• 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.

• Korean journal of communication and information
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• v.34
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• pp.275-305
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• 2006

The main research question of this paper is as follows: How can broadcasting both cause the crisis in democratic participation and yet also offer the solution? The contradiction in broadcast localism has never been adequately resolved in spite of regulation at all in practice, in that localism simply cannot account for the diversity of modern life and for the external forces that incorporate local communities into much larger economic and communications network. The concept of locality in local television, however, has been multiplied and enlarged in order to adjust to "time-space compression". Recently the local television have been "interface" combining and negotiating the globalization of media market and the decentralization of political power, the economies of scale and the activation of local democracy, consequently aiming at the horizontal-cooperative network instead of old vertical-dependent one.

• Spatial Information Research
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• v.8 no.2
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• pp.213-232
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• 2000

It is important to scrutinize spatial patterns in crime analysis since crime data has geographical attribute in itself. We focus on the development of ¨Crime Analysis GIS¨ prototype which can discover spatial patterns in crime data by integrating mapping functions of GIS and spatial analysis techniques. The structure of this system involves integration of DBMS and GIS, and the major functions of the system include (i) exploring spatial distribution of point data, (ii) mapping hot-spot, (iii) clustering analysis of crime occurrence, and (iv) analyzing aggregated areal data. The process of design and implementation of this system is based on object-oriented methodologies. A web-based extension of the prototype using 3-tier architecture is currently under development.

• Journal of Korean Society of Environmental Engineers
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• v.33 no.7
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• pp.501-510
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• 2011

In this study, water pollution sources of 14 major tributaries of Han river and characteristics of water quality for each target streams were evaluated based on water quality data in 2007.1-2009.12 (14 data sets) using a statistical package, SPSS-17.0. Cluster analysis over time and space for each stream resulted in 4 groups for the spatial variations in which type and density of pollution sources in the basins showed the greatest impact on grouping. Moreover, cluster analysis for the time variation in which rainfall, temperature and eutrophication were shown to contribute to the clustering, produced 2 groups, from summer to fall (July-Oct.) and from winter to early summer (Nov.-June). Four factors were found as responsible for the data structure explaining 71-90% of the total variance of the data set depending on the streams and they were organic matter, nutrients, bacterial contamination. Factor analysis showed main factors (water pollutants) changed according to the season with different pattern for each stream. This study demonstrated that water quality of each stream could produce useful outcomes when factor and pollution source of basin were evaluated together.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.4
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• pp.139-144
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• 2011

This study proposed a classification method of LIDAR data by using simultaneously the color information (R, G, B) and reflection intensity information (I) obtained from terrestrial LIDAR and by analyzing the association between these data through the use of statistical classification methods. To this end, first, the factors that maximize variance were calculated using the variables, R, G, B, and I, whereby the factor matrix between the principal factor and each variable was calculated. However, although the factor matrix shows basic data by reducing them, it is difficult to know clearly which variables become highly associated by which factors; therefore, Varimax method from orthogonal rotation was used to obtain the factor matrix and then the factor scores were calculated. And, by using a non-hierarchical clustering method, K-mean method, a cluster analysis was performed on the factor scores obtained via K-mean method as factor analysis, and afterwards the classification accuracy of the terrestrial LiDAR data was evaluated.

• Annual Conference of KIPS
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• 2021.11a
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• pp.948-951
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• 2021

본 논문에서는 직육면체 형태의 실내 공간에서 다중 개체 영역을 검출하는 방법을 제안한다. 평면 검출 알고리즘은 평면성을 띄지 않거나 관측이 미흡한 영역에 대해 기하 정보를 검출할 수 없다. 이로 인해 장애물과 같은 개체의 영역을 파악할 수 없는 한계점이 있다. 제안 방법은 유클리드 클러스터링을 기반으로 군집화를 수행하고, 클러스터의 간소화를 통해 다중 개체 영역을 검출한다. 제안 방법은 직육면체 공간의 내부표면을 활용해 직육면체 공간과 좌표계를 공유하는 주요 개체들의 영역을 다량으로 검출한다. 제안 방법은 실험을 통해 다중 개체 영역이 적합하게 검출되었음을 보인다.

