A Mathematical Model of Ozone Distribution over Walnut Layer in a Vibrating Dryer by Grygorii Kaletnik, Oleg Tsurkan, Anatoly Spirin, Dmytro Prysiazhniuk, Andrii Didyk

“…The impact of the ozone-air mixture depends on distribution features and absorption by the entire layer in the drying chamber. …”
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The utility of combining deep learning with metabarcoding to model biodiversity dynamics at a national scale by Adrian Baggström, Robert Goodsell, Laura van Dijk, Ela Iwaszkiewicz-Eggebrecht, Andreia Miraldo, Ayco J.M. Tack, Tobias Andermann

“…Most of the tested models capture the general seasonal diversity trends, resulting in similar performance metrics. …”
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Machine learning-assisted quantitative prediction of thermal decomposition temperatures of energetic materials and their thermal stability analysis by Zhi-xiang Zhang, Yi-lin Cao, Chao Chen, Lin-yuan Wen, Yi-ding Ma, Bo-zhou Wang, Ying-zhe Liu

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A Multifunctional Tactile Sensory System for Robotic Intelligent Identification and Manipulation Perception by Yue Jiang, Lin Fan, Xilong Sun, Zehe Luo, Herong Wang, Rucong Lai, Jie Wang, Qiyang Gan, Ning Li, Jindong Tian

“…By Combining transfer learning models, which fuses multimodal tactile information to achieve high‐precision (up to 95%) recognition of the multi‐featured targets such as random hardness and texture information under random sampling conditions, including random grasp force and velocity. …”
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Comparison of 7 artificial intelligence models in predicting venous thromboembolism in COVID-19 patients by Indika Rajakaruna, Mohammad Hossein Amirhosseini, Mike Makris, Mike Laffan, Yang Li, Deepa J. Arachchillage

“…Additionally, it achieved the highest area under the curve score (0.983). Conclusion: The SVC model delivered the best overall performance outperforming similar studies that developed deep learning and machine-learning models for COVID-19.…”
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The 3D tooth model segmentation method based on GAC+PointMLP network by Jianjun Chen, Liyuan Zheng, Huilai Zou, Jiafa Mao, Weiguo Sheng

“…This enhanced attention mechanism allows the model to better capture subtle surface structures, facilitating the accurate extraction of valuable local features. …”
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A Review of Physics-Based, Data-Driven, and Hybrid Models for Tool Wear Monitoring by Haoyuan Zhang, Shanglei Jiang, Defeng Gao, Yuwen Sun, Wenxiang Bai

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Intelligent Food Safety: A Prediction Model Based on Attention Mechanism and Reinforcement Learning by Mingxia Wu, Wei Liu, Shengyang Zheng

“…Anchored by historical correlation data and food-specific attributes, the framework initiates its journey by deploying a dual-layer LSTM network to extract salient features. Subsequently, the model undergoes feature augmentation via attention mechanism and reinforcement learning methodologies, culminating in the realization of highly precise food safety predictions. …”
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Surrogate modeling for flow simulations using design variable-coded deep learning networks by Racheet Matai

“…The objective is to train the MLP using data from three bump heights and assess its predictive performance on a middle bump height. The results indicate that the MLP accurately predicts flow features for the middle bump height. …”
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Classification of Tropical Cyclone Tracks in the Northwest Pacific Based on the SD-K-Means Model by Nan Xu, Baisong Yang, Jia Ren

“…Based on these analyses, clustering indicators coupled with TC tracks and motion characteristics are identified. To evaluate the model’s performance, three clustering methods—standard K-Means, DTW (Dynamic Time Warping)-based K-Means, and DBSCAN (Density-Based Spatial Clustering of Applications with Noise)—are compared using the Calinski–Harabasz (CH) index and the Davies–Bouldin Index (DBI) as evaluation metrics. …”
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Enhancing Consumer Agent Modeling Through Openness-Based Consumer Traits and Inverse Clustering by Brahim Benaissa, Masakazu Kobayashi, Hiroshi Takenouchi

