• Title/Summary/Keyword: Parametric uncertainty

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A Study on Technology Forecasting of Unmanned Aerial Vehicles (UAVs) Using TFDEA (TFDEA를 이용한 무인항공기 기술예측에 관한 연구)

  • Jung, Byungki;Kim, H.C.;Lee, Choonjoo
    • Journal of Korea Technology Innovation Society
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    • v.19 no.4
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    • pp.799-821
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    • 2016
  • Unmanned Aerial Vehicles (UAVs) are essential systems for Intelligence, Surveillance, and Reconnaissance (ISR) operations in current battlespace. And its importance will be getting extended because of complexity and uncertainty of battlespace. In this study, we forecast the advancement of 96 UAVs during the period of 32 years from 1982 to 2014 using TFDEA. TFDEA is a quantitative technology forecasting method which is characterized as non-parametric and non-statistical mathematical programming. Inman et al. (2006) showed that TFDEA is more accurate in forecasting compared with classical econometrics (e.g. regression). This study got 4.06% point of annual technological rate of change (RoC) for UAVs by applying TFDEA. And most UAVs in the period are inefficient according to the global SOA frontiers. That is because the countries which develop UAVs are in the middle class of technological level, so more than 60% of world UAVs markets are shared by North America and Europe which are advanced countries in terms of technological maturity level. This study could give some insights for UAVs development and its advancement. And also can be used for evaluating the adequacy of Required Operational Capability (ROC) of suggested future systems and managing the progress of Research and Development (R&D).

Effects of Motion Correction for Dynamic $[^{11}C]Raclopride$ Brain PET Data on the Evaluation of Endogenous Dopamine Release in Striatum (동적 $[^{11}C]Raclopride$ 뇌 PET의 움직임 보정이 선조체 내인성 도파민 유리 정량화에 미치는 영향)

  • Lee, Jae-Sung;Kim, Yu-Kyeong;Cho, Sang-Soo;Choe, Yearn-Seong;Kang, Eun-Joo;Lee, Dong-Soo;Chung, June-Key;Lee, Myung-Chul;Kim, Sang-Eun
    • The Korean Journal of Nuclear Medicine
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    • v.39 no.6
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    • pp.413-420
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    • 2005
  • Purpose: Neuroreceptor PET studies require 60-120 minutes to complete and head motion of the subject during the PET scan increases the uncertainty in measured activity. In this study, we investigated the effects of the data-driven head mutton correction on the evaluation of endogenous dopamine release (DAR) in the striatum during the motor task which might have caused significant head motion artifact. Materials and Methods: $[^{11}C]raclopride$ PET scans on 4 normal volunteers acquired with bolus plus constant infusion protocol were retrospectively analyzed. Following the 50 min resting period, the participants played a video game with a monetary reward for 40 min. Dynamic frames acquired during the equilibrium condition (pre-task: 30-50 min, task: 70-90 min, post-task: 110-120 min) were realigned to the first frame in pre-task condition. Intra-condition registrations between the frames were performed, and average image for each condition was created and registered to the pre-task image (inter-condition registration). Pre-task PET image was then co-registered to own MRI of each participant and transformation parameters were reapplied to the others. Volumes of interest (VOI) for dorsal putamen (PU) and caudate (CA), ventral striatum (VS), and cerebellum were defined on the MRI. Binding potential (BP) was measured and DAR was calculated as the percent change of BP during and after the task. SPM analyses on the BP parametric images were also performed to explore the regional difference in the effects of head motion on BP and DAR estimation. Results: Changes in position and orientation of the striatum during the PET scans were observed before the head motion correction. BP values at pre-task condition were not changed significantly after the intra-condition registration. However, the BP values during and after the task and DAR were significantly changed after the correction. SPM analysis also showed that the extent and significance of the BP differences were significantly changed by the head motion correction and such changes were prominent in periphery of the striatum. Conclusion: The results suggest that misalignment of MRI-based VOI and the striatum in PET images and incorrect DAR estimation due to the head motion during the PET activation study were significant, but could be remedied by the data-driven head motion correction.