Cross-sectional network analysis was employed to explore the complex relationships between depression, anxiety, insomnia, somatic symptoms, childhood trauma, self-esteem, social support, and emotional ...

Abstract: With the dynamic nature of optical service provisioning and network topology reconfigurations, failure identification and management become complex, as the machine learning (ML) model is ...

Stop throwing money at GPUs for unoptimized models; using smart shortcuts like fine-tuning and quantization can slash your ...

Real-time creative tools need more than static scripts. You have spent Modules 1-9 mastering NumPy arrays, writing Python scripts that process images, and generating visuals through code. But what ...

Bayesian networks are probabilistic graphical models that represent variables as nodes connected by directed edges encoding causal or dependency relations. In fault diagnosis, they enable the ...

Experimental - This project is still in development, and not ready for the prime time. A minimal, secure Python interpreter written in Rust for use by AI. Monty avoids the cost, latency, complexity ...

Bio-inspired optimisation algorithms draw upon mechanisms observed in nature to address complex global optimisation tasks. These methods harness principles such as genetic evolution, swarm ...

Abstract: Since it is very important for soldiers to obtain threat information in battlefield environment, this paper determines the threat elements of soldiers in battlefield environment based on ...