• Research in Community and Public Health Nursing
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• v.32 no.4
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• pp.497-505
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• 2021

Purpose: The study aimed to identify the effects of sleep hygiene (use of caffeine, alcohol, night eating syndrome, stress, and coping styles), social network, and smartphone-related factors on quality of sleep in young adults. Methods: This was a descriptive research design. Participants completed a questionnaire on evidence-based variables including caffeine intake, alcohol consumption, social network, night eating syndrome, stress, coping styles, and smartphone-related factors. Stepwise multiple regression was used for data analysis to identify factors that influenced the participants' quality of sleep. This study included 288 young adults in South Korea. Results: This study identified the factors affecting quality of sleep in young adults. Their average weekly sleep duration was 6.86 hours with low sleep quality, indicated by a score of 59.34 points (range 17-100). The predictors of sleep quality were sleep mood, sub-items of night eating syndrome, effects of pain over the last four weeks, and social networks, which explained 33% of the variance. Conclusion: Sleep-induced diseases in young adults could be prevented by identifying sleep mood, pain, and social networks, which is important for health and using them as a basis for intervention.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.1-11
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• 2023

In this paper, instead of using recurrent neural network, we compare a classification performance of time series imaging algorithms using convolution neural network. There are traditional algorithms that imaging time series data (e.g. GAF(Gramian Angular Field), MTF(Markov Transition Field), RP(Recurrence Plot)) in TSC(Time Series Classification) community. Furthermore, we compare STFT(Short Time Fourier Transform) algorithm that can acquire spectrogram that visualize feature of voice data. We experiment CNN's performance by adjusting hyper parameters of imaging algorithms. When evaluate with GunPoint dataset in UCR archive, STFT(Short-Time Fourier transform) has higher accuracy than other algorithms. GAF has 98~99% accuracy either, but there is a disadvantage that size of image is massive.

• Journal of the Korean association of regional geographers
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• v.22 no.3
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• pp.655-665
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• 2016

The meanings and roles of community have been changed. Traditional community theories hinged on the neighborhood have been threatened by the alternative concept of 'communities without propinquity'. Embracing unprecedented development of transportation, information and communication technologies, Propinquity of community has not been a precondition. This paper reviews the development of community theories with a frame of 'communities without propinquity'. Furthermore, applying social network analysis(SNA) approaches, it explores the communality of Topgol Comic Book Space, located in Goesan, Chungbuk and examines spatial characters. Visitors' networks of Topgol Comic Book Space builda up national coverage and expands. It functions as a field of testing various activities without explicit 'fixed purpose'. The case exemplifies a community, continuously enlarging the spatial and social boundaries, performing a series of activities, and connecting both the outside and the local.

• Journal of KIISE
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• v.45 no.2
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• pp.165-174
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• 2018

An online community is a virtual group whose members share their interests and hobbies anonymously with nicknames unlike Social Network Services. However, there are malicious user problems such as users who write offensive contents and there may exist data fragmentation problems in which the data of the same user exists in different nicknames. In addition, nicknames are frequently changed in the online community, so it is difficult to identify them. Therefore, in this paper, to remedy these problems we propose a behavior pattern feature vectors for users considering online community characteristics, propose a new implicit behavior pattern called relationship pattern, and identify the nickname of the same user based on Random Forest classifier. Also, Experimental results with the collected real world online community data demonstrate that the proposed behavior pattern and classifier can identify the same users at a meaningful level.

• Journal of Applied Biological Chemistry
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• v.59 no.4
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• pp.299-304
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• 2016

When used for amplicon sequencing, Illumina platforms produce more than hundreds of sequence artefacts, which affects operational taxonomic units based analyses such as differential abundance and network analyses. Nevertheless it has become a major tool for fecal microbial community analysis. In addition, results from sequence-based fecal microbial community analysis vary depending on conditions of samples (i.e., freshness, time of storage and quantity). We investigated if freeze-drying samples could improve quality of sequence data. Our results showed reduced number of possible artefacts while maintaining overall microbial community structure. Therefore, freeze-drying feces prior to DNA extraction is recommended for Illumina-based microbial community analysis.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.1
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• pp.105-113
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• 2017

