• Journal of the HCI Society of Korea
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• v.2 no.2
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• pp.35-43
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• 2007

This paper presents a system for image matching and recognition based on image feature detection and description techniques from artificial satellite photographs. We propose some kind of parameters from the varied environmental elements happen by image handling process. The essential point of this experiment is analyzes that affects match rate and recognition accuracy when to change of state of each parameter. The proposed system is basically inspired by Lowe's SIFT(Scale-Invariant Transform Feature) algorithm. The descriptors extracted from local affine invariant regions are saved into database, which are defined by k-means performed on the 128-dimensional descriptor vectors on an artificial satellite photographs from Google earth. And then, a label is attached to each cluster of the feature database and acts as guidance for an appeared building's information in the scene from camera. This experiment shows the various parameters and compares the affected results by changing parameters for the process of image matching and recognition. Finally, the implementation and the experimental results for several requests are shown.

• Journal of Environmental Health Sciences
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• v.41 no.2
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• pp.90-101
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• 2015

Objective: This study was conducted to develop a chemical oxygen demand (COD) regression model using water quality monitoring data (January, 2014) obtained from the Han River auto-monitoring stations. Methods: Surface water quality data at 198 sampling stations along the six major areas were assembled and analyzed to determine the spatial distribution and clustering of monitoring stations based on 18 WQPs and regression modeling using selected parameters. Statistical techniques, including combined genetic algorithm-multiple linear regression (GA-MLR), cluster analysis (CA) and principal component analysis (PCA) were used to build a COD model using water quality data. Results: A best GA-MLR model facilitated computing the WQPs for a 5-descriptor COD model with satisfactory statistical results ($r^2=92.64$,$Q{^2}_{LOO}=91.45$,$Q{^2}_{Ext}=88.17$). This approach includes variable selection of the WQPs in order to find the most important factors affecting water quality. Additionally, ordination techniques like PCA and CA were used to classify monitoring stations. The biplot based on the first two principal components (PCs) of the PCA model identified three distinct groups of stations, but also differs with respect to the correlation with WQPs, which enables better interpretation of the water quality characteristics at particular stations as of January 2014. Conclusion: This data analysis procedure appears to provide an efficient means of modelling water quality by interpreting and defining its most essential variables, such as TOC and BOD. The water parameters selected in a COD model as most important in contributing to environmental health and water pollution can be utilized for the application of water quality management strategies. At present, the river is under threat of anthropogenic disturbances during festival periods, especially at upstream areas.

• Journal of KIISE
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• v.42 no.10
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• pp.1239-1246
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• 2015

Cell counting is extensively used to analyze cell growth in biomedical research, and as a result automated cell counting methods have been developed to provide a more convenient and means to analyze cell growth. However, there are still many challenges to improving the accuracy of the cell counting for cells that proliferate abnormally, divide rapidly, and cluster easily, such as cancer cells. In this paper, we present an automated cell counting method for HeLa cells, which are used as reference for cancer research. We recognize and classify the morphological conditions of the cells by using a cell segmentation algorithm based on cell membrane extraction, and we then apply a cell back-tracking algorithm to improve the cell counting accuracy in cell clusters that have indistinct cell boundary lines. The experimental results indicate that our proposed segmentation method can identify each of the cells more accurately when compared to existing methods and, consequently, can improve the cell counting accuracy.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.5
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• pp.97-109
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• 2003

This study is mainly conducted to derive the design drought rainfall by the consecutive duration using probability weighted moments with rainfall in the regional drought frequency analysis. It is anticipated to suggest optimal design drought rainfall of hydraulic structures for the water requirement and drought frequency of occurrence for the safety of water utilization through this study. Preferentially, this study was conducted to derive the optimal regionalization of the precipitation data that can be classified by the climatologically and geographically homogeneous regions all over the regions except Cheju and Ulreung islands in Korea. Five homogeneous regions in view of topographical and climatological aspects were accomplished by K-means clustering method. Using the L-moment ratio diagram and Kolmogorov-Smirnov test, generalized extreme value distribution was confirmed as the best fitting one among applied distributions. At-site and regional parameters of the generalized extreme value distribution were estimated by the method of L-moments. Design drought rainfalls using L-moments following the consecutive duration were derived by the at-site and regional analysis using the observed and simulated data resulted from Monte Carlo techniques. Relative root-mean-square error (RRMSE), relative bias (RBIAS) and relative reduction (RR) in RRMSE for the design drought rainfall derived by at-site and regional analysis in the observed an simulated data were computed and compared. In has shown that the regional frequency analysis procedure can substantially more reduce the RRMSE. RBIAS and RR in RRMSE than those of at-site analysis in the prediction of design drought rainfall. Consequently, optimal design drought rainfalls following the regions and consecutive durations were derived by the regional frequency analysis.

