Study on the Relationship Between Porosity and Mechanical Properties Based on Rock Pore Structure Reconstruction Model by Nan Xiao, Jun-Qing Chen, Xiang Qiu, Fu Huang, Tong-Hua Ling

“…The research workflow incorporated advanced image processing techniques, including adaptive total variation denoising algorithms for CT image enhancement and deep learning-based threshold segmentation for feature extraction. …”
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The Influence of Selected Parameters of the Mathematical Model on the Simulation Performance of a Municipal Waste-to-Energy Plant Absorber by Michał Jurczyk, Marian Banaś, Tadeusz Pająk, Krzysztof Dziedzic, Bogusława Łapczyńska-Kordon, Marcin Jewiarz

“…They will speed up and improve the modelling of chemical processes. The only challenge was to define the chemical reactions and add a calcium molecule to the water droplet model. …”
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Detailed analysis of drift diffusion model parameters estimated for the ultimatum game by Shotaro Numano, Masahiko Haruno

“…While previous research has typically focused on either the choice or response time, a computational approach that integrates both can provide deeper insights into the cognitive and neural processes involved. …”
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MolAttnNet: A Predictive Model for Organic Drug Solubility Based on Graph Convolutional Networks and Transformer-Attention by Chenxu Wang, Yijun Feng, Zhejie Xu, Xiaohui Xu, Bangguo Peng

“…Furthermore, interpretability analysis confirms the model’s reliability in feature extraction and decision-making processes. The proposed framework provides a practical approach for drug solubility prediction and contributes to computational drug discovery methodologies.…”
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Optimization Driven Variational Autoencoder GAN for Artifact Reduction in EEG Signals for Improved Neurological Disorder and Disability Assessment by Sikkandar Mohamed Yacin, Sabarunisha Begum S., Alassaf Ahmad, AlMohimeed Ibrahim, Alhussaini Khalid, Aleid Adham, Alhaidar Abdulrahman Khalid

“…EEG signals are critical for the diagnosis of neurological disorders, for brain-computer interface (BCI) applications, and for the monitoring of neurological disabilities. …”
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DEM calibration insights on the role of particle shape for sub 2 mm particles by Jan Diviš, David Žurovec, Álvaro Ramírez-Gómez, Jakub Hlosta, Jiří Rozbroj, Kamila Pokorná, Jan Nečas, Jiří Zegzulka

“…Results revealed significant differences in flow dynamics, highlighting the enhanced realism of polyhedral models despite increased computational demands. This work provides a comprehensive framework for DEM calibration of fine particulate materials, specifically validated for particle sizes between 400 and 1500 µm, improving simulation accuracy and extending applicability across various industrial processes.…”
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Analysis of air flow formation in a nozzle valve by D. V. Abramkina, A. O. Ivanova, D. F. Karpov, Kh. M. Vafaeva, A. S. Voronov

“…The article examines the results of modeling a nozzle valve with a variable cross-section during its opening and closing processes. Method. The analysis of airflow formation scenarios at various positions of the control diaphragm was performed using Computational Fluid Dynamics (CFD) in the Ansys Fluent software package. …”
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An Advanced Method for Precise ULA SIMO Radar Calibration Utilizing Synthetic Aperture Radar Imaging Artifacts by Michael Braunwarth, Johanna Geiss, Erik Sippel, Martin Vossiek

“…The proposed method leverages the established theory of accumulating channel imbalances in synthetic aperture radar (SAR) processing, enabling the isolation of error power from the desired signal and noise within the image. …”
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Foundation Models and Fine-Tuning: A Benchmark for Out of Distribution Detection by Francesco Cappio Borlino, Lorenzo Lu, Tatiana Tommasi

“…The rise of foundation models is pushing Computer Vision research towards a paradigm shift, in the wake of what already happened in the Natural Language Processing field. …”
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patter: Particle algorithms for animal tracking in R and Julia by Edward Lavender, Andreas Scheidegger, Carlo Albert, Stanisław W. Biber, Janine Illian, James Thorburn, Sophie Smout, Helen Moor

