An approach to forecasting damage due to unfavorable circumstances associated with indistinguishability of source data by V. F. Zolotukhin, A. V. Matershev, L. A. Podkolzina

“…The efficiency of predicting damage to complex systems depends directly on the quality of processing methods, systematization, and the amount of input data. …”
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Mapping the Research Landscape of Agricultural Sciences by Dmitry Devyatkin, Elena Nechaeva, Roman Suvorov, Ilya Tikhomirov

“…Further research on this subject includes the application of the framework to other scientific fields and the integration of other collections of research and technical documentation (especially patents). …”
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Rate-Adaptive LiDAR Point Cloud Streaming Over LEO Satellite Networks by Dominic Laniewski, Nils Aschenbruck

“…We develop a novel, real-time capable rate-adaptation algorithm leveraging Google Draco. It predicts optimal encoding parameters for each mini point cloud to maximize the point cloud quality under varying network conditions. …”
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Simulation and Modelling of C+L+S Multiband Optical Transmission for the OCATA Time Domain Digital Twin by Prasunika Khare, Nelson Costa, Marc Ruiz, Antonio Napoli, Jaume Comellas, Joao Pedro, Luis Velasco

“…In view of that, the fourth-order Runge–Kutta in the interaction picture (RK4IP) method, complemented with an adaptive step size algorithm to further reduce the computation time, is evaluated as an alternative to reduce time complexity. …”
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Information Bottleneck-Based Domain Adaptation for Hybrid Deep Learning in Scalable Network Slicing by Tianlun Hu, Qi Liao, Qiang Liu, Georg Carle

“…Evaluating on a multi-cell network with time-varying slice configurations, the VIB-enhanced IDLA algorithm outperforms baselines such as heuristic and deep reinforcement learning-based solutions, achieving twice the convergence speed and 16.52% higher asymptotic performance after slicing configuration changes. …”
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Protecting vulnerable people during pandemics through home delivery of essential supplies: a distribution logistics model by Eric Breitbarth, Wendelin Groβ, Alexander Zienau

“…The purpose of this paper is to evaluate feasible and resource-efficient home delivery strategies, including collaboration between retailers and logistics service providers based on a practical application. …”
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Optimal Dual Control Strategy for Multi-Interconnected Microgrids Under Unintentional Islanding and Fault Scenarios by H. K. Shaker, Ines Mahmoud, Magdi A. Mosa, K. M. Abdel-Latif, A. A. Ali, H. E. Keshta

“…Conventional fixed-parameter linear controllers such as PI and droop controllers are widely used in MG applications; however, they may not be efficient at rejecting disturbances to MGs. …”
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Feasibility of Implementing Motion-Compensated Magnetic Resonance Imaging Reconstruction on Graphics Processing Units Using Compute Unified Device Architecture by Mohamed Aziz Zeroual, Natalia Dudysheva, Vincent Gras, Franck Mauconduit, Karyna Isaieva, Pierre-André Vuissoz, Freddy Odille

“…Across all datasets, the normalized root mean square error (NRMSE) remained on the order of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mn>10</mn><mrow><mo>−</mo><mn>6</mn></mrow></msup></semantics></math></inline-formula> to <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mn>10</mn><mrow><mo>−</mo><mn>4</mn></mrow></msup></semantics></math></inline-formula>, indicating that the CUDA-accelerated method preserved image quality. Furthermore, a roofline analysis was conducted to quantify the kernel’s performance on one of the evaluated datasets. …”
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Lumen Degradation Lifetime Prediction for High-Power White LEDs Based on the Gamma Process Model by Mesfin Seid Ibrahim, Jiajie Fan, Winco K.C. Yung, Zeyu Wu, Bo Sun

“…The lifetime prediction results show that the accuracy of the proposed method is much better than the TM-21 nonlinear least squares (NLS) approach which makes it promising for future industrial applications.…”
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Quantitative comparison of a novel swept-source optical coherence tomography angiography device with three established systems by Michael Hafner, Siegfried G. Priglinger, Bettina von Livonius, Maximilian J. Gerhardt

“…These findings suggest that DREAM OCT is a promising tool for deep retinal imaging, with strong potential for clinical application and research.…”
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Nav2Scene: Navigation-driven fine-tuning for robot-friendly scene generation by Bowei Jiang, Tongyuan Bai, Peng Zheng, Tieru Wu, Rui Ma

