Advanced Sensor Integration and AI Architectures for Next-Generation Traffic Navigation by Cosmina-Mihaela Rosca, Adrian Stancu, Ionuț-Adrian Gortoescu

“…Current traffic management systems do not solve these challenges, which is why the research presents a new proposal for a traffic optimization system. …”
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LSAF-LSTM-Based Self-Adaptive Multi-Sensor Fusion for Robust UAV State Estimation in Challenging Environments by Mahammad Irfan, Sagar Dalai, Petar Trslic, James Riordan, Gerard Dooly

“…Unmanned aerial vehicle (UAV) state estimation is fundamental across applications like robot navigation, autonomous driving, virtual reality (VR), and augmented reality (AR). This research highlights the critical role of robust state estimation in ensuring safe and efficient autonomous UAV navigation, particularly in challenging environments. …”
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Outlier Traffic Flow Detection and Pattern Analysis Under Unplanned Disruptions: A Low-Rank Robust Decomposition Model by Zhipeng Duan

“…The accelerated proximal gradient solution algorithm is applied to obtain the decomposition results. …”
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Low-noise optimization design for underwater series-connected multi-sphere composite shell structure by Hefan LI, Guanjun ZHANG, Yuzhao KE

“…The particle swarm optimization (PSO) algorithm was employed to optimize the underwater radiation noise of the model, and the results were verified through the finite element method. …”
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Microseismic Data-Driven Short-Term Rockburst Evaluation in Underground Engineering with Strategic Data Augmentation and Extremely Randomized Forest by Shouye Cheng, Xin Yin, Feng Gao, Yucong Pan

“…The insights derived from this research provide a reference for microseismic data-based short-term rockburst prediction when faced with class imbalance and multicollinearity.…”
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Investigation of a staggered dual-rotor wound field synchronous motor for offshore wind turbine full-scale testing platforms by Yang Xue, Shiyao Qin, Chen Qi, Ning Wang, Cong Liu, Wenliang Zhao

“…To enhance average torque and minimize torque ripple, the rotor structure undergoes further optimization through a multi-objective genetic algorithm. Following this, an analysis of the electromagnetic performance of the optimized WFSDM is conducted. …”
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Bayesian semiparametric inference in longitudinal metabolomics data by Abhra Sarkar, Ornella Cominetti, Ivan Montoliu, Joanne Hosking, Jonathan Pinkney, Francois-Pierre Martin, David B. Dunson

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Clinical and imaging diagnosis of pediatric testicular microlithiasis: a physician’s dilemma by Ghada Habachi, Ghada Habachi, Ghada Habachi, Yosra Kerkeni, Yosra Kerkeni, Jouini Riadh, Jouini Riadh

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AI driven cardiovascular risk prediction using NLP and Large Language Models for personalized medicine in athletes by Ang Li, Yunxin Wang, Hongxu Chen

“…This work highlights how NLP-driven AI solutions are transforming biomedical research, accelerating early disease detection, and improving clinical decision-making for both athletes and the general population.…”
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Abnormal Electricity Consumption Behaviors Detection Based on Improved Deep Auto-Encoder by Nvgui LIN, Lanxiu HONG, Daoshan HUANG, Yang YI, Zhixuan LIU, Qifeng XU

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MEIL-NeRF: Memory-Efficient Incremental Learning of Neural Radiance Fields by Jaeyoung Chung, Kanggeon Lee, Sungyong Baik, Kyoung Mu Lee

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Clinical and epidemiological characteristic viral diarrhea in children by A. M. Lukjanova, M. K. Bekhtereva, N. N. Ptichnikova

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Мethodology for calculation of phase behavior of a natural hydrocarbon system with account of formation water mineralization by L. T. Abdrazakova, A. Gilmanov, A. P. Shevelev

“…Unlike the traditional algorithm, this methodology involves the Sechenov equation. …”
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Optimization of energy balances of a photovoltaic power plant with electrochemical and thermal storage of solar energy by B. V. Lukutin, Kadhim Karrar Hameed

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Shipboard power system dynamic reconfiguration optimization strategy considering time-varying load characteristics by Qihuan WU, Zhiyu ZHU, Weihan HAO, Denghao YANG, Cheng XU

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Critical analysis of the existing approach to the calculation of radiation shielding in X-ray rooms by V. Yu. Golikov

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Analysis of the Effectiveness of Traditional and Ensemble Machine Learning Models for Mushroom Classification by Neny Sulistianingsih, Galih Hendro Martono

“… The classification of edible versus poisonous mushrooms presents a critical challenge in the domains of applied biology and public health, particularly due to the serious implications of misidentification. This research employs the UCI Mushroom Dataset to evaluate and compare the effectiveness of several machine learning models, including traditional algorithms like Logistic Regression, Decision Tree, Random Forest, Support Vector Machine, K-Nearest Neighbors and Naïve Bayes, as well as advanced ensemble techniques such as Stacking and Voting Classifier. …”
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Application of Monte Carlo Simulation (MCS) and Fuzzy Finite Element (FFEM) for Investigating the Uncertainty of Seepage in Homogeneous Earth Dams by Milad Kheiry, Farhoud Kalateh

“…The purpose of this research is to investigate the impact of uncertainty in the prediction of seepage flow through earth dams using the Fuzzy Monte Carlo Simulation (FMCS) new hybrid algorithm, which is implemented with the help of the finite element method and monte carlo simulation. …”
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Ultrasonic Mammography with Circular Transducer Array by Krzysztof J. OPIELIŃSKI, Piotr PRUCHNICKI, Tadeusz GUDRA

“…Fast acquisition of measurement data is achieved as a result of parallel switching of opposite transmitting and receiving transducers in the circular array and vertical movement of the array. The algorithm equalizing the length of measurement rays and distances between them was elaborated for the reconstruction of projection images. …”
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Comparison of Spatial Predictability Differences in Truck Activity Patterns: An Empirical Study Based on Truck Tracking Dataset of China by Lianghua Li, Peng Du, Guohua Jiao, Xin Fu

“…Existing research on truck location prediction focuses on direct trajectory prediction and ignores the link between activity patterns and predictability, whereas the mode of operation is an important factor in the difference between activity trajectories, and analyzing the mode of operation can help to develop the next-location prediction algorithms to improve the efficiency of matching truckloads and to reduce costs. …”
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