Multipath intelligent transmission strategy for UAM dynamic networks by WANG Yuting, LENG Supeng, XIONG Kai

“…To further improve the adaptability of the routing algorithm to dynamic environments, an environmental validation mechanism was designed to evaluate the compatibility between current routing strategies and dynamic network, enabling self-adaptive adjustment of routing strategies during the transmission process. …”
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Application of a Hybrid Model Based on CEEMDAN and IMSA in Water Quality Prediction by GUO Li-jin, WU Hao-tian

“…After integrating decomposition, use of entropy, algorithm optimization, and error correction models, eleven comparative experiments were established to evaluate the effectiveness of each optimization method. …”
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A hybrid mutational Northern Goshawk and elite opposition learning artificial rabbits optimizer for PEMFC parameter estimation by Pradeep Jangir, Absalom E. Ezugwu, Kashif Saleem, Arpita, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, G. Gulothungan, Laith Abualigah

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Improved UWB-based indoor positioning system via NLOS classification and error mitigation by Shoude Wang, Nur Syazreen Ahmad

“…In terms of distance measurement error mitigation, the proposed AREKF algorithm reduced errors at the 95th percentile by 70% and 75% in two different environments compared to transfer learning methods on the same public dataset. …”
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Fourier Analysis of CMFD Method in Cylindrical Geometry by WEN Yuchen, HAO Chen, WANG Yizhen

“…The coarse mesh finite difference (CMFD) method has been widely adopted as an acceleration algorithm for neutron transport calculations, effectively reducing computational costs and improving convergence. …”

Performance Evaluation of Image Segmentation Using Dual-Energy Spectral CT Images with Deep Learning Image Reconstruction: A Phantom Study by Haoyan Li, Zhenpeng Chen, Shuaiyi Gao, Jiaqi Hu, Zhihao Yang, Yun Peng, Jihang Sun

“…The evaluation set used 5 mGy VMIs reconstructed with various reconstruction algorithms: FBP, ASIR-V50%, ASIR-V100%, deep learning image reconstruction (DLIR) with low (DLIR-L), medium (DLIR-M), and high (DLIR-H) strength levels. …”
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Phenology-Based Maize and Soybean Yield Potential Prediction Using Machine Learning and Sentinel-2 Imagery Time-Series by Dorijan Radočaj, Ivan Plaščak, Mladen Jurišić

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Dynamic Range Expansion Using Cumulative Histogram Learning for High Dynamic Range Image Generation by Hanbyol Jang, Kihun Bang, Jinseong Jang, Dosik Hwang

“…The novel learning technique is called cumulative histogram-based learning and color difference learning. The superior performance of our technique over conventional methods was assessed through objective evaluations of various types of LDR and HDR images.…”
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BT-YOLO11: Automatic Driving Road Target Detection in Complex Scenarios by Qi Wang, Qi Long Wang

“…The Tri-directional Feature Pyramid Net is used in the feature fusion stage, which adequately fuses different levels of feature information and improves the accuracy and robustness of the algorithm. …”
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Evaluation of the effectiveness of communications between the Department of transport and Development of road transport infrastructure of Moscow and the population within the frame... by R. A. Abramov, Yu. Yu. Temnikova

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Multi-Condition Rolling Bearing Fault Denoising Method and Application Based on RIME-VMD by Xin Zhao, Xuebin Liu, Hanshan Li

“…According to the characteristics of rolling bearing fault signal, RIME (frost and ice algorithm) is utilized to obtain adaptive optimization of the modal number and penalty factors in VMD (variational mode decomposition) algorithm, and then the optimized core parameters are input into VMD to decompose the rolling bearing fault signal. …”
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Wound imaging software and digital platform to assist review of surgical wounds using patient smartphones: The development and evaluation of artificial intelligence (WISDOM AI stud... by Melissa Rochon, Judith Tanner, James Jurkiewicz, Jacqueline Beckhelling, Akuha Aondoakaa, Keith Wilson, Luxmi Dhoonmoon, Max Underwood, Lara Mason, Roy Harris, Karen Cariaga

