Unveiling diagnostic biomarkers and therapeutic targets in lung adenocarcinoma using bioinformatics and experimental validation by Sixuan Wu, Yuanbin Tang, Qihong Pan, Yaqin Zheng, Yeru Tan, Junfan Pan, Yuehua Li

“…In addition, a machine learning model constructed based on Stepglm[backward] with the random forest algorithm achieved the highest C-index (0.999) and screened eight core genes, among which ST14 was noted for its excellent predictive ability. …”
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Machine learning based screening of biomarkers associated with cell death and immunosuppression of multiple life stages sepsis populations by Jie Yang, Fanyan Ou, Binbin Li, Lixiong Zeng, Qiuli Chen, Houyu Gan, Jianing Yu, Qian Guo, Jihua Feng, Jianfeng Zhang

“…It was significantly positively correlated with M0-type macrophages and significantly negatively correlated with activated CD4 + memory T cells. (3) In the adult sepsis population, models constructed using GBM, SVM, and LASSO algorithms showed the best performance. …”
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A data science pipeline applied to Australia's 2022 COVID-19 Omicron waves by James M. Trauer, Angus E. Hughes, David S. Shipman, Michael T. Meehan, Alec S. Henderson, Emma S. McBryde, Romain Ragonnet

“…We developed a package for the construction of infectious disease models, integrated it with several open-source libraries and applied this composite pipeline to multiple data sources that provided insights into Australia's 2022 COVID-19 epidemic. …”
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An ensemble learning model to predict lymph node metastasis in early gastric cancer by Kaiqing Song, Jiaming Wu, Muchen Xu, Mengying Li, Yuqi Chen, Yi Zhang, Hong Chen, Caifeng Jiang

“…An ensemble learning model was subsequently constructed by integrating these five models. The model’s performance was evaluated by the AUC, accuracy, and F1 score. …”
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Water quality prediction and carbon reduction mechanisms in wastewater treatment in Northwest cities using Random Forest Regression model by Jingjing Sun, Xin Guan, Xiaojun Sun, Xiaojing Cao, Yepei Tan, Jiarong Liao

“…The work first establishes a Random Forest Regression (RFR) model. The RFR algorithm integrates Bagging ensemble learning and random subspace theory to construct multiple decision trees and aggregate their predictions, thereby enhancing the model’s prediction accuracy and stability. …”
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TFF-Net: A Feature Fusion Graph Neural Network-Based Vehicle Type Recognition Approach for Low-Light Conditions by Huizhi Xu, Wenting Tan, Yamei Li, Yue Tian

“…To further improve its robustness, we propose an Adaptive Weighted Fusion-Bagging (AWF-Bagging) algorithm, which dynamically assigns weights to base classifiers based on their F1 scores. …”
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A convolutional neural network driven suspension control strategy to enhance sustainability of high-speed trains by Duo Zhang, Hong-Wei Li, Fang-Ru Zhou, Yin-Ying Tang, Qi-Yuan Peng

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Dynamic Coal Flow-Based Energy Consumption Optimization of Scraper Conveyor by Qi Lu, Yonghao Chen, Xiangang Cao, Tao Xie, Qinghua Mao, Jiewu Leng

“…The multi-objective optimization model for energy consumption is solved using the NSGA-II-ARSBX algorithm, yielding a 33.7% reduction in energy consumption, while the lump coal area is reduced by 27.7%, indicating a trade-off between energy efficiency and coal fragmentation. …”
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A Novel Crowdsourcing-Assisted 5G Wireless Signal Ranging Technique in MEC Architecture by Rui Lu, Lei Shi, Yinlong Liu, Zhongkai Dang

“…This study designs a progressive solution by (1) building a crowdsourced data collection network, using mobile terminals equipped with GPS technology to automatically collect device signal features, replacing inefficient manual drive tests; (2) developing a progressive signal update algorithm that integrates real-time crowdsourced data and historical signals to optimize the signal fingerprint database in dynamic environments; (3) establishing an edge service architecture to offload signal matching and trajectory estimation tasks to MEC nodes, using lightweight computing engines to reduce the load on the core network. …”
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Explainable Artificial Intelligence (XAI) for Flood Susceptibility Assessment in Seoul: Leveraging Evolutionary and Bayesian AutoML Optimization by Kounghoon Nam, Youngkyu Lee, Sungsu Lee, Sungyoon Kim, Shuai Zhang

