The EWMA chart for the standard deviation is a useful tool for monitoring the variability of a process quality characteristic. The performance of this chart is usually evaluated under the assumption of known parameters. However, in practice, process parameters are estimated from an in-control Phase I data set. A modified EWMA control chart is proposed for monitoring the standard deviation when ...

This paper presents a method for detecting TCP SYN flooding attack using BENEF model. Our model relies on the significant parameters of anomalous network packets, the statistic of system behavior, and the decision with threshold and fuzzy rule-based technique. With fuzzy technique, rules or a set of rules corresponding with the appropriate membership value are designed for analysis and to find ...

Residual-based control charts are popular methods for statistical process control of autocorrelated processes. To implement these methods, a time series model of the process is required. The model must be estimated from data, in practice, and model estimation errors can cause the actual in-control average run length to differ substantially from the desired value. This article develops a method ...

In this letter, we develop a fixed-point arithmetic, low precision, implementation of an exponentially weighted moving average (EWMA) that is used in a neural network with plastic weights. We analyze the proposed design both analytically and experimentally, and we also evaluate its performance in the application of an attractor neural network. The EWMA in the proposed design has a constant rela...

Cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts are commonly used to detect small changes in the parameters of production processes. Recently, a new control structure was introduced, named as mixed EWMA–CUSUM control chart, which combined both charts. The current study provides a detailed comparison of these three types of control charts when the process p...

Identifying convergence in numerical optimization is an ever-present, difficult, and often subjective task. The statistical framework of Gaussian process surrogate model optimization provides useful measures for tracking optimization progress; however, the identification of convergence via these criteria has often provided only limited success and often requires a more subjective analysis. Here...

Classical techniques for clustering, such as k-means clustering, are very sensitive to the initial set of data centers, so it need to be rerun many times in order to obtain an optimal result. A relatively new clustering approach named Affinity Propagation (AP) has been devised to resolve these problems. Although AP seems to be very powerful it still has several issues that need to be improved. ...

Shewhart control charts have previously been suggested as a process control tool for use in routine linear accelerator (linac) output verifications. However, a comprehensive approach to process control has not been investigated for linac output verifications. The purpose of this work is to investigate a comprehensive process control approach to linac output constancy quality assurance (QA). The...

The Extended Exponentially Weighted Moving Average (extended EWMA) control chart is one of the charts and can be used to quickly detect a small shift. performance evaluated with average run length (ARL). Due deriving explicit formulas for ARL on two-sided extended EWMA trend autoregressive or AR(p) model has not been reported previously. aim this study derive as well AR(1) AR(2) models exponent...

The industrial sector is considered one of the fastest-growing sources greenhouse gases, due to excessive consumption energy required cope with growing production exhaustive products. statistical process monitoring (SPM) can be an effective tool for and controlling carbon emissions from industries. This article presents economic-statistical design combined Shewhart X¯ exponentially weighted mov...