Straightness monitoring of scraper conveyor based on CUDA-accelerated dynamic programming and optimized panoramic stitching by LI Bo, SHI Shouyi, ZHANG Jianjun, XIA Rui, WANG Xuewen, CUI Weixiu, NI Qiang

“…Feature point matches were calculated using K-nearest neighbors (KNN), with incorrect matches filtered using a threshold ratio. …”
Get full text

GLS-YOLO: A Lightweight Tea Bud Detection Model in Complex Scenarios by Shanshan Li, Zhe Zhang, Shijun Li

“…The model leverages GhostNetV2 as its backbone network, replacing standard convolutions with depthwise separable convolutions, resulting in substantial reductions in computational load and memory consumption. Additionally, the C2f-LC module is integrated into the improved model, combining cross-covariance fusion with a lightweight contextual attention mechanism to enhance feature recognition and extraction quality. …”
Get full text

Using explainable machine learning and eye-tracking for diagnosing autism spectrum and developmental language disorders in social attention tasks by Adoración Antolí, Adoración Antolí, Francisco Javier Rodriguez-Lozano, José Juan Cañas, Julia Vacas, Julia Vacas, Fátima Cuadrado, Fátima Cuadrado, Araceli Sánchez-Raya, Araceli Sánchez-Raya, Carolina Pérez-Dueñas, Carolina Pérez-Dueñas, Juan Carlos Gámez-Granados

Get full text

Evaluation of Variations in Morphology and Morphometry of the Hard Palate Using CBCT Images: A Radio-Surgical Perspective by Melda Pelin Akkitap

Get full text

Integrating deep learning and machine learning for improved CKD-related cortical bone assessment in HRpQCT images: A pilot study by Youngjun Lee, Wikum R. Bandara, Sangjun Park, Miran Lee, Choongboem Seo, Sunwoo Yang, Kenneth J. Lim, Sharon M. Moe, Stuart J. Warden, Rachel K. Surowiec

“…High resolution peripheral quantitative computed tomography (HRpQCT) offers detailed bone geometry and microarchitecture assessment, including cortical porosity, but assessing chronic kidney disease (CKD) bone images remains challenging. …”
Get full text

Parameter regionalization of large-scale distributed rainfall–runoff models using a conditional probability method by Takahiro Sayama, Masafumi Yamada, Ayato Yamakita, Yoshito Sugawara

“…The key feature of this method is that the calibration phase calculation assumes spatially uniform parameter sets within the calibrating basins, significantly reducing computational costs. …”
Get full text

A Quantitative Evaluation of UAV Flight Parameters for SfM-Based 3D Reconstruction of Buildings by Inho Jo, Yunku Lee, Namhyuk Ham, Juhyung Kim, Jae-Jun Kim

“…Quantitative evaluation results using various analytical methodologies (multiple regression analysis, Kruskal–Wallis test, random forest feature importance, principal component analysis including K-means clustering, response surface methodology (RSM), preference ranking technique based on similarity to the ideal solution (TOPSIS), and Pareto optimization) revealed that the basic shooting pattern ‘type’ has a significant and statistically significant influence on all major SfM performance metrics (reprojection error, final point count, computation time, reconstruction completeness; Kruskal–Wallis <i>p</i> < 0.001). …”
Get full text

Dynamic Rupture Simulation Reproduces Spontaneous Multifault Rupture and Arrest During the 2016 Mw 7.9 Kaikoura Earthquake by Ryosuke Ando, Yoshihiro Kaneko

Get full text

Research on High-Resolution Modeling of Satellite-Derived Marine Environmental Parameters Based on Adaptive Global Attention by Ruochu Cui, Liwen Ma, Yaning Hu, Jiaji Wu, Haiying Li

Get full text

Extension to the Jiles–Atherton Hysteresis Model Using Gaussian Distributed Parameters for Quenched and Tempered Engineering Steels by Alasdair Regan, John Wilson, Anthony J. Peyton

“…The Jiles–Atherton (J–A) model has seen extensive use for modelling the hysteresis behaviour of ferromagnetic materials due to its computational efficiency, simplicity of use, and small number of physically related parameters. …”
Get full text

Beef Carcass Grading with EfficientViT: A Lightweight Vision Transformer Approach by Hyunwoo Lim, Eungyeol Song

“…Furthermore, we employ Grad-CAM and attention map visualizations to analyze the model’s focus regions and demonstrate that EfficientViT captures holistic contextual features better than CNNs. The model also exhibits robustness across varying loin area proportions. …”
Get full text

NSA-CHG: An Intelligent Prediction Framework for Real-Time TBM Parameter Optimization in Complex Geological Conditions by Youliang Chen, Wencan Guan, Rafig Azzam, Siyu Chen

“…The framework resolves critical limitations of conventional experience-driven approaches that inadequately address the nonlinear coupling between the spatial heterogeneity of rock mass parameters and mechanical system responses. Three principal innovations are introduced: (1) a hardware-compatible sparse attention architecture achieving O(n) computational complexity while preserving high-fidelity geological feature extraction capabilities; (2) an adaptive kernel function optimization mechanism that reduces confidence interval width by 41.3% through synergistic integration of boundary likelihood-driven kernel selection with Chebyshev inequality-based posterior estimation; and (3) a physics-enhanced modelling methodology combining non-Hertzian contact mechanics with eddy field evolution equations. …”
Get full text

Adaptive Real-Time Channel Estimation and Parameter Adjustment for LoRa Networks in Dynamic IoT Environments by Fatimah Alghamdi, Fuad Bajaber

“…This innovative framework provides significant improvements in channel state estimation, communication reliability, adaptive parameter control, and computational efficiency, thereby ensuring robust performance in IoT environments at the same time.…”
Get full text

Estimating Tea Plant Physiological Parameters Using Unmanned Aerial Vehicle Imagery and Machine Learning Algorithms by Zhong-Han Zhuang, Hui-Ping Tsai, Chung-I Chen

“…Among regression models, MIs provided greater stability for tea plant physiological parameters, whereas feature ranking methods had minimal impact on accuracy. …”
Get full text

Dependence of energy-speed characteristics of pneumatic drive on initial parameters of additional volume under counterpressure braking by Andrey N. Sirotenko, Svetlana A. Partko, Bakir Ala Saed

“…Materials and Methods. A computing two-factor experiment is planned and conducted. …”
Get full text

A Bayesian vector-autoregressive application with time-varying parameters on the monetary shocks–production network nexus by Mihaela Simionescu, Nicolas Schneider, Beata Gavurova

Get full text

Predicting visual field global and local parameters from OCT measurements using explainable machine learning by Md Mahmudul Hasan, Jack Phu, Henrietta Wang, Arcot Sowmya, Erik Meijering, Michael Kalloniatis

Get full text

Design a new scheme for image security using a deep learning technique of hierarchical parameters by Khazaal Yasmine M., Falih Mohanaed Ajmi, Majeed Abbas Hamid

Get full text

Attention-Guided Deep Reinforcement Learning for Realistic Neural Painting by Xin Huang, Minglun Gong

“…Specifically, the attention module computes an attention map to guide stroke generation, and a feature-masked reward function prioritizes important regions. …”
Get full text

Effects of Aerodynamic Parameters on Performance of Galloping Piezoelectric Energy Harvester Based on Cross-Sectional Shape Evolutionary Approach by Xiaokang Yang, Bingke Xu, Zhendong Shang, Junying Tian, Haichao Cai, Xiangyi Hu

“…The effects of the aerodynamic parameters on performance are investigated computationally using a distributed parameter electromechanical coupling model. …”
Get full text