Multi-Timescale Energy Consumption Management in Smart Buildings Using Hybrid Deep Artificial Neural Networks by Favour Ibude, Abayomi Otebolaku, Jude E. Ameh, Augustine Ikpehai

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A Comprehensive Analysis of Losses and Efficiency in a Buck ZCS Quasi-Resonant DC/DC Converter by Nikolay Hinov, Tsvetana Grigorova

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Design and Analysis of an Ultra-Wideband High-Precision Active Phase Shifter in 0.18 μm SiGe BiCMOS Technology by Hao Jiang, Zenglong Zhao, Nengxu Zhu, Fanyi Meng

“…This paper presents an active phase shifter for phased array system applications, implemented using 0.18 μm SiGe BiCMOS technology. …”
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A Comparative Study of Electric Vehicles Battery State of Charge Estimation Based on Machine Learning and Real Driving Data by Salma Ariche, Zakaria Boulghasoul, Abdelhafid El Ouardi, Abdelhadi Elbacha, Abdelouahed Tajer, Stéphane Espié

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High-speed aerated jet trajectory simulated by compounding method of Euler-Euler model and meshless SPH method by Junling He, Qingzhi Hou, Jijian Lian, Wenxiao Jia, Panhong Ren

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Efficient neural network training method for unsteady flow field prediction based on data pool by Qiuchi Min, Tianyu Li, Guanxiong Li, Shuyuan Liu, Laiping Zhang, Xiaogang Deng

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Optimisation investigation on hybrid battery thermal management system for electric aircraft based on genetic algorithm by Yuzhuo Wang, Qing Guo, Zhijie Zhou, Haodi Li, Dexiao Ma

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Thermal runaway and flame propagation in battery packs: numerical simulation and deep learning prediction by Zilong Wang, Hosein Sadeghi, Xinyan Huang, Francesco Restuccia

“…The widespread application of lithium-ion battery technology faces a significant challenge from the inherent risk of thermal runaway and consequent fire spread. …”
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A novel graph modeling method for GNN-based hypersonic aircraft flow field reconstruction by Qiao Li, Xingchen Li, Xiaoqian Chen, Wen Yao

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Determining the Strength of Structural Materials by Solving Inverse Problems of Thermoelasticity by Natalia A. Guk, Yurii M. Matsevity, Volodymyr O. Povhorodnii, Mykola O. Safonov

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Disturbance Robust Generalized Predictive Control Applied to an EV Charger Grid Converter by Jefferson S. Costa, Angelo Lunard, Luis F. Normandia Lourenco, Lucas Rodrigues, Alfeu J. Sguarezi Filho

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Interpretable Deep Learning Model for Grape Leaf Disease Classification Based on EfficientNet with Grad-CAM Visualization by Castaka Agus Sugianto, Dini Rohmayani, Jhoanne Fredricka, Mohamed Doheir

“…Traditional manual inspection methods are inefficient and prone to human error, highlighting the need for an automated approach. …”
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Automatic differential kinematics of serial manipulator robots through dual numbers by Luis Antonio Orbegoso Moreno, Edgar David Valverde Ramírez

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Efficient and generalizable nested Fourier-DeepONet for three-dimensional geological carbon sequestration by Jonathan E. Lee, Min Zhu, Ziqiao Xi, Kun Wang, Yanhua O. Yuan, Lu Lu

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Blast loading prediction in a typical urban environment based on Bayesian deep learning by Weiwen Peng, Meilin Pan, Chunjiang Leng, Shufei Wang, Wei Zhong

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Chamber shape optimization for ultra-high-pressure water-jet nozzle based on computational fluid dynamics method and a data-driven surrogate model by Wen-Tao Zhao, Zheng-Shou Chen, Yuan-Jie Chen, Jiang-Long Li

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Modelling flame-to-fuel heat transfer by deep learning and fire images by Caiyi Xiong, Zilong Wang, Xinyan Huang

“…Results show that the proposed AI algorithm trained by flame images can predict both the convective and radiative heat flux distributions on the condensed fuel surface with a relative error below 20%, based on the input of real-time flame morphology that can be captured by a larger grid size. …”
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Monitoring water quality parameters using multi-source data-driven machine learning models by Yubo Zhao, Mo Chen, Jinyu He, Yanping Ma

“…A machine learning model (CNN-RF) was developed to estimate three water quality parameters (TP, DO, COD), and its performance was comprehensively evaluated using four error indices (R², MAE, MSE, MAPE). The results indicated that, compared to models using only spectral reflectance as features, the inclusion of environmental factors significantly enhanced the accuracy of the inversion of the three water quality parameters. …”
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Machine Learning Using Approximate Computing by Padmanabhan Balasubramanian, Syed Mohammed Mosayeeb Al Hady Zaheen, Douglas L. Maskell

“…Approximate computation has emerged as a promising alternative to accurate computation, particularly for applications that can tolerate some degree of error without significant degradation of the output quality. …”
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Godunov-type scheme for air–water transient pipe flow considering variable heat transfer and laboratorial validation by Ling Zhou, Qian-Xun Chen, Yun-Jie Li, Rui-Lin Feng, Zi-Jian Xue

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