Dynamical systems and complex networks: a Koopman operator perspective by Stefan Klus, Nataša Djurdjevac Conrad

“…We will show how these methods can also be used to analyze complex networks and highlight relationships between Koopman operators and graph Laplacians.…”
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Computer vision based automatic evaluation method of Y2O3 steel coating performance with SEM image by Jianhong Zhao, Huamin Yang, Yi Sui

“…This approach not only enhances the training process but also simplifies loss function design, ultimately leading to a proper evaluation of surface modifications in steel materials. …”
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Observational Limitations to the Emergence of Climate Signals by Louis Rivoire, Marianna Linz, Jingyuan Li

“…In reality, observational knowledge suffers from data quality and availability issues, for instance data gaps, changes in instrumentation, issues due to gridding and retrieval algorithms. Overlooking such deficiencies leads to misrepresentations of the time of emergence (ToE). …”
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Swarm intelligence for energy-efficient heating, ventilation, and air conditioning (HVAC) systems: A case study in smart buildings by Vinoth Kanna I, Raja Subramani, Maher Ali Rusho, Shubham Sharma, Ramachandran T, Abinash Mahapatro, Deepak Gupta, Jasmina Lozanovic

“…This research utilizes swarm intelligence algorithms—Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and hybrid PSO-ACO-to optimize energy efficiency and thermal comfort in smart building HVAC systems. …”
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Efficient Spectral Galerkin and Collocation Approaches Using Telephone Polynomials for Solving Some Models of Differential Equations with Convergence Analysis by Ramy Mahmoud Hafez, Hany Mostafa Ahmed, Omar Mazen Alqubori, Amr Kamel Amin, Waleed Mohamed Abd-Elhameed

“…The suggested approach also handles partial differential equations (PDEs), emphasizing hyperbolic PDEs. …”
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Learning data characteristics of a session-based recommendation system and their impact on system performance by Urszula Kużelewska

“…The success of recommendation systems hinges on the quality of the methods used. However, there is also an impact on the input data. Session-based techniques are the most effective way to generate recommendations. …”
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Differential diagnosis of pericarditis. Part I: Anatomical and physiological characteristics of the pericardium, chest pain syndrome, and pericardial effusion by V. Yu. Myachikova, O. M. Moiseeva

“…Anatomical and physiological characteristics of the pericardium, mechanisms of effusion development and tamponade are described. Diagnostic algorithms for chest pain syndrome typical for pericarditis and asymptomatic effusion are provided. …”
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Dostoevsky in Japanese Translations: The Problem of Textual Images by U. P. Strizhak

“…Such analysis will help also to highlight the peculiarities of the “new translation school” that adheres to the strategy of domestication, making the foreign text more readable.…”
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Vehicle Motion Sickness Profiling Through Interpretable Gradient Boosting: A Framework for Advanced Driver Assistance Systems by Jon Ander Ruiz Colmenares, Estibaliz Asua

“…The proposed approach leverages both classical and modern algorithms, with CatBoost emerging as the top-performing model after optimization. …”
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Azo Dyes and the Microbial World: Synthesis, Breakdown, and Bioactivity by Valery M. Dembitsky, Alexander O. Terent’ev

“…Using mathematical algorithms and the PASS program, researchers predict new potential applications based on their structure–activity relationships. …”
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Interest-Rate Products Pricing Problems with Uncertain Jump Processes by Yiyao Sun, Shiqin Liu

“…For this reason, numerical algorithms are designed by using the formulas in order to compute the prices of these structured products. …”
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Machine Learning in Maritime Safety for Autonomous Shipping: A Bibliometric Review and Future Trends by Jie Xue, Peijie Yang, Qianbing Li, Yuanming Song, P. H. A. J. M. van Gelder, Eleonora Papadimitriou, Hao Hu

“…Autonomous vessels are becoming paramount to ocean transportation, while they also face complex risks in dynamic marine environments. …”
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The different member equivalent circulating density prediction model and drilling parameter optimization under narrow density window by Wanchun Zhao, Wanchun Zhao, Zhipeng Yang, Tingting Wang, Yan Zhou, Wei Song, Jingrun Li, Peihong Zhai

“…An ECD prediction model based on drilling parameters and segmented reservoir layers is also proposed. The model uses nonlinear regression algorithms to predict ECD values for different members. …”
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Research on Traffic Accident Severity Level Prediction Model Based on Improved Machine Learning by Jiming Tang, Yao Huang, Dingli Liu, Liuyuan Xiong, Rongwei Bu

“…Decision tree, XGBoost, and random forest algorithms, respectively, were applied for the secondary prediction. …”
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When Machine and Human Meet. Art in the Age of Artificial Intelligence by Sylwia Szykowna

“…The cited historical examples of aesthetic reflection accompanying computer art of the 1960s largely anticipated the changes taking place today, while also serving an important metacritical function. …”
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Specx: a C++ task-based runtime system for heterogeneous distributed architectures by Paul Cardosi, Bérenger Bramas

“…Not only does it allow efficient parallelization across distributed heterogeneous computing nodes, but it also allows for elegant source code structuring by describing hardware-independent algorithms. …”
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Artificial Intelligence in PR: Transformations of Communication Strategies and Campaigns by Maria Nikolova

“…However, the arti-cle also explores the ethical challenges posed by AI, including issues of authenticity, transpar-ency, and data privacy. …”
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Examining the Gender Dynamics in the Gig Economy: A Systematic Literature Review by J. S. Bhagavathi

“…The result of the review shows that, in the gig economy too, women are more represented in already gender–biased jobs, such as childcare, and tutoring, and the gender earnings gap is prevalent in all types of gig platforms. Algorithmic biases and security and safety concerns are also identified in the platform economy. …”
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Estimation of CO₂ Emissions in Transportation Systems Using Artificial Neural Networks, Machine Learning, and Deep Learning: A Comprehensive Approach by Seval Ene Yalçın

“…The proposed approach incorporates artificial neural networks, machine learning, and deep learning algorithms. The case of Turkey was considered as an example. …”
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Cryptomite: A versatile and user-friendly library of randomness extractors by Cameron Foreman, Richie Yeung, Alec Edgington, Florian J. Curchod

“…The library offers a range of two-source, seeded and deterministic randomness extractors, together with parameter calculation modules, making it easy to use and suitable for a variety of applications. We also present theoretical results, including new extractor constructions and improvements to existing extractor parameters. …”
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