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A new algorithm is presented which deals with the problem of detecting small moving targets in infrared image sequences that also contain drifting and evolving clutter. Through development of models of the temporal behavior of the static background, target and cloud edge on a single pixel basis, the new algorithm employing the connecting line of the stagnation points (CLSP) of the temporal profile as the baseline is created and tested. The deviation of the temporal profile and its CLSP is analyzed and it is determined that the distribution of the residual temporal profile obtained by subtracting the baseline from the temporal profile can be modeled by a Gaussian distribution. The occurrences of the targets have intensity values significantly different to the distribution of the residual temporal profile. Unlike the conventional 3-D method, this new algorithm operates on the temporal profile in 1-D space, not in 3-D space, thus having a higher computational efficiency. Experiments with real IR image sequences have proved the validity of the new approach.

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This paper proposes an approach to quantify the concept of resiliency in terms of Quality of Control (QoC) of a control system. Based on this concept, an intelligent resilient control algorithm (RCA) is presented for wireless networked control systems (WNCS) to maintain operational normalcy in face of wireless interference incidents, such as Radio Frequency (RF) jamming and signal blocking. The proposed algorithm closes the control loop with wireless sensors feasible by significantly increasing control system's tolerance to data packet loss and delay caused by wireless interference. The proposed algorithm, along with other well developed wireless technologies, has the potential to enable implementing wireless sensors widely in the next generation of industrial automation and control systems.