IMA-FLADRC-Based Electric-Driven High-Speed Maize Precision Seeding Control Strategy and System by Song Wang, Shujuan Yi, Bin Zhao, Yifei Li, Dongming Zhang, Tao Chen, Wensheng Sun

“…This study develops an electric-driven high-speed maize precision seeding control system, establishing kinematic models for the seeding and guiding motors relative to operating speed. An Improve Mayfly Algorithm-Fuzzy Linear Active Disturbance Rejection Control (IMA-FLADRC)-based control strategy is proposed, integrating a fuzzy algorithm to adaptively adjust the proportional coefficient of the Linear State Error Feedback (LSEF) and optimizing key parameters using an IMA, enhancing system adaptability and robustness. …”
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Research on Rolling Bearing Fault Diagnosis Using Improved Majorization-Minimization-Based Total Variation and Empirical Wavelet Transform by Yangli Ou, Shuilong He, Chaofan Hu, Jiading Bao, Wenjie Li

“…Therefore, an improved particle swarm algorithm (IPSO) is used to find the optimal solution of λ. …”
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Association between admission Braden Skin Score and delirium in surgical intensive care patients: an analysis of the MIMIC-IV database by Meiling Shang, Meiling Shang, Ailing Shang, Yu Xu, Yu Xu

“…Feature importance of BSS was initially assessed using a machine learning algorithm, while restricted cubic spline (RCS) models and multivariable logistic analysis evaluated the relationship between BSS and delirium. …”
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Connected Transit Bus Dynamic Priority Weight Modeling and Conflicting Request Resolution Control at the Signalized Intersection by Shuxian He, Haihang Han, Huan Zhang, Shanzhi Sun, Tony Z. Qiu

“…What is more, it shows better delay optimization for social vehicles than the algorithm with delay as the objective while declining bus delay appreciable quantity with 43.4 s in average. …”
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Spectrum Sharing Design for Integrated Aeronautical Communication and Radar System by Lanchenhui Yu, Jingjing Zhao, Quan Zhou, Yanbo Zhu, Kaiquan Cai

“…An alternative optimization (AO) algorithm is proposed to solve the non-convex problem with highly coupled variables. …”
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Network capacity with probit-based stochastic user equilibrium problem. by Lili Lu, Jian Wang, Pengjun Zheng, Wei Wang

“…The network capacity is formulated as a bi-level programming where the up-level program is to maximize the network capacity through optimizing input parameters (O-D multiplies and signal splits) while the low-level program is the Logit-based or Probit-based SUE problem formulated to model the drivers' route choice. …”
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Investigation of a staggered dual-rotor wound field synchronous motor for offshore wind turbine full-scale testing platforms by Yang Xue, Shiyao Qin, Chen Qi, Ning Wang, Cong Liu, Wenliang Zhao

“…To enhance average torque and minimize torque ripple, the rotor structure undergoes further optimization through a multi-objective genetic algorithm. …”
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Estimating the Risk of Lower Extremity Complications in Adults Newly Diagnosed With Diabetic Polyneuropathy: Retrospective Cohort Study by Alyce S Adams, Catherine Lee, Gabriel Escobar, Elizabeth A Bayliss, Brian Callaghan, Michael Horberg, Julie A Schmittdiel, Connie Trinacty, Lisa K Gilliam, Eileen Kim, Nima S Hejazi, Lin Ma, Romain Neugebauer

“…Methods for early detection of individuals at high risk remain elusive. While data-driven diabetic polyneuropathy algorithms exist, high-performing, clinically useful tools to assess risk are needed to improve clinical care. …”
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SMART DShot: Secure Machine-Learning-Based Adaptive Real-Time Timing Correction by Hyunmin Kim, Zahid Basha Shaik Kadu, Kyusuk Han

“…Our approach addresses critical vulnerabilities in Electronic Speed Controller (ESC) interfaces by deploying four synergistic algorithms—Kalman Filter Timing Correction (KFTC), Recursive Least Squares Timing Correction (RLSTC), Fuzzy Logic Timing Correction (FLTC), and Hybrid Adaptive Timing Correction (HATC)—each optimized for specific error characteristics and attack scenarios. …”
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Analysis of influencing factors and equity in hospitalization expense reimbursement for mobile populations based on random forest model: a cross-sectional study from China by Lisheng Shen, Xinan Lu, Yanyun Zhang, Lin Fei, Bo Dong

