• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.588-591
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• 2021

4차 산업혁명 시대가 도래하면서 세상이 빠른 속도로 변하고 있다. 특히 데이터·인공지능(AI, Artificial Intelligence)의 활용이 적극적으로 다양한 분야에서 적용되기 시작하고 있다. 하지만 산림수종을 분석하는 업무를 수행하는 과정은 수작업으로 진행하다 보니 오류가 다수 발생하고 있다. 따라서 본 논문에서는 수도권 항공사진을 이용하여 소나무, 낙엽송, 침엽수, 활엽수를 대상으로 자동으로 분석하는 AI 학습용 데이터 약 60,000장을 구축하고, 수종을 구분할 수 있는 AI 모델을 개발하였다. 이를 통해 산림변화탐지 및 산림 분야 주제도 제작 시 수종 분할 이미지를 기초자료로 활용함으로써 업무효율 증대를 기대할 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.1053-1054
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• 2023

본 연구는 이기종 기체 센서를 활용하여 식품의 부패 및 발효 정도를 측정하기 위한 AI 기반 식품 품질 관리용 전자코에 관한 내용이다. 정확한 부패 및 발효 정도 측정을 위해 신호 처리 및 분석 기술을 활용하며, 로지스틱 분석 및 회귀 분석을 통해 결과를 도출하고자 한다. 이는 인간의 후각으로 정확하게 맡기 힘든 냄새를 측정함으로써 식중독 사고의 방지 및 식품의 생산/보관/운송을 효율적으로 관리할 수 있다. 또한, 본 연구 결과를 바탕으로 환경, 농업, 의료 등 다양한 분야에서의 적용 가능성을 기대할 수 있다.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1996.10a
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• pp.113-121
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• 1996

AI7075 alloy has been used for aircraft components since it has the advantage of high strength, high toughness, and high corrosion resistance. Many airframe components consist of various combinations of rib-web structure. In this study, various process paramenters such as die design, lubricant, ram speed, forging temperature have been investigated using the experiment and F.E.M. simulation to develop the precision forging technology for AI7075. When lubricant is applied to both material and die, shear friction factor is 0.1 which shows best effect of lubricant. It is specific corner radius of die that minimized forging load regarding process conditions, especially according to the ratio of the width of rib and web. In conclusion, optimum corner radius is 2~3mm when the width of rib and web is 3mm and 20mm respectively.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.821-823
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• 2022

공기질에 대한 인식이 제고됨에 따라 실내공기질 규제가 강화되고 있다. 따라서 기존 고정형 공기청정기를 대체할 효율적인 기술로 자율주행 공기청정기를 연구하였다. 또한 자율주행 공기청정기에 AI 를 적용하여 오염도를 예측하는 방법으로 기존 자율주행 공기청정기와 차별성을 둔다.

• Journal of Korea Foundry Society
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• v.24 no.6
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• pp.314-322
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• 2004

The CaO crucible is expected to serve as a useful tool for melting Ti and its alloys due to its thermodynamic stability. However, tjere still remain problems that need to be resolved in the melting of Ti and its alloys to enable commerical use. The cause of the defects of Ti-6AI-4V alloy castings melted in the CaO crucible were examined and compared with induction skull melting. The key factors of the melting technique using the CaO crucible, affecting the quality of Ti-6AI-4V alloy castings, were investigated. Defects of the Ti-6AI-4V alloy castings are caused by the chemical reduction of CaO by Ti. Pressurizing with argon gas in a vacuum induction chamber is effective for reducing the defects. Preheating of the charged material in the crucible and quick pouring into a mold of lower temperature, just after melting down, are important for produsing sound Ti-6AI-4V castings.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.240-243
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• 2021

Recently, there have been research results of applying Big data and AI technologies to the evaluation and individual learning for education. It is information technology innovations that collect dynamic and complex data, including student personal records, physiological data, learning logs and activities, learning outcomes and outcomes from social media, MOOCs, intelligent tutoring systems, LMSs, sensors, and mobile devices. In addition, e-learning was generated a large amount of learning data in the COVID-19 environment. It is expected that learning analysis and AI technology will be applied to extract meaningful patterns and discover knowledge from this data. On the learner's perspective, it is necessary to identify student learning and emotional behavior patterns and profiles, improve evaluation and evaluation methods, predict individual student learning outcomes or dropout, and research on adaptive systems for personalized support. This study aims to contribute to research in the field of education by researching and classifying machine learning technologies used in anomaly detection and recommendation systems for educational data.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.193-198
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• 2021

