• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.118-122
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• 2005

Data mining is the process of autonomously extracting useful information or knowledge from large data stores or sets. For analyzing data of manufacturing processes obtained from database using data mining, source data should be collected form production process and transformed to appropriate form. To extract those data from database, a computer program should be made for each database. This paper presents a program to extract easily data form database in industry. The advantage of this program is that user can extract data from all types of database and database table and interface with Teamcenter Manufacturing.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2000.11a
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• pp.294-297
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• 2000

Heavy metals are extracted from Chonju stream sediment, roadside soils and sediments along Honam expressway, soils and tailings from mining area using partial ectraction in Standard Method, partial ectraction method with maintaining 0.1N of extraction solution and acid digestion. In samples having buffer capacity against acid, 0.1N of extraction solution can not be maintained and pH of extraction solution increases up to 8.0 when partial extraction in Standard Method is used. The averages and ranges of (heavy metals extracted using partial extraction in standard method, HPE)/(heavy metals extracted using partial extraction method with maintaining 0.1N of extraction solution, HPEM) values are 0.506 and 0.145~1.126 in Cd, 0.534~ and 0.078~0.928 in Zn, 0.461 and 0.041~1.715 in Mn, 0.359 and 0.011~0.874 in Cu, 0.195 and 0.018~1.785 in Cr, 0.710 and 0.003~3.075 in Pb, and 0.088 and 1.73$\times$10$^{-5}$ ~0.303 in Fe. These data indicate that the difference between HPE and HPEM is big in the order of Fe, Cr, Cu, Mn, Cd, Zn and Pb. It is quite possible that the partial extraction method in Standard Method of soil in Korea is not adequate for an assessment of contamination in area where buffer capacity of soil will be decreased or lost after a long term exposure of soils to environmental damage.

• Korean journal of food and cookery science
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• v.7 no.1
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• pp.27-34
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• 1991

This study attempted to set up reasonable extraction time of Omija that was put in water for the various components to soak out. Changes of free sugars, organic acids, reducing sugar, total acid and tannin in Omija with various extraction times were investigated (together with the analysis of each components in Omija fruit). 1. High Performance Liquid Chromatography showed fructose, glucose, and sucrose to be the major free sugars of the Omija fruit. Free sugars and reducing sugar value in Omija beverage increased gradually in according with the extraction time, and marked 75.6% per total free sugars and 82.1% per total reducing sugar at 12 hours. 2. Gas Chromatography showed lactic acid, oxalic acid, fumaric acid, levulinic acid, succinic acid, malic acid, citric acid and pyroglutamic acid to be the major organic acids of the Omija fruit. Organic acids and total acids value in Omija beverage increased gradually on proportion to extraction time, and marked 97.0% per total organic acids at 9 hours and 79.0% per total acids at 12 hours. 3. Tannin content in Omija beverage was increased when extraction time was longer but it showed a low percentage as compared with the reducing sugar and total acid. Tannin content marked 48.8% per total tannin at 12 hours. 4. Sensory evaluation revealed that !1 hours of extraction produced the best quality products based in taste, flavor, color and over-all acceptability, considering the data, it seems possible to conclude that the optimum of time for extraction of Omija to water is 9 hours.

• Korean Journal of Optics and Photonics
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• v.23 no.4
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• pp.143-146
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• 2012

All-optical data extraction, one of the key technologies for all-optical computing and optical communication to perform add-drop, packet switching, and data reset, etc., is experimentally demonstrated by using cross-gain modulation (XGM) of semiconductor optical amplifiers (SOAs). Also, all-optical data extraction based on numerical simulation is performed by using the VPI simulation tool. In this paper, the suggested optical system based on SOAs shows the potential for high speed, and highly integrable and low power optical data computing.

• Korean Journal of Remote Sensing
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• v.19 no.6
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• pp.421-430
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• 2003

The extraction technique for Doppler information(Doppler centroid frequency(f$_{dc}$) and it's rate(f$_{r}$) is very important to make an image from the radar echo signal data. Clutterlock and auto-focusing techniques have been widely used to extract accurate Doppler information. But both techniques are not easy to implement in SAR processor and need quite lots of time to calculate accurate f$_{dc}$ and f$_{r}$ because they are generally based on echo signal data only. In this paper we suggest hybrid method for Doppler extraction using both of echo signal data and orbital and attitude information of satellite. In this method CDE(Correlation Doppler Estimation) technique is only used to estimate exact modular f$_{dc}$ using received echo signal data and rest of other algorithms are based on simple mathematical model of geometry between satellite and ground targets as well as the Doppler frequency ambiguity resolving problem. The experimental results using Radarsat-1 signal data shows that the proposed method can be effectively used for the extraction of Doppler information.

