Category: 7. Maths

Healthcare regulation must adapt rapidly to the challenges posed by QC. Existing frameworks, such as the GDPR, NIS2, or MDR, impose requirements for data protection, device security, and infrastructure resilience, but were developed under…

T2I generation is the most emerging area of generative learning, enabling the model to produce images from the textual input. Various studies proposed methods for T2I generation using different approaches. This section examines the existing…

The key aspect in developing a fault-tolerant routing algorithm is the quality-of-service parameters taken into account to attain the shortest pathways. Typically, fault-tolerant algorithms employ restricted criteria to identify a dependable…

To ensure reliable object localization and environment perception in complex port scenarios, this study adopts LiDAR-based point cloud data rather than relying solely on RGB or thermal imaging. RGB cameras, though capable of capturing rich…

This study develops a novel TTOCDM-XAIRNN methodology. The main intention of the TTOCDM-XAIRNN methodology is to improve the detection and mitigation of cyber threats in dynamic environments. To attain that, the proposed TTOCDM-XAIRNN model…

The methodology adopted for detecting anomalies in IoT networks is outlined in this section. While IoT devices offer connectivity and convenience, data transmitted to the cloud is vulnerable to attacks. Without proper updates and security, these…

With the increase in EV adoption, there is a growing need for accurate power consumption estimates to optimize charging station management³³. The effective planning and development of EV infrastructure can be significantly enhanced through…

Overview

Language learning, as a fundamental capability in artificial intelligence and cognitive science, aims to model the acquisition, processing, and application of language-related knowledge. This subsection provides a conceptual outline of…

In this section, we summarize the mathematical background of some of the different mappings that a neural network can implement and introduce LILs. We treat both training and test data as being sampled from a manifold \(\mathcal {M}\) and the…

In this section, a two-stage algorithm for the robust control of the robot manipulator is presented. The mathematical control design is divided into two following robust control techniques, which are applied to the nonlinear control system.