Real-time congestion control using cascaded LSTM deep neural networks for deregulated power markets by G. Madhu Mohan, T. Anil Kumar, A. Srujana, Yasser Fouad, Alexey Mikhaylov, Nora Baranyai, Kitmo, Ch. Rami Reddy

“…Owing to their computational inefficiency, evolutionary algorithms (EAs) are ineffective for real-time congestion management, necessitating hybrid models to deliver rapid solutions. …”
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Local Diversity-Guided Weakly Supervised Fine-Grained Image Classification Method by Yuebo Meng, Xianglong Luo, Hua Zhan, Bo Wang, Shilong Su, Guanghui Liu

“…Extensive experiments conducted on four fine-grained datasets and explainable visualization demonstrate that the LDGNet can effectively enhance discriminative region localization and detailed feature acquisition for fine-grained objects, achieving competitive performance over other state-of-the-art algorithms.…”
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Scalable Semantic Adaptive Communication for Task Requirements in WSNs by Hong Yang, Xiaoqing Zhu, Jia Yang, Ji Li, Linbo Qing, Xiaohai He, Pingyu Wang

“…The experimental results show that the proposed SSAC is more robust than traditional and other semantic communication algorithms in image classification tasks, and achieves scalable compression rates without sacrificing classification performance, while improving the bandwidth utilization of the communication system.…”
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Human-in-the-Loop Optimization of the Stiffness and Alignment of a Prosthetic Foot to Reduce the Metabolic Cost of Walking by Thijs Tankink, Han Houdijk, Johnnidel Tabucol, Marco Leopaldi, Juha M. Hijmans, Raffaella Carloni

“…Walking on the prosthetic foot with optimized settings during the post-test resulted in a significant reduction in metabolic cost compared to the pre-test with standard settings (−10.6%). …”
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REST Network: An Ensemble Deep Learning Approach for EV Charging Load Forecasting in Artificial Port Supply Chains by Elham Abdullah Alghamdi, Monagi Hassan Alkinani, Abdulwahab Ali Almazroi, Mohammed Alqarni, Eman Ali Aldhahri, Nasir Ayub

“…Traditional forecasting algorithms can fail to address logistics’ complicated, variable charge patterns and uneven data. …”
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Effect of Achieving Sustained SDAI Remission on Erosion Healing in Early Rheumatoid Arthritis - A One-year Prospective HR-pQCT Study by Qihan Wu, Ho So, Tsz-Ho Cheng, Yingzhao Jin, Sze-Lok Lau, Lai-shan Tam

“…After 12 months, a significant reduction in erosion volume and marginal osteosclerosis was observed in both groups. …”
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The Influence of Process and Slag Parameters on the Liquid Slag Layer in Continuous Casting Mold for Large Billets by Zhijun Ding, Chao Wang, Xin Wang, Pengcheng Xiao, Liguang Zhu, Shuhuan Wang

“…Increasing argon flow rate from 0.50 L·min⁻¹ to 1.00 L·min⁻¹ leads to 350 mm deeper bubble penetration, 10 mm reduction in jet penetration depth, 0.002 m·s⁻¹ increase in meniscus velocity, and decreased meniscus temperature due to bubble cooling. …”
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Machine learning-based construction of Immunogenic cell death-related score for improving prognosis and personalized treatment in glioma by Guoyin Li, Yukui Zhao, Yubo He, Zhaoqiang Qian, Yiwen Liu, Xiaoyan Li, Lili Li, Zhiqiang Liu

“…CIBERSORT and ESTIMATE algorithms were employed to evaluate the infiltration of immune cells. …”
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Enhancing noninvasive pancreatic cystic neoplasm diagnosis with multimodal machine learning by Wei Huang, Yue Xu, Zhao Li, Jun Li, Qing Chen, Qiang Huang, Yaping Wu, Hongtan Chen

“…The study’s results indicate that our multimodal machine learning algorithm, which integrates both clinical and imaging data, significantly outperforms single-source data algorithms. …”
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Fractional Optimizers for LSTM Networks in Financial Time Series Forecasting by Mustapha Ez-zaiym, Yassine Senhaji, Meriem Rachid, Karim El Moutaouakil, Vasile Palade

“…We extend several widely used optimization algorithms—including Adam, RMSprop, SGD, Adadelta, FTRL, Adamax, and Adagrad—by incorporating fractional derivatives into their update rules. …”
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Artificial Intelligence Approaches for Geographic Atrophy Segmentation: A Systematic Review and Meta-Analysis by Aikaterini Chatzara, Eirini Maliagkani, Dimitra Mitsopoulou, Andreas Katsimpris, Ioannis D. Apostolopoulos, Elpiniki Papageorgiou, Ilias Georgalas

