• Journal of the Speleological Society of Korea
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• v.45 no.46
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• pp.69-79
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• 1996

동굴은 미지의 세계이고, 암흑의 신비로운 지하세계이기 때문에 우리 인간에게는 매우 흥미로운 공간이라고 할 수 있다. 그러므로 이러한 공간을 관광자원으로 활용하여 지역주민이 소득을 올리고, 청소년에게 탐험의 세계, 모험의 세계는 물론 자연학습의 현장으로 활용할 수 있게 하는 바람직한 경우도 있다. 그러나 이러한 경우 동굴이 개발되면 전자와 같은 긍정적인 면이 있는 반면에 동굴의 파괴, 오손 및 오염과 같은 악영향을 가져오게 되므로 동굴을 개발할 당시부터 악영향을 최소하기 위해서는 환경보전과 환경보호에 커다란 관심을 가져야 한다. 따라서 본 연구에서는 이제 동굴 개장이 2개월밖에 되지 않은 천곡동굴이 관광지로 개방됨으로써 나타나게 될 환경변화를 미리 살펴보고 그에 대한 대책을 마련하려고 하였다. 그 결과는 다음과 같다. 첫째, 천곡동굴의 경우 동굴 공간이 넓고 관광통로가 왕복통로로 되어 있어 체동인구가 2배가 되므로 많은 관광객의 출입시 동굴 내부의 기온이 상승하기 때문에 동시에 관람할 수 있는 적정 관람객 수를 조절해야 한다. 둘째, 천곡동굴은 개장 시일이 오래 경과하지 않았기 때문에 퇴적물의 파손이 전무하다고 할 수 있다. 따라서 이 상태를 계속 유지하기 위해서 동굴 내부에 관리인을 상주시킨다거나, 입동객의 소지품을 보관할 수 있는 장소를 마련하여 동굴퇴적물을 훼손할 수 있는 물건의 반입을 애초에 방지하는 방안도 필요하다고 본다. 마지막으로, 동굴 개발 당시 조명을 너무 가깝게 설치한 때문에 개방 후 얼마 되지 않았음에도 불구하고 몇 군데에서 녹색균류가 관측되고 있으므로 조명시설의 원거리 조정이나 간접조명 대책을 강구해야 한다.만 아니라 오류의 크기도 확률적으로 변하는 상황을 모형에 반영하여 보다 현실성있게 모형화하였다.균 6.5점(2-9점)으로 대체로 높게 나타났는데 이는 대중매체와 신문, 잡지류를 통한 지식의 정보가 많기 때문으로 생각된다 비만 정도에 따라서는 유의적인 차이를 보이지 않았다. 5. 비만 정도와 상호간의 관계를 보면 BMI 수치가 높을수록 비만인 형제수가 많았으며, 자신의 비만 자각도도 높았다. 편식율은 비만 정도가 낮을수록 높았으며, 식품섭취 빈도 점수는 비만군에서 높았으나, 저녁식사 후 간식섭취는 BMI가 높은 군에서 하지 않는 비율이 더 높았는데 이것은 감수성이 예민한 여학생들이 자신의 외모에 대한 의식적인 노력으로 보인다. 이상과 같은 결과를 종합해 볼 때 중학교 여학생들은 학교수업을 중심으로 비교적 규칙적인 생활을 하고 따로 운동을 할 시간이 많지 않은 것으로 나타났다. 비만과 관련하여서는 유전적인 요인도 중요하지만 식습관 개선과 식품이 적절한 선택 등을 강조하여 연령과 생활환경에 맞는 영양교육이 필요하다고 본다.알 수 있으며, 현미 30% 첨가한 B2가 그 다음 순위로 선호되어, 백설기 제조에서 율무와 현미의 첨가량은 10%가 권장된다.농촌 지역 여고생보다 많이 섭취하였고, 탄수화물은 농촌지역 여고생이 대도시 지역 여고생에 비하여 유의적으로 많이 섭취하였다. 지역별 여고생의 에너지섭취 비율은 탄수화물 : 단백질 : 지방의 섭취 비율이 대도시 60.75% : 16.4% 22.9%이며, 중소도시가 62.7% : 15.7% : 21.5%,농촌이66.8% : 14. l% : 19.1%이었다. 영양지식의 정확도나 인지도는 영양소 섭취와 유의적인

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.31 no.2
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• pp.203-221
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• 2020

This study closely analyzed changes in the educational environment and changes in the needs of children's and young people's reading culture programs, which are directly beneficiaries of the promotion of reading culture as they enter the fourth industrial revolution. It also comprehensively evaluated the reading culture promotion project for children and adolescents promoted by the National Children and Youth Library and proposed a reading culture promotion project that meets the needs of the smart era. This study investigated the cases of various domestic and foreign reading culture promotion projects to divulge trends. The authors invited experts from public libraries and school libraries with experience of the reading culture promotion projects and performed Focus Group Interviews (FGI). The authors evaluated individual reading culture program based on the PDCA method (Plan, Do, Check, Act). Based on the data obtained through case studies and expert evaluations, the development plan of reading culture promotion project and the strategy of promoting new projects to be pursued in the National Children and Youth Library were presented. By gathering the results of the research, 'Interactive e-book making platform production / distribution business', 'Game-type reading program production / distribution business', 'Habruta reading culture dissemination project using backward learning method', 'Youth coding branding "Teen-Start -Up"' were proposed as new services.

