• Nuclear Engineering and Technology
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• 제54권2호
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• pp.770-780
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• 2022

In 1993 the University of Extremadura initiated the design, construction and management of the Radiological Alert Network of Extremadura (RAREx). The goal was to acquire reliable near-real-time information on the environmental radiological status in the surroundings of the Almaraz Nuclear Power Plant by measuring, mainly, the ambient dose equivalent. However, the phased development of this network has been carried out from two points of view. Firstly, there has been an increase in the number of stations comprising the network. Secondly, there has been an increase in the number of monitored parameters. As a consequence of the growth of RAREx network, large data volumes are daily generated. To face this big data paradigm, software applications have been developed and implemented in order to maintain the indispensable real-time and efficient performance of the alert network. In this paper, the description of the current status of RAREx network after 30 years of design and performance is showed. Also, the performance of the graphing software for daily assessment of the registered parameters and the automatic on real time warning notification system, which aid with the decision making process and analysis of values of possible radiological and non-radiological alterations, is briefly described in this paper.

• 산경연구논집
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• 제13권9호
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• pp.27-36
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• 2022

Purpose: The coronavirus pandemic has affected the tourism industry in a big way. The travel industry suffered intense damage from the pandemic and procedures acquainted to containing its spread because the pandemic outbreak has led to a decline in the number of tourists and a change in their behavior. At this point, this research is to investigate adequate solutions for tourism industry to overcome the crisis in a post-Covid 19 era. Research design, data and methodology: The current author gathered data from each included study to analyze and summarize the evidence when conducting a literature analysis. This stage involves gathering and reviewing intricate texts databases for the meta-analysis. Results: The current author found total five solutions from numerous literature contents, suggesting how to overcome the crisis in a post-Covid era for tourism industry. Solutions as follows, (1) Drawing beginning illustrations, (2) Introducing Government Backing Programs, (3) Increasing Promotion of Tourism Destinations, (4) Enhancing Safety and Security Measures, and (5) Improving Infrastructure and Facilities. Conclusions: This research suggests that although the global economic recession leads to reduced demand and intense competition from other sectors, the tourism industry will be well positioned to weather these challenges if practitioners of tourism organizations follow five solutions of this research.

• 스마트미디어저널
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• 제12권10호
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• pp.38-46
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• 2023

Farming activities are transforming from traditional skill-based agriculture into knowledge-based and technology-driven digital agriculture. The use of intelligent information and communication technology introduces the idea of smart farming that enables farmers to collect weather data, monitor crop growth remotely and detect crop diseases easily. The introduction of Plantix, a pest and disease management tool in the form of a mobile application has allowed farmers to identify pests and diseases of the crop using their mobile devices. Hence, this study collected the reviews of Plantix to explore the response of the users on the Google Play Store towards the application through Latent Dirichlet Allocation (LDA) topic modeling. Results indicate four latent topics in the reviews: two positive evaluations (compliments, appreciation) and two suggestions (plant options, recommendations). We found the users suggested the application to additional plant options and additional features that might help the farmers with their difficulties. In addition, the application is expected to benefit the farmer more by having an early alert of diseases to farmers and providing various substitutes and a list of components for the remedial measures.

• 스마트미디어저널
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• 제13권2호
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• pp.16-22
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• 2024

Greenhouse provides opportunities to have big yield effectively and efficiently. However, many resources are required, such as fertigation, a kind of solution of nutrient. Resources supply is essential to cultivate crops. Inadequate supply will hinder plant growth whereas the surplus results in waste. In this paper, we are especially interested in the fertigation supply. Further, excess fertigation leads to drainage which is difficult to purify and threatens the environment. To address this challenge, we aim to predict the desired amount of fertigation. To achieve this objective, we first establish a prototype to record the climate conditions inside a rose greenhouse using Internet of Things sensors. Simultaneously, the desired fertigation amount is obtained with the help of weight scale and historical data of fertigation supply and drainage. Second, a method is proposed to predict the desired fertigation by taking the sensors' data as input, with a time-series model. Extensive experimental results suggest the potential of our objective and method. To be specific, our method achieves an average MAE 0.032 in the validation datasets.

• 아태비즈니스연구
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• 제15권1호
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• pp.99-111
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• 2024

Purpose - This study aims to quantify the long tail effect in the digital economy. It also investigates the role of digital platform before and after the COVID-19 pandemic. Design/methodology/approach - We take advantage of a granular data set from one of the biggest digital platforms in Korea. Rather than computing the absolute number of products sold or the Gini coefficient, we estimate the slope of the log-linear relationship of the non-parametric sales distribution. Findings - We find that the use of online food order and delivery services is positively associated with individual restaurant's sales growth. We also document that the long tail effect is increasing over time. Long tail effects are clustered in the cross-section where average revenue per order is high or the restaurant belongs to the top 50% of the sales distribution. Research implications or Originality - The findings may indicate that digital platforms are contributing to the development of the digital economy in Korea. Also, we confirm that digital platforms make it possible for small and sole proprietors to go through the difficulties induced by the COVID-19 pandemic.

