• Journal of the Korean Home Economics Association
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• v.34 no.5
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• pp.13-28
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• 1996

The purpose of this study was to investigate the quality of life for the people living in Kyungsan areas and to suggest welfare policies for the improvement of their quality of life. The research was based on the quality of life model including 10 domains such as community environments, community services, housing , family, social network, education, health, employment and household labor, leisure, and economic security. The survey was carried out in Kyungsan city and its neighboring areas. Using 686 cases, the regional differences were examined with regard to the important variables from 10 domains. Based on the findings, policy implications were suggested to improve the quality of life for the people living in Kyungsan city and its neighboring areas.

• Proceedings of the KIEE Conference
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• 2004.11b
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• pp.258-260
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• 2004

This paper analyse a operating characteristics when the Community Energy System (CES) is operated islanding mode. In the near future, CES might be one of major energy supply structures. The basic concept of CES is that it supplies electrical and thermal energy to the local customer loads through the islanded power network separated from the grid. The CES must be supplying local load with stable energy on the islanding mode, analysing necessary to thoroughly the operation feature. In order to show them, in this paper, we model the CES with 2.34 MVA DG and simulate the operating feature on the islanding mode of CES. The simulation results show that, in order to stability operate, the CES need the efficient load management and generation control schemes during the transition periods.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.366-369
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• 2022

The glut of information aggravated the process of data analysis and other procedures including data mining. Many algorithms were devised in Big Data and Data Mining to solve such an intricate problem. In this paper, we conducted research about the comparison of several similarity measures and community detection algorithms in collaborative filtering for movie recommendation systems. Movielense data set was used to do an empirical experiment. We applied three different similarity measures: Cosine, Euclidean, and Pearson. Moreover, betweenness and eigenvector centrality were used to detect communities from the network. As a result, we elucidated which algorithm is more suitable than its counterpart in terms of recommendation accuracy.

• Therapeutic Science for Rehabilitation
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• v.12 no.4
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• pp.81-96
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• 2023

Objective : This study aimed to examine the association between the structural and functional aspects of social networks and health-promoting behaviors in community-dwelling older adults. Methods : Social networks based on structural and functional aspects and health-promoting behaviors by lifestyle were measured in 226 community-dwelling adults aged 65 years and over. To analyze the collected data, an independent t-test, one-way ANOVA, Pearson's correlation analysis, and hierarchical regression were performed. Results : The network size was the highest in the friend network, and the frequency of contact and social support was the highest in the non-living family network. Health-promoting behaviors were highest for activities of daily living and lowest for productive and social activities. All subfactors of social networks showed significant positive correlations with health-promoting behaviors. Hierarchical regression showed social support from neighbors as the variable with a significant effect on health-promoting behaviors; gender and depression were also influencing factors, and this model showed 37% explanatory power. Conclusion : To promote healthy behaviors of older adultsin the community, the development of health promotion programs and related policies considering social networks centering on social support from neighbors is required.

• Journal of Internet Computing and Services
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• v.10 no.3
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• pp.131-140
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• 2009

Recently, the information visualization research community has given significant attention to graph visualization, especially visualization of social networks. However, visualization of information flows in a very large social network has not been studied in depth. However, information flows are tightly related to the structure of social networks and it shows dynamic behavior of interactions between members of social networks. Thus, we can get much useful information about social networks from information flows. In this paper, we present our research result that enables users to navigate a very large social network in Google Maps' method and to take a look at information flows on the network. To this end, we devise three techniques; (i) mapping a very large social network to a 2-dimensional graph layout, (ii) exploring the graph to all directions with zooming it in/out, and (iii) building an efficient query processing framework. With these methods, we can visualize very large social networks and information flows in a limited display area with a limited computing resources.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.9B
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• pp.760-766
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• 2008

As a backbone network, wireless mesh network (WMN) aims to provide reliable high throughput network connectivity to wireless users. Recent research has focused on routing and channel allocation to increase the capacity of wireless mesh backbones. Wireless mesh networking is an attractive solution for home, community, and enterprise networks as it is a self-configuring, instantly deployable, and lowcost networking system. In this paper, we empirically evaluate and analyze charateristic of WMN to establish WMN testbed by measurement. We use laptops and net4826 Soekris board widely used. Soekris boards are equipped with one network interface card (NIC) or above in our measurements. We also use paket generator, routing demon tools and so on. Throughout this measurements, we show limitation of Soekris board and software we use, and suggest guideline to establish WMN.