• Journal of Gifted/Talented Education
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• v.20 no.3
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• pp.901-919
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• 2010

We have examined the perception and the knowledge of science-gifted students and general students in middle school level about high technology related to the science. The subjects of the investigation were 113 gifted students belonging to the universities' science-gifted education center in Busan or Ulsan, and 159 general students belonging to 2 middle schools in Busan. The survey was conducted with questionnaires on the perceptions concerning the high technology related to the science and the knowledge of a cellular phone without an antenna, and an LED(Light Emission Diode). The results of this survey concluded that the gifted students were more interested and aware of the high technology than the general students, these results are statistically significant. It has been found that there are significant differences between the gifted students and the general students in terms of the areas they want to learn, the source of information and the preferred learning method in advanced science and technology. Also, the gifted students were recognized to be better than general students in understanding an electromagnetic wave related to a cellular phone without an antenna, and a semiconductor connection with an LED.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.2
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• pp.95-111
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• 2021

As the population decreases in an aging society, the average age of drivers increases. Accordingly, the elderly at high risk of being in an accident need autonomous-driving vehicles. In order to secure driving safety on the road, several technologies to respond to various obstacles are required in those vehicles. Among them, technology is required to recognize static obstacles, such as poor road conditions, as well as dynamic obstacles, such as vehicles, bicycles, and people, that may be encountered while driving. In this study, we propose a deep neural network algorithm capable of simultaneously detecting these two types of obstacle. For this algorithm, we used 1,418 road images and produced annotation data that marks seven categories of dynamic obstacles and labels images to indicate road damage. As a result of training, dynamic obstacles were detected with an average accuracy of 46.22%, and road surface damage was detected with a mean intersection over union of 74.71%. In addition, the average elapsed time required to process a single image is 89ms, and this algorithm is suitable for personal mobility vehicles that are slower than ordinary vehicles. In the future, it is expected that driving safety with personal mobility vehicles will be improved by utilizing technology that detects road obstacles.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.1
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• pp.85-95
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• 2019

Recently, studies on the fourth industrial revolution have been actively conducted in the areas of government, business, and academia. Corporate business models that utilize the major agendas of the fourth industrial revolution such as robots, artificial intelligence, Internet of things (IoT), and block chains have been created, and various changes have occurred in not only business, education, and living environments but also in international relations. In this study, we looked at changes in social contribution activities from the perspective of a company facing impacts of the fourth industrial revolution. This study examines the definition and activities of corporate social contribution and how we can contribute to society through corporate activities. 'AT Educom', LG Uplus 'Social Contribution through IoT', KT's anti-infectious disease prevention platform and cases of Intel using IoT. In addition, we have presented what we need to do in the future to promote corporate social contribution activities that will make more meaningful impacts on how corporate social contribution activities will change according to technology development. The first, measuring the performance of corporate social contribution activities needs a standardized methodology and social contribution activities through platform business and ICT should be actively pursued. Lastly, social contribution activities between companies and sectors will increase.

• Journal of the Korea Convergence Society
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• v.10 no.4
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• pp.1-6
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• 2019

Neural networks have been used to predict the direction of stock index movement from past data. The conventional research that predicts the upward or downward movement of the stock index predicts a rise or fall even with small changes in the index. It is highly likely that losses will occur when trading ETFs by use of the prediction. In this paper, a neural network model that predicts the movement direction of the daily KOrea composite Stock Price Index (KOSPI) to reduce ETF trading losses and earn more than a certain amount per trading is presented. The proposed model has outputs that represent rising (change rate in index ${\geq}{\alpha}$), falling (change rate ${\leq}-{\alpha}$) and neutral ($-{\alpha}$ change rate < ${\alpha}$). If the forecast is rising, buy the Leveraged Exchange Traded Fund (ETF); if it is falling, buy the inverse ETF. The hit ratio (HR) of PNN1 implemented in this paper is 0.720 and 0.616 in the learning and the evaluation respectively. ETF trading yields a yield of 8.386 to 16.324 %. The proposed models show the better ETF trading success rate and yield than the neural network models predicting KOSPI.

