Fast 2D forward modeling of electromagnetic propagation well logs using finite element method and data-driven deep learning by A.M. Petrov, A.R. Leonenko, K.N. Danilovskiy, O.V. Nechaev

“…The motivation for this research is the need for advanced modeling algorithms that are fast enough for use in modern quantitative interpretation tools, where thousands of simulations may be required in iterative inversion processes. …”
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Technical, forensic and organisational aspects of work with Monero cryptocurrency by V. V. Nosov, O. V. Manzhai, V. O. Kovtun

“…The work of this algorithm in the test network Stagenet is modelled. …”
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AI-based model for Prediction of Power consumption in smart grid-smart way towards smart city using blockchain technology by Emran Aljarrah

“…To achieve precise load forecasting, a short-term recurrent neural network with an improved sparrow search algorithm (LSTM-RNN-ISSA) is incorporated. The smart grid may then record the projected results. …”
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Reinforcement-Learning-Based Trajectory Design and Phase-Shift Control in UAV-Mounted-RIS Communications by Tianjiao Sun, Sixing Yin, Li Deng, F. Richard Yu

“…As the action space is continuous, the deep deterministic policy gradient (DDPG) algorithm is applied to train the RL model. However, the online interaction between the agent and environment may lead to instability during the training and the assumption of (first-order) Markovian state transition could be impractical in real-world problems. …”
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Estimating Economic Insights: A Machine Learning Method for Estimating the Shanghai Stock Exchange by Reza Seifi Majdar, Seyed Hadi Seyed Hatami

“…Engaging in stock market investments may be uncertain, but it has the possibility of providing substantial profits in the long run. …”
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On Combining Different Acceleration Techniques at the Iterative Solution of PDEs by the Method of Collocations and Least Residuals by Vasily P. Shapeev, Evgenii V. Vorozhtsov

“…Each of the above techniques is shown to make its contribution to the quantitative figure of iteration process speed-up. The algorithm which employs the Krylov subspaces makes the most significant contribution. …”
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Qualification of beatings as non-live-threatening and non-health-threatening violence by O. V. Artyushina

“…The subject. The algorithm of qualification of beatings is researched taking into account changes in the Russian legislation of Russia on the protection of bodily integrity of a person. …”
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Dynamic Stability and Reactive Power Control Using Dandelion-Optimized Cascaded Fractional Order Tilt Controller in Renewable Energy Systems by G. M. Sachin, Abhik Banerjee, S. N. Deepa

“…Similarly, the effectiveness of the DO algorithm is validated through a comparative analysis of dynamic voltage and convergence characteristics with those of traditional algorithms. …”
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Unsupervised Structural Damage Detection Technique Based on a Deep Convolutional Autoencoder by Zahra Rastin, Gholamreza Ghodrati Amiri, Ehsan Darvishan

“…As it is not usually possible to collect data from damaged states of a large civil structure, using such algorithms for these structures may be impractical. …”
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Back‐Projection Imaging of Extended, Diffuse Sources of Volcano‐Tectonic Seismicity During June 2010 at Sierra Negra Volcano, Galápagos by C. L. Kelly, J. F. Lawrence

“…This noise contains valuable information about subsurface processes that occur between volcanic eruptions and may provide critical information for mitigating risks from volcanic hazards. …”
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Determinação da cobertura do solo por análise de imagens e redes neurais Soil cover determination using image analysis and neural networks by Carlos A. A. Varella, Francisco de A. de C. Pinto, Daniel M. de Queiroz, Darly G. de Sena Júnior

“…<br>An image classification algorithm was developed to estimate the soil cover based on artificial neural networks (ANN) trained by back-propagation algorithm. …”
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Mathematical Modeling of Tuberculosis Transmission Dynamics With Reinfection and Optimal Control by Francis Oketch Ochieng

“…The model was fitted to historical TB incidence data for Kenya from 2000 to 2022 using lsqcurvefit algorithm in MATLAB software. The fitting algorithm yielded a mean absolute error (MAE) of 0.0069, demonstrating a close alignment between simulated and observed data. …”
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Model Predictive Control Method for Autonomous Vehicles Using Time-Varying and Non-Uniformly Spaced Horizon by Minsung Kim, Donggil Lee, Joonwoo Ahn, Minsoo Kim, Jaeheung Park

“…This paper proposes an algorithm for path-following and collision avoidance of an autonomous vehicle based on model predictive control (MPC) using time-varying and non-uniformly spaced horizon. …”
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Acne-induced Post-inflammatory Hyperpigmentation: From Grading to Treatment by Nicole Auffret, Marie-Thérèse Leccia, Fabienne Ballanger, Jean Paul Claudel, Serge Dahan, Brigitte Dréno

“…Providing an AI-PIH severity assessment tool as well as preventive and treatment recommendations may help to manage AI-PIH more efficiently. …”
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Measurements and Characterization for Millimeter-Wave Massive MIMO Channel in High-Speed Railway Station Environment at 28 GHz by Shuangde Li, Yuanjian Liu, Leke Lin, Qi Sun

“…And they are processed by using the K-mean algorithm. In addition, propagation characteristics are simulated based on the improved ray tracing method of shooting and bouncing ray tracing/image (SBR/IM). …”
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Exploration of the clinicopathological and prognostic significance of BRCA1 in gastric cancer by Hongrong Zhang, Qi Xu, Hongxing Kan, Yinfeng Yang, Yunquan Cai

“…First, gene expression data for normal and GC tissues were assessed via machine learning and the topological algorithm of CytoHubba, and a total of 792 differentially expressed genes (DEGs) and nine core genes were identified. …”
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A New Support Vector Regression Model for Equipment Health Diagnosis with Small Sample Data Missing and Its Application by Qinming Liu, Wenyi Liu, Jiajian Mei, Guojin Si, Tangbin Xia, Jiarui Quan

“…Actually, it is difficult to obtain a large number of sample data due to equipment failure, and small sample data may also be missing. This paper proposes a novel small sample data missing filling method based on support vector regression (SVR) and genetic algorithm (GA) to improve equipment health diagnosis effect. …”
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Filtering Data of High-Resolution Terrestrial Laser Scanner and Effects of Filtrations on the Landslide Monitoring by Mustafa Zeybek, İsmail Şanlıoğlu, Aşır Genç

“…Point cloud filtering algorithm has automatically obtained two filtered data as the ground and the non-ground. …”
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Using family-based imputation in genome-wide association studies with large complex pedigrees: the Framingham Heart Study. by Ming-Huei Chen, Jie Huang, Wei-Min Chen, Martin G Larson, Caroline S Fox, Ramachandran S Vasan, Sudha Seshadri, Christopher J O'Donnell, Qiong Yang

“…Further examination may be required to generalize this threshold to other studies.…”
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Nowcasting Solar Irradiance Components Using a Vision Transformer and Multimodal Data from All-Sky Images and Meteorological Observations by Onon Bayasgalan, Atsushi Akisawa

“…The proposed architecture is compared against the baselines of the Ineichen clear sky model, a feedforward neural network (FFNN) where cloud coverage is computed from the ASIs by a simple color-channel threshold algorithm, and a hybrid of FFNN and U-Net model, which replaces the color threshold algorithm with fully convolutional layers for cloud segmentation. …”
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