LN-DETR: cross-scale feature fusion and re-weighting for lung nodule detection by Dibin Zhou, Honggang Xu, Wenhao Liu, Fuchang Liu

“…Second, we optimized the computational load of the backbone network, effectively reducing the overall scale of the model. …”
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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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Uncertainty evaluation of surface profile measurement error based on adaptive sparse grid polynomial chaos expansion by Ke Zhang, Xinya Zheng, Ruiyu Zhang

“…First, the surface profile error of the car door outer surface is initially evaluated using a NURBS surface fitting and segmentation approximation algorithm. Next, based on the error evaluation results, a polynomial chaos expansion model for the surface profile error is established. …”
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A Dynamic Kalman Filtering Method for Multi-Object Fruit Tracking and Counting in Complex Orchards by Yaning Zhai, Ling Zhang, Xin Hu, Fanghu Yang, Yang Huang

“…By optimizing the network structure, the improved YOLO detection model provides high-quality detection results for subsequent tracking tasks. …”
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Safety helmet detection methods in heavy machinery factory by Liu Baoju, Wei Xiangqian, Chen Qingshan, Liu Jiaqi, Chen Ye, Yu Peng, Lei shi, Hu Yongfeng

“…When compared with mainstream object recognition algorithms such as SSD, Faster RCNN, and various YOLO versions, the optimized model shows its superiority. …”
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Balancing resource utilization and slice dissatisfaction through dynamic soft slicing for 6G wireless networks by Zeinab Sasan, Siavash Khorsandi

“…Given the NP-hard nature of the problem, we propose the Heuristic Resource Allocation for Soft Slicing (HRASS) algorithm, which achieves near-optimal performance with significantly reduced computational complexity. …”
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Machine learning allows robust classification of lung neoplasm tissue using an electronic biopsy through minimally-invasive electrical impedance spectroscopy by Georgina Company-Se, Virginia Pajares, Albert Rafecas-Codern, Pere J. Riu, Javier Rosell-Ferrer, Ramon Bragós, Lexa Nescolarde

“…This study aims to use classification algorithms with minimally invasive electrical impedance spectroscopy to improve neoplastic lung tissue identification during biopsies. …”
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Statistics and behavior of clinically significant extra-pulmonary vein atrial fibrillation sources: machine-learning-enhanced electrographic flow mapping in persistent atrial fibri... by Peter Ruppersberg, Steven Castellano, Philip Haeusser, Kostiantyn Ahapov, Melissa H. Kong, Stefan G. Spitzer, Stefan G. Spitzer, Georg Nölker, Andreas Rillig, Tamas Szili-Torok

“…However, the underlying machine learning strategy used to develop and refine the EGF algorithm has not yet been detailed. Here, we present how our EGF Model—trained on procedural outcomes from 199 fully anonymized retrospective patient datasets—identifies clinically significant sources of AF and how this machine learning–driven hyperparameter optimization underlies its clinical effectiveness. …”
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Modernizing the Design Process for US Organ Allocation Policy: Toward a Continuous Distribution Policy for Kidneys by Elijah Pivo, PhD(c), James Alcorn, JD, Dimitris Bertsimas, PhD, Sarah E. Booker, MPH, Keighly Bradbrook, PhD, Thomas G. Dolan, MS, Lindsay V. Larkin, BA, Kayla R. Temple, BA, Nikolaos Trichakis, PhD

“…This improvement enabled the simulation of thousands of allocation policies, allowing the introduction of multiobjective optimization as a primary method for policy design. …”
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Research on False Alarm Rate Reducing Strategies for Subway Train Fire Alarm System by ZHANG Qian, XU Shaohong, XUE Hongquan

“…The false alarm rate can be reduced by hardware optimization methods such as adding dust filter devices, adopting dual light source detectors, multi-parameter gas detectors and pyrolysis particle detectors; the rate can also be reduced by optimizing software algorithms (optimization modeling method, automatic adjustment of alarm thresholds, machine self-learning algorithm, etc.). …”
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RIM-Net: A Real-Imaginary-Magnitude Network for NLOS/LOS Identification in UWB Indoor Positioning Systems by Jiacheng Ni, Fang Li, Shuai Cao, Linsong Li

