• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.1062-1065
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• 2010

Plasma 물성 데이터는 Plasma내에서 일어나는 입자(전자, 원자, 이온, 분자 등)들의 충돌에 대한 데이터로써 Plasma 발생 장치 설계 및 제어의 핵심 요소이며, Plasma 공정조건 확립을 위한 필수 정보가 된다. 참조표준은 과학기술데이터나 정보에 대하여 정확도와 신뢰도에 대한 분석 및 평가가 이루어진 공인데이터를 말한다. 이러한 플라즈마 물성 정보를 체계적으로 관리하고 신뢰성 있는 데이터를 필요로 하는 산업체에 지원하기 위하여 특정 참조표준과 참조데이터로 제정, 보급하는 Plasma 물성 참조표준 수집평가 시스템이 필요하고, 이에 대한 설계가 필요하다.

• Journal of the Korea Convergence Society
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• v.6 no.5
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• pp.99-106
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• 2015

The purpose of this research is to bring supportive ways to reinforce the market competitiveness of fusion industry based on the rapidly arising fusion industries considering system improvement and fusion R&D support. The research has proceeded in the order of setup for competitiveness reinforcing way of fusion industry and deduction for competitiveness reinforcing way based on directivity. It classified the fusion industry into introduction, diffusion and development by time, and suggested expert fusion R&D, open type fusion R&D, customized fusion R&D, system improvement of market entrance and supportive way for public purchase as the supportive way. It's purpose is to lead the entrance into the new fusion market, stabilize to settle into the market and create high value products by resolving difficulties for the market entrance of the new fusion products & service, reinforcing the fusion capability and securing the competitive advantage.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.08a
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• pp.95-95
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• 2010

An apparatus for generating flames and more particularly the microwave plasma burner for generating high-temperature large-volume plasma flame was presented. The plasma burner was composed of micvrowave transmission lines, a field applicator, discharge tube, coal and gas supply systems, and a reactor. The plasma burner is operated by injecting coal powders into a 2.45 GHz microwave plasma torch and by mixing the resultant gaseous hydrogen and carbon compounds with plasma-forming gas. We in this work used air, oxygen, steam, and their mixtures as a discharge gas or oxidant gas. The microwave plasma torch can instantaneously vaporize and decompose the hydrogen and carbon containing fuels. It was observed that the flame volume of the burner was more than 50 times that of the torch plasma. The preliminary experiments were carried out by measuring the temperature profiles of flames along the radial and axial directions. We also investigated the characteristics for coal combustion and gasification by analyzing the byproducts from the exit of reactor. As expected, various byproducts such as hydrogen, carbon monoxide, carbon dioxide, hydrogen sulfide, etc. were detected. It is expected that such burner cab be applied to coal gasification, hydrocarbon reforming, industrial boiler of power plants, etc.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.3
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• pp.198-203
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• 2013

Industry convergence is the inexorable trend, which has become a fundamental concept to understand the industrial dynamics and to develop business strategies. However, most of the previous studies on convergence have dealt with the issues at the macro-level (technology- or industry-level), little attention has been paid to the analysis of convergence at the micro level (firm-level). Recognizing that firms are the principal agents that develop fusion technologies, it is encouraged to help firms to work together for technology convergence. Therefore, this research proposes a collaboration model for SMEs, since SMEs tend to have novel ideas and are flexible enough to make fusion-technology. To do this, we conducted a survey for Korean SMEs and analyzed their successful cases of collaboration, which was used as a basis to develop the model. The research results will help develop strategy or policy to promote the collaboration between SMEs and ultimately to make a fusion-technology.

