• Journal of the Korean housing association
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• v.19 no.6
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• pp.85-93
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• 2008

This study analyzes areas, traffic lines and characteristics of block of traditional villages in order to suggest how to build urban village in the way that can solve problems occurring in residential areas these days. The study showed the following results: 1) Traditional villages have definite boundary and entrance, and the community area for the villages is close to the entrance to encourage community activities of villagers. 2) With an access in the form of a blind alley branched from the main road, traditional villages form a small-sized clustering and encourage community activities in a natural way. 3) Formed of block with a pattern of net, blind alley or standing in a line on both sides, traditional villages help residents to form close relations between. These findings suggest that for building desirable urban villages, 1) they should have definite boundary, 2) size and location of community area should be determined in the way to activate community activities of residents, 3) roads inside the village should have branched form rather than standardized check pattern so that small-sized clustering could be formed along the branched inner roads, and 4) clustering in villages should be arranged in a line on both sides or in the form of a blind alley giving consideration to the length and width of roads. The roads should be also of a closed type so that residents could create strong bonds with their neighbors.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.2 no.2
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• pp.120-128
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• 2021

The objective of this study was to analyze the genotype of black-spotted pond frog (Pelophylax nigromaculatus) using seven microsatellite loci to quantify its genetic diversity and population structure throughout the spatial scale of basins of Han, Geum, Yeongsan, and Nakdong Rivers in South Korea. Genetic diversities in these four areas were compared using diversity index and inbreeding coefficient obtained from the number and frequency of alleles as well as heterozygosity. Additionally, the population structure was confirmed with population differentiation, Nei's genetic distance, multivariate analysis, and Bayesian clustering analysis. Interestingly, a negative genetic diversity pattern was observed in the Han River basin, indicating possible recent habitat disturbances or population declines. In contrast, a positive genetic diversity pattern was found for the population in the Nakdong River basin that had remained the most stable. Results of population structure suggested that populations of black-spotted pond frogs distributed in these four river basins were genetically independent. In particular, the population of the Nakdong River basin had the greatest genetic distance, indicating that it might have originated from an independent population. These results support the use of genetics in addition to designations strictly based on geographic stream areas to define the spatial scale of populations for management and conservation practices.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3112-3127
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• 2018

Since time series clustering is performed without prior information, it is used for exploratory data analysis. In particular, clusters of time series with similar shapes can be used in various fields, such as business, medicine, finance, and communications. However, existing time series clustering algorithms have a problem in that time series with different shapes are included in the clusters. The reason for such a problem is that the existing algorithms do not consider the limitations on the size of the generated clusters, and use a dimension reduction method in which the information loss is large. In this paper, we propose a method to alleviate the disadvantages of existing methods and to find a better quality of cluster containing similarly shaped time series. In the data preprocessing step, we normalize the time series using z-transformation. Then, we use piecewise aggregate approximation (PAA) to reduce the dimension of the time series. In the clustering step, we use density-based spatial clustering of applications with noise (DBSCAN) to create a precluster. We then use a modified K-means algorithm to refine the preclusters containing differently shaped time series into subclusters containing only similarly shaped time series. In our experiments, our method showed better results than the existing method.

• Spatial Information Research
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• v.2 no.2
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• pp.175-188
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• 1994

A competitive learning network was proposed as unsupervised training method of remote sensing data, Its performance and computational re¬quirements were compared with conventional clustering techniques such as Se¬quential and K - Means. An airborne remote sensing data set was used to study the performance of these classifiers. The proposed algorithm required a little more computational time than the conventional techniques. However, the perform¬ance of competitive learning network algorithm was found to be slightly more than those of Sequential and K - Means clustering techniques.

• Journal of the Korean Geographical Society
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• v.42 no.4
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• pp.616-631
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• 2007

Residential differentiation is an academic theme which has been given enormous attention in urban studies. This is due to the fact that residential segregation can be seen as one of the best indicators for socio-spatial dialectics occurring on urban space. Measuring how one population group is differentiated from the other group in terms of residential space has been a focal point in the residential segregation studies. The index of dissimilarity has been the most extensively used one. Despite its popularity, however, it has been accused of inability to capture the degree of spatial clustering that unevenly distributed population groups usually display. Further, the spatial indices of segregation which have been introduced to edify the problems of the index of dissimilarity also have some drawbacks: significance testing methods have never been provided; recent advances in spatial statistics have not been extensively exploited. Thus, the main purpose of the research is to devise a spatial separation measure which is expected to gauge not only how unevenly two population groups are distributed over urban space, but also how much the uneven distributions are spatially clustered (spatial dependence). The main results are as follows. First, a new measure is developed by integrating spatial association measures and spatial chi-square statistics. A significance testing method based on the generalized randomization test is also provided. Second, a case study of residential differentiation among groups by educational attainment in major Korean metropolitan cities clearly shows the applicability of the analytical framework presented in the paper.

