• Journal of the Korean Society for Precision Engineering
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• v.12 no.11
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• pp.140-147
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• 1995

This paper deals with conversion from the STL file to the Slice to the Slice cross-sectional information for Stereolithography. The STL file is widely used for Stereolithography, but it is very difficult to convert STL file into Slice file directly. Because it consists of an ordered list of triangular net without any topological information other than the orientation of each facet. So, The system is accomplished by data flow through several intermediate stages such as Reference. SL1. .SL2L. .SL3. and .SLC file. The data processing is performed in 5 steps: 1) Create a Reference file including common information. 2) Modify STL file within the effective range of SL machine. 3) Calculate a point of intersection between plane equation and line equation. 4) Sort z values in ascending order using quick sort algorithm. 5) Search the adjacent points and formulate a closed loop usingsingly linked linear list. The system is developed by using Borland C++ 3.1 compiler in the environment of Pentium PC, and verified to be satisfactory by making some prototypes of electric household appliances.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.91-97
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• 2022

There is hare and tortoise racing algorithm(HTA) for single-source(SS) singly linked list(SLL) with O(n) time complexity. But the fast method is unknown for general graph with multi-source, multi-destination, and multi-branch(MSMDMB). This paper suggests linear time cycle detection algorithm for given undirected and digraph with MSMDMB. The proposed method reduced the given graph G contained with unnecessary vertices(or nodes) to cycle into reduced graph G' with only necessary vertices(or nodes) to cycle based on the condition of cycle formation. For the reduced graph G', we can be find the cycle set C and cycle length λ using linear search within linear time. As a result of experiment data, the proposed algorithm can be obtained the cycle for whole data.