Browse Items (9465 total)

The electricity distribution network is an important component that distributes electricity from substations to end consumers. Monitoring voltage across the network is critical, but direct measurement at all points is often impractical…

Intrusion detection plays an important role in protecting systems from various threats. However, as intrusion techniques become more sophisticated, traditional detection methods have shown limitations in identifying new attacks. This …

In the investment world, the ability to predict stock price movements is a key factor for success among investors and analysts. This study introduces a novel approach for forecasting stock prices in Indonesia's mining sector using a hybrid …

Brain tumors have become a leading cause of mortality worldwide. Detecting and classifying brain tumors accurately at the initial stages is challenging due to their complex and varying structure. In this study, an improved fine-tuned model …

This study introduces a novel method for detecting overtaking vehicles by integrating Virtual Line Detection with the YOLOv8n algorithm. The objective is to enhance road safety by accurately identifying and tracking …

This research investigates the application of Convolutional Variational Autoencoder (CVAE) for multi-class classification of mental health disorders. The study utilizes a diverse dataset comprising five classes: Normal, Anxiety, Depression,…

AbstractThis study addresses the escalating challenge of Twitter spam detection by leveraging the power of Convolutional Neural Networks (CNNs). With the proliferation of spam content on social media platforms, traditional machine…

This study identified ransomware threats in social media platforms by evaluating the performance of Assessing different machine-learning algorithms in various aspects of detecting and classifying ransomware content. The primary problem …

Small datasets and imbalanced classes often cause problems when used as primary research material. In the case of classification and object detection, some researchers proposed Transfer Learning (TF) with several frozen layers. …

This study focuses on using machine learning algorithms to detect cardiovascular diseases, addressing the critical need for accurate and timely diagnosis of these conditions, which are significant contributors to global morbidity and mortality. The…