Closed-Loop Clustering-Based Global Bandwidth Prediction in Real-Time Video Streaming by Sepideh Afshar, Reza Razavi, Mohammad Moshirpour

“…To overcome these challenges, we propose closed-loop clustering-based Global Forecasting Models (GFMs) for SBP. Unlike local models, GFMs apply the same function to all traces enabling cross-learning, and leveraging relationships among traces to address the performance issues seen in current SBP algorithms. …”
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High-throughput phenotyping techniques for forage: Status, bottleneck, and challenges by Tao Cheng, Dongyan Zhang, Gan Zhang, Tianyi Wang, Weibo Ren, Feng Yuan, Yaling Liu, Zhaoming Wang, Chunjiang Zhao

“…These include establishing uniform data collection standards, designing effective algorithms to handle complex genetic and environmental interactions, deepening the cross-exploration of phenomics-genomics, solving the problem of pathological inversion of forage phenotypic growth monitoring models, and developing low-cost forage phenotypic equipment. …”
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Artificial intelligence applied to the study of human milk and breastfeeding: a scoping review by Sergio Agudelo-Pérez, Daniel Botero-Rosas, Laura Rodríguez-Alvarado, Julián Espitia-Angel, Lina Raigoso-Díaz

“…Prediction of exclusive breastfeeding patterns: AI models, such as decision trees and machine learning algorithms, identify factors influencing breastfeeding practices, including maternal experience, hospital policies, and social determinants, highlighting actionable predictors for intervention. 2. …”
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Dynamically Adapted Mesh Construction for the Efficient Numerical Solution of a Singular Perturbed Reaction-diffusion-advection Equation by Dmitry V. Lukyanenko, Vladimir T. Volkov, Nikolay N. Nefedov

“…This  work develops  a theory  of the  asymptotic-numerical investigation of the  moving fronts  in reaction-diffusion-advection models.  By considering  the  numerical  solution  of the  singularly perturbed Burgers’s  equation  we discuss a method  of dynamically  adapted mesh  construction that is able to significantly  improve  the  numerical  solution  of this  type of equations.  …”
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Machine Learning Applications in Use-Wear Analysis: A Critical Review by Anastasia Eleftheriadou, Shannon P. McPherron, João Marreiros

“…By addressing these factors, this paper facilitates the effective use of machine learning, enabling use-wear analysts and archaeologists to develop robust models that automate, accelerate, and improve their research.…”
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The Alliance of BIM and Artificial Intelligence: Challenges for a Reinvented Future – The State of the Art by Ellyssa Abdelmoula, Meriem Zammel, Najla Allani

“… The alliance of Building Information Modeling (BIM) and Artificial Intelligence (AI) is critical for transforming construction management, particularly to fostering more efficient and innovative practices. …”
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Current Topics on the Integration of Artificial Intelligence in the Histopathological and Molecular Diagnosis of Uveal Melanoma by Serena Salzano, Giuseppe Broggi, Andrea Russo, Teresio Avitabile, Antonio Longo, Rosario Caltabiano, Manuel Mazzucchelli

“…<b>Conclusions:</b> Despite these promising developments, this review acknowledges existing hurdles to AI implementation, including issues with data standardization and the interpretability of AI models. It emphasizes the need for further research to fully integrate AI into clinical workflows, ultimately aiming to improve patient care and outcomes.…”
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Research on AIGC-Driven Personalized Mathematics Learning System by Wang Chenggang

“…By integrating generative AI models, adaptive learning algorithms, and real-time feedback mechanisms, the system seeks to enhance student engagement, improve learning outcomes, and foster a deeper understanding of mathematical concepts. …”
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Transformer-Based Deep Learning for Mesoscale Eddy Detection in Sea Surface Temperature Maps by Chen Ji, Wenyang Xu, Xiangtian Zheng, Yasmeen Ahmed, Saad Ahmed Jamal, Fakhar Imam, Mohammed Saleh Ali Muthanna, Maha Ibrahim, Sajid Ullah, Dmitry E. Kucher

“…These eddies&#x2019; precise identification and categorization can improve climate modeling, ocean circulation research, and environmental surveillance. …”
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Artificial intelligence applications in pediatric ophthalmology: A comprehensive review by Anupama Janardhanan, Meenakshi Ravindran, Allapitchai Fathima, Neelam Pawar

