The spatio-temporal evolution of wall-bounded turbulence is characterized by high nonlinearity, multi-scale dynamics, and chaotic nature, making its accurate prediction a significant challenge for ...

Responsible AI involves designing machine learning systems that are transparent, fair, and accountable. In the context of healthcare, responsible AI also includes protecting patient privacy, ensuring ...

As artificial intelligence rapidly reshapes how organisations build products, manage risk, serve customers and run operations, the need for professionals who can design, deploy and govern intelligent ...

However, in indoor environments, non-line-of-sight (NLOS) signals significantly degrade the ranging performance of UWB ...

The role of technology in optimizing ERP order processing has become increasingly important as businesses strive to improve operational efficiency and reduce costs.

Utilities worldwide are turning to artificial intelligence (AI) and machine learning to stabilize networks, forecast ...

This research initiative highlights the importance of ethical and explainable artificial intelligence in workforce ...

In order to solve the problems of physical model simplification error, insufficient fusion of multi-source monitoring data, and low accuracy of life prediction in traditional CNC machine tool life ...

CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...

Abstract: Identifying the emotions hidden in speech (SER) encounters difficulties in virtue of the subjective and variable nature of human emotions, along with limitations such as data dependency, ...

This project uses deep learning techniques to detect malware by analyzing file characteristics, byte sequences, and behavioral patterns. It employs Convolutional Neural Networks (CNNs) for image-based ...

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