Applying Internet information technology combined with deep learning to tourism collaborative recommendation system. by Meng Wang

“…Also, factorization machine technology is used to learn the interaction between the extracted features to improve the prediction model. The results show that the proposed model can maintain an excellent precision of 64.2% when generating personalized recommendation lists for users. …”
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Latest Trend and Challenges in Machine Learning– and Deep Learning–Based Computational Techniques in Poultry Health and Disease Management: A Review by Shwetha V., Maddodi B. S., Vijaya Laxmi, Abhinav Kumar, Sakshi Shrivastava

“…This study reviews the literature using ML and DL techniques in prediction, classification, and disease detection in various metrics, namely, poultry health and disease management. …”
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Functional control of the technical condition method for aircraft control system sensors under complete parametric uncertainty by J. V. Bondarenko, E. Yu. Zybin

“…Fast tuning, fast response and selective sensitivity of the developed algorithms are noted.…”
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Measuring the Dimension Accuracy of Products Created by 3D Printing Technology with the Designed Measuring System by Martin Pollák, Dominik Sabol, Karol Goryl

“…Comprehensive analysis of measurements in combination with advanced algorithms can provide more accurate dimensional characteristics and the prediction of defects. …”
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Integrated multiomics analysis identifies potential biomarkers and therapeutic targets for autophagy associated AKI to CKD transition by Yaojun Wang, Qiang Li

“…Single-cell analysis showed that ATP6V1C1 and COPA were specifically expressed in AKI and CKD, which may be related to renal fibrosis. In addition, drug prediction and molecular docking analysis proposed SZ(+)-(S)-202-791 and PDE4 inhibitor 16 as potential therapeutic agents. …”
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Hybrid LSTM–Attention and CNN Model for Enhanced Speech Emotion Recognition by Fazliddin Makhmudov, Alpamis Kutlimuratov, Young-Im Cho

“…Our approach employs both CNN and LSTM networks, complemented by an attention model, for enhanced emotion prediction. Specifically, the LSTM model addresses the challenges of long-term dependencies, enabling the system to factor in historical emotional experiences alongside current ones. …”
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Application of artificial intelligence in the diagnosis and treatment of lacrimal disorders: challenges and opportunities by PENG Xintong, LI Guangyu

“…However, several challenges persist, such as the complexity of multimodal data integration, limitations in model generalization capabilities, and the need for real-time prediction and dynamic adjustments, all of which necessitate continuous technological innovations, algorithm optimization, and interdisciplinary collaborations. …”
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Comprehensive prevention and control strategy for top coal fire based on the intelligent mine comprehensive management and control platform by Miao ZHAO

“…The existing fire perception and prevention technology and equipment are evaluated, and their problems are pointed out, such as incomplete perception coverage and immature early warning model algorithms. Based on these issues, a comprehensive fire prevention and control center is constructed, and a comprehensive prevention and control strategy is proposed, including fire prediction and early warning, coal spontaneous combustion prevention and treatment strategies, as well as associated disaster prevention and control, and emergency response and rescue strategy previews. …”
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Psychological Stress Identification and Evaluation Method Based on Mobile Human-Computer Interaction Equipment by Na Zhang

“…Through the BP of mobile human-computer interaction equipment, hereditary, genetic algorithms, and Hi-PLS regression method in the artificial neural network, the psychological pressure of college students is identified, evaluated, and predicted from three dimensions such as learning, life, and personal events. …”
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AI-aided short-term decision making of rockburst damage scale in underground engineering by Chukwuemeka Daniel, Shouye Cheng, Xin Yin, Zakaria Mohamed Barrie, Yucong Pan, Quansheng Liu, Feng Gao, Minsheng Li, Xing Huang

“…This study investigates the effectiveness of ensemble machine learning models optimized through Bayesian optimization (BO) in predicting rockburst damage scales. Nine classifier algorithms, including random forest (RF), were evaluated using a dataset of 254 samples. …”
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MFBCE: A Multi-Focal Bionic Compound Eye for Distance Measurement by Qiwei Liu, Xia Wang, Jiaan Xue, Shuaijun Lv, Ranfeng Wei

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Explainable quality assessment of effective aligned skeletal representations for martial arts movements by multi-machine learning decisions by Yiqun Pang, Kaiqi Zhang, Fengmei Li

“…Abstract How to utilize modern technological means to provide both accurate scoring and objective feedback for martial arts movements has become an issue that needs to be addressed in the field of physical education. This study proposes an intelligent scoring method based on machine learning. …”
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Single Vector Hydrophone DOA Estimation: Leveraging Deep Learning with CNN-CBAM by Fanyu ZENG, Yaning HAN, Hongyuan YANG, Dapeng YANG, Fan ZHENG

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Boosting brain-computer interface performance through cognitive training: A brain-centric approach by Ziyuan Zhang, Ziyu Wang, Kaitai Guo, Yang Zheng, Minghao Dong, Jimin Liang

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Swarm intelligence for energy-efficient heating, ventilation, and air conditioning (HVAC) systems: A case study in smart buildings by Vinoth Kanna I, Raja Subramani, Maher Ali Rusho, Shubham Sharma, Ramachandran T, Abinash Mahapatro, Deepak Gupta, Jasmina Lozanovic

“…Thermal comfort analysis through Predicted Mean Vote (PMV) and Predicted Percentage of Dissatisfied (PPD) metrics showed better indoor conditions, with the hybrid model keeping room temperatures within ±0.8 °C of the setpoint and bringing the PPD index down to 8.5 %. …”
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Doodle.AI: Redefining creative play with human-AI competition in real-time doodle recognition by Ishan Panta, Biplov Paneru, Bishwash Paneru, Bipul Thapa

“…The participants draw random words as they compete with an artificial intelligence model, which predicts drawings in real time. The AI component not only adds challenge and thrill but also demonstrates the capability of machine learning in interactive gaming. …”
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Energy-Efficient and Fault-Tolerant Control of a Six-Axis Robot Based on AI Models by Patryk Nowak, Zoran Pandilov

“…The study demonstrates that the application of the algorithm leads to a reduction in robot energy consumption. …”
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Internal Model Control for a Light-Weight Active Noise-Reducing Casing by Krzysztof MAZUR, Marek PAWEŁCZYK

“…Therefore, it can be adequately predicted and the Internal Model Control structure can be used to benefit from algorithms well developed for feedforward systems. …”
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Multi-Sensor Fusion and Machine Learning for Forest Age Mapping in Southeastern Tibet by Zelong Chi, Kaipeng Xu

“…Significant differences in reflectance among different age groups are observed in the 500–1000 nm spectral band, with 100 m resolution PROBA-V data being the most suitable for age prediction. The Random Forest model achieved an overall accuracy of 62% on the independent validation set, with canopy height, L-band radar data, and temperature seasonality being the most important predictors. …”
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Research on the Inversion Method of Dust Content on Mining Area Plant Canopies Based on UAV-Borne VNIR Hyperspectral Data by Yibo Zhao, Shaogang Lei, Xiaotong Han, Yufan Xu, Jianzhu Li, Yating Duan, Shengya Sun

“…Both feature extraction and model selection influence the inversion accuracy, with the LT-CARS and RF combination offering the best predictive performance. Canopy dust content decreases with increasing distance from the dust source. …”
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