Modelling Road Saturation Dynamics on a Complex Transportation Network Based on GPS Navigation Software Data

2020 ◽  
pp. 136-149
Author(s):  
Mariana Cubero-Corella ◽  
Esteban Durán-Monge ◽  
Warner Díaz ◽  
Esteban Meneses ◽  
Steffan Gómez-Campos
Keyword(s):  
Transportation Network ◽  
Gps Navigation ◽  
Navigation Software

Layout Overlay Techniques to Improve Failure Analysis

1998 ◽  
Author(s):  
Christian Burmer ◽  
Siegfried Görlich ◽  
Siegfried Pauthner
Keyword(s):  
Failure Analysis ◽  
Focused Ion Beam ◽  
New Technologies ◽  
Ion Beam ◽  
Image Correlation ◽  
Microelectronic Devices ◽  
Overlay Technique ◽  
Correlation Techniques ◽  
Navigation Software ◽  
Image Format

Abstract New layout overlay technique has been developed based on standard image correlation techniques to support failure analysis in modern microelectronic devices, which are critical to analyze because they are realized in new technologies using sub-ìm design rules, chemical mechanical polishing techniques (CMP) and autorouted design techniques. As the new technique is realized as an extension of a standard CAD-navigation software and as it makes use of standard image format "TIFF" for data input, which is available at all modern equipments for failure analysis, these technique can be applied to all modern failure analysis methods. Here examples are given for three areas of application: circuit modification using Focused Ion Beam (FIB), support of preparation for backside inspection and fault localization using emission microscopy.

Best Neighbor Heuristic Search for Finding Minimum Paths in Transportation Networks

1998 ◽  
Vol 1651 (1) ◽  
pp. 48-52 ◽  
Author(s):  
Jeffrey L. Adler
Keyword(s):  
Heuristic Search ◽  
Transportation Networks ◽  
Transportation Network ◽  
Search Problems ◽  
A Algorithm ◽  
Running Time ◽  
Search Effort ◽  
Wide Range ◽  
Path Search ◽  
Sparse Networks

For a wide range of transportation network path search problems, the A* heuristic significantly reduces both search effort and running time when compared to basic label-setting algorithms. The motivation for this research was to determine if additional savings could be attained by further experimenting with refinements to the A* approach. We propose a best neighbor heuristic improvement to the A* algorithm that yields additional benefits by significantly reducing the search effort on sparse networks. The level of reduction in running time improves as the average outdegree of the network decreases and the number of paths sought increases.

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