• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.378-380
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• 2005

Remote sensing of atmospheric aerosol using MODIS satellite data has been proven to be very useful in global/regional scale aerosol monitoring. Due to their large spatial resolution of $10km^2$ MODIS aerosol optical thickness (AOT) data have limitations for local/urban scale aerosol monitoring applications. Modified Bremen Aerosol Retrieval (BAER) algorithm developed by von Hoyningen-Huene et al. (2003) and Lee et al. (2005) has been applied in this study to retrieve AOT in fe resolutions of $500m^2$ over Korea. Look up tables (LUTs) were constructed from the aerosol properties based on sun-photometer observation and radiation transfer model calculations. It was found that relative error between the satellite products and the ground observations was within about $15\%$. Resulting AOT products were correlated with surface PMIO concentration data. There was good correlation between MODIS AOT and surface PM concentration under certain atmospheric conditions, which supports the feasibility of using the high-resolution MODIS AOT for local and urban scale air quality monitoring

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.9-12
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• 2004

Developing an efficient knowledge base construction mechanism as an input method for expert systems (ES) development is of extreme importance due to the fact that an input process takes a lot of time and cost in constructing an ES. Most ES require experts to explicit their tacit knowledge into a form of explicit knowledge base with a full sentence. In addition, the explicit knowledge bases were composed of strict grammar and keywords. To overcome these limitations, this paper proposes a knowledge conceptualization and construction mechanism for automated knowledge acquisition, allowing an efficient decision. To this purpose, we extended traditional knowledge map (KM) construction process to dynamic knowledge map (DKM) and combined this algorithm with relational database (RDB). In the experiment section, we used medical data to show the efficiency of our proposed mechanism. Each rule in the DKM was characterized by the name of disease, clinical attributes and their treatments. Experimental results with various disease show that the proposed system is superior in terms of understanding and convenience of use.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.4
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• pp.859-865
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• 1999

Many sensors such as a laser, and CCD camera to obtain 3D information have been used, but most of algorithms for laser calibration are inefficient since a huge memory and experiment data are required. This method saves a memory and an experimental data since the 3D information are obtained simply triangulation method. In this paper, the calibration algorithm of a slit km laser based on triangulation method is introduced to calculate 3D information in the real world. The laser beam orthogonally mounted on the XY table is projected on the floor. A CCD camera observes the intersection plane of a light and an object plane. The 3D information is calculated using observed and calibration data.

• Journal of Astronomy and Space Sciences
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• v.33 no.1
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• pp.37-44
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• 2016

This paper presents an algorithm for Real-Time Orbit Determination (RTOD) of navigation satellites for the Korean Regional Navigation Satellite System (KRNSS), when the navigation satellites generate ephemeris by themselves in abnormal situations. The KRNSS is an independent Regional Navigation Satellite System (RNSS) that is currently within the basic/preliminary research phase, which is intended to provide a satellite navigation service for South Korea and neighboring countries. Its candidate constellation comprises three geostationary and four elliptical inclined geosynchronous orbit satellites. Relative distance ranging between the KRNSS satellites based on Inter-Satellite Ranging (ISR) is adopted as the observation model. The extended Kalman filter is used for real-time estimation, which includes fine-tuning the covariance, measurement noise, and process noise matrices. Simulation results show that ISR precision of 0.3-0.7 m, ranging capability of 65,000 km, and observation intervals of less than 20 min are required to accomplish RTOD accuracy to within 1 m. Furthermore, close correlation is confirmed between the dilution of precision and RTOD accuracy.

• Journal of Biomedical Engineering Research
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• v.27 no.6
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• pp.301-309
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• 2006

The main purpose of this study is to derive a regression equation that predicts the individual differences in activity energy expenditure (AEE) using accelerometer during different types of activity. Two subject groups were recruited separately in time: One is a homogeneous group of 94 healthy young adults with age ranged from $20\sim35$ yrs. The other subject group has a broad spectrum of physical characteristics in terms of age and fat ratio. 226 adolescents and adults of age ranged from $12\sim57$ yrs and fat ratio from $4.1\sim39.7%$ were in the second group. The wireless 3-axis accelerometers were developed and carefully fixed at the waist belt level. Simultaneously the total calorie expenditure was measured by gas analyzer. Each subject performed walking and running at speeds of 1.5, 3.0, 4.5, 6.0, 6.5, 7.5, and 8.5 km/hr. A generalized sensor-independent regression equation for AEE was derived. The regression equation was developed fur walking and running. The regression coefficients were predicted as functions of physical factors-age, gender, height, and weight with multivariable regression analysis. The generalized calorie estimation equation predicts AEE with correlation coefficient of 0.96 and the average accuracy of the accumulated calorie was $89.6{\pm}7.9%$.