• Journal of the Economic Geographical Society of Korea
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• v.11 no.3
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• pp.442-458
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• 2008

This paper aims to examine the ways in which project-based organizations (PBOs) are embedded in social networks and geographical clustering in the case of TV drama industry. PBOs refer to a variety of temporary organizational forms for the performance of tasks as to integrate diverse and specialized intellectual resources. PEOs as a flexible and innovative mode of organizing knowledge resources are becoming increasingly worthy of attention in emerging the creative economy. Evidence from interviews with core persons of PEOs like producers, directors, and writers reveals that the key operational mechanism of the project form of organization is based on the highly socialized networks via individual's reputation and past experiences. In other words, the project activity in TV drama is embedded in networks which are socially constructed. Also the geographical clustering plays an important role in PBOs and project practices in TV drama are constructed around a high degree of spatial clustering. PBOs are clustering in Kang-nam and Yeouido, where are located in independent production companies and broadcasting stations. It means that the project formation in TV drama requires geographically-clustered networks of human resources, and socially, culturally and geographically embedded latent networks of interpersonal relationships are a necessary condition of POBs in the TV drama industry.

• Journal of Environmental Impact Assessment
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• v.27 no.5
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• pp.447-474
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• 2018

The purpose of this study is to build a new dataset of spatially interpolated climate data of South Korea by performing various geo-statistical interpolation techniques for comparison with the LDAPS grid data of KMA. Among 595 observation data in 2017, 80 % of the total points and remaining 117 points were used for spatial mapping and quantification,respectively. IDW, cokriging, and kriging were performed via the ArcGIS10.3.1 software and Python3.6.4, and each result was then divided into three clusters and four watersheds for statistical verification. As a result, cokriging produced the most suitable grid climate data for instantaneous temperature. For 1-hr accumulated precipitation, IDW was most suitable for expressing local rainfall effects.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.504-510
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• 2009

Recently, personalized-adaptive services became the center of interest in the world. However the services about music are not widely diffused out. That is because the analyzing of music information is more difficult than analyzing of text information. In this paper, we propose a music recommendation system which provides personalized services. The system keeps a user's listening list and analyzes it to select pieces of music similar to the user's preference. For analysis, the system extracts properties from the sound wave of music and the time when the user listens to music. Based on the properties, a piece of music is mapped into a point in the property space and the time is converted into the weight of the point. At this time, if we select and analyze the group which is selected by user frequently, we can understand user's taste. However, it is not easy to predict how many groups are formed. To solve this problem, we apply the K-means clustering algorithm to the weighted points. We modified the K-means algorithm so that the number of clusters is dynamically changed. This manner limits a diameter so that we can apply this algorithm effectively when we know the range of data. By this algorithm we can find the center of each group and recommend the similar music with the group. We also consider the time when music is released. When recommending, the system selects pieces of music which is close to and released contemporarily with the user's preference. We perform experiments with one hundred pieces of music. The result shows that our proposed algorithm is effective.

• Journal of the Korea Society of Computer and Information
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• v.29 no.10
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• pp.157-164
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• 2024

In this paper, we propose a technique that utilizes the physical properties of foam particles to synthesize foam sounds and efficiently control their size. A typical way to represent sound in physics-based simulation environments is to generate and synthesize virtual sounds. In particular, foam particles have a large number of particles, so synthesizing sounds using only particles is computationally expensive, and a way to reduce the amount of computation is to use spatial information, lattices. In this paper, we present a method for reliably mapping and clustering foam particles into a lattice space. Furthermore, we utilize this structure to control the loudness of the sound according to the location of the sound source and the audience. As a result, the method proposed in this paper proposes an efficient way to synthesize the sound of bubble particles, which utilizes the velocity and position of the bubble particles projected in the lattice space, and synthesizes the sound of bubble particles based on the position relationship of the audience and the directionality of the sound.