Structural Component Identification and Damage Localization of Civil Infrastructure Using Semantic Segmentation by Piotr Tauzowski, Mariusz Ostrowski, Dominik Bogucki, Piotr Jarosik, Bartłomiej Błachowski

“…Therefore, automating this process is highly attractive, which has received significant attention in recent years. …”
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Emotion Recognition from EEG Signals Using Advanced Transformations and Deep Learning by Jonathan Axel Cruz-Vazquez, Jesús Yaljá Montiel-Pérez, Rodolfo Romero-Herrera, Elsa Rubio-Espino

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Determining of Treatment Tactic and Planning of Atypical Removal of Asymptomatic and Without Any Pathological Changes Impacted Mandibular Third Molars by Vares Y., Kyyak S.

“…Detailed diagnostic and operation planning with the help of computer program considerably simplify operation process and reduce the intra- and postoperative complications.…”
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Real-Time Object Detector for Medical Diagnostics (RTMDet): A High-Performance Deep Learning Model for Brain Tumor Diagnosis by Sanjar Bakhtiyorov, Sabina Umirzakova, Musabek Musaev, Akmalbek Abdusalomov, Taeg Keun Whangbo

“…The integration of deep learning technologies in medical diagnostics has improved the accuracy and efficiency of these processes, yet real-time processing remains a challenge due to the computational intensity of current models. …”
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Analyzing the maxillary sinuses using 3D-modeling by O. V. Zeleva, A. V. Kolsanov, P. M. Zel'ter, E. A. Sidorov

“…The study of the anatomy of the maxillary sinuses using computed tomography (CT) techniques is an important area of scientific research. …”
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An effective algorithm to identify the miscibility gap in a binary substitutional solution phase by Fu T., Du Y., Zheng Z.-S., Peng Y.-B., Jin B., Liu Y.-B, Du C.-F., Liu S.-H., Shi C.-Y., Wang J.

“…The Al-Zn and Al-In phase diagrams are computed by using a home-made code to verify the efficiency of these techniques. …”
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Thematic marking of the anthropological corpus: a methodology for classifying miners’ narratives by L. L. Mazitova, L. M. Panteleeva

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A machine learning strategy for the identification of key in silico descriptors and prediction models for IgG monoclonal antibody developability properties by Andrew B. Waight, David Prihoda, Rojan Shrestha, Kevin Metcalf, Marc Bailly, Marco Ancona, Talal Widatalla, Zachary Rollins, Alan C Cheng, Danny A. Bitton, Laurence Fayadat-Dilman

“…Identification of favorable biophysical properties for protein therapeutics as part of developability assessment is a crucial part of the preclinical development process. Successful prediction of such properties and bioassay results from calculated in silico features has potential to reduce the time and cost of delivering clinical-grade material to patients, but nevertheless has remained an ongoing challenge to the field. …”
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Wire coating in eccentric geometry with fluid and solid interaction using 3D simulation by CFD by Kriengkrai Nabudda, Ninart Booprempree, Wirote Ritthong, Kridtapas Cheyaksorn, Sontinan Intasonti, Pongthep Poungthong

“…Wire coating processes are fundamental to the production of high-performance insulated wires, where precise regulation of resin flow and thermal behaviour is imperative to achieving uniform coatings. …”
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Study on Key Parameter Range for Curie Point Passive Shutdown Device Based on Integrated Fast Reactor by LI Xinyu, ZHANG Xisi, XUE Fangyuan, LIU Yizhe

“…In order to ensure timely and effective reactor shutdown, these parameters were essential in the non-dynamic shutdown process and played a crucial role. In this paper, a advanced computational fluid dynamics (CFD) software was used to ensured that unintentional rod ejection during routine reactor operations was avoided. …”
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Extracting Features from Oblique Ground-Based Multispectral Images for Monitoring Cotton Physiological Response to Nitrogen Treatments by Vaishali Swaminathan, J. Alex Thomasson, Nithya Rajan, Robert G. Hardin

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Machine learning-enhanced fully coupled fluid–solid interaction models for proppant dynamics in hydraulic fractures by Dennis Delali Kwesi Wayo, Sonny Irawan, Lei Wang, Leonardo Goliatt

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Improving long‐tail classification via decoupling and regularisation by Shuzheng Gao, Chaozheng Wang, Cuiyun Gao, Wenjian Luo, Peiyi Han, Qing Liao, Guandong Xu

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A Complete System for Automated Semantic–Geometric Mapping of Corrosion in Industrial Environments by Rui Pimentel de Figueiredo, Stefan Nordborg Eriksen, Ignacio Rodriguez, Simon Bøgh

“…Corrosion, a naturally occurring process leading to the deterioration of metallic materials, demands diligent detection for quality control and the preservation of metal-based objects, especially within industrial contexts. …”
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Cognitive «portrait» of children with mental retardation by T. S. Kaminskaya, L. G. Khachatryan, E. V. Kasanave, I. V. Kaminskiy

“…The form of testing makes it possible to more effectively keep patients' attention on completing tasks than when using paper media in the process of neuropsychological examination on the computer psychophysiological complex «Psychomat-99». …”
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Use of Multimodal Artificial Intelligence in Surgical Instrument Recognition by Syed Ali Haider, Olivia A. Ho, Sahar Borna, Cesar A. Gomez-Cabello, Sophia M. Pressman, Dave Cole, Ajai Sehgal, Bradley C. Leibovich, Antonio Jorge Forte

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Mathematical modeling of the effect of stent construction during endoluminal IRE for recanalization of an occluded metal stent by Peter Matkulcik, Martin Hemzal, Tomas Rohan, Dalibor Cervinka, Veronika Novotna, Shraga Nahum Goldberg, Tomas Andrasina

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Constrained Federated Learning for AoI-Limited SFC in UAV-Aided MEC for Smart Agriculture by Mohammad Akbari, Aisha Syed, W. Sean Kennedy, Melike Erol-Kantarci

“…Many IoT devices can be deployed for precision farming, soil management, automated irritation, information gathering, or performing some local processing to provide various services. Due to the computational capacity limitation of IoT devices and their limited power, UAV-aided mobile-edge computing (MEC) is proposed to provide IoT nodes with additional resources by hosting their computation functions and making smart agriculture use cases more operational. …”
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A radiomics-based interpretable machine learning model to predict the HER2 status in bladder cancer: a multicenter study by Zongjie Wei, Xuesong Bai, Yingjie Xv, Shao-Hao Chen, Siwen Yin, Yang Li, Fajin Lv, Mingzhao Xiao, Yongpeng Xie

“…Abstract Objective To develop a computed tomography (CT) radiomics-based interpretable machine learning (ML) model to preoperatively predict human epidermal growth factor receptor 2 (HER2) status in bladder cancer (BCa) with multicenter validation. …”
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Experimental Investigation of Iterative Pseudoinverse Ghost Imaging by Xiaofeng Lv, Shuxu Guo, Chenglong Wang, Chao Yang, Hongwei Zhang, Junfeng Song, Wenlin Gong, Fengli Gao

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