“…Experimental results demonstrate that RIM-Net achieves an average accuracy of 92.36% on benchmark datasets while maintaining generalization capabilities above 85% in unseen environments. Furthermore, the optimization of the TOA algorithm validated the effectiveness of RIM-Net in localization, achieving an average performance improvement of 9.66%. …”
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Domain generalization for image classification based on simplified self ensemble learning. by Zhenkai Qin, Xinlu Guo, Jun Li, Yue Chen

“…In this paper, we present an approach that transcends merely eliminating domain discrepancies by enhancing the model's adaptability to improve its performance in unseen domains. …”
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Shape Adjustment of a Large Planar Phased Array Antenna With Nonlinear Cable Actuators by Jiyang Zhou, Xiang Liu, Guoping Cai, Jun Sun, Dongfang Zhu

“…Giving a detailed theoretical derivation, this paper demonstrates the necessity of considering nonlinearity of the cable actuator and proposes a nonlinear model of the active cable element. Further, an optimization model is established for shape adjustment, and the genetic algorithm is used to solve this problem. …”
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An enhanced iTransformer-based early warning system for predicting automotive rental contract breaches. by Ming Jiang, Dongpeng Peng, Haihan Yu, Shu Chen

“…The enhanced DBSCAN technique, which employs a snow ablation optimizer (SAO) algorithm, establishes an electronic barrier and integrates the iTransformer model for trajectory prediction. …”
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Deep Learning Methods and UAV Technologies for Crop Disease Detection by S. G. Mudarisov, I. R. Miftakhov

“…The paper also addresses challenges associated with the use of unmanned aerial vehicles, such as data quality limitations, the complexity of processing large volumes of images, and the need for the development of more advanced models. The paper proposes solutions to these issues, including algorithm optimization and improved data preprocessing techniques. …”
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Building Up a Robust Risk Mathematical Platform to Predict Colorectal Cancer by Le Zhang, Chunqiu Zheng, Tian Li, Lei Xing, Han Zeng, Tingting Li, Huan Yang, Jia Cao, Badong Chen, Ziyuan Zhou

“…Our results demonstrate that (1) the explored genetic and environmental biomarkers are validated to connect to the CRC by biological function- or population-based evidences, (2) the model can efficiently predict the risk of CRC after parameter optimization by the big CRC-related data, and (3) our innovated heterogeneous ensemble learning model (HELM) and generalized kernel recursive maximum correntropy (GKRMC) algorithm have high prediction power. …”
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Efficient Path Planning and Formation Control in Multi-Robot Systems: A Neural Fields and Auto-Switching Mechanism Approach by Raouf Fareh, Mohammed Baziyad, Tamer Farouk Rabie, Sofiane Khadraoui, Mohammad Habibur Rahman

“…On the other hand, the follower robots are equipped with an auto-switching potential method, which intelligently toggles between attractive forces guiding the followers toward the leader and repulsive forces preventing collisions based on a mathematical model. The effectiveness of this approach is validated through experiments, demonstrating significant improvements in execution speed, path smoothness, and overall system stability compared to competitive methods, including well-known techniques such as A*, Probabilistic RoadMap (PRM), Rapidly-exploring Random Tree Star (RRT*), and also against recent optimization techniques including Grey Wolf Optimization (GWO) and Whale Optimization Algorithm (WOA).…”
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A Systematic Mapping Study on State Estimation Techniques for Lithium-Ion Batteries in Electric Vehicles by Carolina Tripp-Barba, José Alfonso Aguilar-Calderón, Luis Urquiza-Aguiar, Aníbal Zaldívar-Colado, Alan Ramírez-Noriega

“…RUL prediction sees advancements through deep learning techniques, especially LSTM and gated recurrent units (GRUs), improved using algorithms such as Harris Hawks Optimization (HHO) and Adaptive Levy Flight (ALF). …”
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Research on data completion and generation of downhole drilling tool attitude based on Long Short-Term Memory neural networks by Qiwei Liu, Fanmin Kong, Xiaolong Chen, Kang Li

“…To overcome these limitations, a Long Short-Term Memory (LSTM) model, a type of deep learning algorithm known for capturing complex time-series dependencies, is proposed for data completion. …”
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Effect of New Mesh Fins on the Heat Storage Performance of a Solar Phase Change Heat Accumulator by Zihan Zhao, Jingzhi Jiang, Jingzhou An

“…The energy model and the solidification and melting model based on the enthalpy method were used to simulate and calculate the phase change process of PCM. …”
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