• Title/Summary/Keyword: 운영 모드

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SNIPE Mission for Space Weather Research (우주날씨 관측을 위한 큐브위성 도요샛 임무)

  • Lee, Jaejin;Soh, Jongdae;Park, Jaehung;Yang, Tae-Yong;Song, Ho Sub;Hwang, Junga;Kwak, Young-Sil;Park, Won-Kee
    • Journal of Space Technology and Applications
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    • v.2 no.2
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    • pp.104-120
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    • 2022
  • The Small Scale magNetospheric and Ionospheric Plasma Experiment (SNIPE)'s scientific goal is to observe spatial and temporal variations of the micro-scale plasma structures on the topside ionosphere. The four 6U CubeSats (~10 kg) will be launched into a polar orbit at ~500 km. The distances of each satellite will be controlled from 10 km to more than ~1,000 km by the formation flying algorithm. The SNIPE mission is equipped with identical scientific instruments, Solid-State Telescopes(SST), Magnetometers(Mag), and Langmuir Probes(LP). All the payloads have a high temporal resolution (sampling rates of about 10 Hz). Iridium communication modules provide an opportunity to upload emergency commands to change operational modes when geomagnetic storms occur. SNIPE's observations of the dimensions, occurrence rates, amplitudes, and spatiotemporal evolution of polar cap patches, field-aligned currents (FAC), radiation belt microbursts, and equatorial and mid-latitude plasma blobs and bubbles will determine their significance to the solar wind-magnetosphere-ionosphere interaction and quantify their impact on space weather. The formation flying CubeSat constellation, the SNIPE mission, will be launched by Soyuz-2 at Baikonur Cosmodrome in 2023.

A Study on the Appropriate School Placement in Urban Development Area - Centerde on Sejong Special Self-Governing City - (도시개발지역 학교 적정배치 방안 연구 - 세종특별자치시를 중심으로 -)

  • Son, Byung-Gil;Lee, Yong-Hwan
    • The Journal of Sustainable Design and Educational Environment Research
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    • v.22 no.4
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    • pp.9-17
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    • 2023
  • This study explores school location, school environment, educational conditions, and appropriate scale of schools in the context of Sejong City's development area and identifies effective school establishment plans based on the analysis of the needs of the educational community. The research questions for this study include, first, what is the change trend in the number of students as a result of the opening of schools in the development area of Sejong City to the present, and what differences are there between Sejong and other new cities? Second, what challenges arise in school location due to the occurrence of oversized schools and undergraduate institutions? Third, what challenges arise in school location that would limit the ability to create a safe school environment? Fourth, what aspects need to be improved in school location decisions to promote proper placement? A survey was conducted among parents and faculty members to collect data. The findings revealed that first, when establishing a school, identifying an appropriate location for the school was the top priority of the respondents. The second was the proximity of the school to dense housing, with a parent drop zone next to the school site. Third, to address the issue of lack of playgrounds and special class and care classes, respondents called for various measures such as securing school sites within a certain area. Finally, integrated operation schools and school facilities are required in preparation for decreasing school-age populations due to low birth rates.

An Application-Specific and Adaptive Power Management Technique for Portable Systems (휴대장치를 위한 응용프로그램 특성에 따른 적응형 전력관리 기법)

  • Egger, Bernhard;Lee, Jae-Jin;Shin, Heon-Shik
    • Journal of KIISE:Computer Systems and Theory
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    • v.34 no.8
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    • pp.367-376
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    • 2007
  • In this paper, we introduce an application-specific and adaptive power management technique for portable systems that support dynamic voltage scaling (DVS). We exploit both the idle time of multitasking systems running soft real-time tasks as well as memory- or CPU-bound code regions. Detailed power and execution time profiles guide an adaptive power manager (APM) that is linked to the operating system. A post-pass optimizer marks candidate regions for DVS by inserting calls to the APM. At runtime, the APM monitors the CPU's performance counters to dynamically determine the affinity of the each marked region. for each region, the APM computes the optimal voltage and frequency setting in terms of energy consumption and switches the CPU to that setting during the execution of the region. Idle time is exploited by monitoring system idle time and switching to the energy-wise most economical setting without prolonging execution. We show that our method is most effective for periodic workloads such as video or audio decoding. We have implemented our method in a multitasking operating system (Microsoft Windows CE) running on an Intel XScale-processor. We achieved up to 9% of total system power savings over the standard power management policy that puts the CPU in a low Power mode during idle periods.

