• The Journal of the Convergence on Culture Technology
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• v.6 no.1
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• pp.99-104
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• 2020

This paper examines the performance according to the combination pattern of HRM and business strategy. The business strategy was divided into Miles & Snow's prospector, defender, and analyzer. Data were collected from the Korea Labor Institute's workplace panel survey from 2005 to 2015, and the analysis used 465 companies that are common respondents of the six wave surveys. To test the research model, structural equation modeling was employed. The results of the analysis showed that the combination of high commitment HRM and prospector had a positively significant effect on the performance. Contrariwise, the combination of high commitment HRM and defender, the combination of high commitment HRM and analyzer were not significant effect on performance.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2004.10a
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• pp.148-151
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• 2004

Different kinds of feedstock of semisolid a356 aluminum alloy manufactured by EMS stirring only, inoculation of Al-5Ti-B only and combination of inoculation and EMS stirring were investigated. It is found that the grain size of these feedstock are $350{\mu}m$ for EMS casting only, $320{\mu}m$ for inoculation by Al-5Ti-B, and $100{\mu}m$ for the combination of EMS stirring and inoculation of Al-5Ti-B master alloys. The microstructure of the sample obtain by combination of inoculation and EMS system show the best homogeneousness and finest grains.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2004.10a
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• pp.342-345
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• 2004

A combination of deep drawing and cold forging process is tried to achieve near net shaping of automatic transmission part which has drum shape and thickness variation. It is key for successful shaping of the part to find out proper condition to combine two different forming methods. Finite element analysis can be utilized for that purpose effectively. Integrity, reliability, and durability of the part are improved by eliminating machining process. The developed process is applied in real manufacturing process successfully.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.3
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• pp.141-147
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• 2005

In the field of electrical industry, embedded computing environment including hardware and software is getting more important as the industry shifts to the knowledge-based one. Java could play a great role as bridging technology in such a transition because it provides a lot of benefits like dynamic application download, compatibility of cross platform, and its own security solution. However, the Java technology has a limitation of real-time problem when it is applied to the embedded computing system of the electrical industry. To solve the problem, a novel java-native combination model has been proposed and designed to a firmware level. This scheme has been employed in four kinds of control boards. The result shows that the proposed model has great potential to implement the real-time processing in control of the devices.

• Journal of Industrial Technology
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• v.14
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• pp.101-107
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• 1994

This study is to investigate harbor oscillation phenomenon according to combination of the wall structures by model experiment in a three dimensional wave basin. Six different types of wall combination were chosen through combination of erect wall, erect dissipation block, and sand beach, wave height at selected points in the harbor were measured by electronic wave gage. Test results show that the wall structure composed solely of erect walls showed generally highest harbor oscillation. Since natural beach shows lower reflection than erect dissipation block do, we thought it would be more efficient to use natural beach for improved harbor oscillation. The result showed, however, that the erect dissipation block are more efficient than natural beach to attain less harbor oscillation. The reason seens that the erect dissipation blocks have better capability to control breaking wave on the surface of the structure.

• Journal of Information Technology Application
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• v.1 no.3_4
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• pp.69-90
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• 1999

본 논문은 시계열자료의 ARMA 모형화를 위해 계층적(Hierarchical) 문제해결 방식인 인공신경망 기초 의상결정트리분류기상의 인공신경망 구조를 개선하여 지역문제(Local Problem)를 해결하는 복수개의 인공신경망 결과를 Dempster's rule of combination을 이용하여 종합하는 병행적인 (Parallel) ARMA 모형활르 위한 방법론을 제시함으로써 의사결정트리분류기에 근거한 방법론의 단점을 보완하였다. 본 논문에서 제시한 ARMA 모형화를 위한 방법론은 세 단계로 구성되어 있다: 1) ESACF 특성 벡터 추출단계; 2) 개별 인공신경망에 의한 부분적 모델링 단계; 3) Conflict Resolution 단계, 제시한 방법론을 검증하기 위해 모의실험용 자료와 실제 시계열자료를 이용하여 제시된 방법론을 검증하였으며 실험결과 기존 연구에 비해 ARMA 모형화와 정확도가 높은 것으로 나타났다.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2012.11a
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• pp.583-603
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• 2012

• The Monthly Technology and Standards
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• s.14
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• pp.85-98
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• 2003

• Membrane and Water Treatment
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• v.9 no.4
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• pp.205-210
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• 2018

In this study, we investigated coagulants such as polyaluminum chloride (PACl) and ferric chloride ($FeCl_3$) and the combination of a coagulant and powdered activated carbon (PAC) for the removal of dissolved organic matter (DOM) from fish processing effluent to reduce membrane fouling in microfiltration. The efficiency of each pretreatment was investigated through analyses of dissolved organic carbon (DOC) and ultraviolet absorbance at 254 nm ($UVA_{254}$). Membrane flux and silt density index (SDI) analyses were performed to evaluate membrane fouling; molecular weight distributions (MWD) and fluorescence excitation-emission matrix (FEEM) spectroscopy were analyzed to assess DOM characteristics. The results demonstrated that $FeCl_3$ exhibited higher DOC and $UVA_{254}$ removals than PACl for food processing effluent and a combination of $FeCl_3$ and PAC provided comparatively better results than simple $FeCl_3$ coagulation for the removal of DOM from fish processing effluent. This study suggests that membrane fouling could be minimized by proper pretreatment of food processing effluent using a combination of coagulation ($FeCl_3$) and adsorption (PAC). Analyses of MWD and FEEM revealed that the combination of $FeCl_3$ and PAC was more efficient at removing hydrophobic and small-sized DOM.

• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.3944-3951
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• 2021

Several reasons such as no free lunch theorem indicate that there is not a universal Feature selection (FS) technique that outperforms other ones. Moreover, some approaches such as using synthetic dataset, in presence of large number of FS techniques, are very tedious and time consuming task. In this study to tackle the issue of dependency of estimation accuracy on the selected FS technique, a methodology based on the heterogeneous ensemble is proposed. The performance of the major learning algorithms of neural network (i.e. the FFNN-BR, the FFNN-LM) in combination with the diverse FS techniques (i.e. the NCA, the F-test, the Kendall's tau, the Pearson, the Spearman, and the Relief) and different combination techniques of the heterogeneous ensemble (i.e. the Min, the Median, the Arithmetic mean, and the Geometric mean) are considered. The target parameters/transients of Bushehr nuclear power plant (BNPP) are examined as the case study. The results show that the Min combination technique gives the more accurate estimation. Therefore, if the number of FS techniques is m and the number of learning algorithms is n, by the heterogeneous ensemble, the search space for acceptable estimation of the target parameters may be reduced from n × m to n × 1. The proposed methodology gives a simple and practical approach for more reliable and more accurate estimation of the target parameters compared to the methods such as the use of synthetic dataset or trial and error methods.