• Journal of the Korea Society of Computer and Information
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• v.20 no.7
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• pp.1-7
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• 2015

Although data on the internet can be used in various fields such as source of data of IR(Information Retrieval), Data mining and knowledge information servece, and contains a lot of unnecessary information. The removal of the unnecessary data is a problem to be solved prior to the study of the knowledge-based information service that is based on the data of the web page, in this paper, we solve the problem through the implementation of XTractor(XPath Extractor). Since XPath is used to navigate the attribute data and the data elements in the XML document, the XPath analysis to be carried out through the XTractor. XTractor Extracts main text by html parsing, XPath grouping and detecting the XPath contains the main data. The result, the recognition and precision rate are showed in 97.9%, 93.9%, except for a few cases in a large amount of experimental data and it was confirmed that it is possible to properly extract the main text of the news.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.2
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• pp.209-215
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• 2006

Shoreline changes its shapes and attribution dynamically by natural, unnatural acts and is the most information for country. These shorelines can apply to framework data of MGIS (Marine Geographic Information System), and they are getting important to implement a phase of monitoring around coastal areas. This study proposed an algorithm automatically extracting shorelines to use a new developed LiDAR (Light Detection And Ranging) data which is applying in ocean and coastal areas. Then, in result, it was compared to shorelines which is derived from ground survey. In result, it shows stable shorelines in various coast areas such as nature, artificial coast. Additionally, and a possibility of shoreline extraction through LiDAR data.

• The Journal of Bigdata
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• v.6 no.2
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• pp.61-70
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• 2021

The objective of this study was to describe specific approaches for data extraction from graph when statistical information is not directly reported in some articles, enabling data intergration and meta-analysis for quantitative data synthesis. Particularly, meta-analysis is an important analysis tool that allows the right decision making for evidence-based medicine by systematically and objectively selects target literature, quantifies the results of individual studies, and provides the overall effect size. For data integration and meta-analysis, we investigated the strength points about the introduction and application of Adobe Acrobet Reader and Python-based Jupiter Lab software, a computer tool that extracts accurate statistical figures from graphs. We used as an example data that was statistically verified throught an previous studies and the original data could be obtained from ClinicalTrials.gov. As a result of meta-analysis of the original data and the extraction values of each computer software, there was no statistically significant difference between the extraction methods. In addition, the intra-rater reliability of between researchers was confirmed and the consistency was high. Therefore, In terms of maintaining the integrity of statistical information, measurement using a computational tool is recommended rather than the classically used methods.

• Korean Journal of Remote Sensing
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• v.29 no.5
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• pp.569-579
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• 2013

In this study, land-cover classification was implemented using features extracted from multi-temporal SAR data through 3D wavelet transform and the applicability of the 3D wavelet transform as a feature extraction approach was evaluated. The feature extraction stage based on 3D wavelet transform was first carried out before the classification and the extracted features were used as input for land-cover classification. For a comparison purpose, original image data without the feature extraction stage and Principal Component Analysis (PCA) based features were also classified. Multi-temporal Radarsat-1 data acquired at Dangjin, Korea was used for this experiment and five land-cover classes including paddy fields, dry fields, forest, water, and built up areas were considered for classification. According to the discrimination capability analysis, the characteristics of dry field and forest were similar, so it was very difficult to distinguish these two classes. When using wavelet-based features, classification accuracy was generally improved except built-up class. Especially the improvement of accuracy for dry field and forest classes was achieved. This improvement may be attributed to the wavelet transform procedure decomposing multi-temporal data not only temporally but also spatially. This experiment result shows that 3D wavelet transform would be an effective tool for feature extraction from multi-temporal data although this procedure should be tested to other sensors or other areas through extensive experiments.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.3
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• pp.79-84
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• 2021

A feature extraction method capable of reflecting features well while mainaining the properties of data is required in order to process high-dimensional data. The principal component analysis method that converts high-level data into low-dimensional data and express high-dimensional data with fewer variables than the original data is a representative method for feature extraction of data. In this study, we propose a principal component analysis method based on adaptive correlation when selecting principal component variables in principal component analysis for data feature extraction when the data is high-dimensional. The proposed method analyzes the principal components of the data by adaptively reflecting the correlation based on the correlation between the input data. I want to exclude them from the candidate list. It is intended to analyze the principal component hierarchy by the eigen-vector coefficient value, to prevent the selection of the principal component with a low hierarchy, and to minimize the occurrence of data duplication inducing data bias through correlation analysis. Through this, we propose a method of selecting a well-presented principal component variable that represents the characteristics of actual data by reducing the influence of data bias when selecting the principal component variable.