• Journal of the Korea Society of Computer and Information
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• v.20 no.4
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• pp.69-76
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• 2015

We present microscopy based hyperspectral imaging system that successively shows high spatial (micrometer) and temporal resolutions (milisecond), and acquired pseudocolor hemoglobin saturation map a result of various image processing techniques can provide additional information such as oxygen transport, abnormal vascularity and therapeutic effects besides structural and physiological measurements in various diseases. To increase understanding of vascular defects several optical methods of imaging for preclinical/clinical assessment have been developed so far. However, they have some limitations for outcoming resolution and user satisfaction level compared to its cost. A hyperspectral imaging system has shown a wide range of vascular characteristics associated with hypervascularity, aberrant angiogenesis or abnormal vascular remodeling in many diseases. This vascular characteristic is considered as a key component to diagnose and detect a type of disease as evidenced by them.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.5
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• pp.92-99
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• 2011

To measure the traffic pollutants with high temporal and spatial resolution under real conditions, a mobile emission laboratory (MEL) was designed. The equipment of the mini-van provides gas phase measurements of CO, NOx, $CO_2$, THC (Total hydrocarbon) and number density & size distribution measurements of fine and ultra-fine particles by a fast mobility particle sizer (FMPS) and a condensation particle counter (CPC). The inlet sampling port above the bumper enables the chasing of different type of vehicles. This paper introduces the technical details of the MEL and presents data from the car chasing experiment of diesel bus equipped with aftertreatment system. The dilution ratio was calculated by the ratio of ambient NOx and tail-pipe NOx. Most particles from the diesel bus were counted under 300 nm and the peak concentration of the particles was located between 30 and 60 nm. The total PM number emission from diesel bus equipped with DPF was 10 orders of magnitude lower compared to those emitted from base diesel bus. And the total PM number emission from diesel bus equipped with SCR was comparable to the particle emission from base diesel bus.

• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.5
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• pp.55-65
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• 2014

Radar remote sensing is appropriate for rice monitoring because the areas where this crop is cultivated are often cloudy and rainy. Especially, Synthetic Aperture Radar (SAR) can acquire remote sensing information with a high temporal resolution in tropical and subtropical regions due to its all-weather capability. This paper analyzes the relationships between backscattering coefficients of rice measured by RADARSAT-2 SAR and growth parameters during a rice growth period. And we applied the relationships to crop monitoring of paddy rice in North Korea. As a result, plant height and Leaf Area Index (LAI) increased until Day Of Year (DOY) 234 and then decreased, while fresh weight and dry weight increased until DOY 253. Correlation coefficients revealed that Horizontal transmit and Horizontal receive polarization (HH)-polarization backscattering coefficients were correlated highly with plant height (r=0.95), fresh weight (r=0.92), vegetation water content (r=0.91), LAI (r=0.90), and dry weight (r=0.89). Based on the observed relationships between backscattering coefficients and variables of cultivation, prediction equations were developed using the HH-polarization backscattering coefficients. Concerning the evaluation for the applicability of the LAI distribution from RADARSAT-2, the LAI statistic was evaluated in comparison with LAI distribution from RapidEye image. And LAI distributions in Pyongyang were presented to show spatial variability for unaccessible areas.

• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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• v.1 no.1
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• pp.19-33
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• 1997

The high oxidants, which occur the daily maximum concentrations in the afternoon, are transported into the other region via long range transport mechanisms or trapped within the shallow mixing boundary layer and then removed physically (deposition, transport by mountain wind, etc.) and chemically (reaction with local sources). Therefore, modeling formation of photochemical oxidants requires a complex description of both chemical and meteorological processes. In this study, as a part of air quality studies, we reviewed various aspects of photochemical modeling on the basis of currently available literature. The result of the review shows that the model is based on a set of coupled continuity equations describing advection, diffusion, transport, deposition, chemistry, emission. Also photochemical oxidant models require a large amount of input data concerned with all aspects of the ozone life cycle. First, emission inventories of hydrocarbon and nitrogen oxides, with appropriate spatial and temporal resolution. Second, chemical and photochemical data allowing the quantitative description of the formation of ozone and other photochemically-generated secondary pollutants. Third, dry deposition mechanisms particularly for ozone, PAN and hydrogen peroxide to account for their removal by absorption on the ground, crops, natural vegetation, man-made and water surfaces. Finally, meteorological data describing the transport of primary pollutants away from their sources and of secondary pollutants towards the sensitive receptors where environmental damage may occur. In order to improve our present study, shortcomings and limitation of existing models are pointed out and verification process through observation is emphasized.

• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.97-100
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• 2009

The surface parameters associated with the land are usually dependent on the climate, and many physical processes that are displayed in the image sensed from the land then exhibit temporal variation with seasonal periodicity. An adaptive feedback system proposed in this study reconstructs a sequence of images remotely sensed from the land surface having the physical processes with seasonal periodicity. The harmonic model is used to track seasonal variation through time, and a Gibbs random field (GRF) is used to represent the spatial dependency of digital image processes. In this study, the Normalized Difference Vegetation Index (NDVI) was computed for one week composites of the Advanced Very High Resolution Radiometer (AVHRR) imagery over the Korean peninsula for 1996 and 2000 using a dynamic technique, and the adaptive reconstruction of harmonic model was then applied to the NDVI time series for tracking changes on the ground surface. The results show that the adaptive approach is potentially very effective for continuously monitoring changes on near-real time.

