• Korean Journal of Remote Sensing
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• v.29 no.5
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• pp.537-544
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• 2013

Baton Peninsula, where Sejong station is located, mainly covered with snow and vegetation. Because this area is sensitive to climate change, monitoring of surface variation is important to understand climate change on the polar region. Due to the inaccessibility, the remote sensing is useful to continuously monitor the area. The objectives of this research are 1) map classification of land-cover types in the Barton Peninsular around King Sejong station and 2) grasp distribution of vegetation species in classified area. A KOMPSAT-2 multispectral satellite image was used to classify land-cover types and vegetation species. We performed classification with hierarchical procedure using KOMPSAT-2 satellite image and ground reference data, and the result is evaluated for accuracy as well. As the results, vegetation and non-vegetation were clearly classified although species shown lower accuracies within vegetation class.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.438-441
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• 2007

Recently, due to molecular biology and engineering technology, DNA microarray makes people watch thousands of genes and the state of variation from the tissue samples of living body. With DNA Microarray, it is possible to construct a genetic group that has similar expression patterns and grasp the progress and variation of gene. This paper practices Cluster Analysis which purposes the discovery of biological subgroup or class by using gene expression information. Hence, the purpose of this paper is to predict a new class which is unknown, open leukaemia data are used for the experiment, and MCL (Markov CLustering) algorithm is applied as an analysis method. The MCL algorithm is based on probability and graph flow theory. MCL simulates random walks on a graph using Markov matrices to determine the transition probabilities among nodes of the graph. If you look at closely to the method, first, MCL algorithm should be applied after getting the distance by using Euclidean distance, then inflation and diagonal factors which are tuning modulus should be tuned, and finally the threshold using the average of each column should be gotten to distinguish one class from another class. Our method has improved the accuracy through using the threshold, namely the average of each column. Our experimental result shows about 70% of accuracy in average compared to the class that is known before. Also, for the comparison evaluation to other algorithm, the proposed method compared to and analyzed SOM (Self-Organizing Map) clustering algorithm which is divided into neural network and hierarchical clustering. The method shows the better result when compared to hierarchical clustering. In further study, it should be studied whether there will be a similar result when the parameter of inflation gotten from our experiment is applied to other gene expression data. We are also trying to make a systematic method to improve the accuracy by regulating the factors mentioned above.

• Journal of Science Education
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• v.41 no.2
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• pp.248-266
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• 2017

The purpose of this study is to present various examples of collaborative learning based on the Instruction of Internet in the 6th grade elementary school mathematics class. So we introduce the design method of classroom environment for classroom Internet and give example of various teaching methods. This study was conducted for nine months from March to November, 2016, one sixth grade of elementary school in D area. During this period, we conducted Instruction of Internet-based collaborative learning to classify typical teaching cases. We classified into 5 type collaborative learning. First, collaborative learning in the classroom. Second, remote collaborative learning between classroom and classroom. Third, Live participation classes. Forth, project collaborative learning. Fifth, using virtual reality in collaborative learning. In addition, we could identify that there is a difference compared to the conventional learning. It became possible to conduct collaborative learning with other students simultaneously or have opening class with both parents and teachers by using Youtube. These examples can be presented as a case to depart from traditional mathematics class in one classroom. In this regard, we will be able to provide several implications about teaching methods utilizing smart device and Internet in future classroom.

• Journal of the Korea Convergence Society
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• v.11 no.9
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• pp.359-366
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• 2020

The purpose of this study was to find out the differences in the teaching methods of elementary, middle and high school physical education teachers for online physical education classes and the improvement of online education. To this end, an online questionnaire was conducted for 166 physical education teachers belonging to the Busan Metropolitan Physical Education Research Association community, and cross-analysis were conducted. There search results are as follows. First, there was no difference in gender, starting with online school. Second, there were differences in the method sand motivation so online physical education classes according to the type of employment, and there was no difference in improvement. Third, there was significant difference in the motivation for online physical education classes according to the teaching career. Based on these research results, it is expected that various efforts will be needed to promote the adaptation and improvement of education and teachers for online physical education classes.

• Korean Journal of Remote Sensing
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• v.19 no.2
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• pp.170-179
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• 2003

In order to classify Land Use/Land Cover using multispectral images, we have to give consequence to defining proper classes and selecting training sample with higher class separability. The process of satellite hyperspectral image which has a lot of bands is difficult and time-consuming. Furthermore, classification result of hyperspectral image with noise is often worse than that of a multispectral image. When selecting training fields according to the signatures in the study area, it is difficult to calculate covariance matrix in some clusters with pixels less than the number of bands. Therefore in this paper we presented an overview of feature extraction methods for classification of Hyperion data and examined effectiveness of feature extraction through the accuracy assesment of classified image. Also we evaluated the classification accuracy of optimal meaningful features by class separation distance, which is also a method for band reduction. As a result, the classification accuracies of feature-extracted image and original image are similar regardless of classifiers. But the number of bands used and computing time were reduced. The classifiers such as MLC, SAM and ECHO were used.

