Distribution and Moments of the Idle Period and Interarrival Time in the G/M/1 Queueing System by Felipe A. Cruz-Perez, Sandra Lirio Castellanos-Lopez, Genaro Hernandez-Valdez, Mario Eduardo Rivero-Angeles

“…Additionally, the accuracy of the derived distribution and moments of the idle period when the LN interarrival time is approximated by HE distributions of different orders (using the Expectation-Maximization algorithm) is investigated. Numerical results show a good fit accuracy between idle period distributions obtained under the LN and the m-th order HE interarrival time models. …”
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Failure mechanism-driven multi-adversarial domain transfer learning for rolling bearing fault diagnosis by Zhihui Zhang, Zhidan Zhong, Zhe Li, Wentao Mao, Yunhao Cui

“…To address these challenges, this paper proposes a Failure Mechanism-Driven Multi-Adversarial Domain Transfer Learning algorithm. The core of this method is the deep integration of physical prior knowledge with data-driven models. …”
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A Lightweight Direction-Aware Network for Vehicle Detection by Luxia Yang, Yilin Hou, Hongrui Zhang, Chuanghui Zhang

“…The mechanism can fully perceive the details and salient information of input features in multiple directions, thus improving the ability of the model to capture critical features. …”
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Artificial intelligence as one of the key drivers of the economy digital transformation by O.I. Pizhuk

“…Artificial intelligence technologies represent a unique opportunity for us to transform business operations by reducing the number of repetitive, routine tasks, significantly increase productivity, create new products, create new models of economic growth, and improve the efficiency of government agencies, especially at the level of development of solutions aimed at ensuring the well-being of citizens. …”
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A comprehensive approach to predict a rocket's impact with stochastic estimators and artificial neural networks by Jose Abreu, Roberto L. Oliveira, Joao V. Fonseca Neto

“…This approach combines tracking algorithms that are based on stochastic estimators with artificial neural network (ANN) models. …”
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Machine Learning-Based Methodologies for Cyber-Attacks and Network Traffic Monitoring: A Review and Insights by Filippo Genuario, Giuseppe Santoro, Michele Giliberti, Stefania Bello, Elvira Zazzera, Donato Impedovo

“…The number of connected IoT devices is increasing significantly due to their many benefits, including automation, improved efficiency and quality of life, and reducing waste. …”
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Slip and tractive efficiency of an electric tractor with a 4WID E-axle system by SeungYun Baek, HyeonHo Jeon, CheolGyu Park, YongJoo Kim

“…Abstract This study aims to verify the performance of an electric tractor equipped with a four-wheel independent driving (4WID) electric axle (E-axle) system through simulation analysis using a MATLAB/Simulink model. The simulation model was validated through bench testing to ensure accuracy and reliability. …”
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A Systematic Mapping Study on State Estimation Techniques for Lithium-Ion Batteries in Electric Vehicles by Carolina Tripp-Barba, José Alfonso Aguilar-Calderón, Luis Urquiza-Aguiar, Aníbal Zaldívar-Colado, Alan Ramírez-Noriega

“…RUL prediction sees advancements through deep learning techniques, especially LSTM and gated recurrent units (GRUs), improved using algorithms such as Harris Hawks Optimization (HHO) and Adaptive Levy Flight (ALF). …”
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Self-Shielding Treatment to Perform Cell Calculation for Seed Furl In Th/U Pwr Using Dragon Code by Ahmed Amin El Said Abd El Hameed, Mohamed Nagy, Hanaa Abou-Gabal

“…There are mainly two resonance self-shielding models commonly applied: models based on equivalence and dilution and models based on subgroup approach. …”
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Formulation and evaluation of ocean dynamics problems as optimization problems for quantum annealing machines. by Takuro Matsuta, Ryo Furue

“…In contrast, QA using the D-Wave quantum annealing machine fails to obtain good solutions for some cases owing to hardware limitations; in particular, the highly limited connectivity graph of the machine limits the size of the solvable problems, at least under currently available algorithms. Either expanding the machine's connectivity graph or improving the graph-embedding algorithms would probably be necessary for quantum annealing machines to be usable for oceanic and atmospheric dynamics problems.…”
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Data Mining Techniques for Early Detection and Classification of Plant Diseases: An Optimization-Based Approach by Wagh Swapnil, Sharma Ruchi

