A Flow Trace Generator using Graph-based Traffic Classification Techniques

We propose a novel methodology to generate realistic network flow traces to enable systematic evaluation of network monitoring systems in various traffic conditions. Our technique uses a graph-based approach to model the communication structure observed in real-world traces and to extract traffic templates. By combining extracted and user-defined traffic templates, realistic network flow traces that comprise normal traffic and customized conditions are generated in a scalable manner. A proof-of-concept implementation demonstrates the utility and simplicity of our method to produce a variety of evaluation scenarios. We show that the extraction of templates from real-world traffic leads to a manageable number of templates that still enable accurate re-creation of the original communication properties on the network flow level.

Graph-Based Multi-Surface Segmentation of OCT Data Using Trained Hard and Soft Constraints

Optical coherence tomography (OCT) is a well-established image modality in ophthalmology and used daily in the clinic. Automatic evaluation of such datasets requires an accurate segmentation of the retinal cell layers. However, due to the naturally low signal to noise ratio and the resulting bad image quality, this task remains challenging. We propose an automatic graph-based multi-surface segmentation algorithm that internally uses soft constraints to add prior information from a learned model. This improves the accuracy of the segmentation and increase the robustness to noise. Furthermore, we show that the graph size can be greatly reduced by applying a smart segmentation scheme. This allows the segmentation to be computed in seconds instead of minutes, without deteriorating the segmentation accuracy, making it ideal for a clinical setup. An extensive evaluation on 20 OCT datasets of healthy eyes was performed and showed a mean unsigned segmentation error of 3.05 ±0.54 μm over all datasets when compared to the average observer, which is lower than the inter-observer variability. Similar performance was measured for the task of drusen segmentation, demonstrating the usefulness of using soft constraints as a tool to deal with pathologies.

Comparative Ultrastructure and Molecular Phylogeny of Selenidium melongena n. sp and S. terebellae Ray 1930 Demonstrate Niche Partitioning in Marine Gregarine Parasites (Apicomplexa)

Gregarine apicomplexans are a diverse group of single-celled parasites that have feeding stages (trophozoites) and gamonts that generally inhabit the extracellular spaces of invertebrate hosts living in marine, freshwater, and terrestrial environments. Inferences about the evolutionary morphology of gregarine apicomplexans are being incrementally refined by molecular phylogenetic data, which suggest that several traits associated with the feeding cells of gregarines arose by convergent evolution. The study reported here supports these inferences by showing how molecular data reveals traits that are phylogenetically misleading within the context of comparative morphology alone. We examined the ultrastructure and molecular phylogenetic positions of two gregarine species isolated from the spaghetti worm Thelepus japonicus: Selenidium terebellae Ray 1930 and S. melongena n. sp. The ultrastructural traits of S. terebellae were very similar to other species of Selenidium sensu stricto, such as having vermiform trophozoites with an apical complex, few epicytic folds, and a dense array of microtubules underlying the trilayered pellicle. By contrast, S. melongena n. sp. lacked a comparably discrete assembly of subpellicular microtubules, instead employing a system of fibrils beneath the cell surface that supported a relatively dense array of helically arranged epicytic folds. Molecular phylogenetic analyses of small subunit rDNA sequences derived from single-cell PCR unexpectedly demonstrated that these two gregarines are close sister species. The ultrastructural differences between these two species were consistent with the fact that S. terebellae infects the inner lining of the host intestines, and S. melongena n. sp. primarily inhabits the coelom, infecting the outside wall of the host intestine. Altogether, these data demonstrate a compelling case of niche partitioning and associated morphological divergence in marine gregarine apicomplexans. (C) 2014 Elsevier GmbH. All rights reserved.