Wide-Angle Image Distortion Correction and Embedded Stitching System Design Based on Swin Transformer by Shiwen Lai, Zuling Cheng, Wencui Zhang, Maowei Chen

“…Experiments on synthetic and real-world datasets show that the method outperforms mainstream algorithms, with PSNR gains of 3.28 dB and 2.18 dB on wide-angle and fisheye images, respectively, while maintaining real-time performance. …”
Get full text

Predictive framework of vegetation resistance in channel flow by Fengcong Jia, Weijie Wang, Yu Han, Jiayu Du, Yue Zhang, Zihan Liu, Hairong Gao

“…To improve predictive performance, optimization algorithms such as PSO, WSO, and RIME were applied. …”
Get full text

Numerical analysis of geometrical configuration effects on near-field shockwave propagation in CL-20 based underwater explosives by Ji-ping Chen, Jun Wang, Xian-pi Zhang, Yan-jie Zhao, Xing-xing Wu, Fang-zhou Zhu, Jun Yu

“…The computational framework implements algorithmic initiation modeling for detonation processes, coupled with a front-tracking methodology employing the modified ghost fluid method to resolve discontinuities at immiscible phase boundaries. …”
Get full text

Comparative Analysis of Audio Features for Unsupervised Speaker Change Detection by Alymzhan Toleu, Gulmira Tolegen, Rustam Mussabayev, Alexander Krassovitskiy, Bagashar Zhumazhanov

“…These findings offer valuable insights into the impact of feature selection on unsupervised SCD, providing guidance for the development of more robust and accurate algorithms for practical applications.…”
Get full text

A triple pronged approach for ulcerative colitis severity classification using multimodal, meta, and transformer based learning by Md. Nasim Ahmed, Dipta Neogi, Muhammad Rafsan Kabir, Shafin Rahman, Sifat Momen, Nabeel Mohammed

“…We systematically evaluate multiple vision transformer architectures, discovering that a Swin-Base model achieves an accuracy of 90%, while a soft-voting ensemble of diverse ViT backbones boosts performance to 93%. …”
Get full text

A CART-Based Model for Analyzing the Shear Behaviors of Frozen–Thawed Silty Clay and Structure Interface by Fengpan Zhu, Bo Wang, Zhiqiang Liu

“…This study employs integrated machine learning algorithms to model the shear behavior of frozen–thawed silty clay and the structure interface. …”
Get full text

HSDT-TabNet: A Dual-Path Deep Learning Model for Severity Grading of Soybean Frogeye Leaf Spot by Xiaoming Li, Yang Zhou, Yongguang Li, Shiqi Wang, Wenxue Bian, Hongmin Sun

“…However, both conventional field monitoring and machine learning algorithms remain challenged in achieving rapid and accurate detection. …”
Get full text

Multi-Fidelity Machine Learning for Identifying Thermal Insulation Integrity of Liquefied Natural Gas Storage Tanks by Wei Lin, Meitao Zou, Mingrui Zhao, Jiaqi Chang, Xiongyao Xie

“…Three machine learning algorithms—Multilayer Perceptron, Random Forest, and Extreme Gradient Boosting—were evaluated to determine the optimal implementation. …”
Get full text

From Simulation to Implementation: A Systems Model for Electric Bus Fleet Deployment in Metropolitan Areas by Ludger Heide, Shuyao Guo, Dietmar Göhlich

“…This study presents “eflips-X”, a modular, open-source simulation framework that integrates energy consumption modeling, battery-aware block building, depot–block assignment, terminus charger placement, depot operations simulation, and smart charging optimization within a unified workflow. The framework employs empirical energy models, graph-based scheduling algorithms, and integer linear programming for depot assignment and smart charging. …”
Get full text

The synergy of neuromarketing and artificial intelligence: A comprehensive literature review in the last decade by Ahmed H. Alsharif, Junhai Wang, Salmi Mohd Isa, Nor Zafir Md Salleh, Husam Azzawi Dawas, Mohammed H. Alsharif

