• Title/Summary/Keyword: SNSA

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Development of Smart NFC Security Authenticator(SNSA) (Smart NFC 보안인증기기(SNSA) 개발)

  • Kang, Jeong-Jin;Lee, Yong-Cheol
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.13 no.3
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    • pp.177-181
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    • 2013
  • As smart devices and OS with communication capabilities based latest NFC (Near Field Communication) have been spreaded, many applications with using existing RFID are being replaced to NFC. Smart NFC technology and existing services and devices can be easily combined convergence and advantage of smart phones, such as authentication and billing, medical care, the creation of a new paradigm of Network Communication are to be expected. By developing H/W, S/W of the Smart NFC Security Authenticator(SNSA), satisfying with wireless communication test results within accepted reference value, analyzing and testing the impact of topology, the signal performance of Daisy Chain Topology was much better than Star Topology's.

Study on the Variation of Driver's Biosignals According to the Color Temperature of Vehicle Interior Mood Lighting (자동차 실내 무드조명의 색온도에 따른 운전자의 생체신호 변화)

  • Kim, Kyu-Beom;Jo, Hyung-Seok;Kim, Young-Jung;Min, Byung-Chan
    • Science of Emotion and Sensibility
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    • v.23 no.2
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    • pp.3-12
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    • 2020
  • The purpose of this work is to suggest the optimal color temperature, which induces a sense of comfort for autonomous vehicle users through the analysis of biosignal using electroencephalography (EEG) and photoplethysmography (PPG). To achieve this purpose, we applied lighting with a color temperature of 3000 K, 4000 K, 5000 K, and 6000 K to the autonomous driving environment. We experimented in a laboratory equipped with a graphic driving simulator. The experimental procedure is as follows: 1) stabilization (5 min). 2) Uchida-Kraepelin test (3 min). 3) Automatic driving + lighting (3 min). This procedure was repeated four times under different color temperatures. We performed frequency analysis on a collected time-series data and calculated the power value for each frequency band through power spectrum analysis. In the case of EEG, we analyzed α- and β-waves, which are indicators of stability and arousal, respectively. In the case of PPG, we analyzed the sympathetic nervous system activity. To reduce deviations between the subjects, we normalized the data before analysis. The result of the first analysis revealed that α-wave increased only at 5000 K, while the β-wave increased at almost all color temperatures. In addition, in the case of PPG, sympathetic nervous system activity (SNSA) increased under driving conditions. The result of the second analysis revealed that the difference between β-wave and SNSA is insignificant. In conclusion, the increase in α-waves showed that EEG was most stable at 5000 K. The results of this study can be applied to the upcoming autonomous driving era to induce high driver satisfaction. Furthermore, this approach could eventually lead to the acceptance of autonomous vehicles by suggesting a positive effect of autonomous driving.