Abstract Profile monitoring in statistical quality control has attracted attention of many researchers recently. A profile is a function between response variables and one or more independent variables. There have been only a limited number of researches on monitoring multivariate profiles. Indeed, monitoring correlated multivariate profiles is a new subject in the fileld of statistical proces...

abstract profile monitoring in statistical quality control has attracted attention of many researchers recently. a profile is a function between response variables and one or more independent variables. there have been only a limited number of researches on monitoring multivariate profiles. indeed, monitoring correlated multivariate profiles is a new subject in the fileld of statistical process...

Many modern industrial processes are capable of generating rich and complex data records that do not readily permit the use of traditional statistical process control techniques. For example, a “single observation” from a process might consist of n pairs of (x, y) data that can be described as y = f(x) when the process is in-control. Such data structures or relationships between y and x have be...

In many quality control applications, use of a single (or several distinct) quality characteristic(s) is insufficient to characterize the quality of a produced item. In an increasing number of cases, a response curve (profile), is required. Such profiles can frequently be modeled using linear or nonlinear regression models. In recent research others have developed multivariate T 2 control chart...

Multiscale Principal Component Analysis (MSPCA) combines the ability of PCA to decorrelate the variables by extracting a linear relationship, with that of wavelet analysis to extract deterministic features and approximately decorrelate autocorrelated measurements. MSPCA computes the PCA of the wavelet coefficients at each scale, followed by combining the results at relevant scales. Due to its m...

The quality assurance of medical practice in most countries This issue is of obvious concern for monitoring clinical practice, which requires early warning of poor peris effected through a mixture of informal assessment and peer review, and through more formal accreditation, creformance before too many patients are harmed. (3) Case-mix varies among practices, and adjustment for dentialing or de...

Recently, a novel multivariate statistical process monitoring method, known as dissimilarity algorithm(DISSIM), has been developed based on the idea that a change of operating condition can be detected by monitoring a distribution of process data set, where a dissimilarity index is introduced to quantitatively evaluate the difference between distributions of process data. However, as a fixed-mo...

In this paper, a modified independent component analysis (ICA) and its application to process monitoring are proposed. The basic idea of this approach is to use the modified ICA to extract some dominant independent components from normal operating process data and to combine them with statistical process monitoring techniques. The proposed monitoring method is applied to fault detection and ide...

Although refractory epileptic patients suffer from uncontrolled seizures, their quality of life (QoL) may be improved if the seizure can be predicted in advance. In the preictal period, the excessive neuronal activity of epilepsy affects the autonomic nervous system. Since the fluctuation of the R-R interval (RRI) of an electrocardiogram (ECG), called heart rate variability (HRV), reflects the ...

The literature on the performance evaluation of medical expert system is extensive, yet most of the techniques used in the early stages of system development are inappropriate for deployed expert systems. Because extensive clinical and informatics expertise and resources are required to perform evaluations, efficient yet effective methods of monitoring performance during the long-term maintenan...