• Journal of the Korea Convergence Society
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• v.7 no.1
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• pp.189-196
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• 2016

The ultimate goal of this study is to investigate the cases with respect to smart factory that has been introduced by German government. To do this, the study suggest implications for manufacturing version 3.0 that is one of manufacturing revolution agendas in Korea. The main point of smart factory is the convergence between manufacturing and information and communications technologies such as CPS(Cyber-Physical Systems), MES(Manufacturing Execution Systems), 3D Printer, AI(Artificial Intelligence), and so forth. It is hard to accomplish a complete manufacturing automation. In fact, German government had experienced the failure in pursuing the smart factory agenda. But now the agenda is gradually realized by a variety of success stories from German. Thus, this study is to investigate the well-known success stories that came from German.

• Journal of Energy Engineering
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• v.12 no.4
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• pp.302-308
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• 2003

The peformence tests of zinc-based desulfurization sorbents using the yellow earth as support for the hot gas clean up were carried out. The zinc-based sorbent with 25 wt％ yellow earth was prepared, and their properties such as the reaction rate, the sulfur capacity and the attrition resistance, were investigated. The reactivity tests for hot gas desulfurization was performed at middle temperatures (sulfidation/regeneration：480$^{\circ}C$/580$^{\circ}C$). During multi-cyclic desulfurization, the deactivation of zinc-based sorbent was decreased by the addition of yellow earth, and their efficiency was enhanced. The ZnO/yellow earth sorbent had high reactivity, good regenerability, long-term durability (about 19 gS/100 g sorbent for 10-cycles) and high attrition resistance (AI=19.1％). It was concluded that the peroperties of zinc-based sorbent were improved by metal oxides (Fe$_2$O$_3$, Na$_2$O, MnO$_2$, etc) in the yellow earth. From these results, it was confirmed that the desulfurization properties of zinc-based sorbents at middle temperatures could be improved by the yellow earth using as support.

• The Journal of the Korea Contents Association
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• v.20 no.5
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• pp.153-170
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• 2020

With the recent development of AI and ICT, autonomous vehicles are becoming a reality, and sales of the vehicles equipped with partial autonomous driving technology are also rapidly expanding. In this situation, technology research on autonomous vehicles has been actively conducted, but research on exploring the perception of autonomous vehicles from the user's perspective is relatively insufficient. Therefore, this study categorizes autonomous vehicle users into four types - , , , and . Then, it examines the characteristics of each type. For this purpose, we applied Q-methodology, a qualitative research method, to observe self-referent subjectivity of 32 P-samples using a Q-sample which consists of 34 statements. The results of our study have significance in that they provide domestic and global automakers with strategic directions for technological development and market expansion of autonomous vehicles, and academically provide hypotheses for subsequent quantitative research.

• Journal of the Korean Ceramic Society
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• v.35 no.7
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• pp.685-690
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• 1998

The wetting behavior and the characteristic of spontaneous infiltration of pure Al and Al-(Si)-Mg alloys on {{{{ { {Al }_{ 2} O}_{3 } }} in vacuum argon and nitrogen atmosphere were investigated to find out the spontaneous in-filtration mechanism. The wetting of molten Al and Al alloys on {{{{ { {Al }_{ 2} O}_{3 } }} was only possible in cacuum at-mosphere but the sponataneous infiltration of molten Al-(Si)-Mg alloys was successfully made on {{{{ { {Al }_{ 2} O}_{3 } }} pre-form in nitrogen atmoshpere. The difference of wettability and spontaneous infiltration of molten Al and Al alloys on {{{{ { {Al }_{ 2} O}_{3 } }} were found to be related to formation of the Mg-N compound coated layer on {{{{ { {Al }_{ 2} O}_{3 } }} particles which was believd to increase wettability of molten Al alloys on {{{{ { {Al }_{ 2} O}_{3 }.

• Korean Journal of Materials Research
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• v.7 no.1
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• pp.50-56
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• 1997

급냉응고법을 이용하여 고용한도 이상으로 Mn량을 첨가할 때 Mn량에 따른 인장특성의 변화와 시효특성을 조사하였다. 원심분무법으로 AI-4.7%Zn-2.5%Mg-0.2%Zr합금에 Mn량을 각기 달리 첨가한 급냉응고 분말을 제조 하였다. 이 분말을 냉간압축, 진공 탈가스처리를 한 후 15:1로 압출하여 봉상 시편을 만들었다. 분말의 미세조직은 $\alpha$-AI수지상과 수지상간 편석부로 이루어져 있으며 Mn첨가에 따라 조직의 변화는 관찰되지 않았다. 빠른 냉각속도로 인하여 2.0%Mn을 첨가한 경우에도 초정 Mn상을 발견할 수 없었다. 압출재의 미세조직은 아결정립으로 이루어져 있으며 약간의 제2상들이 관찰되었다. 대부분의 Mn 분산상은 압출후 용체화처리 과정에서 형성되었으며 시효경화량은 Mn양에 관계없이 일정하였다. 46$0^{\circ}C$에서 1시간 용체화처리하고 12$0^{\circ}C$에서 24시간 시효처리한 경우 최대의 시효경도값을 나타내었다. 인장강도는 Mn첨가량에 따라 증가 하였는데 이것은 Mn분산상의 밀도증가에 의한 것으로 확인되었다. 2.0%Mn을 첨가한 합금의 시효후 인장강도는 590MPa, 연산율은 4%를 보였다.

