Accelerated development of multi-component alloys in discrete design space using Bayesian multi-objective optimisation by Osman Mamun, Markus Bause, Bhuiyan Shameem Mahmood Ebna Hai

“…Furthermore, we explore the impact of various surrogate model optimisation methods from both computational cost and efficiency perspectives. …”
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Equilibrium Analysis of Electricity Market with Multi-Agents Considering Uncertainty by Zhonghai Sun, Runyi Pi, Junjie Yang, Chao Yang, Xin Chen

“…A hybrid solution methodology integrating nonlinear complementarity formulations with genetic algorithm-based optimization was developed. Extensive numerical case studies validate the methodological efficacy, demonstrating improvements in solution optimality and computational efficiency compared to conventional approaches.…”
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Observer of changes in the forest of the shortest paths on dynamic graphs of transport networks by N. V. Khajynova, M. P. Revotjuk, L. Y. Shilin

“…The proposed version of the construction of the search procedure is based on the mechanisms existing in database management systems for creating different relational representations of the physical data model. This eliminates the need to solve technological problems of complexing heterogeneous models of dynamic transport networks, memory allocation. …”
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Reliability and Quality of Complex Systems by D.N. Novomeisky, M.N. Piganov, E.T. Eskibaev

“…Purpose – Analysis and evaluation of methodological errors in the process of electrophysical processing of film resistors by high-frequency flare discharge, implemented according to a given algorithm. Materials and methods. Computer modeling, programming, full-scale experiment, expert assessments were used. …”

Intelligent Counterforce Allocation Method Using Multi-Agent Reinforcement Learning for Ground Operations by Kiwoong Park, Sangheun Shim

“…The MARL agent is implemented using the Soft Actor-Critic algorithm and scaled through a Graph Attention Network to manage over 40 heterogeneous agents (infantry, tanks, and artillery). …”
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Privacy-preserving method for face recognition based on homomorphic encryption. by Zhigang Song, Gong Wang, Wenqin Yang, Yunliang Li, Yinsheng Yu, Zeli Wang, Xianghan Zheng, Yang Yang

“…To overcome this limitation, this paper introduces an optimization scheme based on clustering algorithms to accelerate the facial recognition process within the HE_FaceNet framework. …”
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ADAM-DETR: an intelligent rice disease detection method based on adaptive multi-scale feature fusion by Hanyu Song, Xinyue Huang, Ziqiang Wang, Jianwei Hu, Huasheng Zhang, Hui Yang

“…The algorithm innovatively designs three core modules: the AdaptiveVision Network (AVN) backbone for enhanced feature extraction, the Dual-Domain Enhanced Transformer (DDET) module for spatiotemporal-frequency domain collaboration, and the Adaptive Multi-scale Feature Model (AMFM) for improved feature fusion. …”
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Advanced GPU Techniques for Dynamic Remeshing and Self-Collision Handling in Real-Time Cloth Tearing by Jong-Hyun Kim, Jung Lee

“…We also present a method to optimize kernels based on a complete binary tree in arbitrary triangular meshes, improving performance. …”
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The application of blockchain with a comparative approach and its impact on risk, flexibility and internal control evaluation by mohammadsadegh aminipoor, HamidReza GholamniaRoshan, azadeh kiapour, Iman Dadashi

“…Overall, blockchain can help improve risk, flexibility and internal control assessment. …”
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YOLO11-ARAF: An Accurate and Lightweight Method for Apple Detection in Real-World Complex Orchard Environments by Yangtian Lin, Yujun Xia, Pengcheng Xia, Zhengyang Liu, Haodi Wang, Chengjin Qin, Liang Gong, Chengliang Liu

“…Second, to reinforce feature learning in visually challenging orchard environments, the enhanced attention module AFGCAM was embedded into the model architecture. Third, we applied knowledge distillation to transfer the enhanced model to a compact YOLO11n framework, maintaining high detection efficiency while reducing computational cost, and optimizing it for deployment on devices with limited computational resources. …”
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Distinguishing novel coronavirus influenza A virus pneumonia with CT radiomics and clinical features by Lianyu Sui, Huan Meng, Jianing Wang, Wei Yang, Lulu Yang, Xudan Chen, Liyong Zhuo, Lihong Xing, Yu Zhang, Jingjing Cui, Xiaoping Yin

