Distributed blockchain assisted secure data aggregation scheme for risk-aware zone-based MANET by V R. Sugumaran, E. Dinesh, R. Ramya, Elangovan Muniyandy

“…Data aggregation is secured through a Two-Step Secure (STS) method and Elliptic Curve Cryptography (ECC), while optimal routing is achieved using the Improved Elephant Herd Optimization (IEHO) algorithm. …”
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Real-Time Human Group Detection and Clustering in Crowded Environments Using Enhanced Multi-Object Tracking by Hyunmin Lee, Donggoo Kang, Hasil Park, Sangwoo Park, Dasol Jeong, Joonki Paik

“…To address these limitations, we propose a novel algorithm that integrates an optimized YOLOv8 model with DeepSORT tracking, enhancing both detection accuracy and real time performance. …”
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Application of the SWAT Hydrological Model for the Catchment Area of the Koudiat Acerdoune Dam on the Isser River, Algeria by L. Chebihi, M. Habi, A. Elouissi

“…Model parameters were optimized using the SWAT-CUP optimization method and the SUFI-2 algorithm. …”
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Learning-Based Multi-Stage Formation Scheduling with a Hybrid Controller by Zhichao Zhang, Yao Li

“…The comparison with other scheduling strategies demonstrates the optimality and effectiveness of our proposed framework and algorithms.…”
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Flexible hardware for teaching and research in renewable energy and off-grid microgrids by Cristian Escudero-Quintero, Juan Pablo Guzman-Rodriguez, Juan Pablo Villegas-Ceballos, Elkin Edilberto Henao-Bravo, Daniel Gonzalez-Montoya

“…Microgrids are an active research field due to their integration of renewable and non-renewable energy sources alongside energy storage systems to supply both DC and AC loads. While existing studies extensively explore hierarchical control structures, focusing on algorithm design and optimization, practical implementation remains challenging due to system complexity. …”
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Vehicle detection in drone aerial views based on lightweight OSD-YOLOv10 by Yang Zhang, Xiaobing Chen, Su Sun, Hongfeng You, Yuanyuan Wang, Jianchu Lin, Jiacheng Wang

“…Abstract To address the challenges of low performance in vehicle image detection from UAV aerial imagery, difficulties in small target feature extraction, and the large parameter size of existing models, we propose the OSD-YOLOv10 algorithm, an enhanced version based on YOLOv10n. The proposed algorithm incorporates several key innovations: First, we employ online convolutional reparameterization to construct the OCRConv module and design a lightweight feature extraction structure, SPCC, to replace the conventional C2f module, thereby reducing computational load and parameter count. …”
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Neural operators for hydrodynamic modeling of underground gas storage facilities by D. D. Sirota, K. A. Gushchin, S. A. Khan, S. L. Kostikov, K. A. Butov

“…The model can be recommended for use in planning and decision-making purposes regarding various aspects of UGS operation, such as optimal control of gas wells, pressure control, and management of gas reserves.…”
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Study of model construction of fuel production from waste plastic pyrolysis based on machine learning by CHEN Sihan, YUAN Zhilong, WANG Ye, SUN Yifei*

“…The Gradient Boosting Regression (GBR) algorithm has the best fitting performance for predicting oil yield (R^2=0.91, RMSE=7.78), while the adaptive boosting algorithm (AdaBoost) has the best fitting performance for predicting gas yield (R^2=0.83, RMSE=6.42), enabling accurate prediction of reaction conditions. …”
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An Adaptive Unscented Kalman Ilter Integrated Navigation Method Based on the Maximum Versoria Criterion for INS/GNSS Systems by Jiahao Zhang, Kaiqiang Feng, Jie Li, Chunxing Zhang, Xiaokai Wei

“…On this basis, fully considering the high-order moments of estimation errors, the maximum versoria criterion is introduced as the optimization criterion to construct a novel cost function, further effectively suppressing deviations caused by non-Gaussian disturbances and improving system navigation accuracy. …”
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Adaptive Granularity-Fused Keypoint Detection for 6D Pose Estimation of Space Targets by Xu Gu, Xi Yang, Hong Liu, Dong Yang

