• Title/Summary/Keyword: Industrial Cluster

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Enhanced Production of Itaconic Acid through Development of Transformed Fungal Strains of Aspergillus terreus

  • Shin, Woo-Shik;Park, Boonyoung;Lee, Dohoon;Oh, Min-Kyu;Chun, Gie-Taek;Kim, Sangyong
    • Journal of Microbiology and Biotechnology
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    • v.27 no.2
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    • pp.306-315
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    • 2017
  • Metabolic engineering with a high-yielding mutant, A. terreus AN37, was performed to enhance the production of itaconic acid (IA). Reportedly, the gene cluster for IA biosynthesis is composed of four genes: reg (regulator), mtt (mitochondrial transporter), cad (cis-aconitate decarboxylase), and mfs (membrane transporter). By overexpressing each gene of the IA gene cluster in A. terreus AN37 transformed by the restriction enzyme-mediated integration method, several transformants showing high productivity of IA were successfully obtained. One of the AN37/cad transformants could produce a very high amount of IA (75 g/l) in shake-flask cultivations, showing an average of 5% higher IA titer compared with the high-yielding control strain. Notably, in the case of the mfs transformants, a maximal increase of 18.3% in IA production was observed relative to the control strain under the identical fermentation conditions. Meanwhile, the overexpression of reg and mtt genes showed no significant improvements in IA production. In summary, the overexpressed cis-aconitate decarboxylase (CAD) and putative membrane transporter (MFS) appeared to have positive influences on the enhanced IA productivity of the respective transformant. The maximal increases of 13.6~18.3% in IA productivity of the transformed strains should be noted, since the parallel mother strain used in this study is indeed a very high-performance mutant that has been obtained through intensive rational screening programs in our laboratory.

The Role of Gyeonggi Province in the Industrial Development of the Republic of Korea: A C ase Study of the Program of the National Innovative Cluster (한국의 산업발전과 경기도의 역할: 국가혁신클러스터 사업을 사례로)

  • Jung, Sung-Hoon
    • Journal of the Economic Geographical Society of Korea
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    • v.24 no.3
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    • pp.232-242
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    • 2021
  • The aim of this article is to examine the role of Gyeonggi Province in the industrial development in the Republic of Korea by taking a case study of the program of the national innovative cluster (NIC). In such program which has been for the purpose of the regional industrial development for non-Seoul metropolitan regions (N-SMRs) since 2018, the total firms' transactions were highly focused upon Gyeonggi Province and other Seoul metropolitan regions (SMRs). Especially, firms' transactions in 5 clusters of the total 14 clusters concentrated on Gyeonggi Province. Within this context, the future direction of this policy program for the regional industrial development and the national balanced development is more focused upon a win-win strategy between the SMR and N-SMRs rather than the dichotomy between them.

The Spatial Characteristics of Network in Zhongguancun Cluster - Focus on the Corporate Activities - (중관촌(中關村) 클러스터 네트워크의 공간적 특성 - 기업 활동을 중심으로 -)

  • Zhan, Jun
    • Journal of the Korean association of regional geographers
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    • v.18 no.3
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    • pp.298-309
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    • 2012
  • This paper studies the characteristics of the network of the Zhongguancun Cluster, the most representative innovative cluster of the high-tech industry in China at present. For this study, Zhongguancun Cluster was the first high-tech cluster created in China in 1988, the current Zhongguancun Cluster plays a leading role in the development of the high-tech industry in China. In addition, the Zhongguancun Cluster has attracted global attention and helped elevate China as a key region in terms of research development in relation to the high-tech industry. With regard to the spatial characteristics of the network belonging to the companies in Zhongguancun Cluster, purchase and producer services and information and R&D network have a strong tendency to be local, while on the other hand the product sales network has a strong tendency to be non-local. It is because the political support supplied by the government, institutional base that provides high-tech companies, producer services and information regarding producer services is relatively well prepared and managed in Zhongguancun Cluster. The spatial characteristics of the R&D network have a very strong local character is due to the location of the Zhongguancun Cluster where companies, universities and research centers with outstanding research development capacity as well as various support organizations for technology innovation within the cluster are included. On the other hand, because the high-tech products produced in this area are sold all across China as well as in foreign countries, the product sales network has a strong non-local character. Strengthening the local network in terms of the main agents of the cluster is the most important aspect in order to develop a certain industrial cluster into an innovative cluster. In this respect, if the Zhongguancun Cluster is seen from the perspective of a network, it has a basic network foundation. However, to strengthen international competitiveness, not only the local network but also the international network should be strengthened.

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Selecting Ordering Policy and Items Classification Based on Canonical Correlation and Cluster Analysis

  • Nagasawa, Keisuke;Irohara, Takashi;Matoba, Yosuke;Liu, Shuling
    • Industrial Engineering and Management Systems
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    • v.11 no.2
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    • pp.134-141
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    • 2012
  • It is difficult to find an appropriate ordering policy for a many types of items. One of the reasons for this difficulty is that each item has a different demand trend. We will classify items by shipment trend and then decide the ordering policy for each item category. In this study, we indicate that categorizing items from their statistical characteristics leads to an ordering policy suitable for that category. We analyze the ordering policy and shipment trend and propose a new method for selecting the ordering policy which is based on finding the strongest relation between the classification of the items and the ordering policy. In our numerical experiment, from actual shipment data of about 5,000 items over the past year, we calculated many statistics that represent the trend of each item. Next, we applied the canonical correlation analysis between the evaluations of ordering policies and the various statistics. Furthermore, we applied the cluster analysis on the statistics concerning the performance of ordering policies. Finally, we separate items into several categories and show that the appropriate ordering policies are different for each category.