Oceanic Application of Satellite Synthetic Aperture Radar - Focused on Sea Surface Wind Retrieval - (인공위성 합성개구레이더 영상 자료의 해양 활용 - 해상풍 산출을 중심으로 -)

  • Jang, Jae-Cheol;Park, Kyung-Ae
    • Journal of the Korean earth science society
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    • v.40 no.5
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    • pp.447-463
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    • 2019
  • Sea surface wind is a fundamental element for understanding the oceanic phenomena and for analyzing changes of the Earth environment caused by global warming. Global research institutes have developed and operated scatterometers to accurately and continuously observe the sea surface wind, with the accuracy of approximately ${\pm}20^{\circ}$ for wind direction and ${\pm}2m\;s^{-1}$ for wind speed. Given that the spatial resolution of the scatterometer is 12.5-25.0 km, the applicability of the data to the coastal area is limited due to complicated coastal lines and many islands around the Korean Peninsula. In contrast, Synthetic Aperture Radar (SAR), one of microwave sensors, is an all-weather instrument, which enables us to retrieve sea surface wind with high resolution (<1 km) and compensate the sparse resolution of the scatterometer. In this study, we investigated the Geophysical Model Functions (GMF), which are the algorithms for retrieval of sea surface wind speed from the SAR data depending on each band such as C-, L-, or X-band radar. We reviewed in the simulation of the backscattering coefficients for relative wind direction, incidence angle, and wind speed by applying LMOD, CMOD, and XMOD model functions, and analyzed the characteristics of each GMF. We investigated previous studies about the validation of wind speed from the SAR data using these GMFs. The accuracy of sea surface wind from SAR data changed with respect to observation mode, GMF type, reference data for validation, preprocessing method, and the method for calculation of relative wind direction. It is expected that this study contributes to the potential users of SAR images who retrieve wind speeds from SAR data at the coastal region around the Korean Peninsula.

Estimation of spatial distribution of snow depth using DInSAR of Sentinel-1 SAR satellite images (Sentinel-1 SAR 위성영상의 위상차분간섭기법(DInSAR)을 이용한 적설심의 공간분포 추정)

  • Park, Heeseong;Chung, Gunhui
    • Journal of Korea Water Resources Association
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    • v.55 no.12
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    • pp.1125-1135
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    • 2022
  • Damages by heavy snow does not occur very often, but when it does, it causes damage to a wide area. To mitigate snow damage, it is necessary to know, in advance, the depth of snow that causes damage in each region. However, snow depths are measured at observatory locations, and it is difficult to understand the spatial distribution of snow depth that causes damage in a region. To understand the spatial distribution of snow depth, the point measurements are interpolated. However, estimating spatial distribution of snow depth is not easy when the number of measured snow depth is small and topographical characteristics such as altitude are not similar. To overcome this limit, satellite images such as Synthetic Aperture Radar (SAR) can be analyzed using Differential Interferometric SAR (DInSAR) method. DInSAR uses two different SAR images measured at two different times, and is generally used to track minor changes in topography. In this study, the spatial distribution of snow depth was estimated by DInSAR analysis using dual polarimetric IW mode C-band SAR data of Sentinel-1B satellite operated by the European Space Agency (ESA). In addition, snow depth was estimated using geostationary satellite Chollian-2 (GK-2A) to compare with the snow depth from DInSAR method. As a result, the accuracy of snow cover estimation in terms with grids was about 0.92% for DInSAR and about 0.71% for GK-2A, indicating high applicability of DInSAR method. Although there were cases of overestimation of the snow depth, sufficient information was provided for estimating the spatial distribution of the snow depth. And this will be helpful in understanding regional damage-causing snow depth.