• Journal of Information Technology Services
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• v.10 no.3
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• pp.21-30
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• 2011

Expectation for improvement of creativity and problem-solving capability has increased the creative robotics classes in the form of after-school activity in more than half of total elementary schools. While Ministry of Education, Science and Technology has promoted 'Green IT Guidelines' as a part of 'Eco-friendly Green School Development Project', the Green issues have not been considered enough in those creative robotics classes. In this paper, we would like to address the Green issues, especially in the r-Learning services based on UCR (User Created Robots). First, trend of green IT education, r-Learning services and UCR are reviewed. And the current status of eco-related operations and teachers' perception in the robotics classes of elementary schools is investigated. Examples of Green UCR are also searched and green programs based on the three kinds of UCR, UC-TR, UC-AR, UC-CR, are explored. Finally, we propose action plans to promote the UCR-based r-Learning service reflecting green issues.

• Journal of the Korean Society of Visualization
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• v.19 no.2
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• pp.41-47
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• 2021

River and stream are the important water supply source in our lives. Eutrophication causes excessive green algae growth including microcystis, which makes harmful to ecosystem and human health. Therefore, the water purification process to remove green algae is essential. In Korea, green algae alarm system exists depending on the concentration of green algae cells in river or stream. To maintain the growth amount under control, green algae monitoring system is being used. However, the unmanned, small and automatic monitoring system would be preferable. In this study, we developed the 3D printed device to measure the concentration of green algae cell using microfluidic droplet generator and deep learning. Deep learning network was trained by using transfer learning through pre-trained deep learning network. This newly developed microfluidic cell counter has sufficient accuracy to be possibly applicable to green algae alarm system.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.2
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• pp.139-146
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• 2020

The camouflage pattern was difficult to distinguish from the surrounding background, so it was difficult to classify the object and the background image when the color image is used as the training data of deep-learning. In this paper, we proposed a red-green color blindness image transformation method using the principle that people of red-green blindness distinguish green color better than ordinary people. Experimental results show that the camouflage soldier's recognition performance improved by proposed a deep learning model of the ensemble technique using the imitated red-green-blind image data and the original color image data.

• The Journal of Information Systems
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• v.25 no.1
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• pp.25-47
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• 2016

Purpose In this study, the relationships among environmental information exchange with suppliers(EIES), green collaboration with suppliers, green learning by environmental information, the adoption of green supply-chain management techniques(AGSMT) (i.e., the green purchasing, product design and production, and the recovery of extra facilities and inventories), environmental performance, and the organizational performance of a firm were empirically investigated. Design/methodology/approach Data for this study were drawn from a survey of the current status of EIES levels and AGSMT usage observed in Korean manufacturing firms. In total, 500 organizations were randomly selected from a population of about 1,000 firms that are listed on the Korean stock market. In order to collect empirical data, this research administered questionnaires with the sample firms. Only chief production executives were selected as respondents. A questionnaire with a cover letter was mailed to each respondent. The survey was conducted during a 3-month period between March 2015 and June 2015. Finally, 78 valid data of the sample firms were collected. Findings The results of this study showed that EIES positively affects the green corporation and learning. According to the results, it was observed that both green corporation and green learning have a positive impact on the levels of AGSMT(i.e., the green purchasing, product design and production). It was also demonstrated that AGSMT has a direct positive impact on environmental performance. In examining the effects of environmental performance on the organizational performance of a firm, significant impact was found.

• 한국IT서비스학회:학술대회논문집
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• 2010.05a
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• pp.260-265
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• 2010

국제적으로 관심이 증가되고 있는 지구 온난화와 환경문제는 제조업체, 유통업체, 서비스업체 뿐만 아니라 교육현장에 있어서도 매우 중요한 이슈이다. 창의성 증진에 대한 기대로 성장하고 있는 로봇교육은 OECD 및 EU 국가정부의 환경영향 카테고리인 유독성, 비에너지 자원고갈의 문제와 연결된다. 본 논문에서는 r-Learning을 위한 교구로봇교육에서 환경이슈를 고려하는 미래지향적 Green UCR(User Created Robots)에 대한 이론적 개념을 정립하고자 한다. 그리고 교과부에서는 '친환경 그린스쿨 조성사업'을 추진하고 있는데, 창의성 증진뿐만 아니라 환경보호에 대한 인지적 교육 효과가 매우 큰 초등학교의 Green 로봇교육은 제대로 조명받고 있지 못하는 실정이다. 이에 국내외 Green 로봇 제품 및 교육 현황을 살펴보고, 국내의 초등 방과후학교 로봇교실에서의 연간 전국 건전지 사용실태 추정수치와 교사의 Green UCR에 대한 이슈를 조사하여 제시하고자 한다. 마지막으로 이를 토대로 업체, 교육기관, 정부를 위한 그린 UCR 교육 서비스를 위한 가이드라인을 제시한다.

