5G Network on Wings: A Deep Reinforcement Learning Approach to the UAV-Based Integrated Access and Backhaul by Hongyi Zhang, Zhiqiang Qi, Jingya Li, Anders Aronsson, Jan Bosch, Helena Holmstrom Olsson

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Learning to Infer Weather States Using Partial Observations by Jie Chao, Baoxiang Pan, Quanliang Chen, Shangshang Yang, Jingnan Wang, Congyi Nai, Yue Zheng, Xichen Li, Huiling Yuan, Xi Chen, Bo Lu, Ziniu Xiao

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ORANSight-2.0: Foundational LLMs for O-RAN by Pranshav Gajjar, Vijay K. Shah

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Recursive GNNs for Learning Precoding Policies With Size-Generalizability by Jia Guo, Chenyang Yang

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TopoRSNet: A Unique Approach to Maintaining Topological Features for Digital Rock Image Rescaling With Minimal Quality Degradation by Kunning Tang, Yufu Niu, Ying DaWang, Vanessa Robins, Peyman Mostaghimi, Mark Lindsay, Ryan T. Armstrong

“…This method enables scalable analysis of multiscale rock features, allowing for broader integration of 3D imaging in geoscientific modeling, simulation, and machine learning workflows.…”
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Neuromorphic Wireless Split Computing With Multi-Level Spikes by Dengyu Wu, Jiechen Chen, Bipin Rajendran, H. Vincent Poor, Osvaldo Simeone

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Deep Ensemble Learning With Pruning for DDoS Attack Detection in IoT Networks by Makhduma F. Saiyedand, Irfan Al-Anbagi

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Benchmarking uncertainty quantification for protein engineering. by Kevin P Greenman, Ava P Amini, Kevin K Yang

“…Machine learning sequence-function models for proteins could enable significant advances in protein engineering, especially when paired with state-of-the-art methods to select new sequences for property optimization and/or model improvement. …”
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Discussing the Construction of a Budget Management System Combining Multimedia Technology and Financial Risk Management by Xiaoyi Jiang

“…This paper mainly studies and innovates the data mining process and the support vector machine model and designs the data preprocessing method in the data mining process to perform feature selection and optimize the parameters of the support vector machine model. …”
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Robust Design of a Six-Phase Segmented Switch Reluctance Motor Considering Manufacturing Tolerances and Manufacturing Processes by Farshid Mahmouditabar, Nick J. Baker

“…The results demonstrate that the optimization model presented increases the likely torque output of a machine built with a normal distribution of manufacturing errors.…”
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基于模糊约束的同步带传动参数的多目标优化设计 by 何嘉洲, 唐伟强

“…Using multi-objectives fuzzy optimization method for the sample of timing belt drive of beverage filling machine, based on the Fuzz and random for timing belt drive parameters and considering the indefinite character of the value of design parameters, the mathematics model of fuzzy design optimization satisfied with the conditions of transmission property is set up, and the optimization and result analysis are given.…”
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A Differential Evolutionary-Based XGBoost for Solving Classification of Physical Fitness Test Data of College Students by Baoyue Liang, Weifu Qin, Zuowen Liao

“…To accurately and timely identify the physical health status of college students, a hybrid model of DE-XGBoost is proposed in this study: a discrete coding strategy is designed to solve the XGBoost hyperparameter optimization problem, and differential evolution (DE) is used to achieve global parameter optimization. …”
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A Compressor - System Digital Twin for Performance Prediction Under a Wide Range of Flow and Operating Conditions by Alberto Serena, Lars E. Bakken

“…Turbomachines are essential equipment in propulsion, energy conversion and process engineering; their efficiency and optimization require the exploration of tailored designs and the exploitation of the full machine capability. …”
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Point-SPV: end-to-end enhancement of object recognition in simulated prosthetic vision using synthetic viewing points by Ashkan Nejad, Ashkan Nejad, Ashkan Nejad, Burcu Küçükoǧlu, Jaap de Ruyter van Steveninck, Sandra Bedrossian, Joost Heutink, Joost Heutink, Gera A. de Haan, Gera A. de Haan, Frans W. Cornelissen, Marcel van Gerven

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某型全自动铆接机刺铆压扁机构凸轮的改进设计 by 陈旭东

“…The cam for thorn riveting and flattening mechanism in automatic riveting machine is the key to decide the quality of electrolytic capacitors.Taking riveting machine of full-automatic riveting/winding assembling appliance,Through motion simulation for its 3D model in Inventor,it is found that the original cam motion performance is conform to the law of quadratic polynomial,the vibration and shock of riveting machine has impact on product processing quality.Based on the quintic polynomial,the improvement of this mechanism is carried out,the motion law of cam oscillating bar is changed.Experiments show that through optimization,the precision and stability of riveting machine is improved.The quality of aluminum electrolytic capacitor becomes better.…”
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基于工作空间的航空发动机柔性工装尺度优化及刚度分析 by 石宏, 李伟楠, 陈亮, 朱宁, 金印

“…Based on the study of flexible assembly tooling configuration on aero-engine,he workspace of aero-engine flexible assembly tooling is calculated,and a mathematic model is set up by Monte Carlo method,the design parameter dimensional optimization for workspace is carried out,then the global condition number for construction of different sizes is solved,the result is used for the optimization of machine kinematic.At last the conservative congruence transformation（CCT）stiffness matrix is derived,and stiffness mapping in the direction of X,Y,Zis simulated.These results are applied for the analysis and discuss of stiffness.This work has outstanding theoretical significance for assembly accuracy improvement,optimizing assembly performance,pose and position reasonable selection during the assembly and dimensional optimization.…”
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Unveiling quantum phase transitions from traps in variational quantum algorithms by Chenfeng Cao, Filippo Maria Gambetta, Ashley Montanaro, Raul A. Santos

“…Addressing these challenges, our work introduces a hybrid algorithm that combines quantum optimization with classical machine learning. This approach leverages the capability of near-term quantum computers to prepare locally trapped states through finite optimization. …”
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Quantitative Prediction of Low-Permeability Sandstone Grain Size Based on Conventional Logging Data by Deep Neural Network-Based BP Algorithm by Hongjun Fan, Xiaoqing Zhao, Zongjun Wang, Zheqing Zhang, Ao Chang

“…Machine learning of median grain size from conventional logging data was systematically carried out through conventional logging sensitivity curve optimization, algorithm modeling, network parameter optimization, median grain size prediction, and validation, and the relative error in its quantitative prediction met application requirements. …”
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An Interior Point Method for L1/2-SVM and Application to Feature Selection in Classification by Lan Yao, Xiongji Zhang, Dong-Hui Li, Feng Zeng, Haowen Chen

“…This paper studies feature selection for support vector machine (SVM). By the use of the L1/2 regularization technique, we propose a new model L1/2-SVM. …”
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Anomaly-Based Intrusion Detection System for the Internet of Medical Things by Eichie Franklin, Bernardi Pranggono

“…We proposed using hyperparameter-optimized Machine and Deep Learning models to address these concerns to build more robust security solutions. …”
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