Interactive online learning method for students based on artificial intelligence by Cizhang Li, Wenfen Yin

“…This study proposes a novel approach that integrates the Dwarf Mongoose Optimization (DMO) algorithm with a Gated Recurrent Unit (GRU) neural network to develop an AI-powered interactive online learning model. …”
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Control-Oriented Real-Time Trajectory Planning for Heterogeneous UAV Formations by Weichen Qian, Wenjun Yi, Shusen Yuan, Jun Guan

“…Inspired by Model Predictive Control (MPC), in the trajectory planning stage, the method generates multi-step trajectory points using an improved artificial potential field (APF) method, estimates the actual formation trajectory using the prediction network, and optimizes the trajectory through a multi-objective particle swarm optimization (MOPSO) algorithm after evaluating the planning costs. …”
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Lightweight blasthole image detection and positioning method by Shan PAN, Ting YU, Zhongwen YUE, Zijian TIAN, Qingyu JIN

“…To tackle the issues of large parameter size and low frames per second (FPS) in the blasthole image detection and localization algorithm network model, a lightweight Sc_C2f module is proposed to optimize the network structure. …”
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Development of Explainable Machine Learning Models to Identify Patients at Risk for 1-Year Mortality and New Distant Metastases Postendoprosthetic Reconstruction for Lower Extremit... by Jiawen Deng, BHSc, Myron Moskalyk, BHSc, MSc, Madhur Nayan, MD, PhD, Ahmed Aoude, MEng, MD, FRCSC, Michelle Ghert, MD, FRCSC, Sahir Bhatnagar, PhD, Anthony Bozzo, MSc, MD, FRCSC

“…Including percent necrosis did not significantly improve model performance. The top predictors identified were patient age, largest tumor dimension, and tumor stage. …”
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Classification of Vaginal Cleanliness Grades through Surface‐Enhanced Raman Spectral Analysis via The Deep‐Learning Variational Autoencoder–Long Short‐Term Memory Model by Jia‐Wei Tang, Xin‐Ru Wen, Hui‐Min Chen, Jie Chen, Kun‐Hui Hong, Quan Yuan, Muhammad Usman, Liang Wang

“…Finally, the reliability of the optimal model is tested using blind test data (N = 10/group for each cleanliness level). …”
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An IoT-enabled AI system for real-time crop prediction using soil and weather data in precision agriculture by MD Shaifullah Sharafat, Nilavro Das Kabya, Rahimul Islam Emu, Mehrab Uddin Ahmed, Jakaria Chowdhury Onik, Mohammad Aminul Islam, Riasat Khan

“…Context: Precision agriculture leverages advanced technologies such as the Internet of Things (IoT) and artificial intelligence (AI) to enhance crop productivity by providing data-driven insights. In Bangladesh, optimizing crop recommendations using real-time soil and environmental data is crucial for improving agricultural decision-making. …”
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Machine-learning models for differentiating benign and malignant breast masses: Integrating automated breast volume scanning intra-tumoral, peri-tumoral features, and clinical info... by Meixue Dai, Yueqiong Yan, Zhong Li, Jidong Xiao

“…SHAP analysis revealed the contribution of key features, improving model interpretability. Conclusion This study demonstrates the value of integrating radiomics and clinical features for breast mass diagnosis, with optimized peritumoral regions enhancing model performance. …”
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New method for landslide susceptibility evaluation in alpine valley regions that considers the suitability of InSAR monitoring and introduces deformation rate grading by Dingyi Zhou, Zhifang Zhao, Wenfei Xi, Xin Zhao, Jiangqin Chao

“…The landslide susceptibility model is developed utilizing the Particle Swarm Optimization-Back Propagation (PSO-BP) algorithm. …”
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An Analysis of Intelligent Turkish Text Classification Models for Routing Calls in Call Centers: A Case Study on the Republic of Turkiye Ministry of Trade Call Center by Muammer Özdemir, Yasin Ortakcı

“…The results indicate that a combination of the Random Forest classifier and Word2Vec text vectorization method is the optimal model that can manage to route calls in real-time.…”
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Developing a Machine Learning Model for Predicting 30-Day Major Adverse Cardiac and Cerebrovascular Events in Patients Undergoing Noncardiac Surgery: Retrospective Study by Ju-Seung Kwun, Houng-Beom Ahn, Si-Hyuck Kang, Sooyoung Yoo, Seok Kim, Wongeun Song, Junho Hyun, Ji Seon Oh, Gakyoung Baek, Jung-Won Suh

