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Introduction: The COVID-19 pandemic has exacerbated mental health challenges, particularly depression among college students. Detecting at-risk students early is crucial but remains challenging, particularly in developin...

Abstract The high prevalence of Haemonchus contortus and its anthelmintic resistance have affected sheep production worldwide. Machine learning approaches are able to investigate the complex relationships among the facto...

Local people in Ternate, North Maluku, often use local languages to communicate on social media. This poses a challenge for newcomers to understand the implied meaning and emotions of the messages conveyed through social...

We show how machine learning techniques can be applied for the classification of topological phases in finite leaky photonic lattices using limited measurement data. We propose an approach based solely on a single real-s...

Leaf senescence is a complex trait which becomes crucial for grain filling because photoassimilates are translocated to the seeds. Therefore, a correct sync between leaf senescence and phenological stages is necessary to...

Diffractive Neural Networks (DNNs) leverage the power of light to enhance computational performance in machine learning, offering a pathway to high-speed, low-energy, and large-scale neural information processing. Howeve...

Tesis de Maestría External Early Warning Systems (EWSs) have traditionally been designed to warn policymakers of potential balance of payments crises. This study compares the performance of three different EWSs Machine ...