May 2025 - 26 articles
Predicting corporate bankruptcy is a key task in financial risk management, and selecting a machine learning model with superior generalization performance is crucial for prediction accuracy. This study evaluates the effectiveness of k-fold cross-val...
Nowadays, the use of biomechanical devices in medical processes and industrial applications allows us to perform tasks in a simpler and faster way. In the medical field, these devices are becoming more and more common, especially in therapeutic appli...
This research introduces a novel hybrid machine learning framework for automated quality prediction and classification of silicon solar modules in production lines. Unlike conventional approaches that rely solely on encapsulation loss rate (ELR) for...
Gene regulatory networks (GRNs) describe the interactions between transcription factors (TFs) and their target genes, playing a crucial role in understanding gene functions and how cells regulate gene expression under different conditions. Recent adv...
In this article, fourth-order systems of ordinary differential equations are studied. These systems are of a special form, which is used in modeling gene regulatory networks. The nonlinear part depends on the regulatory matrix W, which describes the...
Dengue fever (DF) is considered one of the most rapidly spreading infectious diseases, which is primarily transmitted to humans by bites from infected Aedes mosquitoes. The current investigation considers the spread patterns of dengue disease with an...
Loaded Volterra integral equations represent a novel class of integral equations that have attracted considerable attention in recent years due to their numerous applications in various fields of science and engineering. This class of Volterra integr...
One of the key barriers to neural network adoption is the lack of computational resources and high-quality training data—particularly for unique objects without existing datasets. This research explores methods for generating realistic syntheti...
This study aims to comprehensively evaluate the mechanical performance of dry-spun twisted carbon nanotube (CNT) yarns (CNTYs) subjected to uniaxial tensile load. To this end, in contrast to earlier approaches, the current research lies in an innovat...
This study presents a digital twin approach to quantifying the durability and failure risk of concrete gravity dams by integrating advanced numerical modelling with field monitoring data. Building on a previously developed finite element model for da...
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