Graph neural processes for molecules: an evaluation on docking scores and strategies to improve generalization by Miguel García-Ortegón, Srijit Seal, Carl Rasmussen, Andreas Bender, Sergio Bacallado

“…So far, most studies of NPs have focused on low-dimensional datasets of highly-correlated tasks. While these homogeneous datasets are useful for benchmarking, they may not be representative of realistic transfer learning. …”
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Leveraging machine learning for data-driven building energy rate prediction by Nasim Eslamirad, Mehdi Golamnia, Payam Sajadi, Francesco Pilla

“…This paper presents a novel, data-driven approach for predicting Building Energy Ratings (BER) in urban environments, using advanced Machine Learning (ML) algorithms. Focusing on Dublin, we integrate diverse geospatial datasets with building-specific and neighbourhood-scale features to classify BER. …”
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Probing the Pitfalls: Understanding SVD’s Shortcomings in Language Model Compression by Сергей Александрович Плетенев

“…However, targeted compression approaches, such as selectively compressing the most redundant parts of the model or weighting algorithms, mitigated these negative effects. Conclusion:  These results demonstrate that factorization, when used properly, can significantly reduce computational requirements while preserving the core linguistic capabilities of large language models. …”
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Synthetic Financial Data: A Case Study Regarding Polish Limited Liability Companies Data by Aleksandra Szymura

“…This action allows data to be shared externally while guaranteeing their privacy. Methodology: New datasets were generated based on financial information about Polish limited liability companies, which come from the Orbis database and refers to 2020. …”
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A Lightweight Model for Shine Muscat Grape Detection in Complex Environments Based on the YOLOv8 Architecture by Changlei Tian, Zhanchong Liu, Haosen Chen, Fanglong Dong, Xiaoxiang Liu, Cong Lin

“…Automated harvesting of “Sunshine Rose” grapes requires accurate detection and classification of grape clusters under challenging orchard conditions, such as occlusion and variable lighting, while ensuring that the model can be deployed on resource- and computation-constrained edge devices. …”
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Optimization of Adaptive Observation Strategies for Multi-AUVs in Complex Marine Environments Using Deep Reinforcement Learning by Jingjing Zhang, Weidong Zhou, Xiong Deng, Shuo Yang, Chunwang Yang, Hongliang Yin

“…Additionally, experiments with three, five, and seven AUVs reveal that while increasing platform numbers enhances predictive accuracy, the benefits diminish with additional units.…”
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Executive summary: indonesian guidelines on polycystic ovary syndrome management by Mila Maidarti, Achmad Kemal Harzif, Amalia Shadrina, Nafi'atul Ummah, Wiryawan Permadi

“…The levels of available health services and management algorithms for PCOS in Indonesia are also included. …”
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Classification of Metallic Powder Morphology Using Traditional and Automated Static Image Analysis: A Comparative Study by Cindy Charbonneau, Fabrice Bernier, Étienne Perrault, Roger Pelletier, Louis-Philippe Lefebvre

“…The results from shape descriptors can vary based on image resolution, gray/color thresholding, and software algorithms. There are various commercial systems available for characterizing particle shape, some of which use images taken of static particles, while others use images of particles in motion. …”
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Capsule Endoscopy Image Enhancement for Small Intestinal Villi Clarity by Shaojie Zhang, Yinghui Wang, Peixuan Liu, Yukai Wang, Liangyi Huang, Mingfeng Wang, Ibragim Atadjanov

“…This approach improves edge detail while suppressing noise and avoiding edge overshoot, providing clearer images for diagnosis. …”
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The role of artificial intelligence in enhancing personalized learning pathways and clinical training in dental education by Chengchen Hu, Fang Li, Shengguo Wang, Zhi Gao, Shan Pan, Maofeng Qing

“…Moreover, AI-driven innovations in dental biomaterials are optimizing material selection and prosthetic design, while robotic-assisted systems are enhancing precision in clinical training and treatment procedures. …”
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Enhanced Fishing Monitoring in the Central-Eastern North Pacific Using Deep Learning with Nightly Remote Sensing by Jiajun Li, Jinyou Li, Kui Zhang, Xi Li, Zuozhi Chen

