SIMULATION OF STATIC AND DYNAMIC LOSSES IN MOSFET KEYS by V. P. Babenko, V. K. Bityukov, V. V. Kuznetsov, D. S. Simachkov

“…The power of dynamic losses when turning the transistor off does not depend on the gate current. However, this is true only for this scheme, because the discharge of the gate capacitance occurs through a resistor with a fixed value for the key resistance. …”
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Analysis of fault detection and defect categorization in photovoltaic inverters for enhanced reliability and efficiency in large-scale solar energy systems by Malik Stephanie, Daßler David, Patel Dharm, Klute Carola, Klengel Robert, Dietrich Andreas, Kaufmann Kai, Hennig Carsten, Wehnert Danny, Ebert Matthias

“…This study presents a systematic approach for examining the performance and vulnerability of large-scale, grid-connected PV systems in relation to inverter faults − particularly those linked to insulated-gate bipolar transistor (IGBT) component. The focus is on an interdisciplinary approach, utilising methodologies from materials science, data analysis, statistics, and machine learning to investigate defect mechanisms, identify recurring issues, and analyse their impacts for a system portfolio of 64 MWp. …”
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Digital Transformation in African Heritage Preservation: A Digital Twin Framework for a Sustainable Bab Al-Mansour in Meknes City, Morocco by Imane Serbouti, Jérôme Chenal, Saâd Abdesslam Tazi, Ahmad Baik, Mustapha Hakdaoui

“…By utilizing advanced methods for data collection, processing, and analysis, the framework creates a robust data hub for Digital Twin Heritage Buildings (DT_HB). …”
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GTrXL-SAC-Based Path Planning and Obstacle-Aware Control Decision-Making for UAV Autonomous Control by Jingyi Huang, Yujie Cui, Guipeng Xi, Shuangxia Bai, Bo Li, Geng Wang, Evgeny Neretin

“…To address these issues, this paper integrates DRL with the Transformer architecture to propose the GTrXL-SAC (gated Transformer-XL soft actor critic) algorithm. …”
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Deep learning driven prediction and comparative study of surrounding rock deformation in high speed railway tunnels by Zeping Yang, Zhikai Cheng, Da Wu

“…Using 300-hour continuous deformation records from multiple cross-sections of the G Tunnel (March 2023), a novel WOA-CNN-GRU model is developed, integrating data preprocessing, feature extraction, and prediction. …”
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Integration of metaheuristic based feature selection with ensemble representation learning models for privacy aware cyberattack detection in IoT environments by M. Karthikeyan, R. Brindha, Maria Manuel Vianny, V. Vaitheeshwaran, Mrinal Bachute, Sanket Mishra, Bibhuti Bhusan Dash

“…The AMFS-ELPPCD model utilizes the adaptive Harris hawk optimization (AHHO) model for the feature process selection of the subset. Furthermore, ensemble models such as bidirectional gated recurrent unit (BiGRU), Wasserstein autoencoder (WAE), and deep belief network (DBN) are used for the classification process. …”
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Research on event extraction methods for medical by Yuekun MA, Moxiao CUI

“…Secondly, on this basis, dynamic interaction between local and global information was achieved through gating mechanisms to enhance the ability of model to identify argument boundaries. …”
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An Ensemble of Convolutional Neural Networks for Sound Event Detection by Abdinabi Mukhamadiyev, Ilyos Khujayarov, Dilorom Nabieva, Jinsoo Cho

“…The proposed CRNN model integrates spatial and temporal feature extraction by processing these spectrograms through convolution and bi-directional gated recurrent unit (GRU) layers. …”
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DualCMNet: a lightweight dual-branch network for maize variety identification based on multi-modal feature fusion by Xinhua Bi, Hao Xie, Ziyi Song, Jinge Li, Chang Liu, Xiaozhu Zhou, Helong Yu, Chunguang Bi, Ming Zhao

