• Journal of Korea Technology Innovation Society
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• v.20 no.4
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• pp.970-988
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• 2017

As an innovation cluster has become an important policy tool for attaining regional and national competitiveness, many nations and regions are making great efforts to foster innovation clusters. In the case of Korea also, many innovation clusters have been established and some of them are recently receiving a lot of attention due to their performance. In fact, there have been lots of investment by the central and regional governments. However, there have been no in-depth analyses on Korean successful innovation clusters. This study investigates some of the success factors of a Korean representative innovation cluster, Pangyo Techo Valley. We find out that the Pangyo Techno Valley has four groups of success factors: innovative environment, consistent policy support by regional government, knowledge networks, and good feed-back system of innovation. Our findings would have some theoretical and practical implications for innovation cluster research and policy practice.

• The Journal of the Korea Contents Association
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• v.10 no.9
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• pp.348-362
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• 2010

In the Knowledge-based economy, it is inevitable for companies to implement knowledge management(KM in short) to improve management performance. In order to better understand the KM, it is necessary to examine the relationship between success factors of KM and KM performance in agribusiness sector. This study empirically analyzes the impact of success factors of Knowledge Management on companies' management performance in agribusiness cluster. From the survey data of 43 companies located in Sunchang fermented soybean products Industrial cluster, the study finds that four factors- learning culture, network, knowledge sharing and knowledge creating- influence management performance in a positive way. It also examines whether Industrial cluster strategy functions as a moderator between KM success factors and companies' performance. Furthermore, this study concludes that Sunchang fermented soybean Industrial cluster has not reached to the final stage of KM and suggests elements for further improvements.

• Journal of the Economic Geographical Society of Korea
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• v.16 no.3
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• pp.492-511
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• 2013

According to IASB(International Accounting Standards Board), R&D(Research and Development) is defined as a tertiary sector industry combining research and development. Many studies investigated R&D industry clusters in the form of high-tech cluster(Coe et al., 2007). However, these studies only generalized various spatial cluster of R&D industries. In particular, the studies could not considers cluster formation process over time lacking statistical significance in space-time perspectives. This study, therefore, indicates the limitation of recent R&D cluster literature which only considers either time or space. In addition, this study explores space-time clusters in R&D industry together with textile and cloth industry for comparison. Discovering the existence and location of clusters, this study utilized space-time K function and space-time scan statistics. The result shows that R&D industry presents significant clusters only in spatial dimension. No significant clusters were found in space-time dimension. However, textile and clothing industry presents significant clusters in both spatial and space-time dimensions.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.557-565
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• 2021

This study was attempted to identify differences in self-esteem and grit in adolescents depending on the type of parenting attitude. Among the Korea Children Youth Panel Survey conducted by National Youth Policy Institute, the data of 2,438 first-year middle school students in 2018 year were analyzed. The collected data were analyzed using hierarchical cluster analysis and k-mean cluster analysis. As a result, the adolescent's perceived parenting attitude was classified into four types: 'passive affection acceptance', 'active affection acceptance', 'authoritarian inconsistency', and 'lack of affection rejection'. Also, there were significant differences in self-esteem and the degree of grit among the four clusters of parenting attitudes. Both self-esteem and grit were highest in the "active affection acceptance" group 2. In the future, differentiated parental education is needed for each cluster to improve self-esteem and grit of adolescents, and this study can be used as a basic data for the development of educational programs.

• The Journal of Bigdata
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• v.5 no.2
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• pp.135-143
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• 2020

This paper proposes a pre-processing method and a dimensional reduction method in the analysis of shopping carts where there are many correlations between variables when dividing the types of consumers in the agri-food consumer panel data. Cluster analysis is a widely used method for dividing observational objects into several clusters in multivariate data. However, cluster analysis through dimensional reduction may be more effective when several variables are related. In this paper, the food consumption data surveyed of 1,987 households was clustered using the K-means method, and 17 variables were re-selected to divide it into the clusters. Principal component analysis and factor analysis were compared as the solution for multicollinearity problems and as the way to reduce dimensions for clustering. In this study, both principal component analysis and factor analysis reduced the dataset into two dimensions. Although the principal component analysis divided the dataset into three clusters, it did not seem that the difference among the characteristics of the cluster appeared well. However, the characteristics of the clusters in the consumption pattern were well distinguished under the factor analysis method.