• World Technopolis Review
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• v.1 no.1
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• pp.56-64
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• 2012

This paper provides a case study to explore the Kitakyushu case as a good referential example on STP development for rejuvenation of declining industrial city. The major data for the case, basically, has been sourced from some materials published by the municipality of Kitakyushu City, the website of the Kitakyushu Science and Research Park (KSRP) etc. The City of Kitakyushu has promoted the KSRP development to overcome industrial decline and stimulate city renaissance as a new industrial city. The core of the development was to develop a high-level education and research environment by gathering several HEIs into one campus. Based on the environment, the Kitakyushu Foundation for the Advancement of Industry and Science and Technology (FAIS) played the critical role as a coupler to make various networks and boost industry-academiaadministration innovation. The KSRP, and then, has been designated as a project area of some cluster projects initiated by the central government. It means that local projects can be synchronized, synergized and synthesized with national projects in the KSRP. In addition, through a series of the environmental approach from the Kitakyushu Eco-town Project to the Low Carbon Society Project, the development of the KSRP is being extended into the region. In the Kitakyushu case, networking is the essence of the KSRP development from the planning stage. First of all, the plan put emphasis on networking of academia for the knowledge creation based on competitive collaboration that is expected as the mainspring of rejuvenating declining industrial area and making a new industrial city that the plan aimed. Then, the roles of two organizations are very important for networking, especially networking of networks: the Campus Management Committee as an interface and the FAIS as a coupler. STP development without some strategic considerations for networking as the way of interaction among its participants cannot be a tool to promote innovation and rejuvenate a declining industrial area. The Kitakyushu case mentioned above explains the matter clearly.

• Journal of the Korean Society of Clothing and Textiles
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• v.27 no.11
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• pp.1338-1349
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• 2003

The color of apparels has the close interdependency on the skin colors of the wearers. This study was carried out to group the skin colors of Korean males into several similar skin colors and to analyze their preference colors. The skin colors were measured quantitatively and classified into several clusters that has similar hue, value and chroma with Munsell color system that is internationally used to communicate the colors. Sample size was 420 Korean males. With color spectrometer, JX-777, 4 points of the body were measured. All subjects had been shown with 40 color chips and answered their preference colors. Data were analysed by K-means Cluster analysis, Duncan test, Frequency and Chi square test using SPSS WIN 10 statistical package. Findings were as follows: 1. The skin colors of Korean males were mixed with skin colors of YR, R, and Y. 2. 420 subjects who have YR color were clustered in 3 kinds of skin color groups. 3. The average face color of total subjects was 4.81YR 5.91/4.97 in Munsell color system, 60.74 in L value, 13.71 in a value, 24.54 in b value. 136 observations out of 420 subjects were composed of Type 1: 4.50YR 6.35/4.87 and 192 observations were composed of Type 2: 4.62YR 5.86/5.12 and 92 observations were composed of Type 3: 5.67YR 5.37/4.79. 4. The average skin color of total 420 subjects was 6.26YR 6.07/4.41 and 62.33 in L value, 10.64 in a value, 23.48 in b value. The average skin color of Type 1 was 6.27YR 6.44/4.27 and of Type 2 was 6.15YR 5.91/4.49 and of Type 3 was 6.49YR 5.84/4.43 respectively. 5. 3 groups showed that the most preference color of sport$.$casual was 2.5Y 8/16 and 7.5PB 4/16 and the most preference color to their skins was 7.5PB 4/16 and 7.5YR 7/16.

