• Hwankyungkyoyuk
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• v.16 no.1
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• pp.34-47
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• 2003

The purpose of this study is to analyze the program development process of a nonformal environmental education(EE) program in detail. For the purpose, following research questions were answered in "the Nature School in the Forest" program in Eco-Club 1) What is the program development process? 2) What is the role of staffs, program developers, in the program development process? What are the meanings of their pedagogical approach? 3) With the findings of this study, how is the researcher able to develop ground theory for community-based nonformal EE, and to promote theoretical discussion for field improvement? The data were mainly gathered through participation observation and unstructured interview. And the data were analyzed by qualitative techniques such as clustering, factoring, noting pattern and themes, seeing plausibility, making metaphors, and building logical chain of evidence. The following conclusion comes out of the findings of this study. "The Nature School in the Forest" program is a educational device which the community-based NGO chose as a strategy to change individuals and community with its ideological purpose. And the program development process was the contiuous group decision-making process among staffs and volunteers. Consequently "the Nature School in the Forest" program is a circulated process of the voluntary activists training and their participation in program operation.

• KIISE Transactions on Computing Practices
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• v.21 no.1
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• pp.40-45
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• 2015

Online social networks(OSN) are very popular nowadays. As OSNs grows, the commercial markets are expanding their social commerce by applying Influence Maximization. However, in reality, there exist more than two players(e.g., commercial companies or service providers) in this same market sector. To address the Influence Maximization problem between adversaries, we first introduced Influence Maximization against the social adversaries' problem. Then, we proposed an algorithm that could efficiently solve the problem efficiently by utilizing social network properties such as Betweenness Centrality, Clustering Coefficient, Local Bridge and Ties and Triadic Closure. Moreover, our algorithm performed orders of magnitudes better than the existing Greedy hill climbing algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.569-574
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• 2011

In this paper, we introduce the subspace contrasting group identification problem and propose an algorithm to solve the problem. In order to identify contrasting groups, the algorithm first determines two groups of which attribute values are in one of the contrasting ranges specified by the analyst, and searches for the contrasting groups while increasing the dimension of subspaces with an association rule mining strategy. Because the dimension of microarray data is likely to be tens of thousands, it is burdensome to find all contrasting groups over all possible subspaces by query generation. It is very useful in the sense that the proposed method allows to find those contrasting groups without analyst's involvement.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.637-644
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• 2006

Biomedical image is often complex. An applied image analysis system should deal with the images which are of quite low quality and are challenging to segment. This paper presents a framework for color cell image segmentation by learning and classification online. It is a robust two-stage scheme using kernel method and watershed transform. In first stage, a two-class SVM is employed to discriminate the pixels of object from background; where the SVM is trained on the data which has been analyzed using the mean shift procedure. A real-time training strategy is also developed for SVM. In second stage, as the post-processing, local watershed transform is used to separate clustering cells. Comparison with the SSF (Scale space filter) and classical watershed-based algorithm (those are often employed for cell image segmentation) is given. Experimental results demonstrate that the new method is more accurate and robust than compared methods.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.4_2
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• pp.683-691
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• 2020

In the era of super-aged societies, research and development (R&D) projects related to aging are very important agenda for establishing the direction of future R&D planning and technological competitiveness in the country. In order to respond promptly to this agenda, it is essential to establish a national-level convergence R&D policy. In this study, we utilized the global R&D funding project data from major nations (US, Europe, Japan), and then standardized them with the same fields. To analyze the current status of global R&D related to aging, we performed cluster analysis based on the co-occurrence matrix to explore convergence R&D areas in the US, Europe, and Japan related to aging. In addition, comparative analysis by country suggested that different points on the interdisciplinary area and the convergence of aging-related R&D by each country. These results provide fundamental understandings for the status of convergence in aging-related global R&D, the current technology trends, and establish the direction and strategy of R&D policy.

• Journal of Contemporary Eastern Asia
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• v.18 no.1
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• pp.189-216
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• 2019

The frequent occurrence of overwhelming disasters necessitates risk communication systems capable of operating effectively in disaster contexts. Few studies have examined risk communication networks during disasters through social networking services (SNS). This study therefore investigates the patterns of risk communication by comparing Korean and international networks based on the social amplification of risk communication in the context of the Sewol ferry disaster (SFD). In addition, differences in language use and patterns between Korean and international contexts are identified through a semantic analysis using KrKwick, NodeXL, and UCINET. The SFD refers to the sinking of the ferry while carrying 476 people, mostly secondary school students. The results for interpersonal risk communication reveal that the structure of the Korean risk communication network differed from that of the international network. The Korean network was more fragmented, and its clustering was more sparsely knitted based on the impact and physical proximity of the disaster. Semantic networks imply that the physical distance from the disaster affected the content of risk communication, as well as the network pattern.