“…The study then introduces the inverse clustering approach, which prioritizes maximizing predictive model accuracy over within-cluster similarity. This method iteratively refines cluster assignments to optimize prediction performance, minimizing errors in forecasting consumer design preferences. …”
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Anti-Chaff Jamming Method of Radar Based on Real Dataset and Residual Attention Model by Shuolei Li, Bin Liu, Lin Zhou, Jingping Liu

“…Specifically, we introduce an attention mechanism that enables the network to focus on the most informative and stable hierarchical features of the high-resolution range profile (HRRP) data, significantly improving the model’s feature extraction capability and overall performance. …”
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Generating Human-Interpretable Rules from Convolutional Neural Networks by Russel Pears, Ashwini Kumar Sharma

“…For example, convolutional neural networks or CNNs perform image classification at a level equivalent to that of humans on many image datasets. …”
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A Hybrid Large Language Model for Context-Aware Document Ranking in Telecommunication Data by Abhay Bindle, Preeti Singla, Sachin Sharma, Abdukodir Khakimov, Reem Ibrahim Alkanhel, Ammar Muthanna

“…This paper presents hybrid document retrieval and ranking approach that integrates statistical, probabilistic, and neural network-based retrieval models to enhance information retrieval performance in telecommunication domain. …”
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Alignment-Enhanced Interactive Fusion Model for Complete and Incomplete Multimodal Hand Gesture Recognition by Shengcai Duan, Le Wu, Aiping Liu, Xun Chen

“…Hand gesture recognition (HGR) based on surface electromyogram (sEMG) and Accelerometer (ACC) signals is increasingly attractive where fusion strategies are crucial for performance and remain challenging. Currently, neural network-based fusion methods have gained superior performance. …”
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NeuroScale: evolutional scale-based protein language models enable prediction of neuropeptides by Hongqi Zhang, Shanghua Liu, Wei Su, Xueqin Xie, Junwen Yu, Fuying Dao, Mi Yang, Hao Lyu, Hao Lin

“…Additionally, we systematically analyzed the impact of protein sequence similarity thresholds and multi-scale sequence lengths on model performance, further validating NeuroScale’s robustness and generalizability. …”
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A Novel Method for 3D Lung Tumor Reconstruction Using Generative Models by Hamidreza Najafi, Kimia Savoji, Marzieh Mirzaeibonehkhater, Seyed Vahid Moravvej, Roohallah Alizadehsani, Siamak Pedrammehr

“…We introduce a second GAN model with a novel loss function that significantly improves tumor detection accuracy. …”
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Concept of natural genome reconstruction. Part 3. Analysis of changes in the amount of telomeric DNA in colony cells as a new amplified feature that arose during the processing of... by V. S. Ruzanova, S. G. Oshikhmina, G. S. Ritter, E. V. Dolgova, S. S. Kirikovich, E. V. Levites, Y. R. Efremov, T. V. Karamysheva, A. G. Bogomolov, M. I. Meschaninova, A. L. Mamaev, O. S. Taranov, S. V. Sidorov, S. D. Nikonov, O. Y. Leplina, A. A. Ostanin, E. R. Chernykh, N. A. Kolchanov, A. S. Proskurina, S. S. Bogachev

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End-to-End Deep-Learning-Based Surrogate Modeling for Supersonic Airfoil Shape Optimization by Diogo Pereira, Frederico Afonso, Fernando Lau

“…A novel end-to-end multitask Convolutional Neural Network is proposed to predict the aerodynamic coefficients of an airfoil shape, extracting global and local features directly from the geometry. The surrogate model is thoroughly examined and validated, including an analysis of model explainability. …”
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Early Prediction of Remaining Useful Life for Lithium-Ion Batteries with the State Space Model by Yuqi Liang, Shuai Zhao

“…The model has the ability to make forecasts using these few historical data. …”
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