Using cluster analysis and genetic algorithm to develop portfolio investment strategy based on investor information (군집분석과 유전자 알고리즘을 활용한 투자자 거래정보 기반 포트폴리오 투자전략)

  • Cheong, Donghyun;Oh, Kyong Joo
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.1
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    • pp.107-117
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    • 2014
  • The main purpose of this study is to propose a portfolio investment strategy based on investor types information. For improvement of investment performance, artificial intelligence techniques are used to construct a portfolio. Among many artificial intelligence techniques, cluster analysis is applied to select securities and genetic algorithm is applied to assign the respective weight within the portfolio. Empirical experiments in the Korean stock market show that proposed portfolio investment strategy is practicable and superior strategy. This result implies that analysis of investor's trading behavior may assist investors to make an investment decision and to get superior performance.

Differences in Learning Strategies for High School Students by Cluster Type of Hope (고등학생의 희망 군집유형별 학습전략의 차이)

  • Kim, Jin-Cheol;Jang, Bong Seok
    • Journal of Industrial Convergence
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    • v.18 no.3
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    • pp.1-6
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    • 2020
  • The purpose of this study is to theoretically understand hope theory suggested by Snyder and confirm its utility in the school settings. We analyzed the survey data responded by general high school students to find clustering types of hope and mean difference of learning strategies by each type through ANOVA. Results are as follows. First, hope by cluster analysis resulted in four types. Second, hope and learning strategy showed statistically positive correlation. Especially two sub-variables of hope and meta-cognition had highest correlation. Researchers suggested the direction of a future study to investigate structural relation among hope profile, student achievement, adjustment, and etc.

Clusters and Strategy in Regional Economic Development (지역경제개발에서 클러스터와 발전전략)

  • Feser, Edward
    • Journal of the Korean Academic Society of Industrial Cluster
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    • v.3 no.1
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    • pp.26-38
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    • 2009
  • Many economic development practitioners view cluster theory and analysis as constituting a general approach to strategy making in economic development, which may lead them to prioritize policy and planning interventions that cannot address the actual development challenges in their cities and regions. This paper discusses the distinction between strategy formation and strategic planning, where the latter is the programming of development strategies that are identified through a blend of experience, intuition, and analysis. Cluster theories and analytical tools can provide useful informational inputs into a strategy making effort and they can also be helpful for programming specific interventions (i.e., strategic planning). However, they should not be used as the exclusive or even predominant framework for filtering information about the competitive advantages of a region or for formulating strategy. To do so forces strategy making into a conceptual box defined by only one highly stylized theory of regional growth and development.

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Analysis and Improvement of User Manual Design of Agricultural Machines Made by Small Manufactures (중소기업에서 제작한 농기계 사용설명서의 특성분석과 개선방안)

  • Kim Jeong-Man;Lee Jin-Choon
    • Journal of Korea Society of Industrial Information Systems
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    • v.9 no.4
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    • pp.32-40
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    • 2004
  • This study tried to analyze the characteristic data, gathered by the semantic differential method, of respondents, user manuals and agricultural machines with the traditional statistical approach, i.e., cluster analysis and factor analysis semantic differential methods. Though the existing papers of the traditional sensory engineering only suggested the fragmentary result of analysis, this study tries to analyze the data with step-by-step approach, in which this study is analyzing the data with cluster analysis to get the characteristics of respondents, and then using the factor analysis to condensing the adjectives of describing the manual characteristics into several components. Concludingly, this study suggested a prototype of analyzing the semantic differential data with using cluster analysis and factor analysis.

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A Clustering Method Considering the Threshold of Energy Consumption Model in Wireless Sensor Networks (무선 센서 네트워크에서 에너지 소모 모델의 임계값을 고려한 클러스터링 기법)

  • Kim, Jin-Su
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.10
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    • pp.3950-3957
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    • 2010
  • Wireless sensor network is composed of sensor node with limited sources, and to maintain and repair is vexatious once made up. Accordingly it is important matter to maximize the network lifetime by minimizing the energy consumption in wireless sensor network, and utilizing the limited sources efficiently. In this paper, I propose a technique arranging the cluster number with efficiency in clustering method to optimize the energy consumption. The energy usage needed for wireless transmission varies in distance(threshold). This technique reduces the energy consumption considering the threshold when arranging the cluster number. I verify that the clustering method organized through the valid processes outperform the LEACH(Low-Energy Adaptive Clustering Hierarchy) in total energy consumption.

Sequential use of SOM, DEA and AHP method for the stepwise benchmarking of emerging technology (신흥 기술의 단계적 벤치마킹을 위한 SOM, DEA와 AHP 방법의 순차 활용)

  • Yu, Peng;Lee, Jang Hee
    • Knowledge Management Research
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    • v.13 no.5
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    • pp.43-64
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    • 2012
  • Emerging technologies have significant implications in establishing competitive advantages and are characterized by continuous rapid development. Efficient benchmarking is more and more important in the development of emerging technologies. Similar input level and importance are two necessary criteria need to be considered for emerging technology's benchmarking. In this study, we proposed a sequential use of self-organizing map(SOM), data envelopment analysis(DEA) and analytical hierarchy process(AHP) method for the stepwise benchmarking of emerging technology. The proposed method uses two-level SOM to cluster the emerging technologies with similar required input levels together, then, in each cluster, uses DEA-BCC model to evaluate the efficiencies of the emerging technologies and do tier analysis to form tiers. On each tier, AHP rating method is used to calculate each emerging technology's importance priority. The optimal benchmarking path of each cluster is established by connecting the emerging technologies with the highest importance priority. In order to validate the proposed method, we apply it to a case of biotechnology. The result shows the proposed method can overcome difficulties in benchmarking, select suitable benchmarking targets and make the benchmarking process more efficient and reasonable.

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