Tracing the Evolution and Legacy of Professor A.P. Iofinov’s Scientific School by S. G. Mudarisov, R. R. Kamaletdinov

“…Their development and application contribute to improving the operational capabilities of agricultural machinery and bolstering the overall efficiency of the agricultural industry. …”
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An End-to-End Solution for Large-Scale Multi-UAV Mission Path Planning by Jiazhan Gao, Liruizhi Jia, Minchi Kuang, Heng Shi, Jihong Zhu

“…However, traditional heuristic algorithms are frequently trapped in local optima, require task-specific manual tuning, and exhibit limited generalization capabilities. …”
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Adaptive Multi-Scale Bayesian Framework for MFL Inspection of Steel Wire Ropes by Xiaoping Li, Yujie Sun, Xinyue Liu, Shaoxuan Zhang

“…Compared with state-of-the-art methods, including long short-term memory (LSTM), attention mechanisms, and isolation forests, our approach demonstrated significant improvements in precision, recall, and F1 score across various tolerance levels. …”
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Software and methodological support for additional professional courses: ideas, problems, monitoring by O. D. Prokhorenko, S. V. Morin, O. A. Kozyreva

“…By building prospects for theorizing and implementing ideas for improving the quality of modeling and using software and methodological support for further education courses, we can distinguish in the integrative representation of the direction and prospects of an individual’s achievements three types of solving professional and pedagogical problems theorized in the work (algorithmic, creative-stimulative and innovative-promising).…”
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Leveraging Deep Spatiotemporal Sequence Prediction Network with Self-Attention for Ground-Based Cloud Dynamics Forecasting by Sheng Li, Min Wang, Minghang Shi, Jiafeng Wang, Ran Cao

“…Compared with other spatiotemporal sequence prediction models, CloudPredRNN++ shows significant improvements in evaluation metrics, improving the accuracy of cloud dynamics forecasting and alleviating long-term dependency decay, thus confirming the effectiveness in ground-based cloud prediction tasks.…”
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Breaking Down Walls: A Literature Review on the Power of Artificial Intelligence in Enhancing Universal Language Connection by Sheida Jamalnia, Zahra Karimian

“…However, challenges such as translation inaccuracies, algorithmic biases, and ethical concerns necessitate continuous improvement and human oversight.Conclusion: AI is revolutionizing global communication by overcoming linguistic barriers and fostering inclusive interactions. …”
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GAB-YOLO: a lightweight deep learning model for real-time detection of abnormal behaviors in juvenile greater amberjack fish by Mingxin Liu, Mingxin Liu, Chun Zhang, Cong Lin, Cong Lin

“…Meanwhile, existing automated detection algorithms often struggle with a trade-off between detection accuracy and model size. …”
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Physics-informed deep learning model for line-integral diagnostics across fusion devices by Cong Wang, Weizhe Yang, Haiping Wang, Renjie Yang, Jing Li, Zhijun Wang, Yixiong Wei, Xianli Huang, Chenshu Hu, Zhaoyang Liu, Xinyao Yu, Changqing Zou, Zhifeng Zhao

“…Furthermore, the implementation of the Softplus activation function in the final two fully connected layers improves model performance. This enhancement results in a reduction in the ${E_1}$ by approximately $1.06 \times {10^{ - 2}}$ on synthetic datasets and about $0.11 \times {10^{ - 2}}$ on experimental datasets. …”
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Hybrid OFDM-Digital Filter Multiple Access PONs Utilizing Spectrally Overlapped Digital Orthogonal Filtering by Abdulai Sankoh, Wei Jin, Zhuqiang Zhong, Jiaxiang He, Yanhua Hong, Roger Philip Giddings, Iestyn Pierce, Maurice O'Sullivan, Jeffrey Lee, Tim Durrant, Jianming Tang