Recently, interests in the 4th industry have increased the level of demand for pest control by farmers in the field of rice farming, and the interests and use of agricultural pest control drones. Therefore, the diversification of agricultural control drones that spray high-concentration pesticides and the increase of agricultural exterminators due to the acquisition of national drone certifications are rapidly developing the agricultural sector in the drone industry. In addition, as detailed projects, an effective platform is required to construct large-scale big data due to pesticide management, exterminator management, precise spraying, pest control work volume classification, settlement, soil management, prediction and monitoring of damages by pests, etc. and to process the data. However, studies in South Korea and other countries on development of models and programs to integrate and process the big data such as data analysis algorithms, image analysis algorithms, growth management algorithms, AI algorithms, etc. are insufficient. This paper proposed an online drone pest control management information platform to meet the needs of managers and farmers in the agricultural field and to realize precise AI pest control based on the agricultural drone pest control processor using drones and presented foundation for development of a comprehensive management system through empirical experiments.

• Korean Journal of Materials Research
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• v.7 no.10
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• pp.877-883
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• 1997

Ar 및 Ar과 $N_{2}$ 분위기하에서 rf 마그네트론 스퍼터링방법으로 Ta-AI과 Ta-AI-N합금막을 제조하였다. Ta-7.9at.% AI계열, Ta-26.7 at% AI게열과 Ta-45.4at.%AI계열에 Ar에 대한 질서유량비로 26%까지 질소를 첨가하여 Ta-AI-N박막을 증착한후, 300-$600^{\circ}C$온도 구산에서 열처리 전후의 구조 및 전기적 특성과 열적안정성을 통하여 레지스터의 적용가능성을 조사하였다. 구조 및 조성 분석은 X-선 회절과 Rutherford Backscattering Spectrometry(RBS)로 관찰하였고 열적안정성은 4단자법(four point probe method)을 이용한 저항변화를 통하여 측정하였다. 순수 Ta에 AI을 첨가하면 확장된 $\beta$($\beta$-Ta)N 합금박막에서 가장 열적안정성이 우수하게 나타났던 질소첨가 범위는 Ta $N_{hcp}$또는 TaN/ sub fcc/또는 Ta $N_{fcc}$와 비정질과의 혼합상순으로 상천이를 나타내었다. Ta-AI-N 합금박막에서 가장 열적안정성이 우수하게 나타났던 질서첨가 범위는 Ta-26.7at. % AI계열의 경우 19-36at.% $N_{2}$구간이었고, Ta-45.5at.% AI계열의 경우는 30-45at.%구간이었다. Ta-AI합금박막은 질소가 첨가되지 않아도 열처리 온도 및 시간에 따라 약 10% 이내의 비교적 작은 저항변화를 보여 열적안정성이 우수하지만 질소를 첨가하여 Ta-AI-N합금박막을 형성시킬경우, 증착된 상태에서 이미 큰 비저항을 나타내었고 열처리 동안 3%이내의 매우 작은 저항변화를 나타내었기 때문에 레지스터용 재료로써 열적안정성에 대한 잠재력이 크다.

• Smart Media Journal
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• v.12 no.8
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• pp.60-68
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• 2023

After COVID-19, hotel industry is rapidly experiencing changes in the business environment, and under the influence of the Fourth Industrial Revolution, hotel industry is striving to secure competitive advantages through differentiation, including the use of big data and the IoT in service provision, as well as the introduction of artificial intelligence(AI) robot services. This study analyzed the perceived value of AI robot services and their impact on usage attitudes and behavioral intentions of customers who have used hotels that have introduced AI robot services. The results of the study showed that the value of robot services perceived by customers who have used robot services in hotels is categorized into three dimensions: social, experiential, and functional, and all of them have a positive effect on usage attitudes, with social, functional, and experiential values having a positive effect on usage attitudes in that order. Attitude toward use was also analyzed to have a positive effect on behavioral intention, which is consistent with the value-attitude-behavior model. Therefore, it is necessary for hotels to improve the satisfaction of hotel guests through diversified services of AI robot service.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.499-503
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• 2024

Broadcasting programs are provided to various media such as Internet replay, OTT, and IPTV services as well as self-broadcasting. In this case, it is very important to provide keywords for search that represent the characteristics of the content well. Broadcasters mainly use the method of manually entering key keywords in the production process and the archive process. This method is insufficient in terms of quantity to secure core metadata, and also reveals limitations in recommending and using content in other media services. This study supports securing a large number of metadata by utilizing closed caption data pre-archived through the DTV closed captioning server developed in EBS. First, core metadata was automatically extracted by applying Google's natural language AI technology. The next step is to propose a method of finding core metadata by reflecting priorities and content characteristics as core research contents. As a technology to obtain differentiated metadata weights, the importance was classified by applying the TF-IDF calculation method. Successful weight data were obtained as a result of the experiment. The string metadata obtained by this study, when combined with future string similarity measurement studies, becomes the basis for securing sophisticated content recommendation metadata from content services provided to other media.