Acquisition of a Computational Cluster Grid for Research and Education in Science and Mathematics

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This project, establishing two cluster machines with some flexible networking between them in order to conduct research in various CS and science disciplines, supports, among others, the following research areas: intelligent agents, network control and management, data mining, and graph theory. The development of e-learning and navigation training systems using multi-agent and knowledge-based reasoning techniques presents an efficient, real-time, intelligent and interactive distributed training environment for an educational learning system and seafarers navigation training system. An understanding of network control and management system using cluster grid provides a new approach to better handle critical tasks such as service provision, fault detection, and network protection where traditional approaches are not scalable/reliable or too complex. The development of efficient and effective machine learning, text mining, and natural language processing (NLP) techniques for bioinformatics systems (e.g. gene disease associations) aids in analyzing volumes of electronic biomedical texts. Computer programs automatically generate interesting graph theory conjectures for theorists to prove or refute.