• Korean Journal of Remote Sensing
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• v.33 no.1
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• pp.79-88
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• 2017

The RapidEye satellite sensor has various spectral wavelength bands, and it can capture large areas with high temporal resolution. Therefore, it affords advantages in generating various types of thematic maps, including land cover maps. In this study, we applied a supervised classification scheme to generate high-resolution land cover maps using RapidEye images. To improve the classification accuracy, object-based classification was performed by adding brightness, yellowness, and greenness bands by Tasseled Cap Transformation (TCT) and Normalized Difference Water Index (NDWI) bands. It was experimentally confirmed that the classification results obtained by adding TCT and NDWI bands as input data showed high classification accuracy compared with the land cover map generated using the original RapidEye images.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_2
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• pp.521-527
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• 2013

Rule set is an important step which impacts significantly on accuracy of object-oriented classification result. Therefore, this paper proposes a rule set to extract land cover from Landsat Thematic Mapper (TM) imagery acquired in Donganh, Hanoi, Vietnam. The rules were generated to distinguish five classes, namely river, pond, residential areas, vegetation and paddy. These classes were classified not only based on spectral characteristics of features, but also indices of water, soil, vegetation, and urban. The study selected five indices, including largest difference index max.diff; length/width; hue, saturation and intensity (HSI); normalized difference vegetation index (NDVI) and ratio vegetation index (RVI) based on membership functions of objects. Overall accuracy of classification result is 0.84% as the rule set is used in classification process.

• Journal of Oriental Neuropsychiatry
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• v.20 no.1
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• pp.107-118
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• 2009

Objectives : One's mind turned over by environment and personal relationship is Emotion. Emotion is composed by several basic feelings. This basic feeling is called Chiljung in Oriental Medicine. This study is confirmed difference of Chiljung by Constitution. Methods : 80 persons of Oriental medicine university students were tested by Qustionnaire for the Sasang Constitution Classification II(QSCCII) and Thematic Apperception Test(TAT). Constitution is distinguished by QSCCII. 11 pieces picture of TAT were showed one minute and then had person to discribe one's feelings. Two data were analyzed by statistical analysis. Results : Result is as follows, tested TAT about expression of inherent basic emotion. 1. It has relations with cognitive thought process 2. Expression of Chiljung has some relations with constitution and personal trait. Conclusion : Chiljung of inherent basic emotion is cognitive and has difference between constitutions by TAT.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.3
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• pp.163-170
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• 2001

The objective of this study was to evaluate land cover classification of PyeongTaeg area by Landsat Thematic Mapper Data June, 1997. This study was also to make more correct reference data using DGPS, aerophoto, and topographical chart etc.. The result of the area of paddy and upland were estimated 4,949 $\textrm{km}^2$ and 16,157 $\textrm{km}^2$, respectively. Correctness of estimation by using DGPS, aerophoto, topographical chart were shown over 90% correct in case of rice paddy field, water, and sea, while upland, vinyl house, forest, grassland, village were shown low correctness. Total average accuracy was shown to be 85.8%. Correctness of paddy field showed high value of 92%, showing that use of remote sensing data was proved to be effective methods to estimate spatial distribution and cultivation status of paddy field. Classification result of sea, water area, downtown had higher correctness, while upland, vinyl-house, grassland were proved to be relatively low correctness because of it's small area and mixed distribution.

• Korean Journal of Remote Sensing
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• v.16 no.4
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• pp.367-373
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• 2000

Natural and artificial land features are very dynamic, changing somewhat repidly in our lifetime. It is important that such changes are inventoried accurately so that the physical and human processes at work can be more fully understood. Change detection is a technique used to determine the change between two or more time periods of a particular object of study. Change detection is an important process in monitoring and managing natural resources and urban development because it provides quantitative analysis of the spatial distribution in the population of interest. The purpose of this research is to detect environmental changes surrounding an area of Mountain Moscow, Idaho using Landsat Thematic Maper (TM) images of (July 8, 1990 and July 20, 1991). For accurate classification, the Image enhancement process was performed for improving the image quality of each image. A SPOT image (Aug. 14, 1992) was used for image merging in this research. Supervised classification was performed using the maximum likelihood method. Accuracy assessments were done for each classification. Two images were compared on a pixel-by-pixel basis using the post-classification comparison method that is used for detecting the changes of the study area in this research. The 'from-to' change class information can be detected by post classification comparison using this method and we could find which class change to another.