• Science of Emotion and Sensibility
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• v.24 no.2
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• pp.39-48
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• 2021

According to International Associating for the Study of Pain (IASP) definition, neuropathic pain is a disorder characterized by dysfunction of the nervous system that, under normal conditions, mediates virulent information to the central nervous system (CNS). This pain can be divided into a disease with provable lesions in the peripheral or central nervous system and states with an incorporeal lesion of any nerves. Both conditions undergo long-term and chronic processes of change, which can eventually develop into chronic pain syndrome, that is, nervous system is inappropriately adapted and difficult to heal. However, the treatment of neuropathic pain itself is incurable from diagnosis to treatment process, and there is still a lack of notable solutions. Recently, several studies have observed the responses of CNS to harmful stimuli using image analysis technologies, such as functional magnetic resonance imaging (fMRI), positron emission tomography (PET), and optical imaging. These techniques have confirmed that the change in synaptic-plasticity was generated in brain regions which perceive and handle pain information. Furthermore, these techniques helped in understanding the interaction of learning mechanisms and chronic pain, including neuropathic pain. The study aims to describe recent findings that revealed the mechanisms of pathological pain and the structural and functional changes in the brain. Reflecting on the definition of chronic pain and inspecting the latest reports will help develop approaches to alleviate pain.

• Journal of the Korean Chemical Society
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• v.64 no.6
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• pp.379-388
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• 2020

The purpose of this study are to develop the TEP activity for learning experimental apparatus at elementary school and to test the effects of the TEP activity. This study consists of two steps. First through literature research on the difficulties and needs of experimental apparatus education developed the form that how to educate the experimental apparatus at elementary school. Second, applied the TEP activity and figured out the effects as two aspect(knowledge about experimental apparatus and actual using skill during lesson). This worksheet was applied to 3rd grade students in elementary school about 4 experimental apparatuses(Beaker, Electronic scale, Glass rod, Spatula). The results of this study are as follows: There is no specific time to teach what is and how to use experimental apparatus by regular curriculum. So many students and teachers need method and time to learn them. Also they want to lots of opportunities to use them. With that needs given previously, TEP activity developed by 3 steps. 1. Trigger interest 2. Explore experimental apparatus: learned knowledges about experimental apparatus focused on appearance(name, purpose, directions for use, precautions) 3. Practice experimental apparatus: actual using time to acquire skills. After that did the survey of knowledge and observation of students' behavior during usual class to confirm the effects. According to the results, TEP activity helped the students to improve there awareness of the experimental apparatus and actual using skills.

• The Journal of the Acoustical Society of Korea
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• v.40 no.1
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• pp.18-30
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• 2021

The ultimate goal of the present study is to establish the acoustical performance standards of classroom for the elderly who are incomplete hearing people. As a pilot survey, the present study was conducted to investigate the listening environment and the actual condition of speech perception performance of education facilities for elderly, Acoustic performances of two education facilities for elderly in Cheongju were measured and questionnaire survey was done to elderly people. Also, speech intelligibility tests were undertaken by Consonant Vowel Consonant (CVC) and Phonetically Balanced Words (PBW) methods. The questionnaire survey showed that the elderly were satisfied with the listening environment of the educational facilities in general. Also, it was found that acoustical performances satisfy with the acoustic criteria of general classrooms in Korea. However, the results of the speech intelligibility test showed that the scores of elderly were significantly lower than twenties with normal hearing. It was also revealed that the scores are reduced as the age increases. Thus, it was concluded that the acoustical performance standards of educational facilities for the normal hearing were not suitable for educational facilities for the elderly.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.12
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• pp.291-306
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• 2020

Nowadays, Data-Network-AI (DNA)-based intelligent services and applications have become a reality to provide a new dimension of services that improve the quality of life and productivity of businesses. Artificial intelligence (AI) can enhance the value of IoT data (data collected by IoT devices). The internet of things (IoT) promotes the learning and intelligence capability of AI. To extract insights from massive volume IoT data in real-time using deep learning, processing capability needs to happen in the IoT end devices where data is generated. However, deep learning requires a significant number of computational resources that may not be available at the IoT end devices. Such problems have been addressed by transporting bulks of data from the IoT end devices to the cloud datacenters for processing. But transferring IoT big data to the cloud incurs prohibitively high transmission delay and privacy issues which are a major concern. Edge computing, where distributed computing nodes are placed close to the IoT end devices, is a viable solution to meet the high computation and low-latency requirements and to preserve the privacy of users. This paper provides a comprehensive review of the current state of leveraging deep learning within edge computing to unleash the potential of IoT big data generated from IoT end devices. We believe that the revision will have a contribution to the development of DNA-based intelligent services and applications. It describes the different distributed training and inference architectures of deep learning models across multiple nodes of the edge computing platform. It also provides the different privacy-preserving approaches of deep learning on the edge computing environment and the various application domains where deep learning on the network edge can be useful. Finally, it discusses open issues and challenges leveraging deep learning within edge computing.