Mine pressure prediction based on empirical mode decomposition linear model by Yuwei ZHU, Pengfei WANG, Huixian WANG, Qiangqiang NIU, Liang XIN

“…To ensure the safe and efficient extraction of coal mines and reduce sudden roof accidents, this study proposes a novel multivariate long-term sequence mine pressure prediction model—the Empirical Mode Decomposition Linear Model (EMD–Mixer). …”
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SPICE-Compatible Degradation Modeling Framework for TDDB and LER Effects in Advanced Packaging BEOL Based on Ion Migration Mechanism by Shao-Chun Zhang, Sen-Sen Li, Ying Ji, Ning Yang, Yuan-Hao Shan, Li Hong, Hao-Gang Wang, Wen-Sheng Zhao, Da-Wei Wang

“…The proposed model is rooted in the fundamental physics of metal ion migration and the evolution of conductive filaments (CFs) within the dielectric layer under operational stress conditions. …”
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Application of the mathematical modeling of the processes of geofiltration and geomigration at the deposits of mineral waters of IV group of complexity (Kislovodsk deposits of mine... by A. V. Malkov, I. S. Pomelyayko, V. F. Dubogrey, V. V. Khmel

“…On the basis of geological and hydrogeological characteristics of the structure, a three-layer flat-spatial model of geofiltration is proposed, including top layer of pressure-gravity aquifer of Upper Valanginian subhorizon and two pressure ones: Lower Valanginian subhorizon and Tithonian horizon. …”
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Comparative Analysis of Hybrid Attention and Progressive Layering Through a Comprehensive Evaluation of ARU-Net and PLU-Net in Brain Tumour Segmentation by Noman Ahmed Siddiqui, Muhammad Tahir Qadri, Muhammad Ovais Akhter, Tahira Anwar, Fahad Farooq

“…The current study is an in-depth comparative study of two different deep-learning models the Novel Hybrid Channel Attention Regression U-Net (ARU-Net) and Progressive Layered U-Net (PLU-Net) that build on the U-Net architecture as an enhancement to increase the segmentation accuracy of the BraTS 2021 dataset with respect to the T1, T1ce, T2, and FLAIR modalities. …”
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Study on Optimization of Rice-Drying Process Parameters and Directional Regulation of Nutrient Quality by Jinquan Li, Kezhen Chang, Jun Yin, Yi Jin, Xiaokang Yi, Zhongjie Zhang, Yichuan He, Qiaonan Yang, Zhihui Tang, Xiaoyu Liu, Wenfu Wu

“…The relationship between each factor and nutrient quality was revealed through response surface analysis, and the regression model and process optimization parameters were established. …”
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Enhancing dental model accuracy through optimized vat photopolymerization additive manufacturing parameters by Clément Tien, Camille Jean, Lucas Poupaud, Floriane Laverne, Frédéric Segonds

“…This study investigates the key additive manufacturing (AM) process parameters that influence the dimensional accuracy of dental models produced using the vat photopolymerization Digital Light Processing (DLP) technology. …”
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Investigation into the role of layered nanoporous modified clays for adsorption/desorption of rosemary essential oil in the gas phase and the ability of this system as an antioxida... by Doha Berraaouan, Mohamed Tirinsi, Ramzi A. Mothana, Hanan M. Al-Yousef, Marie-Laure Fauconnier, Samira Salhi, Abdesselam Tahani

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Crucial heat damage analysis and optimization of a mid-sized pickup truck based on a deep Gaussian process model by Zebin Zhang, Sisi Liu, Xianzong Meng, Tingting Wang, Shizhao Jing, Chuanrui Wang, Dongchen Qin

“…Based on simulation results, a multi-objective two-layer deep Gaussian process model predicted heat source temperatures. …”
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Modeling and Efficiency Analysis of an Immersed Heat Exchanger for Solar-Powered Industrial Heat Processes: A Case Study on Wool Washing by Messaoud Hazmoune, Mohammed Debbache, Mohammed Gmal Osman, Benaoumeur Aour, Cornel Panait, Mohammed Laissaoui, Gheorghe Lazaroiu

“…Numerical simulations were performed using ANSYS CFX v19.2 software with the k-ε turbulence model to evaluate the thermal performance and temperature distribution. …”
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Interfacial processes of Mg anodes for magnesium-sulfur batteries: An EIS study by Joachim Häcker, Tobias Rommel, Pia Lange, Felix Kampmann, Jürgen Remmlinger, Zhirong Zhao-Karger, K. Andreas Friedrich, Maryam Nojabaee

