This study uses natural language processing (NLP) techniques to analyze the political discourse of the surprise presidential candidate, focusing on linguistic patterns, sentiment distribution, and recurring themes. This study addresses the problem of how TikTok virality and algorithmic...

The advent of artificial intelligence paradigms has contributed a great deal towards improving predictive accuracy in medicine especially in the prompt diagnosis of chronic diseases. Feature selection is crucial in refining classification models by identifying and eliminating non-informative or...

The cellular manufacturing system is an approach based on the nature of group technology that can reduce overhead costs. These systems are designed to organize machine cells and components to reduce movement between cells and enhance the efficiency of machine usage in manufacturing environments....

Can algorithms enhance bureaucrats' work in developing countries? In data-poor environments, bureaucrats often exercise discretion over key decisions, such as audit selection. Exploiting newly digitized micro-data, this study conducted an at-scale field experiment whereby half of Senegal's...

This study investigates the impact of competition on credit risk in the Turkish banking system, focusing on Islamic (participation) and conventional banking under the same regulatory conditions regarding credit risk. The credit risk model is trained using CatBoost, extreme gradient boosting...

The exponential escalation of cyber threats and attacks targeting Internet of Things (IoT) devices in this decade necessitates the development of effective intrusion detection methods. This paper presents an innovative anomaly-based intrusion detection system that leverages machine learning (ML)...