Ship escape, survival and rescue detection system for Great Lakes winter shipboard operations : final report /

Cover title.

A comparison of microcomputer packages for network-based highway planning. Interim report.

Texas State Department of Highways and Public Transportation, Transportation Planning Division, Austin

Description of an experimental on-line, minicomputer-based information retrieval system /

Thesis (M. S.)--University of Illinois at Urbana-Champaign.

The five orders of architecture; the casting of shadows and the first principles of construction, based on the system of Vignola.

Mode of access: Internet.

The network security center : a system level approach to computer network security /

Includes bibliographical references (p. 55).

Operator's manual : detection system, ground movement (Honeywell Inc. MAGID T4, DT-509/GSQ), FSN 6350-150-6807.

"14 February 1972."

Implementation of a triple modular redundant FPGA based safety critical system for reliable software execution

This paper describes the implementation of a TMR (Triple Modular Redundant) microprocessor system on a FPGA. The system exhibits true redundancy in that three instances of the same processor system (both software and hardware) are executed in parallel. The described system uses software to control external peripherals and a voter is used to output correct results. An error indication is asserted whenever two of the three outputs match or all three outputs disagree. The software has been implemented to conform to a particular safety critical coding guideline/standard which is popular in industry. The system was verified by injecting various faults into it.

A neural network based technique for automatic classification of road cracks

This paper presents a neural network based technique for the classification of segments of road images into cracks and normal images. The density and histogram features are extracted. The features are passed to a neural network for the classification of images into images with and without cracks. Once images are classified into cracks and non-cracks, they are passed to another neural network for the classification of a crack type after segmentation. Some experiments were conducted and promising results were obtained. The selected results and a comparative analysis are included in this paper.