Study of methods for extracting contours of objects on raster images of amber samples by Yu.O. Podchashynskyi, A.V. Ryzhuk

“…Effective methods and algorithms for detecting objects and their contours on raster images significantly improve the performance of TVS in applied tasks. …”
Get full text

HSNMF enables accurate and effective analysis for the college students' psychological health education data and student life data by Yuanyuan Ma, Yuanyuan Ma, Lifang Liu

“…The results showed that the low-dimensional latent variables learned from HSNMF contained rich semantic information, further improving the performance of traditional machine learning models. …”
Get full text

Cyber threat intelligence for smart grids using knowledge graphs, digital twins, and hybrid machine learning in SCADA networks by Nabeel Al-Qirim, Munir Majdalawieh, Anoud Bani-hani, Hussam Al Hamadi

“…This enhanced visualization provides deeper insights into attack dynamics and significantly improves predictive accuracy, showcasing the effectiveness of the proposed method in understanding and mitigating cyber threats.…”
Get full text

StomachNet: Optimal Deep Learning Features Fusion for Stomach Abnormalities Classification by Muhammad Attique Khan, Muhammad Shahzad Sarfraz, Majed Alhaisoni, Abdulaziz A. Albesher, Shuihua Wang, Imran Ashraf

“…In the initial stage, the contrast is improved by fusing bi-directional histogram equalization with top-hat filtering output. …”
Get full text

Designing CITOBOT: A portable device for cervical cancer screening using human-centered design, smart prototyping, and artificial intelligence by Marcela Arrivillaga, Paula C. Bermúdez, Juan Pablo García-Cifuentes, Hernán Darío Vargas-Cardona, Daniela Neira, Maria del Mar Torres, Mérida Rodríguez-López, Daniela Morales, Bleider Arizala

“…Despite technological advancements that have improved the quality of cervical images captured during visual inspections, several challenges persist. …”
Get full text

Complete spatiotemporal quantification of cardiac motion in mice through multi-view magnetic resonance imaging and super-resolution reconstruction by Tanmay Mukherjee, Maziyar Keshavarzian, Elizabeth M. Fugate, Vahid Naeini, Amr Darwish, Jacques Ohayon, Kyle J. Myers, Dipan J. Shah, Diana Lindquist, Sakthivel Sadayappan, Roderic I. Pettigrew, Reza Avazmohammadi

“…Results: SRR-derived strains were validated against a kinematic benchmark established through the in-silico heart model phantom. Improvements in global strain accuracy were confirmed in both in-plane (radial and circumferential) and through-plane (longitudinal) strains. …”
Get full text

Deep Multi-Modal Skin-Imaging-Based Information-Switching Network for Skin Lesion Recognition by Yingzhe Yu, Huiqiong Jia, Li Zhang, Suling Xu, Xiaoxia Zhu, Jiucun Wang, Fangfang Wang, Lianyi Han, Haoqiang Jiang, Qiongyan Zhou, Chao Xin

“…In conclusion, our deep multi-modal information-switching model enhances skin lesion identification by capturing relationship features and fine-grained details across multi-modal images, improving both accuracy and interpretability. …”
Get full text

Toward generalizable prediction of antibody thermostability using machine learning on sequence and structure features by Ameya Harmalkar, Roshan Rao, Yuxuan Richard Xie, Jonas Honer, Wibke Deisting, Jonas Anlahr, Anja Hoenig, Julia Czwikla, Eva Sienz-Widmann, Doris Rau, Austin J. Rice, Timothy P. Riley, Danqing Li, Hannah B. Catterall, Christine E. Tinberg, Jeffrey J. Gray, Kathy Y. Wei

“…Our results suggest that such models can be broadly applicable for improving the biological characteristics of antibodies. …”
Get full text

Artificial Intelligence-Assisted Selection Strategies in Sheep: Linking Reproductive Traits with Behavioral Indicators by Ebru Emsen, Muzeyyen Kutluca Korkmaz, Bahadir Baran Odevci

“…Despite these barriers, AI-assisted behavioral phenotyping has the potential to improve genetic progress, animal welfare, and sustainability. …”
Get full text

Ant Colony Optimization Using Common Social Information and Self-Memory by Yoshiki Tamura, Tomoko Sakiyama, Ikuo Arizono

“…We apply the existing ACO algorithms and ASIM to some TSP benchmarks and compare the ability to solve TSP.…”
Get full text

Machine Learning Applications in Gray, Blue, and Green Hydrogen Production: A Comprehensive Review by Xuejia Du, Shihui Gao, Gang Yang

