Disease monitoring and surveillance play a crucial role in control and eradication programs, as it is important to track implemented strategies in order to reduce and/or eliminate a specific disease. The objectives of this study were to assess the performance of different statistical monitoring methods for endemic disease control program scenarios, and to explore what impact of variation (noise...

Statistical process control is a very useful method to improve the product quality and reduce reworks and scraps. In a production environment, control charts are the most important tool to determine whether a process is in-control or out-of-control. Control charts are to detect the occurrence of the shifts in a process rapidly so that their causes can be found and the necessary corrective actio...

Objectives: To evaluate and compare the performance of various quality control methods for nuchal translucency (NT) measurements. Methods: Fetal NT measurements performed over a oneyear period in a single center were used for the study. The retrospective quality review methods proposed by the Fetal Medicine Foundation (FMF) and the Woman & Infants Hospital of Rhode Island (WIHRI) were assessed ...

  Although control charts are very common to monitoring process changes, they usually do not indicate the real time of the changes. Identifying the real time of the process changes is known as change-point estimation problem. There are a number of change point models in the literature however most of the existing approaches are dedicated to normal processes. In this paper we propose a novel app...

Abstract Machine learning-based condition monitoring of wind turbines’ critical components is an active area research, especially for pitch systems, which suffer from a high failure rate. In this work, we successfully predicted and detected the high-temperature fault electric motor by analyzing SCADA data through ensemble approach. For that, normal behavior models to predict temperature were co...