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Available Article Reprints:
- Testing Concrete with Neural Networks
- Donald G. Pratt and Jeannette Lawrence
Nondestructive testing (NDT) methods are techniques used to obtain information about the properties or the internal condition of an object without damaging the object. Thus NDT methods are extremely valuable in assessing the condition of structures, such as bridges, buildings, and highways. Because of the current emphasis on rehabilitation and renovation of structures, there is a critical need for the development of NDT methods that can be used to evaluate the condition of structures so that effective repair procedures can be undertaken.
- Decoding Numerical Sequences
- James R. Johnson, Netrologic, Inc. 5200 Springfield Pike, Suite 312 Dayton, OH 45431
The ability to predict data sequences is important in data transmission due to the need to provide error correction. Certain algorithms can predict repetitive code with good accuracy, but fail in the presence of noisy code sequences. A back propagation neural network was trained in noisy data and was able to predict code sequences with much better than random accuracy based on the statistics that it extracted autonomously from the code data structures. Accuracies from 62% to 93% correct were obtained depending upon the initial conditions and the presence or absence of noise. Higher accuracies could probably be obtained by training a network with a wider variety of training samples.
- Reducing Hospital Costs
- Jeannette Lawrence
A new hospital information and patient prediction system has improved the quality of care, reduced the death rates and saved millions of dollars in resources at Anderson Memorial Hospital in South Carolina. The CRTS/QURI system uses neural networks trained with BrainMaker (from California Scientific) to predict the severity of illness and use of hospital resources. Developed by Steven Epstein, Director of Systems Development and Data Research, the CRTS/QURI system's goal is to provide educational information and feedback to physicians and others to improve resource efficiency and patient care quality.
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