“…<h4>Methods and analysis</h4>Conducted from September 2023 to March 2024, the study phases included compiling a training dataset of 37,974 images, creating a testing set of 3,634 images, developing an AI algorithm using 'You Only Look Once' models, and conducting prospective tests compared against clinical nurse specialists' evaluations. …”
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Decision-Making Model for Life Cycle Management of Aircraft Components by Igor Kabashkin, Vitaly Susanin

“…These studies showcase the model’s versatility in handling different failure patterns and maintenance requirements. …”
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Exploring Procedural Content Generation of Environments for Virtual Museums: A Mixed-Initiative Approach by Claudio Rubio, Nicolas A. Barriga, Ben Ingram, Huizilopoztli Luna-García, Felipe Besoain

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探討強化學習演算法之素材推薦機制與AI學習履歷之學習者感知 Learner Perceptions of AI-Powered Learning Portfolios and Personalized Material Recommendation Mechanisms in Reinforcement Learning Algorithms... by 曾建維 Jian-Wei Tzeng, 黃天麒 Tien-Chi Huang, 薛承祐 Cheng-Yu Hsueh, 廖英淞 Ying-Song Liao

“…Consistent percentile rank increases following practice question completion suggest the system’s capacity to deliver personalized recommendations on the basis of individual differences, thereby facilitating concept-specific feedback and adaptive learning. …”
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Integration of multi agent reinforcement learning with golden jackal optimization for predicting average localization error in wireless sensor networks by K. Lakshmi Prabha, Hanan Abdullah Mengash, Hamed Alqahtani, Randa Allafi

“…The proposed optimized MARL framework dynamically learns optimal parameter adjustments through a reward mechanism, minimizing localization error and its variability even under dynamic network conditions. The GJO algorithm fine-tunes the hyperparameters of MARL to improve generalization across different WSN configurations. …”
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Construction of a risk prediction model for pulmonary infection in patients with spontaneous intracerebral hemorrhage during the recovery phase based on machine learning by Jixiang Xu, Yuan Li, Fumin Zhu, Fumin Zhu, Xiaoxiao Han, Liang Chen, Yinliang Qi, Yinliang Qi, Xiaomei Zhou, Xiaomei Zhou

“…Seven ML algorithms were employed to build predictive models, with performance evaluated based on the area under the receiver operating characteristic (AUC) curve, sensitivity, specificity, and accuracy. …”
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Enhanced AdaBoostM1 with Multilayer Perceptron for Stock Price Prediction by Rebwar Mala Nabi, Soran AB. Saeed, Habibollah Haron

“…Among the predictive models, various adaptations of the AdaBoostM1 algorithm have been applied to stock market prediction, either by tuning parameters or experimenting with different base learners. …”
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Intelligent power control strategy based on self-tuning fuzzy MPPT for grid-connected hybrid system by H. Chaib, S. Hassaine, Y. Mihoub, S. Moreau

“…Unlike conventional methods that rely on logical switches, this intelligent strategy utilizes fuzzy rules adapted to different operating modes for more sophisticated energy control. …”
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Performance assessment of basalt fibre concrete under freeze-thaw cycles using hybrid long short-term memory models by Qingguo Yang, Honghu Wang, Qigui Yi, Liuyuan Zeng, Rui Xiang, Longfei Guan, Jiawei Cheng, Keling Chen, Yunhao Li

“…By integrating self-conducted experimental data and referenced datasets, a diverse experimental database was constructed. Improved algorithms, namely Asynchronous Learning Particle Swarm Optimization (AsyLnCPSO) and Hybrid Genetic Algorithm-based Particle Swarm Optimization (GA-HIDMS-PSO), were paired with LSTM neural networks to systematically evaluate their adaptability and effectiveness in predicting the performance of basalt fiber-reinforced concrete under freeze-thaw conditions. …”
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