Occlusion-Robust Multi-Target Tracking and Segmentation Framework with Mask Enhancement by Hao Sheng, Defa Zhang, Dazhi Yang, Da Yang, Xi Liu, Wei Ke

“…The framework merges the mask-based methods above into a mask-integrated multi-hypothesis tracking algorithm, achieves superior adaptability in occluded scenarios, and enhances the robustness of MOTS tasks. …”
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A hybrid attack detection strategy for cybersecurity using moth elephant herding optimisation‐based stacked autoencoder by Abdullah Shawan Alotaibi

“…Finally, the attack detection is performed using the stacked autoencoder classifier, which is trained using the proposed MEHO algorithm. The MEHO algorithm is developed by integrating the Moth search (MS) algorithm and the Elephant Herding Optimisation (EHO). …”
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Optimization of Fused Deposition Modeling Parameters for Mechanical Properties of Polylactic Acid Parts Based on Kriging and Cuckoo Search by Yuan Yang, Yiyang Wang, Bowen Xue, Changxu Wang, Bo Yang

“…As an emerging rapid manufacturing technology, 3D printing has been widely applied in numerous fields such as aerospace, shipbuilding, and wind power, by virtue of its advantage in efficiently fabricating components with complex structures and integrated functions. In response to the problems of poor mechanical properties and difficulty in selecting process parameters for fused deposition modeling (FDM), this paper analyzed the principle of FDM and proposed a parameter optimization method based on a Kriging and Cuckoo Search (CS) algorithm aimed at improving the mechanical properties of 3D printed polylactic acid (PLA) parts. …”
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Evaluating end-to-end autonomous driving architectures: a proximal policy optimization approach in simulated environments by Ângelo Morgado, Kaoru Ota, Mianxiong Dong, Nuno Pombo

“…The findings highlight the strengths of PPO in managing continuous control tasks, achieving smoother and more adaptable driving behaviors than value-based algorithms like Deep Q-Networks. However, challenges remain in generalization and computational demands, with end-to-end systems requiring extensive training time. …”
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ABOUT COMPLEX APPROACH TO MODELLING OF TECHNOLOGICAL MACHINES FUNCTIONING by A. A. Honcharov

“…When a control activation is given to the controlling device of the technological machine its modelling is executed at an algorithmic or logic level and the obtained output signals are interpreted as events and information about them is transferred to executive mechanisms.The proposed scheme of aggregate integration considers element models as object classes and the integration scheme is presented as a combination of object property values (combination of a great many input and output contacts) and combination of object interactions (in the form of an integration operator). …”
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Correlation between the white blood cell/platelet ratio and 28-day all-cause mortality in cardiac arrest patients: a retrospective cohort study based on machine learning by Huai Huang, Guangqin Ren, Shanghui Sun, Zhi Li, Yongtian Zheng, Lijuan Dong, Shaoliang Zhu, Xiaosheng Zhu, Wenyu Jiang

“…ObjectiveThis study aims to evaluate the association between the white blood cell-to-platelet ratio (WPR) and 28-day all-cause mortality among patients experiencing cardiac arrest.MethodsUtilizing data from 748 cardiac arrest patients in the Medical Information Mart for Intensive Care-IV (MIMIC-IV) 2.2 database, machine learning algorithms, including the Boruta feature selection method, random forest modeling, and SHAP value analysis, were applied to identify significant prognostic biomarkers. …”
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Enhancing education quality with hybrid clustering and evolutionary neural networks in a multi phase framework by Saleem Malik, Chandrakanta Mahanty, Jnanaranjan Mohanty, Krunal Vaghela, T. Narmadha, R. Sivaranjani, Javed Khan Bhutto, Saiful Islam, Anwar Khan, Amanuel Zewdie

“…HPEFCM-FSP consistently outperforms K-means and Fuzzy C-means in clustering educational data by getting higher Silhouette Scores and Dunn Index values on benchmark datasets. This algorithm’s strong feature selection and clustering help target educational interventions by revealing student learning behaviors. …”
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Opportunities, Challenges, and Future Directions for Generative Artificial Intelligence in Library Information Literacy Education: A Scoping Review by Fan YUAN, Jia LI

“…However, the study also identifies several critical challenges, including concerns about data accuracy concerns, inherent algorithmic biases, risks to academic integrity, and the potential weakening of independent thinking skills due to over-reliance on AI systems. …”
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Efficient AOA Estimation and NLOS Signal Utilization for LEO Constellation-Based Positioning Using Satellite Ephemeris Information by Junqi Guo, Yang Wang

“…For high-precision angle of arrival (AOA) estimation, current spectrum search algorithms are computationally expensive. To address this, we propose a method that downscales the 2D joint spectrum search algorithm by incorporating satellite ephemeris a priori information. …”
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Evaluating the feasibility of automating dataset retrieval for biodiversity monitoring by Alexandre Fuster-Calvo, Sarah Valentin, William C. Tamayo, Dominique Gravel

