Implementation of a power supply with optimized voltage and power quality control by a smart filter by Adel Akbarimajd, Amir Mohammadhoseini Heiran

“…This smart filter is designed to be controlled based on a support vector machine (SVM)  machine learning scheme. Experimental results are provided to illustrate the successful and high-quality supply of power needed to  start a helicopter. …”
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Neural network-based evaluation method for alignment state of air spring vibration isolation device by Zhiwei LIU, Liang SHI, Song LIU

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Simulation Based Performance Assessment of Developing Heterarchical Control for a Flexible Assembly System by Ismayyir Dhuha Kadhim, AL-Khafaji Mohanned.M.H., Dawood Lamyaa M.

“…The simulation procedure included specifying the parameters and initial conditions of the system, executing the simulation, and assessing the outcomes. …”
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GRAPPA—A hybrid graph neural network for predicting pure component vapor pressures by Marco Hoffmann, Hans Hasse, Fabian Jirasek

“…We found excellent prediction accuracy for unseen components, outperforming state-of-the-art group contribution methods and other machine learning approaches in applicability and accuracy. …”
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Deep Learning Model Approach to Predict Diabetes Type 2 Based on Clinical, Biochemical, and Gut Microbiota Profiles by Pablo Caballero-María, Javier Caballero-Villarraso, Javier Arenas-Montes, Alberto Díaz-Cáceres, Sofía Castañeda-Nieto, Juan F. Alcalá-Díaz, Javier Delgado-Lista, Fernando Rodríguez-Cantalejo, Pablo Pérez-Martínez, José López-Miranda, Antonio Camargo

“…Our objective was to develop a predictive model of the risk of developing T2DM based on clinical, biochemical, and intestinal microbiota parameters, which estimates the time margin for developing this disease. …”
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Cervical Cancer Detection Using Deep Neural Network and Hybrid Waterwheel Plant Optimization Algorithm by Sarah A. Alzakari, Amel Ali Alhussan, S.K. Towfek, Marwa Metwally, Dina Ahmed Salem

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Hybrid Gaussian Process Regression Models for Accurate Prediction of Carbonation-Induced Steel Corrosion in Cementitious Mortars by Teerapun Saeheaw

“…This study presents a comprehensive framework integrating domain expertise with advanced machine learning for carbonation-induced corrosion prediction. …”
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RL-BMAC: An RL-Based MAC Protocol for Performance Optimization in Wireless Sensor Networks by Owais Khan, Sana Ullah, Muzammil Khan, Han-Chieh Chao

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Multi-objective optimization of low moisture food extrusion processing through active learning and robotics by Deborah Becker, Jean-Vincent Le Bé, Cornelia Rauh, Christoph Hartmann

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Suppression of irradiation defects and crack propagation in niobium via grain boundary engineering: A deep potential molecular dynamics study by Jiahang Li, Yajun Zhang, Jie Wang, Huadong Yong

“…Here, we developed a multi-scale framework based on first-principles simulations, machine learning potential, and molecular dynamics simulations. …”
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Real-time monitoring of water quality dynamics using low-cost sensor networks in Lagos lagoon by Idowu Ayisat Aneyo, Mumin Olatunji Oladipo, Funmilayo Victoria Doherty, Julius Osato Ehigie, Adebayo Fasasi Adebari, Abdulwakeel Oluwatobi Atoyebi, Peter Ozomata Balogun, Ambrose Obinna Ikpele

“…Acoustic analysis revealed dominant frequencies below 500 Hz, indicative of biological and anthropogenic activity in the lagoon. Machine learning models trained on 31 species closely agreed with the environmental dataset despite some noticeable deviations, suggesting potential improvements through data augmentation and model refinement. …”
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Low Capillary Elastic Flow Model Optimization Using the Lattice Boltzmann Method and Non-Dominated Sorting Genetic Algorithm by Yaqi Hou, Wei Zhang, Jiahua Hu, Feiyu Gao, Xuexue Zong

“…This paper establishes an LBM multiphase flow model enhanced by machine learning. The hyperparameters of the machine learning model are optimized using the particle swarm algorithm. …”
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Outlook towards deployable continual learning for particle accelerators by Kishansingh Rajput, Sen Lin, Auralee Edelen, Willem Blokland, Malachi Schram

“…Particle accelerators are high power complex machines. To ensure uninterrupted operation of these machines, thousands of pieces of equipment need to be synchronized, which requires addressing many challenges including design, optimization and control, anomaly detection and machine protection. …”
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Measurement-Based Neural Network Technique for Modeling the Low-Frequency Electric Field Radiated Behavior of Satellite Units by Anna N. Lampou, Anargyros T. Baklezos, Konstantinos K. Spyridakis, Dimitrios A. Rigas-Papakonstantinou, Ioannis O. Vardiambasis, Christos D. Nikolopoulos

“…In this work, a machine learning technique employing a measurement-driven artificial neural network (ANN) architecture is proposed as a solution to the precise determination of the position and the moment of equivalent electric dipoles for unit characterization. …”
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Production Capacity Prediction for Tight Gas Reservoirs Based on ADASVRLGBM by MENG Sihai, ZHANG Zhansong, GUO Jianhong, HAN Zihao, ZENG Weijie, LYU Hengyang

“…The integrated model systematically analyzes the correlation of factors influencing tight gas production, extracts key feature parameters, and builds a predictive model with gas well production capacity as the output label. …”
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Integrated noninvasive diagnostics for prediction of survival in immunotherapy by M. Yeghaian, Z. Bodalal, T.M. Tareco Bucho, I. Kurilova, C.U. Blank, E.F. Smit, M.S. van der Heijden, T.D.L. Nguyen-Kim, D. van den Broek, R.G.H. Beets-Tan, S. Trebeschi

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Enhanced Prediction and Evaluation of Hydraulic Concrete Compressive Strength Using Multiple Soft Computing and Metaheuristic Optimization Algorithms by Tianyu Li, Xiamin Hu, Tao Li, Jie Liao, Lidan Mei, Huiwen Tian, Jinlong Gu

“…In the initial stage, several classic machine learning models are selected as base models, and the optimal parameters of these models are obtained using the improved metaheuristic-based gray wolf algorithm. …”
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A Lightweight Kernel Density Estimation and Adaptive Synthetic Sampling Method for Fault Diagnosis of Rotating Machinery with Imbalanced Data by Wenhao Lu, Wei Wang, Xuefei Qin, Zhiqiang Cai

“…Comparative experiments further demonstrate that KAMS not only delivers exceptional diagnostic performance but also significantly reduces network parameters and computational resource requirements.…”
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Research on identification method of bituminous coal based on terahertz time-domain spectroscopy by Shuguang Miao, Shuguang Miao, Xiang Liu, Xiang Liu, Yue Zhang, Yue Zhang, SuWen Li, SuWen Li, Enjie Ding, Enjie Ding

“…The traditional coal type identification method needs to measure a variety of parameters of coal samples to obtain more accurate results, and the detection process is time-consuming and laborious, and can not realize the rapid identification of coal types. …”
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AI4EF: Artificial Intelligence for Energy Efficiency in the building sector by Alexandros Menelaos Tzortzis, Georgios Kormpakis, Sotiris Pelekis, Ariadni Michalitsi-Psarrou, Evangelos Karakolis, Christos Ntanos, Dimitris Askounis

“…Featuring a modular framework, AI4EF includes customizable building retrofitting, photovoltaic installation assessment, and predictive modeling tools that allow users to input building parameters and receive tailored recommendations for achieving energy savings and carbon reduction goals. …”
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