“…Secondly, the random forest algorithm was applied to evaluate the importance of the factors influencing hospitalization expense reimbursement. …”
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TAL-SRX: an intelligent typing evaluation method for KASP primers based on multi-model fusion by Xiaojing Chen, Xiaojing Chen, Jingchao Fan, Jingchao Fan, Shen Yan, Longyu Huang, Longyu Huang, Longyu Huang, Guomin Zhou, Guomin Zhou, Jianhua Zhang, Jianhua Zhang

“…Then, a hybrid neural network is constructed by combining ANN and LSTM to capture nonlinear relationships and extract complex features, while the Transformer algorithm is introduced to capture global dependencies in high-dimensional feature space. …”
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Energy Efficient Design for Two-Way AF Relay Networks by Yong Li, Zhengguang Zheng, Mingyue Zhao, Yunli Chen, Chuanyong Liu

“…In this paper, we consider a system where two source nodes communicate with each other via an amplify-and-forward (AF) relay node and study the power allocation schemes to maximize EE while ensuring a certain data rate. We propose an optimal energy-efficient power allocation algorithm based on iterative search technique. …”
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Management of Calcified Coronary Lesions by Khaled Al-Shaibi, Aditya Bharadwaj, Atul Mathur, Ashish Jaikishen, Robert Riley

“…A variety of treatment options for these lesions exist, including specialized balloons, atherectomy, and intravascular lithotripsy. While there is currently no universally accepted algorithm for choosing between these treatment strategies, several different algorithms exist, and the optimization of these treatment regimens will continue to evolve in the coming years. …”
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Stability of optical knots in atmospheric turbulence by D. G. Pires, D. Tsvetkov, H. Barati Sedeh, N. Chandra, N. M. Litchinitser

“…Additionally, we propose an optimization algorithm to maximize the distance between the phase singularities at each longitudinal plane, facilitating measurements of optical knots and improving their performance in the presence of turbulence.…”
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An Improved Diagnosis Approach for Short-Circuit Fault Diagnosis in MPC-Based Current Source Inverter System by Jonggrist Jongudomkarn, Pirat Khunkitti, Apirat Siritaratiwat

“…In the presence of faulty switches, the algorithm identifies the phase of the reference current where the predicted currents align with the reference values. …”
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A model predictive control method for directional borehole trajectories in underground coal mines by Hao LI, Ningping YAO, Chengda LU, Jinbao ZHANG, Hongchao WEI, Jiajun WU, Jinyu LI

“…Finally, the control algorithm was validated using the drilling data from a coal mine in Hancheng City, Shaanxi Province. …”
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An echo state network based on enhanced intersecting cortical model for discrete chaotic system prediction by Xubin Wang, Pei Ma, Jing Lian, Jizhao Liu, Yide Ma

“…The model incorporates a neuron model with internal dynamics, including adaptive thresholds and inter-neuron feedback, into the reservoir structure. A Bayesian Optimization algorithm was employed for the selection of hyperparameters. …”
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SmartExplorer1.0: A Novel Intelligent Framework for Path Planning in Robotics by Chiara Furio, Angelo Ugenti, Giulio Reina, Mario Massimo Foglia, Luciano Lamberti

“…The SmartExplorer1.0 algorithm (SE1.0) utilizes Digital Terrain Models (DTMs) as input to identify navigable areas and plan optimal routes by incorporating terrain gradients, obstacle types, and environmental conditions. …”
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A Deep Reinforcement Learning-Based Cooperative Guidance Strategy Under Uncontrollable Velocity Conditions by Hao Cui, Ke Zhang, Minghu Tan, Jingyu Wang

“…This method employs the multi-agent proximal policy optimization (MAPPO) algorithm to construct a continuous action space framework for intelligent cooperative guidance. …”
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Meta-learning assisted robust control of universal quantum gates with uncertainties by Shihui Zhang, Zibo Miao, Yu Pan, Sibo Tao, Yu Chen

“…The inner reinforcement learning network focuses on decision making for specific optimization problems, while the outer meta-learning network adapts to varying environments and provides feedback to the inner network. …”
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