“…Furthermore, low-level optimization techniques like genetic algorithms as well as particle swarm optimization are used to fine tune the specific model parameters and to reduce the computational overhead for improving the detection efficacy still more. …”
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Research on Recognition of Green Sichuan Pepper Clusters and Cutting-Point Localization in Complex Environments by Qi Niu, Wenjun Ma, Rongxiang Diao, Wei Yu, Chunlei Wang, Hui Li, Lihong Wang, Chengsong Li, Pei Wang

“…Comparative experiments on YOLOv5s, YOLOv8s, and YOLOv11s models revealed that YOLOv11s achieved a recall of 0.91 in leaf-occluded environments, marking a 21.3% improvement over YOLOv5s, with a detection speed of 28 Frames Per Second(FPS). …”
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Exploring interconnections among atoms, brain, society, and cosmos with network science and explainable machine learning by Daniele Caligiore, Daniele Caligiore, Anna Monreale, Anna Monreale, Giulio Rossetti, Angela Bongiorno, Giuseppe Fisicaro

“…The results of domains cross-fertilization could support practical applications, such as improving neuroprosthetics and brain-machine interfaces by leveraging criticality in materials science and neuroscience or developing advanced materials for space exploration. …”
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Possibilities of statistical methodology in the study of economic security of the region by Dmitry V. Dianov, Elena A. Radugina

“…The use of the designated statistical tools allowed obtaining such results as justification of analytical capabilities and approbation of statistical methods in the study of economic security of the Moscow region; formation of clusters, consisting of homogeneous municipal districts of the Moscow region, designated as clustering units; calculation of relative analytical indicators; construction and interpretation of regression models.Conclusion: the complex of the obtained results and conclusions, as well as the scientifically based algorithm of statistical tools application, tested in the work, are undoubtedly an important information component in the management of economic and financial security not only in the Moscow region, but also in any region, both in the Central Federal district and in the whole central Russia.…”
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Global Aerosol Climatology from ICESat-2 Lidar Observations by Shi Kuang, Matthew McGill, Joseph Gomes, Patrick Selmer, Grant Finneman, Jackson Begolka

“…This work highlights the importance of vertical aerosol distributions needed for more accurate quantification of the aerosol–cloud interaction influence on radiative forcing for improving global climate models.…”
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DMF-YOLO: Dynamic Multi-Scale Feature Fusion Network-Driven Small Target Detection in UAV Aerial Images by Xiaojia Yan, Shiyan Sun, Huimin Zhu, Qingping Hu, Wenjian Ying, Yinglei Li

“…However, traditional detection models suffer significant performance degradation due to challenges including substantial scale variations, high proportions of small targets, and dense occlusions in UAV-captured images. …”
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Advanced GPU Techniques for Dynamic Remeshing and Self-Collision Handling in Real-Time Cloth Tearing by Jong-Hyun Kim, Jung Lee

“…In this study, we propose a GPU-optimized dynamic remeshing algorithm that enables real-time processing of high-resolution cloth tearing. …”
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Trajectories of Cognitive Complaints in Patients With Breast Cancer and Their Association With Psychosocial and Neurobiological Factors by Rob Colaes, Gwen Schroyen, Rebeca Alejandra Gavrila Laic, Jeroen Blommaert, Sigrid Hatse, Ann Smeets, Stefan Sunaert, Sabine Deprez

“…Using the partition around medoids (PAM) algorithm on the difference scores of cognitive complaints, patients were clustered into distinct groups. …”
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ThermOptCobra: Thermodynamically optimal construction and analysis of metabolic networks for reliable phenotype predictions by Pavan Kumar S, Nirav Pravinbhai Bhatt

“…Moreover, it enhances sampling algorithms by enabling loopless sample generation. In summary, ThermOptCOBRA significantly improves TIC handling in GEMs, advancing metabolic model quality for deeper insights into cellular metabolism.…”
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Wineinformatics: Wine Score Prediction with Wine Price and Reviews by Yuka Nagayoshi, Bernard Chen

“…Using this dataset, classifiers, and normalization methods, the models with and without the price feature were compared. …”
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