-MDAN) is proposed. This method leverages incomplete data from multiple-source domains to address distribution disparities in deep domain adaptation. …”
Get full text

Transmuted Generalized Weibull Lindley (TGWL) distribution: Bayesian inference and Bayesian neural network approaches for lifetime data modeling by Pius Marthin, Gadde Srinivasa Rao

“…Focusing on addressing the wide range of behavior in lifetime data, we introduce a new distribution termed Transmuted Generalized Weibull Lindley (TGWL) specifically for lifetime datasets. …”
Get full text

Generalized Metaplectic Convolution-Based Cohen's Class Time-Frequency Distribution: Theory and Application by Manjun Cui, Zhichao Zhang, Jie Han, Yunjie Chen, Chunzheng Cao

Get full text

Adaptive wetland management: Insights from nonlinear dynamics between vegetation and hydrological variables by Haihua Jing, Jianwei Liu, Qin Zhang, Zhenshan Wang, XiaoTeng Pang, Xinghan Xu

“…Using the NaoLiRiver Wetlands as a case study, we developed a comprehensive framework integrating spatiotemporal image fusion, Generalized Additive Modeling (GAM), and Random Forest analysis to analyze 20 years of remote sensing and hydrological data. …”
Get full text

Dynamic Modeling of a Kaplan Hydroturbine Using Optimal Parametric Tuning and Real Plant Operational Data by Hong Wang, Sunil Subedi, Wenbo Jia

“…This changing energy generation landscape requires advance technology integration and adaptive parameter optimization for hydropower systems via digital twin effort. …”
Get full text

Lab-to-Field Generalization Gap: Assessment of Transfer Learning for Bearing Fault Detection by Eleonora Iunusova, Andreas Archenti

“…Their potential to address the generalization gap was assessed by analyzing the model adaptability from lab-recorded data to data from emulated workshop conditions, where real-world variability was replicated by embedding synthetic noise into the lab-recorded data. …”
Get full text

Improving Offshore Wind Speed Forecasting with a CRGWAA-Enhanced Adaptive Neuro-Fuzzy Inference System by Yingjie Liu, Fahui Miao

“…The proposed CRGWAA integrates Chebyshev mapping initialization, an elite-guided reflection refinement operator, and a generalized quadratic interpolation strategy to enhance population diversity, adaptive exploration, and local exploitation capabilities. …”
Get full text

Corrected optimal subsampling for a class of generalized linear measurement error models by Ruiyuan Chang, Xiuli Wang, Mingqiu Wang

“…The consistency and asymptotic normality of the estimators in the general subsampling are also derived. In addition, optimal subsampling probabilities are obtained based on the general subsampling algorithm using the A-optimality and L-optimality criteria and the truncation method, and then an adaptive two-step algorithm is developed. …”
Get full text

Adaptive Defense: Zero-Day Attack Detection in NIDS With Deep Reinforcement Learning by Khorshed Alam, Md Fahad Monir, Md Junayed Hossain, Mohammad Shorif Uddin, Md. Tarek Habib

Get full text

Integrated morphophysiological, transcriptomic, and metabolomic data uncover the molecular mechanism of environmental adaptation of Zanthoxylum armatum with different latitudinal g... by Yuan Guo, Xueqian Fu, Chong Sun, Chong Sun, Yifei Deng, Han Liu, Long Tong, Mi Kuang, Ning Tang, Wenying Yang, Xia Liu, Zexiong Chen

Get full text