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Study on the Establishment of Risk Assessment Criteria for the Dynamic Reliability Test of Performance Improvement Weapon System using Recycling Software
Hunyong Shin, Young-Soo Choi, Min-Ho Park, Hyung-suk Kim, Dae-San Oh, Jong-Kyu Kim, Jong-Geun Kim, Sungshin Kim
http://doi.org/10.5626/JOK.2022.49.1.67
Recently, as the proportion of software in weapon systems has increased and software reliability has an important influence on weapon systems, the importance of weapon system software reliability testing is being emphasized. In existing studies, reliability test standards are presented with a focus on new R&D software. However, recent studies on reliability test subjects and criteria are inadequate for R&D of the performance improvement weapon system software. In particular, establishment of standards and measures is required because it highly influences not only project schedule, but also the cost required for testing, depending on the test subject and standards. In this study, in order to solve this problem, the risk evaluation criteria for selecting the dynamic reliability test target of the recycled software in the performance improvement weapon system were proposed. The risk evaluation criteria were separated by dividing the developed software in the performance improvement weapon system into a new function and a modified function. Also, different criteria were established for complexity and correlation according to the function characteristics. Using this risk evaluation standard, risk evaluation was performed on the Korea Variable Message Format (KVMF) tactical computer performance improvement software, and dynamic reliability test subjects were selected. The efficiency of the dynamic reliability test was confirmed by comparing the risk assessment results and the dynamic test results evaluated by the proposed method with other newly developed projects.
RNN-based Body Posture Estimation Method for 3D UI in Virtual Reality
Wonjun Seong, Byungmoon Kim, BoYu Gao, Jini Kwon, HyungSeok Kim
http://doi.org/10.5626/JOK.2020.47.4.362
Providing intuitive and natural interface is crucial in virtual reality applications. There have been many studies on proper 3D interfaces that require the accurate tracking of body posture. Based on previous studies, we propose an effective body posture estimation method for 3D interfaces. In this study, we focused on the body-fixed UI, especially movements of the upper body. To track body posture, it is necessary to apply additional sensors such as RGB/RGB-D camera, magnetic/optical trackers, etc. The goal of this study was to track the body posture with conventional virtual reality devices only. We applied conventional HMD with head tracker and hand-held controllers. With these three trackers which are not directly attached to the body, an RNN-based method is proposed to effectively estimate the upper body pose. Experiments shows that the proposed method could track the upper body position and orientation within 5% of the error rate, compared with the explicit tracker data. The proposed method could be applied to design body-fixed UI or body-related interfaces without additional devices, which would enhance the accessibility of virtual reality applications.
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