“…Automating these tasks through advanced algorithms holds immense potential to revolutionize biodiversity monitoring. …”
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Performance of two different artificial intelligence models in dental implant planning among four different implant planning software: a comparative study by Pathompong Roongruangsilp, Walita Narkbuakaew, Pathawee Khongkhunthian

“…Abstract Background The integration of artificial intelligence (AI) in dental implant planning has emerged as a transformative approach to enhance diagnostic accuracy and efficiency. …”
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Metrological evaluation and classification of porosity in metal additive manufacturing using X-ray computed tomography by Ibon Holgado, Naiara Ortega, José A. Yagüe-Fabra, Soraya Plaza, Herminso Villarraga-Gómez

“…Ensuring the structural integrity of metal additive manufacturing (AM) components is challenging due to inherent porosity, which critically affects mechanical performance. …”
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Data-Driven-Based Full Recovery Technology and System for Transformer Insulating Oil by Feng Chen, Li Wang, Zhiyao Zheng, Bin Pan, Yujia Hu, Kexin Zhang

“…The recovery process incorporates oil–gas saturation monitoring and an oil–gas precipitation assessment algorithm based on neural networks to enable intelligent control, ensuring thorough recovery of residual oil from transformers. …”
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Optimization of Adaptive I²H ∞ Control Method Based on Multiple Input Sensors by Yu Gu, Hanyang Li, Zeting Mei, Hao Wen, Yuanxiong Jin, Wenxuan Dong

“…The core contributions of this study include: 1) Designing a multi-sensor current reference estimator to dynamically generate the optimal electromagnetic torque through state variables such as wheel speed, acceleration, slope, and human factor database (heart rate, subjective score, fatigue index) to achieve real-time prediction of rider demand; 2) Proposing an adaptive current reference value estimation algorithm that integrates feedforward compensation and error feedback to ensure smooth switching of assistance modes and suppress sensor noise; 3) Developing an intention-induced H<inline-formula> <tex-math notation="LaTeX">$\infty $ </tex-math></inline-formula> robust current tracking controller that significantly enhances the system&#x2019;s robustness to parameter fluctuations and external disturbances by optimizing the H<inline-formula> <tex-math notation="LaTeX">$\infty $ </tex-math></inline-formula> norm of the closed-loop transfer function, while supporting personalized riding assistance.…”
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An Improved Tuning of PID Controller for PV Battery-Powered Brushless DC Motor Speed Regulation Using Hybrid Horse Herd Particle Swarm Optimization by A. RamaKrishnan, A. Shunmugalatha, K. Premkumar

“…In this study, speed control of PV battery-powered brushless DC motor (BLDC) is controlled by novel hybrid horse herd particle swarm optimization- (HHHPSO-) tuned proportional integral derivative (PID) controller. The optimal gain parameter of the PID controller is tuned by hybrid horse herd optimization algorithm. …”
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Efficient energy management using fuzzy logic control in a gym microgrid with stationary bikes, PV generation, and battery storage systems by Abdelfattah El Azzab, Abdelmounime El Magri, Ilyass El Myasse, Rachid Lajouad

“…This article presents the control and energy management system for a gym microgrid that integrates multiple stationary bikes and a photovoltaic (PV) generation system connected. …”
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An ensemble learning model to predict lymph node metastasis in early gastric cancer by Kaiqing Song, Jiaming Wu, Muchen Xu, Mengying Li, Yuqi Chen, Yi Zhang, Hong Chen, Caifeng Jiang

“…The study utilized both univariate and multivariate logistic regression analyses to identify independent risk factors for lymph node metastasis of early gastric cancer, while employing five distinct algorithms to calculate feature weights. The optimal feature combination for each algorithm model was determined by combining the six highest weight features from all five models along with the independent risk factors. …”
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Explainable Model of Fusion Network With Enhanced Optimization Approach for Tuberculosis Diagnosis by C. R. Dhivyaa, K. Nithya, C. Sathiya Kumar, R. Sudhakar

“…It combines the results from AEO (Artificial Ecosystem-based Optimization), MBO (Monarch butterfly optimization), and Seagull-Algorithm to form three optimized feature subsets. …”
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Intelligent data-driven system for mold manufacturing using reinforcement learning and knowledge graph personalized optimization for customized production by Chengcai He, Jiaxing Deng, Jingchun Wu, Beicheng Qin, Jinxiang Chen, Yan Li, Qiangsheng Huang

“…The proposed system integrates knowledge graphs with intelligent algorithms to support the development of a smart quality control framework tailored to personalized manufacturing. …”
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Study on the Impact of Input Parameters on Seawater Dissolved Oxygen Prediction Models by Wenqing Li, Jing Lv, Yuhang Wang, Xiangfeng Kong

“…Future research will develop a parameter adaptive selection algorithm, conduct the dynamic monitoring of multi-scale environmental factors, and achieve the intelligent optimization and verification of model parameters.…”
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