Development of a multi-level feature fusion model for basketball player trajectory tracking by Tao Wang

“…This study has the following two contributions. Firstly, a new model of athlete trajectory tracking is proposed, which improves the accuracy and efficiency of multi-target tracking by optimizing object detection algorithm and introducing hybrid branch network. …”
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Effectiveness of machine learning models in diagnosis of heart disease: a comparative study by Waleed Alsabhan, Abdullah Alfadhly

“…An extensive array of preprocessing techniques is thoroughly examined in order to optimize the predictive models’ quality and performance. …”
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Investigation on Photovoltaic Array Modeling and the MPPT Control Method under Partial Shading Conditions by Jianbo Bai, Leihou Sun, Rupendra Kumar Pachauri, Guangqing Wang

“…Optimized particle swarm optimization (OPSO) is used to control the multipeak output model that can quickly and accurately track the global maximum power point (GMPP) of PV modules under PSCs. …”
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On differential privacy for federated learning in wireless systems with multiple base stations by Nima Tavangaran, Mingzhe Chen, Zhaohui Yang, José Mairton B. Da Silva Jr., H. Vincent Poor

“…To find the locally optimal solutions of this problem, we first propose an algorithm that schedules the resource blocks and users. …”
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Multi-objective optimization of custom implant abutment design for enhanced bone remodeling in single-crown implants using 3D finite element analysis by Pongsakorn Poovarodom, Chaiy Rungsiyakull, Jarupol Suriyawanakul, Qing Li, Keiichi Sasaki, Nobuhiro Yoda, Pimduen Rungsiyakull

“…In conclusion, the depth and taper have a significant effect on bone remodeling. This optimized model significantly improves bone density uniformity.…”
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Enhanced Detection of Leishmania Parasites in Microscopic Images Using Machine Learning Models by Michael Contreras-Ramírez, Jhonathan Sora-Cardenas, Claudia Colorado-Salamanca, Clemencia Ovalle-Bracho, Daniel R. Suárez

“…Machine learning models (ANN, SVM, and RF) optimized through Grid Search were applied for classification. …”
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Analysis of the state of geometrization development and digital modeling in open-pit mining enterprises by M.S. Kunytska, D.S. Polishchyk, O.V. Shapochnikov

“…Key development trends are identified: integration of digital technologies, improvement of methods of collecting and processing geospatial data, introduction of machine learning algorithms for risk prediction. …”
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Robust InceptionV3 with Novel EYENET Weights for Di-EYENET Ocular Surface Imaging Dataset: Integrating Chain Foraging and Cyclone Aging Techniques by Muhammad Ahmad Khan, Saif Ur Rehman Khan, Hafeez Ur Rehman, Suliman Aladhadh, Ding Lin

“…This research highlights the potential of nature-inspired optimization algorithms and tailored datasets to enhance AI model robustness and adaptability in the context of medical disease diagnosis, particularly in the field of diabetic eye disease.…”
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Classification of edible vegetable oils based on three-dimensional fluorescence spectroscopy and ISSA-SVM by ZHANG Jing, QI Guohong, CHEN Jingzhao, CAO Xiaoli, LI Lili

“…ObjectiveTo improve the classification accuracy of edible vegetable oils, an identification model based on three-dimensional fluorescence spectroscopy and ISSA-SVM was established.MethodsCombining the feature information of three-dimensional fluorescence spectroscopy, an improved sparrow search algorithm was used to optimize the parameters of the SVM model, constructing an edible vegetable oil identification method that integrates the characteristics of three-dimensional fluorescence spectroscopy information and the ISSA-SVM model.ResultsCompared with the SVM model, GA-SVM model, PSO-SVM model, and SSA-SVM model, the classification accuracy of the ISSA-SVM model for edible vegetable oils reached 100%.ConclusionThe ISSA-SVM model has higher convergence efficiency, system stability, and the ability to avoid local optimal solutions, which can effectively cope with complex and variable sample classification tasks.…”
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A novel network-level fused deep learning architecture with shallow neural network classifier for gastrointestinal cancer classification from wireless capsule endoscopy images by Muhammad Attique Khan, Usama Shafiq, Ameer Hamza, Anwar M. Mirza, Jamel Baili, Dina Abdulaziz AlHammadi, Hee-Chan Cho, Byoungchol Chang

