An effective communication topology for performance optimization: a case study of the finite-volume wave modeling (FVWAM) by R. Pang, R. Pang, R. Pang, F. Yu, F. Yu, F. Yu, Y. Gao, Y. Yuan, Y. Yuan, Y. Yuan, L. Yuan, Z. Gao

“…<p>High-resolution models are essential for simulating small-scale processes and topographical features, which play a crucial role in understanding meteorological and oceanic events, as well as climatic patterns. …”
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Abnormal Sound Detection of Wind Turbine Gearboxes Based on Improved MobileFaceNet and Feature Fusion by Yuelong Liang, Haorui Liu, Yayu Chen

“…To solve problems such as the unstable detection performance of the sound anomaly detection of wind turbine gearboxes when only normal data are used for training, and the poor detection performance caused by the poor classification of samples with high similarity, this paper proposes a self-supervised wind turbine gearbox sound anomaly detection algorithm that fuses time-domain features and Mel spectrograms, improves the MobileFaceNet (MFN) model, and combines the Gaussian Mixture Model (GMM). …”
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Improving crop rotation classification using a random forest model incorporating spatial heterogeneity by Xiaomi Wang, Qi Tang, Kang Yang

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Interpretable Machine Learning Framework for Non-Destructive Concrete Strength Prediction with Physics-Consistent Feature Analysis by Teerapun Saeheaw

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A compositional model for effort‐aware Just‐In‐Time defect prediction on android apps by Kunsong Zhao, Zhou Xu, Meng Yan, Lei Xue, Wei Li, Gemma Catolino

“…In general, high‐quality features are benefits for improving the classification performance. …”
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Fish Biomass Estimation Under Occluded Features: A Framework Combining Imputation and Regression by Yaohui Yang, Lijun Zhang, Zhixiang Liu, Tuyan Luo, Baolong Bao, Liping Zhou, Jingxiang Xu

“…In biomass estimation based on size-related features, regression models are commonly used to predict fish mass. …”
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Relationship extraction between entities with long distance dependencies and noise based on semantic and syntactic features by Lei Wang, Fei Wu, Xiaoqing Liu, Jilong Cao, Mingwei Ma, Zhaoyang Qu

“…Specifically, we leverage contextual semantic features generated by the pre-trained BERT model alongside syntactic features derived from dependency syntax graphs, effectively utilizing the complementary strengths of both sources of information to enhance the model’s performance in long-distance dependency scenarios. …”
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Performance Evaluation of a Hybrid Roundabout Using a Microscopic Simulation by Yavuz User, Seyitali İlyas, Gultekin Tinaztepe

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A stacked ensemble approach to detect cyber attacks based on feature selection techniques by Wahida Ferdose Urmi, Mohammed Nasir Uddin, Md Ashraf Uddin, Md. Alamin Talukder, Md. Rahat Hasan, Souvik Paul, Moumita Chanda, John Ayoade, Ansam Khraisat, Rakib Hossen, Faisal Imran

“…However, the effectiveness of CADS is highly dependent on selecting pertinent features. This research evaluates the impact of three feature selection techniques—Recursive Feature Elimination (RFE), Mutual Information (MI), and Lasso Feature Selection (LFS)—on CADS performance. …”
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Physics-inspired time-frequency feature extraction and lightweight neural network for power quality disturbance classification by Zhiwen Hou, Boyu Wang, Jingrui Liu, Yumeng He, Yuxuan Yao

“…This study proposes a lightweight and efficient classification method for Power Quality Disturbances (PQDs) using the PowerMobileNet model, which combines the S-transform for time-frequency feature extraction and the MobileNetV3-CBAM neural network for enhanced classification performance. …”
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Predicting Landing Position Deviation in Low-Visibility and Windy Environment Using Pilots’ Eye Movement Features by Xiuyi Li, Yue Zhou, Weiwei Zhao, Chuanyun Fu, Zhuocheng Huang, Nianqian Li, Haibo Xu

“…Two machine learning models (SVR and RF) and four deep learning models (GRU, LSTM, CNN-GRU, and CNN-LSTM) are trained with these feature sets to predict the landing position deviation. …”
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Simultaneous count data feature selection and clustering using Multinomial Nested Dirichlet Mixture by Fares Alkhawaja, Manar Amayri, Nizar Bouguila

“…The Minimum Message Length criterion is used to simultaneously determine the best number of components in the mixture with the updated selected features. At the price of convergence times, the results show better performance through different metrics, as the model aims to select the salient features and tune away the non-salient anomalistic features.…”
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A Computational Model of Attention-Guided Visual Learning in a High-Performance Computing Software System by Alice Ahmed, Md. Tanim Hossain

“…The work employs relative two-dimensional positional encoding to address the challenge of encoding two-dimensional data such as photographs. The feature-similarity gain model proposes that attention multiplicatively strengthens neuronal responses based on how similar their feature tuning is to the attended input. …”
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A Lightweight and High-Performance YOLOv5-Based Model for Tea Shoot Detection in Field Conditions by Zhi Zhang, Yongzong Lu, Yun Peng, Mengying Yang, Yongguang Hu

“…Then, YOLOv5 was modified with a parallel-branch fusion downsampling block and a lightweight feature extraction block. The modified model was then further compressed using model pruning and knowledge distillation, which led to additional improvements in detection performance. …”
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Identification of biomarkers for knee osteoarthritis through clinical data and machine learning models by Wei Chen, Haotian Zheng, Binglin Ye, Tiefeng Guo, Yude Xu, Zhibin Fu, Xing Ji, Xiping Chai, Shenghua Li, Qiang Deng

“…Models were developed for subsets of variables, including the top 5, top 10, top 15, and all identified features. …”
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Integrating fuzzy Kano model and fuzzy importance–performance analysis to analyse the attractive factors of new products by Le Xi, Hui Zhang, Sunan Li, Jianxin Cheng

“…The results indicate that the attractive factors sorted through integrated fuzzy Kano model–fuzzy importance–performance analysis have deconstructed abstract factors and feature factors of the customer service robot. …”
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Performance prediction of sintered NdFeB magnet using multi-head attention regression models by Qichao Liang, Qiang Ma, Hao Wu, Rongshun Lai, Yangyang Zhang, Ping Liu, Tao Qi

“…The model enables parallel data processing, accelerates both training and inference speed, and reduces reliance on feature engineering and hyperparameter tuning. …”
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High-Performance and Lightweight AI Model with Integrated Self-Attention Layers for Soybean Pod Number Estimation by Qian Huang

“…In future work, we plan to expand the dataset by incorporating diverse soybean images to enhance model generalizability. Additionally, we aim to explore more advanced attention mechanisms—such as CBAM or ECA—to further improve feature extraction and model performance. …”
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Comparative Analysis of VGG16 and ResNet50 Model Performence in Cardiac ECG Image Classification by Hanif Rizaqi, Imam Tahyudin

“…To enhance training efficiency and prevent overfitting, early stopping was implemented based on validation loss performance. Model performance was evaluated using accuracy, precision, recall, and F1-score metrics. …”
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Dynamic Text Augmentation for Robust Sentiment Analysis: Enhancing Model Performance With EDA and Multi-Channel CNN by Komang Wahyu Trisna, Jinjie Huang, Yuanjian Chen, I Gede Juliana Eka Putra

“…Additionally, the proposed model achieves an average performance improvement of 11.34% over previous models.…”
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