• Korean Journal of Agricultural and Forest Meteorology
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• v.2 no.4
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• pp.175-182
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• 2000

Spatial interpolation of daily temperature forecasts and observations issued by public weather services is frequently required to make them applicable to agricultural activities and modeling tasks. In contrast to the long term averages like monthly normals, terrain effects are not considered in most spatial interpolations for short term temperatures. This may cause erroneous results in mountainous regions where the observation network hardly covers full features of the complicated terrain. We developed a spatial interpolation model for daily minimum temperature which combines inverse distance squared weighting and elevation difference correction. This model uses a time dependent function for 'mountain slope lapse rate', which can be derived from regression analyses of the station observations with respect to the geographical and topographical features of the surroundings including the station elevation. We applied this model to interpolation of daily minimum temperature over the mountainous Korean Peninsula using 63 standard weather station data. For the first step, a primitive temperature surface was interpolated by inverse distance squared weighting of the 63 point data. Next, a virtual elevation surface was reconstructed by spatially interpolating the 63 station elevation data and subtracted from the elevation surface of a digital elevation model with 1 km grid spacing to obtain the elevation difference at each grid cell. Final estimates of daily minimum temperature at all the grid cells were obtained by applying the calculated daily lapse rate to the elevation difference and adjusting the inverse distance weighted estimates. Independent, measured data sets from 267 automated weather station locations were used to calculate the estimation errors on 12 dates, randomly selected one for each month in 1999. Analysis of 3 terms of estimation errors (mean error, mean absolute error, and root mean squared error) indicates a substantial improvement over the inverse distance squared weighting.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.538-544
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• 2021

Technology readiness assessment is a procedure for managing defense project risk factors based on the preemptive identification of technical risks. Under current regulations, technology readiness is determined based on considerations of the ratings of factors itemized on a checklist, whether unsatisfied factors have a fatal impact on the project, and whether countermeasures for unsatisfied factors have been established. However, objective criteria for assessing the impact of unsatisfied factors have not been presented, and thus, at present, the results of technology readiness level determinations are largely subjective. In addition, the importance of questions on the checklist is dependent on individual project characteristics and this is not considered during the assessment process. In this paper, we propose an improved technology readiness assessment procedure that considers the characteristics of each project. Using the proposed procedure, we quantitatively determined the importance of each checklist item using a weighting method. We found the devised procedure improved the reliability and objectivity of technology readiness assessment results. A case analysis of a complex weapons system is presented to demonstrate these improvements.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.1
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• pp.183-190
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• 2012

This study constructs an expert search system which has a mutual cooperation function based on thesis and author profile. The proposed methodology is as follows. First, we propose weighting method which can search a keyword and the most relevant keyword. Second, we propose a method which can search the experts efficiently with this weighting method. On the preferential basis, keywords and author profiles are extracted from the papers, and experts can be searched through this method. This system will be available to many fields of social network. However, this information is distributed to many systems. We propose a method using multi-ontology to integrate distributed data. The multi-ontology is composed of meta ontology, instance ontology, location ontology and association ontology. The association ontology is constructed through analysis of keyword association dynamically. An expert network is constructed using this multi-ontology, and this expert network can search expert through association trace of keyword. The expert network can check the detail area of expertise through the research list which is provided by the system.

• Journal of The Korean Digital Architecture Interior Association
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• v.13 no.1
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• pp.33-41
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• 2013

Considering the fact that quality of life(QOL) conceptually has objective and subjective attributes but difficulties in measuring the subjective aspect cause a number of studies not to be balanced, this study exploits AHP(Analytical Hierarchy Process) which has been used for systematic decision making to include the other aspect. As the first step of the process decision making hierarchy model is set by content analysis of the UNDP QOL index and additional review of previous studies. 'Improving urban QOL' is a goal on top, 'Economical QOL', 'Environmental QOL', 'Social QOL' and 'Physical QOL' are dimensions of sub-goal(means objectives), and further decomposition follows. AHP shows that the dimensions of economical, physical, environmental and social QOL scored higher respectively. The aim of the model is to measure and prioritize the urban QOL in the two case study cities. The final score of the each city could be computed by integration of relative weights of dimensions for urban QOL. The final score of QOL for city A was 0.6642 and for city B the figure decreased to 0.3358. The method of this study could be used in stages of the process of urban planning. First stage is when planners try to have a correct and reliable perspective from the existed conditions of the city. Second stage is when the projects should be investigated to be confirmed for their efficiency. In other words planners can direct the scarce resources towards the aspects of QOL which are more important. And the results revealed that using AHP creates opportunity to involving the different groups in the stage of criteria weighting so that the attitudes of local community could be integrated well to the decision making to be suitable for a new paradigm of participatory and communicative planning.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2004.06a
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• pp.361-367
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• 2004

For assessment of tritium and radiocarbon ingestion dose to off site individuals, water, hydrogen, and carbon content of main farm produce of Korea were investigated to replace the existing data in K-DOSE60, the Offsite Dose Calculation Manual (ODCM) of Korea Hydro ＆ Nuclear Power Co. Ltd, (KHNP). Main items and weighting factors of farm produce were determined with the nationwide food intake data in 2001, 2002. Main farm produce were sampled around Kori, Wolsong, Ulchin, Younggwang nuclear power sites, Content of each produce was multiplied by weighting factor and summed up to make the weighted mean group value For grains, water, hydrogen, and carbon content was not much different from the existing data currently used in K-DOSE60, but root vegetables had 3.5 times more hydrogen, and leafy vegetables and fruits had 0.7∼1.3 times more or less water, hydrogen, and carbon contents than K-DOSE60.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.3 no.1
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• pp.23-30
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• 2005

