The ever increasing number of malicious software (malware) requires domain experts to shift their analysis process towards more individualized approaches to acquire more information about presently unknown malware samples. KAMAS is a knowledge-assisted visual analytics prototype for behavioral malware analysis, which allows IT-security experts to categorize and store potentially harmful system ...

Abstract It is shown how infinite sequences of densities with defined properties can be used to evaluate the expected performance of mathematical aggregation rules for elicited densities. The performance of these rules is measured through the expected variance, calibration, and expected Brier score of the aggregate. A general result for the calibration of the arithmetic average of densities fro...

ABSTRACT Commodity trade mispricing, especially the undervaluation of commodity exports, disproportionately harms low-income countries that depend on exports for most their export earnings. Such should (re)consider adopting rule-based pricing methods as a prescriptive alternative to transaction-based valuation systems. This article firmly grounds in market parameters. It calls hybrid form marke...

In this paper, we present a feasibility study in automating the insurance claims processing system related to automotive sector. In automobile insurance claims processing, usually an adjuster is sent to specific location from where the claim has been registered to physically inspect the validity of the claim. Sending adjusters for each and every such claim imposes a cost factor. With the increa...

In this paper, we propose diagnosis of steady-state process behaviour using rules derived from the signed directed graph(SDG) representing the interaction among the process variables. All abnormalities are correlated using backward reasoning through rules to yield a diagnosis. These rules can be added with experimental rules which are obtained from experts on plant operation.

Credit card frauds are unauthorized transactions that are made or attempted by a person or an organization that is not authorized by the card holders. In addition to machine learning-based techniques, credit card companies often employ domain experts to manually specify rules that exploit domain knowledge for improving the detection process. Over time, however, as new (fraudulent and legitimate...