• Proceedings of the KSRS Conference
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• v.2
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• pp.816-819
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• 2006

One of the most difficult parameters to measure in the sea is current speed and direction. Recently, efforts are being made to estimate the ocean current vectors by utilizing sequential satellite imageries. In this study, we attempted to estimated sea surface current vector (sscv) by using satellite ocean color imageries of SeaWifs around the Korean Peninsula. This ocean color image data has 1-day sampling interval and spatial resolution of 1x1 km. Maximum cross-correlation method is employed which is aimed to detect similar patterns between sequential images. The estimated current vectors are compared to the surface geostrophic current vectors obtained from altimeter of sea level height data. In utilizing the color imagery data, some limitations and drawbacks exist so that in warm water region where phytoplankton concentration is relatively lower than in cold water region, estimation of sscv is poor and unreliable. On the other hand, two current vector fields agree reasonably well in the Korean South Sea region where high concentration of chlorophyll-a and weak tide is observed. In the future, with ocean color images of shorter sampling interval by COMS satellite, the algorithm and methodology developed in the study would be useful in providing the information for the ocean current around Korean Peninsula.

• Proceedings of the KSRS Conference
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• v.1
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• pp.487-490
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• 2006

Ocean Color Monitor (OCM) onboard the Indian Remote Sensing Satellite IRS-P4 has been used to retrieve chlorophyll concentration in the Bay of Bengal and the Arabian Sea using a bio-optical algorithm. Cloud masking and atmospheric corrections have been performed before applying mapping function to derive chlorophyll concentration from IRS-P4 OCM data. We have retrieved chlorophyll concentration from OCM, and MODIS during the summer and winter season along the eastern and western coast of India at every 1 degree latitude at increasing distance (25, 50, 100, 150 and 200km) away from the coast as well as near river mouths for the period 2000-2003. We have also studied spatial and temporal dynamics of monthly MODIS Aqua (for period July 2002-April 2004). The seasonal dynamics of chlorophyll concentration over the Bay of Bengal and the Arabian Sea have been discussed using OCM and MODIS for both the coastal region and the open sea.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.4
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• pp.175-182
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• 2002

This paper proposes an analytic method for measuring the accurate fundamental frequency component of a fault current signal distorted with a DC-offset, a characteristic frequency component, and harmonics. The proposed algorithm is composed of four stages: sine filer, linear filter, Prony's method, and measurement. The sine filter and the linear filter eliminate harmonics and the fundamental frequency component, respectively. Then Prony's method is used to estimate the parameters of the DC-offset and the characteristic frequency component. Finally, the fundamental frequency component is measured by compensating the sine-filtered signal with the estimated parameters. The performance evaluation of the proposed method is presented for a-phase to around faults on a 345 kV 200 km overhead transmission line. The EMTP is used to generate fault current signals under different fault locations and fault inception angles. It is shown that the analytic method accurately measures the fundamental frequency component regardless of the characteristic frequency component as well as the DC-offset.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.286-289
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• 2007

This study is to develop a cloud detection algorit1un for COMS and it is currently tested by using MODIS level 2B and MTSAT-1R satellite radiance data. Unlike many existing cloud detection schemes which use a threshold method and traditional statistical methods, in this study a feed-forward neural network method with back-propagation algorit1un is used. MODIS level 2B products are matched with feature information of five-band MTSAT 1R image data to form the training dataset. The neural network is trained over the global region for the period of January to December in 2006 with 5 km spatial resolution. The main results show that this model is capable to detect complex cloud phenomena. And when it is applied to seasonal images, it shows reliable results to reflect seasonal characteristics except for snow cover of winter. The cloud detection by the neural network method shows 90% accuracy compared to the MODIS products.

• Korean Journal of Agricultural and Forest Meteorology
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• v.7 no.2
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• pp.171-183
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• 2005

In order to monitor the global terrestrial carbon cycle, NASA (National Aeronautics and Space Administration) provides 8-day GPP images by use of satellite remote-sensing reflectance data from MODIS (Moderate Resolution Imaging Spectroradiometer) at l-km nadir spatial resolution since December, 1999. MODIS GPP algorithm adopts DAO (Data Assimilation Office) meteorological data to calculate daily GPP. By evaluating reliability of DAO data with respect to surface weather station data, we examined the effect of errors from DAO data on MODIS GPP estimation in the Korean Peninsula from 2001 to 2003. Our analyses showed that DAO data underestimated daily average temperature, daily minimum temperature, and daily vapor pressure deficity (VPD), but overestimated daily shortwave radiation during the study period. Each meteorological variable resulted in different spatial patterns of error distribution across the Korean Peninsula. In MODIS GPP estimation, DAO data resulted in overestimation of GPP by $25\%$ for all biome types but up to $40\%$ for forest biomes, the major biome type in the Korean Peninsula. MODIS GPP was more sensitive to errors in solar radiation and VPD than in temperatures. Our results indicate that more reliable gridded meteorological data than DAO data are necessary for satisfactory estimation of MODIS GPP in the Korean Peninsula.