Finding a suitable chest x-ray image size for the process of Machine learning to build a model for predicting Pneumonia by Kriengsak Yothapakdee, Yosawaj Pugtao, Sarawoot Charoenkhun, Tanunchai Boonnuk, Kreangsak Tamee

“…This study focused on algorithm performance and training/testing time, evaluating the most suitable chest X-ray image size for machine learning models to predict pneumonia infection. …”
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Blockchain smart contract vulnerability detection based on GR algorithm by WANG Deguang, SHAN Mengtao, LI Fengqi, TONG Ning

“…Thus, a robust data foundation for multi-category detection was established. At the algorithmic design level, an improved GR (gated recurrent unit-random forest) algorithm model was proposed. …”
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Optimal Design of Integrating Two‐Level Artificial Intelligent With Three Degrees of Freedom‐PDF (TLNF‐3DOFPDF) Controller for AGC of Three‐Area Multi‐Sources Power System... by Getaneh Mesfin Meseret, Rajesh Kumhar, Tarkesh Kumar Mahato, Nishant Kumar, Poonam Lakra, M. D. Mofeed Alam

“…Controller parameters are fine‐tuned using a novel metaheuristic method called the Skill Optimization Algorithm (SOA). The research assesses controller performance using multiple indices Integral of Time‐weighted Squared Error (ITSE), Integral of Squared Error (ISE), Integral of Time‐weighted Absolute Error (ITAE), and Integral of Absolute Error (IAE) and finds that ISE yields the most optimal results. …”
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Rapid and Accurate Measurement of Major Soybean Components Using Near-Infrared Spectroscopy by Chenxiao Li, Jiatong Yu, Sheng Wang, Qinglong Zhao, Qian Song, Yanlei Xu

“…Comparative analysis revealed that the RF model consistently outperformed the others across most combinations. …”
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A Predictive Method for Greenhouse Soil Pore Water Electrical Conductivity Based on Multi-Model Fusion and Variable Weight Combination by Jiawei Zhao, Peng Tian, Jihong Sun, Xinrui Wang, Changjun Deng, Yunlei Yang, Haokai Zhang, Ye Qian

“…We propose a hybrid prediction model—PSO–CNN–LSTM–BOA–XGBoost (PCLBX)—that integrates a particle swarm optimization (PSO)-enhanced convolutional LSTM (CNN–LSTM) with a Bayesian optimization algorithm-tuned XGBoost (BOA–XGBoost). …”
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Advanced Planning Systems in Production Planning Control: An Ethical and Sustainable Perspective in Fashion Sector by Martina De Giovanni, Mariangela Lazoi, Romeo Bandinelli, Virginia Fani

“…The integration of metaheuristic algorithms—especially Ant Colony Optimization (ACO) and hybrid models like GA-ACO—further improves optimization performance by offering high-quality, near-optimal solutions without requiring extensive structural modeling. …”
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Adaptive dynamic ϵ-simulated annealing algorithm for tumor immunotherapy by Xiaoyan Sun, Xiaoyan Sun, Ying Jiang

“…The algorithm is applied to an improved tumor immunotherapy model (ITIT), formulated using ordinary differential equations (ODEs) based on established experimental and clinical studies. …”
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Adaptive average arterial pressure control by multi-agent on-policy reinforcement learning by Xiaofeng Hong, Walid Ayadi, Khalid A. Alattas, Ardashir Mohammadzadeh, Mohamad Salimi, Chunwei Zhang

“…Abstract The current research introduces a model-free ultra-local model (MFULM) controller that utilizes the multi-agent on-policy reinforcement learning (MAOPRL) technique for remotely regulating blood pressure through precise drug dosing in a closed-loop system. …”
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An Intelligent Client Selection Algorithm of Federated Learning for Class-imbalance by ZHU Suxia, WANG Yunmeng, YAN Peisen, SUN Guanglu

“… In the federated learning application scenario, if the data among the client devices shows the characteristics of non- independence identically distribution, or even class-imbalance, the optimization goal of the client local model will deviate from the global optimization goal, which brings great challenges to the performance of the global model. …”
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YOLOX-S-TKECB: A Holstein Cow Identification Detection Algorithm by Hongtao Zhang, Li Zheng, Lian Tan, Jiahui Gao, Yiming Luo

“…Therefore, this paper proposes a cow identification method based on YOLOX-S-TKECB. (1) Based on the characteristics of Holstein cows and their breeding practices, we constructed a real-time acquisition and preprocessing platform for two-dimensional Holstein cow images and built a cow identification model based on YOLOX-S-TKECB. (2) Transfer learning was introduced to improve the convergence speed and generalization ability of the cow identification model. (3) The CBAM attention mechanism module was added to enhance the model’s ability to extract features from cow torso patterns. (4) The alignment between the apriori frame and the target size was improved by optimizing the clustering algorithm and the multi-scale feature fusion method, thereby enhancing the performance of object detection at different scales. …”
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A quadratic weighted centroid algorithm for tunnel personnel positioning by Haiying Wang, Linhao Liang, Jian Xu, Hui She, Wuxiang Li