“…Emotion, attention, and memory have become vital in NM and AI studies. AI algorithms analyze vast neural and physiological datasets, offering marketers insights into the emotional impact of campaigns, granular insights into consumer focus, and optimizing content for maximum impact. …”
Get full text

GCV-SLAM: Ground Constrained Visual SLAM Through Local Ground Planes by Yu Fan, Peng Zhang, Zhi Wang, Chengbao Liu, Guang Zhang

“…The classical visual Simultaneous Localization and Mapping(SLAM) algorithms assume that the camera moves in a free 3D space, while it is not valid for ground vehicles whose poses are influenced by ground surfaces. …”
Get full text

Cereal and Rapeseed Yield Forecast in Poland at Regional Level Using Machine Learning and Classical Statistical Models by Edyta Okupska, Dariusz Gozdowski, Rafał Pudełko, Elżbieta Wójcik-Gront

“…The random forest model was best for rapeseed yield, while for cereal, the best prediction was observed for multiple linear regression or neural network models. …”
Get full text

From molecules to data: the emerging impact of chemoinformatics in chemistry by Anup Basnet Chetry, Keisuke Ohto

“…Additionally, it outlines future challenges and opportunities, emphasizing the need for improved algorithms, data standardization, and interdisciplinary collaboration. …”
Get full text

Unraveling the Reshaping of Human Resource Management Function: the mediating role of artificial intelligence by Samuel Bangura, Anos Chitamba Chitamba, Lucia Zithobile Ngidi, Sizwe Mbona

“…However, the study also identifies potential challenges associated with AI adoption, including concerns related to algorithmic bias, data privacy, transparency, and employee apprehensions. …”
Get full text

Reinforcement learning in artificial intelligence and neurobiology by Tursun Alkam, Andrew H Van Benschoten, Ebrahim Tarshizi

“…Empirical studies reveal neural correlates of RL algorithms in the basal ganglia, prefrontal cortex, and hippocampus, supporting their roles in planning, memory, and decision-making. …”
Get full text

Precision Medicine in Lung Cancer Screening: A Paradigm Shift in Early Detection—Precision Screening for Lung Cancer by Hsin-Hung Chen, Yun-Ju Wu, Fu-Zong Wu

“…However, implementation must also address challenges related to health equity, algorithmic bias, and system integration. As precision medicine continues to evolve, it holds the promise of optimizing early detection, minimizing harm, and extending the benefits of lung cancer screening to broader and more diverse populations. …”
Get full text

A Novel Ensemble of Deep Learning Approach for Cybersecurity Intrusion Detection with Explainable Artificial Intelligence by Abdullah Alabdulatif

“…Recursive Feature Elimination is utilized for optimal feature selection, while SHapley Additive exPlanations (SHAP) provide both global and local interpretability of the model’s decisions. …”
Get full text

An Empirical Comparison of Machine Learning and Deep Learning Models for Automated Fake News Detection by Yexin Tian, Shuo Xu, Yuchen Cao, Zhongyan Wang, Zijing Wei

“…Our results show that transformer-based models, especially ALBERT, achieve state-of-the-art performance (macro F1 up to 0.99) with rich context, while classical ensembles remain viable for constrained settings. …”
Get full text

Automated Microservices Identification Through Business Process Analysis: A Semantic-Driven Clustering Approach by Idris Oumoussa, Rajaa Saidi

“…The rise of microservice architectures has further evolved software development practices, building upon the foundation established by web services in breaking down monolithic systems, while offering more finely detailed, coherent, and loosely interconnected services. …”
Get full text

Au-Ag Bimetallic Nanoparticles for Surface-Enhanced Raman Scattering (SERS) Detection of Food Contaminants: A Review by Pengpeng Yu, Chaoping Shen, Xifeng Yin, Junhui Cheng, Chao Liu, Ziting Yu

“…Food contaminants, including harmful microbes, pesticide residues, heavy metals and illegal additives, pose significant public health risks. While traditional detection methods are effective, they are often slow and require complex equipment, which limits their application in real-time monitoring and rapid response. …”
Get full text