• Journal of the korean academy of Pediatric Dentistry
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• v.29 no.2
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• pp.270-277
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• 2002

Since founded in 1959, it's well known that the KAPD has pioneered in the researches and clinical aspects of pediatric dentistry in Korea. It's official journal, the Journal of the KAPD, was first published in 1974 and has pressed total 956 articles up to now(March, 2001). In this study, all the articles pressed in this journal have been surveyed, focussing in their main theme, their chronological and thematic distribution. The thematic classification was made with the reference of the previous studies and renowned textbooks in pediatric dentistry. And we obtained the results as follows: 1. The researches on dental materials and dental equipments have shown continuous increase throughout the period. 2. The researches on dental caries, caries prevention and systemic disorders have occupied relatively high proportion consistently. 3. The researches on malocclusions and cysts/minor surgery have shown increasing tendency in the second period, but are decreasing in the third period. 4. The researches on craniofacial growth/development, tooth development/eruption, developmental disorders of teeth, management of eruption space have shown decreasing tendency. 5. The researches on behavioral research, oral habits, occlusion of primary-mixed dentition have shown very low proportion, reaching no more than 1% throughout the period.

• The Journal of Information Systems
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• v.23 no.3
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• pp.127-142
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• 2014

Plagiarism occurs when the content is copied without permission or citation, and the problem of plagiarism has rapidly increased because of the digital era of resources available on the World Wide Web. An important task in plagiarism detection is measuring and determining similar text portions between a given pair of documents. One of the main difficulties of this task is that not all similar text fragments are examples of plagiarism, since thematic coincidences also tend to produce portions of similar text. In order to handle this problem, this paper proposed association analysis in data mining to detect plagiarism. This method is able to detect common actions performed by plagiarists such as word deletion, insertion and transposition, allowing to obtain plausible portions of plagiarized text. Experimental results employing an unsupervised document classification strategy showed that the proposed method outperformed traditionally used approaches.

• International Journal of Contents
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• v.1 no.2
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• pp.26-30
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• 2005

According to the fast growth of information on the Internet, it is becoming increasingly difficult to find and organize useful information. To reduce information overload, it needs to exploit automatic text classification for handling enormous documents. Support Vector Machine (SVM) is a model that is calculated as a weighted sum of kernel function outputs. This paper describes a document classifier for web documents in the fields of Information Technology and uses SVM to learn a model, which is constructed from the training sets and its representative terms. The basic idea is to exploit the representative terms meaning distribution in coherent thematic texts of each category by simple statistics methods. Vector-space model is applied to represent documents in the categories by using feature selection scheme based on TFiDF. We apply a category factor which represents effects in category of any term to the feature selection. Experiments show the results of categorization and the correlation of vector length.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.19 no.2
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• pp.163-172
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• 2001

This study present the quadratic programming as the classification method of remote sensed data applying to the extraction of landcover and examine it's applicable capability by comparing the classification accuracy of quadratic programming with that of neural network and maximum likelihood method which are used in the extraction of thematic layer. As the results, as drawing the more improved classification results by 6% than maximum likelihood method, we could discern that the method of quadratic programming is appliable to classifying the remote sensed data. Also, in the classification of quadratic programming method, we could definitely indicate the results which was ignored in the previous extreme(binary) classification method by affecting the class decision with the class composition proportion.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.1
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• pp.105-113
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• 2011

Since existing thematic maps have been made with medium- to low-resolution satellite images, they have several shortcomings including low positional accuracy and low precision of presented thematic information. Digital aerial photo image taken recently can express panchromatic and color bands as well as NIR (Near Infrared) bands which can be used in interpreting forest areas. High resolution images are also available, so it would be possible to conduct precision land cover classification. In this context, this paper implemented object-based land cover classification by using digital aerial photos with 0.12m GSD (Ground Sample Distance) resolution and IKONOS satellite images with 1m GSD resolution, both of which were taken on the same area, and also executed qualitative analysis with ortho images and existing land cover maps to check the possibility of object-based land cover classification using digital aerial photos and to present usability of digital aerial photos. Also, the accuracy of such classification was analyzed by generating TTA(Training and Test Area) masks and also analyzed their accuracy through comparison of classified areas using screen digitizing. The result showed that it was possible to make a land cover map with digital aerial photos, which allows more detailed classification compared to satellite images.