• 한국압력기기공학회 논문집
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• 제11권1호
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• pp.20-24
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• 2015

Steam generator(S/G) tubes in pressurized water reactor (PWR's) are subject to several types of degradation. This degradation includes denting, pitting, intergranular attack(IGA), intergranular stress corrosion cracking(IGSCC), fatigue, fretting and wear. Degradation can be derived from either the primary side(inside) or the secondary side(outside) of the tube. Recent issue for tube degradation in domestic steam generator is the tube end cracking on seal weld region. The seal weld region at the tube end and tube itself is regarded as a pressure boundary between the primary side and the secondary side. One of the Westinghouse Model-F S/G has experienced tube end cracking and its number of plugging approximately becomes to the operating limit up to 5% due to tube end cracking which was reported as SAI/MAI(single/multiple axial indication) or SCI/MCI(Single/multiple circumferential indication) from the results of eddy current testing. Eddy current mock-up test was carried out to determine the origin of cracking whether it is from weld zone area or parent tube. This result was helpful to analyze crack location on ECT data. Correct action on this problem was the installation of tube-end sleeve. Last year, after removing 340 installed plugs from tubes, selected 269 tubes took tube-end sleeve installation. Tube-end sleeve brought pressure boundary from parent tube to installed sleeve tube. Tube-end sleeve has the benefit of reducing outage period and increasing more revenue than replacing S/G. This paper is provided to assist interest parties in effectively understanding this issue.

• 한국컴퓨터정보학회논문지
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• 제25권8호
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• pp.73-79
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• 2020

최근 4차 산업혁명의 시작으로 사물인터넷, 인공지능, 가상현실, 5G 등 분야의 기술이 많이 발전하고 있다. 그 중 사물인터넷의 경우 다른 기술들에 비해 현재 상용화가 많이 되어 있으며, 계속해서 사물의 연결 수는 매년 증가하고 있다. 이렇게 계속해서 증가하고 있는 사물인터넷은 사용자의 편의성과 많은 정보를 제공하는 큰 장점이 있지만, 보안은 발전 속도와 비교하면 따라가지 못하고 있다는 것으로 나타났다. 사물인터넷 서비스는 관련 기기마다 서비스를 계속해서 제공하고 있지만, 현재는 기기의 서비스를 활용하여 다른 기술과 결합해서 새로운 서비스를 제공하는 유형도 늘어가고 있는 것으로 나타났으며, 앞으로도 더욱 더 넓은 범위의 서비스가 생겨날 것으로 예상한다. 이렇게 다방면으로 빠르게 발전하고 있는 사물인터넷 기술의 발전방향을 파악하여 안전하게 사물인터넷을 사용할 수 있도록 관련된 보안연구가 필요하다. 이에 따른 연구의 결과는 하드웨어 업그레이드나 소프트웨어적인 패치로 안정성을 보장할 수 있었다. 본 논문에서는 사물인터넷에 관련된 보안 이슈와 서비스에 관한 연구를 조사하여 발전방향을 분석한 후 현재 트랜드를 알아보고 이와 관련하여 필요한 보안요소 앞으로의 보안방향 및 서비스제공이 어떠한 형태로 발전되어 나아갈지 알아본다.

• 한국융합학회논문지
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• 제11권9호
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• pp.21-29
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• 2020

최근 디지털 사회의 도래로 다양한 데이터가 폭발적으로 증가하고, 그중 문헌 내 주제어를 도출하는 토픽 모델링에 관한 연구가 활발히 진행되고 있다. 본 논문의 연구목표는 토픽 모델링 방법 중 하나인 DTM(Dynamic Topic Model) 모델을 적용해 D.N.A.(Data, Network, A.I) 분야에 대한 연구동향을 탐색하는데 있다. 실험 데이터는 최근 6년간(2015~2020) ICT(Information and Communication Technology) 분야 중 기술대분류가 SW·AI에 해당하는 연구과제 1,519개 사업에 대해 DTM 모델을 적용하였다. 실험결과로, D.N.A. 분야의 기술 키워드 Big data, Cloud, Artificial Intelligence와 확장된 의미의 기술 키워드 Unstructured, Edge Computing, Learning, Recognition 등이 매년 연구에 표출되었으며, 해당 키워드 들이 특정 연구과제에 종속되지 않고 다른 연구과제에서도 포괄적으로 연구되고 있음을 확인하였다. 끝으로 본 논문의 연구결과는 향후 D.N.A. 분야에 대한 정책기획·과제기획 등 연구개발 기획 과정과 기업의 기술 확보전략·마케팅 전략 등 다양한 곳에 활용될 수 있을 것으로 기대한다.

