Study of unusable liquid propellant residues evaporation processes parameters in the tanks of launch vehicle worked-off stage in microgravity by V. I. Trushlyakov, V. A. Urbansky

“…The physical and mathematical model of the liquid evaporation process is based on the first thermodynamics law. …”
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Conv1D-LSTM: Autonomous Breast Cancer Detection Using a One-Dimensional Convolutional Neural Network With Long Short-Term Memory by Mitanshi Rastogi, Meenu Vijarania, Neha Goel, Akshat Agrawal, Cresantus N. Biamba, Celestine Iwendi

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The proteomic landscape of trophoblasts unravels calcium-dependent syncytialization processes and beta-chorionic gonadotropin (ß-hCG) production by Anna-Lena Gehl, Daniel Klawitter, Ulrich Wissenbach, Marnie Cole, Christine Wesely, Heidi Löhr, Petra Weissgerber, Adela Sota, Markus R. Meyer, Claudia Fecher-Trost

“…Methods Here, we combine human trophoblast model cell cultures, hormone assays, antibody-based detection methods and high-resolution mass spectrometry analyzes to assess changes in cellular processes during syncytialization. …”
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Decoding Human Facial Emotions: A Ranking Approach Using Explainable AI by Sudheer Babu Punuri, Sanjay Kumar Kuanar, Tusar Kanti Mishra, Veeranki Venkata Rama Maheswara Rao, Shiva Shankar Reddy

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An optimal operation method for hydrogen refueling stations considering the electric energy-reserve-hydrogen coupling market environment by ZHOU Xin, CHEN Shun, TAN Hong, CHEN Daicai, RAN Menghong

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WTL-CNN: a news text classification method of convolutional neural network based on weighted word embedding by Weidong Zhao, Lin Zhu, Ming Wang, Xiliang Zhang, Jinming Zhang

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Post-Ultraviolet-Curing Process Effects on Low-Velocity Impact Response of 3D Printed Polylactic Acid Parts by Tarkan Akderya

“…The impact behaviour of the specimens produced with production parameters of 200 °C printing temperature, 0.2 mm layer thickness, 50 mm/s printing speed, 100% infill rate, and 45° raster angle was compared with the raw specimens after the post-UV-curing process was applied. …”
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An adaptive deep learning approach based on InBNFus and CNNDen-GRU networks for breast cancer and maternal fetal classification using ultrasound images by Mamuna Fatima, Muhammad Attique Khan, Anwar M. Mirza, Jungpil Shin, Areej Alasiry, Mehrez Marzougui, Jaehyuk Cha, Byoungchol Chang

“…The InBnFUS network combines 5-Blocks inception-based architecture (Model 1) and 5-Blocks inverted bottleneck-based architecture (Model 2) through a depth-wise concatenation layer, while CNNDen-GRU incorporates 5-Blocks dense architecture with an integrated GRU layer. …”
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Collaborative planning of distribution-grid and micro-grid considering bilateral transactions under wind-solar uncertain conditions by Shuzheng WANG, Shouhao WU, Zhi WU, Yuzhu SUN

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Ultra-Reliable and Low-Latency Wireless Hierarchical Federated Learning: Performance Analysis by Haonan Zhang, Peng Xu, Bin Dai

“…However, due to the broadcast nature of wireless communication, the WHFL is susceptible to eavesdropping during the training process. Apart from this, recently ultra-reliable and low-latency communication (URLLC) has received much attention since it serves as a critical communication service in current 5G and upcoming 6G, and this motivates us to study the URLLC-WHFL in the presence of physical layer security (PLS) issue. …”
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Decomposition-Aware Framework for Probabilistic and Flexible Time Series Forecasting in Aerospace Electronic Systems by Yuanhong Mao, Xin Hu, Yulang Xu, Yilin Zhang, Yunan Li, Zixiang Lu, Qiguang Miao

“…This design enables the model to process multiple distinct sequences independently while maintaining the flexibility to learn shared patterns across channels. …”
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Assessing the suitability of the Langevin equation for analyzing measured data through downsampling by Pyei Phyo Lin, Matthias Wächter, Joachim Peinke, M Reza Rahimi Tabar

“…Such non-continuous changes pose a significant challenge for general processes and have profound implications for risk management. …”
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An Improved Deep Learning Model for Electricity Price Forecasting by Rashed Iqbal, Hazlie Mokhlis, Anis Salwa Mohd Khairuddin, Munir Azam Muhammad

“…Hence, this work proposed two-fold contributions which are (1) effective time series preprocessing module to ensure feasible time-series data is fitted in the deep learning model, and (2) an improved long short-term memory (LSTM) model by incorporating linear scaled hyperbolic tangent (LiSHT) layer in the EPF. …”
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DETAILS’ REPAIR OF CONSTRUCTION AND ROAD MACHINES: FLUCTUATIONS’ MODELLING by V. E. Ovsyannikov, V. I. Vasilyev

“…The error doesn’t exceed 20%. The developed model considers geometrical parameters of the tool (a departure, plate corners, etc.), the modes of cutting both mechanical properties of the processed material and parameters of the chip formation. …”
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Deep Learning Model for Analyzing EEG Signal Analysis by Varun Gupta, Vivek Kumar, Prince, Saurabh Singh, Young-Seok Lee, In-Ho Ra

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Use of computer vision analysis for labeling inattention periods in EEG recordings with visual stimuli by Dmitry Yu Isaev, Samantha Major, Kimberly L. H. Carpenter, Jordan Grapel, Zhuoqing Chang, Matias Di Martino, David Carlson, Geraldine Dawson, Guillermo Sapiro

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Insights into structure and activity of a UDP-GlcNAc 2-epimerase involved in secondary cell wall polymer biosynthesis in Paenibacillus alvei by Cordula Stefanović, Max S. G. Legg, Nick Mateyko, Jakob J. Ender, Tea Kuvek, Chris Oostenbrink, Christina Schäffer, Stephen V. Evans, Fiona F. Hager-Mair

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Laser transformation hardening effect on hardening zone features and surface hardness of tool steel AISI D2 by D. Lesyk, V. Dzhemelinskyi, S. Martinez, А. Lamikiz, О. Dаnylеikо, V. Hyzhevskyi

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DermaTransNet: Where Transformer Attention Meets U-Net for Skin Image Segmentation by Anum Abdul Salam, Muhammad Usman Akram, Muhammad Haroon Yousaf, Babar Rao

“…To enhance the efficacy of analysis and assist pathologists, computer-aided diagnostic systems have been proposed to automate the process of disease detection and classification. A crucial initial step in skin disease diagnosis is the accurate segmentation of skin layers, as it facilitates the identification of regions of interest for subsequent processing. …”
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GDPR and Large Language Models: Technical and Legal Obstacles by Georgios Feretzakis, Evangelia Vagena, Konstantinos Kalodanis, Paraskevi Peristera, Dimitris Kalles, Athanasios Anastasiou

“…Large Language Models (LLMs) have revolutionized natural language processing but present significant technical and legal challenges when confronted with the General Data Protection Regulation (GDPR). …”
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