“…This systematic review evaluates the performance of AI algorithms for GA segmentation and highlights their key limitations from the literature. …”
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The Performance of an ML-Based Weigh-in-Motion System in the Context of a Network Arch Bridge Structural Specificity by Dawid Piotrowski, Marcin Jasiński, Artur Nowoświat, Piotr Łaziński, Stefan Pradelok

“…In civil and bridge engineering, they can facilitate the identification of specific patterns through the analysis of data acquired from structural health monitoring (SHM) systems. To evaluate the prediction capabilities of ML, this study examines the performance of several ML algorithms in estimating the total weight and location of vehicles on a bridge using strain sensing. …”
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Real-time classification of EEG signals using Machine Learning deployment by Swati CHOWDHURI, Satadip SAHA, Samadrita KARMAKAR, Ankur CHANDA

“…This study proposes a machine learning-based approach for predicting the level of students' comprehension with regard to a certain topic. …”
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Review of Urban Rail Transit Ticket Clearing Methods by WANG Yao, LI Jiming, GAO Shen, LIU Guangjie, XU Zhongquan

“…A more scientific and reasonable clearing scheme needs to further strengthen big data research on the AFC (automatic fare collection) system, and more importantly, relying on existing technologies and computing models is required to strengthen the real-time analysis and overtime prediction accuracy of passengers′ path selection behavior, so as to enable the clearing mechanism accurately make adaptive dynamic adjustments according to actual operating conditions.…”
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IMU-LiDAR integrated SLAM technology for unmanned driving in mines by HU Qingsong, LI Jingwen, ZHANG Yuansheng, LI Shiyin, SUN Yanjing

“…In this study, a roadway environment feature-assisted SLAM algorithm integrating inertial measurement unit (IMU) and LiDAR was proposed. …”
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Volcano activity classification from synergy of EO data and machine learning: an application to Mount Etna volcano (Italy) by C. Petrucci, G. Romoli, A. Pignatelli, E. Trasatti, F. Zuccarello, F. Greco, M. Dozzo, G. Bilotta, F. Spina, G. Ganci

“…These findings are one of the first attempts of integrating satellite data with Artificial Intelligence (AI) to enhance the accuracy of volcanic state predictions and mitigate risks associated with eruptions, while emphasizing the need for rigorous validation against well-documented case studies.…”
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MFGC-Net: Bridging and Fusing Multiscale Features and Global Contexts for Multitask Sea Ice Fine Segmentation by Tianen Ma, Xinwei Chen, Linlin Xu, Pengfei Ma, Peilin Yu

“…Sea ice segmentation from synthetic aperture radar (SAR) imagery is a key task in polar sea ice monitoring, which is crucial for global climate prediction and polar route planning. However, the existing sea ice segmentation algorithms for SAR images often fail to consider long-range contextual dependencies when capturing multiscale features, resulting in an inability to fully exploit multiscale global contextual information. …”
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Differentiable Deep Learning Surrogate Models Applied to the Optimization of the IFMIF-DONES Facility by Galo Gallardo Romero, Guillermo Rodríguez-Llorente, Lucas Magariños Rodríguez, Rodrigo Morant Navascués, Nikita Khvatkin Petrovsky, Rubén Lorenzo Ortega, Roberto Gómez-Espinosa Martín

“…Specifically, neural operators are employed to predict deuteron beam envelopes along the longitudinal axis of the accelerator and neutron irradiation effects at the end, after the beam collision. …”
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Two-Way Feature Extraction Using Sequential and Multimodal Approach for Hateful Meme Classification by Apeksha Aggarwal, Vibhav Sharma, Anshul Trivedi, Mayank Yadav, Chirag Agrawal, Dilbag Singh, Vipul Mishra, Hassène Gritli

“…These approaches utilize a combination of glove, encoder-decoder, and OCR with Adamax optimizer deep learning algorithms. Facebook Challenge Hateful Meme Dataset is utilized which contains approximately 8500 meme images. …”
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Identifying and mapping open-boll cotton fields in the southeastern United States with time series PhenoCam, Sentinel-2 and Sentinel-1 images by Fang Liu, Xiangming Xiao, Yuanwei Qin, Luo Liu

“…The starting dates of the open-boll period varied across the southeastern United States, mainly ranging from the day of the year (DOY) 244 to 304 (September and October). The color-based algorithm performed well in multiple years and different regions, demonstrating the algorithm’s robustness and potential for regional application. …”
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