• Hwankyungkyoyuk
• /
• v.20 no.1
• /
• pp.19-27
• /
• 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'.

• Journal of the Korea Society of Computer and Information
• /
• v.14 no.12
• /
• pp.55-62
• /
• 2009

This paper proposes a decision method of fuzzy weights by utilizing degrees of contribution in order to classify insect footprint patterns having difficulties to classify species clearly. Insect footprints revealed delicately in the form of scattered spots since they are very small. Therefore it is not easy to define shape of footprints unlike other species, and there are lots of noises in the footprint patterns so that it is difficult to distinguish those from correct data. For these reasons, the extracted feature set has obvious feature values with some uncertain feature values, so we estimate weights according to degrees of contribution. If the one of feature values has distinct difference enough to decide a class among other classes, high weight is assigned to make classification. A calculated weight determines the membership values by fuzzy functions and objects are classified into the class having a superior value.atu present experimental resultseighrontribution. Iinsect footprints with noises by the proposed method.

• International conference on construction engineering and project management
• /
• 2020.12a
• /
• pp.157-166
• /
• 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.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.40 no.5
• /
• pp.535-546
• /
• 2020

Land cover maps are derived from satellite and aerial images by the Ministry of Environment for the entire Korea since 1998. Even with their wide application in many sectors, their usage in research community is limited. The main reason for this is the map compilation cycle varies too much over the different regions. The situation requires us a new and quicker methodology for generating land cover maps. This study was conducted to automatically generate land cover map using aerial ortho-images and Landsat 8 satellite images. The input aerial and Landsat 8 image data were trained by Residual U-Net, one of the deep learning-based segmentation techniques. Study was carried out by dividing three groups. First and second group include part of level-II (medium) categories and third uses group level-III (large) classification category defined in land cover map. In the first group, the results using all 7 classes showed 86.6 % of classification accuracy The other two groups, which include level-II class, showed 71 % of classification accuracy. Based on the results of the study, the deep learning-based research for generating automatic level-III classification was presented.

• Journal of Cadastre & Land InformatiX
• /
• v.50 no.1
• /
• pp.75-85
• /
• 2020

This study examines machine learning cross-validation to utilized create ROI for classification of land cover. The study area located in Sejong and one KOMPSAT-3A image was used in this analysis: procedure on October 28, 2019. We used four bands(Red, Green, Blue, Near infra-red) for learning cross validation process. In this study, we used K-fold method in cross validation and used SVM kernel type with cross validation result. In addition, we used 4 kernels of SVM(Linear, Polynomial, RBF, Sigmoid) for supervised classification land cover map using extracted ROI. During the cross validation process, 1,813 data extracted from 3,500 data, and the most of the building, road and grass class data were removed about 60% during cross validation process. Based on this, the supervised SVM linear technique showed the highest classification accuracy of 91.77% compared to other kernel methods. The grass' producer accuracy showed 79.43% and identified a large mis-classification in forests. Depending on the results of the study, extraction ROI using cross validation may be effective in forest, water and agriculture areas, but it is deemed necessary to improve the distinction of built-up, grass and bare-soil area.

• Advances in pediatric surgery
• /
• v.1 no.2
• /
• pp.140-148
• /
• 1995

To study the clinical profiles and outcome of surgery in infants with esophageal atresia, we reviewed 96 esophageal atresia cases who were treated from April, 1978 to June, 1995. There were 51 male and 45 female infants, a ratio of 1.1:1. The low birth weight(<2500g) patients were 32%. Clinical findings at the time of diagnosis included drooling in 57%, choking in 50%, cyanosis in 38%, respiratory distress in 27% and swallowing difficulty in 20%. Gross classification included 6 cases of type A esophageal atresia(6%), 79 cases of type C(82%), 3 cases of type E (3%) and 8 cases of type F(8%). Associated anomalies occurred in 34 infants(35%). Among them, cardiac anomalies were most common(60%). A primary repair of the defect was carried out in 76 patients with type A or C. A staged operation comprising a repair or gastric tube interposition after gastrostomy was performed in 8 patients. In all 3 infants with H-type, a division of fistula was performed. Esophageal resection and anastomosis was done in 8 infants with esophageal stenosis. In one infant, a gastrostomy was performed and he expired before staged operation. Anastomotic complications included leakage in 16 cases(17%), stricture in 37 cases(39%) and recurrent tracheoesopohageal fistula in 3 cases(3%). The mortality rate was 14% and the leading cause of death was pneumonia. The overall survival rate was 86%, and according to Waterston criteria, the survival rates were 93%, 85% and 58% in class A, Band C, respectively. 75 patients were followed up with median follow up 6.4 years. Among them, 93% were uneventful and 7% had frequent pneumonia.

• Journal of Acupuncture Research
• /
• v.32 no.4
• /
• pp.91-102
• /
• 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.

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.11 no.5
• /
• pp.38-59
• /
• 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.

• Journal of Environmental Science International
• /
• v.17 no.6
• /
• pp.679-687
• /
• 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
• /
• 2004.08a
• /
• pp.663-667
• /
• 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.