• Korea Journal of Hospital Management
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• v.23 no.2
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• pp.28-41
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• 2018

Purpose: This study purposed to analyze the spatial accessibility of mental health institutions in Ganwon-Do using Geographic Information System and to suggest policy implications. Methodology: Network analysis was applied to assess the spatial accessibility of mental health institutions in Gangwon-Do. To perform the network analysis, network data set was built using administrative district map, road network, address of mental health institutions in Gangwon-Do. After building network data set, Two network analysis methods, 1) Service area analysis, 2) Origin Destination cost matrix were applied. Service area analysis calculated accessive areas that were within specified time. And using Origin Destination cost matrix, travel time and road travel distance were calculated between centroids of Eup, Myeon, Dong and the nearest mental health institutions. Result: After the service area analysis, it is estimated that 19.63% of the total areas in Gangwon-Do takes more than 60 minutes to get to clinic institutions. For hospital institutions, 23.08% of the total areas takes more than 60 minutes to get there. And 59.96% of Gangwon-do takes more than 30 minutes to get to general hospitals. The result of Origin-Destination cost matrix showed that most Eup Myeon Dong in Gangwon-Do was connected to the institutions in Wonju-si, Chuncheon-si, Gangneung-si. And it showed that there were large regional variation in time and distance to reach the institutions. Implication: Results showed that there were regional variations of spatial accessibility to the mental health institutions in Gangwon-Do. To solve this problem, Several policy interventions could be applied such as mental health resources allocation plan, telemedicine, providing more closely coordinated services between mental health institutions and community mental health centers to enhance the accessibility.

• Journal of the Korea Society of Computer and Information
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• v.20 no.4
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• pp.87-93
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• 2015

Recently, an idea has been suggested in which members construct the network by sharing their surplus bandwidth of their own access point. This kind of network is called public-shared network. As an application, SVC video streaming delivery system on public-shared network has been proposed. To send video stream from the stream server to clients, a tree structure is constructed where the root is a stream server, internal nodes are sharable access points, and leafs are clients. The previous researches have focused on constructing the minimal sharable-bandwidth tree which can serve all video streaming requests using the minimal sharable bandwidth. In this paper, we have shown that the problem of constructing a tree structure with given sharable access points to serve maximal video streaming requests is NP-hard. We also have developed an efficient heuristic algorithm for this problem and evaluated experimentally our algorithm.

• Journal of Intelligence and Information Systems
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• v.11 no.2
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• pp.17-29
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• 2005

The purpose of the study was to explore the potential of the Social Network Analysis as an analytical tool for scientific investigation of learner-learner, or learner-tutor interaction within a Computer Supported Corporative Learning (CSCL) environment. Theoretical and methodological implication of the Social Network Analysis had been discussed. Following theoretical analysis, an exploratory empirical study was conducted to test statistical correlation between traditional performance measures such as achievement and team contribution index, and the centrality measure, one of the many quantitative measures the Social Network Analysis provides. Results indicate the centrality measure was correlated with the higher order teaming performance and the peer-evaluated contribution indices. An interpretation of the results and their implication to instructional design theory and practices were provided along with some suggestions for future research.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.4
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• pp.23-32
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• 2021

For agricultural water management, it is essential to establish the digital infrastructure data such as agricultural watershed, irrigated area and canal network in rural areas. Approximately 70,000 irrigation facilities in agricultural watershed, including reservoirs, pumping and draining stations, weirs, and tube wells have been installed in South Korea to enable the efficient management of agricultural water. The total length of irrigation and drainage canal network, important components of agricultural water supply, is 184,000 km. Major problem faced by irrigation facilities management is that these facilities are spread over an irrigated area at a low density and are difficult to access. In addition, the management of irrigation facilities suffers from missing or errors of spatial information and acquisition of limited range of data through direct survey. Therefore, it is necessary to establish and redefine accurate identification of irrigated areas and canal network using up-to-date high resolution images. In this study, previous existing data such as RIMS (Rural Infrastructure Management System), smart farm map, and land cover map were used to redefine irrigated area and canal network based on appropriate image data using satellite imagery, aerial imagery, and drone imagery. The results of the building the digital infrastructure in rural areas are expected to be utilized for efficient water allocation and planning, such as identifying areas of water shortage and monitoring spatiotemporal distribution of water supply by irrigated areas and irrigation canal network.