• Journal of Korea Technology Innovation Society
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• v.19 no.4
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• pp.848-872
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• 2016

This study is an empirical analysis that makes a survey on the evaluation of innovation cluster. For this purpose, we explore a case of innovation cluster, the Pangyo Techno Valley. This survey applies a research frame and evaluation contents that the innovation performance which is the institutional, physical, and social configurations of innovation clusters. In particular, this empirical analysis identifies the configuration factors which are the rational influence factors of individual subjects, in order to foster innovation clusters from the case study of the Pangyo Techno Valley. We can suggest that innovation policy from the results of innovation performance by applied configuration factors for evaluation of innovation cluster in order to enhance and facilitate for innovation cluster. Also, this study can provide lessons for regional policy implementation and new cluster policy agenda in Korea.

• Journal of Korea Multimedia Society
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• v.11 no.8
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• pp.1082-1092
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• 2008

In wireless sensor networks, clustering protocol such as LEACH is an efficient method to increase whole networks lifetime. However, this protocol result in high energy consumption at the cluster head node. Hence, this protocol must changes the cluster formation and cluster head node in each round to prolong the network lifetime. But this method also causes a high amount of energy consumption during the set-up process of cluster formation. In order to improve energy efficiency, in this paper, we propose a new cluster formation algorithm. In this algorithm, we define a intra cluster as the sensor nodes within close proximity of each other. In a intra cluster, a node senses and transmits data at a time on the round-robin basis. In a view of whole network, intra cluster is treated as one node. During the setup phase of a round, intra clusters are formed first and then they are re-clustered(network cluster) by choosing cluster-heads(intra clusters). In the intra cluster with a cluster-head, every member node plays the role of cluster-head on the round-robin basis. Hence, we can lengthen periodic round by a factor of intra cluster size. Also, in the steady-state phase, a node in each intra cluster senses and transmits data to its cluster-head of network cluster on the round-robin basis. As a result of analysis and comparison, our scheme reduces energy consumption of nodes, and improve the efficiency of communications in sensor networks compared with current clustering methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.389-392
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• 2007

In this paper, we propose an algorithm that improve network lifetime by adjusting cluster size according to location information of sensor node in wireless sensor network (WSN) using clustering technique. The sensed information in each cluster transfers to sink node through inter-cluster communications. Cluster head (CH) that nearby located in sink node much more spend own energy than far away CHs, because nearer CH forwards more data, so network lifetime is decreased. Proposed algorithm minimizes energy consumption in adjacent cluster to sink node by decreasing cluster site, and improve CH lifetime by distributing transmission paths. As a result of analysis, the proposed algorithm shows longer network lifetime in WSN.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.6
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• pp.1201-1206
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• 2007

In this paper, we propose an algorithm that improve network lifetime by adjusting cluster size according to location information of sensor node in wireless sensor network (WSN) using clustering algorithm. The collected sensing information by sensor nodes in each cluster are transferred to sink node using inter-cluster communications method. Cluster head (CH) that located nearby sink node spend much more energy than those of far from sink node, because nearer CH forwards more data, so network lifetime has a tendency to decrease. Proposed algorithm minimizes energy consumption in adjacent cluster to sink node by decreasing cluster size, and improve CH lifetime by distributing transmission paths. As a result of mathematical analysis, the proposed algorithm shows longer network lifetime in WSN.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.1
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• pp.19-30
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• 2021

This research studied the effect of visual improvement of "72 Hour Project" that has regenerated small scale derelict spaces in Seoul through citizen participation. 29 projects built form 2016 to 2019 were analyzed. The research analyzed landscape image preference of before and after status of projects using 12 pairs of landscape adjectives. Basic statistical analysis, correlation analysis, factor analysis, cluster analysis, and ANOVA were performed based on the survey results. Since the satisfaction level of the projects compared with the before-condition was 3.63 higher than 3.00, it could be concluded that there was an meaningful effect of visual improvement after completion of the projects. As the result of the factor analysis, landscape adjective pairs were categorized into two factors: harmony and aesthetics. Through the cluster analysis, four clusters were formed and characteristics of each cluster were identified. As the result of rhe cluster analysis, the cluster with the high harmony level and the aesthetics level showed the highest overall satisfaction level. Comparing each cluster, it could be concluded that the factor of harmony was more important than the factor of aesthetics in evaluating the satisfaction level of projects. Analyzing qualitative aspects of project groups, spatially well-balanced design with generous vegetation areas was more effective in landscape improvement than artistic design with visually strong installations. Further researches based on behavior studies of actual users are required to compensate the limits of this research. This research can contribute to establish the improved direction of policies to regenerate various types of small scale derelict spaces.