Kinematic Optimization of a Flexible Wing Undergoing Flapping and Pitching by Yue Wu, Changchuan Xie, Yang Meng, Chao Yang

“…In addition, the optimization algorithm maximizes the thrust efficiency while satisfying the required lift. …”
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Enhancing classification of a large lower-limb motor imagery EEG dataset for BCI in knee pain patients by Chongwen Zuo, Yi Yin, Haochong Wang, Zhiyang Zheng, Xiaoyan Ma, Yuan Yang, Jue Wang, Shan Wang, Zi-gang Huang, Chaoqun Ye

“…Traditional decoding algorithms achieved accuracies of 51.43%, 55.71%, and 76.21%, while the proposed OTFWRGD algorithm reached an average accuracy of 86.41%. …”
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Using Graph Neural Networks in Reinforcement Learning With Application to Monte Carlo Simulations in Power System Reliability Analysis by Oystein Rognes Solheim, Boye Annfelt Hoverstad, Magnus Korpas

“…For the actor part of this architecture, we have implemented both a deterministic agent being a variant of the Twin Delayed DDPG-algorithm, and a stochastic agent with similarities to the Soft Actor Critic-algorithm. …”
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A Multi-Objective PSO-GWO Approach for Smart Grid Reconfiguration with Renewable Energy and Electric Vehicles by Tung Linh Nguyen, Quynh Anh Nguyen

“…Distribution network reconfiguration emerges as a pivotal strategy to mitigate power losses, facilitate the seamless assimilation of renewable generation, and regulate the charging and discharging dynamics of EVs, thereby constituting a critical endeavor in modern electrical engineering. While the Particle Swarm Optimization algorithm is renowned for its rapid convergence and effective exploitation of solution spaces, its capacity to thoroughly explore complex search domains remains limited, particularly in multifaceted optimization challenges. …”
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Tensor-Based Efficient Federated Reinforcement Learning for Cyber-Physical-Social Intelligence by Xin Nie, Laurence T. Yang, Fulan Fan, Zecan Yang

“…By leveraging tensor to model state-action values and employing tensor decomposition techniques for dimensionality reduction, this method effectively reduces model parameters and communication overhead while maintaining strong interpretability, accelerates algorithm convergence speed. …”
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Towards Optimizing the Downlink Transmit Power in UAV-Integrated IRS Wireless Systems by Ali Reda, Tamer Mekkawy, Ashraf Mahran

“…In interference scenarios and with different numbers of IRS meta-atoms, the proposed algorithm achieves a power reduction of approximately 8 and 13 dBm, while maintaining the same required signal-to-interference-plus-noise ratio. …”
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Bats of a feather: Range characteristics and wing morphology predict phylogeographic breaks in volant vertebrates by Sydney K. Decker, Kaiya L. Provost, Bryan C. Carstens

“…In bats, phylogeographic breaks are concentrated in biodiversity hotspots while breaks estimated in bird species are more widespread across temperate and tropical zones. …”
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AI based data-driven point cloud optimization strategy in cloud computing framework for improving rendering performance of virtual city scenes by Cao Zhongda

“…Comparison of the proposed method and model of the study revealed that the F1 value and accuracy of the proposed algorithm was 0.87 and 93.9% respectively, which is better than the comparison algorithm. …”
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Enhancing Pose Estimation Using Multiple Graphical Markers with Spatial and Temporal Outlier Detection by Doyoung Kim, Jae Hwan Bong, Seongkyun Jeong

“…Our approach incorporates two key mechanisms: spatial consistency verification to detect invalid markers within the marker array, and temporal stability analysis to identify and exclude outlier measurements. The algorithm enhances pose estimation accuracy by averaging measurements from valid markers while preventing any single marker from dominating the estimation process. …”
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Optimization of Electric Vehicle Charging and Discharging Strategies Considering Battery Health State: A Safe Reinforcement Learning Approach by Shuifu Gu, Kejun Qian, Yongbiao Yang

“…The algorithm filters out strategies that violate constraints by introducing a logarithmic barrier function. …”
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Optimizing ML models for cybercrime detection: balancing performance, energy consumption, and carbon footprint through multi-objective optimization by Romil Rawat

