• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.79-82
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• 2005

Recently the necessity of road data is still being increased in industrial society, so there are many repairing and new constructions of roads at many areas. According to the development of government, city and region, the update and acquisition of road data for GIS (Geographical Information System) is very necessary. In this study, the fusion method with range data(3D Ground Coordinate System Data) and Intensity data in stand alone LiDAR data is used for road extraction and then digital image processing method is applicable. Up to date Intensity data of LiDAR is being studied. This study shows the possibility method for road extraction using Intensity data. Intensity and Range data are acquired at the same time. Therefore LiDAR does not have problems of multi-sensor data fusion method. Also the advantage of intensity data is already geocoded, same scale of real world and can make ortho-photo. Lastly, analysis of quantitative and quality is showed with extracted road image which compare with I: 1,000 digital map.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.12
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• pp.1062-1067
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• 2005

This paper discusses a skeleton feature extraction method for ubiquitous robot system. The skeleton features are used to analyze human motion and pose estimation. In different conventional feature extraction environment, the ubiquitous robot system requires more robust feature extraction method because it has internal vibration and low image quality. The new hybrid silhouette extraction method and adaptive skeleton model are proposed to overcome this constrained environment. The skin color is used to extract more sophisticated feature points. Finally, the experimental results show the superiority of the proposed method.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.395-398
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• 2017

We propose a web crawler system with keyword extraction function in this paper. Researches on the keyword extraction in existing text mining are mostly based on databases which have already been grabbed by documents or corpora, but the purpose of this paper is to establish a real-time keyword extraction system which can extract the keywords of the corresponding text and store them into the database together while grasping the text of the web page. In this paper, we design and implement a crawler combining RAKE keyword extraction algorithm. It can extract keywords from the corresponding content while grasping the content of web page. As a result, the performance of the RAKE algorithm is improved by increasing the weight of the important features (such as the noun appearing in the title). The experimental results show that this method is superior to the existing method and it can extract keywords satisfactorily.

• Korean Management Science Review
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• v.20 no.2
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• pp.1-16
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• 2003

Previous research on data extraction and integration for data warehousing has concentrated mainly on the relational DBMS or partly on the object-oriented DBMS. Mostly, it describes issues related with the change data (deltas) capture and the incremental update by using the triggering technique of active database systems. But, little attention has been paid to data extraction approaches from other types of source systems like hierarchical DBMS, etc. and from source systems without triggering capability. This paper argues, from the practical point of view, that we need to consider not only the types of information sources and capabilities of ETT tools but also other factors of source systems such as operational characteristics (i.e., whether they support DBMS log, user log or no log, timestamp), and DBMS characteristics (i.e., whether they have the triggering capability or not, etc), in order to find out appropriate data extraction techniques that could be applied to different source systems. Having applied several different data extraction techniques (e.g., DBMS log, user log, triggering, timestamp-based extraction, file comparison) to S bank's source systems (e.g., IMS, DB2, ORACLE, and SAM file), we discovered that data extraction techniques available in a commercial ETT tool do not completely support data extraction from the DBMS log of IMS system. For such IMS systems, a new date extraction technique is proposed which first creates Index database and then updates the data warehouse using the Index database. We illustrates this technique using an example application.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.103-111
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• 2005

In this paper, we have designed a deployment process system that extract and integrate information related to technology and market opportunities through searching for external environment and internal condition on multi-dimensional space in order to generate new research themes. It is expected that this theme extraction model could be contributed to the maximization of R&D productivity by systemization of the opportunity extraction process for generating research themes in R&D center or laboratory.

• Journal of International Society for Simulation Surgery
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• v.3 no.2
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• pp.74-76
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• 2016

Computer-aided navigation system is helpful in maxillofacial surgery with real time instrument positioning and clear anatomic identification. Generally, completely impacted tooth extraction surgery have e high risk by iatrogenic injury such as, adjacent tooth injury, normal anatomical structure injury. This case report describes performing extraction of impacted supernumerary teeth on anterior maxilla by using the navigation system in a 15 years old male patient.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2355-2358
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• 2003

The purpose of this paper is to investigate two major feature extraction techniques based on generic modular face recognition system. Detailed algorithms are described for principal component analysis (PCA) and independent component analysis (ICA). PCA and ICA ate statistical techniques for feature extraction and their incorporation into a face recognition system requires numerous design decisions. We explicitly state the design decisions by introducing a modular-based face recognition system since some of these decision are not documented in the literature. We explored different implementations of each module, and evaluate the statistical feature extraction algorithms based on the FERET performance evaluation protocol (the de facto standard method for evaluating face recognition algorithms). In this paper, we perform two experiments. In the first experiment, we report performance results on the FERET database based on PCA. In the second experiment, we examine performance variations based on ICA feature extraction algorithm. The experimental results are reported using four different categories of image sets including front, lighting, and duplicate images.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.4
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• pp.346-352
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• 2011

This paper presents a system of road extraction for traffic images from a single camera. The road in the images is subject to large changes in appearance because of environmental effects. The proposed system is based on the integration of color correlograms and random forest. The color correlogram depicts the color properties of an image properly. Using the random forest, road extraction is formulated as a learning paradigm. The combined effects of color correlograms and random forest create a robust system capable of extracting the road in very changeable situations.

• Journal of the Korean Chemical Society
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• v.13 no.3
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• pp.199-204
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• 1969

The distribution rate of 4f and 5f series elements in chelate and ion association extraction system was studied. Clear difference between lighter and heavier part of 4f series are observed. Trivalent Am and Cm were appeared to be grouped into the lighter part of 4f series. And also the variation of distribution ratio according to the varied temperature was studied. The variation modes of distribution ratio are different according to the extraction system. Atomic number dependence in the chelate extraction system was observed.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1058-1060
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• 2003

A ground control point (GCP) is a point on the surface of Earth where image coord inates and map coordinates can be identified. The GCP is useful for the geometric correction of systematic and unsystematic errors usually contained in a remotely sensed data. Especially in case of synthetic aperture radar (SAR) data, it has serious geometric distortions caused by inherent side looking geometry. In addition, SAR images are usually severely corrupted by speckle noises so that it is difficult to identify ground control points. We developed a ground point extraction algorithm that has an improved capability. An application of radargrammetry to Daejon area in Korea was studied to acquire the geometric information. For the ground control point extraction algorithm, an ERS SAR data with precise Delft orbit information and rough digital elevation model (DEM) were used. We analyze the accuracy of the results from our algorithm by using digital map and GPS survey data.