Blending Ensemble Learning Model for 12-Lead Electrocardiogram-Based Arrhythmia Classification by Hai-Long Nguyen, Van Su Pham, Hai-Chau Le

“…Experiments conducted with seven diverse machine learning algorithms (Adaptive Boosting, Extreme Gradient Boosting, Decision Trees, k-Nearest Neighbors, Logistic Regression, Random Forest, and Support Vector Machine) demonstrate that the proposed blending solution, utilizing an LR meta-model with three optimal base models, achieves a superior classification accuracy of 96.48%, offering an effective tool for clinical decision support.…”
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A Summary of the Existing Data on Cleft Surgical Outcomes: What Do We Not Know? by Priyanka Naidu, MBChB, MS, Alexander T. Plonkowski, MBBS, MRes, Caroline A. Yao, MD, MS, William P. Magee, III, MD, DDS

“…These protocols all aim to achieve optimal aesthetic appearance and speech outcomes while limiting significant complications such as velopharyngeal insufficiency and midface hypoplasia. …”
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Two Power Allocation and Beamforming Strategies for Active IRS-aided Wireless Network via Machine Learning by Q. Cheng, J. Bai, X. Wang, B. Shi, W. Gao, F. Shu

“…Simulation results show that the proposed algorithms can effectively improve the rate performance compared to fixed PA strategies, only optimizing PA factor, aided by passive IRS, and without IRS.…”
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Complex Neutrosophic Approach for Uncertainty Management in Employment Competence for Higher Vocational College Students by Shuo Du, Lijuan Zhao

“…The proof-of-concept analysis highlighted the best-ranked alternative while offering intuitions about the sensitivity of the decision process. …”
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A Solution for Predicting the Timespan Needed for Grinding Roller Bearing Rings by Cezarina Chivu, Mitica Afteni, Gabriel Radu Frumusanu, Florin Susac

“…The optimal management of manufacturing processes can be achieved through a set of optimal decisions, which must be made to choose the best method to follow every time the process planner reaches a point when several potential manufacturing paths branch off. …”
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Slip and tractive efficiency of an electric tractor with a 4WID E-axle system by SeungYun Baek, HyeonHo Jeon, CheolGyu Park, YongJoo Kim

“…The highest tractive efficiency was observed when slip was within the 10–20% range, indicating that this slip range corresponds to the optimal operating condition. The primary findings of this study identify the appropriate slip range and provide fundamental data for developing slip control algorithms for the 4WID E-axle system. …”
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A Novel Graph Reinforcement Learning-Based Approach for Dynamic Reconfiguration of Active Distribution Networks with Integrated Renewable Energy by Hua Zhan, Changxu Jiang, Zhen Lin

“…The dynamic reconfiguration of active distribution networks (ADNDR) essentially belongs to a complex high-dimensional mixed-integer nonlinear stochastic optimization problem. Traditional mathematical optimization algorithms tend to encounter issues like slow computational speed and difficulties in solving large-scale models, while heuristic algorithms are prone to fall into local optima. …”
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Robust Cross-Validation of Predictive Models Used in Credit Default Risk by Jose Vicente Alonso, Lorenzo Escot

“…Model validation is a challenging Machine Learning task, usually more difficult for consumer credit default models because of the availability of small datasets, the modeling of low-frequency events (imbalanced data), and the bias in the explanatory variables induced by the train/test sets split of the validation techniques (covariate shift). While many methodologies have been developed, cross-validation is perhaps the most widely accepted, often being part of the model development process by optimizing the hyperparameters of predictive algorithms. …”
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Emergent behaviors in multiagent pursuit evasion games within a bounded 2D grid world by Sihan Xu, Zhaohui Dang

“…After training with MARL algorithms, pursuers achieved a 99.9% success rate in 1,000 randomized pursuit-evasion trials, demonstrating the effectiveness of the learned strategies. …”
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Efficient topology control for time-varying spacecraft networks with unreliable links by Wei Zhang, Hong Ma, Tao Wu, Xueshu Shi, Yiwen Jiao