• Journal of the Korean Ceramic Society
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• v.45 no.11
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• pp.739-743
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• 2008

Microfluidic device can be applied in a wide range of chemical and biological technology. In this paper, ceramic-based T-type passive mixers for microfluidic applications were fabricated by LTCC process combined with thick film photolithography. The base ceramic material in thick film was amorphous cordierite $((Mg,Ca)_2Al_4Si_5O_{18})$ and photoimageable polymers were added to give a photosensitivity. Two types of passive mixer, which showed the channel width of 1.0 mm and $200{\mu}m$, respectively, were designed considering mixing efficiency in the channel and their microfluidic properties were discussed in detail.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.11a
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• pp.464-464
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• 2007

환경오염으로 인한 각종 질병 및 증후군 등의 발생으로 가정용 산업용에서 환경관련 기술들이 다양한 분야로 확대되고 있다. 본 연구에서는 양이온 및 음이온 양쪽이온을 최대한 발생시키며, 오존 발생량은 억제하고 소비전력을 절감하고자 Ag-Pd 전극을 적용한 세라믹스 클러스터를 개발하였다. Ag-Pd 전극과 매칭되는 세라믹스 조성을 개발한 후 적층공정 기술을 이용하여 후막형 클러스터를 제조하였다. 전극 패턴모양, 전극간 방전간격 및 전극 보호층의 두께에 따른 음이온 발생량을 측정하여 최적화를 위한 실험을 진행하였으며, 음이온 발생량 100만개이상, 오존발생량 0.6ppb인 특성을 확인하였다.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.88-97
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• 2023

Traffic flow prediction is of great significance in urban planning and traffic management. As the complexity of urban traffic increases, existing prediction methods still face challenges, especially for the fusion of spatiotemporal information and the capture of long-term dependencies. This study aims to use the fusion model of graph neural network to solve the spatio-temporal information fusion problem in traffic flow prediction. We propose a new deep learning model Spatio-Temporal Information Fusion using Graph Neural Networks (STFGNN). We use GCN module, TCN module and LSTM module alternately to carry out spatiotemporal information fusion. GCN and multi-core TCN capture the temporal and spatial dependencies of traffic flow respectively, and LSTM connects multiple fusion modules to carry out spatiotemporal information fusion. In the experimental evaluation of real traffic flow data, STFGNN showed better performance than other models.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.496-498
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• 2023

Brain tumor segmentation problem has challenges in the tumor diversity of location, imbalance, and morphology. Attention mechanisms have recently been used widely to tackle medical segmentation problems efficiently by focusing on essential regions. In contrast, the fusion approaches enhance performance by merging mutual benefits from many models. In this study, we proposed a 3D dual fusion attention network to combine the advantages of fusion approaches and attention mechanisms by residual self-attention and local blocks. Compared to fusion approaches and related works, our proposed method has shown promising results on the BraTS 2018 dataset.

• Journal of Fisheries and Marine Sciences Education
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• v.27 no.6
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• pp.1880-1890
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• 2015

The purpose of this study was to development of the 'convergence motive' scale for interdisciplinary knowledge fusion. Based on results from literature review, this study clarifies a theoretical ground for 'convergence motive'. Initial items to measure this concept were verified by content analysis and then finalized. After a pilot test done with 568 college students, gathered data were analyzed by item selection and exploratory factor analysis to verify their validity. Next, the main test implemented with 1,211 college students was analyzed with exploratory factor analysis using the method for rotation based on maximum likelihood analysis and direct oblimin for validating the final items to measure 'convergence motive'. As a result, the scale for 'convergence motive' consists of 43 items to measure the following four factors: collaboration to identifying and solving problems, challenge of a new perspective, communication for convergence, cohesion for convergence. Construct validity and criterion-related validity were performed at last to check this scale's theoretical construct. In conclusion, this study concluded that the scales for convergence motive could be generalized and applicable to other samples.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.493-495
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• 2023

Deep learning methods and attention mechanisms have been incorporated to improve facial emotion recognition, which has recently attracted much attention. The fusion approaches have improved accuracy by combining various types of information. This research proposes a fusion network with self-attention and local attention mechanisms. It uses a multi-layer perceptron network. The network extracts distinguishing characteristics from facial images using pre-trained models on RAF-DB dataset. We outperform the other fusion methods on RAD-DB dataset with impressive results.