• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.4
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• pp.33-43
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• 2011

This study is to make snowfall distribution map for the 4 heavy snowfall events of January 2001, March of 2004, December of 2005 and January of 2010, and compare the results for three cases of construction methods. The cases are to generate the map by applying IDW(Inverse Distance Weighting) interpolation to 76 ground measured snowfall point data (Snow Depth Map; SDM), mask out the SDM with the MODIS snow cover area (MODIS SCA) of Terra MODIS (MODerate resolution Imaging Spectroradiometer) (SDM+MODIS SCA; SDM_M), and consider the snowdepth lapse rate of snowfall by elevation (Digital Elevation Model; DEM) to the second case (SDM_M+DEM; SDM_MD). By applying the MODIS SCA, the SCA of 4 events was 62.9%, 44.1%, 52.0%, and 69.0% for the area of South Korea. For the average snow depth, the SDM_M decreased 0.9cm, 1.9cm, 0.8cm, and 1.5cm compared to SDM and the SDM_MD increased 1.3cm, 0.9cm, 0.4cm, and 1.2cm respectively.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.6 no.1
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• pp.1-12
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• 2001

Tidal computations of $M_2,\;S_2,\; K_1$ and $O_1$ constituents in the northeast Asian sea are presented by blending the Topex/Poseidon (T/P) altimeter data into a hydrodynamic model with $5'{\times}5'$ resolution. A series of sensitivity experiments on a weighting factor, which is the control parameter in the blending method, are carried out using $M_2$ constituent. The weighting factor is set to be in inverse proportion to the square root of water depth to reduce noises which could occur in data-assimilative model by blending T/P data. Model results obtained by blending the T/P-derived $M_2,\;S_2,\; K_1$ and $O_1$ constituents simultaneously are compared with all T/P-track tidal data; Average values of amplitude and phase errors are close to zero. Standard deviations of amplitude and phase errors are approximately 2 cm and less than 10 degrees respectively. The data-assimilative model results show a quite good agreement with T/P-derived tidal data, particularly in shallow water region (h<250m). In deep water regions, T/P-derived tidal data show unreasonable spatial variations in amplitude and phase. The data-assimilative model results differ from T/P-derived data, but are improved to show reasonable spatial variations in amplitude and phase. In addition, the T/P-blended model results are in good agreement with coastal tide gauge data which are not blended into the model.

• Spatial Information Research
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• v.15 no.3
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• pp.267-278
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• 2007

Internationally many models are developed and applied to predict the impact of the climate change, as occurring a lot of symptoms by climate change. Also, in Korea, according to increasing the application of the climate effect model in many research fields, it is required to study the method for preparing climate data and the characteristics of the climate. In this study IDSW (Inverse Distance Squared Weighting), one of the spatial statistic methods, is applied to interpolate. This method estimates a point of interest by assigning more weight to closer points, which are limited to be select by 3 in 100 km radius. As a result, annual average temperature and precipitation had increased by $0.4^{\circ}C$ and 412 mm during 1977 to 2006. They are also predicted to increase by $3.96^{\circ}C$, 319 mm in the 2100 compared to 2007. High variability of temperature and precipitation for last 30 years shows in some part of the Gangwon-do and in the southern part of Korea. Besides in the study of the variable trend, the variability of temperature and precipitation is inclined to increase in Gangwon-do and southern east part, respectively. However, during 2071 to 2100 variability of temperature is predicted to be high in midwest of Korea and variability of precipitation in the east. In the trend of variability, variability of temperature is apt to increase into west south, and variability of precipitation increase in midwest and a part of south.

