IEEE

A Multi-Head Attention and Residual Dense Network with Dynamic Sampling for Fine-Grained Network Intrusion Classification

Abstract: Network Intrusion Detection Systems are essential for monitoring and analyzing network traffic to detect and prevent unauthorized access, malicious activities, and security breaches in real ...
IEEE

Impact of Data Imbalance on Reservoir Fracture Identification

Abstract: Fractures in oil and gas reservoirs are crucial for hydrocarbon storage and fluid flow, significantly affecting recovery rates. However, fracture identification is a typically imbalanced ...
IEEE

Performance of Sampling Methods on Imbalanced Data: Comparative Analysis

Abstract: Imbalanced data affects a range of machine learning applications including bioengineering. Sampling is the most common approach to deal with imbalanced data. In this study, the effectiveness ...
IEEE

Enhancing Lidar Point Cloud Sampling via Colorization and Super-Resolution of Lidar Imagery

Abstract: Recent advancements in lidar technology have led to improved point cloud resolution as well as the generation of 360° low-resolution images by encoding depth, reflectivity, or near-infrared ...
IEEE

A Quality-Aware Sampling Framework for Efficient 3D Point Cloud Transmission

Abstract: The large volume of data from the point cloud brings significant demands on network bandwidth. However, the current transmission framework only considers using lossy compression to control ...
IEEE

A Clustering-Based Oversampling Approach for Class Imbalance in Mixed Data

Abstract: Class imbalance is a recurring problem in machine learning, especially in domains like SME's, healthcare, finance, and fraud detection, where rare but important events are often ...
IEEE

Dealing With Class Imbalance in Uplift Modeling-Efficient Data Preprocessing via Oversampling and Matching

Abstract: Uplift modeling is a widely recognized predictive approach used to identify individuals who are more likely to respond positively to an intervention or treatment, such as a marketing ...
IEEE

On the signal distortion in a sampling-rate enhanced DAS system with mode division multiplexing

Abstract: In this paper, signal distortion in a sampling-rate enhanced distributed acoustic sensing (DAS) system with mode division multiplexing is studied. Infidelity effect of the phase response of ...
IEEE

A Novel Expandable Borderline Smote Over-Sampling Method for Class Imbalance Problem

Abstract: The class imbalance problem can cause classifiers to be biased toward the majority class and inclined to generate incorrect predictions. While existing studies have proposed numerous ...
EurekAlert!

Machine learning prediction of long-term sickness absence due to mental disorders using Brief Job Stress Questionnaire data

Long-term sickness absence (LTSA) is a significant issue, causing productivity decline, financial difficulties, and increased mental health issues, with mental disorders being the most common cause.
Frontiers

LiDAR point cloud down-sampling strategy with multi-dimensional membership fusion

This study devises an innovative LiDAR point cloud down-sampling strategy that capitalizes on the properties of Fuzzy C Means (FCM) clustering membership functions in each dimension. Traditional ...