• 한국융합학회논문지
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• 제13권4호
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• pp.233-244
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• 2022

최근 기업경영과 관련되어 가장 주목받고 있는 것은 ESG(Environmental, Social, Governance) 일 것이다. ESG 경영을 선언한 많은 기업들이 있지만, KT는 2021년 본격적인 ESG 경영을 선언하며 지속가능경영의 전략을 이해관계자들과 공유하고 있다. 또한 KT는 국내 ICT 업계 최초로 ESG 채권을 발행하며 ESG 경영을 강화하고 있다. 코로나19로 정보기술산업이 더욱 중요해진 시점에서 본 연구는 KT의 ESG 경영 목표와 전략의 사례를 환경, 사회, 지배구조 영역으로 구분하여 살펴보고자 하였다. KT는 환경 영역에서 '환경경영', '환경대응', '에너지 자원', '친환경 프로젝트'를 통해 환경 건전성 달성을 목표로 하고 있었다. 또한 사회 영역에서 '사회공헌', '동반성장', '인권경영' 등을 통해 진정성 있는 사회적 가치 창출을 추구하였다. 마지막으로 지배구조 영역에서는 '윤리·컴플라이언스', '리스크 관리' 등을 통해 경제적 신뢰성을 추구하기 위한 투명한 기업 경영 체계를 지향하고 있었다. 특히 KT는 디지털 플랫폼 기업이라는 특징을 기반으로 AI, BigData 기술을 활용하여 환경, 사회문제를 해결하기 위한 전략을 추진하며 KT만의 ESG 경영을 도모하고 있었다. 본 연구는 화두로 떠오른 ESG 경영과 관련해 KT의 ESG 경영 사례를 통해 ESG전략 수립과 ESG 경영 발전방향에 대한 시사점을 도출하고자 한다.

• 한국농림기상학회지
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• 제22권4호
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• pp.340-345
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• 2020

본 연구에서는 첨단 옥외환경조절시설인 SPAR 시스템의 작물 및 환경 관측 자료의 품질 관리와 보증 방법을 최초로 제시하였다. 특히 실시간 군락 CO2플럭스의 경우에는 수집되는 자료의 특성을 고려하여 이상치의 제거와 보정이 병행되어야 함을 확인하였다. 본 연구를 통해 구축된 자료 처리 방법들은 향후 SPAR 자료를 통한 작물 생육 모형 개선에 매우 중요하게 활용될 수 있을 것으로 보인다. SPAR 내 작물과 환경 관련 10분 평균 자료는 국립식량과학원 내 작물 연구 통합 정보시스템(Crop Research Information System, CRIS) 웹사이트(www2.nics.go.kr/cris)에서 이용 가능하다.

• 한국사회복지학
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• 제66권3호
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• pp.133-158
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• 2014

경제적, 사회적, 인구학적 변화에 따라 전세계적으로 돌봄노동의 규모와 중요성은 상당히 커졌다. 그에 따라 한국을 포함한 많은 나라들에서 돌봄노동자는 노동력을 구성하는 의미있는 부분으로 자리잡게 되었다. 그러나 여전히 돌봄노동은 다른 노동에 비해 임금수준이 낮고 열악한 노동으로 평가되고 있다. 이 연구는 한국 돌봄노동의 실태를 조망하고, 성향점수매칭법을 통해 임금불이익을 실증적으로 추정하는 것을 목적으로 한다. 돌봄노동에 대한 실태분석을 통해 돌봄직업이 학력, 연령, 근속기간과 관련하여 위계화되어 있음을 알 수 있었다. 또한 성향점수 매칭법을 활용하여 돌봄노동의 임금불이익을 추정한 결과, 돌봄직업 근로자는 다른 직업 근로자보다 시간당 임금수준이 9.2% 낮음을 확인할 수 있었다. 돌봄노동조건의 열악함과 임금불이익은 사회서비스 확대와 관련하여 우선적으로 해결해야할 과제이다. 적절한 보상체계 없는 돌봄노동의 안정적 재생산은 어려우며, 사회서비스의 원활한 공급과 적절한 질 유지 또한 불가능하기 때문이다.

• 국제학술발표논문집
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• The 7th International Conference on Construction Engineering and Project Management Summit Forum on Sustainable Construction and Management
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• pp.24-31
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• 2017

As the concept of sustainability becomes more and more popular, a large amount of literature have been recorded recently on intelligent green building and smart city (IGB&SC). It is therefore needed to systematically analyse the existing knowledge structure as well as the future new development of this domain through the identification of the thematic trends, landmark articles, typical keywords together with co-operative researchers. In this paper, Citespace software package is applied to analyse the citation networks and other relevant data of the past eleven years (from 2006 to 2016) collected from Web of Science (WOS). Through this, a series of professional document analysis are conducted, including the production of core authors, the influence made by the most cited authors, keywords extraction and timezone analysis, hot topics of research, highly cited papers and trends with regard to co-citation analysis, etc. As a result, the development track of the IGB&SC domains is revealed and visualized and the following results reached: (i) in the research area of IGB&SC, the most productive researcher is Winters JV and Caragliu A is most influential on the other hand; (ii) different focuses of IGB&SC research have been emerged continually from 2006 to 2016 e.g. smart growth, sustainability, smart city, big data, etc.; (iii) Hollands's work is identified with the most citations and the emerging trends, as revealed from the bursts analysis in document co-citations, can be concluded as smart growth, the assessment of intelligent green building and smart city.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2022년도 추계학술대회
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• pp.81-81
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• 2022

Recently, many studies on big data based smart farming have been conducted. Research to quantify morphological characteristics using image data from various crops in smart farming is underway. Rice is one of the most important food crops in the world. Much research has been done to predict and model rice crop yield production. The number of productive tillers per plant is one of the important agronomic traits associated with the grain yield of rice crop. However, modeling the basic growth characteristics of rice requires accurate data measurements. The existing method of measurement by humans is not only labor intensive but also prone to human error. Therefore, conversion to digital data is necessary to obtain accurate and phenotyping quickly. In this study, we present an image-based method to predict leaf number and evaluate tiller number of individual rice crop using YOLOv5 deep learning network. We performed using various network of the YOLOv5 model and compared them to determine higher prediction accuracy. We ako performed data augmentation, a method we use to complement small datasets. Based on the number of leaves and tiller actually measured in rice crop, the number of leaves predicted by the model from the image data and the existing regression equation were used to evaluate the number of tillers using the image data.