“…In contrast, the sulfur species significantly influence the impedance response by altering the surface layer composition. By systematic process assignment of the gained spectra in Mg|Mg and Mg|S cells, specific equivalent circuit models for different anodes and cell conditions are derived. …”
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SIMULATING MACHINING OF CONTINUOUSLY VARIABLE TRANSMISSION PULLEYS IN COMPLEX BLADE TOOL TRAJECTORY IN ANSYS SOFTWARE PACKAGE by A.A. Generalova, A.A. Nikulin, D.S. Bychkov

“…The purpose of the study is to develop a computer model for complex spatial movement of a cutting tool, which makes it possible to study the stress-strain and thermal state of the cutting process, chip formation conditions, predict the quality parameters of the surface layer, and also take into account the characteristics of the workpiece and the cutting tool, with the subsequent possibility of parameterizing the process. …”

TrBot: A Turkish Deep Learning Chatbot Utilizing Seq2Seq Model by Bilal Babayigit, Habibelahi Rahmani, Mohammed Abubaker

“…This study presents TrBot, a general-purpose Turkish chatbot that utilizes deep learning techniques, specifically a seq2seq model with Long Short-Term Memory (LSTM) layers. …”
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Using the LTO Network Level 1 Blockchain to Automate Inter-Organizational Business Processes by Khrypko Serhii L., Shcherbakov Serhii S.

“…The article is devoted to the consideration of blockchain technology as a means of automating inter-organizational business processes. It is noted that the digitalization and automation of internal business processes bring significant benefits in terms of increasing productivity and reducing costs. …”
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Regression Model Employing Spiking Neural Network for Bio-Signal Analysis With Hardware Integration by Choongseop Lee, Geunbo Yang, Jaewoo Baek, Yuntae Park, Mingyu Cheon, Jongkil Park, Cheolsoo Park

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Convolutional networks can model the functional modulation of the MEG responses associated with feed-forward processes during visual word recognition by Marijn van Vliet, Oona Rinkinen, Takao Shimizu, Anni-Mari Niskanen, Barry Devereux, Riitta Salmelin

“…Traditional models of reading lack a realistic simulation of the early visual processing stages, taking input in the form of letter banks and predefined line segments, making them unsuitable for modeling early brain responses. …”
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Introducing a volume change function in process-based modelling of soil development due to land management: A proof of concept by Hamza Chaif, Saba Keyvanshokouhi, Peter Finke, Cédric Nouguier, Nicolas Moitrier, Nicolas Beudez, Sophie Cornu

“…Most process-based models of soil development with explicit water transfer are based on an assumption of constant soil volume over time. …”
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Two-layer asynchronous distributed optimal voltage control for VSC-HVDC-connected large-scale wind farm clusters by Fuyan Liu, Feifan Shen, Pan Hu, HeSong Cui, Sheng Huang, Ji Zhang, Xia Ma, Kun He

“…This study proposes a two-layer asynchronous distributed optimal voltage control (TADOVC) scheme for voltage source converter high voltage direct current (VSC-HVDC)-connected large-scale wind farm clusters (WFCs). …”
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An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures by Andrzej D. Dobrzycki, Ana M. Bernardos, José R. Casar

“…This research addresses this gap by presenting a detailed analysis of layer-freezing strategies. We systematically investigate multiple freezing configurations across YOLOv8 and YOLOv10 variants using four challenging datasets that represent critical infrastructure monitoring. …”
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Modulation of X-Ray Flux by Obscuration of Neutron Star Boundary Layer by G. Török, K. Klimovičová, D. Lančová, M. Matuszková, E. Šrámková, M. Urbanec, M. Čemeljić, R. Šprňa, V. Karas

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Blockchain efficient Byzantine fault tolerance consensus algorithm for IIoT by LI Fengqi, SONG Qingqing, XU Hui, DU Xuefeng, GAO Jialong, TONG Ning, WANG Deguang

“…Considering the malicious risks associated with diverse terminals in the industrial Internet of things (IIoT), a practical Byzantine fault tolerant (PBFT) efficient consensus algorithm based on credit score and dynamic double layer (CD-PBFT) was proposed to meet the requirements of high efficiency and security fault tolerance in the consensus process. …”
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