• Convergence Security Journal
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• v.17 no.2
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• pp.153-158
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• 2017

The robot imitates humans and recognizes the external environment and judges the situation. The robot is a machine that operates autonomously. Robots are divided into manufacturing robots and service robots. Service robots are classified as professional service robots and personal service robots. Because of the intensified competition of productivity in manufacturing industries, rising safety issues, low birth rate and aging, the robots industry is emerging. Recently, the robot industry is a complex of advanced technology fields, and it is attracting attention as a new industry where innovation potential and growth potential are promising. IT, BT, and NT related elements are fused and implemented, and the ripple effect is very large. Due to changes in social structure and life patterns, social interest in life extension and health is increasing. There is much interest in the medical field. Now the artificial intelligence (AI) industry is growing rapidly. It is necessary to secure global competitiveness through strengthening cooperation between large and small companies. We must combine R&D investment capability and marketing capability, which are advantages of large corporations, and robotic technology. We need to establish a cooperative model and secure global competitiveness through M&A.

• Congress of the korean instutite of fire investigation
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• 2011.04a
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• pp.102-116
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• 2011

With the spread of FMD and AI in the country livestock farmers have used lime(CaO) prevalently and due to incorrect storage lime served as a fire ignition source in a number of cases. As combined chemically with water, lime has exothermic reaction. Then In these experiments we want to know how exothermic reaction - caused by lime - acts as sources of fire ignition in any circumstances and conditions. So we have done experimental work of ignition temperature and ignition process in the artificial conditions as lime combined chemically with water. As a result, we have confirmed that lime could be flammable material sufficiently as a fire ignition source with the proper presence of heat and moisture conditions. If the lime served as sources of fire ignition, as identification techniques of fire scene, we must ascertain the existence of water, flammable material and Calcium Hydroxide($Ca(OH)_2$). We should take special precautions in order to prevent fire and educate the safe handling of lime to the manufacturer and agricultural cooperative's joint livestock farmers who product or use lime.

• The Korean Journal of Food And Nutrition
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• v.24 no.1
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• pp.132-137
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• 2011

The objective of this study was to develop mixed seasoning products with Korean chili peppers(Capsicum annuum L.) and examine their characteristics based on a sensory evaluation. One-hundred chili pepper-related products were collected from American local favorites and analyzed for composition. Four different seasonings were prepared for the value-added seasoning products, and their sensory characteristics were measured. The Korean fish chili seasoning product showed higher overall acceptability, compared to local American seasoning(McCormick). The completed Korean chili seasoning products contained red pepper(20%), various herbs(31.7%), salt(11.5%), mushroom(8.6%), garlic(8.5%), curry, paprika(5.7%), and citron(2.8%). These results suggest the possibility of substituting mixed seasonings from foreign countries into Korean dishes.

• Food Science and Industry
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• v.54 no.3
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• pp.124-131
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• 2021

In the 4th industrial revolution, Artificial Intelligence (AI), big data, Internet of Things (IoT) are already around us, making our society hyper-connected and blurring the lines between the digital and biological spheres. We witness drastic changes not only in the food industry, but also in economy, society and our life as a whole. Technologies bring industrial reorganization and greater changes at the system level and the food industry is not exceptional. Human demand for foods continues to grow and the very nature of the food industry remains unchanged, but its production, distribution and marketing face unprecedent innovations. Passing through the global pandemic, the food industry has been evolved into 'contact-free', as the safety become our top priority. Amid the gradual shift to technology-oriented society, the smarter food safety management skills and tools are being adopted in many countries exerting greater efforts to enhance traceability and to upgrade AI-powered safety management system.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.2
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• pp.57-64
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• 2021

This study presents a method for realtime fuel consumption prediction using real data collected from OBDII. With the advent of the era of self-driving cars, electronic control units(ECU) are getting more complex, and various studies are being attempted to extract and analyze more accurate data from vehicles. But since ECU is getting more complex, it is getting harder to get the data from ECU. To solve this problem, the firmware was developed for acquiring accurate vehicle data in this study, which extracted 53,580 actual driving data sets from vehicles from January to February 2019. Using these data, the ensemble stacking technique was used to increase the accuracy of the realtime fuel consumption prediction model. In this study, Ridge, Lasso, XGBoost, and LightGBM were used as base models, and Ridge was used for meta model, and the predicted performance was MAE 0.011, RMSE 0.017.