• Journal of The Korean Society of Grassland and Forage Science
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• v.32 no.4
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• pp.437-446
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• 2012

As a part of establishing suitability classification for forage production, use of the national soil and climate database was attempted for Italian ryegrass (Lolium multiflorum Lam., IRG) in Gangwon Province. The soil data base were from Heugtoram of the National Academy of Agricultural Science, and the climate data base were from the National Center for Agro-Meteorology, respectively. Soil physical properties including soil texture, drainage, slope available depth and surface rock contents, and soil chemical properties including soil acidity and salinity, organic matter content were selected as soil factors. The crieria and weighting factors of these elements were scored. Climate factors including average daily minimum temperature, average temperature from March to May, the number of days of which average temperature was higher than $5^{\circ}C$ from September to December, the number of days of precipitation and its amount from October to May of the following year were selected, and criteria and weighting factors were scored. The electronic maps were developed with these scores using the national data base of soil and climate. Based on soil scores, the area of Goseong, Sogcho, Gangreung, and Samcheog in east coastal region with gentle slope were classified as the possible and/or the proper area for IRG cultivation in Gangwon Province. The lands with gentle or moderate slope of Cheolwon, Yanggu, Chuncheon, Hweongseong, Pyungchang and Jeongsun in west side slope of Taebaeg mountains were classified as the possible and/or proper area as well. Based on climate score, the east coastal area of Goseong, Sogcho, Yangyang, Gangreung and Samcheog could be classified as the possible or proper area. Most area located on west side of the Taebaeg mountains were classified as not suitable for IRG production. In scattered area in Chuncheon and Weonju, where the scores exceeded 60, the IRG cultivation should be carefully managed for good production. For better application of electronic maps.

• The Journal of Engineering Geology
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• v.24 no.1
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• pp.39-52
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• 2014

Limestone caves that consist of main passages and branches are formed by a variety of processes, and have the characteristic of developing with a preferred orientation controlled by discontinuities such as bedding, joints, and faults around the cave. However, it is difficult to analyze a representative orientation from various orientations. To interpret the overall development orientation of limestone caves, this study proposes new development orientation analysis methods, termed the Average Span Ratio Method (ASRM) and the Individual Development Ratio Method (IDRM), using the weighting of persistence. Nine limestone caves in Korea were randomly selected for testing the new methods. The methods show a stronger development orientation for limestone caves than that obtained by traditional methods, which consider only the distribution of development orientations. Based on an analysis of the relationship between the average span and the dip angle of bedding, it is confirmed that shallowly dipping bedding is a major contributor to the expansion of span in limestone caves. In addition, using scan-line survey data acquired in the field, we perform an RMR analysis of stability of the ground around limestone caves.

• Journal of Environmental Science International
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• v.22 no.2
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• pp.151-161
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• 2013

The assessment of personal exposure is a critical component in population-based epidemiologic studies of air pollution. This study was conducted to apply and compare the four exposure estimation methods of individual-level to air pollution concentration in a cohort including 2,283 subjects in Gwangyang, Korea. Individual-level exposure of air pollution were estimated using multiple approaches, including average across all monitors, nearest monitor, and spatial interpolation by inverse distance weighting and kriging. The mean concentrations of $PM_{10}$, $NO_2$, $SO_2$, CO, $O_3$ by four exposure estimation methods were slightly different but not significantly different from each other. Cross-validation showed that kriging was more accurate than other exposure estimation methods because kriging has probably predicted individual exposure levels equivalent to residential locations after estimating the parameters of a model according to the spatial surface of air pollution concentration. These data support that spatial interpolation methods may provide better estimates than selecting the value from the nearest monitor and averaging across values from all monitors by reflecting spatial attributes of air pollution on personal level.

• Journal of the Korean Society for Marine Environment & Energy
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• v.15 no.4
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• pp.330-336
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• 2012

We surveyed and evaluated quantities and distribution characteristics of debris on the sea floor around active fishing grounds around the islands in the southwest coast of Korea in 2007 where the average depth is below 40m. Proper recovery gears mainly to haul the derelict fishing gears are selected considering the sea bed types of the areas. The collected debris amounts were used to estimate the total amount of the surveyed area. The number of hauls per trial times the amount of the debris was extended to whole sampling area and the weighting factor from the opinion was applied to reach the total amount of marine debris on the floor. The amount of the deposited marine debris around Wangdeung-do area is estimated as about 686 $kg/km^2$, and the cost of the collection and treatment for the deposited marine debris is estimated about 3.9 billion KRW after consideration of the proper size of the working ships, labor, transport and treatment cost.

