Lightweight Fire Detection in Tunnel Environments by Shakhnoza Muksimova, Sabina Umirzakova, Dilnoza Abduxalikovna Babaraximova, Young Im Cho

“…It achieved an accuracy of 92%, a precision of 89%, a recall of 90%, and an F1 score of 89.5%, outperforming state-of-the-art (SOTA) models in all key metrics. Furthermore, the model demonstrated resilience under varied environmental conditions, including high smoke density and sensor failures, maintaining reliable performance. …”
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An Adaptive Intrusion Detection System for Evolving IoT Threats: An Autoencoder-FNN Fusion by J. Jasmine Shirley, M. Priya

“…Rigorous evaluations demonstrate the model’s robust performance, achieving a remarkable accuracy of 99.55% in binary classification and 90.91% in multiclass classification. …”
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Object Re-Identification Based on Federated Incremental Subgradient Proximal Optimization by Li Kang, Chuanghong Zhao, Jianjun Huang

“…However, the real statistical heterogeneity in federated object re-identification leads to domain shift issues, resulting in decreased performance and generalization ability of the ReID model. …”
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Feasibility of EfficientDet-D3 for Accurate and Efficient Void Detection in GPR Images by Sung-Pil Shin, Sang-Yum Lee, Tri Ho Minh Le

“…The model combines advanced feature extraction and compound scaling to balance accuracy and computational efficiency, making it suitable for real-time applications. …”
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PREOPERATIVE PREDICTION OF WALL INVASION DEPTH OF PRIMARY TUMOR (PT) IN GASTRIC CANCER PATIENTS by M.YU. REUTOVICH, O.V. KRASKO, A.I. PATSEIKA, H.S. HUSSEIN

“…The clinical validation of the model was performed by evaluating the long-term treatment outcomes. …”
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Pharmacist-led surgical medicines prescription optimization and prediction service improves patient outcomes - a machine learning based study by Xianlin Li, Xianlin Li, Xiunan Yue, Lan Zhang, Xiaojun Zheng, Nan Shang

“…The Random Forest (RF) model performed the best (AUC = 0.893) and retained high accuracy with 12 features (AUC = 0.886). …”
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Experimental and Numerical Simulation Researches of Critical Heat Flux in Tube under Motion Condition by XIA Binzhuo, XIA Fanting, ZHANG Kui, CHEN Ronghua, TIAN Wenxi, QIU Suizheng

“…This model includes drag force, lift force, virtual mass force, and turbulent dissipation force. …”

Machine Learning-Based Predictive Maintenance for Photovoltaic Systems by Ali Al-Humairi, Enmar Khalis, Zuhair A. Al-Hemyari, Peter Jung

“…Dimensionality reduction through the principal component analysis and correlation-based feature selection enhanced the model performance as well as the interpretability. …”
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SAG-YOLO: A Lightweight Real-Time One-Day-Old Chick Gender Detection Method by Yulong Chang, Rongqian Sun, Zheng Yang, Shijun Li, Qiaohua Wang

“…In video stream detection, the model achieves 100% accuracy for female chicks and 96.25% accuracy for male chicks, demonstrating strong performance under motion blur and feature fuzziness. …”
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Machine learning using genotype and gene-expression data identifies alterations of genes involved in infection susceptibility, antigen presentation and cytokine signalling as key c... by Nicholas Pudjihartono, Daniel Ho, Justin Martin O’Sullivan

“…These SNP sets were then used as features in a Lasso-regularised logistic regression model to predict JIA disease status. …”
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Improving seasonal precipitation forecasts in the Western United States through statistical downscaling by B Vernon, W Zhang, Y Chikamoto

“…Here, analog statistical downscaling is demonstrated as an effective approach to enhance the spatial resolution of operational seasonal forecasts provided by the North American Multi-Model Ensemble. Downscaling was performed by building an analog ‘library’, in which corresponding model forecasts and observed values during the training period were stored. …”
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Environmental adaptations in metagenomes revealed by deep learning by Johanna C. Winder, Simon Poulton, Taoyang Wu, Thomas Mock, Cock van Oosterhout