• Journal of Korea Spatial Information System Society
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• v.7 no.3 s.15
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• pp.45-53
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• 2005

Nowadays, using the mobile communication devices, such as a mobile phone, PDA, telematics device, and so forth, are increasing. The large parts of the services with these mobile devices are the position tracking and the route planning. For offering these services, it is increasing the use of the spatial data on the mobile environment. Although the storage of mobile device expands more than before, it still lacks the necessary storage on the spatial data. In this paper, lossy compression technique on the spatial data is suggested, and then it is analyzed the compression ratio and the amount of loss data by the test. Suggested compression technique on the spatial data at this paper is applied to the real-data, and others methods, suggested at the previous studies, is applied to same data. According as the results from both are compared and analyzed, compression technique suggested at this study shows better performance when the compression result is demanded the high position accuracy.

• Journal of the Economic Geographical Society of Korea
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• v.11 no.2
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• pp.175-191
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• 2008

In the early stage of industrial development, most of software companies were agglomerated at the CBD(Central Business Districts) in Seoul. However, the spatial distribution pattern of Korean Software industry has been changed according to the propagation of broadband, the change in rents, the governmental policy for industrial districts. In this research, using the software year book at 1997 and 2007, the emerging new pattern was analyzed using spatial clustering analysis. As a results of research, the spatial distribution was expanded in morphological changes. However, it was found that there was not a significant difference in a degree of accumulation. In the aspect of behavioral movement of companies, they tend to be relocated from the CBD to urban fringes and their movement is related to the product life cycle in selecting the clustered place.

• Korean Journal of Acupuncture
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• v.36 no.4
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• pp.292-299
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• 2019

Objectives : DongUiBoGam is one of the representative medical literatures in Korea. We used text mining methods and analyzed the characteristics of the indications of each meridian in the second chapter of DongUiBoGam, WaeHyeong, which addresses external body elements. We also visualized the relationships between the meridians and the disease sites. Methods : Using the term frequency-inverse document frequency (TF-IDF) method, we quantified values regarding the indications of each meridian according to the frequency of the occurrences of 14 meridians and 14 disease sites. The spatial patterns of the indications of each meridian were visualized on a human body template according to the TF-IDF values. Using hierarchical clustering methods, twelve meridians were clustered into four groups based on the TF-IDF distributions of each meridian. Results : TF-IDF values of each meridian showed different constellation patterns at different disease sites. The spatial patterns of the indications of each meridian were similar to the route of the corresponding meridian. Conclusions : The present study identified spatial patterns between meridians and disease sites. These findings suggest that the constellations of the indications of meridians are primarily associated with the lines of the meridian system. We strongly believe that these findings will further the current understanding of indications of acupoints and meridians.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3108-3120
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• 2019

Point cloud is widely used in 3D applications due to the recent advancement of 3D data acquisition technology. Polygonal mesh-based compression has been dominant since it can replace many points sharing a surface with a set of vertices with mesh structure. Recent point cloud-based applications demand more point-based interactivity, which makes point cloud compression (PCC) becomes more attractive than 3D mesh compression. Interestingly, an exploration activity has been started to explore the feasibility of PCC standard in MPEG. In this paper, a new color attribute compression method is presented for point cloud data. The proposed method utilizes the spatial redundancy among color attribute data to construct a color palette. The color palette is constructed by using K-means clustering method and each color data in point cloud is represented by the index of its similar color in palette. To further improve the compression efficiency, the spatial redundancy between the indices of neighboring colors is also removed by marking them using a flag bit. Experimental results show that the proposed method achieves a better improvement of RD performance compared with that of the MPEG PCC reference software.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.223-224
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• 2021

Recently, k-farthest neighbor (kFN) queries have not as much attention as k-nearest neighbor (kNN) queries. Therefore, this study considers moving k-farthest neighbor (MkFN) queries for spatial network databases. Given a positive integer k, a moving query point q, and a set of data points P, MkFN queries can constantly retrieve k data points that are farthest from the query point q. The challenge with processing MkFN queries in spatial networks is to avoid unnecessary or superfluous distance calculations between the query and associated data points. This study proposes a batch processing algorithm, called MOFA, to enable efficient processing of MkFN queries in spatial networks. MOFA aims to avoid dispensable distance computations based on the clustering of both query and data points. Moreover, a time complexity analysis is presented to clarify the effect of the clustering method on the query processing time. Extensive experiments using real-world roadmaps demonstrated the efficiency and scalability of the MOFA when compared with a conventional solution.