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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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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Analysis of a Four-Legged Robot Kinematics during Rotational Movements of Its Body by M. J. Fernando, G. R. Saypulaev, M. R. Saypulaev

“…To provide high precision in controlling their movement, it is required to develop mathematical models and algorithms for planning the robot movement along various trajectories. …”
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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

“…Several machine learning algorithms, including Random Forest, Gradient Boosting, and Stacking ensembles, as well as deep learning models such as TabNet, were evaluated for crop prediction. …”
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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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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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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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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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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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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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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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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

“…Firstly， a unit combination model that incorporates AC power flow constraints is constructed， and a two-stage solution strategy based on second-order cone relaxation is adopted to perform 8，760-hour time-sequenced simulations in the multi-period optimal power flow model. …”
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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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An Integrated Electricity–Gas–Heat Energy System Based on the Synergy of Long- and Short-Term Energy Storage by Min Zhang, Jinhao Wang, Huiqiang Zhi, Jun Zhao, Xiao Chang, Shifeng Zhang, Xiangyu Guo, Tengxin Wang

“…Therefore, this paper proposes an integrated energy system planning and optimization method based on hybrid energy storage. Firstly, an adaptive noise integration empirical modal decomposition method based on the optimization improvement of the grey wolf algorithm is designed for the power allocation strategy of the hybrid energy storage system; secondly, for the electric–gas system, an energy management strategy for the hybrid electric–gas energy storage system, taking into account the operating characteristics of the alkaline electrolyzer, is proposed in order to strengthen the complementary mechanism between electric energy storage and gas energy storage. …”
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Development of a postoperative recurrence prediction model for stage Ⅰ non-small cell lung cancer patients using multimodal data based on machine learning by ZHANG Di, WU Yi, XU Yu

“…A combined model was further constructed by integrating both feature sets, and model performance was compared to identify the optimal predictive model.Results‍　‍This study screened the features from non-contrast CT images and ultimately selected 7 radiomic features for constructing radiomic model. …”
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