• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2006.07a
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• pp.664-664
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• 2006

• Journal of Digital Convergence
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• v.9 no.6
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• pp.71-80
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• 2011

Gyeongnam province is well known for its high concentration on machinery manufacturing industry. However, this province is losing competitive advantage due to the lack of IT S/W industry. In this paper, we propose a way for adoption of u-Manufacturing technology to promote IT S/W industry in Gyeongnam. At first, we identified the needs of manufacturing companies and the capabilities of the IT S/W companies with survey. Based on the survey analysis, then we set up the u-Manufacturing concept and proposed Manufacturing IT middleware to support it. Finally, we proposed a strategy to promote smoothly the adoption of u-Manufacturing technology in this area.

• IT SoC Magazine
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• s.18
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• pp.46-46
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• 2007

• Korean Journal of Food Science and Technology
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• v.39 no.6
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• pp.658-662
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• 2007

In this study, wild sesame leaf aromas (WSLA) were extracted and the extracted aromas were entrapped in porous potato starch micelles. The entrapped aromas did not evaporate, even by heated water treatments, and remained until a physical treatment such as chewing. Thus, the entrapped WSLA starch was used to make precooked instant noodles in order to mask or/and reduce an unpleasant raw flour flavor. The efficiencies of the flavor entrapment were analyzed using gas-chromatography equipped with solid phase micro-extraction (SPME), as well as by sensory evaluation. The highest yield of the porous potato starch was shown as 82.4% at an inlet temperature (IT) of $170^{\circ}C$, an exhaust temperature (ET) of $90^{\circ}C$, and a feeding rate (FR) of 40 mL/min. In the porous starch made by IT at $200^{\circ}C$, ET at $100^{\circ}C$, and FR at 50 mL/min, the entrapment efficiency was 68% by GC analysis; this starch also had the highest WSLA and consumer acceptability, but the lowest raw flour flavor, according to the sensory evaluation results.

• Journal of Digital Convergence
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• v.12 no.9
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• pp.359-367
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• 2014

This study aimed to identify empirically the differences of user interface experience factors for such manufacturers as Samsung, LG, Sky, Apple, etc., which are fiercely competing in the mobile market at home and abroad. In addition, this study aimed to verify how different the impact of such user interface experience factors on product attitudes and intention to repurchase would be for each manufacturer. As a result of the study, it was verified that there was a difference in the user experience between the manufacturers for all of the factors forming user satisfaction experience, which included information, interaction, useful experience and design experience satisfaction. Second, it was also verified that there was a difference between the manufacturers in terms of product attitudes. Lastly, it was verified that there was a difference between the manufacturers in terms of intention to repurchase. Specifically, it was found that Samsung had a higher degree of intention to repurchase than LG and Sky, whereas Apple had a higher degree hereof then Samsung. It is expected that the above results of study will provide the aforementioned manufacturers useful implications for establishing UI strategies through the contemplation of differences for each manufacturer in addition to the expansion of studies related to UI experience.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.158-161
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• 2023

스마트팩토리는 기존 제조산업과 ICT(Information & Communication Technology)가 융합된 지능형 공장이다. 이는 직접적인 제조공정 과정이 수행되는 OT(Operational Technology) 영역(0~3계층)과 전사업무 관리를 수행하는 IT(Information Technology) 영역(4~5계층)으로 구분되며, 각 영역과 계층이 연결되어 제조·물류·유통 과정의 자동화 및 지능화를 제공한다. 그러나 각 영역과 계층이 연결됨에 따라 보안위협 벡터가 증가하고 있으며, 다영역·다계층 환경인 스마트팩토리에 적합한 대응체계 연구를 위해 영역별 보안위협 관련 데이터를 통합하여 처리 및 관리하는 아키텍처 연구가 필요한 실정이다. 이에 따라 본 논문에서는 스마트팩토리 환경 내 IT 및 OT 영역 장치를 식별하고 보안위협 관련 데이터 통합 처리 및 관리를 위한 아키텍처를 제안한다.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.2
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• pp.41-56
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• 2019

