• 대한원격탐사학회지
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• 제29권2호
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• pp.219-233
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• 2013

본 연구에서는 아시아-오세아니아 지역에서의 세 지표면 방출률 자료 (MODIS, CIMSS, KNU)의 시 공간적 분포와 변동 특성을 비교 분석하였다. 세 자료 모두 계절에 관계없이 티베트 고원, 페르시아만 주변의 중동지역 및 호주 사막지역, 저위도 지역에서 매우 유사한 방출률 분포를 보이고 있다. 일부지역을 제외한 대부분 지역에서 $12{\mu}m$ 채널의 방출률이 $11{\mu}m$보다 크며, 특히 티베트 고원과 중동지역, 호주 사막지역 일부에서 그 차이가 크다. 저위도 지역에서의 방출률은 서로 상이하지만 방출률의 계절변동이 크지 않은 공통점을 보이고 있다. 그러나 그 외 대부분 지역에서 세 자료는 방출률의 시 공간 변동성에서 큰 차이를 보이고 있다. KNU 자료는 여름에 높고 겨울에 낮은 방출률을 보여 계절변동이 뚜렷하나, MODIS와 CIMSS 자료는 계절에 따른 방출률 변화가 불규칙하며 뚜렷하지 않았다. KNU와 MODIS(KNU와 CIMSS; MODIS와 CIMSS) 자료간의 공간상관계수의 연평균은 $11{\mu}m$와 $12{\mu}m$ 채널에서 각각 0.423과 0.399 (0.330, 0.101; 0.541, 0.154)로 낮다. 특히 $12{\mu}m$ 채널의 경우 서로 상관성이 매우 낮을 뿐만 아니라 상관계수의 월 변동도 강하게 나타나 세 자료간 일치성이 매우 낮다. 본 연구 결과는 아시아-오세아니아 지역에서의 지표면 방출률 자료 개선이 시급함을 제시한다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.554-556
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• 2005

Meteorological imager on the Multi-functional Transport Satellite (MTSAT-IR), which has been operating formally since 28 June 2005, was intercalibrated with a polar orbit satellite [Aqua Moderate Resolution Imaging Spectroradiometer (Aqua/MODIS)] as a well-calibrated instrument. The intercalibration method used in this study was developed by the Cooperative Institute for Meteorological Satellite Studies (CIMSS). This was done for the infrared window channels. The differences of MTSAT-IR and MODIS were are -0.26 K for $11\;\mu m-IR$ window channel, 0.40 K for $12\;\mu m-IR$, window channel, and -0.67 K for $6.7\;\mu m-water$ vapor channel.

• Smart Structures and Systems
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• 제6권2호
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• pp.91-100
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• 2010

An experimental study was carried out to investigate the shape control of plates via embedded shape memory alloy (SMA) wires. An extensive body of literature proposes the use of SMA wires to actively modify the shape or stiffness of a structure; in most cases, however, the study focuses on modeling and little experimental data is available. In this work, a simple proof of concept specimen was built by attaching four prestrained SMA wires to one side of a carbon fiber laminate plate strip. The specimen was clamped at one end and tested in an environmental chamber, measuring the tip displacement and the SMA temperature. At heating, actuation of the SMA wires bends the plate; at cooling deformation is partially recovered. The specimen was actuated a few times between two fixed temperatures $T_c$ and $T_h$, whereas in the last actuation a temperature $T_f$ > $T_h$ was reached. Contrary to most model predictions, in the first actuation the transformation temperatures are significantly higher than in the following cycles, which are stable. Moreover, if the temperature $T_h$ is exceeded, two separate actuations occur during heating: the first follows the path of the stable cycles; the second, starting at $T_h$, is similar to the first cycle. An interpretation of the phenomenon is given using some differential scanning calorimeter (DSC) measurements. The observed behavior emphasizes the need to build a more comprehensive constitutive model able to include these effects.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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• pp.278-281
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• 2006

Korea Meteorological Administration(KMA) has issued the tropical storm(typhoon) warning or advisories when it was developed to tropical storm from tropical depression and a typhoon is expected to influence the Korean peninsula and adjacent seas. Typhoon information includes current typhoon position and intensity. KMA has used the Dvorak Technique to analyze the center of typhoon and it's intensity by using available geostationary satellites' images such as GMS, GOES-9 and MTSAT-1R since 2001. The Dvorak technique is so subjective that the analysis results could be variable according to analysts. To reduce the subjective errors, QuikSCAT seawind data have been used with various analysis data including sea surface temperature from geostationary meteorological satellites, polar orbit satellites, and other observation data. On the other hand, there is an advantage of using the Subjective Dvorak Technique(SDT). SDT can get information about intensity and center of typhoon by using only infrared images of geostationary meteorology satellites. However, there has been a limitation to use the SDT on operational purpose because of lack of observation and information from polar orbit satellites such as SSM/I. Therefore, KMA has established Advanced Objective Dvorak Technique(AODT) system developed by UW/CIMSS(University of Wisconsin-Madison/Cooperative Institude for Meteorological Satellite Studies) to improve current typhoon analysis technique, and the performance has been tested since 2005. We have developed statistical relationships to correct AODT CI numbers according to the SDT CI numbers that have been presumed as truths of typhoons occurred in northwestern pacific ocean by using linear, nonlinear regressions, and neural network principal component analysis. In conclusion, the neural network nonlinear principal component analysis has fitted best to the SDT, and shown Root Mean Square Error(RMSE) 0.42 and coefficient of determination($R^2$) 0.91 by using MTSAT-1R satellite images of 2005. KMA has operated typhoon intensity analysis using SDT and AODT since 2006 and keep trying to correct CI numbers.

• Smart Structures and Systems
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• 제6권5_6호
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• pp.675-687
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• 2010

Structural Health Monitoring (SHM) is the science and technology of monitoring and assessing the condition of aerospace, civil and mechanical infrastructures using a sensing system integrated into the structure. Impedance-based SHM measures impedance of a structure using a PZT (Lead Zirconate Titanate) patch. This paper presents a low-power wireless autonomous and active SHM node called Autonomous SHM Sensor 2 (ASN-2), which is based on the impedance method. In this study, we incorporated three methods to save power. First, entire data processing is performed on-board, which minimizes radio transmission time. Considering that the radio of a wireless sensor node consumes the highest power among all modules, reduction of the transmission time saves substantial power. Second, a rectangular pulse train is used to excite a PZT patch instead of a sinusoidal wave. This eliminates a digital-to-analog converter and reduces the memory space. Third, ASN-2 senses the phase of the response signal instead of the magnitude. Sensing the phase of the signal eliminates an analog-to-digital converter and Fast Fourier Transform operation, which not only saves power, but also enables us to use a low-end low-power processor. Our SHM sensor node ASN-2 is implemented using a TI MSP430 microcontroller evaluation board. A cluster of ASN-2 nodes forms a wireless network. Each node wakes up at a predetermined interval, such as once in four hours, performs an SHM operation, reports the result to the central node wirelessly, and returns to sleep. The power consumption of our ASN-2 is 0.15 mW during the inactive mode and 18 mW during the active mode. Each SHM operation takes about 13 seconds to consume 236 mJ. When our ASN-2 operates once in every four hours, it is estimated to run for about 2.5 years with two AAA-size batteries ignoring the internal battery leakage.