“…After incorporating clinical features, the clinical model’s discriminatory and predictive efficacy further improved in testing sets (AUC, 0.669 vs. 0.820, P = 0.002). …”
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MAB-RSP: Data pricing based on Stackelberg game in MCS by Yongjiao Sun, Xueyan Ma, Anrui Han

“…We introduce two novel contributions. First, the MAB-RS algorithm leverages multi-armed bandit reinforcement learning and a data freshness model to dynamically optimize seller recruitment, efficiently balancing exploration of unknown sellers and exploitation of high-quality ones. …”
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SR-YOLO: Spatial-to-Depth Enhanced Multi-Scale Attention Network for Small Target Detection in UAV Aerial Imagery by Shasha Zhao, He Chen, Di Zhang, Yiyao Tao, Xiangnan Feng, Dengyin Zhang

“…Second, a small target detection layer and a bidirectional feature pyramid network mechanism are introduced to enhance the neck network, thereby strengthening the feature extraction and fusion capabilities for small targets. Finally, the model’s detection performance for small targets is improved by utilizing the Normalized Wasserstein Distance loss function to optimize the Complete Intersection over Union loss function. …”
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Proposed Comprehensive Methodology Integrated with Explainable Artificial Intelligence for Prediction of Possible Biomarkers in Metabolomics Panel of Plasma Samples for Breast Canc... by Cemil Colak, Fatma Hilal Yagin, Abdulmohsen Algarni, Ali Algarni, Fahaid Al-Hashem, Luca Paolo Ardigò

“…The SHapley Additive Descriptions (SHAP) analysis evaluated the optimal prediction model for interpretability. <i>Results</i>: The RF algorithm showed improved accuracy (0.963 ± 0.043) and sensitivity (0.977 ± 0.051); however, LightGBM achieved the highest ROC AUC (0.983 ± 0.028). …”
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Sustainable Energy and Exergy Analysis in Offshore Wind Farms Using Machine Learning: A Systematic Review by Hamid Reza Soltani Motlagh, Seyed Behbood Issa-Zadeh, Abdul Hameed Kalifullah, Arife Tugsan Isiacik Colak, Md Redzuan Zoolfakar

“…By integrating theoretical insights with empirical evidence, this study proposes a unified framework that leverages ML algorithms to optimize turbine performance, reduce maintenance costs, and minimize environmental impacts. …”
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Assessing Urban Vulnerability to Emergencies: A Spatiotemporal Approach Using K-Means Clustering by Ibrahim Mutambik

“…The findings highlight the value of incorporating both spatial and temporal data to enhance emergency response strategies and optimize urban planning efforts. This study contributes to the literature on smart cities by providing a scalable and adaptable method for improving urban resilience in the face of evolving challenges.…”
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Adaptive Feature Selection of Unbalanced Data for Skiing Teaching by Tao Feng

“…Finally, the experimental results on the public imbalanced dataset show that the proposed algorithm effectively improves the classification performance of imbalanced data.…”
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The Next Frontier in Brain Monitoring: A Comprehensive Look at In-Ear EEG Electrodes and Their Applications by Alexandra Stefania Mihai (Ungureanu), Oana Geman, Roxana Toderean, Lucas Miron, Sara SharghiLavan

“…Recent studies have demonstrated that in-ear EEG can record signals qualitatively comparable to scalp EEG, with an optimized signal-to-noise ratio and improved electrode stability. …”
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Linear Continuous-Time Regression and Dequantizer for Lithium-Ion Battery Cells with Compromised Measurement Quality by Zoltan Mark Pinter, Mattia Marinelli, M. Scott Trimboli, Gregory L. Plett

“…This paper presents two modular algorithms to improve data quality and enable fast, robust parameter identification. …”
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TKEO-Enhanced Machine Learning for Classification of Bearing Faults in Predictive Maintenance by Xuanbai Yu, Olivier Caspary

“…These findings offer new insights to support reliable predictive maintenance in industrial settings and provide a new perspective for future research into active vibration control, where vibration signal analysis, feature extraction, and mathematical modeling play key roles in optimizing control algorithms and enhancing the efficiency of adaptive control systems.…”
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