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

“…The participation of good nodes in the consensus and the removal of faulty nodes were ensured by the credit score model. The parallelism of transaction verification and read write operations was achieved through the implementation of a double layer architecture. …”
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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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NUMERICAL MODELING OF THE CINDER FORMATION PROCESS WITH APPLICATION OF SYMMETRICAL IMPLICIT SCHEMA IN MOVING HEATED INGOT OF CHROMIUM STEEL by A. N. Chichko, A. S. Borozdin

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Recognition of Industrial Spare Parts Using an Optimized Convolutional Neural Network Model by Chandralekha Mohan, Takfarinas Saber, Priyadharshini Jayadurga Nallathambi

“…In this article, a novel Deep Learning-based object recognition model based on a convolutional neural network architecture is proposed and constructed using stacked convolutional layers to extract and learn features of the spare parts efficiently with the goal of improving the effectiveness of the spare part image recognition process. …”
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Characterization and modeling of laser transmission welded polyetherketoneketone (PEKK) joints: Influence of process parameters and annealing on weld properties by Marcela Matus-Aguirre, Benoît Cosson, Christian Garnier, Fabrice Schmidt, André Chateau Akué-Asséko, France Chabert

“…The depths of the molten layer (ML) and semi-crystalline layer (scL) vary with laser power and assembly type. …”
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Simulation of Drying‐Rewetting Processes in Numerical Groundwater Models Using a New Picard Iteration‐Based Method by Chuiyu Lu, Wen Lu, Qingyan Sun, Xin He, Lingjia Yan, Tao Qin, Chu Wu, Shangqi Han, Zhenjiang Wu, Weichen Wu

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Knot-TPP: A Unified Deep Learning Model for Process Incidence and Tool Wear Monitoring in Stacked Drilling by Jiduo Zhang, Robert Heinemann, Otto Jan Bakker

“…This study proposed a knot–Temporal Pyramid Pooling (TPP) model aimed at monitoring both process incidences and tool wear in the drilling of hybrid stacks, which subsequently informs the machine tool to adjust cutting parameters or, if necessary, replaces the tool. …”
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Influence of the design concept of an experimental demonstration model of a rocket design element on the process of heat and mass transfer by V. I. Trushlyakov, Yu. V. Surikova, D. Yu. Davydovich

“…A conceptual design of an experimental demonstration model of three-layer structure of a launch vehicle body is proposed, based on the replacement of aluminum honeycomb filler with an energy-related material, in particular, based on composite solid rocket propellants. …”
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ATT-BLKAN: A Hybrid Deep Learning Model Combining Attention is Used to Enhance Business Process Prediction by Junyi Xu, Xianwen Fang

“…This is achieved by enhancing the BiLSTM model’s ability to capture long-term dependencies through the addition of Agent Attention, while utilising KAN in place of the traditional Multi-Layer Perceptron (MLP) to improve prediction performance and mechanism interpretability. …”
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Oxidative Dissolution of Sulfide Minerals in Porous Media Under Evaporative Conditions: Multiphase Experiments and Process‐Based Modeling by Navid Ahmadi, Muhammad Muniruzzaman, Jacopo Cogorno, Massimo Rolle

“…We investigate the oxidative dissolution of pyrite under evaporative conditions and advance a mechanistic understanding of the interactions between multiple physical processes and mineral/surface reactions. We performed a set of experiments in which initially water saturated and anoxic soil columns, containing a top layer of pyrite, are exposed to the atmosphere under no evaporation (single‐phase) and natural evaporative (two‐phase) conditions. …”
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Establishment of a Numerical Model and Process Optimization for the Moving Induction Hardening of a Whole-Roll Flatness Roll by Huaxin Yu, Shuang Liao, Zhichao Li, Ziwei Xu, Shan Li

“…The calculated hardness value of the roll surface in the simulation model reaches 950 HV, which agrees well with the experimental hardness results, validating the ability of the numerical model to guide specific processes.…”
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A stacked ensemble model for traffic conflict prediction using emerging sensor data by Bowen Cai, Léah Camarcat, Nicolette Formosa, Mohammed Quddus

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A Multi-Architecture Approach for Offensive Language Identification Combining Classical Natural Language Processing and BERT-Variant Models by Ashok Yadav, Farrukh Aslam Khan, Vrijendra Singh

“…We also propose an architecture that utilizes advanced transformer models such as BERT, ALBERT, and ELECTRA for pre-processing and encoding, with 1D CNN and neural network layers serving as the classification components. …”
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Hybrid physical model and status data-driven approach for quality-reliable digital light processing 3D printing by Lidong Zhao, Xueyun Zhang, Zhi Zhao, Limin Ma, Lifang Wu

“…Analyzing the collected data provides both status and anomaly information, enabling in-situ repair strategies to address abnormalities with minimal disruption to the printing process. Additionally, an Extended Kalman Filter integrates status data with physical models to dynamically optimise printing parameters. …”
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TSAS—YOLOv8: An Optimization Detection Model for Capturing Small Target Features and Processing Key Information by Yongbo Yuan, Linlin Cao

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Evaluation of processes driving iodine monoxide and ozone variability over the Western Pacific warm pool by Takashi Sekiya, Hisashiro Takashima, Yugo Kanaya, Fumikazu Taketani, Kengo Sudo, Martina M. Friedrich, Michel Van Roozendael

“…The impact of iodine has been extensively studied using three-dimensional chemical transport models (CTMs). However, the factors governing the variability of iodine monoxide (IO) and ozone in the marine boundary layer (MBL) remain uncertain. …”
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TECHNIQUE OF DESIGNING OF TECHNOLOGICAL PROCESSES OF CENTRIFUGAL PROCESSING by Yu.A. PROSKORJAKOVA

“…Article is devoted to research of process of centrifugal processing. Theoretical models are developed for definition of an average arithmetic deviation of a structure of the established roughness, depth of the strengthened layer and a degree of hardening. …”
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Modelling of elastoviscoplastic properties of the subgrade. Problem statement 2 by V. M. Bel’Kov

“…Research of railway embankments in terms of physical and chemical mechanics were conducted discretely, without the creation of a coherent model of stability of layered systems, taking into account all the determining factors. …”
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Modelagem da infiltração em solos com encrostamento superficial. Parte I: modelo GAML para solos estratificados Modelling of the soil water infiltration in crusting soil. Part I: G... by João H. Zonta, Mauro A. Martinez, Fernando F. Pruski, Demetrius D. da Silva, Marcelo R. dos Santos

“…<br>ABSTRACT The aim of this study was to evaluate the Green-Ampt-Mein-Larson (GAML) model and GAML model modified by Moore (1981) for layered soils, in the simulation of water infiltration process in crusting soil. …”
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