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A Prediction Modeling Framework For Noisy Welding Quality Data, Junheung Park Jan 2015

A Prediction Modeling Framework For Noisy Welding Quality Data, Junheung Park

Wayne State University Dissertations

Numerous and various research projects have been conducted to utilize historical manufacturing process data in product design. These manufacturing process data often contain data inconsistencies, and it causes challenges in extracting useful information from the data. In resistance spot welding (RSW), data inconsistency is a well-known issue. In general, such inconsistent data are treated as noise data and removed from the original dataset before conducting analyses or constructing prediction models. This may not be desirable for every design and manufacturing applications since every data can contain important information to further explain the process. In this research, we propose a prediction …


Predictive Analytics For Disease Condition Of Patients In Emergency Department, Azade Tabaie Jan 2015

Predictive Analytics For Disease Condition Of Patients In Emergency Department, Azade Tabaie

Wayne State University Theses

Emergency Departments (EDs) in hospitals are experiencing severe crowding and prolonged patient waiting times. The reported crowding in hospitals shows patients in hospital hallways, long waiting times and full occupancy of ED beds. ED crowding has several potential unfavorable effects including patients and staff frustration, lower patient satisfaction and poor health outcomes. The primary motivations behind this study are shortening the patients’ waiting time and improving patient satisfaction and level of care.

The very initial interaction between clinicians and a patient is recorded on nurse triage notes which contain details of the reason for patient’s visit including specific symptoms and …