SFMattingNet: A Trimap-Free Deep Image Matting Approach for Smoke and Fire Scenes by Shihui Ma, Zhaoyang Xu, Hongping Yan

“…Taking into account the unique characteristics of smoke and fire, the network incorporates a non-rigid object feature extraction module and a spatial awareness module, achieving improved performance. …”
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SympCoughNet: symptom assisted audio-based COVID-19 detection by Yuhao Lin, Xiu Weng, Bolun Zheng, Weiwei Zhang, Zhanjun Bu, Yu Zhou

“…We trained and evaluated SympCoughNet on the UK COVID-19 Vocal Audio Dataset. Our model demonstrated significant performance improvements over traditional audio-only approaches, achieving 89.30% accuracy, 94.74% AUROC, and 91.62% PR on the test set. …”
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MACHINE LEARNING-BASED CLASSIFICATION OF HBV AND HCV-RELATED HEPATOCELLULAR CARCINOMA USING GENOMIC BIOMARKERS by Sami Akbulut, Zeynep Küçükakçalı, Cemil Çolak

“…Accuracy, balanced accuracy, sensitivity, specificity, the positive predictive value, the negative predictive value, and F1 score performance metrics were evaluated for a model performance. …”
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Brokel: Towards enabling multi-level cloud elasticity on publish/subscribe brokers by Vinicius Facco Rodrigues, Ivam Guilherme Wendt, Rodrigo da Rosa Righi, Cristiano André da Costa, Jorge Luis Victória Barbosa, Antonio Marcos Alberti

“…Aiming at bypassing the aforesaid problems, this article proposes Brokel, a multi-level elasticity model for Pub/Sub brokers. Users, things, and applications use Brokel as a centralized messaging service broker, but in the back-end the middleware provides better performance and cost (used resources × performance) on message delivery using virtual machine (VM) replication. …”
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AI-Based Forecasting in Renewable-Rich Microgrids: Challenges and Comparative Insights by Martins Osifeko, Josiah Lange Munda

“…Statistical testing via Friedman (<inline-formula> <tex-math notation="LaTeX">$\chi ^{2} = 10$ </tex-math></inline-formula>,858.39, p &#x003C;0.00001) and Nemenyi post-hoc tests confirmed significant differences in model performance. The study demonstrates that, with effective feature engineering, classical ML models can rival deep learning counterparts in forecasting accuracy. …”
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OA-MEN: a fusion deep learning approach for enhanced accuracy in knee osteoarthritis detection and classification using X-Ray imaging by Xiaolu Ren, Xiaolu Ren, Lingxuan Hou, Shan Liu, Peng Wu, Siming Liang, Haitian Fu, Chengquan Li, Ting Li, Yongjing Cheng

“…We propose a deep learning model named OA-MEN, which integrates a hybrid model combining ResNet and MobileNet feature extraction with multi-scale feature fusion. …”
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A precise spatiotemporal fusion crop classification framework based on parcels by Liegang Xia, Changge Chen, Jiancheng Luo, Xiaodong Hu, Xuanzhi Lu, Hongfeng Yu, Keyu Lu

“…Experimental validations using Pearson correlation coefficients and TWDTW similarity comparisons reveal that larger parcels have time series features that more strongly represent the features of typical samples. …”
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Multichannel Attention-Based TCN-GRU Network for Remaining Useful Life Prediction of Aero-Engines by Jiabao Zou, Ping Lin

“…This paper presents an innovative RUL prediction model designed specifically for aircraft engine applications. …”
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Transmission Tower Tilt State Recognition Based on Parameter Optimization of VMD-SVD and LSTM by Long ZHAO, Guanru WEN, Zhicheng LIU, Peng YUAN, Xinsheng DONG

“…Finally, the LSTM neural network is introduced for feature classification to form a fault diagnosis model. …”
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Smart Contract Security in Decentralized Finance: Enhancing Vulnerability Detection with Reinforcement Learning by Jose Juan de Leon, Cenchuan Zhang, Christos-Spyridon Koulouris, Francesca Medda, Rahul