“…By adopting a Gaussian filter model to improve the range accuracy of the received signal strength indicator algorithm and combining the centroid algorithm and weighting factor with a trilateration positioning model, a quadratic weighted centroid algorithm is proposed to improve the positioning accuracy of unknown positioning nodes. …”
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Nonlinear Narrowband Active Noise Control for Tractors Based on a Momentum-Enhanced Volterra Filter by Tao Zhang, Zhixuan Guan, Shuai Zhang, Kai Song, Boyan Huang

“…To address this challenge, this paper proposes a momentum-enhanced Volterra filter-based active noise control (ANC) algorithm that improves both the modeling capability of nonlinear acoustic paths and the convergence performance of the system. …”
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Matlab-Based Modeling and Simulations to Study the Performance of Different MPPT Techniques Used for Photovoltaic Systems under Partially Shaded Conditions by Jehun Hahm, Jaeho Baek, Hyoseok Kang, Heejin Lee, Mignon Park

“…The proposed method applied a model to simulate the performance of the PV system for solar energy usage, which is compared to the conventional methods under nonuniform insolation improving the PV system utilization efficiency and allowing optimization of the system performance. …”
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Data-driven EV charging infrastructure with uncertainty based on a spatial–temporal flow-driven (STFD) models considering batteries by Talal Alharbi, Ahmed Abdalrahman, Mostafa H. Mostafa

“…The ESS placement is modeled as a multi-objective optimization problem, aiming to enhance voltage stability, reduce power losses, and improve voltage profiles. …”
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Development and validation of a quick screening tool for predicting neck pain patients benefiting from spinal manipulation: a machine learning study by Changxiao Han, Guangyi Yang, Haibao Wen, Minrui Fu, Bochen Peng, Bo Xu, Xunlu Yin, Ping Wang, Liguo Zhu, Minshan Feng

“…Conclusion Our machine learning model demonstrates robust performance in identifying suitable candidates for spinal manipulation among neck pain patients, offering clinicians an evidence-based practical tool to optimize patient selection and potentially improve treatment outcomes.…”
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Maximum likelihood self-calibration for direction-dependent gain-phase errors with carry-on instrumental sensors:case of deterministic signal model by WANG Ding1, PAN Miao2, WU Ying1

“…Aim at the self-calibration of direction-dependent gain-phase errors in case of deterministic signal model,the maximum likelihood method（MLM） for calibrating the direction-dependent gain-phase errors with carry-on instrumental sensors was presented.In order to maximize the high-dimensional nonlinear cost function appearing in the MLM,an improved alternative projection iteration algorithm,which could optimize the azimuths and direction-dependent gain-phase errors was proposed.The closed-form expressions of the Cramér-Rao bound（CRB） for azimuths and gain-phase errors were derived.Simulation experiments show the effectiveness and advantage of the novel method.…”
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Research on the Stability of Express Delivery Supply Chain Based on Risk Propagation Model ------ Case Studies of SF Express and JD Logistics by Fan Yunhui

“…Based on the research results, optimization strategies such as dynamic path optimization algorithms and blockchain-based information isolation mechanisms are proposed, providing theoretical tools and practical references for risk prevention and control in the express delivery industry.…”
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Optimization of software project evaluation system by Li ding .

“…An improved particle swarm optimization algorithm is introduced to solve the problem of determining the connection weight coefficient of the evaluation model accurately and efficiently. …”
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Neurodynamic robust adaptive UWB localization algorithm with NLOS mitigation by Yanxu Liu, Enwen Hu, Yudong Chen, Changyou Guo

“…We proposed an adaptive distance error upper bound method to improve the accuracy of localization model. Tested in representative numerical simulation and real environments, our proposed robust adaptive positioning algorithm outperforms existing methods in terms of localization accuracy and robustness, especially in severe NLOS environments.…”
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Maximum likelihood self-calibration for direction-dependent gain-phase errors with carry-on instrumental sensors:case of deterministic signal model by WANG Ding1, PAN Miao2, WU Ying1

“…Aim at the self-calibration of direction-dependent gain-phase errors in case of deterministic signal model,the maximum likelihood method（MLM） for calibrating the direction-dependent gain-phase errors with carry-on instrumental sensors was presented.In order to maximize the high-dimensional nonlinear cost function appearing in the MLM,an improved alternative projection iteration algorithm,which could optimize the azimuths and direction-dependent gain-phase errors was proposed.The closed-form expressions of the Cramér-Rao bound（CRB） for azimuths and gain-phase errors were derived.Simulation experiments show the effectiveness and advantage of the novel method.…”
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