A Reactive Agent-based Neural Network Car Following Model

This paper presented a novel approach to develop car following models using reactive agent techniques for mapping perceptions to actions. The results showed that the model outperformed the Gipps and Psychophysical family of car following models. The standing of this work is highlighted by its acceptance and publication in the proceedings of the International IEEE Conference on Intelligent Transportation Systems (ITS), which is now recognised as the premier international conference on ITS. The paper acceptance rate to this conference was 67 percent. The standing of this paper is also evidenced by its listing in international databases like Ei Inspec and IEEE Xplore. The paper is also listed in Google Scholar. Dr Dia co-authored this paper with his PhD student Sakda Panwai.

The Pineapple EST sequencing and microarray project

We have initiated an EST sequencing project to survey a range of expressed sequences from green fruit, yellow fruit, roots, and root-knot nematode infected root/gall tissues. In total, 5681 edited EST sequences were retrieved. Clone redundancy was high in the fruit libraries, with the combined fruit 1548 clone sequences clustering into just 634 contigs comprising 191 consensus sequences and 443 singletons. Half of all fruit EST clone sequences clustered within approximately 14 and 9% of contigs from green unripe and yellow ripe libraries respectively, indicating that a small subset of genes dominates the majority of the transcriptome. The root and root/gall libraries had lower levels of redundancy than the fruit libraries. Half of the root/gall ESTs clustered within approximately 40% of all contigs, indicating the roots possess a more complex transcriptome. Contig assembly and cluster analysis revealed major differences in the abundant gene sequences expressed between the unripe green and the ripe yellow fruit tissues, or gene sequences expressed between the weeks 1-4 and weeks 5-10 nematode infected gall vascular cylinder libraries.