• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.5
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• pp.2383-2389
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• 2011

Ubiquitous applications require hybrid continuous query processing which processes both on-line data stream and spatial data in the disk. In the hybrid continuous spatial query processing, disk access costs for the high-volume spatial data should be minimized. However, previous indexing methods cannot reduce the disk seek time, because it is difficult that the data are stored in contiguity with others. Also, existing methods for the space-filling curve considering data cluster have the problem which does not cluster available data for queries. Therefore, we propose the region storage structure for efficient data access in hybrid continues spatial query processing. This paper shows that there is an obvious improvement of query processing costs through the contiguous data storing method and the group processing for user queries based on the region storage structure.

• Publications of The Korean Astronomical Society
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• v.27 no.5
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• pp.399-409
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• 2012

As a part of the short-period variability survey (SPVS) at Bohyunsan Optical Astronomy Observatory, we obtained time-series BV CCD images in the region of Cyg OB3 association centered on the open cluster NGC 6871. The observations were performed for 18 nights from September 5, 2008 to September 1, 2009. We found 15 short-period variable stars in the region. They are ${\delta}$ Scuti type stars belonging to the local spiral arm, Orion spur. Among them, only two stars were previously known, and the rest are newly discovered ones. In this paper, we have performed a multiple-frequency analysis to determine frequencies of the 15 ${\delta}$ Scuti type stars, using the discrete Fourier transform and linear least-square fitting methods. One of the newly discovered variable stars is a double-mode ${\delta}$ Scuti type star with the fundamental and the first overtone modes, and two are high amplitude ${\delta}$ Scuti stars.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.1
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• pp.1-16
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• 2024

Alvin Toffler mentioned that it is important for future society to keep pace with synchronization and that time deviations can hinder social development. As we experience the new normal era of untact, we have experienced an increase in non-face-to-face contact and accelerated digital transformation. Amid these rapid changes, we can maintain the need for synchronization or change in space. Therefore, we would like to study what kind of settlements people create and choose. We looked at the metaverse as an object that could indirectly find out about this, and used the content called "Animal Crossing" to collect data related to the spatial form of the metaverse. Sampling utilized a judgment sampling method during non-probability sampling to alleviate differences due to the progress of the game. The collected data was classified according to floor plan and location type and briefly organized through descriptive statistics. After matching each facility by use, data was constructed by setting coordinates for each cluster and listing them. This data was interpreted graphically on the coordinate plane for each cluster, and Euclidean analysis was performed to analyze the relationships between clusters and residential choice using a Euclidean matrix. As a result of the analysis, it could be interpreted that efficiency was pursued by arranging similar functions in close proximity. Nevertheless, when choosing a residence, it was interpreted that the intention was to create a community through arrangement adjacent to residents rather than efficiency or convenience. Due to the differences between the metaverse and the real world, it is expected that there will be limitations in equating it with reality. However, through the space expressed in the virtual world by people who are far away from the constraints of reality, we can indirectly know the wishes that we have not been able to express due to our lack of awareness.

• Journal of the Korean Society for information Management
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• v.30 no.4
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• pp.31-59
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• 2013

The purpose of this study was to examine the intellectual structure of domestic LIS in the 1990s and 2000s using author bibliographic coupling analysis (ABCA). First, cluster analysis and multi-dimensional scaling analysis were performed to examine core subject areas and to map authors in two-dimensional space. Second, network analysis was used to visualize intellectual relationships among subject areas and to reveal the top subject areas for global centrality. Third, the 1990s and 2000s intellectual structures was compared to identify the changes of the intellectual structure over the course of time.

• The Research Journal of the Costume Culture
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• v.13 no.4 s.57
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• pp.564-575
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• 2005

The purposes of this study were to investigate the effects of shopping orientation on fashion shopping mall environments and purchase intention in internet fashion shopping mall. Data were obtained from 423 internet fashion shopping mall consumers who have experiences of buying products or visiting to internet fashion shopping mall in Busan, and were analyzed using by factor analysis, Cronbach's alpha, cluster analysis, ANOVA and Duncan test. The results showed shopping orientation perceived by Internet fashion shopping mall consumers were consisted five factors: Brand loyalty orientation, Economical orientation, Fashion orientation, Time saving orientation and Internet shopping orientation. Internet fashion shopping mall environments were composed of Visual information, Loading speed, Space composition, Product assortment, Checkout service, and Help desk. Consumers were classified by the shopping orientation into the Economical shopper, Fashion/brand shopper, and Convenience shopper. Economical shopper and Fashion/brand shopper rise in the estimation of Visual information, Product assortment, and Checkout service of shopping mall environment. Additionally, they were likely to have more intentions to purchase than the other types of shoppers in internet fashion shopping mall.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.5
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• pp.487-496
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• 2020