“…We first employed the Tree-based Pipeline Optimization Tool (TPOT), an evolutionary AutoML algorithm, to construct baseline ensemble models using Gradient Boosting (GB), Random Forest (RF), and XGBoost (XGB). …”
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Optimization of Fused Deposition Modeling Parameters for Mechanical Properties of Polylactic Acid Parts Based on Kriging and Cuckoo Search by Yuan Yang, Yiyang Wang, Bowen Xue, Changxu Wang, Bo Yang

“…As an emerging rapid manufacturing technology, 3D printing has been widely applied in numerous fields such as aerospace, shipbuilding, and wind power, by virtue of its advantage in efficiently fabricating components with complex structures and integrated functions. In response to the problems of poor mechanical properties and difficulty in selecting process parameters for fused deposition modeling (FDM), this paper analyzed the principle of FDM and proposed a parameter optimization method based on a Kriging and Cuckoo Search (CS) algorithm aimed at improving the mechanical properties of 3D printed polylactic acid (PLA) parts. …”
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A novel prediction method for low wind output processes under very few samples based on improved W‐DCGAN by Shihua Liu, Han Wang, Weiye Song, Shuang Han, Jie Yan, Yongqian Liu

“…Finally, three prediction algorithms are used to construct LWOP prediction models based on both generated and actual samples, respectively. …”
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Dynamic contagion potential framework for optimizing infection control in healthcare by Alexandra Fedrigo, Mohamad Nassar, Jennifer Bail, Antonia Bates-Ford, Satyaki Roy

“…The framework also introduces a CP-based optimization algorithm for patient-to-unit assignments that jointly minimizes contagion risk while satisfying clinical and logistical constraints.ResultsThe framework's efficacy is validated through modular and integrated evaluations. …”
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Multi-Agent Mapping and Tracking-Based Electrical Vehicles with Unknown Environment Exploration by Chafaa Hamrouni, Aarif Alutaybi, Ghofrane Ouerfelli

“…When rapid deliveries are required, the algorithm prioritizes faster routes, whereas, for flexible schedules, it optimizes energy conservation. …”
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Drilling Condition Identification Method for Imbalanced Datasets by Yibing Yu, Huilin Yang, Fengjia Peng, Xi Wang

“…Finally, a coupled model integrating bidirectional long short-term memory (BiLSTM) networks and gated recurrent units (GRUs) is constructed. …”
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Species Distribution Models and Ecological Suitability Analysis for Potential Tick Vectors of Lyme Disease in Mexico by Patricia Illoldi-Rangel, Chissa-Louise Rivaldi, Blake Sissel, Rebecca Trout Fryxell, Guadalupe Gordillo-Pérez, Angel Rodríguez-Moreno, Phillip Williamson, Griselda Montiel-Parra, Víctor Sánchez-Cordero, Sahotra Sarkar

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DualTransAttNet: A Hybrid Model with a Dual Attention Mechanism for Corn Seed Classification by Fei Pan, Dawei He, Pengjun Xiang, Mengdie Hu, Daizhuang Yang, Fang Huang, Changmeng Peng

“…Existing classification algorithms often suffer from limitations such as reliance on single information sources, constrained feature extraction capabilities, time consumption, low accuracy, and the potential to cause irreversible damage to seeds. …”
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Distress-Based Pavement Condition Assessment Using Artificial Intelligence: A Case Study of Egyptian Roads by Mostafa M. Radwan, Sundus A. Faris, Ahmed Y. Barakat, Ahmad Mousa

“…The pavement is a complex construction subject to a range of environmental and loading conditions. …”
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Visual analysis of multi-subject association patterns in high-dimensional time-varying student performance data by Lianen Ji, Ziyi Wang, Shirong Qiu, Guang Yang, Sufang Zhang

“…MAPVis consists of two stages: in the first stage, we extract students’ learning patterns and further introduce mutual information to explore the distribution of learning patterns; in the second stage, various learning patterns and subject attributes are integrated based on a hierarchical apriori algorithm to achieve a multi-subject interactive exploration of the association patterns among students, courses, and teachers. …”
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Non-overlapping friction element for soil-structure interaction and its application by Tonglu LI, Haitao WANG, Sifan YUAN, Yingzhe LI, Xinglai SUN, Wei SHEN, Yukai FU, Ping LI

“…The corresponding finite element algorithm is established by constructing the element stiffness matrix of the non-overlapping friction element and assembling it into the global stiffness matrix. …”
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