• The Journal of the Korea Contents Association
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• v.12 no.9
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• pp.27-39
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• 2012

The purpose of this study is to develop and suggest u-project teaching and learning model in order to effectively practice multidisciplinary and practical green growth conversion education, In order to achieve the purpose of study, the researchers conducted surveys to middle and high school teachers (189), teachers-to-be (285), and middle school students (358) on green growth perception, and analyzed relation between the ten green growth strategic directions and the 2007 and 2009 curricula. The extraction of the teaching and learning contents for the ubiquitous green growth conversion education and the development of a TUGG (Teaching Ubiquitously for Green Growth) model that is suitable for middle school application were also pursued. This study will increase the understanding of the necessity and propriety of green growth and also promote multidisciplinary and practical green growth conversion education.

• Journal of Environmental Science International
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• v.32 no.8
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• pp.573-583
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• 2023

This study was conducted to verify the effectiveness of improving indoor environmental awareness, relieving stress, and improving learning efficiency in school indoor green space, and suggest desirable ways to develop indoor green space in the future. As part of the study, a survey was conducted among 225 individuals across six schools in a metropolitan area with garden and panel-type indoor gardens inside the school building. The survey comprised the current status and use of indoor green spaces, the perception of indoor green spaces, improvement measures in indoor green spaces, and basic properties. Semantic Differential (SD) was used to investigate the impression of school indoor spaces. Resultantly, the more frequent the use of green spaces in the school, the more they feel the positive effects of indoor green spaces, such as improving the school's indoor environment, reducing stress, and improving learning efficiency. In addition, it appears that the more frequent contact with the natural environment, the more they feel the positive effects provided by indoor green space at school. Therefore, it is suggested that educational conditions must be improved by revitalizing various green welfare, including indoor green areas, at the school level.

• Journal of Haehwa Medicine
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• v.12 no.1
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• pp.11-26
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• 2003

Alzheimer's disease (AD) is characterized by amyloid deposition and associated loss of neunons in brain regions involved in learning and memory processes. Several causes of evidence support that the congnitive disturbance is closed associated with the deficit of cerebral acetylcholine neurotransmission, and the effect of carboxyl terminal 105 amino acid fragment (CT105) of the amyloid precursor protein (APP) on the gene expression of proinflammatory cytokines. We tested it on the scopolamine-induced amnesia model of the ICR mouse using the Morris water maze with repeated orally administration of 1st Green-Tea extract (200 mg/kg) and 2nd Green-Tea extract (200 mg/kg). The Green-Tea prevents impairment of learning and memory and neuronal loss in mouse models of cognitive disturbance and it demonstrated selectivity for inhibition of acetylcholinesterase (AChE). Furthermore, the repeated administration of Green-Tea, CT105-induced alzheimer's mouse model showed central cholinergic activity by ameliorates learning and memory impairment, and isolation of CD14 microglia showed significantly decreases intracellular release of the proinflammatory cytokines tumor necrosis factor-${\alpha}$, interleukin-$1{\beta}$ and reactive oxygen species (ROS). Because of its composite profile, oral therapeutic index and a prophylactic, Green-Tea is considered the better therapeutic candidate for the treatment of Alzheimer's disease.

• Journal of Korean Society for Quality Management
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• v.35 no.1
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• pp.113-123
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• 2007

This paper considers the development of e-learning training program for the six sigma green belt. Comparative studies of existing e-learning programs are performed and a new one is proposed. A catapult simulator is developed and the automatic grading function which immediately computes the result of the catapult simulation and gives feedback to the trainees is presented. An illustrative example is also given.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.15-21
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• 2023

This paper is a study on the development of an artificial intelligence model that recognizes a hole cup on a golf green. A CNN-based object detection algorithm was used to recognize the hole cup on the green. Also, Apple's CreateML was used to create a model of the object detection algorithm. This paper created a JSON file with 120 training images and annotations to meet the needs of CreateML. In addition, for more accurate learning, data amplification algorithm was used for learning data and 288 learning data were used for learning. By changing the Iterations, Batch size, and Grid size required by CreateML, we found parameter values that improve the performance of the model. A prototype app was developed by applying the developed model, and performance was measured on an actual golf course green using the prototype app. As a result of the measurement, it was found that the hole cup was accurately recognized within 10m, which is the typical golfer's putting distance.