• Journal of Korean Medical Science
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• 제33권48호
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• pp.309.1-309.13
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• 2018

Background: The aim of this study was to observe long-term outcomes of very low birth weight infants (VLBWIs) born between 2013 and 2014 in Korea, especially focusing on neurodevelopmental outcomes. Methods: The data were collected from Korean Neonatal Network (KNN) registry from 43 and 54 participating units in 2013 and 2014, respectively. A standardized electronic case report form containing 30 items related to long-term follow up was used after data validation. Results: Of 2,660 VLBWI, the mean gestational age and birth weight were $29^{1/7}{\pm}2^{6/7}$ weeks and $1,093{\pm}268g$ in 2013 and $29^{2/7}{\pm}2^{6/7}$ weeks and $1,125{\pm}261g$ in 2014, respectively. The post-discharge mortality rate was 1.2%-1.5%. Weight < 50th percentile was 46.5% in 2013 and 66.1% in 2014. The overall prevalence of cerebral palsy among the follow up infants was 6.2% in 2013 and 6.6% in 2014. The Bayley Scales of Infant Developmental Outcomes version II showed 14%-25% of infants had developmental delay and 3%-8% of infants in Bayley version III. For the Korean developmental screening test for infants and children, the area "Further evaluation needed" was 5%-12%. Blindness in both eyes was reported to be 0.2%-0.3%. For hearing impairment, 0.8%-1.9% showed bilateral hearing loss. Almost 50% were readmitted to hospital with respiratory illness as a leading cause. Conclusion: The overall prevalence of long-term outcomes was not largely different among the VLBWI born between 2013 and 2014. This study is the first large national data study of long-term outcomes.

• 인터넷정보학회논문지
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• 제21권6호
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• pp.133-139
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• 2020

Big data, artificial intelligence (AI), and machine learning are keywords that represent the Fourth industrial Revolution. In addition, as the development of science and technology, the Korean government, public institutions and industries want professionals who can collect, analyze, utilize and predict data. This means that data analysis and utilization education become more important. Education on data analysis and utilization is increasing with trends in other academy. However, it is true that not many academy run long-term and systematic education. Korea Institute of Science and Technology Information (KISTI) is a data ecosystem hub and one of its performance missions has been providing data utilization and analysis education to meet the needs of industries, institutions and governments since 1966. In this study, KISTI's data education was analyzed using the number of curriculum trainees per year from 2001 to 2019. With this data, the change of interest in education in information and data field was analyzed by reflecting social and historical situations. And we identified the characteristics of KISTI and trainees. It means that the identity, characteristics, infrastructure, and resources of the institution have a greater impact on the trainees' interest of data-use education.In particular, KISTI, as a research institute, conducts research in various fields, including bio, weather, traffic, disaster and so on. And it has various research data in science and technology field. The purpose of this study can provide direction forthe establishment of new curriculum using data that can represent KISTI's strengths and identity. One of the conclusions of this paper would be KISTI's greatest advantages if it could be used in education to analyze and visualize many research data. Finally, through this study, it can expect that KISTI will be able to present a new direction for designing data curricula with quality education that can fulfill its role and responsibilities and highlight its strengths.

• Journal of Information Processing Systems
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• 제18권3호
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• pp.359-373
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• 2022

The new crown pneumonia (COVID-19) has become a global epidemic. The disease has spread to most countries and poses a challenge to the healthcare system. Contact tracing technology is an effective way for public health to deal with diseases. Many experts have studied traditional contact tracing and developed digital contact tracking. In order to better understand the field of contact tracking, it is necessary to analyze the development of contact tracking in the field of computer science by bibliometrics. The purpose of this research is to use literature statistics and topic analysis to characterize the research literature of contact tracking in the field of computer science, to gain an in-depth understanding of the literature development status of contact tracking and the trend of hot topics over the past decade. In order to achieve the aforementioned goals, we conducted a bibliometric study in this paper. The study uses data collected from the Scopus database. Which contains more than 10,000 articles, including more than 2,000 in the field of computer science. For popular trends, we use VOSviewer for visual analysis. The number of contact tracking documents published annually in the computer field is increasing. At present, there are 200 to 300 papers published in the field of computer science each year, and the number of uncited papers is relatively small. Through the visual analysis of the paper, we found that the hot topic of contact tracking has changed from the past "mathematical model," "biological model," and "algorithm" to the current "digital contact tracking," "privacy," and "mobile application" and other topics. Contact tracking is currently a hot research topic. By selecting the most cited papers, we can display high-quality literature in contact tracking and characterize the development trend of the entire field through topic analysis. This is useful for students and researchers new to field of contact tracking ai well as for presenting our results to other subjects. Especially when comprehensive research cannot be conducted due to time constraints or lack of precise research questions, our research analysis can provide value for it.