“…Abstract State‐space models are a powerful modelling framework in movement ecology that represents individual movements and the processes connecting movements to observations. However, fitting state‐space models to animal‐tracking data can be difficult and computationally expensive. …”
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Use of Augmented Reality in the Design of Land Facilities Supporting Nuclear-Powered Submarines by Cristiane Lopes Canuto, Rodrigo Toth Reis, Paulo Caixeta de Oliveira, Douglas Brandão Baroni, Thiago Rampim de Marcos, Sad Sandrini Borsoi, Gabriel Nóbile Diniz

“…The study presents an initial application of AR aimed at evaluating the integration and functionality of the proposed setup (computer, AR smart glasses, application, file conversion and transfer processes, etc.). …”
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Modified water balance model for groundwater recharge estimations using cloud integration by Arup Kumar Das, Saurabh Kumar Gupta, Suraj Kumar Singh, Pradeep Kumar Rawat, Shruti Kanga

“…Within MWBM, improvements in groundwater management include the use of remote sensing techniques as well as modernization of computational processes to enhance recharge estimates. …”
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Optimized Application of CGA-SVM in Tight Reservoir Horizontal Well Production Prediction by Chao Wang, Ruogu Wang, Yuhan Lin, Jiafei Zhang, Xiaofei Xie, Zidan Zhao, Yunlin Xu

“…Limited by the number of parameters, the traditional linear fitting method has low computational efficiency and a large error, which brings difficulties to horizontal well production prediction. …”
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A Fast Power Market Clearing Method Based on Active Constraints Identification by Deep Learning by Yunliang WU, Jianxin ZHANG, Bao LI, Peng LI, Zhiyong LI, Xin ZHOU, Yan YANG, Xiaowen LAI

“…Secondly, a deep learning strategy is proposed for identification of active constraint sets, which can provide technical support for deep neural networks to effectively identify the active constraints of SCED from two aspects: feature vector design and efficient processing of the results of deep neural network. Finally, the effectiveness of the proposed method is verified in the IEEE 30 standard test system with renewable energy sources. …”
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Digital fabrication of colors with colloidal crystals and colloidal glasses by Rahul Karyappa, Deepshikha Arora, Tzee Luai Meng, Qiang Zhu, Joel Yang, Hongfei Liu

“…The advent of digital manufacturing, in which additive manufacturing is combined with computer-aided design (CAD), can overcome some of the challenges in fabricating structures from colloidal particles. …”
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Back pain in young people: approaches to diagnosis and treatment by N. A. Shostak, N. G. Pravdyuk, A. V. Novikova

“…The degree of compensation for scoliosis, hereditary abnormalities in the development of the spine, the severity of early degenerative processes, and metabolic diseases of the skeleton that were not identified during school years determine a non-standard scope of diagnostic and therapeutic measures for the doctor. …”
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A staged deep learning approach to spatial refinement in 3D temporal atmospheric transport by M. Giselle Fernández-Godino, Wai Tong Chung, Akshay A. Gowardhan, Matthias Ihme, Qingkai Kong, Donald D. Lucas, Stephen C. Myers

“…However, their high computational cost makes them impractical for applications requiring rapid responses or iterative processes, such as optimization, uncertainty quantification, or inverse modeling. …”
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Channel component correlation analysis for multi-channel EEG feature component extraction by Wenqiang Yan, Wenqiang Yan, Qi Luo, Chenghang Du

“…IntroductionElectroencephalogram (EEG) analysis has shown significant research value for brain disease diagnosis, neuromodulation and brain-computer interface (BCI) application. The analysis and processing of EEG signals is complex since EEG are nonstationary, nonlinear, and often contaminated by intense background noise. …”
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A Lightweight Network for Water Body Segmentation in Agricultural Remote Sensing Using Learnable Kalman Filters and Attention Mechanisms by Dingyi Liao, Jun Sun, Zhiyong Deng, Yudong Zhao, Jiani Zhang, Dinghua Ou

“…However, the spectral noise caused by complex light and shadow interference and water quality differences, combined with the diverse shapes of water bodies and the high computational cost of image processing, severely limits the accuracy of water body recognition in agricultural watersheds. …”
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Application of the Integral Energy Criterion and Neural Network Model for Helicopter Turboshaft Engines’ Vibration Characteristics Analysis by Serhii Vladov, Maryna Bulakh, Denys Baranovskyi, Eduard Kisiliuk, Victoria Vysotska, Maksym Romanov, Jan Czyżewski

“…It averages the assessment of unique signal processing algorithms, which ensures reliable defect classification under flight vibration conditions. …”
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