From measured results of the neutron fields at some principal places within the containment building in a CE type nuclear power plant in operation, the radiation exposure of a worker to the neutron at there was evaluated and the equivalent dose reflecting new recommendation (ICRP 60) was compared with that doing the old one (ICRP 26). The measured neutron field was also compared with calibration neutron field. From the analysis, the following conclusion was obtained: the average neutron radiation weighting factor according to new recommendation is 2.41 to 2.71 times higher than the old one. The average neutorn radiation weighting factor at the measured place was similar to that at calibration neutron field. The average neutron energy at measured place was between 42 and 158 keV and higher than that of calibration field of 500 keV. So, the measured equivalent dose in nuclear power plant could be overestimated compared to the real equivalent dose.

• Korean Journal of Remote Sensing
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• v.27 no.6
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• pp.653-662
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• 2011

Land surface temperature (LST) is a one of the key variables of land surface which can be estimated from geostationary meteorological satellite. In this study, we have developed the three sets of LST retrieval algorithm from MTSAT-2 data through the radiative transfer simulations under various atmospheric profiles (TIGR data), satellite zenith angle, spectral emissivity, and surface lapse rate conditions using MODTRAN 4. The three LST algorithms are daytime, nighttime and total LST algorithms. The weighting method based on the solar zenith angle is developed for the consistent retrieval of LST at the early morning and evening time. The spectral emissivity of two thermal infrared channels is estimated by using vegetation coverage method with land cover map and 15-day normalized vegetation index data. In general, the three LST algorithms well estimated the LST without regard to the satellite zenith angle, water vapour amount, and surface lapse rate. However, the daytime LST algorithm shows a large bias especially for the warm LST (> 300 K) at day time conditions. The night LST algorithm shows a relatively large error for the LST (260 ~ 280K) at the night time conditions. The sensitivity analysis showed that the performance of weighting method is clearly improved regardless of the impacting conditions although the improvements of the weighted LST compared to the total LST are quite different according to the atmospheric and surface lapse rate conditions. The validation results of daytime (nighttime) LST with MODIS LST showed that the correlation coefficients, bias and RMSE are about 0.62~0.93 (0.44~0.83), -1.47~1.53 (-1.80~0.17), and 2.25~4.77 (2.15~4.27), respectively. However, the performance of daytime/nighttime LST algorithms is slightly degraded compared to that of the total LST algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.3
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• pp.288-296
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• 1992

This paper describes an improved 2D QPS(quadrature polar separable) filter design and its applications to texture processing. The filter kernel pair consists of the product of a radial weighting function based on the finite PSS (prolate spheroidal sequences) and an exponential at tenuation function for the orientational angle. It is quadrature and polar separable in the frequency domain. It is near optimal in the energy loss because we let the orientational angle function approximate the radial weighting function. The filter frequency characteristics is easy to control as it depends only upon the design specifications such as the bandwidth, the directional angle, the attenuation constant, and the shift constant of the central frequency. Some applications of the filter in texture processing, such as the generation of the texture image, the estimation of orientation angles, and the segmentations for the synthetic texture image, are considered. The result shows that the filter with the wide bandwidth can be used for the generation of discrimination of the strong orientational textures and the segmentation results are good.

• Korean Journal of Remote Sensing
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• v.33 no.4
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• pp.359-375
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• 2017

We developed fog detection algorithm (KNU_FDA) based on the optical and textural properties of fog using satellite (COMS) and ground observation data. The optical properties are dual channel difference (DCD: BT3.7 - BT11) and albedo, and the textural properties are normalized local standard deviation of IR1 and visible channels. Temperature difference between air temperature and BT11 is applied to discriminate the fog from other clouds. Fog detection is performed according to the solar zenith angle of pixel because of the different availability of satellite data: day, night and dawn/dusk. Post-processing is also performed to increase the probability of detection (POD), in particular, at the edge of main fog area. The fog probability is calculated by the weighted sum of threshold tests. The initial threshold and weighting values are optimized using sensitivity tests for the varying threshold values using receiver operating characteristic analysis. The validation results with ground visibility data for the validation cases showed that the performance of KNU_FDA show relatively consistent detection skills but it clearly depends on the fog types and time of day. The average POD and FAR (False Alarm Ratio) for the training and validation cases are ranged from 0.76 to 0.90 and from 0.41 to 0.63, respectively. In general, the performance is relatively good for the fog without high cloud and strong fog but that is significantly decreased for the weak fog. In order to improve the detection skills and stability, optimization of threshold and weighting values are needed through the various training cases.

• Journal of the Korean Data and Information Science Society
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• v.21 no.4
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• pp.669-679
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• 2010

A sample survey design is suggested for the service satisfaction evaluation of regional education offices based on the sample size of 2009 Gyeongnam regional education offices's customer satisfaction survey. The sample design is developed to fit the goal of evaluation of individual regional offices and allocate at least the minimum sample size to each city or county in Gyeongnam to achieve the goal of the survey. The population is stratified according to the regions and the types of schools, and the sample of schools is selected with proportional to the size of classes within each stratum. Finally, each sample student is selected according to two-stage cluster sampling within each sample school. Weighting averages, weighting totals and so on can be evaluated for analysis purposes. Their variance estimates can be evaluated using re-sampling methods like BBR, Jackknife, linearization-substitution methods, which are generally used for the data from a complex sample.