“…Furthermore, it explores existing AI models and their applicability in diagnosing refractive errors and strabismus. …”
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Analysis of Energy Sustainability and Problems of Technological Process of Primary Aluminum Production by Yury Valeryevich Ilyushin, Egor Andreevich Boronko

“…The results of this study can be used to improve the energy efficiency and environmental friendliness of aluminum production.…”
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Panoramic radiographic features for machine learning based detection of mandibular third molar root and inferior alveolar canal contact by A. Canberk Ulusoy, Tuğçe Toprak, M. Alper Selver, Pelin Güneri, Betül İlhan

“…Future work should focus on developing automated segmentation algorithms for M3M and IAC on PRs, to identify relevant anatomical structures, thereby improving clinical usability. …”
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AI-Driven Innovation in Skin Kinetics for Transdermal Drug Delivery: Overcoming Barriers and Enhancing Precision by Nubul Albayati, Sesha Rajeswari Talluri, Nirali Dholaria, Bozena Michniak-Kohn

“…Advances in artificial intelligence (AI) address these challenges through predictive modeling and personalized medicine approaches. Machine learning models trained on extensive molecular datasets predict skin permeability and accelerate the selection of suitable drug candidates. …”
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Tracing the Evolution and Legacy of Professor A.P. Iofinov’s Scientific School by S. G. Mudarisov, R. R. Kamaletdinov

“…Furthermore, they have played a crucial role in the creation of digital twins for agricultural machines, based on models of technological processes. This advancement significantly enhances the precision and efficiency in resource utilization, improves the quality of work, and boosts productivity in agriculture.…”
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Leveraging Deep Spatiotemporal Sequence Prediction Network with Self-Attention for Ground-Based Cloud Dynamics Forecasting by Sheng Li, Min Wang, Minghang Shi, Jiafeng Wang, Ran Cao

“…Compared with other spatiotemporal sequence prediction models, CloudPredRNN++ shows significant improvements in evaluation metrics, improving the accuracy of cloud dynamics forecasting and alleviating long-term dependency decay, thus confirming the effectiveness in ground-based cloud prediction tasks.…”
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The Impact of a Deep Learning Self-Adaptive Colour Restoration Pipeline for Deep Underwater Images in 3D Reconstruction by M. Vlachos, D. Skarlatos, S. Demesticha

“…The proposed approach leverages deep learning to correct colour distortions without relying on physical models of underwater light propagation. Evaluation was performed using established feature detection algorithms, such as SIFT and SURF, applied to multiple underwater datasets capturing diverse imaging conditions. …”
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Scientific Machine Learning for Elastic and Acoustic Wave Propagation: Neural Operator and Physics-Guided Neural Network by Nafisa Mehtaj, Sourav Banerjee

“…Through comparative analysis of existing NO algorithms applied across different engineering fields, this study demonstrates how NOs improve generalization, accelerate inference, and enhance scalability for practical wave modeling scenarios. …”
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Advances in Aircraft Skin Defect Detection Using Computer Vision: A Survey and Comparison of YOLOv9 and RT-DETR Performance by Nutchanon Suvittawat, Christian Kurniawan, Jetanat Datephanyawat, Jordan Tay, Zhihao Liu, De Wen Soh, Nuno Antunes Ribeiro

“…Beyond a detailed review, we experimentally evaluate the accuracy and feasibility of existing low-cost, easily deployable hardware (drone) and software solutions (computer vision algorithms). Specifically, real-world data were collected from an abandoned aircraft with visible defects using a drone to capture video footage, which was then processed with state-of-the-art computer vision models—YOLOv9 and RT-DETR. …”
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Advancements in epilepsy classification: Current trends and future directions by Rajani Rai B, Karunakara Rai B, Mamatha A S, Kavitha Sooda

“…The paper synthesizes cutting-edge techniques with the focus on the application of hybrid models that combine traditional signal processing techniques with machine learning algorithms. …”
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Key Role and Optimization Dispatch Research of Technical Virtual Power Plants in the New Energy Era by Weigang Jin, Peihua Wang, Jiaxin Yuan

“…For each method, this review presents its mathematical models and solution algorithms. This review highlights the significance of TVPPs in enhancing power system flexibility, improving renewable energy integration, and providing ancillary services. …”
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