• Management & Information Systems Review
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• v.31 no.3
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• pp.223-248
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• 2012

This study analyses support policy and structural change of textile industry in Daegu Kyungbuk region, and suggests major issues for textile industry's innovation. In Daegu Kyungbuk, it was 1999 that a policy, so called Milano Project, in order to promote a textile industry was devised. In 2004, the Regional Industrial Promotion Plan was devised. The plan was born from a view point of establishing a regional innovation system and of promoting the innovative clusters under a knowledge based economy. After then, the Regional Industry Promotion Project or Regional Strategic Industry Promotion Project became a core of regional textile industrial policy. Research results indicated that the first stage Milano project (1999-2003) showed both positive and negative effects. There were no long-term development plan, clear vision and strategy. But, core industrial infrastructure for differentiated product development, such as New product Development Support Center and Dyeing Design Practical Application Center, was constructed. The second stage Daegu Textile Industry Promotion Plan (2004-2008) displayed a significant technological performance and new product sales with the assistance of Kyungbuk province. Also, textile industry revealed positive fruits such as financial structure, productivity, and profitability as a result of strong restructuring. In industrial structure, there was a important change from clothe textile material to industry textile material. Most of textile companies did not showed high capability in CEO's technology innovation intention, entrepreneurship, R&D and human resource competency in compare with other industry. We suggested that Daegu Kyungbuk has to select and concentrate on the high-tech textile material and living textile for sustainable development and competitiveness. We also proposed a confidence and cooperation based innovation network and company oriented innovation cluster.

• Journal of Korea Water Resources Association
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• v.53 no.2
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• pp.107-119
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• 2020

This study analyzed past drought characteristics based on the observed rainfall data and performed a long-term outlook for future extreme droughts using Representative Concentration Pathways 8.5 (RCP 8.5) climate change scenarios. Standardized Precipitation Index (SPI) used duration of 1, 3, 6, 9 and 12 months, a meteorological drought index, was applied for quantitative drought analysis. A single long-term time series was constructed by combining daily rainfall observation data and RCP scenario. The constructed data was used as SPI input factors for each different duration. For the analysis of meteorological drought observed relatively long-term since 1954 in Korea, 12 rainfall stations were selected and applied 10 general circulation models (GCM) at the same point. In order to analyze drought characteristics according to climate change, trend analysis and clustering were performed. For non-stationary frequency analysis using sampling technique, we adopted the technique DEMC that combines Bayesian-based differential evolution ("DE") and Markov chain Monte Carlo ("MCMC"). A non-stationary drought frequency analysis was used to derive Severity-Duration-Frequency (SDF) curves for the 12 locations. A quantitative outlook for future droughts was carried out by deriving SDF curves with long-term hydrologic data assuming non-stationarity, and by quantitatively identifying potential drought risks. As a result of performing cluster analysis to identify the spatial characteristics, it was analyzed that there is a high risk of drought in the future in Jeonju, Gwangju, Yeosun, Mokpo, and Chupyeongryeong except Jeju corresponding to Zone 1-2, 2, and 3-2. They could be efficiently utilized in future drought management policies.

• Korean Journal of Environmental Biology
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• v.32 no.4
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• pp.286-296
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• 2014

In this study, we investigated the macrobenthic community structure and spatiotemporal variations in Uljin Marine Ranching area, East Sea of Korea. Macrobenthos were collected using a modified van Veen grab sampler from April to September 2013. Total number of species sampled was 345 and mean density was 5,797 ind. $m^{-2}$, both of which were dominated by the polychaetes. The most dominant species were Spiophanes bombyx (53.64%), followed by Magelona sp.1 (6.96%), Cadella semitorta (2.73%), Lumbrineris longifolia (2.16%) and Alvenius ojianus (2.08%). Cluster analysis and nMDS ordination analysis based on the Bray-Curtis similarity identified 2 station groups. The group 1 (station 2, 3, 5, 6, 8 and 9) was characterized by high abundance of the polychaetes Magelona sp.1, Lumbrineris longifolia, Scoloplos armiger, Praxillella affinis, Maldane cristata and the bivalve Alvenius ojianus, with fine sediment above 30m water depth. On the other hand, the group 2 (station 1, 4, 7 and 10) was numerically dominated by the polychaete Lumbrineriopsis sp. and the bivalve Cadella semitorta, with coarse sediment below 5m water depth. Collectively, the macrobenthic community structure showed a distinct spatial trend, which seemed to be related to the water depth and sediment composition.