The assessment of the level of achievement of course learning outcomes is the most crucial step for improving the quality of the course, contributing to the assessment of the level of achievement of the learning outcomes of an academic program.

These findings underscore the potential of deep ensemble strategies in medical image classification, offering a promising advancement for clinical applications in dermatology and improving the reliability of skin cancer diagnostics.

In the dynamic field of video retrieval, precise and effective search methods are crucial for managing complex datasets. This work provides cutting-edge solutions for the VBS 2025 challenge and offers valuable insights into enhancing video search techniques.

This project facilitates interaction between Caller Devices and the RCS System. It includes a user interface, a backend server, and integrates both Caller Devices and the RCS system. The project manages real-time communication between devices and the RCS system using MQTT for device-to-server communication and API for server-to-RCS communication.

The findings suggest that the combination between AI and IoT technologies can significantly enhance shrimp farming efficiency, mitigate economic losses, and promote sustainable aquaculture practices.

This study proposes a confidence-based multimodal fusion approach using HuBERT for speech and PhoBERT-v2 for text to recognize emotions in Vietnamese. The method achieves high accuracy on benchmark datasets while maintaining real-time performance, making it suitable for practical applications.