• 주류공업
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• v.17 no.4
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• pp.19-31
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• 1997

• 주류공업
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• v.17 no.4
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• pp.32-41
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• 1997

• Journal of Information Management
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• v.17 no.2
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• pp.28-48
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• 1984

• Plant Journal
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• v.7 no.4
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• pp.40-44
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• 2011

• Journal of Korea Fair Competition Federation
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• no.25
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• pp.73-75
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• 1997

공정거래위원회는 산업연구원(KIET)과 공동으로 지난 9월 3일(수) 대한상공회의소에서 300여명의 학계, 업계 및 관계부처 공무원들이 참석한 가운데$\lceil$카르텔 국제규범화의 영향 및 대응$\rfloor$이라는 주제로 $\lceil$제2회 국제경쟁정책 세미나$\rfloor$를 개최하였다. 동 세미나는 내년 4월에 확정될 카르텔관련 OECD 정책권고에서 각국의 경성카르텔(가격 고정, 생산량 제한, 시장분할 등) 금지원칙의 확립과, 적용제외 카르텔의 축소 및 제거 등을 통해 효과적인 경쟁법 집행체제를 확립하고, 회원국 양자 또는 다자협정을 통해 비밀정보를 공유하는 등 카르텔에서의 국제 협력의 강화, 특히 경성카르텔에 대한 국제적 공조조사 등의 법집행을 강화한다는 내용이 담길 것으로 예상됨에 따라, 경쟁정책 국제규범화(소위 경쟁라운드:CR)에 대한 정부와 기업의 적절한 대응방안 모색을 위한 방향을 제시하는 데 있다. 동 세미나에는 경쟁정책 분야의 세계적인 권위자인 하버드대 프레드릭 쉬어러(F.M. Scherer) 교수의 기조연설에 이어 테리 윈슬로(Terry Winslow) OECD 사무국 자문관과 KDI의 신광식 연구위원 등 4명의 국내외 전문가들의 주제발표와 지정 및 자유토론이 이루어졌다.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.11a
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• pp.641-644
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• 2006

Recently, fiber cementitious composite has been researched due to its good ductility. In this paper, Ductile Fiber Reinforcement Cementitious Coposite (DFRCC) is applied as reinforcement in concrete to prove its better performance. Compare to ordinary concrete, DFRCC has higher ductility which helps control the propagation of cracking without decreasing the elastic modulus and ultimate strength. In this research, experiments of different mixture ratios have been implemented to find a suitable mixture ratio value to produce high performance DFRCC material.

• Proceedings of the KIEE Conference
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• 1984.07a
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• pp.257-259
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• 1984

• 주류산업
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• v.23 no.4
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• pp.1-10
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• 2003

산업연구원은 2003년의 성장률이 3% 정도에 머물겠지만, 2004년에는 5.5% 내외로 높아질 것으로 전망하였다. 비단 산업연구원 뿐 아니라, 국내외 유수의 전망기관들이 한결같이 경기회복을 예상하는 전망치를 내놓고 있다.

• 주류산업
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• v.23 no.4
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• pp.33-40
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• 2003

2003년 11월 기준 우리나라의 수출은 1,744억달러, 수입은 1,611억 달러이며, 무역수지는 132억달러의 흑자를 기록하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4678-4702
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• 2018

Traffic Matrix estimation has always caught attention from researchers for better network management and future planning. With the advent of high traffic loads due to Cloud Computing platforms and Software Defined Networking based tunable routing and traffic management algorithms on the Internet, it is more necessary as ever to be able to predict current and future traffic volumes on the network. For large networks such origin-destination traffic prediction problem takes the form of a large under- constrained and under-determined system of equations with a dynamic measurement matrix. Previously, the researchers had relied on the assumption that the measurement (routing) matrix is stationary due to which the schemes are not suitable for modern software defined networks. In this work, we present our Compressed Sensing with Dynamic Model Estimation (CS-DME) architecture suitable for modern software defined networks. Our main contributions are: (1) we formulate an approach in which measurement matrix in the compressed sensing scheme can be accurately and dynamically estimated through a reformulation of the problem based on traffic demands. (2) We show that the problem formulation using a dynamic measurement matrix based on instantaneous traffic demands may be used instead of a stationary binary routing matrix which is more suitable to modern Software Defined Networks that are constantly evolving in terms of routing by inspection of its Eigen Spectrum using two real world datasets. (3) We also show that linking this compressed measurement matrix dynamically with the measured parameters can lead to acceptable estimation of Origin Destination (OD) Traffic flows with marginally poor results with other state-of-art schemes relying on fixed measurement matrices. (4) Furthermore, using this compressed reformulated problem, a new strategy for selection of vantage points for most efficient traffic matrix estimation is also presented through a secondary compression technique based on subset of link measurements. Experimental evaluation of proposed technique using real world datasets Abilene and GEANT shows that the technique is practical to be used in modern software defined networks. Further, the performance of the scheme is compared with recent state of the art techniques proposed in research literature.