• Korean Journal of Remote Sensing
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• v.23 no.2
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• pp.119-124
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• 2007

The few observed data related snowmelt was the major cause of difficulty in extracting snowmelt factors such as snow cover area, snow depth and depletion curve. Remote sensing technology is very effective to observe a wide area. Although many researchers have used remote sensing for snow observation, there were a few discussions on the characteristics of spatial and temporal variation. Snow cover maps were derived from NOAA AVHRR images for the winter seasons from 1997 to 2006. Distributed snow depth was mapped by overlapping between snow cover maps and interpolated snowfall maps from 69 meteorological observation stations. Model parameters (Snow Cover Area: SCA, snow depth, Snow cover Depletion Curve: SDC) building for 5 major watersheds in South Korea. Especially SDC is important parameter of snowmelt model.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.485-493
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• 2006

This study is to combine precipitation data with different spatial-temporal characteristics using an optimal weighting method. This optimal weighting method is designed for combination of AWS rain gage data and S-band RADAR-estimated rain data with weighting function in inverse proportion to own mean square error for the previous time step. To decide the optimal weight coefficient for optimized precipitation according to different training time, the method has been performed on Changma case with a long spell of rainy hour for the training time from 1 hour to 10 hours. Horizontal field of optimized precipitation tends to be smoothed after 2 hours training time, and then optimized precipitation has a good agreement with synoptic station rainfall assumed as true value. This result suggests that this optimal weighting method can be used for production of high-resolution quantitative precipitation rate using various data sets.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.515-523
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• 2018

In order to obtain consistent change detection result for multi-temporal satellite images, preprocessing must be performed. In particular, the preprocessing related to the spectral values can be performed by the radiometric normalization, and relative radiometric normalization is generally utilized. However, most relative radiometric normalization methods assume a linear relationship between the two images, and nonlinear spectral characteristics such as phenological differences are not considered. Therefore, this study proposes a relative radiometric normalization which assumes nonlinear relationships that can perform compositive normalization of radiometric and phenological characteristics. The proposed method selects the subject and reference images, and then extracts the radiometric control set samples through the no-change method. In addition, spectral indexes as well as pixel values are extracted in order to consider sufficient information, and modeling of nonlinear relationships is performed through multilayer perceptron. Finally, the proposed method is compared with the conventional relative radiometric normalization methods, which shows that the proposed method is visually and quantitatively superior.

• Convergence Security Journal
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• v.18 no.2
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• pp.33-40
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• 2018

ICT technology has been applied to various educational fields, but applying to educational test field is limited. Computer-based test (CBT) can overcome temporal and spatial constraints of conventional paper-based test, but is vulnerable to fraud by test parties. In this paper, we propose real-time monitoring and process management methods to enhance the security of CBT. In the proposed methods, the test screens of students are periodically captured and transferred to the professor screen to enable real-time monitoring, and the possible processes used for cheating can be blocked before testing. In order to monitor the screen of many students in real time, effective compression of the captured original image is important. We applied three-step compression methods: initial image compression, resolution reduction, and re-compression. Through this, the original image of about 6MB was converted into the storage image of about 3.8KB. We use the process extraction and management functions of Windows API to block the processes that may be used for cheating. The CBT system of this paper with the new security enhancement methods shows the superiority through comparison of the security related functions with the existing CBT systems.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.49-60
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• 2022

Motivated by the high-resolution properties of high-order Weighted Essentially Non-Oscillatory (WENO) and flux limiter (FL) for steep-gradient problems and the robust convergence of Jacobian-free Newton-Krylov (JFNK) methods for nonlinear systems, the preconditioned JFNK fully implicit high-order WENO and FL schemes are proposed to solve the transient two-phase two-fluid models. Specially, the second-order fully-implicit BDF2 is used for the temporal operator and then the third-order WENO schemes and various flux limiters can be adopted to discrete the spatial operator. For the sake of the generalization of the finite-difference-based preconditioning acceleration methods and the excellent convergence to solve the complicated and various operational conditions, the random vector instead of the initial condition is skillfully chosen as the solving variables to obtain better sparsity pattern or more positions of non-zero elements in this paper. Finally, the WENO_JFNK and FL_JFNK codes are developed and then the two-phase steep-gradient problem, phase appearance/disappearance problem, U-tube problem and linear advection problem are tested to analyze the convergence, computational cost and efficiency in detailed. Numerical results show that WENO_JFNK and FL_JFNK can significantly reduce numerical diffusion and obtain better solutions than traditional methods. WENO_JFNK gives more stable and accurate solutions than FL_JFNK for the test problems and the proposed finite-difference-based preconditioning acceleration methods based on the random vector can significantly improve the convergence speed and efficiency.