Solar Flare Prediction Using Multivariate Time Series of Photospheric Magnetic Field Parameters: A Comparative Analysis of Vector, Time Series, and Graph Data Representations by Onur Vural, Shah Muhammad Hamdi, Soukaina Filali Boubrahimi

“…The vector-based approach condenses multivariate time series into a compressed vector form, the time series representation leverages temporal patterns, and the graph-based method models interdependencies between magnetic field parameters. The results demonstrate that the vector representation approach exhibits exceptional robustness in predicting solar flares, consistently yielding strong and reliable classification outcomes by effectively encapsulating the intricate relationships within photospheric magnetic field data when coupled with appropriate downstream machine learning classifiers.…”
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Synthesis of optimal laws for frequency-adjustable hydraulic drives of manipulation systems of mobile machines by Lagerev A.V., Lagerev I.A.

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Prediction of Machining Characteristics and Machining Performance for Grade 2 Titanium Material in a Wire Electric Discharge Machine Using Group Method of Data Handling and Artific... by Sudhir Jain Prathik, Athimoolam Sundaramahalingam, Maddur Eswara Nithyashree, Addamani Rudreshi, Gonchikar Ugrasen

“…Subsequently, simpler functional relationship plots were generated between these parameters to recognize the potential information about the machining characteristics and machining performance. …”
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Digital technology for spectral analysis of oscillation parameters by A. V. Gulaj, V. M. Zajcev

“…This work presents a method of polyharmonic approximation of the parameters of the signals reflecting oscillatory processes in machines based on the additive combinations of sinusoidal functions. …”
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Stabilization of Contour Milling on CNC Machines by Yuri Petrakov, Artur Myhovych

“…Therefore, the MRR as the main process parameter was considered the research subject. This parameter determines the cutting intensity and is responsible for forming the required surface quality of the part. …”
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Justification of the Crank Tedder Parameters for Mineral Fertilizers by Sayakhat Nukeshev, Kairat Yeskhozhin, Yerzhan Akhmetov, Boris Gorbunov, Dinara Kossatbekova, Khozhakeldi Tanbayev, Adilet Sugirbay, Kaldybek Tleumbetov

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Comparative Analysis of Automated Machine Learning and Optimized Conventional Machine Learning for Concrete’s Uniaxial Compressive Strength Prediction by Chukwuemeka Daniel

“…This study pioneers the application of automated machine learning (AutoML) and conventional ML techniques to unravel the intricate relationships between the UCS and six factors. …”
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AE-XGBoost: A Novel Approach for Machine Tool Machining Size Prediction Combining XGBoost, AE and SHAP by Mu Gu, Shuimiao Kang, Zishuo Xu, Lin Lin, Zhihui Zhang

“…Taking the actual size of the machine tool as the response parameter, based on the size parameters in the milling process of the CNC machine tool, the effectiveness of the model is verified. …”
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Biomechanical parameter assessment for classification of Parkinson’s disease on clinical scale by Abdul Haleem Butt, Erika Rovini, Dario Esposito, Giuseppe Rossi, Carlo Maremmani, Filippo Cavallo

“…Biomechanical parameters were acquired from six exercises through wearable inertial sensors: SensFoot V2 and SensHand V1. …”
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Non-Parametric Reconstruction of Cosmological Observables Using Gaussian Processes Regression by José de Jesús Velázquez, Luis A. Escamilla, Purba Mukherjee, J. Alberto Vázquez

“…Recent advancements in machine learning have significantly enhanced its application across various scientific fields, including physics, and particularly cosmology, where data analysis plays a crucial role in problem-solving. …”
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Analysis of Driving Factors of Cropland Productivity in Northeast China Using OPGD-SHAP Framework by Runzhao Gao, Hongyan Cai, Xinliang Xu

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Investigating translation for Indic languages with BLOOMZ-3b through prompting and LoRA fine-tuning by Aarathi Rajagopalan Nair, Deepa Gupta, B. Premjith

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A Short-Term Load Interval Forecasting Method Based on EEMD-SE and PSO-KELM by Lin ZHANG, Jichun LIU

Subjects: “…kernel extreme learning machine…”
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Machine Processing of Milk in Dairy Production by Gerber Y., Gavrilov A.

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Machine Learning G-Code Optimization by Héctor Lasluisa-Naranjo, David Rivas-Lalaleo, Joaquín Vaquero-López, Christian Cruz-Moposita

“…G-codes are essential in CNC systems, providing crucial instructions for controlling machine parameters and operations in manufacturing, including 3D printing. …”
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Machining of glass fiber reinforced polyamide

“…In conclusion, it was observed that the chip formation mechanism affects the thrust dependence on the machining parameters. A traditional modeling approach is able to predict thrust only in presence of a continuous chip. …”
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ENERGY ANALYSIS OF MOBILE MACHINE VIBRATIONS by N. N. Hurski, Y. I. Slabko, R. I. Fourounjiev

“…Initial data of the mobile machine parameters, results of computer-aided modeling of a soil road microstructure and distribution of released by vibrations are given in the paper.…”
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RESEARCH OF REFUSALS AND RELIABILITY OF THE MOBILE MACHINES by А. А. ANDROSSOV, M. R. GALADZHEVA, L. M. GROSHEV, S. A. PARTKO

“…In this article necessary and sufficient parameters for calculation of reliability of load-carrying constructions and running systems of mobile machines are defined. …”
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FINE POSITIONING SYSTEM OF MACHINE PARTS by A.V. LITVIN, A.A. ZAKHAROV

“…Electric circuit of analog and digital units of fine positioning system of machine parts using the programmable microcontroller is presented. …”
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Noise reduction problems of vibratory machines by J. MICHALCZYK

“…Special attention is devoted to the problems of optimization of vibration parameters in the machines mentioned above, with restrictions imposed by the required production output and quality of the manufacturing process. …”
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