Combining protective clothes with human body models for finite element ballistic impact simulations by Matthias Boljen, Marcin Jenerowicz, Steffen Bauer, Elmar Straßburger

“… The ballistic deformation of an ultra-high-molecular-weight (UHMW) polyethylene (PE) composite has been subjected numerically to a multi-layered soft ballistic fabric package modelled upon the body contours of the Global Human Body Models Consortium (GHBMC) human body models M50-P and F05-P. …”
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Combining protective clothes with human body models for finite element ballistic impact simulations by Matthias Boljen, Marcin Jenerowicz, Steffen Bauer, Elmar Straßburger

“… The ballistic deformation of an ultra-high-molecular-weight (UHMW) polyethylene (PE) composite has been subjected numerically to a multi-layered soft ballistic fabric package modelled upon the body contours of the Global Human Body Models Consortium (GHBMC) human body models M50-P and F05-P. …”
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Combining protective clothes with human body models for finite element ballistic impact simulations by Matthias Boljen, Marcin Jenerowicz, Steffen Bauer, Elmar Straßburger

“… The ballistic deformation of an ultra-high-molecular-weight (UHMW) polyethylene (PE) composite has been subjected numerically to a multi-layered soft ballistic fabric package modelled upon the body contours of the Global Human Body Models Consortium (GHBMC) human body models M50-P and F05-P. …”
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Combining protective clothes with human body models for finite element ballistic impact simulations by Matthias Boljen, Marcin Jenerowicz, Steffen Bauer, Elmar Straßburger

“…The ballistic deformation of an ultra-high-molecular-weight (UHMW) polyethylene (PE) composite has been subjected numerically to a multi-layered soft ballistic fabric package modelled upon the body contours of the Global Human Body Models Consortium (GHBMC) human body models M50-P and F05-P. …”
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Performance Comparison of Prediction of Hydraulic Jump Length Under Multiple Neural Network Models by Ziyuan Xu, Zirui Liu, Yingzi Peng

“…We utilized a multi-task learning strategy, incorporating a shared feature extraction layer for characteristic modeling of hydraulic jumps within Physics-Informed Neural Networks (PINNs). …”
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Stratification and overturning circulation are intertwined controls on ocean heat uptake efficiency in climate models by L. Vogt, L. Vogt, J.-B. Sallée, C. de Lavergne

“…Despite the importance of OHUE, there remain substantial uncertainties concerning the physical mechanisms controlling its magnitude in global climate model simulations: ocean mixed-layer depth, Atlantic Meridional Overturning Circulation (AMOC) strength, and upper-ocean stratification strength have all been previously proposed as controlling factors.…”
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End-to-End Detector Optimization with Diffusion Models: A Case Study in Sampling Calorimeters by Kylian Schmidt, Krishna Nikhil Kota, Jan Kieseler, Andrea De Vita, Markus Klute, Abhishek, Max Aehle, Muhammad Awais, Alessandro Breccia, Riccardo Carroccio, Long Chen, Tommaso Dorigo, Nicolas R. Gauger, Enrico Lupi, Federico Nardi, Xuan Tung Nguyen, Fredrik Sandin, Joseph Willmore, Pietro Vischia

“…Our results demonstrate that the diffusion model effectively captures critical performance metrics for calorimeter design, guiding the automatic search for a layer arrangement and material composition that align with known calorimeter principles. …”
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High quality large‐scale nickel‐rich layered oxides precursor co‐precipitation via domain adaptation‐based machine learning by Junyoung Seo, Taekyeong Kim, Kisung You, Youngmin Moon, Jina Bang, Waunsoo Kim, Il Jeon, Im Doo Jung

“…Our domain adaptation based machine learning model, which accounts for equipment wear and environmental variations, achieves a defect detection accuracy of 97.8% based on machine data and process conditions. …”
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Superlubricating electrical contact between graphite layers by Yanmin Liu, Dong Wang, Ke Zhang, Haijun Wu, Guoqing Yu, Qiang Zhang, Yuanzi Zhou, Tianbao Ma, Aisheng Song