“…Specifically, we first introduce path planning score (PPS), which is defined based on the results of the path planning algorithm and can be used to evaluate the robot navigation suitability of a given scene. …”
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Comparison of Electronic Surveillance With Routine Monitoring for Patients With Lymphoma at High Risk of Relapse: Prospective Randomized Controlled Phase 3 Trial (Sentinel Lymphoma... by Katell Le Dû, Adrien Chauchet, Sophie Sadot-Lebouvier, Olivier Fitoussi, Bijou Fontanet, Arnaud Saint-Lezer, Frédéric Maloisel, Cédric Rossi, Sylvain Carras, Anne Parcelier, Magali Balavoine, Anne-Lise Septans

“…We evaluated the effect of a web-mediated follow-up application for patients with lymphoma at high risk of relapse. …”
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The diagnostic and prognostic capability of artificial intelligence in spinal cord injury: A systematic review by Saran Singh Gill, Hariharan Subbiah Ponniah, Sho Giersztein, Rishi Miriyala Anantharaj, Srikar Reddy Namireddy, Joshua Killilea, DanieleS.C. Ramsay, Ahmed Salih, Ahkash Thavarajasingam, Daniel Scurtu, Dragan Jankovic, Salvatore Russo, Andreas Kramer, Santhosh G. Thavarajasingam

“…Method: ology: The primary aim was to evaluate the performance of AI algorithms in diagnosing and prognosticating tSCI. …”
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A machine learning model for predicting obesity risk in patients with diabetes mellitus: analysis of NHANES 2007–2018 by Wenqiang Wang, Ruiqing Mo, Xingyu Chen, Sijie Yang

“…The best-performing model was visualized using a nomogram to enhance clinical applicability.ResultsA total of 3,794 participants with type 2 diabetes were included in the analysis, of whom 57.0% were classified as obese. …”
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Construction and Simulation of a Strategic HR Decision Model Based on Recurrent Neural Network by Xiaorong Li, Lijun Zhang, Dongchen Li, Dan Guo

“…In this paper, RNN (Recurrent Neural Network) algorithm is used to conduct an in-depth analysis of HR strategic decision-making and an HR strategic decision model is constructed for simulation. …”
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Parsimonious and explainable machine learning for predicting mortality in patients post hip fracture surgery by Fouad Trad, Bassel Isber, Ryan Yammine, Khaled Hatoum, Dana Obeid, Mohammad Chahine, Rachid Haidar, Ghada El-Hajj Fuleihan, Ali Chehab

“…In this study, we developed machine learning (ML) algorithms to estimate 30-day mortality risk post-hip fracture surgery in the elderly using data from the National Surgical Quality Improvement Program (NSQIP 2012–2017, n = 62,492 patients). …”
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SK-TreePCN: Skeleton-Embedded Transformer Model for Point Cloud Completion of Individual Trees from Simulated to Real Data by Haifeng Xu, Yongjian Huai, Xun Zhao, Qingkuo Meng, Xiaoying Nie, Bowen Li, Hao Lu

“…SK-TreePCN demonstrates applicability and robustness in recovering individual tree point clouds. …”
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Intelligent Methods of Operational Response to Accidents in Urban Water Supply Systems Based on LSTM Neural Network Models by Aliaksey A. Kapanski, Nadezeya V. Hruntovich, Roman V. Klyuev, Aleksandr E. Boltrushevich, Svetlana N. Sorokova, Egor A. Efremenkov, Anton Y. Demin, Nikita V. Martyushev

“…This paper investigates the application of recurrent neural networks, specifically Long Short-Term Memory (LSTM) models, for pressure forecasting in urban water supply systems. …”
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A salient feature establishment tactic for cassava disease recognition by Jiayu Zhang, Baohua Zhang, Zixuan Chen, Innocent Nyalala, Kunjie Chen, Junfeng Gao

“…These results suggest that the proposed algorithm is well suited for cassava leaf disease classification applications and offers a robust solution for advancing agricultural technology.…”
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Machine learning frameworks to accurately predict coke reactivity index by Ayat Hussein Adhab, Morug Salih Mahdi, Krunal Vaghela, Anupam Yadav, Jayaprakash B, Mayank Kundlas, Ankur Srivastava, Jayant Jagtap, Aseel Salah Mansoor, Usama Kadem Radi, Nasr Saadoun Abd, Samim Sherzod

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