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System monitors are applications used to monitor other systems (often mission critical) and take corrective actions upon a system failure. Rather than reactively take action after a failure, the potential of fuzzy logic to anticipate and proactively take corrective actions is explored here. Failures adversely affect a system's non-functional qualities (e.g., availability, reliability, and usability) and may result in a variety of losses such as data, productivity, or safety losses. The detection and prevention of failures necessarily improves a critical system's non-functional qualities and avoids losses. The paper is self contained and reviews set and logic theory, fuzzy inference systems (FIS), explores parametrization, and tests the neighborhood of rule thresholds to evaluate the potential for anticipating failures. Results demonstrate detectable gradients in FIS state spaces and means fuzzy logic based system monitors can anticipate rule violations or system failures.

The impetus behind data analytics and integration is the need for greater insight and data visibility, but since a growing share of our data is multimedia, there is a parallel need for methods that can align multimedia data. This paper explores georeferencing, which is used to combine spatial datasets and used here to align map images to 2D GIS models. This paper surveys various approaches for building the key components of a georeferencing solution, notes their strengths and weaknesses, and comments on their trajectory to help orient future work. The implementation presented here uses Hough transforms for feature detection, nearest neighbor correspondences with simplistic similarity measures, and a population based optimizer. The comparison among metaheuristics has shown that Differential Evolution (DE) frameworks appear especially suited for this problem. In particular, the controlled randomization of DE parameters appears to display the best performance in terms of execution time and competitive performance in terms of function evaluations even with respect to more complex memetic implementations.

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