• Genomics & Informatics
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• v.12 no.4
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• pp.145-150
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• 2014

Recent technical advances, such as chromatin immunoprecipitation combined with DNA microarrays (ChIp-chip) and chromatin immunoprecipitation-sequencing (ChIP-seq), have generated large quantities of high-throughput data. Considering that epigenomic datasets are arranged over chromosomes, their analysis must account for spatial or temporal characteristics. In that sense, simple clustering or classification methodologies are inadequate for the analysis of multi-track ChIP-chip or ChIP-seq data. Approaches that are based on hidden Markov models (HMMs) can integrate dependencies between directly adjacent measurements in the genome. Here, we review three HMM-based studies that have contributed to epigenetic research, from a computational perspective. We also give a brief tutorial on HMM modelling-targeted at bioinformaticians who are new to the field.

• Journal of Korea Water Resources Association
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• v.43 no.1
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• pp.15-24
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• 2010

Regional frequency analysis is often used to overcome the limitation of point frequency analysis to estimate probability rainfall depths. However, point frequency analysis is still used in drought analyses. This study proposed a practical method to categorize the homogeneous regions of drought characteristics for the analyses of regional characteristics of droughts in Korea. Using rainfall data from 58 observation stations managed by the Korea Meteorological Administration, this study calculated drought attributes, i.e., mean drought indices for various durations using the Standardized Precipitation Index (SPI) and drought severities expressed by durations, depth, and intensity. The drought attributes provided useful information for categorizing stations into the hydrological homogeneous regions. This study introduced a cluster analysis with K-means techniques to group observation stations. The cluster analysis grouped observation stations into 6 regions in Korea. The data in the hydrological homogeneous region would be used in spatial analysis of drought characteristics and drought regional frequency analysis.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.186-188
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• 2005

Because forest fire changes the direction according to the environmental elements, it is difficult to predict the direction of it. Currently, though some researchers have been studied to which predict the forest fire occurrence and the direction of it, using the remote detection technique, it is not enough and efficient. And recently because of the development of the sensor technique, a lot of In-Situ sensors are being developed. These kinds of In-Situ sensor data are used to collect the environmental elements such as temperature, humidity, and the velocity of the wind. Accordingly we need the prediction technique about the environmental elements analysis and the direction of the forest fire, using the In-Situ sensor data. In this paper, as a technique for predicting the direction of the forest fire, we propose the correlation analysis technique about In-Situ sensor data such as temperature, humidity, the velocity of the wind. The proposed technique is based on the clustering method and clusters the In-Situ sensor data. And then it analyzes the correlation of the multivariate correlations among clusters. These kinds of prediction information not only helps to predict the direction of the forest fire, but also finds the solution after predicting the environmental elements of the forest fire. Accordingly, this technique is expected to reduce the damage by the forest fire which occurs frequently these days.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.4
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• pp.189-199
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• 2014

Floodplain is a flat plain between levees and rivers. This paper suggests a methodology for analyzing the land uses in the Nakdong River floodplain using the RapidEye imagery and the given LiDAR(LIght Detection And Ranging) DEM(Digital Elevation Models). First, the levee boundaries are generated using the LiDAR DEM, and the area of the floodplain is extracted from the given RapidEye imagery. The land uses in the floodplain are identified in the extracted RapidEye imagery by the ISODATA(Iterative Self-Organizing Data Analysis Technique Analysis) clustering. The overall accuracy of the identified land uses by the ISODATA clustering is 91%. Analysis of the identified land uses in the floodplain is implemented by counting the number of the pixels constituting the land cover clusters. The results of this research shows that the area of the river occupies 46%, the area of the bare soil occupies 36%, the area of the marsh occupies 11%, and the area of the grass occupies 7% in the identified floodplain.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.5 no.3
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• pp.76-85
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• 2024

The purpose of this study is to propose a new method of analysis focusing on interconnections between species rather than traditional biodiversity analysis, which represents ecosystems in terms of species and individual counts such as species diversity and species richness. This new approach aims to enhance our understanding of ecosystem networks. Utilizing data from the 4th National Natural Environment Survey (2014-2018), the following eight taxonomic groups were targeted for our study: herbaceous plants, woody plants, butterflies, Passeriformes birds, mammals, reptiles & amphibians, freshwater fishes, and benthonic macroinvertebrates. A co-occurrence frequency analysis was conducted using nationwide data collected over five years. As a result, in all eight taxonomic groups, the degree value represented by a linear regression trend line showed a slope of 0.8 and the weighted degree value showed an exponential nonlinear curve trend line with a coefficient of determination (R²) exceeding 0.95. The average value of the clustering coefficient was also around 0.8, reminiscent of well-known social phenomena. Creating a combination set from the species list grouped by temporal information such as survey date and spatial information such as coordinates or grids is an easy approach to discern species distributed regionally and locally. Particularly, grouping by species or taxonomic groups to produce data such as co-occurrence frequency between survey points could allow us to discover spatial similarities based on species present. This analysis could overcome limitations of species data. Since there are no restrictions on time or space, data collected over a short period in a small area and long-term national-scale data can be analyzed through appropriate grouping. The co-occurrence frequency analysis enables us to measure how many species are associated with a single species and the frequency of associations among each species, which will greatly help us understand ecosystems that seem too complex to comprehend. Such connectivity data and graphs generated by the co-occurrence frequency analysis of species are expected to provide a wealth of information and insights not only to researchers, but also to those who observe, manage, and live within ecosystems.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.1
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• pp.63-70
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• 2014

