FedACT: An adaptive chained training approach for federated learning in computing power networks by Min Wei, Qianying Zhao, Bo Lei, Yizhuo Cai, Yushun Zhang, Xing Zhang, Wenbo Wang

“…Second, we propose a Genetic-Algorithm-based Sorting (GAS) method to optimize the order of clients participating in training. …”
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Introducing an oncoplastic approach for centrally located breast cancer patients by Mohammadreza Karoobi, Seyed Mostafa Meshkati Yazd, Fatemeh Aminolroaya, Hadiseh Mahram, Samineh Saghafinia, Stefano Pompei, Nahid Nafissi, Pantea Khalili

“…This study aims to present a comprehensive algorithm designed to optimize surgical planning and enhance aesthetic outcomes for patients undergoing surgery for central breast cancers. …”
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Quantifying ruminal health: A statistical review and application of area and time under the curve in animal science by Luis O. Tedeschi

“…The integration of robust analytical frameworks like ATAUC provides a pathway for improved decision-making, enhanced productivity, and greater welfare in ruminant systems while offering insights applicable to other time-dependent phenomena in science and industry.…”
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DS-AdaptNet: An Efficient Retinal Vessel Segmentation Framework With Adaptive Enhancement and Depthwise Separable Convolutions by Shuting Chen, Chengxi Hong, Hong Jia

“…Second, we develop a Context-Aware Adaptive Threshold Optimization (CA-ATO) algorithm that dynamically determines optimal thresholds by integrating multi-scale contextual information and uncertainty estimates, substantially improving boundary delineation accuracy and fine structure preservation. …”
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Towards a smart debt collection system: a Design Science Research approach by Michał Przybyłek, Adam Przybyłek, Konrad Wojciechowski, Illia Shkroba

“…This shift opens up new perspectives and possibilities in the field of debt collection, such as increased efficiency, improved accuracy, and scalability. The application of AI algorithms in this context has the potential to revolutionize the industry and enhance overall debt collection practices. …”
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Research on Near-Infrared Non-Invasive Blood Glucose Detection Technology by Wang Jinshuo

“…In response to the complex and easily interfered characteristics of near-infrared spectral signals, an innovative BP neural network algorithm is introduced to construct a prediction model. …”
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LN-DETR: cross-scale feature fusion and re-weighting for lung nodule detection by Dibin Zhou, Honggang Xu, Wenhao Liu, Fuchang Liu

“…These results highlight the superior detection accuracy of the proposed network while maintaining computational efficiency.…”
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Hyperelastic behavior of cable gland silicon shroud: finite element analysis by Ganesh Bhoye, Ishant Jain

“…These findings highlight the silicon shroud as a superior alternative to conventional polyvinyl chloride shrouds, offering enhanced flexibility, reduced weight, and improved environmental resistance. The hyperelastic material model developed in this study provides a robust tool for predicting the shroud’s behavior under varied loading conditions, enabling optimized designs and ensuring long-term performance.…”
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Automatic Calculation of Average Power in Electroencephalography Signals for Enhanced Detection of Brain Activity and Behavioral Patterns by Nuphar Avital, Nataniel Shulkin, Dror Malka

“…Results indicate that the IIR Chebyshev filter, configured with a 0.5% passband ripple and a fourth-order design, outperformed the alternatives by effectively reducing average power while preserving signal fidelity. This optimized filtering approach significantly improves the accuracy of neural signal visualizations, thereby facilitating the creation of detailed brain activity maps. …”
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A comparative study of ultra-massive MIMO intelligent receivers with adversarial robustness and energy efficiency for 6G applications by Pushkar Nidagundi, Advesh Darvekar, Malik Amber, Ramesh R

“…The Taguchi method yields up to 40 % improvement in energy efficiency while maintaining near-perfect BER. …”
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Integrating Learning-Driven Model Behavior and Data Representation for Enhanced Remaining Useful Life Prediction in Rotating Machinery by Tarek Berghout, Eric Bechhoefer, Faycal Djeffal, Wei Hong Lim

