Semantics-based web service discovery using information retrieval techniques

This paper demonstrates an experimental study that examines the accuracy of various information retrieval techniques for Web service discovery. The main goal of this research is to evaluate algorithms for semantic web service discovery. The evaluation is comprehensively benchmarked using more than 1,700 real-world WSDL documents from INEX 2010 Web Service Discovery Track dataset. For automatic search, we successfully use Latent Semantic Analysis and BM25 to perform Web service discovery. Moreover, we provide linking analysis which automatically links possible atomic Web services to meet the complex requirements of users. Our fusion engine recommends a final result to users. Our experiments show that linking analysis can improve the overall performance of Web service discovery. We also find that keyword-based search can quickly return results but it has limitation of understanding users’ goals

Deterministic methods in stochastic optimal control

SIGLEAvailable from British Library Document Supply Centre- DSC:0678.231F(AD-A--260-478)(microfiche) / BLDSC - British Library Document Supply CentreGBUnited Kingdo

A cell-type-specific role for murine Commd1 in liver inflammation

The transcription factor NF-kappaB plays a critical role in the inflammatory response and it has been implicated in various diseases, including non-alcoholic fatty liver disease (NAFLD). Although transient NF-kappaB activation may protect tissues from stress, a prolonged NF-kappaB activation can have a detrimental effect on tissue homeostasis and therefore accurate termination is crucial. Copper Metabolism MURR1 Domain-containing 1 (COMMD1), a protein with functions in multiple pathways, has been shown to suppress NF-kappaB activity. However, its action in controlling liver inflammation has not yet been investigated. To determine the cell-type-specific contribution of Commd1 to liver inflammation, we used hepatocyte and myeloid-specific Commd1-deficient mice. We also used a mouse model of NAFLD to study low-grade chronic liver inflammation: we fed the mice a high fat, high cholesterol (HFC) diet, which results in hepatic lipid accumulation accompanied by liver inflammation. Depletion of hepatocyte Commd1 resulted in elevated levels of the NF-kappaB transactivation subunit p65 (RelA) but, surprisingly, the level of liver inflammation was not aggravated. In contrast, deficiency of myeloid Commd1 exacerbated diet-induced liver inflammation. Unexpectedly we observed that hepatic and myeloid Commd1 deficiency in the mice both augmented hepatic lipid accumulation. The elevated levels of proinflammatory cytokines in myeloid Commd1-deficient mice might be responsible for the increased level of steatosis. This increase was not seen in hepatocyte Commd1-deficient mice, in which increased lipid accumulation appeared to be independent of inflammation. Our mouse models demonstrate a cell-type-specific role for Commd1 in suppressing liver inflammation and in the progression of NAFLD

Human Perception of the Measurement of a Network Attack Taxonomy in Near Real-Time

Part 3: Peace, War, Cyber-Security and ICTInternational audienceThis paper investigates how the measurement of a network attack taxonomy can be related to human perception. Network attacks do not have a time limitation, but the earlier its detected, the more damage can be prevented and the more preventative actions can be taken. This paper evaluate how elements of network attacks can be measured in near real-time(60 seconds). The taxonomy we use was developed by van Heerden et al (2012) with over 100 classes. These classes present the attack and defenders point of view. The degree to which each class can be quantified or measured is determined by investigating the accuracy of various assessment methods. We classify each class as either defined, high, low or not quantifiable. For example, it may not be possible to determine the instigator of an attack (Aggressor), but only that the attack has been launched by a Hacker (Actor). Some classes can only be quantified with a low confidence or not at all in a sort (near real-time) time. The IP address of an attack can easily be faked thus reducing the confidence in the information obtained from it, and thus determining the origin of an attack with a low confidence. This determination itself is subjective. All the evaluations of the classes in this paper is subjective, but due to the very basic grouping (High, Low or Not Quantifiable) a subjective value can be used. The complexity of the taxonomy can be significantly reduced if classes with only a high perceptive accuracy is used