Unveiling the startup characteristics of pump as turbine using computational and experimental techniques by Dessie Tarekegn Bantelay, Girma Gebresenbet, Bimrew Tamrat Admasu, Muluken Temesgen Tigabu, Muluken Zegey Getie

“…During the start-up transient phase, the transient characteristic parameters such as pump rotational speed, head, and flow rate change significantly. …”
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Development of deep-learning-based autonomous agents for low-speed maneuvering in Unity by Riccardo Berta, Luca Lazzaroni, Alessio Capello, Marianna Cossu, Luca Forneris, Alessandro Pighetti, Francesco Bellotti

“…While blogs and forums discuss training machine learning models in Unity, a lack of scientific articles on DRL agents for AD persists. …”
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Predicting Overload Risk on Plasma-Facing Components at Wendelstein 7-X from IR Imaging Using Self-Organizing Maps by Giuliana Sias, Emanuele Corongiu, Enrico Aymerich, Barbara Cannas, Alessandra Fanni, Yu Gao, Bartłomiej Jabłoński, Marcin Jakubowski, Aleix Puig Sitjes, Fabio Pisano, W7-X Team

“…This paper proposes a machine learning approach for developing a real-time overload detector, trained and tested on OP1.2a experimental data. …”
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Global Energy Systems Modeling: Structure and Environmental Impacts by Olha Kovalchuk, Oksana Tulai, Olga Zavytii, Ludmila Babala, Roman Ivanytskyy, Pavlo Chopyk

“…This study analyzes energy systems across 66 countries using machine learning methods, based on comprehensive energy performance and environmental indicators. …”
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Faster Image2Video Generation: A Closer Look at CLIP Image Embedding’s Impact on Spatio-Temporal Cross-Attentions by Ashkan Taghipour, Morteza Ghahremani, Mohammed Bennamoun, Aref Miri Rekavandi, Zinuo Li, Hamid Laga, Farid Boussaid

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Data-driven strategies for digital native market segmentation using clustering by Md Ashraf Uddin, Md. Alamin Talukder, Md. Redwan Ahmed, Ansam Khraisat, Ammar Alazab, Md. Manowarul Islam, Sunil Aryal, Ferdaus Anam Jibon

“…To tackle these challenges, we introduce a Machine Learning-based Digital Native Market Segmentation designed to cater specifically to the interests of digital natives. …”
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Visual Three-Dimensional Reconstruction of Aortic Dissection Based on Medical CT Images by Xiaojie Duan, Dandan Chen, Jianming Wang, Meichen Shi, Qingliang Chen, He Zhao, Ruixue Zuo, Xiuyan Li, Qi Wang

“…With the rapid development of CT technology, especially the higher resolution of CT machine and a sharp increase in the amount of slices, to extract and three-dimensionally display aortic dissection from the huge medical image data became a challenging task. …”
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Analytical Inertia Identification of Doubly Fed Wind Farm with Limited Control Information Based on Symbolic Regression by Mengxuan Shi, Yang Li, Xingyu Shi, Dejun Shao, Mujie Zhang, Duange Guo, Yijia Cao

“…Finally, the effectiveness of the proposed method is validated in an IEEE three-machine nine-bus system containing a doubly fed wind power cluster. …”
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Medium and short-term load forecasting based on NPMA-LSSVM algorithm in the case of unbalance and minority sample data by YANG Qiuyu, KUANG Shusen, ZHENG Xiaogang, YE Guoqi, ZHANG Zhongxin

“…Finally, the least square support vector machine (LSSVM) load forecasting model is established, and the improved mayfly algorithm with nonlinear inertia factor and polynomial variation is used to optimize the model parameters to achieve accurate load forecasts. …”
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Discovering New Tyrosinase Inhibitors by Using In Silico Modelling, Molecular Docking, and Molecular Dynamics by Kevin A. OréMaldonado, Sebastián A. Cuesta, José R. Mora, Marcos A. Loroño, José L. Paz

“…<b>Methods</b>: Four machine learning algorithms and topographical descriptors were tested for model construction. …”
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Voice-Evoked Color Prediction Using Deep Neural Networks in Sound–Color Synesthesia by Raminta Bartulienė, Aušra Saudargienė, Karolina Reinytė, Gustavas Davidavičius, Rūta Davidavičienė, Šarūnas Ašmantas, Gailius Raškinis, Saulius Šatkauskas

