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.

Rapid Facilitation of Ultrasound Production and Lordosis in Female Hamsters by Horizontal Cuts Between the Septum and Preoptic Area

Horizontal cuts between the septum and preoptic area (anterior roof deafferentation, or ARD) dramatically affect sexual behavior, and in ways that could explain a variety of differences across behavioral categories (precopulatory, copulatory), species, and the sexes. Yet little is known about how these effects develop. Such information would be useful generally and could be pivotal in clarifying the mechanism for ultrasonic vocalization in female hamsters. Ultrasounds serve these animals as precopulatory signals that can attract males and help initiate mating. Their rates can be increased by either ARD or lesions of the ventromedial hypothalamus (VMN). If these effects are independent, they would require a mechanism that includes multiple structures and pathways within the forebrain and hypothalamus. However, it currently is not clear if they are independent: VMN lesions could affect vocalization by causing incidental damage to the same fibers targeted by ARD. Fortunately, past studies of VMN lesions have described a response with a very distinctive time course. This raises the possibility of assessing the independence of the two lesion effects by describing just the development of the response to ARD. To accomplish this, female hamsters were observed for levels of ultrasound production and lordosis before and after control surgery or ARD. As expected, both behaviors were facilitated by these cuts. Further, these effects began to appear by two days after surgery and were fully developed by six days. These results extend previous descriptions of the ARD effect by describing its development and time course. In turn, the rapid responses to ARD suggest that these cuts trigger disinhibitory changes in pathways that differ from those affected by VMN lesions. 2013

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.