“…On the basis of the electronic property fluctuation (EPF) model and first principles calculations, we revealed that the sliding energy barrier remains almost unchanged under an applied current because of the negligible electron transfer variation during the sliding process. …”
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In situ vertical observations of the layered structure of air pollution in a continental high-latitude urban boundary layer during winter by R. Pohorsky, A. Baccarini, A. Baccarini, N. Brett, B. Barret, S. Bekki, G. Pappaccogli, E. Dieudonné, B. Temime-Roussel, B. D'Anna, M. Cesler-Maloney, A. Donateo, S. Decesari, K. S. Law, W. R. Simpson, J. Fochesatto, S. R. Arnold, J. Schmale

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Retinal Nerve Fiber Layer and Macular Ganglion Cell Layer Thickness in Subjects Suffering from Diabetes Mellitus: An Observational Study by Anujja Gharat, Nayana Anil Potdar, Salma Mohd Iqbal Tabani, Burhanuddin Kaidjoher Fakhri, Darshana B. Rathod, Twinkle Choksi

“…Purpose: The purpose of this study was to investigate the relationship of retinal nerve fiber layer (RNFL) and ganglion cell–inner plexiform layer (GCIPL) thickness in between normal healthy eyes and those affected by diabetes mellitus (DM) and also associate it with the extent of the disease. …”
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Exploring Decentralized Warehouse Management Using Large Language Models: A Proof of Concept by Tomaž Berlec, Marko Corn, Sergej Varljen, Primož Podržaj

“…This paper presents a novel approach to decentralized warehouse management integrating Large Language Models (LLMs) into the decision-making processes of autonomous agents, which serves as a proof of concept for shared manufacturing. …”
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Physiological signal-based mental stress detection using hybrid deep learning models by Nandini Modi, Yogesh Kumar, Kapil Mehta, Neelam Chaplot

“…These spectrograms are then processed by CNN layers to extract spatial patterns, followed by MLP layers for mental stress state classification. …”
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Canopy Temperature Estimation Using Gene Expression Programming Models and Artificial Neural Networks by Mehri Saeidinia, AmirHameh Haghiabi

“…The MLP models outperformed GEP models during the training and testing processes. …”
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A Novel Method for 3D Lung Tumor Reconstruction Using Generative Models by Hamidreza Najafi, Kimia Savoji, Marzieh Mirzaeibonehkhater, Seyed Vahid Moravvej, Roohallah Alizadehsani, Siamak Pedrammehr

“…We introduce a second GAN model with a novel loss function that significantly improves tumor detection accuracy. …”
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Beyond Classical AI: Detecting Fake News with Hybrid Quantum Neural Networks by Volkan Altıntaş

“…The model integrates classical fully connected neural layers with a parameterized quantum circuit, enabling the processing of textual data within both classical and quantum computational domains. …”
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Enhancing Sentiment Analysis with a CNN-Stacked LSTM Hybrid Model by Shao Shuaijie

“…This model uses CNN for its advantage of capturing local features in the sequence after the embedding process, and LSTM for its advantage of capturing long-term dependencies in such sequential data after CNN layer. …”
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GPU-Based Implementation of Pruned Artificial Neural Networks for Digital Predistortion Linearization of Wideband Power Amplifiers by Wantao Li, Raul Criado, William Thompson, Gabriel Montoro, Kevin Chuang, Pere L. Gilabert

“…The proposed pruning method is applied to the first hidden layer of a feed-forward real-valued time-delay neural network, commonly used for DPD purposes. …”
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DeSPPNet: A Multiscale Deep Learning Model for Cardiac Segmentation by Elizar Elizar, Rusdha Muharar, Mohd Asyraf Zulkifley

“…By processing features at different spatial resolutions, the multiscale densely connected layer in the form of the Pyramid Pooling Dense Module (PPDM) helps the network to capture both local and global context, preserving finer details of the cardiac structure while also capturing the broader context required to accurately segment larger cardiac structures. …”
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Analysis of argument structure constructions in a deep recurrent language model by Pegah Ramezani, Pegah Ramezani, Achim Schilling, Achim Schilling, Patrick Krauss, Patrick Krauss

“…In future work, we plan to compare these model-derived representations with neuroimaging data from continuous speech perception, further bridging computational and biological perspectives on language processing.…”
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