Effectively Detecting Communities by Adjusting Initial Structure via Cores by Mei Chen, Zhichong Yang, Xiaofang Wen, Mingwei Leng, Mei Zhang, Ming Li

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Machine Learning-Based Alfalfa Height Estimation Using Sentinel-2 Multispectral Imagery by Hazhir Bahrami, Karem Chokmani, Saeid Homayouni, Viacheslav I. Adamchuk, Rami Albasha, Md Saifuzzaman, Maxime Leduc

“…Our findings showed that XGB and RF could predict alfalfa crop height with an R² of 0.79 and a mean absolute error (MAE) of around 4 cm Our findings indicated that SVR exhibited the lowest accuracy among the three algorithms tested, with R² of 0.69 and an MAE of 4.63 cm. …”
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Playing hide and seek with primates: A comparative study of Theory of Mind by Aurore San‑Galli, Marie Devaine, Cinzia Trapanese, Shelly Masi, Sébastien Bouret, Jean Daunizeau

“…In fact, the location of the food was chosen by learning algorithms, some of which endowed with artificial ToM. …”
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Efficient Resource Allocation for Blockchain-Enabled Mobile Edge Computing: A Joint Optimization Approach by Moein Valitabar, Mohammad Fathi, Keivan Navaie

“…Performance evaluation results demonstrate the effectiveness of these algorithms, achieving significant reductions in total energy consumption while maximizing the efficiency of communication and computational resources. …”
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Vectorized building rooftop prints of the Qinghai-Tibetan Plateau and its neighboring regions by Tao Ye, Hongyu Shan, Jidong Wu, Qiang Zhou, Mingfu Ma, Wenzhi Zhao, Ru Ya, Yuan Gao, Lizheng Wu

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Modified Traffic Flow Model with Connected Vehicle Microscopic Data for Proactive Variable Speed Limit Control by Jie Fang, Huixuan Ye, Said M. Easa

“…The proposed VSL control algorithm adopts the Model Predictive Control (MPC) framework, which employs a modified version of the classic traffic flow model METANET to take advantage of the microscopic data in traffic flow predictions. …”
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Improving medical machine learning models with generative balancing for equity and excellence by Brandon Theodorou, Benjamin Danek, Venkat Tummala, Shivam Pankaj Kumar, Bradley Malin, Jimeng Sun

“…Abstract Applying machine learning to clinical outcome prediction is challenging due to imbalanced datasets and sensitive tasks that contain rare yet critical outcomes and where equitable treatment across diverse patient groups is essential. …”
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Research on Near-Infrared Non-Invasive Blood Glucose Detection Technology by Wang Jinshuo

“…In response to the complex and easily interfered characteristics of near-infrared spectral signals, an innovative BP neural network algorithm is introduced to construct a prediction model. …”
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Comprehensive Analysis Based on the Cancer Immunotherapy and Immune Activation of Gastric Cancer Patients by Feng Jiang, Qilong Ma

“…Finally, we were able to produce a 6-gene prognostic prediction model using immune-related genes. Further analysis revealed that the prognostic prediction model is closely related to the prognosis of patients with GC. …”
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Adaptive switching and routing protocol design and optimization in internet of things based on probabilistic models by Yi Yang

“…The paper explores the subject of data flow optimization using Fuzzy Assisted Cuckoo Search Optimization (FACSO), traffic flow using Gaussian Process Regression (GPR), and CH prediction using the Stochastic Optimization Algorithm (SOA). …”
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Research on gating alignment strategy for flow scheduling in satellite formation by XU Chuan, ZHANG Rufeng, HE Xiongwen, CUI Zhaojing, ZHAO Guofeng

“…Secondly, an online rolling gray scale prediction algorithm was designed to predict the delay of inter-node links, and based on the prediction results, the gated list deviation of neighboring nodes could be corrected dynamically to ensure the consistency of multi-node gated scheduling. …”
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Research on gating alignment strategy for flow scheduling in satellite formation by XU Chuan, ZHANG Rufeng, HE Xiongwen, CUI Zhaojing, ZHAO Guofeng

