Enhancing Online Learning Through Multi-Agent Debates for CS University Students by Jing Du, Guangtao Xu, Wenhao Liu, Dibin Zhou, Fuchang Liu

“…This lack of trust can potentially undermine the effectiveness of learning in educational scenarios. To address these issues, we introduce a novel approach that integrates multi-agent debates into a lecture video Q&A system, aiming to assist computer science (CS) university students in self-learning by using LLMs to simulate debates between affirmative and negative debaters and a judge to reach a final answer and presenting the entire process to users for review. …”
Get full text

KNEE OSTEOARTHRITIS STAGE CLASSIFICATION BASED ON HYBRID FUSION DEEP LEARNING FRAMEWORK by Delveen Luqman Abd Alnabi, Shereen Sh Ahmed, Nisreen Luqman Abd Alnabi

“…Handling huge number of X-ray images and the ability to detect the correct disease stage is based on advanced artificial intelligence technologies, like machine learning and deep learning. This study presents a novel deep learning-based fusion framework designed for detecting the severity of knee osteoarthritis and classifying its stages. …”
Get full text

Multi-Objective Machine Learning Optimization of Cylindrical TPMS Lattices for Bone Implants by Mansoureh Rezapourian, Ali Cheloee Darabi, Mohammadreza Khoshbin, Irina Hussainova

Get full text

Cognitive Learning, Monitoring and Assistance of Industrial Workflows Using Egocentric Sensor Networks. by Gabriele Bleser, Dima Damen, Ardhendu Behera, Gustaf Hendeby, Katharina Mura, Markus Miezal, Andrew Gee, Nils Petersen, Gustavo Maçães, Hugo Domingues, Dominic Gorecky, Luis Almeida, Walterio Mayol-Cuevas, Andrew Calway, Anthony G Cohn, David C Hogg, Didier Stricker

“…Being entirely learning-based, the proposed system can be applied to various tasks and domains. …”
Get full text

Automatic Restoration of Dunhuang Murals and Process Visualization Method Based on Deep Learning by Miao Jia, Jie Hu, Zhongliang Yang, Weijie Liu, Jin Qi, Bin Chen

“…In addition, we propose a method for constructing and preserving the contour maps of mural images and present the model’s training process. Using the deep learning model, professional restorers can provide visual feedback on the restoration process to directly compare the restoration patterns of different rounds. …”
Get full text

Federated Synergy: Hierarchical Multi-Agent Learning for Sustainable Edge Computing in IIoT by S. Benila, K. Devi

“…This novel approach integrates hierarchical reinforcement learning with multi-agent federated learning to enhance decision-making in dynamic edge computing environments. …”
Get full text

Machine learning-based prediction of shear strength in interior beam-column joints by Iman Kattoof Harith, Wissam Nadir, Mustafa S. Salah, Ahmed Y. Mohammed, Mohammed L. Hussien

Get full text

Benchmarking Deep Learning for Wetland Mapping in Denmark Using Remote Sensing Data by Muhammad Rizwan Asif

“…Therefore, this article presents a comprehensive benchmark analysis of several DL models for wetland classification in Denmark. …”
Get full text

The European Social Fund and Popularizing Lifelong Learning and Vocational Education in the Lubelskie Voivodship by Krzysztof Grabczuk

“… The accession of Poland to the European Union created both new opportunities and tasks for many entities. This article presents the analysis of the use of the European funds from the European Social Fund for vocational education (9.2 Improvement of the quality and attractiveness of vocational training) and lifelong learning (9.3 Popularizing formal lifelong learning in school forms). …”
Get full text

Explainable few-shot learning workflow for detecting invasive and exotic tree species by Caroline M. Gevaert, Alexandra Aguiar Pedro, Ou Ku, Hao Cheng, Pranav Chandramouli, Farzaneh Dadrass Javan, Francesco Nattino, Sonja Georgievska

“…This research presents a workflow that tackles both challenges by proposing an explainable few-shot learning workflow for detecting invasive and exotic tree species in the Atlantic Forest of Brazil using Unmanned Aerial Vehicle (UAV) images. …”
Get full text

Combined Application of Deep Learning and Radiomic Features for Classification of Lung CT Images by Shariati Faridoddin, V. A. Pavlov

“…Lung cancer, distinguished by its heterogeneity, presents significant challenges in diagnosis and treatment, requiring innovative approaches for precise mutation classification.Aim. …”
Get full text

The effects of summer learning on social-emotional and behavioral outcomes: A meta-analysis by Kathleen Lynch, Lindsay Lanteri, Lily An, Zid Mancenido, Jennifer Richardson