“…The research utilizes the Non-Dominated Sorting Genetic Algorithm II (NSGA-II), a multi-objective evolutionary algorithm (MOEA), to reduce data dimensionality and identify key features for traffic analysis related to global human trafficking (HTr). …”
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libBICOS – An Open Source GPU-Accelerated Library implementing BInary COrrespondence Search for 3D Reconstruction by C. Liebender, M. Bleier, A. Nüchter

“…Our GPU-accelerated implementation reduces the latency of disparity computation using 7MP images on modern hardware down to 20 milliseconds. Based on the algorithm introduced by Dietrich et al. (2019), we extend their approach by increasing the descriptor size while augmenting postprocessing to increase its applicability on other types of pattern projections. …”
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Intuition-guided Reinforcement Learning for Soft Tissue Manipulation with Unknown Constraints by Xian He, Shuai Zhang, Jian Chu, Tongyu Jia, Lantao Yu, Bo Ouyang

“…Successful simulation results confirmed that the proposed framework can manipulate the soft tissue while avoiding obstacles and adding new positional constraints. …”
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Enhanced Rapid Autofocus Back-Projection for PBSAR Based on the GEO Satellite by Te Zhao, Jun Wang, Zuhan Cheng, Ziqian Huang, Jiaqi Song

“…Conventional autofocusing algorithms operate under the assumption that measurement errors primarily perturb phase components while exerting negligible influence on signal envelopes. …”
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Identifying Coronal Mass Ejection Active Region Sources: An Automated Approach by Julio Hernandez Camero, Lucie M. Green, Alex Piñel Neparidze

“…We find that CME–flare association rates increase with flare intensity, aligning with previous studies. While our approach has limitations, such as focusing exclusively on SHARP regions and relying on a limited set of posteruptive signatures, it significantly reduces the time required for CME source identification while providing transparent, reproducible results. …”
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Scenario-Based Association Rule Mining in Veterinary Services Using FP-Growth: Differentiating Clinical and Customer-Driven Patterns by Rafi Dio, Aulia Agung Dermawan, Dwila Sempi Yusiani, Rifaldi Herikson, Andikha Andikha, Dwi Ely Kurniawan, Adyk Marga Raharja

“…This study aims to differentiate between procedural and customer-driven service patterns by applying the FP-Growth association rule mining algorithm to 1,000 anonymized transactions comprising 94 unique items, collected from a veterinary clinic in West Java, Indonesia, during 2023. …”
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Efficient black-box attack with surrogate models and multiple universal adversarial perturbations by Tao Ma, Hong Zhao, Ling Tang, Mingsheng Xue, Jing Liu

“…Additionally, we optimize this process using a Genetic Algorithm (GA), allowing for efficient search of the perturbation space while conserving query budget. …”
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Optimizing frequency stability with adaptive fast frequency reserves and Wide-Area Monitoring Systems by Bwandakassy Elenga Baningobera, Irina Oleinikova, Kjetil Uhlen

“…These additional stability considerations enhance the algorithm’s capacity to maintain frequency stability without excessive load shedding or oscillatory behavior. …”
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Applying machine learning to predict bowel preparation adequacy in elderly patients for colonoscopy: development and validation of a web-based prediction tool by Jianying Liu, Wei Jiang, Yahong Yu, Jiali Gong, Guie Chen, Yuxing Yang, Chao Wang, Dalong Sun, Xuefeng Lu

“…The SHAP algorithm helped rank feature importance. A web-based application was developed using the Streamlit framework to enhance clinical usability.Results The Boruta algorithm identified 7 key features. …”
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Automatic Recognition of Motor Skills in Triathlon: A Novel Tool for Measuring Movement Cadence and Cycling Tasks by Stuart M. Chesher, Carlo Martinotti, Dale W. Chapman, Simon M. Rosalie, Paula C. Charlton, Kevin J. Netto

“…<b>Background/Objectives</b>: The purpose of this research was to create a peak detection algorithm and machine learning model for use in triathlon. …”
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