Training datasets
For our training dataset, we generated five million mathematical expressions based on 100, 000 predefined expression skeletons with up to two independent variables, following the same setup as used in T-JSL3. These skeletons…

For our training dataset, we generated five million mathematical expressions based on 100, 000 predefined expression skeletons with up to two independent variables, following the same setup as used in T-JSL3. These skeletons…

In this section, the MSM is used to obtain the AS of the previously provided system of Eqs. (5)-(7). Therefore, we focus our study on the dynamic behavior of this system in a narrow region bounded by the static equilibrium point34. Then, the…

This paper proposes a prediction method to characterize the pattern of community feature changes, learn their impact on evolutionary events, and forecast critical events in the next timeframe. In this section, we will analyze the effectiveness of…

De Cooman, B. C., Chin, K. G. & Kim, J. High Mn TWIP steels for automotive applications. New. Trends Developments Automot. Syst. Eng. 1, 101–128. https://doi.org/10.5772/14086 (2011).
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In this work, the dataset used to study the variability of fatalities due to these violent events was acquired from the Armed Conflict Location and Event Data Project (ACLED). ACLED is a data collection, analysis, and crisis mapping project…

A computational simulation utilizing the SAM was carried out to improve CSP system performance. This simulation incorporated both real and satellite data on DNI to evaluate and optimize key system parameters precisely. In this research, we aim to…

We set out to examine the stereotypes and biases in Stable Diffusion XL (SDXL), a text-to-image generator used daily by millions worldwide8. To this end, we developed a classifier to predict the race and gender of any given face image, and…

Wang, R., Chen, S., Tian, G., Wang, P. & Ying, S. Post-secondary classroom teaching quality evaluation using small object detection model. Sci. Rep. 14, 5816 (2024).
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This framework outlines a systematic approach for evaluating hospital website usability using machine learning techniques. It combines structured usability parameters with predictive modeling to generate actionable insights for digital healthcare…
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