“…Accurate pose determination requires robust algorithms capable of handling these complexities while maintaining reliability under various environmental conditions. …”
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A Precise Oxide Film Thickness Measurement Method Based on Swept Frequency and Transmission Cable Impedance Correction by Yifan Li, Qi Xiao, Lisha Peng, Songling Huang, Chaofeng Ye

“…This method can be utilized to measure oxide film thickness in nuclear power maintenance inspections following extensive testing and engineering optimization.…”
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Machine Learning-Driven Acoustic Feature Classification and Pronunciation Assessment for Mandarin Learners by Gulnur Arkin, Tangnur Abdukelim, Hankiz Yilahun, Askar Hamdulla

“…This study confirms the effectiveness of objective assessment methods based on formant analysis in speech acquisition research, provides a theoretical basis for algorithm optimization in speech evaluation systems, and holds significant application value for the development of Computer-Assisted Language Learning (CALL) systems and the improvement of multi-ethnic Mandarin speech recognition technology.…”
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Machine-learning-derived prediction models of outcomes for patients with pseudomyxoma peritonei: development and validation in two retrospective cohorts by Yu-Run Cui, Xin-Li Liang, Yan Li

“…Recent advancements have shown that machine learning (ML) algorithms hold great promise in developing predictive models within the medical field. …”
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Robust QoT Assured Resource Allocation in Shared Backup Path Protection Based EONs by Venkatesh Chebolu, Sadananda Behera, Goutam Das

“…Next, we employ our SBPP-IA algorithm for dynamic traffic scenario and compare it with existing algorithms in terms of different QoT parameters. …”
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FLDQN: Cooperative Multi-Agent Federated Reinforcement Learning for Solving Travel Time Minimization Problems in Dynamic Environments Using SUMO Simulation by Abdul Wahab Mamond, Majid Kundroo, Seong-eun Yoo, Seonghoon Kim, Taehong Kim

“…Addressing these issues requires innovative approaches for optimizing road network utilization. While Deep Reinforcement Learning (DRL)-based methods have shown remarkable effectiveness in dynamic scenarios like traffic management, their primary focus has been on single-agent setups, limiting their applicability to real-world multi-agent systems. …”
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Enhancing healthcare AI stability with edge computing and machine learning for extubation prediction by Kuo-Yang Huang, Ying-Lin Hsu, Che-Liang Chung, Huang-Chi Chen, Ming-Hwarng Horng, Ching-Hsiung Lin, Ching-Sen Liu, Jia-Lang Xu

“…Given the pivotal role of ventilators, accurately predicting extubation outcomes is essential to optimize patient care. This study presents an edge computing-based framework that incorporates machine learning algorithms to predict ventilator extubation success using real-time data collected directly from ventilators. …”
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A Gain-Computation Enhancements Resource Allocation for Heterogeneous Service Flows in IEEE 802.16 m Mobile Networks by Wafa Ben Hassen, Meriem Afif

“…This method has a crucial role in the resource management and optimization. In a single service access, we propose a dynamic resource allocation algorithm at the physical layer aiming to maximize the cell data rate while ensuring fairness among users. …”
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Hyperspectral Imaging for Non-Destructive Moisture Prediction in Oat Seeds by Peng Zhang, Jiangping Liu

“…Subsequently, a dual-optimized neural network model, termed Bayes-ASFSSA-BP, was developed by incorporating Bayesian optimization and the Adaptive Spiral Flight Sparrow Search Algorithm (ASFSSA). …”
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Quantum Conformal Prediction for Reliable Uncertainty Quantification in Quantum Machine Learning by Sangwoo Park, Osvaldo Simeone

“…Quantum machine learning is a promising programming paradigm for the optimization of quantum algorithms in the current era of noisy intermediate-scale quantum computers. …”
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Monte Carlo Simulation and Experimental Validation for Radiation Protection with Multiple Complex Source Terms and Deep Penetration for a Radioactive Liquid Waste Cementation Facil... by Wenqian Li, Xuegang Liu, Sheng Fang, Xueliang Fu, Kaiqiang Guo

“…The complex shielding also leads to a deep penetration problem; hence, the optimization algorithm and variance reduction techniques were adopted. …”
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