• Journal of agriculture & life science
• /
• v.43 no.6
• /
• pp.105-109
• /
• 2009

Kyungsan nursery complex which has a vast area for the production of various species of fruit tree stocks is in a high demand of virus-free saplings. Apple tree stocks, the most important products, urgently need more rapid and reliable viral diagnosis. In this study, a bead beater was tested because of convenience in dealing with large number of samples. Also, industrial glass bead abrasive (0.4 mm in diameter) at very low cost was used in a disposable way. For bead beater-aided RNA extraction from apple stem tissues, the guanidine thiocyanate method was confirmed to be very reliable. Silca membrane filter tube in connection to vacuum filtering device was strongly suggested for simplifying RNA capture and washing steps. Apple virus detection was confirmed by RT-PCR.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.33 no.6
• /
• pp.980-989
• /
• 2009

Amur cork tree was extracted in methanol with the purpose of investigating the most effective extraction procedure for detecting the chromophore using the GC-MS analysis. Different procedures of waterbath and hotplate extractions were carried out and five different GC-MS instrument parameters including the operating temperatures in the GC capillary column and the MSD scan range were tested for their efficiencies. Berberine was determined by the detection of dihydroberberine at 15.0 min r.t. Hotplate was a better device for extracting amur cork tree than waterbath shaker either with or without presoaking in the room temperature. Water was not an adequate extraction medium for the berberine detection. The most effective GC-MS parameter was Method 4; the initial temperature at $50^{\circ}C$ followed by the temperature increase of $23^{\circ}C$/min until $210^{\circ}C$, then increase of $30^{\circ}C$/min until the final temperature reach at $305^{\circ}C$, then hold for 14 minutes to maintain the total run time 24.12 minutes. The MSD scan range for Method 4 was $35\sim400$m/z.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.42 no.3 s.303
• /
• pp.73-80
• /
• 2005

Recently there have been many efforts to support searching and browsing based on the visual content of image and multimedia data. Most existing approaches to content-based image retrieval rely on query by example or user based low-level features such as color, shape, texture. But these methods of query are not easy to use and restrict. In this paper we propose a method for automatic color object extraction and labelling to support multiple queries of content-based image retrieval system. These approaches simplify the regions within images using single colorizing algorithm and extract color object using proposed Color and Spatial based Binary tree map(CSB tree map). And by searching over a large of number of processed regions, a index for the database is created by using proposed labelling method. This allows very fast indexing of the image by color contents of the images and spatial attributes. Futhermore, information about the labelled regions, such as the color set, size, and location, enables variable multiple queries that combine both color content and spatial relationships of regions. We proved our proposed system to be high performance through experiment comparable with another algorithm using 'Washington' image database.

• The KIPS Transactions:PartD
• /
• v.15D no.1
• /
• pp.23-30
• /
• 2008

The basic research of context aware in ubiquitous environment is an internet technique and XML. The XML data of continuous stream type are popular in network application through the internet. And also there are researches related to query processing for streaming XML data. As a basic research to efficiently query, we propose not only a labeled ordered tree model representing the XML but also a mining method to extract frequent structures from streaming XML data. That is, XML data to continuously be input are modeled by a stream tree which is called by XFP_tree and we exactly extract the frequent structures from the XFP_tree of current window to mine recent data. The proposed method can be applied to the basis of the query processing and index method for XML stream data.