This study introduces how GISs (Geographic Information Systems) are used to assess spatial disparities in urban green spaces in the Chicago. Green spaces provide us with a variety of benefits, namely environmental, economic, and physical benefits. This study seeks to explore socioeconomic relationships between green spaces and their surrounding communities and to evaluate spatial disparities from a variety of perspectives, such as health-related, socioeconomic, and physical environment factors. To achieve this goal, this study used spatial statistics, such as optimized hotspot analysis, network analysis, and space-time cluster analysis, which enable conclusions to be drawn from the geographic data. In particular, 12 variables within the three factors are used to assess spatial disparities in the benefits of the use of green spaces. Finally, the variables are standardized to rank the community areas and identify where the most vulnerable community areas or parks are. To evaluate the benefits given to the community areas, this study used the z- and composite scores, which are compared in the three different combinations. After identifying the most vulnerable community area, crime data is used to spatially understand when and where crimes occur near the parks selected. This work contributes to the work of urban planners who need to spatially evaluate community areas in considering the benefits of the uses of green spaces.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.118-121
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• 1996

This paper describes ECG signal labeling based on Fuzzy clustering, which is necessary at automated ECG diagnosis. The NPPA(Non parametric partitioning algorithm) compares the correlations of wave forms, which tends to recognize the same wave forms as different when the wave forms have a little morphological variation. We propose to apply Fuzzy clustering to ECG QRS Complex labeling, which prevents the errors to mistake by using If-then comparision. The process is divided into two parts. The first part is a parameters extraction process from ECG signal, which is composed of filtering, QRS detection by mapping to a phase space by time delay coordinates and generation of characteristic vectors. The second is fuzzy clustering by FCM(Fuzzy c-means), which is composed of a clustering, an assessment of cluster validity and labeling.

• Journal of Information Processing Systems
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• v.14 no.1
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• pp.140-149
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• 2018

Social data such as users' comments are unstructured in nature and up-to-date technologies for analyzing such data are constrained by the available storage space and processing time when fast storing and processing is required. On the other hand, it is even difficult in using a huge amount of dynamically generated social data to analyze the user features in a high speed. To solve this problem, we design and implement a topic association analysis system based on the latent Dirichlet allocation (LDA) model. The LDA does not require the training process and thus can analyze the social users' hourly interests on different topics in an easy way. The proposed system is constructed based on the Spark framework that is located on top of Hadoop cluster. It is advantageous of high-speed processing owing to that minimized access to hard disk is required and all the intermediately generated data are processed in the main memory. In the performance evaluation, it requires about 5 hours to analyze the topics for about 1 TB test social data (SNS comments). Moreover, through analyzing the association among topics, we can track the hourly change of social users' interests on different topics.

• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.31.2-31.2
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• 2020

Mass segregation, a tendency of more massive galaxies being distributed closer to the cluster center, is naturally expected from dynamical friction, but its presence is still controversial. Using deep optical observations of 14 Abell clusters (KYDISC) and a set of hydrodynamic simulations (YZiCS), we find in some cases a hint of mass segregation inside the virial radius. Segregation is visible more clearly when the massive galaxy fraction is used instead of mean stellar mass. The trend is more significant in the simulations than in the observations. To find out the mechanisms working on mass segregation, we look into the evolution of individual clusters simulated. We find that the degree of mass segregation is different for different clusters: the trend is visible only for low-mass clusters. We compare the masses of galaxies and their dark haloes at the time of infall and at the present epoch to quantify the amount of tidal stripping. We then conclude that satellites that get accreted at earlier epochs, or galaxies in more massive clusters go through more tidal stripping. These effects in combination result in a correlation between the host halo mass and the degree of stellar mass segregation. This is a work submitted to The Astrophysical Journal (under review).

• 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.