“…The proposed framework offers improved accuracy, precision, and computational efficiency compared to state-of-the-art models. …”
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Accelerated Reconstruction of Scenes Using CUDA-Based Parallel Computing by Gui Zou, Jin Jiang, Qi Chen

“…Since the drone needs to use an embedded onboard computer and stereo matching algorithms require massive computing resources, this paper studies the optimization of CUDA-based stereo matching algorithms on embedded devices to improve the reconstruction effect of scenes and achieve rapid reconstruction, thereby reducing time costs, and enhancing drone efficiency.…”
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Target detection of helicopter electric power inspection based on the feature embedding convolution model. by Dakun Liu, Wei Zhou, Linzhen Zhou, Wen Guan

“…In the simulation experiment, the accuracy of the model in electric power circuit and equipment detection is improved by 30% compared with the traditional algorithm, and the inspection range is expanded by 26%. …”
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Revealing the Driving Factors of Household Energy Consumption in High-Density Residential Areas of Beijing Based on Explainable Machine Learning by Zizhuo Qi, Lu Zhang, Xin Yang, Yanxia Zhao

“…Data were collected through field surveys, questionnaires, and interviews, covering 16 influencing factors across household, building, environment, and transportation categories. A hyperparameter-optimized ensemble model (XGBoost, RF, GBDT) was employed, with XGBoost combined with genetic algorithm tuning performing best. …”
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A nonlinear dynamic hysteresis model and dynamic performance of the piezoelectric ring bending actuator by Yuesong Li, Bang Wang

“…Second, an improved model of the piezoelectric ring bending actuator was developed based on the Bouc–Wen model, and its parameters were identified by the particle swarm optimization algorithm. …”
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Strategic Power Flow-Stackelberg Dynamics for Minimizing Transmission Losses in Peer-to-Peer Trading by K. V. Biji Varghese, Dattatraya N. Gaonkar

“…Results from these tests are compared with existing energy trading systems, highlighting improvements in scalability, efficiency, and overall performance. …”
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Enhanced load frequency regulation in microgrids with renewable energy sources and electric vehicles by Imran Khan, Suheel Abdullah Malik, Amil Daraz, Baitullah Bareer

“…Simulation results show that the (I-P) cascaded PDN controller significantly outperforms existing controllers, such as PID, and PI-based models, by reducing frequency deviations, improving settling time, and minimizing overshoot and error indices. …”
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Leveraging ensemble convolutional neural networks and metaheuristic strategies for advanced kidney disease screening and classification by Abeer saber, Esraa Hassan, Samar Elbedwehy, Wael A. Awad, Tamer Z. Emara

“…The proposed model combines multiple DL models to improve overall performance by leveraging the strengths of different architectures, ensembles can enhance accuracy, robustness, and generalization. …”
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THEORETICAL AND METHODOLOGICAL PRINCIPLES OF APPLICATION OF AGENT-ORIENTED APPROACH TO MODELING PROCESSES OF LOCAL HROMADAS by Yevgen Kotukh, Maryna Riabokin

“…The article also outlines a multi-step algorithm for modeling decision-making and coordination processes within the decentralized budget structure. …”
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An intelligent SWMM calibration method and identification of urban runoff generation patterns by Zixin Yang, Zixin Yang, Zixin Yang, Jiahong Liu, Jiahong Liu, Jiahong Liu, Youcan Feng, Youcan Feng, Youcan Feng, Jia Wang, Jia Wang, Hao Wang, Hao Wang, Hao Wang, Changhai Li, Changhai Li, Changhai Li

“…This study proposes a universal and effective method to enhance model accuracy by optimizing parameter value ranges through an unsupervised intelligent clustering algorithm. …”
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A model predictive control method for directional borehole trajectories in underground coal mines by Hao LI, Ningping YAO, Chengda LU, Jinbao ZHANG, Hongchao WEI, Jiajun WU, Jinyu LI

“…The improved MPC method with the feedback correction mechanism for predicting directional borehole trajectories removes the impacts of model adaptation and steady-state errors. …”
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