Statistical monitoring tools are well established in the literature, creating organizational cultures such as Six Sigma or Total Quality Management. Nevertheless, most of this literature is based on normality assumption, e.g., law large numbers, and brings limitations towards truncated processes open questions field. This work was motivated by register elements related to water particles (relat...

This paper analyses Rosca's ARL as a general framework for automatic subroutine discovery. We review and compare a number of heuristics for code selection, and experimentally test their e ectiveness in the ARL framework. We also propose and analyse a new heuristic, the Saliency, and two extensions to ARL: di usion of the new subroutines through mutation and the MaxFit technique to adaptively ch...

Computing Bias-Optimal Policies Sridhar Mahadevan Department of Computer Science and Engineering University of South Florida Tampa, Florida 33620 [email protected] Abstract Average-reward reinforcement learning (ARL) is an undiscounted optimality framework that is generally applicable to a broad range of control tasks. ARL computes gain-optimal control policies that maximize the expected pa...

Power exponentiation is an important operation in modern cryptography. This operation can be efficiently calculated using the concept of the addition chain. In this paper, two new systematic methods, a Run-length method and a Hybrid method, are proposed to generate a short addition chain. The performance of these two methods are theoretically analyzed and it is shown that the Hybrid method is m...

The recently introduced triple exponentially weighted moving average (TEWMA) chart is the extended form of classical EWMA and double (DEWMA) charts. On other hand, auxiliary information-based (AIB) homogeneously ( HWMA AIB ) used for monitoring process location shifts ef...

Recently, monitoring quality of a process or product that is characterized by a function or profile is becoming more popular. Many applications are shown for profile monitoring. Most existing control schemes, which have been suggested for profile monitoring in the literatures, consider the independence assumption of observation within profiles. However, in certain situation, this assumption can...

Neural networks because of their abilities are used to patterns recognition. In statistical process control charts, a common cause variation distort expected form of unnatural patterns and so detection of assignable causes efficiently and precisely in a real-time is difficult. Therefore it would be logical to propose models based neural networks for recognition and analysis of patterns in proce...