• 융합신호처리학회논문지
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• 제23권4호
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• pp.256-263
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• 2022

피부암은 세계에서 가장 흔한 질병 중 하나로 국내에선 발병률이 지난 5년 동안 약 100%가 증가했고 미국에선 매년 500만여 명이 피부암을 진단받는다. 피부암은 주로 자외선의 노출로 피부 조직이 오랜 시간 손상되면서 발생하게 된다. 피부암의 악성종양인 흑색종은 피부 위에서 발생하는 멜라닌 세포 모반과 생김새가 유사해 2차 징후가 발생하지 않는 한 일반인이 자각하기 어려운 점이 있다. 본 논문에서는 이러한 피부암의 조기 발견과 분류를 위해 피부암 병변 윤곽선 검출 알고리즘과 피부암 병변 분류를 수행하는 딥러닝 모델인 CRNN을 제안한다. 실험 결과 본 논문에서 제안하는 윤곽선 검출 알고리즘을 이용할 시 분류 정확도가 97%로 가장 높은 정확도를 보였고 Canny 알고리즘의 경우 78%를 보였고 Sobel의 경우 55%, Laplacian의 경우 46%를 보였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권4호
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• pp.1123-1146
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• 2023

In South Korea, there have been many studies on efficient building-energy management using renewable energy facilities in single zero-energy houses or buildings. However, such management was limited due to spatial and economic problems. To realize a smart zero-energy city, studying efficient energy integration for the entire city, not just for a single house or building, is necessary. Therefore, this study was conducted in the eco-friendly energy town of Chungbuk Innovation City. Chungbuk successfully realized energy independence by converging new and renewable energy facilities for the first time in South Korea. This study analyzes energy data collected from public buildings in that town every minute for a year. We propose a smart city building-energy management model based on the results that combine various renewable energy sources with grid power. Supervised learning can determine when it is best to sell surplus electricity, or unsupervised learning can be used if there is a particular pattern or rule for energy use. However, it is more appropriate to use reinforcement learning to maximize rewards in an environment with numerous variables that change every moment. Therefore, we propose a power distribution algorithm based on reinforcement learning that considers the sales of Energy Storage System power from surplus renewable energy. Finally, we confirm through economic analysis that a 10% saving is possible from this efficiency.

• 디지털융복합연구
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• 제20권3호
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• pp.53-61
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• 2022

본 연구의 목적은 인공지능 챗봇이 한국 대학생 영어학습자들에게 전치사와 관사 두 목표 문법을 습득하는데 효과적인지 실험하기 위한 것이었다. 필수 영어 과목을 수강한 46명의 1학년 학생들을 대상으로 하였다. 참여자들은 실험군과 통제군. 두 그룹으로 무작위로 선별되었다 (각 그룹 23명). 실험 그룹은 6주 동안 챗봇과 6번의 채팅 세션을 가졌다. 사전·사후 실험을 통해 영어 작문에서 목표 문법의 오류 빈도의 변화를 비교함으로써 효과를 검토했다. 실험결과는 챗봇과의 대화 후에 실험군이 전치사와 관사 모두에서 누락 오류의 평균을 유의하게 줄였다는 것을 보여줬다. 다른 오류 범주에서 큰 효과를 거두기 위해서는 학생들의 단답형 또는 부정확한 답변을 줄이고 챗봇과의 대화에 적극적으로 참여하도록 유도하는 챗봇 피드백이 개선되어야 한다.

• 산업경영시스템학회지
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• 제46권2호
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• pp.176-182
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• 2023

With about 80% of the global economy expected to shift to the global market by 2030, exports of reverse direct purchase products, in which foreign consumers purchase products from online shopping malls in Korea, are growing 55% annually. As of 2021, sales of reverse direct purchases in South Korea increased 50.6% from the previous year, surpassing 40 million. In order for domestic SMEs(Small and medium sized enterprises) to enter overseas markets, it is important to come up with export strategies based on various market analysis information, but for domestic small and medium-sized sellers, entry barriers are high, such as lack of information on overseas markets and difficulty in selecting local preferred products and determining competitive sales prices. This study develops an AI-based product recommendation and sales price estimation model to collect and analyze global shopping malls and product trends to provide marketing information that presents promising and appropriate product sales prices to small and medium-sized sellers who have difficulty collecting global market information. The product recommendation model is based on the LTR (Learning To Rank) methodology. As a result of comparing performance with nDCG, the Pair-wise-based XGBoost-LambdaMART Model was measured to be excellent. The sales price estimation model uses a regression algorithm. According to the R-Squared value, the Light Gradient Boosting Machine performs best in this model.