Biomedical subjects

S Y Sohn

Publications and source records attributed to S Y Sohn.

3 recordsLinked to original sources

PubMed1999

Quality function deployment applied to local traffic accident reduction.

One of the major tasks of police stations is the management of local road traffic accidents. Proper prevention policy which reflects the local accident characteristics could immensely help individual police stations in decreasing various severity levels of road traffic accidents. In order to relate accident variation to local driving environmental characteristics, we use both cluster analysis and Poisson regression. The fitted result at the level of each cluster for each type of accident severity is utilized as an input to quality function deployment. Quality function deployment (QFD) has been applied to customer satisfaction in various industrial quality improvement settings, where several types of customer requirements are related to various control factors. We show how QFD enables one to set priorities on various road accident control policies to which each police station has to pay particular attention.

Accident Prevention↗

PubMed1999

A comparative study for stepwise correlated binary regression.

Real-time monitored binary data are often recorded along with a large amount of associated covariates for biomedical image processing. Serially measured binary outcomes and covariates could be autocorrelated. Appropriate variable selection schemes are necessary to find a set of influential covariates on the changes in the correlated binary outcomes. Selected variables can be used as feedback information to reduce the dimension of the database. In this context, we examine the performance of the stepwise correlated binary regression. Several realistic situations of the real-time monitored binary data are considered in Monte-Carlo simulation. Results of a simulation study are discussed.

Algorithms↗

PubMed1998

Meta-analysis on total braking time.

The total braking time (TBT) distribution is used as an input to two important traffic safety parameters: minimum following gap and stopping sight distance. It is therefore important to accurately estimate the TBT distribution. However, the previously published results on TBT distribution vary widely and confuse practitioners. In this paper, a meta-analysis is used in an effort to investigate the sources of variation in the studies of TBT. According to the results of the meta-analysis, significant characteristics of the mean of total braking time are the awareness level of the driver and the country in which the experiment took place. In addition to these two characteristics, both the type of brake stimulus and the distance away from the brake stimulus are found to be influential characteristics on the variance of total braking time. Based on several combinations of these factors, TBT distributions are reconstructed. It is recommended that the percentile estimates of TBT used for the minimum following gap and stopping sight distance need to be adjusted.

Analysis of Variance↗