“…Experimental results from extensive public datasets of smart contracts revealed that the PPO model performs better than DQN and demonstrates effectiveness in identifying unchecked-call vulnerability. …”
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Nitrous oxide prediction through machine learning and field-based experimentation: A novel strategy for data-driven insights by Muhammad Hassan, Khabat Khosravi, Travis J. Esau, Gurjit S. Randhawa, Aitazaz A. Farooque, Seyyed Ebrahim Hashemi Garmdareh, Yulin Hu, Nauman Yaqoob, Asad T. Jappa

“…The new models demonstrated good performance according to R2 values, while the SVR model ranged from unacceptable to good. …”
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Intelligent recognition and sustainable security protection strategies for abnormal behavior of power grid operation data based on multidimensional digital portrait and deep neural... by Qingqing Ren, Wanqing Kang, Xuehui Yang, Qingpeng Wang, Qiang Huang

“…The model performs well, especially for anomaly category D, achieving an accuracy of 0.965 and an F1 score of 0.827. …”
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A Fault Diagnosis Method for Dry Vacuum Pump Bearing Based on Finite Element Simulation With Deep Transfer Learning by Yanfeng Wei, Haibin Liu, Min Wei, Mingfei Li

“…Secondly, an attention mechanism is introduced in the feature extraction layer, combined with a deep transfer learning framework based on domain adversarial networks, to optimize feature extraction and align source and target domain features, thereby improving the accuracy of fault diagnosis and model generalization ability. …”
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Anti-RANKL Inhibits Thymic Function and Causes DRONJ in Mice by Yusuke Nakamura, Takashi Kikuiri, Takahiro Sugiyama, Ayako Maeda, Daisuke Izumiyama, Daigo Yahata, Yoshitaka Yoshimura, Tetsuo Shirakawa, Yoshimasa Kitagawa

“…Anti-mouse RANKL monoclonal antibody and melphalan were performed to create a mouse model of DRONJ-like lesions in female C57BL/6J mice. …”
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Container Truck High-Risk Events Prediction and Its Influencing Factors Analyses Based on Trajectory Data by Zhihao Zhu, Yuan Meng, Rongjun Cheng

“…Machine learning and related classification models are selected for conflict prediction. It is worth noting that the XGBoost model performs better than other models on the four datasets, with an accuracy of 0.86 and an AUC value of 0.933. …”
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Reacting Flow Characteristics of Wall-mounted Ramps in Strut-injection Scramjet Combustors under Varying Hydrogen Jet Pressures by A. Antony Athithan, S. Jeyakumar

“…A numerical investigation is performed using Reynolds Averaged Navier Stokes (RANS) equations in combination with the Shear Stress Transport (SST) k-ω turbulence model to understand flow mechanics at supersonic combustion. …”
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Integration of Structural Characteristics from GEDI Waveforms for Improved Forest Type Classification by Mary M. McClure, Satoshi Tsuyuki, Takuya Hiroshima

“…The labeled clusters were then further refined and used as training data to generate a wall-to-wall forest cover type map by classifying biannual images. The highest-performing model was a KNN model with 13 spectral and 3 terrain features achieving 81.7% accuracy. …”
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Use of machine learning for simplification of University Personality Inventory (UPI) by Weihua Guo, Jinsheng Hu, Qi Qiang, Xianke Chen

“…Additionally, we analyzed individual features and feature combinations. Results: Among the three models, the Random Forest model performed the best, with an accuracy of 89.4 %. …”
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Thermal study of the modular high-temperature gas-cooled reactor by Antonella Lombardi Costa, Mario Cerrogrande Ramos, Vitor Vasconcelos Araújo Silva, Claubia Pereira, Maria Auxiliadora Fortini Veloso

“…The core simulations have been performed to three power values: 350, 450 and 600 MWth. …”
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Social stability risk analysis caused by land acquisition and migration for water conservancy project construction by Feng Li, Xuewan Du, Xin Huang, Huimin Li, Xiaoxia Fei

“…Thus, this study intends to examine the dynamic development of the local government and resettlers by taking into account the effect of psychological judgments of benefits and losses as well as the dynamic features of each party. Taking into account the perceived gain function and concentrating on the viewpoints of the local government and resettlers, a dynamic game model is built utilizing the Prospect Theory and Mental Accounting theory. …”
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