Simulating the root-to-shoot ratio of natural grassland biomass in China by the AutoGluon framework by Rui Guo, Xiaodong Huang, Yangjing Xiu, Minglu Che, Jinlong Gao, Shuai Fu, Qisheng Feng, Tiangang Liang

“…In this study, a high-accuracy R/S model was constructed using the AutoGluon framework and traditional machine learning (ML) algorithms with 1,367 R/S samples of grassland in China, integrating climate, soil, terrain and spectral features. …”
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Method for Knowledge Transfer via Multi-Task Semi-Supervised Self-Paced by Yao Zhao, Hongying Liu, Huaxian Pan, Zhen Song, Chunting Liu, Anni Wei, Baoshuang Zhang, Wei Lu

“…With the aid of a self-controlled learning pace, a more robust and globally optimal model can be gradually constructed. Experimental results on several benchmark datasets show that our method achieves a performance gain of 3%-15% in classification accuracy compared to baseline algorithms, along with significant advantages in convergence speed.…”
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A double-layer ensemble framework for rubber plantation mapping using multi-source data in the google earth engine: a case study of the southwestern border region of China by Hui Wang, Jie Li, Jinliang Wang, Yuncheng Deng, Shupeng Gao, Jing Zou, An Chen, Haichao Xu

“…This layer utilizes five machine learning algorithms, namely Random Forest, Maximum Entropy Model, Gradient Tree Boosting, Support Vector Machine, and Classification and Regression Tree, to construct the corresponding PFT-EMs. …”
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Digital pathology-based artificial intelligence model to predict microsatellite instability in gastroesophageal junction adenocarcinomas by Zhenqian Li, JingQi Chen, Miaomiao Sun, Daoming Li, Kuisheng Chen

“…A whole-slide image (WSI)-level AI model was constructed by integrating deep learning- generated pathological features with six machine learning algorithms.ResultsThe MLP model showed demonstrated the highest performance in predicting MSI-H in the test cohort, achieving an AUC of 93.3%, a sensitivity of 0.841, and a specificity of 0.952. …”
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AlzhCPI: A knowledge base for predicting chemical-protein interactions towards Alzheimer's disease. by Jiansong Fang, Ling Wang, Yecheng Li, Wenwen Lian, Xiaocong Pang, Hong Wang, Dongsheng Yuan, Qi Wang, Ai-Lin Liu, Guan-Hua Du

“…Another 104 binary classifiers were further constructed to predict the CPI for 26 preclinical AD targets based on the naive Bayesian (NB) and recursive partitioning (RP) algorithms. …”
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Research on Security Enhancement for Abnormal Content Release in Unified Audio Video Information service Systems by FENG Junhao

“…Method The content audit system using decision tree algorithms is combined with a unified audio video information service system, to construct an integrated data and multi-dimensional information security model, thereby improving the existing audio video information security management system. …”
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A New High-Performance Photovoltaic Emulator Suitable for Simulating and Validating Maximum Power Point Tracking Controllers by Ambe Harrison, Njimboh Henry Alombah

“…Currently, researchers face several challenges in testing MPPT algorithms due to the unpredictable nature of solar PV power generation. …”
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Impurity rates detection for pepper harvesting based on YOLOv8n-Seg-ASB and random forest by Lijian Lu, Jin Lei, Chenming Cheng, Shiguo Wang, Chengfu Wang, Xinyan Qin

“…To address the inaccuracies and inefficiencies of pepper impurity rates detection caused by complex material compositions and variable harvesting environments, this paper proposes a detection technique based on deep and machine learning algorithms. First, a machine vision-based image acquisition device for pepper material is designed to reliably capture high-quality real-time images. …”
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Identify the potential target of efferocytosis in knee osteoarthritis synovial tissue: a bioinformatics and machine learning-based study by Shangbo Niu, Shangbo Niu, Shangbo Niu, Mengmeng Li, Mengmeng Li, Mengmeng Li, Jinling Wang, Jinling Wang, Jinling Wang, Peirui Zhong, Peirui Zhong, Peirui Zhong, Xing Wen, Xing Wen, Xing Wen, Fujin Huang, Fujin Huang, Fujin Huang, Linwei Yin, Linwei Yin, Linwei Yin, Yang Liao, Yang Liao, Yang Liao, Jun Zhou, Jun Zhou, Jun Zhou

“…Subsequently, we utilized univariate logistic regression analysis, least absolute shrinkage and selection operator regression, support vector machine, and random forest algorithms to further refine these genes. The results were then inputted into multivariate logistic regression analysis to construct a diagnostic nomogram. …”
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The prognostic predictive value of indirect bilirubin-inflammation score in patients with nasopharyngeal carcinoma by JI Huojin, LI Jun, LUO Yonglin, QIN Weiling, YE Yinxin, CAI Yonglin

