• 한국환경교육학회지:환경교육
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• 제20권1호
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• pp.19-27
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• 2007

This study was intended to answer the question, 'What kinds of effects will be aroused by experiential learning for environment based on living area?'. Experiential learning for environment was operated to 17 elementary school students in 4th grade in Kyeong-san city. The results were drawn analyzing the mind map for the changes of environmental consciousness before and after learning, and they are as below. First, it had an effect to change the meaning association of the relationship between 'river and me'. Meaning association was 'river-a thing' before experiential learning, but it was developed as 'river-a thing-me' after learning. This means that students expanded understanding of the world that they were belonging and self-spatialization was promoted. The expansion of meaning association would be a start point and a method to promote their segmentation for each student. Second, students could self-directly modify misconception and preconception after experiential learning. It showed that students could find meanings in the world that they were belonging by experiential learning for environment, and misconception obtained by concept learning without actual situation could be revised through the truth recognition in meanings, and student could see what things displayed. Therefore preconception would be corrected. Of course, everything would not be completed by just one time of experiential learning, and consistent experience learning should be operated. Third, experiential learning promoted the change of sensitivity. Students had shallow sensitivity, which appeared in the relation with things, since having learned only inside of class without a direct observation. However their sensitivity could be increased by experiencing specific things. Fourth, there was the change of classification recognition. Students found properties of things with a direct observation. It raised their ability to classify things, and to understand an individual thing in 'a class'.

• 한국컴퓨터정보학회논문지
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• 제14권12호
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• pp.55-62
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• 2009

이 논문에서는 개체를 명확하게 분류하기 어려운 곤충 발자국 영상으로부터 개체를 인식하기 위해서 추출된 특징값 성분들의 기여도를 측정하고, 서로 관계된 기여도에 따라 가중치를 조정하는 퍼지 가중치 결정 방법을 제안한다. 곤충은 몸의 크기가 작아서 발자국은 작은 점의 형태로 나타난다. 그리고 다른 생물체의 발자국과 달리, 규칙적인 형상을 정의하기 어렵고 발자국 데이터와 구분이 분명하지 않는 노이즈와 혼재하기 때문에 개체를 판단하는데 많은 어려움이 있다. 이런 이유로 추출된 곤충 발자국 특징값은 명확하게 구분되는 특징성분 영역과 그렇지 않는 성분을 함께 가지게 된다. 이중 어떤 성분이 다른 성분과 비교하여 다른 클래스와 구분하기에 충분한 변별력을 가질 경우, 개체를 분류하도록 높은 가중치를 할당한다. 산출된 가중치는 퍼지함수에 의해서 출력신호를 결정하고 우세한 출력신호에 의해서 개체를 판단할수 있다. 제안한 기여도 퍼지 가중치 결정 방법을 이용하여 발자국영상의 인식 실험을 수행하고 실험 결과를 제시하였다.

• 국제학술발표논문집
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• The 8th International Conference on Construction Engineering and Project Management
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• pp.157-166
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• 2020

Automated rebar fabrication, which requires effective information exchange between model designers and fabricators, has brought the integration and interoperability of data from different sources to the notice of both academics and industry practitioners. Industry Foundation Classes (IFC) was one of the most commonly used data formats to represent the semantic information of prefabricated components in buildings, whereas the data format utilized by rebar fabrication machine is BundesVereinigung der Bausoftware (BVBS), which is a numerical data structure exchanging reinforcement information through ASCII encoded files. Seamless transformation between IFC and BVBS empowers the automated rebar fabrication and improve the construction productivity. In order to improve data interoperability between IFC and BVBS, this study presents an IFC extension based on the attributes required by automated rebar fabrication machines with the help of Information Delivery Manual (IDM) and Model View Definition (MVD). IDM is applied to describe and display the information needed for the design, construction and operation of projects, whereas MVD is a subset of IFC schema used to describe the automated rebar fabrication workflow. Firstly, with a rich pool of vocabularies practitioners, OmniClass is used in information exchange between IFC and BVBS, providing a hierarchy classification structure for reinforcing elements. Then, using International Framework for Dictionaries (IFD), the usage of each attribute is defined in a more consistent manner to assist the data mapping process. Besides, in order to address missing information within automated fabrication process, a schematic data mapping diagram has been made to deliver IFC information from BIM models to BVBS format for better data interoperability among different software agents. A case study based on the data mapping will be presented to demonstrate the proposed IFC extension and how it could assist/facilitate the information management.