• Journal of the Korean Geographical Society
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• v.40 no.6 s.111
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• pp.653-670
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• 2005

The purpose of this study is to explore a spatial agglomeration characteristics and innovative milieu of the shoemaking industry in Seoul. In order to explain it, currently discussed dynamic agglomeration economies approach is applied and as an example, shoemaking industry in Seoul has been analyzed. The result of this research can be boardly summarized into two points. Frist, agglomeration economy is changing from urbanization economy to localization economy in this newly rising core of shoemaking industry which is Sung-Su dong area. Also, cooperative effects based on collective efficiency between companies and people are being generated within the area. This is largely affected by networking infrastructure between companies and people within the area, non-trade dependency and social capital acclamation. Secondly, the lack of institutional agglomeration formation in this area is considered to be the obstacle for the long-term development and innovation spin-off. This means recognition switch-over and institutional concern and support is needed in the future from the public sector.

• Fashion & Textile Research Journal
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• v.15 no.5
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• pp.682-693
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• 2013

Camouflage is evaluated by scientific principle in the fields of biology, military science, and art. It has a strong influence on contemporary fashion and means exposure with concealment. This study analyzed the visual characteristics of camouflage patterns in fashion design through documentaries and fashion photos. The fashion design results areas follow. The simple blending of a disruptive motif indicated an inaccurate repetition of a disruptive motif, the discontinuous or continuous connection of disruptive motif, the irregular repetition of a disruptive animal silhouette, the collage of a different disruptive motif, the craft of a disruptive motif and the intensive color match of a disruptive motif. It represented the maximization of complication, fantastic and fanciness. The overlap of a disruptive motif showed the overlap of disruptive print patterns with transparency and an overlap of different fabrics with a disruptive pattern. It represented spatial relationships of three dimensions as well as the maximization of visual illusion and the reinforcement of attractiveness. The blurring of a disruptive motif showed the pointage of disruptive motif, the pointage of image, value gradation, the whole blurring of a disruptive pattern cluster and stained appearance. It represented the obscurity of motif form, the uncertainty of object and double meaning. The trompe l'oeil of a partial background object showed the realistic and the painterly imitation of color and texture for partial objects through a close-up. It represented amazement and pleasure by illusion, scarcity and the decoration of surface and synecdochical remind. In conclusion, camouflage in fashion was weakened and modified from a classical military context by a unique expression of various motifs.

• Journal of Korea Port Economic Association
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• v.34 no.2
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• pp.51-68
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• 2018

This paper compares the differences in management performance in the logistics market and analyzes the differences in business characteristics depending on the industry types. In addition, the effects of industry types and business characteristics on management performance are examined. The analysis method used is ANOVA and K-means clustering. The implication of the study are as follows. First, in the logistics market in Japan, there was a difference in management performance among the types of industry. The warehousing service type had the highest profitability and stability among all the industry types. Second, differences in business characteristics by industry types were tested. It was found that offshore cargo transportation type was more capital intensive than the other types. In addition, warehousing service type had higher business leadership and credit transaction than others. Third, industry types and clusters based on business characteristics had a significant impact on management performance through interaction effects. For the profitability variables in detail, other clusters had a significant effect between transportation types(onshore and offshore cargo) and warehousing service type. On the other hand, in stability variables, one cluster was effective in all types, which is a characteristic that lowers both capital intensity and business leadership.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.154-154
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• 2018

To interpret the climate projections for the future as well as present, recognition of the consequences of the climate internal variability and quantification its uncertainty play a vital role. The Korean Peninsula belongs to the Far East Asian Monsoon region and its rainfall characteristics are very complex from time and space perspective. Its internal variability is expected to be large, but this variability has not been completely investigated to date especially using models of high temporal resolutions. Due to coarse spatial and temporal resolutions of General Circulation Models (GCM) projections, several studies adopted dynamic and statistical downscaling approaches to infer meterological forcing from climate change projections at local spatial scales and fine temporal resolutions. In this study, stochastic downscaling methodology was adopted to downscale daily GCM resolutions to hourly time scale using an hourly weather generator, the Advanced WEather GENerator (AWE-GEN). After extracting factors of change from the GCM realizations, these were applied to the climatic statistics inferred from historical observations to re-evaluate parameters of the weather generator. The re-parameterized generator yields hourly time series which can be considered to be representative of future climate conditions. Further, 30 ensemble members of hourly precipitation were generated for each selected station to quantify uncertainty. Spatial map was generated to visualize as separated zones formed through K-means cluster algorithm which region is more inconsistent as compared to the climatological norm or in which region the probability of occurrence of the extremes event is high. The results showed that the stations located near the coastal regions are more uncertain as compared to inland regions. Such information will be ultimately helpful for planning future adaptation and mitigation measures against extreme events.