This study is to analyze impact of geography and timing on the real transactions prices of apartment complexes in Seoul using data provided by the Ministry of Land, Infrastructure and Transport. The average real transactions and location data of apartment complex was combined into the GIS data. First, the pattern of apartment real transaction price change by period and by area was analyzed by kriging, the one of the spatial interpolation technique. Second, to analyze the pattern of apartment market price change by administrative district(administrative 'Dong' unit), the average of market price per unit area was calculated and converted to Moran I value, which was used to analyze the clustering level of the real transaction price. Through the analysis, spatial-temporal distribution pattern can be found and the type of change can be forecasted. Therefore, this study can be referred as of the base data research for the housing or local policies. Also, the regional unbalanced apartment price can be presented by analyzing the vertical pattern of the change in the time series and the horizontal pattern of the change based on GIS.

• Journal of Wetlands Research
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• v.15 no.3
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• pp.397-406
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• 2013

Wetland conservation plan has been established to protect ecologically important wetlands based on vegetation integrity, spatial distribution of endangered species, but recently more demands are concentrated on the landscape ecological approaches such as topological relationship, neighboring area, spatial arrangements between wetlands at the broad scale. Landscape ecological analysis and graph theory are conducted to identify spatial characteristics related to core nodes and weak links of wetland networks in Nakdong basin. Regular planar model, which is selected for wetland networks, is applied in the Nakdong basin. The analysis indicates that 5 regional groups and 4 core wetlands are extracted with 15km threshold distance. The IIC and PC values based on the binary and probability models suggest that the wetland group C composed of main stream of Nakdong river and Geumho river is the most important area for wetland network. Wetland conservation plan, restoration projected of damaged and weak links between wetlands should be proposed through evaluating the node, links, and networks from wetlands at the local to the regional scale in Nakdong basin.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.6_1
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• pp.507-516
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• 2007

Segmentation and organization of the LiDAR (Light Detection and Ranging) data of the Earth's surface are difficult tasks because the captured LiDAR data are composed of irregularly distributed point clouds with lack of semantic information. The reason for this difficulty in processing LiDAR data is that the data provide huge amount of the spatial coordinates without topological and/or relational information among the points. This study introduces LiDAR data segmentation technique by utilizing histograms of the LiDAR height image data and analyzing roof shape for 3D reconstruction and visualization of the buildings. One of the advantages in utilizing LiDAR height image data is no registration required because the LiDAR data are geo-referenced and ortho-projected data. In consequence, measurements on the image provide absolute reference coordinates. The LiDAR image allows measurement of the initial building boundaries to estimate locations of the side walls and to form the planar surfaces which represent approximate building footprints. LiDAR points close to each side wall were grouped together then the least-square planar surface fitting with the segmented point clouds was performed to determine precise location of each wall of an building. Finally, roof shape analysis was performed by accumulated slopes along the profiles of the roof top. However, simulated LiDAR data were used for analyzing roof shape because buildings with various shapes of the roof do not exist in the test area. The proposed approach has been tested on the heavily built-up urban residential area. 3D digital vector map produced by digitizing complied aerial photographs was used to evaluate accuracy of the results. Experimental results show efficiency of the proposed methodology for 3D building reconstruction and large scale digital mapping especially for the urban area.

• Journal of the Korean Society of Industry Convergence
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• v.21 no.1
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• pp.29-36
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• 2018

Low pressure casting process for unidirectional carbon fiber reinforced aluminum (UD-CF/Al) composites which is an infiltration route of molten Al into porous UD-CF preform has been a cost-effective way to obtain metal matrix composites (MMCs) but, easy to cause non-uniform fiber distribution as CF clustering. Such clustered CFs have been a problem to decrease the density and thermal conductivity (TC) of composites, due to the existence of pores in the clustered area. To obtain high thermal performance composites for heat-sink application, the relationship between fiber distribution and porosity has to be clearly investigated. In this study, the CF distribution was evaluated with quantification approach by using two-dimensional spatial distribution method as local number 2-dimension (LN2D) analysis. Note that the CFs distribution in composites sensitively changed by sizes of Cu bridging particles between the CFs added in the UD-CF preform fabrication stage, and influenced on only $LN2D_{var}$ values.

• Korean Institute of Interior Design Journal
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• v.20 no.2
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• pp.47-54
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• 2011

In Alvar Aalto's designs, important factors of complex building designs including Wolfsburg cultural center are that they insinuate how to develop each architectural type and how to combine them in a building. The humane and physical background studies, and wholistic and systematic approaches are adopted to fulfill research purposes. Comparison with other buildings are necessary to reveal true meaning of this building. The result of analysis show characteristics of Wolfsburg cultural center as follows; hybrid composition of mass and elevation, spatial effect using level difference and light, massing variation of roof, and creating space for various activities. Wolfsburg cultural center designed in late 1950s has greatly affected Aalto's later works through various architectural experiments because it is the first cultural complex project that combined various architectural types. Especially library in the cultural center has shown transitional characteristics to famous fan-type libraries of 1960s while maintained features about Viipuri library. Wolfsburg cultural center act as an another type which present new principles of clustering, massing and exterior design. Its true meaning lies in forming a humanizing place beyond spatial configuration.