Network externality can be defined as the effect that one user of a good or service has on the value of that product to other people. When a network externality is present, the value of a product or service is dependent on the number of others using it. There exist asymmetries in network externalities between the online and traditional offline marketing channels. Technological capabilities such as interactivity and real-time communications enable the creation of virtual communities. These user communities generate significant direct as well as indirect network externalities by creating added value through user ratings, reviews and feedback, which contributes to eliminate consumers' concern for buying products without the experience of 'touch and feel'. The offline channel offers much less scope for such community building, and consequently, almost no possibility for the creation of network externality. In this study, we analyze the effect of network externality on the competition between online and conventional offline marketing channels using game theory. To do this, we first set up a two-period game model to represent the competition between online and offline marketing channels under network externalities. Numerical analysis of the Nash equilibrium solutions of the game showed that the pricing strategies of online and offline channels heavily depend not only on the strength of network externality but on the relative efficiency of online channel. When the relative efficiency of online channel is high, the online channel can greatly benefit by the network externality. On the other hand, if the relative efficiency of online channel is low, the online channel may not benefit at all by the network externality.

• Journal of Navigation and Port Research
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• v.48 no.3
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• pp.181-191
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• 2024

Ports play a crucial role in the complex global supply chain. While many researchers have used social network analysis (SNA) to study active networks, there is a lack of SNA cohesion analysis specifically related to logistics and trade. Therefore, this study aims to identify time-series structural changes in all domestic import and export logistics networks, including regions, ports, and airports, by utilizing techniques such as k-core and community analysis. To carry out this analysis, we rely on data from the Korea Customs Service's Import and Export Logistics Statistical Yearbook spanning from 2004 to 2022. The findings from the k-core and community analysis indicate that the cohesion of the domestic import and export logistics network has continuously strengthened over time. Moreover, it reveals that regions, ports, and airports are becoming more cohesive and homogeneous, with Busan Port emerging as the central hub of a large community. These insights are expected to enhance our understanding of global logistics dynamics and contribute to the development of policies and sustainable import and export logistics processes.

• Journal of Internet Computing and Services
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• v.20 no.6
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• pp.73-84
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• 2019

Machine learning as a service, the so-called MLaaS, has recently attracted much attention in almost all industries and research groups. The main reason for this is that you do not need network servers, storage, or even data scientists, except for the data itself, to build a productive service model. However, machine learning is often very difficult for most developers, especially in traditional science due to the lack of well-structured big data for scientific data. For experiment or application researchers, the results of an experiment are rarely shared with other researchers, so creating big data in specific research areas is also a big challenge. In this paper, we introduce the KISTI-ML platform, a community-based rapid AI model development for scientific data. It is a place where machine learning beginners use their own data to automatically generate code by providing a user-friendly online development environment. Users can share datasets and their Jupyter interactive notebooks among authorized community members, including know-how such as data preprocessing to extract features, hidden network design, and other engineering techniques.

• Journal of Information Management
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• v.36 no.2
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• pp.125-151
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• 2005

The eight types of Korean bibliographic information of biology and life science are included in PubMed that serves universal medical bibliographic information. Other domestic bibliographic information are served on its own format at different organizations. To fulfill the CCBB homepage user's request that it is necessary that integration of bibliographic service for quick acquisition of research information, we intends to construct metadata registry and service about bibliographic information of biology and life science. This paper describes the design and implementation of bibliographic information network prototype for biology and life science that can be used to share latest research result, seminar presentation data, research note, and research paper etc as well as to exchange information between researchers through Open Archiving Community.

• Korean Journal of Social Welfare
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• v.38
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• pp.234-254
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• 1999

Volunteering has been defined as a form of altruistic helping behavior directed at improving other's welfare. Volunteering is, however, also identified as a type of collective action for community welfare. In this regard, this study tests whether neighborhood member's network and collective identity are more important determinants to explain participation in volunteer work than altruistic or normative motivation. This study estimates a model in which volunteering is determined by empathy, normative beliefs, neighborhood networks(friendship, contacts, and integration), and identity as a neighborhood member. This study shows that empathy, normative beliefs, and collective identity as a neighborhood member have significant impacts on participation in volunteer work. In addition, this study reveals that neighborhood member's network has an indirect impact on volunteering through identity as a neighborhood member. These results suggest that neighbor-hood community member's ties and collective identity are important sources for community welfare and collective volunteer work.