“…We prove that such an optimization problem is NP-hard. Then, we provide five heuristic algorithms, which can significantly maintain low topology cost efficiency ratio while achieving high reliable connectivity. …”
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Enhancing network slice security with Deep Reinforcement Learning and Moving Target Defense strategies by Andreas Andreou, Constandinos X. Mavromoustakis, Evangelos Markakis, Athina Bourdena, George Mastorakis

“…By modelling the problem as a Markov Decision Process (MDP), the proposed framework leverages advanced DRL algorithms to learn optimal policies for deploying MTD mechanisms across network slices by continuously adapting defences to counter evolving cyber threats. …”
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A practical study of artificial intelligence-based real-time feedback in online physical education teaching by Jiewei Ma, Lianzhen Ma, Shilong Qi, Bo Zhang, Wenpian Ruan

“…Future research should focus on optimizing algorithms and integrating adaptive learning to create more effective OLPE strategies.…”
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Quantum Edge Detection and Convolution Using Paired Transform-Based Image Representation by Artyom Grigoryan, Alexis Gomez, Sos Agaian, Karen Panetta

“…We demonstrate that our approach achieves improved processing speed compared to classical methods while maintaining comparable accuracy. The successful implementation of real-world images highlights the potential of this research for large-scale quantum image processing, architecture-specific optimizations, and applications beyond edge detection.…”
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Tomographic SAR imaging via generative adversarial neural network with cascaded U‐Net architecture by Jie Li, Kun Wang, Zhiyuan Li, Bingchen Zhang, Yirong Wu

“…The tests show promising results with the limited number of acquisitions while reducing the computation time.…”
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Variant Design of Girder-Slab Structure with Different Geometric Cells Under Flexural Vibrations by Andrey A. Chernyaev, Kirill V. Marfin

“…Therefore, the development of methods and algorithms for searching of the most rational and optimal design solutions is of great significance. …”
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Efficient structure learning of gene regulatory networks with Bayesian active learning by Dániel Sándor, Péter Antal

“…We evaluate scalable structure learning algorithms within an active learning framework to optimize intervention selection. …”
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Evaluating Material Parameter Influence on Drapability Using VStitcher by Malin Schiller, Soraya Flohr, Jeanne Marisol Delmas, Anja Krüger, Anne-Marie Miene, Patrizia Zimmermann, Lena Wolf, Miriam Seffers, Michelle-Sophie Ruchay-Drammeh, Ulrike Reinhardt, Lilia Sabantina

“…The most significant effect on the drape coefficient (DC) is seen with increased bending stiffness, while changes in thickness, elongation, and shear stiffness have a minimal effect. …”
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Advances and challenges in neoantigen prediction for cancer immunotherapy by Yi Zhang, Ting-Ting Chen, Xiong Li, Ai-Lin Lan, Peng-Fei Ji, Ya-Juan Zhu, Xue-Yao Ma

“…Future advancements will focus on dynamic tumor microenvironment monitoring, multi-omics integration, improved computational models and algorithms to refine neoantigen prediction, and developing optimized personalized vaccines.…”
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A multi-functional simulation platform for on-demand ride service operations by Siyuan Feng, Taijie Chen, Yuhao Zhang, Jintao Ke, Zhengfei Zheng, Hai Yang

“…However, due to cost and reliability issues, it is commonly infeasible to validate these models and train/test these optimization algorithms within real-world ride-sourcing platforms. …”
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STUDY OF ROBUST TOA DISCRIMINATORS FOR SPACE-BASED RADAR ALTIMETER by D. S. Borovitsky, A. E. Zhesterev, V. P. Ipatov, R. M. Mamchur

“…In the  robust  algorithms TOA-measuring  is performed without  using  any  echo  physical  model.  …”
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