The rapid urbanization process has led to many prominent environmental issues in urban areas, resulting from a drastic change in land use. The Urban Heat Island (UHI) effect is of particular concern because it has a significant impact on the livabili...
Federated learning (FL) is emerging as a key approach for collaborative machine learning (ML) in distributed information systems where direct data sharing is infeasible due to policy constraints. In security operations center (SOC) settings, we study...
This study aimed to develop an artificial intelligence-based classification system using ultrasound images obtained via a transgluteal cleft scanning approach for detecting fecal retention in the lower rectum. The goal was to support accurate, object...
When the medicine-picking robot grasps drugs, its flexibility and accuracy in grasping detection mainly depend on the precision of visual guidance for the robot. The result of grasping detection directly determines whether the grasping task can be su...
In an increasingly interconnected world, the security of sensitive data and critical operations is paramount. This study presents the development of a Network Intrusion Detection System (NIDS) that analyzes both inbound and outbound network traffic t...
An Intrusion Detection System (IDS) is an important component of cybersecurity, meant to monitor malicious behaviour, detect, and respond to unauthorized activities in computer systems or networks. Generally, Intrusion detection (IDS) is classified i...
To address the issues of low adaptability and significant tracking errors in parking scenarios when using fixed look-ahead distance Pure Pursuit (PP) algorithms, this paper proposes an automatic parking path tracking control algorithm based on Fuzzy ...
In recent years, multimodal sentiment analysis has gained prominence due to its ability to leverage diverse data types for improved accuracy. However, combining text and image modalities presents challenges in effectively integrating and processing t...
This paper proposes a lightweight video action recognition framework that integrates 3D Convolutional Neural Networks (CNNs), the Histogram Transformer Block (HTB), and the Split-Attention Residual Block (SAB), while also introducing Spatiotemporal T...
BACKGROUND: Metabolic syndrome (MetS) is characterized by chronic inflammation and can be worsened by circadian disruption, which is common among shift work. Machine learning can predict the risk of MetS in shift workers using inflammatory biomarkers...
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