• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.4
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• pp.381-392
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• 2011

Pollutant loads calculated with unit factor method can not identity seasonal variations of pollutant inputs. Estimation of pollutant loads considering rainfall runoff can overcome these limits. SCS curve number method was applied to estimate runoff of each event of Koeup watershed of Koheung estuary lake. SCS curve numbers were calculated based upon land use, soil types of the catchment using GIS. Point and nonpoint source pollutant loads were summed up for total loads estimation. Those from nonpoint source were estimated by multiplying the calculated runoff and expected mean concentrations (EMC) presented by the Minister of Environment of Korea. DEM can present three dimensional views of a terrain, identity stream networks and flow accumulation. Furthermore, it can examine accumulated pollutant loads of specific point of a catchment. Therefore, cell based pollutant load estimation was attempted using DEM. ArcView was utilized to collect, store and manipulate spatial and attribute data of pollutant sources and features of the catchment. Cell-based DEM which was established by the GRID module of ARC/INFO was employed to estimate flows and pollutant loads.

• The Journal of the Korea Contents Association
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• v.20 no.11
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• pp.249-257
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• 2020

The study aims to explore whether the Supplier's social medial activities and the consumer's social media activities mediate between the characteristics of purchasing cosmetics and the intention of purchasing. To answer this question, a total of 321 consumers participated in the study, and a self-report type of questionnaires were utilized to collect the data. For the data analysis, descriptive statistical analysis and structural equation modeling(SEM) were applied. The results from the study are as follows. First, the characteristics of purchasing cosmetics did not affect the intention of purchasing cosmetics. Second, both the Supplier's and the consumer's social media activities positively predicted the intention of purchasing, among which the consumer's activities were ascertained to make more influential impact on the intention of purchasing cosmetics. Third, both Supplier's and consumer's social media activities completely mediated between the characteristics of purchasing cosmetics and the intention of purchasing. More discussions are suggested for marketing strategies in the study.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.6 s.312
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• pp.65-84
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• 2006

In this paper, we present an improved image formation model and propose a color image enhancement based on the model. In the presented image formation model, an input image is represented as a product of global illumination, local illumination, and reflectance. In the proposed color image enhancement, an input RGB color image is converted into an HSV color image. Under the assumption of white-light illumination, the H and S component images are remained as they are and the V component image only is enhanced based on the image formation model. The global illumination is estimated by applying a linear LPF with wide support region to the input V component image and the local illumination by applying a JND (just noticeable difference)-based nonlinear LPF with narrow support region to the processed image, where the estimated global illumination is eliminated from the input V component image. The reflectance is estimated by dividing the input V component image by the estimated global and local illuminations. After performing the gamma correction on the three estimated components, the output V component image is obtained from their product. Histogram modeling is next executed such that the final output V component image is obtained. Finally an output RGB color image is obtained from the H and S component images of the input color image and the final output V component image. Experimental results for the test image DB built with color images downloaded from NASA homepage and MPEG-7 CCD color images show that the proposed method gives output color images of very well-increased global and local contrast without halo effect and color shift.

• Journal of the Korea Convergence Society
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• v.7 no.1
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• pp.161-166
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• 2016

Deformation, stress and fatigue life due to the configuration of tie rod end are investigated in this study. Tie rod ends with the total three kinds of configurations are modelled with three dimensions through CATIA program and the simulation analysis is carried out with the ANSYS finite element analysis program. There are the models of A, B and C by the configuration of the rod end. As this study result, maximum deformation, maximum equivalent stress and maximum fatigue life of A type model are shown to be 0.0614mm, 160.27MPa and 336,930cycles respectively. And maximum deformation, maximum equivalent stress and maximum fatigue life of B type model are shown to be 0.0648mm, 90.889MPa and 1,171,000cycles respectively. Maximum deformation, maximum equivalent stree and maximum fatigue life of C type model are also shown to be 0.0402mm, 84.794MPa and 20,000,000cycles respectively. The durability of the models of tie rod ends through the values of this result could be estimated and the data for the design and development of more improved tie rod end could be secured. And it is possible to be grafted onto the convergence technique at design and be shown as the esthetic sense.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.1
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• pp.12-25
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• 2009

The aim of this study is to analyze the periodical and spatial characteristics of urban crime and to find out the factors that affect the crime occurrence. For these, crime data of Masan City was examined and crime occurrence pattern is ploted on a map using crime density and criminal hotspot analysis. The spatial relationship of crime occurrence and factors affecting crime were also investigated using ESDA (Exploratory Spatial Data Analysis) and SAR (Spatial Auto-Regression) model. As a result, it was found that crimes had strong tendency of happening during a certain period of time and with spatial contiguity. Spatial contiguity of crimes was made clear through the spatial autocorrelation analysis on 5 major crimes. Especially, robbery revealed the highest spatial autocorrelation. However as a autocorrelation model, Spatial Error Model(SEM) had statistically the highest goodness of fit. Moreover, the model proved that old age population ratio, property tax, wholesale-retail shop number, and retail & wholesale number were statistically significant that affect crime occurrence of 5 most major crimes and theft crime. However population density affected negatively on assault crime. Lastly, the findings of this study are expected to provide meaningful ideas to make our cities safer with U-City strategies and services.