“…Secondly, an online rolling gray scale prediction algorithm was designed to predict the delay of inter-node links, and based on the prediction results, the gated list deviation of neighboring nodes could be corrected dynamically to ensure the consistency of multi-node gated scheduling. …”
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Multi-LiDAR-Based 3D Object Detection via Data-Level Fusion Method by Yu Luo, Tao Wang, Shuai Lu, Xuerui Dai, Zhi Li

“…Our algorithm has improved the global trajectory fusion rate from 91.7% to 95.6%. …”
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Simulation and experimental verification of the precision finishing method for optical free-form surface segmentation. by Chenhua Jiang, Enzhong Zhang, Wei Zhang, Jiaqi Hu, Jiechen Guo, Xiaodong Li

“…Finally, experiments revealed a 12.28% reduction in machining path length and a 12.56% reduction in machining time using the segmentation machining method. …”
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AIoT Monitoring for Early Identification of Diseases in Grapevines: Complete Study by Mihaela Hnatiuc, Domnica Alpetri, Sorin-Robertino Sintea, Bogdan Hnatiuc, Gabriel Margarit Raicu, Mirel Paun, Ionica Dina

“…Machine learning (ML) algorithms, running on a server with an NVIDIA R3900 card, process this data to predict potential infections caused by pathogens such as Plasmopara viticola, Uncinula necator, and Botrytis. …”
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Machine-Learning-Driven Analysis of Wear Loss and Frictional Behavior in Magnesium Hybrid Composites by Barun Haldar, Hillol Joardar, Arpan Kumar Mondal, Nashmi H. Alrasheedi, Rashid Khan, Murugesan P. Papathi

“…Data-driven machine learning (ML) algorithms were utilized to identify complex patterns and predict relationships between input variables and output responses. …”
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Nondestructive estimation of leaf chlorophyll content in banana based on unmanned aerial vehicle hyperspectral images using image feature combination methods by Weiping Kong, Weiping Kong, Lingling Ma, Huichun Ye, Huichun Ye, Jingjing Wang, Chaojia Nie, Binbin Chen, Xianfeng Zhou, Wenjiang Huang, Zikun Fan

“…We concluded that the nonlinear Gaussian process regression model with the VIs and TFs-PC1 combination selected by maximal information coefficient as input achieved the highest accuracy in LCC prediction for banana, with the highest R2 of 0.776 and lowest RMSE of 2.04. …”
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A novel molecular classification system based on the molecular feature score identifies patients sensitive to immune therapy and target therapy by Yang Li, Yang Li, Yinan Ding, Yinan Ding, Jinghao Wang, Xiaoxia Wu, Xiaoxia Wu, Dinghu Zhang, Dinghu Zhang, Han Zhou, Han Zhou, Pengfei Zhang, Pengfei Zhang, Guoliang Shao, Guoliang Shao

“…Subsequently, machine learning algorithms were used to predict the classifications and prognoses. …”
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A comprehensive investigation of the relationship between dietary fatty acid intake and preserved ratio impaired spirometry: multimethodology based on NHANES by Chenyuan Deng, Yu Jiang, Yuechun Lin, Hengrui Liang, Wei Wang, Jianxing He, Ying Huang

“…Subsequently, innovative implementation of the principal component analysis (PCA), Weighted Quantile Sum (WQS) regression, and Bayesian Kernel Machine Regression (BKMR) approaches were employed to assess the joint impact of the various intake of FAs, as well as total saturated, monounsaturated, and polyunsaturated FAs on PRISm. To facilitate the prediction of PRISm, six distinct machine learning algorithms were constructed, followed by the application of SHAP analysis to elucidate the contribution of individual predictors. …”
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Integrated phenotypic and transcriptomic characterization of desmin-related cardiomyopathy in hiPSC-derived cardiomyocytes and machine learning-based classification of disease feat... by Vivien Batoumeni, Yeranuhi Hovhannisyan, Bénédicte Gobert, Keyhan Alvandipour, Jennifer Arthur Ataam, Ombline Conrad, David Hoffmann, Nicolas Wiest-Daesslé, Jochen Dobner, José Américo Nabuco Leva Ferreira Freitas, Hakim Hocini, Zhenlin Li, Laurent Brino, Andrea Rossi, Onnik Agbulut, Peter Sommer, Pierre Joanne, Konstantinos Gkatzis

“…Finaly, we developed a machine learning prediction model to classify cellular phenotypes, which can be used for translational research, including drug candidate screening. …”
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