• Knowledge Management Research
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• v.14 no.2
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• pp.71-88
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• 2013

The aim of this study was to investigate why people voluntarily contribute knowledge to others, primarily strangers, in the electronic network of practice for job examination expected potential competing. This paper is organized as follows. First, we introduce the electronic network of practice which is the knowledge sharing community for job examination, and discuss the key issues for understanding knowledge sharing in these networks on the basis of individual motivations, relational capital, sense of community, and sense of rivalry to develop a research model for this study. To test the proposed research model, we adopted the survey method for data collection, and examined our hypotheses by applying the multiple regression analysis method to the collected data. Our unit of analysis was the individual. The findings of this study show that the intention of knowledge sharing is influenced by the reputation and the enjoy helping as the factors of individual motivations, by the reciprocity as the factor of relational capital, and by a sense of rivalry as a psychological factor. Lastly, contributions of this study and future research opportunities are also discussed.

• Journal of Microbiology and Biotechnology
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• v.33 no.6
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• pp.760-770
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• 2023

Continuous cropping obstacles have become a serious factor restricting sustainable development in modern agriculture, while companion planting is one of the most common and effective methods for solving this problem. Here, we monitored the effects of companion planting on soil fertility and the microbial community distribution pattern in pepper monoculture and companion plantings. Soil microbial communities were analyzed using high-throughput sequencing technology. Companion plants included garlic (T1), oat (T2), cabbage (T3), celery (T4), and white clover (T5). The results showed that compared with the monoculture system, companion planting significantly increased the activities of soil urease (except for T5) and sucrase, but decreased catalase activity. In addition, T2 significantly improved microbial diversity (Shannon index) while T1 resulted in a decrease of bacterial OTUs and an increase of fungal OTUs. Companion planting also significantly changed soil microbial community structures and compositions. Correlation analysis showed that soil enzyme activities were closely correlated with bacterial and fungal community structures. Moreover, the companion system weakened the complexity of microbial networks. These findings indicated that companion plants can provide nutrition to microbes and weaken the competition among them, which offers a theoretical basis and data for further research into methods for reducing continuous cropping obstacles in agriculture.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.115-115
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• 2020

Water network partitioning (WNP) is an initiative technique to divide the original water distribution network (WDN) into several sub-networks with only sparse connections between them called, District Metered Areas (DMAs). Operating and managing (O&M) WDN through DMAs is bringing many advantages, such as quantification and detection of water leakage, uniform pressure management, isolation from chemical contamination. The research of WNP recently has been highlighted by applying different methods for dividing a network into a specified number of DMAs. However, it is an open question on how to determine the optimal number of DMAs for a given network. In this study, we present a method to divide an original WDN into DMAs (called Clustering) based on community structure algorithm for auto-creation of suitable DMAs. To that aim, many hydraulic properties are taken into consideration to form the appropriate DMAs, in which each DMA is controlled as uniform as possible in terms of pressure, elevation, and water demand. In a second phase, called Sectorization, the flow meters and control valves are optimally placed to divide the DMAs, while minimizing the pressure reduction. To comprehensively evaluate the WNP performance and determine optimal number of DMAs for given WDN, we apply the framework of multiple-criteria decision analysis. The proposed method is demonstrated using a real-life benchmark network and obtained permissible results. The approach is a decision-support scheme for water utilities to make optimal decisions when designing the DMAs of their WDNs.

• Journal of Korean Society of Archives and Records Management
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• v.13 no.3
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• pp.127-150
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• 2013

Growing interest in everyday-life archives and community archives leads to the establishment of small-scale archives in the private sector. Interoperability of descriptive information is necessary to be able to have a link between these factors. The purpose of this study is to explore how descriptive information can be interoperable in private archives, which participate in the archives network, and to suggest a direction in organizing the private and community archives network. For this purpose, it investigated the current situation of archival description in small-scale private archives in Korea, especially in terms of collection, and analyzed descriptive information applied to four foreign archives networks. Based on the analysis, it gives some suggestions for sharing descriptive information in Private and Community Archive Network (PCAN) in Korea.

• Imaging Science in Dentistry
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• v.51 no.2
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• pp.187-193
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• 2021

Purpose: This study aimed to assess the usefulness of machine learning and automation techniques to match pairs of panoramic radiographs for personal identification. Materials and Methods: Two hundred panoramic radiographs from 100 patients (50 males and 50 females) were randomly selected from a private radiological service database. Initially, 14 linear and angular measurements of the radiographs were made by an expert. Eight ratio indices derived from the original measurements were applied to a statistical algorithm to match radiographs from the same patients, simulating a semi-automated personal identification process. Subsequently, measurements were automatically generated using a deep neural network for image recognition, simulating a fully automated personal identification process. Results: Approximately 85% of the radiographs were correctly matched by the automated personal identification process. In a limited number of cases, the image recognition algorithm identified 2 potential matches for the same individual. No statistically significant differences were found between measurements performed by the expert on panoramic radiographs from the same patients. Conclusion: Personal identification might be performed with the aid of image recognition algorithms and machine learning techniques. This approach will likely facilitate the complex task of personal identification by performing an initial screening of radiographs and matching ante-mortem and post-mortem images from the same individuals.

