Sequential Design Process of a 350-kW Class Dual Three-Phase IPMSM for a Wheeled Armored Vehicle by Ji-Chang Son, Min-Su Kwon, Dong-Kuk Lim

“…The overall geometric parameters are determined through electromagnetic analysis in the detailed design stage and an initial model that satisfies the requirements is derived. …”
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Integrating AI and Multi-objective Optimization for Enhanced Microgrid Energy Management Using Quadratic Programming by Agrawal Priyanka, Thethi H. Pal, Mohammad Q., Gupta Navya, Asha V., Reddy K. Jyothsna

“…Both the fuzzy environment of the microgrid operation as a whole and the uncertainty among the predicted parameters are manageable in the suggested solution. …”
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Characterization of material properties of renewable biobased powder for 3D printing using the traditional moulding sand test methods of foundry technology by Abdulkader Ali Kadauw, Tillmann Bohme, Henning Zeidler

“…Based on the results from testing, process parameters can be adjusted. There are currently no standardised methods for the testing of 3D printing materials. …”
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Eco-Driving Level Evaluation Model for Electric Buses Entering and Leaving Stops by Aihong Lyu, Huiming Zhang, Yubo Shen, Yali Zhang

“…The representative parameters of driving behaviors for entering and leaving stops are then selected through correlation analysis and multiple stepwise linear regression analysis. …”
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Microwave Tomography System for Methodical Testing of Human Brain Stroke Detection Approaches by Ilja Merunka, Andrea Massa, David Vrba, Ondrej Fiser, Marco Salucci, Jan Vrba

“…It is therefore suitable for large-scale measurements with high variability of measured data for stroke detection and classification based on machine learning methods. In order to verify the functionality of the measuring system, S-parameters were measured for a hemorrhagic phantom sequentially placed on 23 different positions and distributions of dielectric parameters were reconstructed using the Gauss-Newton iterative reconstruction algorithm. …”
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Virtual sensing-enabled digital twin framework for real-time monitoring of nuclear systems leveraging deep neural operators by Raisa Hossain, Farid Ahmed, Kazuma Kobayashi, Seid Koric, Diab Abueidda, Syed Bahauddin Alam

“…Machine learning-driven virtual sensors offer a transformative solution by complementing physical sensors in monitoring critical degradation indicators. …”
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Wearable Standalone Sensing Systems for Smart Agriculture by Dongpil Kim, Mohammad Zarei, Siyoung Lee, Hansol Lee, Giwon Lee, Seung Goo Lee

“…Existing sensors often have technical limitations, measuring only specific parameters with limited reliability and spatial or temporal resolution. …”
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Analysis of the Surface Quality Characteristics in Hard Turning Under a Minimal Cutting Fluid Environment by Sandip Mane, Rajkumar Bhimgonda Patil, Anindita Roy, Pritesh Shah, Ravi Sekhar

“…The findings showed that surface roughness increases with feed rate, identified as the most influential parameter, while the depth of cut shows a negligible effect. …”
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Force calculation of the fastening mechanism of the end tower of a mobile transport and reloading rope unit using a holding rope by V.I. Tarichko, A.V. Lagerev, I.A. Lagerev

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Motor Bearing Failure Identification Using Multiple Long Short-Term Memory Training Strategies by Youcef ATMANI, Ammar Mesloub, Said Rechak

“…In the context of condition-based maintenance of rotating machines in manufacturing systems, the early diagnosis of possible faults related to rolling elements of the bearing is mainly based on techniques from artificial intelligence, namely, Machine Learning (ML) and Deep Learning (DL). …”
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A Methodology for Electricity Demand Forecasting Using a Hybrid Approach by Fanidhar Dewangan, Monalisa Biswal, Nand Kishor

“…A comparative analysis of the proposed method is conducted against other available approaches, including various time-series decomposition methods, different machine learning techniques, and alternative test system.…”
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Development of a spatial accuracy compensation method based on multi-beam laser interferometer by Lihua Lei, Changjian Sun, Zhangning Xie, Lijie Liang, Yunxia Fu, Bo Zhang

“…The error in the X/Y/Z axis data of the computer numerical control (CNC) machine tool is determined using the multi-beam laser interferometer. …”
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Research on Forecasting Sales of Pure Electric Vehicles in China Based on the Seasonal Autoregressive Integrated Moving Average–Gray Relational Analysis–Support Vector Regression M... by Ru Yu, Xiaoli Wang, Xiaojun Xu, Zhiwen Zhang

“…Aiming to address the complexity and challenges of predicting pure electric vehicle (EV) sales, this paper integrates a time series model, support vector machine and combined model to forecast EV sales in China. …”
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A Comprehensive Dataset of Surface Water Quality Spanning 1940-2023 for Empirical and ML Adopted Research by Md. Rajaul Karim, M. M. Mahbubul Syeed, Ashifur Rahman, Khondkar Ayaz Rabbani, Kaniz Fatema, Razib Hayat Khan, Md Shakhawat Hossain, Mohammad Faisal Uddin

“…The resulting dataset consists of 2.82 million measurements of eight water quality parameters that span 1940 - 2023. This dataset can support meta-analysis of water quality models and can facilitate Machine Learning (ML) based data and model-driven investigation of the spatial and temporal drivers and patterns of surface water quality at a cross-regional to global scale.…”
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A Method for Predicting Trajectories of Concealed Targets via a Hybrid Decomposition and State Prediction Framework by Zhengpeng Yang, Jiyan Yu, Miao Liu, Tongxing Peng, Huaiyan Wang

“…The RBMO further refines critical parameters within the ISVMD-ELM pipeline, ensuring adaptability and computational efficiency across diverse scenarios. …”
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A Hybrid Framework for Soil Property Estimation from Hyperspectral Imaging by Daniel La’ah Ayuba, Jean-Yves Guillemaut, Belen Marti-Cardona, Oscar Mendez

“…Hyperspectral imaging provides a non-invasive means of quantifying key soil parameters, but effectively utilizing the high-dimensional hyperspectral data presents significant challenges. …”
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SubsurfaceBreaks v. 1.0: a supervised detection of fault-related structures on triangulated models of subsurface homoclinal interfaces by M. P. Michalak, C. Gerhards, P. Menzel

“…Support Vector Machine (SVM) is employed as the classification algorithm, achieving high precision and recall rates for fault-related observations. …”
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Artificial intelligence in the food industry: innovations and applications by Hang Yang, Wenxuan Jiao, Lingyun Zouyi, Hongli Diao, Shibin Xia

“…Advanced ML models are employed to analyze production data, monitor quality parameters, and predict shelf life, ensuring compliance with stringent regulatory standards. …”
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Fault Diagnosis of Rolling Bearing Based on Modified Deep Metric Learning Method by Zengbing Xu, Xiaojuan Li, Hui Lin, Zhigang Wang, Tao Peng

“…And then, BPNN classifier of DMN-Yu method is used to fine tune the network parameters and diagnose the fault category. Finally, the effectiveness and feasibility of the proposed DMN-Yu method is verified with the rolling bearing fault diagnosis test. …”
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Introducing Iterative Model Calibration (IMC) v1.0: a generalizable framework for numerical model calibration with a CAESAR-Lisflood case study by C. Banerjee, K. Nguyen, C. Fookes, G. Hancock, T. Coulthard

“…<p>In geosciences, including hydrology and geomorphology, the reliance on numerical models necessitates the precise calibration of their parameters to effectively translate information from observed to unobserved settings. …”
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