IO Bound Property: A System Perspective Evaluation

File systems have been mostly benchmarked as per the application perspective. This approach hides all the underlying complexities of the system including the actual I/O being done with the secondary storage device like magnetic disk. The IO bound property of a file system is necessarily to be evaluated because the most dominant performance limiting factor of a file system is its I/O operation with secondary storage device. This IO bound property of file system dictates the quantity and frequency of IO that a file system does with secondary storage device. In this paper, we argue system perspective of file system benchmarks and develop a benchmark to evaluate some common disk file systems for IO bound property. The goal of this paper is to better understand the behavior of file systems and unveil the low level complexities faced by file systems

TOWARDS ARTIFICIAL NEURAL NETWORK MODEL TO DIAGNOSE THYROID PROBLEMS

Medical diagnosis can be viewed as a pattern classification problem: based a set of input features the goal is to classify a patient as having a particular disorder or as not having it. Thyroid hormone problems are the most prevalent problems nowadays. In this paper an artificial neural network approach is developed using a back propagation algorithm in order to diagnose thyroid problems. It gets a number of factors as input and produces an output which gives the result of whether a person has the problem or is healthy. It is found that back propagation algorithm is proved to be having high sensitivity and specificity

1997-1998 Bulletin

Volume 108, Number 4. Scanned from the copy held in the Registrar\u27s Office.https://ecommons.udayton.edu/bulletin/1039/thumbnail.jp