“…The deep neural network classified previously unseen voice recordings with 0.84 accuracy, 0.81 specificity, 0.86 sensitivity, and 0.85 and 0.81 F1-scores for blue and pink classes, respectively. The machine learning algorithms revealed that voice parameters, such as Mel-frequency cepstral coefficients, Chroma vectors, and sound energy, play the most significant role. …”
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The Concept and Measurements of an Adjustable Holder for Large Magnets Applicable for a THz Undulator Working in Superradiant Emission by Paweł J. Romanowicz, Jarosław Wiechecki, Daniel Ziemiański, Robert Nietubyć, Paweł Krawczyk

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On Realization of Intelligent Decision Making in the Real World: A Foundation Decision Model Perspective by Ying Wen, Ziyu Wan, Ming Zhou, Shufang Hou, Zhe Cao, Chenyang Le, Jingxiao Chen, Zheng Tian, Weinan Zhang, Jun Wang

“…The pervasive uncertainty and dynamic nature of real-world environments present significant challenges for the widespread implementation of machine-driven Intelligent Decision-Making (IDM) systems. …”
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3D gamma analysis between treatment plans for nominally beam‐matched medical linear accelerators using PyMedPhys by Fada Guan, William Donahue, Simon Biggs, Matthew Jennings, Emily Draeger, Huixiao Chen, Yuenan Wang, Ngoc Nguyen, David J. Carlson, Zhe Chen, Dae Yup Han

“…An in‐house script was used to automatically create new plans for the target linac and calculate dose using parameters of the original plans. 3D gamma analysis was performed to compare plan dose distributions between the target and original linacs using PyMedPhys. …”
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Combination of skin sympathetic nerve activity and urine biomarkers in improving diagnostic accuracy for urge urinary incontinence by Yu-Chen Chen, Hao-Wei Chen, Tzu-Yu Liu, Yung-Shun Juan, Yu-Peng Liu, Shiou-Lan Chen, Chien-Hung Lee, Wei-Chung Tsai, Wen-Jeng Wu

“…Logistic regression and support vector machine with L1 penalty were applied to SKNA and urine biomarker measurements. …”
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Analysis of the adaptability of frequency emergency control considering the active support characteristics of grid-forming new energy by Shuangshuang WANG, Xuelian WU, Zhaowei LI, Ling ZHU, Yuchen DAI, Defu CAI

“…Based on this model，the influence of various frequency control parameters，such as power reserves of new energy and droop control coefficients，on the effectiveness of frequency emergency control is analyzed comprehensively. …”
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Subdivision of river channel sand micro-scale facies with feature attention spatio-temporal network by Ruipu Zhao, Lili Zeng, Chendong Fu, Xiaoqing Zhao

“…The feature attention module dynamically assigns weights to logging parameters based on their correlation with the target classification, enhancing the contribution of key parameters to the classification task. …”
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Study on Operating Modes of a Biofuel Diesel Engine by V. A. Likhanov, O. P. Lopatin

“…The research results may be useful both to scientists working on this topic, and to engineers and technicians in the machine-building industry.…”
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Background for modeling the dynamic characteristics of advanced spacecraft drives considering the operation of oscillators by A. N. Sova, M. I. Stepanov, V. A. Sova, A. I. Bykov

“…Mathematical modeling methods, techniques of machine mechanics and dynamics are applied. Basic parameters of the proposed design dynamics, which are governing parameters in terms of the implementation of the target functions of the spacecraft, are calculated. …”
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Introducing a Novel Figure of Merit for Evaluating Stability of Perovskite Solar Cells: Utilizing Long Short-Term Memory Neural Networks by Zahraa Ismail, Ahmet Sait Alali, Ahmad Muhammad, Mahmoud Ashraf, Sameh O. Abdellatif

“…Our findings indicate that the LSTM model effectively captures and predicts the complex relationships between key design parameters&#x2014;efficiency, fill factor, and open-circuit voltage&#x2014;and degradation-induced changes in PSCs. …”
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