• 대한토목학회논문집
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• 제40권5호
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• pp.535-546
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• 2020

환경부에서는 위성영상과 항공영상을 이용하여 토지피복지도를 1998년부터 제작하여 배포하고 있으나, 권역별 제작 주기가 달라 활용성이 저하된다. 이에, 본 연구에서는 항공정사영상과 Landsat 8 위성영상을 이용하여, 토지피복지도를 자동으로 생성하기 위한 연구를 수행하였다. 토지피복지도를 자동적으로 제작하기 위하여 딥러닝 기반 세그먼테이션 방법의 하나인 Residual U-Net을 활용하였다. 토지피복지도의 제작 시기와 가장 근접한 시기의 항공 및 위성영상을 신경망을 통하여 학습하고, 학습결과를 3가지 실험군으로 나누어 토지피복지도와 비교하여 정확도 평가를 수행하였다. 첫 번째 군으로 대분류 7개 전체를 활용한 결과의 경우, 선행연구에서 대분류 4개에만 적용된 결과보다도 향상된 86.6 %의 분류 정확도를 나타내었다. 중분류를 일부 포함한 2개의 실험군의 경우에는 71 %의 정확도를 나타내었다. 본 연구 결과를 바탕으로 신경망을 활용한 대분류 항목에 대한 자동 분류 가능성을 제시하였으며, 중분류 및 세분류에 대한 기초연구로 활용이 가능할 것으로 판단된다.

• 지적과 국토정보
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• 제50권1호
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• pp.75-85
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• 2020

본 연구는 토지피복 분류에 사용 가능한 ROI 생성 과정에서 기계학습 기반 교차검증을 활용하였다. 연구지역은 세종시를 포함한 2019년 10월 28일 단시기 KOMPSAT-3A 영상을 활용하였다. 연구 과정에서 4개의 밴드(Red, Green, Blue, Near Infra-red)를 독립변수로 교차검증 과정에서 학습시켰다. 또한 SVM의 4가지 기법(Linear, Polynomial, RBF, Sigmoid)을 활용하여 추출된 ROI를 기반으로 토지피복 분류를 실시하였다. 교차검증 과정에서 훈련된 3,500개의 데이터 중 1,813개의 데이터가 추출되었으며 건물, 도로, 그리고 초지에서 약 60%의 데이터가 제거되었다. 추출된 ROI를 기반으로 다른 SVM기법에 비해 SVM Linear 기법이 91.77%로 가장 높은 분류 정확도를 나타냈다. 분류 클래스 중 초지의 경우 산림과의 오분류가 가장 많이 발생하며 79.43%의 생산자 정확도로 가장 낮은 분류 정확도를 보여주었다. 연구 결과에 따라 교차검증에서 추출된 ROI는 산림, 수역, 그리고 농업지역에 대해서는 90%이상의 분류정확도를 보여주며 효과적인 분류결과를 도출할 수 있었으나, 80%의 분류정확도를 보여주는 건물, 도로, 나대지, 그리고 초지 지역을 분류하는 방법에 대해서는 추가적인 연구가 진행되어야 할 필요성이 존재한다.

• Advances in pediatric surgery
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• 제1권2호
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• pp.140-148
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• 1995

저자들은 96예의 선천성 식도 폐쇄를 분석하여 다음의 결과를 얻었다. 1) 남녀비는 1.1:1로 비슷하였다. 2) 출생시 평균 체중은 2.8kg 였고 2.5kg 미만의 저출생 체중아가 32.3%를 차지했다. 3) 주증상은 타액 분비 과다, 수유시 호흡 곤란, 청색증 등이었다. 4) Gross 분류법에 의한 해부학적 유형은 Type C가 가장 많은 빈도로 관찰되었다(82.3%). 5) 동반 선천성 기형이 35%에서 관찰되었고 이 중 심장 기형이 가장 많은 빈도로 관찰되었다(60%). 6) 수술은 Type A, C의 경우 일차적 문합을 시행하였고 일차적 문합이 불가능한 원간격 결손 환아에서 역위관 삽입술이 시행되었다. Type E(H-type)의 경우 식도기관루 절제술이, Type F의 경우 식도협착부위 절제 및 단단 문합술이 시행되었다. 7) 수술후 주요 합병증은 문합부 누출, 문합부 협착, 기관 식도루 재발 등이었다. 8) 생존율은 86%였고 Waterston Criteria에 따른 생존율은 Class A, 93%, Class B, 86%, Class, 58%였다. 9) 추적 조사 결과 93%의 환아가 건강했고 7%의 환아가 잦은 호흡기 감염으로 입원한 병력이 있었다.