• Journal of agricultural medicine and community health
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• v.47 no.4
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• pp.268-274
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• 2022

Objectives: The purpose of this study was to identify the individual and regional risk factors on depression using community-based data in Jeollabuk-do. Methods: This cross-sectional study obtained data from the Community Health Survey 2018 in Jeollabuk-do. The dependent variable was depression measured by Patient Health Questionnaire-9 (PHQ-9). The prevalence of depression was defined if total score of PHQ-9 was 10 or higher. A multilevel analysis was conducted to consider individual and regional level independent variables that could be risk factors for depression. Results: In the individual level, female gender and smokers had significantly higher odds ratios (ORs) for depression of 1.58 and 1.72, respectively. Subjects with economic activity, higher income and higher education had significantly lower ORs of 0.53, 0.41 and 0.66. In the regional level, higher greening rates and lower levels of PM2.5 had statistically lower ORs at the significance level of 10%. Conclusion: By conducting this study, risk factors associated with depression were identified in individual- and regional-level. This study suggests that health projects are needed to control regional level risk factors including community networks for mental health management in addition to the traditional individual level risk factors.

• Journal of Microbiology and Biotechnology
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• v.33 no.8
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• pp.1013-1022
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• 2023

Arbuscular mycorrhizal fungi (AMF) are widespread soil endophytic fungi, forming mutualistic relationships with the vast majority of land plants. Biochar (BC) has been reported to improve soil fertility and promote plant growth. However, limited studies are available concerning the combined effects of AMF and BC on soil community structure and plant growth. In this work, a pot experiment was designed to investigate the effects of AMF and BC on the rhizosphere microbial community of Allium fistulosum L. Using Illumina high-throughput sequencing, we showed that inoculation of AMF and BC had a significant impact on soil microbial community composition, diversity, and versatility. Increases were observed in both plant growth (the plant height by 8.6%, shoot fresh weight by 12.1%) and root morphological traits (average diameter by 20.5%). The phylogenetic tree also showed differences in the fungal community composition in A. fistulosum. In addition, Linear discriminant analysis (LDA) effect size (LEfSe) analysis revealed that 16 biomarkers were detected in the control (CK) and AMF treatment, while only 3 were detected in the AMF + BC treatment. Molecular ecological network analysis showed that the AMF + BC treatment group had a more complex network of fungal communities, as evidenced by higher average connectivity. The functional composition spectrum showed significant differences in the functional distribution of soil microbial communities among different fungal genera. The structural equation model (SEM) confirmed that AMF could improve the microbial multifunctionality by regulating the rhizosphere fungal diversity and soil properties. Our findings provide new information on the effects of AMF and biochar on plants and soil microbial communities.

• International Journal of Contents
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• v.2 no.1
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• pp.1-4
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• 2006

E-business is not like e-commerce. E-business is more comprehensive than e-commerce. In the near future, it is expected that ebusiness prevails in the fields of wireless, peer-to-peer networks, streaming media and biometrics technologies. In this paper, we discuss the past and current of e-business, and then research topics of e-business, including new technology and the directions.

• Proceedings of the Korea Database Society Conference
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• 1998.09a
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• pp.101-114
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• 1998

Digital Library Definitions； A library that has been extended and enhanced by the application of digital technology. Contents and services accessible and deliverable via electronic networks to and from the worldwide libraries and commercial information resources. A large, organized collection of multimedia information for providing users of a community with coherent access to certain information services. A realistic means to build an Information Infrastructure for advanced Internet services of the future. more …(omitted)

• Korean Security Journal
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• no.19
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• pp.187-205
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• 2009

In this study, Horgan(2005)'s argument highlights the centrality to any successful counter-terrorism strategy of understanding the social context in which terrorist ideologies take root. Counter-terrorism refers to the practices, tactics, techniques, and strategies that governments, militaries, police departments and corporations adopt in response to terrorist threats and/or acts, both real and imputed. Pickering et al.(2008) historically explained four counter-terrorism strategies as traditional counter-terrorism model, community intelligence model, belonging model, social cohesion model. It is thus proposed that counter-terrorism strategies are based in established networks within the community and proactively seeks to continually renew these relationships between the community and police. This approach must embrace an explicit recognition of multiculturalism and its political imperative and drive in a policing organization explicitly committed to social cohesion and human rights in both discourse and practice. We, therefore, suggests community tree counter-terrorism approaches, or community intelligence model, belonging model and social cohesion model to apply to counter-terrorism agencies in Korea. These models are on the basis of Pickering et al.'s counter-terrorism models, which by using community policing to boot socially cohesion police are better able to position themselves as mediators to negotiate settlements between the competing demands of different social groups.