Learning atomic forces from uncertainty-calibrated adversarial attacks by Henrique Musseli Cezar, Tilmann Bodenstein, Henrik Andersen Sveinsson, Morten Ledum, Simen Reine, Sigbjørn Løland Bore

“…Abstract Adversarial approaches, which intentionally challenge machine learning models by generating difficult examples, are increasingly being adopted to improve machine learning interatomic potentials (MLIPs). …”
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Discriminative graph regularized representation learning for recognition. by Jinshan Qi, Rui Xu

“…We provide detailed theoretical derivations of the resulting optimization problems of DGRL and KDGRL. Meanwhile, we design two simple and tractable parameter estimation procedures based on cross-validation technique to speed up the model selection processes for DGRL and KDGRL. …”
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Calculation Methods for the Permeability Coefficient of Concrete Face Rockfill Dam with Cracks by Zhongwen Shi, Zhongru Wu, Chongshi Gu, Bo Chen, Hailong Zhang, Wenzhong Yin, Bangbin Wu

“…Moreover, an inversion algorithm based on particle swarm optimization and support vector machine was proposed and applied. …”
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Class Imbalance in the Automatic Interpretation of Remote Sensing Images: A Review by Pengdi Chen, Yuanrui Ren, Baoan Zhang, Yuan Zhao

“…The solution to the proposed problem involves three aspects: model innovation and optimization, loss function improvement, and data augmentation. …”
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Enhanced Detection of Intrusion Detection System in Cloud Networks Using Time-Aware and Deep Learning Techniques by Nima Terawi, Huthaifa I. Ashqar, Omar Darwish, Anas Alsobeh, Plamen Zahariev, Yahya Tashtoush

“…In contrast, Deep Neural Network (DNN) models showed significant improvements with optimization, with DNN combined with GS (DNN-GS) reaching 89% accuracy. …”
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Experiment on physical and mechanical properties of tomato seedling pot for automatic vegetable transplanter by Liang Xifeng, Cai Yangyang, Wang Yongwei

“…At the same time, to analyze the creep characteristics of seedling pot, creep test has been done using a universal testing machine Instron 5543 and P100 flat probe and combined with the describe of Burgers model. …”
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Cloud based real-time multivariate multi-step prediction of systolic blood pressure and heart rate using temporal convolutional network and Apache Spark by Hager Saleh, Nora El-Rashidy, Sherif Mostafa, Abdulaziz AlMohimeed, Shaker El-Sappagh, Zainab H. Ali

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Criteria-calibration approaches to deep learning-based cervical cancer radiation treatment auto-planning by Yongguang Liang, Jingru Yang, Shuoyang Wei, Yanfei Liu, Shumeng He, Kang Zhang, Jie Qiu, Bo Yang

“…Abstract Background Knowledge-Based Planning (KBP) pipelines, which integrate machine learning-based models to predict dose distribution, have gained popularity in clinical radiation therapy. …”
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Injecting structure-aware insights for the learning of RNA sequence representations to identify m6A modification sites by Yue Yu, Shuang Xiang, Minghao Wu

“…Finally, a support vector machine is utilized for classifying these representations. …”
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Comparative Analysis of Time Series Prediction Algorithms on Multiple Network Function Data of NWDAF by Dasheng Chen, Qi Song, Yinbin Zhang, Ling Li, Zhiming Yang

“…Following data collection, a total of six models were employed for network element performance prediction, encompassing both machine learning and deep learning approaches. …”
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A Framework for Integrating Robotic Process Automation with Artificial Intelligence Applied to Industry 5.0 by Leonel Patrício, Leonilde Varela, Zilda Silveira, Carlos Felgueiras, Filipe Pereira

“…Incorporating ethical governance and continuous upskilling, the model ensures technological advancement aligns with societal and environmental values. …”
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FLPneXAINet: Federated deep learning and explainable AI for improved pneumonia prediction utilizing GAN-augmented chest X-ray data. by Shuvo Biswas, Rafid Mostafiz, Mohammad Shorif Uddin, Muhammad Shahin Uddin

“…These optimized features were then inputted into machine learning (ML) models, including K-nearest neighbor (KNN), naive bayes (NB), support vector machine (SVM), and RF, for pneumonia prediction. …”
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Simulation and Evaluation of the Performance of Pneumatic Residual Film Recycler Comb Teeth by Sen Jiang, Baiyu Chen, Haojie Jiang, Pengfei Guo, Xufeng Wang, Can Hu, Wensong Guo

“…This study can provide a reference for the structural design and optimization of working parameters of future deep tillage machines.…”
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Remote sensing of terrestrial gross primary productivity: a review of advances in theoretical foundation, key parameters and methods by Wenquan Zhu, Zhiying Xie, Cenliang Zhao, Zhoutao Zheng, Kun Qiao, Dailiang Peng, Yongshuo H. Fu

“…Regarding estimation methods, although the four main categories of RS-based GPP estimation models (statistical model, light use efficiency model, RS-based process model and machine learning-based model) have made significant progress in parameter optimization, the estimation accuracy and mechanism innovation remain less than satisfactory. …”
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Distributed Photovoltaic Power Energy Generation Prediction Based on Improved Multi-objective Particle Algorithm by Yuanzheng Xiao, Huawei Hong, Feifei Chen, Xiaorui Qian, Ming Xu, Hanbin Ma

“…A hybrid LSTM-PSO model was created, where the LSTM network served as the core prediction model, and the improved MO-PSO algorithm optimized its hyperparameters, enhancing generalization and avoiding overfitting. …”
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Adaptive Real-Time Transmission in Large-Scale Satellite Networks Through Software-Defined-Networking-Based Domain Clustering and Random Linear Network Coding by Shangpeng Wang, Chenyuan Zhang, Yuchen Wu, Limin Liu, Jun Long

“…Existing research primarily emphasizes traffic prediction and scheduling using spatiotemporal models and machine learning. However, these approaches often depend on extensive historical data for training, making real-time adaptation to rapidly changing network topologies and traffic patterns challenging in dynamic satellite environments. …”
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Cost Index Predictions for Construction Engineering Based on LSTM Neural Networks by Jiacheng Dong, Yuan Chen, Gang Guan

“…A prediction framework based on the LSTM model, which was trained by using these collected data, was established for the purpose of cost index predictions and test. …”
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Advanced Deep Learning Methods to Generate and Discriminate Fake Images of Egyptian Monuments by Daniyah Alaswad, Mohamed A. Zohdy

“…Our findings indicate that specific model optimization strategies produce superior outcomes by creating better-quality and historically correct representations of diverse Egyptian monuments. …”
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Research progress and prospects of intelligent mine ventilation by LIU Xiangying

“…Second, the high uncertainty of the mine environment and the low level of automation in human-machine collaborative decision-making limit the adaptive optimization capabilities of the ventilation network. …”
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Selective Feature Sets Based Fake News Detection for COVID-19 to Manage Infodemic by Manideep Narra, Muhammad Umer, Saima Sadiq, Ala' Abdulmajid Eshmawi, Hanen Karamti, Abdullah Mohamed, Imran Ashraf

“…Considering the problematic consequences of fake news, efforts have been made for the timely detection of fake news using machine learning and deep learning models. Such works focus on model optimization and feature engineering and the extraction part is under-explored area. …”
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