“…The first part focuses on comprehensive data preprocessing using only feature scaling and selection via random forest (RF) algorithm, streamlining the process by minimizing human intervention while managing data complexity. …”
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Path Planning for Lunar Rovers in Dynamic Environments: An Autonomous Navigation Framework Enhanced by Digital Twin-Based A*-D3QN by Wei Liu, Gang Wan, Jia Liu, Dianwei Cong

“…This paper proposes a digital twin-enhanced hierarchical planning method, A*-D3QN-Opt (A-Star-Dueling Double Deep Q-Network-Optimized). The framework combines the A* algorithm for global optimal paths in static environments with an improved D3QN (Dueling Double Deep Q-Network) for dynamic obstacle avoidance. …”
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Adaptive machine learning framework: Predicting UHPC performance from data to modelling by Yinzhang He, Shaojie Gao, Yan Li, Yongsheng Guan, Jiupeng Zhang, Dongliang Hu

“…Bayesian optimization fine-tuned each model's hyperparameters to identify the optimal model-FS combination. …”
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Domain generalization for image classification based on simplified self ensemble learning. by Zhenkai Qin, Xinlu Guo, Jun Li, Yue Chen

“…Experimental results on three public benchmark datasets (OfficeHome, PACS, and VLCS) demonstrate that our proposed algorithm achieves an improvement of up to 3 . 38% over existing methods in terms of generalization performance, particularly in complex and diverse real-world scenarios, such as autonomous driving and medical image analysis. …”
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Polymer electrolyte membrane fuel cell performance Revolutionized: Artificial intelligence-validated asymmetric flow channels enhance mass transport via hybrid analytical-numerical... by Nima Ahmadi, Ghader Rezazadeh

“…Experimental validation confirms a current density improvement of up to 5.6 % over conventional designs, while Artificial Intelligence (AI)-driven optimization via a hybrid Convolutional Neural Network and Genetic Algorithm independently identifies the same optimal configuration. …”
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Industrial-scale prediction of cement clinker phases using machine learning by Sheikh Junaid Fayaz, Néstor Montiel-Bohórquez, Shashank Bishnoi, Matteo Romano, Manuele Gatti, N. M. Anoop Krishnan

“…The framework can potentially enable real-time optimization of cement production, thereby providing a route toward reducing material waste and ensuring quality while reducing the associated emissions under real-world conditions.…”
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Numerical Solution of the Inverse Thermoacoustics Problem Using QFT and Gradient Method by Syrym E. Kasenov, Aigerim M. Tleulesova, Almas N. Temirbekov, Zholaman M. Bektemessov, Rysbike A. Asanova

“…The inverse problem was reduced to an optimization problem, where the objective function was minimized using gradient methods, including the accelerated Nesterov algorithm. …”
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Research on the policy inconsistency, network motifs and low carbon effects for municipal solid waste management by Bo Lv, Tianxu Cui, Daiheng Li, Weiyue Yao

“…It offers strategies for enhancing carbon reduction through network optimization and phased policy design, aiding low - carbon MSWM policy improvement.…”
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Parametric Sensitivity Analysis of Safe Train Interval Model Based on Relative Braking Distance by QIAN Hua, LYU Haojiong

“…This study sought to analyze the sensitivity of key parameters affecting these safe intervals, to harness the potential of virtual coupling technology in improving efficiency while ensuring operational safety. …”
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Advanced artificial intelligence with federated learning framework for privacy-preserving cyberthreat detection in IoT-assisted sustainable smart cities by Mahmoud Ragab, Ehab Bahaudien Ashary, Bandar M. Alghamdi, Rania Aboalela, Naif Alsaadi, Louai A. Maghrabi, Khalid H. Allehaibi

“…Eventually, the walrus optimization algorithm (WOA) is used for hyperparameter tuning to improve the parameters of the SSAE approach and achieve optimal performance. …”
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