Cloud manufacturing is a new concept of manufacturing process that works like a single factory with connected multiple factories. The cloud manufacturing system is a kind of large-scale CPS that produces products through the collaboration of distributed manufacturing facilities based on technologies such as cloud computing, IoT, and virtualization. It utilizes diverse and distributed facilities based on centralized information systems, which allows flexible composition user-centric and service-oriented large-scale systems. However, the cloud manufacturing system is composed of a large number of highly heterogeneous subsystems. It has difficulties in interconnection, data exchange, information processing, and system verification for system construction. In this paper, we derive the user requirements of various aspects of the cloud manufacturing system, such as functional, human, trustworthiness, timing, data and composition, based on the CPS Framework, which is the analysis methodology for CPS. Next, by analyzing the user requirements we define the system requirements including scalability, composability, interactivity, dependability, timing, interoperability and intelligence. We map the defined CPS system requirements to the requirements of oneM2M, which is the platform standard for IoT, so that the support of the system requirements at the level of the IoT platform is verified through Mobius, which is the implementation of oneM2M standard. Analyzing the verification result, finally, we propose a large-scale cloud manufacturing platform based on oneM2M that can meet the cloud manufacturing requirements to support the overall features of the Cloud Manufacturing CPS with dependability.

• Korean Journal of Materials Research
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• v.9 no.3
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• pp.307-314
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• 1999

The effect of manufacturing variables, such as reactant powder$(TiB_2, B_4C)$, sintering temperature, and sintering time has been investigated on the microstructure and the mechanical properties of in-situ processed Ti/TiB composites. The mechanical properties were evaluated by measuring the compressive yield strength. The compressive yield strength of the in-situ processed composites was higher than that of the Ti-6AI-4V. The compressive yield strength of the composite made with TiE, reactant powder was higher than that of $B_4C$, mixed at the same volume fraction of reinforcement. It is because bonding nature between the matrix and the $TiB_2$, reactant powder was more strong than that of the other materials. It was proven by the examining the crack propagation path.

• Electronics and Telecommunications Trends
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• v.36 no.1
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• pp.64-70
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• 2021

The future society will be changed through an artificial intelligence (AI) based intelligent revolution. To prepare for the future and strengthen industrial competitiveness, countries around the world are implementing various policies and strategies to utilize AI in the manufacturing industry, which is the basis of the national economy. Manufacturing AI technology should ensure accuracy and reliability in industry and should be explainable, unlike general-purpose AI that targets human intelligence. This paper presents the future shape of the "autonomous factory" through the convergence of manufacturing and AI. In addition, it examines technological issues and research status to realize the autonomous factory during the stages of recognition, planning, execution, and control of manufacturing work.

• Informatization Policy
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• v.25 no.3
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• pp.3-28
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• 2018

The purpose of this study is to analyze the research trends and present future research directions in the field of Cyber Physical System (CPS), a key element in the 4th Industrial Revolution, Industry 4.0, and Smart Manufacturing that are currently promoted as important innovation agenda both at home and abroad. In this study, (1) the concepts of industry 4.0, smart manufacturing and CPS are summarized; (2) analysis criteria of these fields are established; and 3) analysis results are presented and future research direction is proposed. 74 overseas and 8 domestic literature on manufacturing CPS from 2013 to 2017 are identified through 'Google Scholar Search'. Major results of the analysis are summarized as follows: (1) research on a common methodology and framework for the manufacturing CPS needs to be done based on the analysis of the existing methodologies and frameworks of various perspectives; (2) in order to improve the maturity of the manufacturing CPS, it is necessary to study actual deployment and operations of CPS, including the existing systems; (3) it is necessary to study the diagnostic methodology that can evaluate manufacturing CPS and suggest improvement strategy; and (4) as for the detailed model and tool, it is necessary to reinforce research on SCM production planning and human-machine collaboration while considering the characteristics of CPS.