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Engineering Commons

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Electrical and Computer Engineering

Missouri University of Science and Technology

2024

Data models

Articles 1 - 2 of 2

Full-Text Articles in Engineering

Controller Area Network With Flexible Data Rate (Can Fd) Eye Diagram Prediction, Junyong Park, Manho Lee, Shinyoung Park, Jonghoon Kim, Joungho Kim, Donghyun Kim Jan 2024

Controller Area Network With Flexible Data Rate (Can Fd) Eye Diagram Prediction, Junyong Park, Manho Lee, Shinyoung Park, Jonghoon Kim, Joungho Kim, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

A method for predicting the eye diagram for a controller area network with a flexible data rate (CAN FD) is proposed in this article. A CAN FD changes a data rate according to the status to overcome the limitation of latency. In other words, when data to be transmitted are accumulated, the CAN FD increases the data rate up to 5 Mb/s. The CAN FD has a bus topology consisting of multiple electronic control units, which results in a significant amount of signal reflection. Thus, the above causes the signal integrity analysis uncertain. To avoid this, this article proposes a …


Multiple Imputation For Robust Cluster Analysis To Address Missingness In Medical Data, Arnold Harder, Gayla R. Olbricht, Godwin Ekuma, Daniel B. Hier, Tayo Obafemi-Ajayi Jan 2024

Multiple Imputation For Robust Cluster Analysis To Address Missingness In Medical Data, Arnold Harder, Gayla R. Olbricht, Godwin Ekuma, Daniel B. Hier, Tayo Obafemi-Ajayi

Mathematics and Statistics Faculty Research & Creative Works

Cluster Analysis Has Been Applied To A Wide Range Of Problems As An Exploratory Tool To Enhance Knowledge Discovery. Clustering Aids Disease Subtyping, I.e. Identifying Homogeneous Patient Subgroups, In Medical Data. Missing Data Is A Common Problem In Medical Research And Could Bias Clustering Results If Not Properly Handled. Yet, Multiple Imputation Has Been Under-Utilized To Address Missingness, When Clustering Medical Data. Its Limited Integration In Clustering Of Medical Data, Despite The Known Advantages And Benefits Of Multiple Imputation, Could Be Attributed To Many Factors. This Includes Methodological Complexity, Difficulties In Pooling Results To Obtain A Consensus Clustering, Uncertainty Regarding …