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Financial institutions constantly face at the risk of default by borrowers which can result in significant financial losses. It is essential to develop an appropriate predictive model for loan default to reduce these ris...

This study presents a novel machine learning approach to assess human well-being through the analysis of brain wave activities. We developed a Random Forest classifier to categorize brain wave patterns into three states ...

Abstract A good wireless network design depends on technical and financial viability and a number of other criteria that must be met. Following the emergence of new technologies and services, such as 5G transmission and ...

The rapid proliferation of unmanned aerial vehicles (UAVs) has created an urgent need for robust detection & identification systems to ensure airspace security and safety. However, the scarcity of large-scale, div...

Land use and land cover (LULC) changes have an important effect on the dynamics of climate change, affecting the structure and functioning of ecosystems. Greenhouse gases in the atmosphere are directly related to the fun...

This study provides a quantitative framework for wellbeing outcome prediction through intentional cognitive pattern alteration. We demonstrated 81.67% accurate prediction of wellbeing states, in a three-level classificat...

The adoption of artificial intelligence (AI) in cardiovascular disease prediction has significantly improved risk stratification, offering new avenues for early diagnosis and preventive care. With the growing availabilit...

"This thesis investigates the application of machine learning methods to the task of deforestation monitoring using time-series satellite data. The objective is to assess how different algorithmic approaches perform in d...