“…Alternately, for the same ONU count, >2.2-fold aggregate upstream signal transmission capacity increases and >0.7 dB upstream power budget improvements are achievable. The performance improvements vary by <18% for a transmission distance range as large as 50 km. …”
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The Emerging Role of Computed Tomography Coronary Angiography in the Left Main Stem Percutaneous Coronary Intervention by Asad Shabbir, Abdelrahman Attia, Nikkole Marie Weber, Mustafa Alhassan, Monika Radike, Conor M Lane, Apurva Bhavana Challa, Malgorzata Wamil

“…This review highlights the evolving role of CTCA in LMS PCI, underscoring its clinical utility in improving procedural precision and, subsequently, patient outcomes. …”
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Challenges and opportunities with ChatGPT in oral oncology: The journey ahead by Ribwar Arsalan Mohammed, Sirwan Khalid Ahmed

“…Collaboration among stakeholders is essential to overcome these challenges and fully harness the benefits of AI in improving outcomes for oral oncology patients.…”
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Multi‐function radar work mode recognition based on residual shrinkage reconstruction recurrent neural network by Lihong Wang, Kai Xie

“…These features are then processed through a residual shrinkage structure to reduce noise, which significantly improves the model's robustness in non‐ideal scenarios. …”
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Method of automatic coregistration of digital remote sensing images from different sources by A.N. Borisov, V.V. Myasnikov, V.V. Sergeev

“…To achieve a universal and robust solution in the latter stages, the best-known algorithms were compared: SIFT, SAR-SIFT, RIFT, and the trainable RoMa. …”
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Optimization of Enterprise Labor Resource Allocation Based on Quality Optimization Model by Gaoyang Liang, Long Xu, Liang Chen

“…Companies take project-based management as their organizational strategy, and project quality assurance plays a vital role in improving customer satisfaction and enhancing corporate image. …”
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Simulation modelling of single nucleotide genetic polymorphisms by Николай Николаевич Яцков, Владимир Владимирович Апанасович, Василий Викторович Гринев

“…The developed approach improves the accuracy of determining SNPs in DNA molecules and permits to investigate the reliability of specific experiments as well as to estimate the errors of determination of the parameters obtained in real experimental conditions. …”
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Point Cloud Deep Learning Methods for Particle Shower Reconstruction in the DHCAL by Borysova Maryna, Bressler Shikma, Gross Eilam, Kakati Nilotpal, Zavazieva Darina

“…Combined with Graph Attention Transformers (GATs) and DeepSets algorithms, this results in an improvement over existing baseline techniques for particle identification and energy resolution. …”
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Enhancing Engineering and Architectural Design Through Virtual Reality and Machine Learning Integration by Ali Shehadeh, Odey Alshboul

“…This research underscores the transformative impact of combining VR and ML on additive manufacturing (AM) workflows, significantly improving efficiency and reducing the iterative nature of traditional methods. …”
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Mental health evaluation during internet blackouts: A case study of Bangladesh Quota Movement by Rafi Mohammad Ariful Islam, Islam Tahidul

“…Machine learning models were employed to classify the stress levels, with the Decision Tree model achieving 55% accuracy, the Random Forest model improving to 67%, and XGBoost performing better than both with over 94% accuracy. …”
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Hyperspectral data of understory elements in boreal forests: In situ and laboratory measurementsMendeley DataMendeley Data by Audrey Mercier, Susanna Karlqvist, Aarne Hovi, Miina Rautiainen

“…These data support the analysis of vegetation characteristics, training of classification algorithms and improvement of forest radiative transfer models, and could be used to evaluate the potential of hyperspectral data to discriminate the understory elements of boreal forest.…”
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The Implementation of BCTrustAI.SL into the Automated Practices of Digital Labour Platforms to Ensure Fairness, Transparency and Accountability by Şaban İbrahim Göksal, Kristi Joamets

“… Since digital labour platforms may infringe upon the rights of platform workers through automated decision-making and monitoring practices, the European Parliament and of the Council has adopted the Directive (EU) 2024/2831 on improving working conditions in platform work (Directive 2024/2831). …”
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