“…We identified environment-specific features that appear to drive classification. Our best-performing ANN was able to classify between 75.9 and 97.8% of sequences correctly. …”
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A novel clinical risk scoring system for neurodevelopmental outcomes among survivors of neonatal hypoxic-ischemic encephalopathy (HIE) by Theresa Estiphan, Julie Sturza, Renée A. Shellhaas, Martha D. Carlson

“…We examined bivariate associations between the neonatal characteristics and Bayley-III scores. We then performed stepwise logistic regression. To create the risk scores, a participant was given one point for each of the factors included in the final model. …”
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Intelligent Detection of Tomato Ripening in Natural Environments Using YOLO-DGS by Mengyuan Zhao, Beibei Cui, Yuehao Yu, Xiaoyi Zhang, Jiaxin Xu, Fengzheng Shi, Liang Zhao

“…This module performs convolution in stages on the feature map, generating more feature maps with fewer parameters and computational resources, thereby improving the model’s feature extraction capability while reducing parameter count and computational cost. …”
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Human Brain-Inspired Network Using Transformer and Feedback Processing for Cell Image Segmentation by Hinako Mitsuoka, Kazuhiro Hotta

“…Feeding back feature maps with detailed information near the output of the model obtained once inference is performed to the lower layers improves the accuracy of segmentation, especially in areas with complex textures and small objects, by enhancing the ability to extract features near boundaries and details. …”
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PhyIndBC: Development of a machine learning tool for screening of potential breast cancer inhibitors from phytochemicalsGitHub by Agneesh Pratim Das, Subhash M. Agarwal

“…Multiple ML techniques viz., k-nearest neighbor (KNN), random forest (RF), support vector machine (SVM), and extreme gradient boosting (XGB) were combined with various molecular fingerprints (MACCS and Morgan2) to develop multiple predictive models. Among these models, the RF algorithm coupled with the MACCS fingerprint emerged as the best performing model. …”
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Construction of knowledge graph for gas polyethylene pipelines based on ALBERT-BiGRU-CRF by Zhilong Yu, Juan Zhou, Qiang Wang, Haiting Zhou, Yun Song, Chenjia Zong

“…Next, the improved ALBERT, incorporating features from various levels, generates high-quality word vectors, which serve as input feature vectors for the bidirectional gated recurrent unit (BiGRU) model to improve the model’s semantic comprehension ability in processing pipeline O&M data. …”
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iCOR: End-to-End Electrocardiography Morphology Classification Combining Multi-Layer Filter and BiLSTM by Siti Nurmaini, Wisnu Jatmiko, Satria Mandala, Bambang Tutuko, Erwin Erwin, Alexander Edo Tondas, Annisa Darmawahyuni, Firdaus Firdaus, Muhammad Naufal Rachmatullah, Ade Iriani Sapitri, Anggun Islami, Akhiar Wista Arum, Muhammad Ikhwan Perwira

“…However, previous studies indicate that models developed for specific datasets and environments perform poorly when used with varying ECG signal morphology characteristics. …”
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Mobile-YOLO: A Lightweight Object Detection Algorithm for Four Categories of Aquatic Organisms by Hanyu Jiang, Jing Zhao, Fuyu Ma, Yan Yang, Ruiwen Yi

“…Our model first utilizes the Mobile-Nano backbone network we proposed, which enhances feature perception while maintaining a lightweight design. …”
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Acoustic Inspired Brain-to-Sentence Decoder for Logosyllabic Language by Chen Feng, Lu Cao, Di Wu, En Zhang, Ting Wang, Xiaowei Jiang, Jinbo Chen, Hui Wu, Siyu Lin, Qiming Hou, Junming Zhu, Jie Yang, Mohamad Sawan, Yue Zhang

“…We also verified that incorporating acoustic-related features into the design of prediction models substantially enhances the accuracy of initials, tones, and finals. …”
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