• The KIPS Transactions:PartA
• /
• v.12A no.2 s.92
• /
• pp.109-116
• /
• 2005

In this paper, we introduce the method that a user analyses the similarity of the two programs by using keyword from the syntactic tree, created after the syntax analysis, and its implementation. The main advantage of the method is the performance improvement through using only keyword of syntax tree. In the paper, we propose the similarity evaluation model and how we extract keyword from syntax tree. In addition, we also show the improvement in the performance in analysis and in the system's structure. We expect that our system will be utilized in the similarity evaluation in text and XML documents.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.18 no.1 s.116
• /
• pp.96-104
• /
• 2007

Currently, there is a lack of suitable prediction model and measurement data for vegetation loss. So in this paper, vegetation loss measurement has been performed for seven different tree-species, including dawn-redwood tree, plane tree, pine tree and hymalaya cedar in the frequency range of $1.0{\sim}6.0\;GHz$, for the two years, from 2005 to 2006 years. And then, extraction and revision for the proposed RET model input parameters in ITU-R P.833 has been performed. The key results of measurement and RET modeling has been presented in this paper. The results of this study have been adapted for ITU-R recommendation at the ITU-R meeting in 2005 and 2006.

• Journal of Cadastre & Land InformatiX
• /
• v.46 no.1
• /
• pp.87-100
• /
• 2016

The acquisition of the forest resource information has depended on a partial sampling method or aerial photographs which demand a lot of effort and time because of the vast areas and the difficult approach. For the acquisition of the forest resource information, there have been the optical remote-sensing and the multi-spectrum image to offer only horizontal distributions of trees, but a new technological approach, such as Airborne LiDAR, is more necessary to acquire directly three dimensional information related to the forest terrains and trees' features. This paper proposes an algorithm for the forest information extraction such as trees' individual numbers and the heights of trees by using LiDAR data. Especially, this proposed algorithm adopts a region growing method for the extraction of the vegetation-point and extracts the forest information using morphological features of trees.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.18 no.1
• /
• pp.211-216
• /
• 2018

In this paper, we studied the way that classify whether unknown PE file is malware or not. In the classification problem of malware detection domain, feature extraction and classifier are important. For that purpose, we studied what the feature is good for classifier and the which classifier is good for the selected feature. So, we try to find the good combination of feature and classifier for detecting malware. For it, we did experiments at two step. In step one, we compared the accuracy of features using Opcode only, Win. API only, the one with both. We founded that the feature, Opcode and Win. API, is better than others. In step two, we compared AUC value of classifiers, Bernoulli Naïve Bayes, K-nearest neighbor, Support Vector Machine and Decision Tree. We founded that Decision Tree is better than others.

• Journal of Korean Society for Geospatial Information Science
• /
• v.18 no.4
• /
• pp.11-20
• /
• 2010

In situation that carbon dioxide emissions are being increased as urbanization, urban green space is being promoted as an alternative to find solution for these problems. In urban areas, trees have the ability to reduce carbon dioxide as well as to be aesthetic effect. In this study, we proposed the methodology which uses only LIDAR data in order to extract these trees information effectively. To improve the operational efficiency according to the extraction of trees, the proposed methodology was carried out using multiple data processing such as point, polygon and raster. Because the existing NDSM(Normalized Digital Surface Model) contains both the building and tree information, it has the problems of high complexity of data processing for extracting trees. Therefore, in order to improve these problems, this study used modified NDSM which was removed estimate regions of building. To evaluate the performance of the proposed methodology, three different zones which coexist buildings and trees within urban areas were selected and the accuracy of extracted trees was compared with the image taken by digital camera.

• The Journal of Korean Association of Computer Education
• /
• v.15 no.2
• /
• pp.9-18
• /
• 2012

This study investigated the extraction algorithm fitting for variables of adolescents' computer use type with the sample from KYPS data (3409 in the second grade of the junior high school; 1704 boys and 1705 girls). The results of the decision tree model revealed that : (1) Gender, computer use time, misdeed friends, parent supervision, other agreement of misdeed, parent study expectation, self-control, teacher attachment, and sibling relation were significant for entertainment type. (2) Gender, cyberclub, computer use time, self-belief, online misdeed were significant for relation type. (3) Study enthusiasm, personal study time, optimistic disposition, study and spare time, cyberclub, self-belief, and other people criticism were significant for information type. These results suggest that adolescents' diverse conditions should be considered for using computer more efficiently.