“…In this study, enhanced fishing extraction algorithms based on computer vision were developed and tested. …”
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Intelligent System for Reducing Waste and Enhancing Efficiency in Copper Production Using Machine Learning by Bagdaulet Kenzhaliyev, Timur Imankulov, Aksultan Mukhanbet, Sergey Kvyatkovskiy, Maral Dyussebekova, Nurdaulet Tasmurzayev

“…Forward prediction achieved near-perfect accuracy, while backward prediction highlighted the inherent complexity of inverse modeling. …”
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Wearable Spine Tracker vs. Video-Based Pose Estimation for Human Activity Recognition by Jonas Walkling, Luca Sander, Arwed Masch, Thomas M. Deserno

“…The FlexTail model performs better for detecting sitting and transitions, like standing up, while the camera-based model is better for activities that involve arm and hand movements.…”
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Transceiver Design for an FDA-MIMO Radar and MIMO Communication Spectral Coexistence System by Qihang XU, Lan LAN, Guisheng LIAO, Kewei WANG, Tongxing ZHENG

“…In addition, the communication transmission codebook is approximated using an inequality theorem, and the radar transmission waveform is optimized using Taylor expansion and relaxation algorithms. Simulation results reveal that this joint design method can effectively improve the SINR of the radar system while ensuring communication throughput, thereby considerably enhancing the performance of the FDA-MIMO radar and MIMO communication spectral coexistence system under mainlobe jamming conditions.…”
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A HRWS SAR Motion Compensation Method with Multichannel Phase Correction by Liming Zhou, Minglong Deng, Jing He, Bing Wang, Shengmiao Zhang, Xuanyu Liu, Shunjun Wei

“…Many motion compensation algorithms have been used to improve the quality of single-channel SAR images, while fewer studies have been conducted on multichannel SAR motion compensation methods. …”
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Revolutionizing Education with Artificial Intelligence (AI)? Challenges, and Implications for Open and Distance Learning (ODL) by Mohd Rushidi Mohd Amin, Ismaanzira Ismail, Vinesh Maran Sivakumaran

“…This transformative technology holds the potential to revolutionize education delivery through personalized learning algorithms, adaptive learning, and intelligent tutoring systems, tailoring educational experiences to individual students. …”
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A GPU parallelization of the neXtSIM-DG dynamical core (v0.3.1) by R. Jendersie, R. Jendersie, C. Lessig, C. Lessig, T. Richter

“…Based on our assessment of usability and performance, CUDA demonstrates the best performance while Kokkos is a suitable option for its robust heterogeneous computing capabilities. …”
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Optimizing Skin Quality via AI-Enhanced Physical Activity by Niki Tertipi, Eleni Sfyri, Vasiliki Sofia Grech, Vasiliki Kefala, Efstathios Rallis

“…., UV exposure and pollution levels). AI algorithms process this data to create dynamic, adaptive exercise routines designed to maximize skin benefits while minimizing potential harm (e.g., exercise-induced oxidative stress in sensitive skin types). …”
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Mitigating Catastrophic Forgetting in Pest Detection Through Adaptive Response Distillation by Hongjun Zhang, Zhendong Yin, Dasen Li, Yanlong Zhao

“…Our method effectively reduces catastrophic forgetting during incremental learning, enabling the student detector to maintain memory of old classes while assimilating new pest categories. Experimental evaluations on the large-scale IP102 pest dataset demonstrate that the proposed ARD method consistently outperforms existing state-of-the-art algorithms across various class-incremental learning scenarios, significantly narrowing the performance gap compared to fully trained models.…”
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Configuring Transmission Thresholds in IIoT Alarm Scenarios for Energy-Efficient Event Reporting by David E. Ruiz-Guirola, Onel L. A. Lopez, Samuel Montejo-Sanchez

“…In low-density scenarios, all proposed methods outperform the benchmark, while in high-density scenarios, only Voronoi-(i), K-nearest neighbors, and Q-learning show better performance. …”
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