• Journal of Acupuncture Research
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• 제32권4호
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• pp.91-102
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• 2015

Objectives : The Oriental medical device industry is expected to continue to experience significant growth. It should increase its global market share rather than focusing on the domestic market. Countries around the world self-regulate their domestic market, so this study aims to aid in the development of a particular overseas market by introducing the U.S.(the largest market) medical device registration and approval process. Methods : For an understanding of the US medical device licensing process, we researched the relevant regulatory organization (FDA), the history, definition and classification of medical devices, the approval and 510(k) submission process related to substantial equivalence, IEC 60601-1 Edition 3, usability tests, and so on. Results : Medical devices in the United States are assigned to one of three regulatory classes: Class I, Class II and Class III, based on the level of control necessary to assure the safety and effectiveness of the device. If a company's device is classified as Class II and if it is not exempt, a 510k will be required for marketing. 1) A 510(k) is a premarket submission made to the FDA to demonstrate that the new device to be marketed is "substantially equivalent" to a legally marketed device (predicate device) 2) The IEC 60601-1 Edition 3 preparation process, which contains information related to usability, is expensive and time-consuming but a critical requirement. Conclusions : Although the U.S. market has high barriers to entry, access to this, large overseas market will encourage development of the Oriental medical device industry and commercial value enhancement is expected.

• 한국환경복원기술학회지
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• 제11권5호
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• pp.38-59
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• 2008

This research has a meaning to provide basic data for eco-friendly way of district unit plans and ecological landscape planning by evaluation of biotope preservation value at the level of district unit and designating land development of the site, the whole area of Sinseo-dong (Dong-gu, Daegu metropolitan city) for research site. The summary of analysis result is as follows. As a result of classification of biotope types on the research site, it is divided into 11 biotope groups such as a residential biotope group and 51 specific biotope types which is subordinate to the groups. As a result of the first value assessment on classified biotope types, there are 16 types of natural rivers which is full of vegetation as a I class. Also it is analysed as 9 types of IIclass, 14 of IIIclass, 8 of IVclass, and 4 of Vclass. In particular, in light of a wildlife habitat, EB, in case of broad-leaved tree of mixed forest assessed as a II class, was classified into Iclass which is one-step upgraded as a final class with the analysis as there is a structural characteristic (more than 71% of low density, 50 years of age-class). As a result of second assessment, it is analysed that there are 17 special sites (1a,1b) and 33 special sites (2a, 2b, 2c) respectively for preservation of species and biotope. Particularly, in case of the No. 27 space, it was assessed that it has the value of about medium (IIIclass) level, but its value was upgraded with the on-spot detailed investigation that most of Aristolochia contorta, designated as a rare plant by Ministry of Environment, is growing. It is regarded that the above-mentioned research result on evaluation of biotope preservation value is expected to provide very important basic materials for future district unit plans and smooth integration with landscape ecology plans and eco-friendly space development.

• 한국환경과학회지
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• 제17권6호
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• pp.679-687
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• 2008

In this study, we implemented landslide distribution of Jeju Island using ANN and GIS, respectively. To do this, we first get the counter line from 1:2,5000 digital map and use this counter line to make the DEM. for the evaluate the land slide susceptibility. Next, we abstracted slop map and aspect map from the DEM and get the land use map using ISODATA classification method from Landsat 7 images. In the computation processes of landslide analysis, we make the class to the soil map, tree diameter map, Isohyet map, geological map and so on. Finally, we applied the ANN method to the landslide one and calculated its weighted values. GIS results can be calculated by using Acrview program and produced Jeju landslide susceptibility map by usign Weighted Overlay method. Based on our results, we found the relatively weak points of landslide ware concentrated to the top of Halla mountains.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.663-667
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• 2004

This paper presents new pruning and learning methods for the fuzzy rule-based classifier. The structure of the proposed classifier is framed from the fuzzy sets in the premise part of the rule and the Bayesian classifier in the consequent part. For the simplicity of the model structure, the unnecessary features for each fuzzy rule are eliminated through the iterative pruning algorithm. The quality of the feature is measured by the proposed correctness method, which is defined as the ratio of the fuzzy values for a set of the feature values on the decision region to one for all feature values. For the improvement of the classification performance, the parameters of the proposed classifier are finely adjusted by using the gradient descent method so that the misclassified feature vectors are correctly re-categorized. The cost function is determined as the squared-error between the classifier output for the correct class and the sum of the maximum output for the rest and a positive scalar. Then, the learning rules are derived from forming the gradient. Finally, the fuzzy rule-based classifier is tested on two data sets and is found to demonstrate an excellent performance.