“…Additionally, existing multimodal methods face high computational complexity, making it difficult to balance accuracy and efficiency.MethodsBased on multi-modal data from 11 maize varieties, this paper presents DualCMNet, a novel dual-branch deep learning framework that utilizes a one-dimensional convolutional neural network (1D-CNN) for hyperspectral data processing and a MobileNetV3 network for spatial feature extraction from images. …”
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An Exploratory Assessment of LLMs’ Potential for Flight Trajectory Reconstruction Analysis by Qilei Zhang, John H. Mott

“…Despite these promising outcomes, the study identifies notable limitations, particularly related to model hallucination outputs and token length constraints that restrict the model’s scalability to extended data sequences. Ultimately, this research underscores the substantial potential of LLMs to revolutionize flight trajectory reconstruction and their promising role in time series data processing, opening broader avenues for advanced applications throughout the aviation and transportation sectors.…”
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Improving the prediction of streamflow in large watersheds based on seasonal trend decomposition and vectorized deep learning models by Ningchang Kang, Zhaocai Wang, Anbin Zhang, Hang Chen

“…These components are then modeled independently: long short-term memory (LSTM) and convolutional neural networks (CNN) handle trend and seasonal patterns, while gated recurrent units (GRU) and Transformer process residual fluctuations. …”
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TMFN: a text-based multimodal fusion network with multi-scale feature extraction and unsupervised contrastive learning for multimodal sentiment analysis by Junsong Fu, Youjia Fu, Huixia Xue, Zihao Xu

“…Second, we design a text-based multimodal feature fusion module, which consists of a text gating unit (TGU) and a text-based channel-wise attention transformer (TCAT). …”
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AI-based real-time prediction of cross-sectional phase distribution during laser heat treatment via sequential thermal imaging and image-to-image synthesis by Myeonggyun Son, Hyungson Ki

“…Experimental data were collected from 16 experimental conditions by varying laser power and scanning speed. …”
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SOT-MRAM-based true in-memory computing architecture for approximate multiplication by Min Song, Qilong Tang, Xintong Ouyang, Wei Duan, Yan Xu, Shuai Zhang, Long You

“…An optimized data mapping strategy facilitating bit-serial operations with an extensive degree of parallelism was also adopted. …”
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Calibration of syndrome measurements in a single experiment by Christian Wimmer, Jochen Szangolies, Michael Epping

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Optimized Machine Learning-Augmented Hybrid Empirical Models for AlGaN/GaN HEMTs: A Comprehensive Analysis by Ahmad Khusro, Saddam Husain, Mohammad Hashmi

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Evaluating the impact, implementation experience and political economy of primary care networks in Kenya: protocol for a mixed methods study by Beatrice Amboko, Jacinta Nzinga, Benjamin Tsofa, Peter Mugo, Anita Musiega, Beryl Maritim, Ethan Wong, Caitlin Mazzilli, Wangari Ng’ang’a, Brittany Hagedorn, Gillian Turner, Anne Musuva, Felix Murira, Nirmala Ravishankar, Salim Hussein, Edwine Barasa

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Stakeholder Interviews to Inform Best Practice for Public Facing COVID-19 Wastewater Dashboards [version 2; peer review: 2 approved, 1 approved with reservations] by Tim Rhodes, Daniela Morales, Kathleen M O'Reilly

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Estimated Modern Use: Employing A Service Statistics-Based Indicator to Monitor Family Planning Programs [version 1; peer review: awaiting peer review] by Priya Emmart, Jessica Williamson, Emily Sonneveldt, Margaret Reeves, Kristin Bietsch

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Vaccine decision-making among pregnant women: a protocol for a cross-sectional mixed-method study in Brazil, Ghana, Kenya and Pakistan [version 2; peer review: 1 approved, 2 approv... by Prachi Singh, Jessica L Schue, Emily S Miller, Berhaun Fesshaye, Ruth A Karron, Shanelle Quinn, Maria Laura Costa, Renato T Souza, Kwasi Torpey, Jose Guilherme Cecatti, Emefa Modey, Caroline Dinam Badzi, Ferdinand Okwaro, Chris Guure, Sarah Saleem, Muhammad Asim, Saleem Jessani, Haleema Yasmeen, Sidrah Nausheen, Vanessa Brizuela, Grace Belayneh, Rupali J Limaye, Sami Gottlieb, Marleen Temmerman

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