Generally, the traditional Shewhart p chart has been developed by for charting the binomial data. This chart has been developed using the normal approximation with condition as low defect level and the small to moderate sample size. In real applications, however, are away from these assumptions due to skewness in the exact distribution. In this paper, a modified Exponentially Weighted Moving Av...

Fog computing (FC) is a networking paradigm where wireless devices known as fog nodes are placed at the edge of network (close to Internet Things (IoT) devices). provide services in lieu cloud. Thus, improving performance and making it attractive social media-based systems. Security issues one most challenges encountered FC. In this paper, we propose an anomaly-based Intrusion Detection Prevent...

Serial correlation can seriously affect the performance of traditional control charts. Many authors have studied the effect of autocorrelation on EWMA control charts and have shown how to modify the control limits to account for autocorrelation. In this paper we compare three different estimation methods for the variance of the EWMA statistic that is adapted to autocorrelated data. This compari...

Adaptive Cumulative SUM charts (ACUSUM) have been recently proposed for providing an overall good detection over a range of mean shift sizes. The basic idea of the ACUSUM chart is to first adaptively update the reference value based on an Exponentially Weighted Moving Average (EWMA) estimate and then to assign a weight on it using a certain type of weighting function. A linear weighting functio...

The existing optimal design of the fixed sampling interval S2-EWMA control chart to monitor the sample variance of a process is based on the average run length (ARL) criterion. Since the shape of the run length distribution changes with the magnitude of the shift in the variance, the median run length (MRL) gives a more meaningful explanation about the in-control and out-of-control performances...