• The KIPS Transactions:PartD
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• v.8D no.2
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• pp.154-165
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• 2001

A number of attempts to develop methods for measuring software effort have been focused on the area of software engineering and many models have also been suggested to estimate the effort of software projects. Almost all current models use algorithmic or statistical mechanisms, but the existing algorithmic effort estimation models have failed to produce accurate estimates. Furthermore, they are unable to reflect the rapidly changing technical environment of software development such as module reuse, 4GL, CASE tool, etc. In addition, these models do not consider the paradigm shift of software engineering and information systems(i.e., Object Oriented system, Client-Server architecture, Internet/Intranet based system etc.). Thus, a new approach to software effort estimation is needed. After reviewing and analyzing the problems of the current estimation models, we have developed a model and a system architecture that will improve estimation performance. In this paper, we have adopted a neural network model to overcome some drawbacks and to increase estimation performance. We will also address the efficient system architecture and estimation procedure by a similar case-based approach and finally suggest the heuristic search method to find the best estimate of target project through empirical experiments. According to our experiment with the optimally parsimonious neural network model the mean error rate was significantly reduced to 14.3%.

• Korean Journal of Remote Sensing
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• v.36 no.3
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• pp.487-501
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• 2020

As a viable option for retrieval of LST (Land Surface Temperature), this paper presents a DNN (Deep Neural Network) based approach using 148 Landsat 8 images for South Korea. Because the brightness temperature and emissivity for the band 10 (approx. 11-㎛ wavelength) of Landsat 8 are derived by combining physics-based equations and empirical coefficients, they include uncertainties according to regional conditions such as meteorology, climate, topography, and vegetation. To overcome this, we used several land surface variables such as NDVI (Normalized Difference Vegetation Index), land cover types, topographic factors (elevation, slope, aspect, and ruggedness) as well as the T₀ calculated from the brightness temperature and emissivity. We optimized four seasonal DNN models using the input variables and in-situ observations from ASOS (Automated Synoptic Observing System) to retrieve the LST, which is an advanced approach when compared with the existing method of the bias correction using a linear equation. The validation statistics from the 1,728 matchups during 2013-2019 showed a good performance of the CC=0.910~0.917 and RMSE=3.245~3.365℃, especially for spring and fall. Also, our DNN models produced a stable LST for all types of land cover. A future work using big data from Landsat 5/7/8 with additional land surface variables will be necessary for a more reliable retrieval of LST for high-resolution satellite images.

• Journal of Korean Society of Forest Science
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• v.101 no.2
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• pp.185-194
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• 2012

The purpose of this contribution is to develop the framework of a methodology for identifying potential errors in georeferencing and in an application of it using specimens of Ox-Knee, Achyranthes bidentata Blume in Korea. At infraspecific level, uncertainty of identification showed that 41% of A. bidentata var. japonica and 28% of var. bidentata were misidentified, suggesting that the uncertainty level was independent of the reliability of experts' identification. For georeference specimen records, 71 specimens out of total 303 were selected and utilized as occurrence data: Uncertainty was 32.4 km at maximum and was 0.1297 km at minimum (mean = 4,055 m, s.d. = 5,772 m). Var. japonica is common throughout most of the southeastern Korea and west coastal areas, while var. bidentata has been found as far north as Gyeonggi and Gangwon provinces. We modelled the potential distribution of two varieties using Bioclim approach in Korea based on several environmental factors. Our results indicated the most important region for var. japonica lies the west coast ranges and southern area, while for Chungcheongnam-do of potential high diversity occurs for var. bidentata. This study shows that the major factors to determine the distribution patterns of two varieties were thermal factors, rather than precipitation. The Bioclim model using geocode and georeferencing data makes the information increasingly useful and reliable. To improve data quality, it requires full management from data collection to final databases including data cleaning.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.9
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• pp.143-147
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• 2016

Recently, digital tomosynthesis system (DTS) has been developed to reduce overlap using conventional X-ray and to overcome high patient dose problem using computed tomography (CT). The purpose of this study was to develop image reconstruction algorithm and to evaluate image characteristics and dose with chest digital tomosynthesis (CDT) system. Image reconstruction was used for filtered back-projection (FBP) methods and system geometry was constructed ${\pm}10^{\circ}$, ${\pm}15^{\circ}$, ${\pm}20^{\circ}$, and ${\pm}30^{\circ}$ angular range for acquiring phantom images. Image characteristics carried out root mean square error (RMSE) and signal difference-to-noise ratio (SDNR), and dose is evaluated effective dose with ${\pm}20^{\circ}$ angular range. According to the results, the phantom image with slice thickness filter has superb RMSE and SDNR, and effective dose was 0.166 mSv. In conclusion, we demonstrated usefulness of developed CDT image reconstruction algorithm and we constructed CDT basic output data with measuring effective dose.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.1
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• pp.63-70
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• 2017

In this paper, a magnetic flux leakage(MFL) based steel bar damage detection was first researched to quantify the signals from damages on the wire rope. Though many researches inspecting damages using a MFL method was proceeded until the present, the researches are at the level that diagnose whether damages are or not. This has limitation to take measures in accordance with the damage level. Thus, a MFL inspection system was modeled using a finite element analysis(FEM) program dealing with electromagnetism problems, and a steel bar specimen was adopted as a ferromagnetic object. Then, an experimental study was also carried out to verify the simulation results with a steel bar which has same damage conditions as the simulation. The MFL signals was nearly not affected by the increase of the inspection velocity, and the magnitudes of the signals are not identical according to the change of the defect width even the defects have same depth. On the basis of the analysis, the signal properties from the damages were extracted to classify the type of damages, and it could be confirmed that classification of damages using extracted signal properties is feasible.