“…We present a comprehensive meta-analysis of the effects of summer learning programs on PK–12 students’ SEL outcomes.The meta-analysis indicates that summer learning programs can have significant positive effects on students’ SEL outcomes, suggesting that summer programs have the potential to improve both academic and SEL competencies.Researchers and policymakers can use these findings to inform decision-making regarding summer learning programs’ design and implementation, as well as future research that can further strengthen the evidence base.…”
Get full text

Domain-incremental white blood cell classification with privacy-aware continual learning by Pratibha Kumari, Afshin Bozorgpour, Daniel Reisenbüchler, Edgar Jost, Martina Crysandt, Christian Matek, Dorit Merhof

“…Experimental results demonstrate that conventional fine-tuning methods degrade performance on previously learned tasks and struggle with domain shifts. In contrast, our continual learning strategy effectively mitigates catastrophic forgetting, preserving model performance across varying domains. …”
Get full text

Interpretable Prediction and Analysis of PVA Hydrogel Mechanical Behavior Using Machine Learning by Liying Xu, Siqi Liu, Anqi Lin, Zichuan Su, Daxin Liang

“…However, rational design remains challenging due to complex structure–property relationships involving multiple formulation parameters. This study presents an interpretable machine learning framework for predicting PVA hydrogel tensile strain properties with emphasis on mechanistic understanding, based on a comprehensive dataset of 350 data points collected from a systematic literature review. …”
Get full text

A Quantum Q-Learning Fault Diagnosis Method for Intelligent Manufacturing Equipment by Yi Chen, Kai Deng, Xuelin Du, Zichao Chang, Tong Wan

“…To address these challenges, a novel fault diagnosis approach grounded in quantum Q-learning is presented in this paper. The distinct advantages of quantum computing are innovatively integrated with the decision-making framework of Q-learning through this method. …”
Get full text

Reconstructing Molecular Networks by Causal Diffusion Do‐Calculus Analysis with Deep Learning by Jiachen Wang, Yuelei Zhang, Luonan Chen, Xiaoping Liu

“…This study introduces a novel approach that combines intervention operations and diffusion models within a do‐calculus framework by deep learning, i.e., Causal Diffusion Do‐calculus (CDD) analysis, to infer causal networks between molecules. …”
Get full text

Evaluating the Quality of AI-Generated Digital Educational Resources for University Teaching and Learning by Qian Huang, Chunlan Lv, Li Lu, Shuang Tu

“…With the proliferation of artificial intelligence in education, AI-generated digital educational resources are increasingly being employed as supplements for university teaching and learning. However, this raises concerns about the quality of the content produced. …”
Get full text

Stroma and lymphocytes identified by deep learning are independent predictors for survival in pancreatic cancer by Xiuxiang Tan, Mika Rosin, Simone Appinger, Julia Campello Deierl, Konrad Reichel, Mariëlle Coolsen, Liselot Valkenburg-van Iersel, Judith de Vos-Geelen, Evelien J. M. de Jong, Jan Bednarsch, Bas Grootkoerkamp, Michail Doukas, Casper van Eijck, Tom Luedde, Edgar Dahl, Jakob Nikolas Kather, Shivan Sivakumar, Wolfram Trudo Knoefel, Georg Wiltberger, Ulf Peter Neumann, Lara R. Heij

“…To dig more information and identify potential biomarkers from PDAC pathological slides, we trained a deep learning (DL) model based U-net-shaped backbone. This DL model can automatically detect tumor, stroma and lymphocytes on whole slide images (WSIs) of PDAC patients. …”
Get full text

Evaluating the impact of metabolic indicators and scores on cardiovascular events using machine learning by Guanmou Li, Cheng Luo, Teng Ge, Kunyang He, Miao Zhang, Jinlin Hu, Baoshi Zheng, Rongjun Zou, Xiaoping Fan

“…This research highlights the significance of metabolic indices in stratifying cardiovascular risks and presents potential avenues for targeted preventive strategies.…”
Get full text

Identifying thermokarst lakes using deep learning and high-resolution satellite images by Kuo Zhang, Min Feng, Yijie Sui, Jinhao Xu, Dezhao Yan, Zhimin Hu, Fei Han, Earina Sthapit

“…Due to the typically small sizes and highly dynamic nature of thermokarst lakes, their identification in large regions remains challenging. This study presented a deep-learning model and applied it to high-resolution (1.2 m) satellite imagery to automatically delineate and inventory thermokarst lakes. …”
Get full text