Parameter free AEWMA control chart for dispersion in semiconductor manufacturing.

The study presents a new parameter free adaptive exponentially weighted moving average (AEWMA) control chart tailored for monitoring process dispersion, utilizing an adaptive approach for determining the smoothing constant. This chart is crafted to adeptly detect shifts within anticipated ranges in process dispersion by dynamically computing the smoothing constant. To assess its effectiveness, the chart's performance is measured through concise run-length profiles generated from Monte Carlo simulations.

Risk adjusted EWMA control chart based on support vector machine with application to cardiac surgery data.

In the current study, we demonstrate the use of a quality framework to review the process for improving the quality and safety of the patient in the health care department. The researchers paid attention to assessing the performance of the health care service, where the data is usually heterogeneous to patient's health conditions. In our study, the support vector machine (SVM) regression model is used to handle the challenge of adjusting the risk factors attached to the patients.

Knowledge and Attitude of Undergraduate Health Professions Students towards Hepatitis B and C.

The current study sought to establish the attitude and knowledge level of medical science students in Tibah University towards hepatitis B and C. A cross-sectional study involving 369 students drawn from the faculties of medicine, dentistry, applied medical sciences, pharmacy, nursing, and medical rehabilitation sciences was conducted where a standardised questionnaire was used to determine the attitude and knowledge level of undergraduate students drawn from the college of medicine in Tibah University, Saudi Arabia, regarding viral infections. With a mean of 0.