• Radioisotope journal
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• v.10 no.3
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• pp.72-77
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• 1995

• The KSFM Journal of Fluid Machinery
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• v.3 no.2 s.7
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• pp.66-77
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• 2000

• Broadcasting and Media Magazine
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• v.21 no.3
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• pp.106-115
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• 2016

• KIPE Magazine
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• v.23 no.3
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• pp.48-52
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• 2018

• Electronics and Telecommunications Trends
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• v.7 no.1
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• pp.3-15
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• 1992

• 대한치과교정학회:학술대회논문집
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• 2003.10a
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• pp.101.3-102
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• 2003

• KIPE Magazine
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• v.15 no.3
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• pp.54-65
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• 2010

• KIPE Magazine
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• v.26 no.3
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• pp.39-46
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• 2021

• Journal of IKEEE
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• v.19 no.3
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• pp.415-423
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• 2015

The DO-178C guide, which is referenced as the software development guide when a certification of the airworthiness in the commercial airplane is acquired by FAA in US, is recently referenced for the local military aircraft airworthiness. This indicates that when the auditor of the military aircraft airworthiness looks over the software development documents, the auditor reviews if all of the documents are verified in accordance with the DO-178C guide. However, when we developed the military aircraft intercom, We developed its control software in accordance with the CMMI level 3, since there were no requirements for the compliance of the DO-178C guide. Therefore, When we consider the airworthiness of this intercomm system, The analysis for how much the software development based on the CMMI level 3 is different from the DO-178C guide is needed to prepare the essential software documents additionally. Thus, This study analyzes the differences between CMMI level 3 and DO-178C guide and provides that which data on the CMMI level 3 is necessary for the compliance of the aircraft airworthiness comparing with the DO-178C. The analyzed result can be applied at the software development of the other military aircraft avionics equipment based on the CMMI model environment considering the compliance of the military aircraft airworthiness.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.2
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• pp.129-137
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• 2020

Currently, The autonomous vehicle market is researching and developing four-level autonomous vehicles beyond the commercialization of three-level autonomous vehicles. Because unlike the level 3, the level 4 autonomous vehicle has to deal with an emergency directly, the most important aspect of a four-level autonomous vehicle is its stability. In this paper, we propose an Optimized Vehicle Routing System (OVRS) that determines the route with the lowest probability of an accident at the destination of the vehicle rather than an immediate response in an emergency. The OVRS analyzes road and surrounding vehicle information collected by The RSU communication to predict road hazards, and sets the route for the safer and faster road. The OVRS can improve the stability of the vehicle by executing the route guidance according to the road situation through the RSU on the road like the network routing method. As a result, the RPNN of the ASICM, one of the OVRS modules, was about 17% better than the CNN and 40% better than the LSTM. However, because the study was conducted in a virtual environment using a PC, the possibility of accident of the VPDM was not actually verified. Therefore, in the future, experiments with high accuracy on VPDM due to the collection of accident data and actual roads should be conducted in real vehicles and RSUs.