“…ObjectiveThis study aimed to use the Observational Medical Outcomes Partnership Common Data Model to develop a predictive model by applying machine learning algorithms that can effectively predict major adverse cardiac and cerebrovascular events (MACCE) in patients undergoing noncardiac surgery. …”
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Fuzzy Robust Modification Design of EMU Transmission Gear by Ziqiang Sheng, Yuedong Wang, Xiaoning Bai, Shenxuan Wang

“…On this basis， the fuzzy theory is introduced， the mathematical model of gear modification robust optimization is established based on improved tolerance model， the NSGA-III algorithm is used to find the optimal solution， and the comparison with other modification schemes is completed. …”
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Bio-Inspired Compliant Joints and Economic MPC Co-Design for Energy-Efficient, High-Speed Locomotion in Snake-like Robots by Shuai Zhou, Gengbiao Chen, Mingyu Gong, Jing Liu, Peng Xu, Binshuo Liu, Nian Yin

“…Critically, this work adopts a synergistic design philosophy where mechanical components and control parameters are co-optimized through shared dynamic modeling. The proposed predictive control strategy optimizes locomotion speed while minimizing energy consumption. …”
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Short-term Wind Power Forecasting Based on BWO‒VMD and TCN‒BiGRU by LU Jing, ZHANG Yanru, WANG Rui

“…Given the instability and high volatility of wind power generation, this study proposes a short-term wind power prediction method based on BWO‒VMD and TCN‒BiGRU to improve the accuracy of wind power prediction and better support the energy transition under the “dual carbon” strategy.MethodsA short-term wind power generation prediction model based on the beluga whale optimization (BWO) algorithm, variational mode de-composition (VMD), temporal convolutional network (TCN), and bidirectional gated recurrent unit (BiGRU) was carefully proposed to improve the prediction accuracy of wind power generation, particularly considering its inherent instability and high volatility. …”
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Electric Vehicle Cluster and Scheduling Strategy Based on Dynamic Game by LI Shuai, DING Xiying, JIANG Hongfa

“…The upper layer takes the peak shaving demand and peak shaving cost of distribution system operator (DSO) as the optimization objectives, and uses an improved multi-objective particle swarm optimization algorithm to obtain the game strategy set of DSO. …”
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The vessel movement optimisation with excessive control by С. Зинченко, А. Бень, П. Носов, И. Попович, В. Матейчук, О. Грошева

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Revolutionize 3D-Chip Design With Open3DFlow, an Open-Source AI-Enhanced Solution by Yifei Zhu, Zhenxuan Luan, Dawei Feng, Weiwei Chen, Lei Ren, Zhangxi Tan

“…<italic>Open3DFlow</italic>&#x2019;s open-source nature allows seamless integration of custom AI optimization algorithms. As a showcase, we leverage large language models (LLMs) to help the bonding pad placement. …”
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Recent Results on the Use of Artificial Intelligence Techniques Applied to Wireless Power Transfer Systems by Federico Amadei, Michele Quercio, Francesco Riganti Fulginei

“…The article discusses various approaches, including supervised learning, regression models, and Q-learning algorithms, highlighting their ability to reduce design time, improving system efficiency, and mitigate risks associated with misalignment and object interference. …”
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A Global Coverage Path Planning Method for Multi-UAV Maritime Surveillance in Complex Obstacle Environments by Yiyuan Li, Weiyi Chen, Bing Fu, Zhonghong Wu, Lingjun Hao

“…Secondly, a method for calculating obstacle-avoidance path costs based on the Voronoi diagram is proposed, laying the foundation for obtaining the optimal access order. Thirdly, an improved discrete grey wolf optimizer (IDGWO) algorithm integrated with variable neighborhood search (VNS) operations is proposed to perform task assignment for multiple UAVs and achieve workload balancing. …”
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Pig Aggression Tracking and Analysis Application Based on A RPMeMOTR Method by Shuqin Tu, Haoxuan Ou, Aqing Yang, Yun Liang, Jiaying Du, Yuefei Cao, Ruilin He, Fang Yuan

“…To address the above challenges, this study proposes an RPMeMOTR approach by combining the RKNet model and the P-ids algorithm based on MeMOTR for pig aggression tracking and analysis. …”
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A typical scenario generation method for renewable energy power systems based on time-sequenced operational simulations by PENG Zhuyi, SONG Shan, XU Sixuan, GU Kanghui, GE Yi, WANG Quanquan, SUN Wentao

“…Secondly， based on data characteristics such as renewable energy output levels， line congestion conditions， and unit startup-shutoff from the time-sequenced simulation results， an improved K-means algorithm is employed to extract typical scenarios. …”
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