• The Journal of Information Systems
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• v.30 no.1
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• pp.21-44
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• 2021

Purpose The opportunities and approaches to big data have grown in various ways in the digital era. Business analytics is nowadays an inevitable strategy for organizations to earn a competitive advantage in order to survive in the challenged environments. The purpose of this study is to analyze the intellectual structure of business analytics literature to have a better insight for the organizations to the field. Design/methodology/approach This research analyzed with the data extracted from the database Web of Science. Total of 427 documents and 23,760 references are inserted into the analysis program CiteSpace. Author co-citation analysis is used to analyze the intellectual structure of the business analytics. We performed clustering analysis, burst detection and timeline analysis with the data. Findings We identified seven sub- areas of business analytics field. The top four sub-areas are "Big Data Analytics Infrastructure", "Performance Management System", "Interactive Exploration", and "Supply Chain Management". We also identified the top 5 references with the strongest citation bursts including Trkman et al.(2010) and Davenport(2006). Through timeline analysis we interpret the clusters that are expected to be the trend subjects in the future. Lastly, limitation and further research suggestion are discussed as concluding remarks.

• Journal of Animal Science and Technology
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• v.62 no.6
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• pp.790-800
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• 2020

The Yeonsan Ogye (YO) chicken is a natural heritage of Korea, characterized by black feathers, skin, bones, eyes, and comb. The purebred of YO population has been reared under the natural mating system with no systematic selection and breeding plan. The purpose of this study was to identify the genetic diversity and find the optimal number of population sub-division using 12 polymorphic microsatellite (MS) markers to construct a pedigree-based breeding plan for the YO population. A total of 509 YO birds were used for this study. Genetic diversity and population structure analysis were conducted based on the MS marker genotype information. The overall average polymorphic information content value and expected heterozygosity of the population were 0.586, and 0.642, respectively. The K-mean cluster analysis based on the genetic distance result confirmed that the current YO population can be divided into three ancestry groups. Individuals in each group were evaluated based on their genetic distance to identify the potential candidates for a future breeding plan. This study concludes that a future breeding plan with known pedigree information of selected founder animals, which holds high genetic diversity, could be the best strategy to ensure the conservation of the Korean YO chicken population.

• Journal of applied mathematics & informatics
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• v.41 no.4
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• pp.861-868
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• 2023

Nonlinear network creates complex homotopy structural communication in wireless network medium because of complex distribution approach. Due to this multicast topological connection structure, the queuing probability was non regular principles to create routing structures. To resolve this problem, we propose a Co-cluster homotopy queuing model (Co-CHQT) for Nonlinear Algebraic Topological Structure (NLTS-) for improving poison distribution network communication. Initially this collects the routing propagation based on Nonlinear Distance Theory (NLDT) to estimate the nearest neighbor network nodes undernon linear at x_(a,b)→ax²+bx² = c. Then Quillen Network Decomposition Theorem (QNDT) was applied to sustain the non-regular routing propagation to create cluster path. Each cluster be form with co variance structure based on Two unicast 2(n+1)-Z2(n+1)-Z network. Based on the poison distribution theory X_(a,b) ≠ µ(C), at number of distribution routing strategies weights are estimated based on node response rate. Deriving shorte;'l/st path from behavioral of the node response, Hilbert -Krylov subspace clustering estimates the Cluster Head (CH) to the routing head. This solves the approximation routing strategy from the nonlinear communication depending on Max- equivalence theory (Max-T). This proposed system improves communication to construction topological cluster based on optimized level to produce better performance in distance theory, throughput latency in non-variation delay tolerant.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.2
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• pp.86-96
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• 2006

Ecoclimap-1, a new complete surface parameter global database at a 1-km resolution, was previously presented. It is intended to be used to initialize the soil-vegetation- atmosphere transfer schemes in meteorological and climate models. Surface parameters in the Ecoclimap-1 database are provided in the form of a per-class value by an ecoclimatic base map from a simple merging of land cover and climate maps. The principal objective of this ecoclimatic map is to consider intra-class variability of life cycle that the usual land cover map cannot describe. Although the ecoclimatic map considering land cover and climate is used, the intra-class variability was still too high inside some classes. In this study, a new strategy is defined; the idea is to use the information contained in S10 NDVI SPOT/VEGETATION profiles to split a land cover into more homogeneous sub-classes. This utilizes an intra-class unsupervised sub-clustering methodology instead of simple merging. This study was performed to provide a new ecolimatic map over Northeast Asia in the framework of Ecoclimap-2 global database construction for surface parameters. We used the University of Maryland's 1km Global Land Cover Database (UMD) and a climate map to determine the initial number of clusters for intra-class sub-clustering. An unsupervised classification process using six years of NDVI profiles allows the discrimination of different behavior for each land cover class. We checked the spatial coherence of the classes and, if necessary, carried out an aggregation step of the clusters having a similar NDVI time series profile. From the mapping system, 29 ecosystems resulted for the study area. In terms of climate-related studies, this new ecosystem map may be useful as a base map to construct an Ecoclimap-2 database and to improve the surface climatology quality in the climate model.