• Journal of Internet Computing and Services
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• v.17 no.5
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• pp.89-95
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• 2016

In a software testing domain, test case prioritization techniques improve the performance of regression testing, and arrange test cases in such a way that maximum available faults be detected in a shorter time. User-sessions and cookies are unique features of web applications that are useful in regression testing because they have precious information about the application state before and after making changes to software code. This approach is in fact a user-session based technique. The user session will collect from the database on the server side, and test cases are released by the small change configuration of a user session data. The main challenges are the effectiveness of Average Percentage Fault Detection rate (APFD) and time constraint in the existing techniques, so in this paper developed an intelligent framework which has three new techniques use to manage and put test cases in group by applying useful criteria for test case prioritization in web application regression testing. In dynamic weighting approach the hybrid criteria which set the initial weight to each criterion determines optimal weight of combination criteria by evolutionary algorithms. The weight of each criterion is based on the effectiveness of finding faults in the application. In this research the priority is given to test cases that are performed based on most common http requests in pages, the length of http request chains, and the dependency of http requests. To verify the new technique some fault has been seeded in subject application, then applying the prioritization criteria on test cases for comparing the effectiveness of APFD rate with existing techniques.

• Steel and Composite Structures
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• v.15 no.1
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• pp.103-130
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• 2013

Fire performance and fire safety of high-rise buildings have become major concerns after the disasters of World Trade Center in the U.S. in 2001 and Windsor tower in Spain in 2005. Performance based design (PBD) approaches have been considered as a better method for fire resistance design of structures because it is capable of incorporating test results of most recent fire resistance technologies. However, there is a difficulty to evaluate fireproof performance of large structures, which have multiple structural members such as columns, slabs, and walls. The difficulty is mainly due to the limitation in the testing equipment, such as size of furnace that can be used to carry out fire tests with existing criteria like ISO 834, BS 476, and KS F 2257. In the present research, a large scale calorie meter (10 MW) was used to conduct three full scale fire tests on medical modular blocks. Average fire load of 13.99 $kg/m^2$ was used in the first test. In the second test, the weighting coefficient of 3.5 (the fire load of 50 $kg/m^2$) was used to simulate the worst fire scenario. The flashover of the medical modular block occurred at 62 minutes in the first test and 12 minutes in the second test. The heat resistance capacity of the external wall, the temperatures and deformations of the structural members satisfied the requirements of fire resistance performance of 90 minutes burning period. The total heat loads and the heat values for each test are calculated by theoretical equations. The duration of burning was predicted. The predicted results were compared with the test results, and they agree quite well.

• Journal of Korean Society for Atmospheric Environment
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• v.27 no.5
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• pp.545-557
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• 2011

The objective of this study was to estimate the trends of each pollutant using the air pollution monitoring networks data from January 2005 to December 2008 in Daegu area. Also, the spatial characteristics of each pollutant were determined using the Pearson correlation coefficients and COD (coefficients of divergence). In this study, the trends of hourly, monthly, seasonal, and total average concentrations of each pollutant for the 10 sites were analyzed. The Ihyeon site showed highest concentration for the $SO_2$, $NO_2$, and PM10}. In the case of $O_3$, the Jisan site showed highest concentration among the other sites. Also, industrial area presented highest concentration for the $SO_2$, CO, and PM10. On the other hand, $NO_2$ showed highest in commercial area. The IDW (inverse distance weighting) method was used to estimate characteristics of spatial distribution. The results provide identify spatial distribution for each pollutant. Also, the Pearson correlation coefficients and COD values provide spatial variability among the monitoring sites. The COD of each pollutant showed very low values for all of the sites pairs. On the other hand, the Pearson correlation coefficients showed high values for all of the sites pairs. Finally, analysis of spatial variability can be used to characterize the spatial uniformity and similarity of concentrations from each pollutant.