“…Results By comparing 14 types of machine learning algorithms, the optimal model, oblique random survival forest, was selected to construct IBI score. …”
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A deep neural network framework for estimating coastal salinity from SMAP brightness temperature data by Yidi Wei, Qing Xu, Qing Xu, Xiaobin Yin, Xiaobin Yin, Yan Li, Yan Li, Kaiguo Fan

“…The framework leverages machine learning interpretability tools (Shapley Additive Explanations, SHAP) to optimize input feature selection and employs a grid search strategy for hyperparameter tuning.Results and discussionSystematic validation against independent in-situ measurements demonstrates that the baseline DNN model constructed for the entire region and time period outperforms conventional algorithms including K-Nearest Neighbors, Random Forest, and XGBoost and the standard SMAP SSS product, achieving a reduction of 36.0%, 33.4%, 40.1%, and 23.2%, respectively in root mean square error (RMSE). …”
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Utilizing an NLP-supported mobile reflection application to explore academic engagement, application engagement, and performance in engineering and physics courses by Saira Anwar, Ahmed Ashraf Butt, Muhsin Menekse

“…Abstract Background Technology-enhanced classrooms now integrate a range of educational apps designed to improve student outcomes. …”
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A nicotinamide metabolism-related gene signature for predicting immunotherapy response and prognosis in lung adenocarcinoma patients by Meng Wang, Wei Li, Fang Zhou, Zheng Wang, Xiaoteng Jia, Xingpeng Han

“…Subsequently, differential expression analysis was conducted using the limma package, and univariate, multivariate and LASSO regression analyses were performed on the screened genes to construct a risk model for LUAD. Next, the MCP-counter, TIMER and ESTIMATE algorithms were utilized to comprehensively assess the immune microenvironmental profile of LUAD patients in different risk groups. …”
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Machine learning-based brain magnetic resonance imaging radiomics for identifying rapid eye movement sleep behavior disorder in Parkinson’s disease patients by Yandong lian, Yibin Xu, Linlin Hu, Yuguo Wei, Zhaoge Wang

“…Feature reduction was performed on the training set data to construct radiomics signatures. Additionally, multi-factor logistic regression analysis identified clinical predictors associated with PD-RBD, and these clinical features were integrated with the radiomics signatures to develop predictive models using various machine learning algorithms. …”
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Cam Design and Pin Defect Detection of Cam Pin Insertion Machine in IGBT Packaging by Wenchao Tian, Pengchao Zhang, Mingfang Tian, Si Chen, Haoyue Ji, Bingxu Ma

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Research on Maneuvering Motion Prediction for Intelligent Ships Based on LSTM-Multi-Head Attention Model by Dongyu Liu, Xiaopeng Gao, Cong Huo, Wentao Su

“…We propose a novel maneuvering motion prediction method based on Long Short-Term Memory (LSTM) and Multi-Head Attention Mechanisms (MHAM). To construct a foundational dataset, we integrate Computational Fluid Dynamics (CFD) numerical simulation technology to develop a mathematical model of actual ship maneuvering motions influenced by wind, waves, and currents. …”
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A deep learning framework for predicting disease-gene associations with functional modules and graph augmentation by Xianghu Jia, Weiwen Luo, Jiaqi Li, Jieqi Xing, Hongjie Sun, Shunyao Wu, Xiaoquan Su

“…ModulePred performs graph augmentation on the protein interaction network using L3 link prediction algorithms. It builds a heterogeneous module network by integrating disease-gene associations, protein complexes and augmented protein interactions, and develops a novel graph embedding for the heterogeneous module network. …”
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Dynamic Collaborative Optimization Method for Real-Time Multi-Object Tracking by Ziqi Li, Dongyao Jia, Zihao He, Nengkai Wu

“…On the MOT17 test set, it achieves 63.7% in HOTA, 61.4 FPS in processing speed, and 79.4% in IDF1, outperforming current state-of-the-art tracking algorithms.…”
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State of Health Prediction for Lithium-Ion Batteries Based on Gated Temporal Network Assisted by Improved Grasshopper Optimization by Xiankun Wei, Silun Peng, Mingli Mo

“…Accurate SOH prediction provides a reliable reference for lithium-ion battery maintenance. However, novel algorithms are still needed because few studies have considered the correlations between monitored parameters in Euclidean space and non-Euclidean space at different time points. …”
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Predicting College Student Engagement in Physical Education Classes Using Machine Learning and Structural Equation Modeling by Liguo Zhang, Jiarui Gao, Liangyu Zhao, Zetan Liu, Anlin Guan

“…The findings underscore the importance of integrating digital tools strategically in PE classrooms to enhance engagement. …”
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