“…Among these, green hydrogen—particularly via water electrolysis and biomass gasification—received the most attention, reflecting its central role in decarbonization strategies. ML algorithms such as artificial neural networks (ANNs), random forest (RF), and gradient boosting regression (GBR) have been widely applied to predict hydrogen yield, optimize operational conditions, reduce emissions, and improve process efficiency. …”
Get full text

Leveraging AI for Sustainable Energy Development in Solar Power Plants Operating Under Shading Conditions by Farhad Khosrojerdi, Stéphane Gagnon, Raul Valverde

“…This paper demonstrates how AI-based control systems can improve energy output in a solar power plant under shading conditions. …”
Get full text

SVF: Support Vector Federation by Mirko Polato, Roberto Esposito, Lorenzo Sciandra

“…Simple random perturbation works remarkably well in practice, and indeed we provide a bound on the approximation error of the learnt model which goes to zero as the number of input features grows. …”
Get full text

Artificial Neural Network Framework for Hybrid Control and Monitoring in Turning Operations by Bogdan Felician Abaza, Vlad Gheorghita

“…This paper proposes a hybrid control and monitoring framework designed to enhance turning operations by integrating artificial neural networks (ANNs) for predictive modeling and adaptive recalibration. The system leverages machine learning (ML) to improve machining efficiency, tool longevity, and energy consumption optimization. …”
Get full text

DualPFL: A Dual Sparse Pruning Method with Efficient Federated Learning for Edge-Based Object Detection by Shijin Song, Sen Du, Yuefeng Song, Yongxin Zhu

“…To this end, we propose a novel communication-efficient federated learning framework, DualPFL (Dual Sparse Pruning Federated Learning), designed to address these issues by implementing dynamic sparse pruning and adaptive model aggregation strategies. The experimental results demonstrate that, compared to similar works, our framework can improve convergence speed by more than two times under non-IID data, achieving up to 84% accuracy on the CIFAR-10 dataset, 95% mean average precision (mAP) on the COCO dataset using YOLOv8, and 96% accuracy on the TT100K traffic sign datasets. …”
Get full text

Integrated artificial intelligence approach for well-log fluid identification in dual-medium tight sandstone gas reservoirs by Wurong Wang, Wurong Wang, Linbo Qu, Linbo Qu, Dali Yue, Dali Yue, Wei Li, Wei Li, Junlong Liu, Wujun Jin, Jialin Fu, Jialin Fu, Jiarui Zhang, Jiarui Zhang, Dongxia Chen, Dongxia Chen, Qiaochu Wang, Qiaochu Wang, Sha Li, Sha Li

“…Reservoir classification based on geological genetic mechanism significantly reduces data noise and prediction ambiguity, thereby improving the efficiency of model training.DiscussionThe final model is constructed by an ensemble method that integrates multiple sub-models, including fuzzy C-means clustering (FCM), gradient boosting decision tree (GBDT), backpropagation neural network (BPNN), random forests (RF), and light gradient boosting machines (LightGBM). …”
Get full text

Role of artificial intelligence in earlier diagnosis of bronchopulmonary dysplasia by Lam Q. Bui, Sandhya J. Kadam

“…A deep learning component can be used for lung segmentation of preterm chest radiographs to build a BPD prediction model by focusing on lung anatomy. This article explains the criteria used for BPD diagnosis and compares them with AI-based algorithms, especially for accuracy, applicability, and efficiency. …”
Get full text

Validation of the vertical canopy cover profile products derived from GEDI over selected forest sites by Yu Li, Hongliang Fang, Yao Wang, Sijia Li, Tian Ma, Yunjia Wu, Hao Tang

“…The partial difference between GEDI CC and ALS CC is attributed to definitional discrepancies. Further improvement of the CC algorithm can be made by using vegetation-specific waveform processing algorithms and realistic ρv/ρg values.…”
Get full text

First trimester circulating miR-208b-3p and miR-26a-1-3p are relevant to the prediction of gestational hypertension by Andrée-Anne Clément, Cécilia LÉGARÉ, Véronique Desgagné, Kathrine Thibeault, Frédérique White, Michelle S. Scott, Pierre-Étienne Jacques, William D Fraser, Patrice Perron, Renée Guérin, Marie-France Hivert, Anne-Marie Côté, Luigi Bouchard

“…The addition of miR-208b-3p, and miR-26a-1-3p to the model significantly improves the prediction performance over that of MAP alone (p = 0.03). …”
Get full text

A Robust Gaze Estimation Approach via Exploring Relevant Electrooculogram Features and Optimal Electrodes Placements by Zheng Zeng, Linkai Tao, Hangyu Zhu, Yunfeng Zhu, Long Meng, Jiahao Fan, Chen Chen, Wei Chen

“…The MAE and RMSE can be improved to 2.80° and 3.74° ultimately, while only using 10 features extracted from 2 channels. …”
Get full text