• Korean Journal of Remote Sensing
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• v.20 no.6
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• pp.419-425
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• 2004

This study has proposed a data fusion method based on the Dempster-Shafer evidence theory The Dempster-Shafer fusion uses mass functions obtained under the assumption of class-independent Gaussian assumption. In the Dempster-Shafer approach, uncertainty is represented by 'belief interval' equal to the difference between the values of 'belief' function and 'plausibility' function which measure imprecision and uncertainty By utilizing the Dempster-Shafer scheme to fuse the data from multiple sensors, the results of classification can be improved. It can make the users consider the regions with mixed classes in a training process. In most practices, it is hard to find the regions with a pure class. In this study, the proposed method has applied to the KOMPSAT-EOC panchromatic image and LANDSAT ETM+ NDVI data acquired over Yongin/Nuengpyung. area of Kyunggi-do. The results show that it has potential of effective data fusion for multiple sensor imagery.

• Journal of the Korean association of regional geographers
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• v.4 no.2
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• pp.65-77
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• 1998

One of the fundamental, important preconditions for effective teaching of geography is to collect a variety of picture data available for class and to manage the data systematically. The purpose of this study is to present one method about how to supply basic picture data available for class of Korean geography for the high school program to teachers in service and how to collect, manage and utilize the data. A total of 233 picture data related to contents of the textbook of Korean Geography have been gathered through this study, and a database has been constructed for the data. Directories were generated for individual units of the textbook, and the collected picture data was stored in the image file of each directory. This data was recorded in a CD and attached as an appendix. Since the primary purpose of this study is to suggest one method, the picture data in a database for the present study is just a fraction of lots of data available for class of Korean geography. If the user persistently enlarges and manages data based on the results of this study, the data will become a good instructional aid. The picture data can be printed over the transparent film and used for class by using the overhead protector (OHP), or it can be also used as a remote self-study tool through the computer telecommunications network (e.g., LAN or INTERNET. etc,). Most desirable, however, is to develop teachers' own method by taking account of separate units of the textbook or diverse educational environments.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.223-231
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• 2022

Covid-19, which has made a huge difference in our daily lives, has also brought major changes to our college education. As the class was changed from the traditional face-to-face class to a non face-to-face class, both teachers and students had difficulties in adapting, and problems such as the occurrence of academic achievement gaps due to non face-to-face classes were also raised. Therefore, this study aims to find out what attitudes students have toward non-face-to-face classes at universities caused by Covid-19. Accordingly, this study tried to identify the types of subjective perceptions college students have toward non-face-to-face classes by applying the Q methodology, and to suggest points for reference in the development and improvement of non-face-to-face classes in the future. Five types were found as a result of analysis using 30 P samples and 34 Q samples. First, learning efficiency-oriented type, second, class participation and communication-oriented type, third, non-face-to-face class active acceptance and utilization type, fourth, dissatisfaction type due to remote system and equipment operation errors, fifth, passive response type according to the situation to be. From the results of this study, it seems that it is necessary to develop an educational method for effective non-face-to-face class considering the characteristics of each type, and the merits of non-face-to-face classes, especially recorded lectures, in terms of learning efficiency, are evident. Therefore, even if face-to-face classes are conducted entirely at universities, it is believed that providing video-recorded lectures in class will be of great help to students' learning.

• Journal of Environmental Impact Assessment
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• v.8 no.3
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• pp.77-90
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• 1999

The degree of green naturality (DGN) has played a key role for maintaining the environmental quality from inappropriate developments, although the quality and effectiveness of the mapping of DGN has been under debate. In this study, spatial distribution of degree of green naturality was initially estimated from forest stand maps that were produced from the aerial photo interpretation and extensive field survey. Once the boundary of initial classes of DGN were defined, it were overlaid with normalized difference vegetation index (NDVI) data that were derived from the recently obtained Landsat Thematic Mapper data. NDVI was calculated for each pixel from the radiometrically corrected satellite image. There were no significant differences in mean values of vegetation index among the initial DGN classes. However, the satellite derived vegetation index was very effective to delineate the developed and damaged forest lands and to adjust the initial value of DGN according to the distribution of NDVI within each class.

• Journal of Industrial Technology
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• v.26 no.A
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• pp.75-80
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• 2006

A vibration monitoring is performed on a 1kW class stand alone wind turbine(W/T). When a W/T model is developed, general performance under various wind condition should be verified to introduce the product in the market. Especially, vibration characteristics within operating speed range are very important in the aspect of structural stability as well as generator's electrical efficiency. This paper examines the vibration performance of a home made 1kW W/T. Various data of the W/T model are acquired in real time using a remote vibration monitoring system installed in Daekwanryung test site. Vibration stability of the W/T structure is diagnosed based upon the data and the result is used to estimate the applicability of the W/T model.