• Journal of Korea Multimedia Society
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• v.9 no.9
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• pp.1173-1183
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• 2006

Matrix-star, Pancake, and RFM graphs have such a good property of Star graph and a lower network cost than Hypercube. Matrix-star graph has Star graph as a basic module and the node symmetry, the maximum fault tolerance, and the hierarchical decomposition property. Also it is an interconnection network that improves the network cost against Star graph. In this paper, we propose a method to embed among Matrix-star Pancake, and RFM graphs using the edge definition of graphs. We prove that Matrix-star $MS_{2,n}$ can be embedded into Pancake $P_{2n}$ with dilation 4, expansion 1, and $RFM_{n}$ graphs can be embedded into Pancake $P_{n}$ with dilation 2. Also, we show that Matrix-star $MS_{2,n}$ can be embedded into the $RFM_{2n}$ with average dilation 3.

• Korean Journal of Remote Sensing
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• v.18 no.6
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• pp.337-344
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• 2002

In general, in order to obtain position information from satellite images, satellite sensor model which represents the geometric relationship between sensor and targeted area should be established in the first place. However, it is not simple for modelling pushbroom satellite sensor due to the image capturing process. In recent development of new generation imaging sensors, a generic sensor model, which is applicable to all types of sensors such as frame, pushbroom, whiskbroom, and SAR is in great need to the remote sensing and photogrammetry community. In this paper, the RFM as sensor model was implemented with KOMPSAT EOC and SPOT satellite images and analyzed in cases where the number and distribution of ground control points were varied. The test results of RFM were presented and compared with those of Direct Linear Transformation(DLT).

• 한국지형공간정보학회:학술대회논문집
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• 2002.03a
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• pp.27-33
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• 2002

최근 들어 다항식비례모형(RFM: Rational Function Model)은 비전문가에게 있어서 지형보정을 위한 정확도 문제를 해결함과 동시에 센서 종류에 상관없이 적용 가능한 범용적인 센서모델링 기법으로 각광을 받고 있다. 그러나 엄밀(physical) 모델이 없는 센서 혹은 위성의 궤도력 자료를 제공하지 않는 센서의 경우 다항식비례모형의 적용을 위해서는 다수의 매개변수 사용으로 인한 계수들 간의 상관성을 고려해야 한다. 이에 본 연구에서는 2차 다항식비례모형에 기초하여 전방 다항식비례모형(Forward RFM)과 상관도 분석을 통한 전방 다항식비례모형의 이른 및 위치정확도에 관한 연구를 수행하였다. 대상연구지역은 KOMPSAT(Korea Multi-Purpose Satellite)과 SPOT으로 촬영한 대전광역시와 그 주변지역으로 SPOT과 KOMPSAT 모두 상관성 분석 전에는 대략 50% 정도의 검사점에 대해 과대오차(>100m)가 얻어졌으며, 이 점들을 제외한 검사점에 대해서도 SPOT은 평균수평오차 20-24m, 평균표고오차 25m, KOMPSAT은 평균수평오차 15-24m, 평균표고오차 30m를 나타내었다. 전방 다항식비례모형에 대하여 상관성 분석을 수행한 후에는 검사점에 대한 모든 과대오차 조정결과가 소거되었고 검사점에 대해서 SPOT은 평균수평오차 8.8m, 평균표고오차 25.2m, KOMPSAT은 평균수평오차 8.4m, 평균표고오차 14.5m를 나타내었다. 최종적으로 연구지역에 대한 수치표고모형의 제작을 통해 상관도 분석을 통한 다항식비례모형의 실제 적용 가능성을 보여주었다.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.2
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• pp.77-81
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• 2013

The international standard AIS, which stands for the safety of ship navigation and vessel traffic management, provides 27 messages to exchange the navigational information of ship. Among 27 messages, message ID 6 and 8 are defined as the binary data format to exchange application specific information and are classified into IFM for international use and RFM for national or regional use. Since international standards are based on English, there have been some needs to exchange data in Hangul text for vessel traffic management to correct the static and dynamic ships' information. In this paper, I analyze international standards to provide a Hangul text messaging service based on RFM and propose a RFM message and a simple protocol to correct information of a ship.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.2
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• pp.543-547
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• 2012

The environmental education is more and more important according to increasing environmental problems, but university students don't receive it actively. Actually, environmental education in university is conducted and focused on environmental engineering. In order to have an effect on environmental education for all engineering college students, the course of environmental education consists of various fields of engineering study including environmental engineering. The environmental education categories for engineering college students are determined by using an AHP technique in this study. After educating engineering college students with the developed environmental education course, we evaluated the environmental education performance using the survey on perception level and purchasing data of environmentally consciously products by statistical and RFM analysis.

• Journal of Service Research and Studies
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• v.1 no.1
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• pp.49-60
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• 2011

Recently, with the growing of social network sites, people's choice is also getting more and more. So the notion of loyalty has become an important construct within the Social Network framework because of member is easy switching on the social networking sites. Despite the increasing importance of social network sites loyalty question, there's very little research in this area. In electronic commerce, the website loyalty development process is based on both website satisfaction and website trust toward the net-enabled business. But how to target the members with high or low loyalty in the social network sites is still a question. In this paper we propose one improved RFM model to evaluate the member loyalty to find the potential members for improving the service quality of the social network site. In addition, an empirical case study is performed to demonstrate how this procedure works. Moreover, further applications of this research are provided for improved social network sites experiences and how to use the model to practice.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.121-128
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• 2003

사면관측 원리에 의해 획득되는 레이더 영상은 레이더파의 입사각도와 지표면의 경사도 및 방위각에 따라 기하학적 왜곡이 발생하게 된다. 전 국토의 70% 이상이 산악지형인 국내 여건을 감안한다면 레이더 영상의 정량적 활용을 위해서는 정밀한 기하보정이 반드시 필요하다. 본 연구에서는 RADSARSAT-1 SAR 영상에 대하여 세 가지 기하보정 방법을 적용하였다. 먼저 GCP 만을 이용한 단순기하보정을 수행하였고, 두번째로 위성의 자세와 위치정보 등을 이용하여 센서모델을 통한 보정을 하였다. 마지막으로 다양한 영상자료에 적용할 수 있는 RFM(Rational Function Model)을 이용하여 기하보정을 하였다. 이 세 가지 방법으로 기하보정된 레이더 영상의 위치정확도를 모의 레이더 영상과 비교 분석하였다. 또한 RFM을 이용한 보정결과를 검증하기 위하여 SIR-C 영상을 추가로 분석하였다.

• 한국지형공간정보학회:학술대회논문집
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• 2002.11a
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• pp.73-80
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• 2002

RFM is believed to be universally applicable to any type of the sensor. Most of researches carried out lately are concentrated on terrain-independent method, but the researches about approvement of accuracy by way of terrain-dependent method are required to increase a practical use of satellite imagery in nonprofessional groups. This research focused on a means to improve RFM solution, a matching technique, and a generation of DEM through a correlation analysis, with terrain-dependent solution. The result shows that accuracy problem which is caused by over-parameterization on RFCs was removed through correlation analysis, and it was possible to generate a accurate DEM with terrain-dependent solution. And also, the application of RFM with different satellite images show sensor independent characteristics of RFM

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.1
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• pp.1-9
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• 2011

The objective of this paper is to improve the accuracy of the 3D geopositioning extracted from Rational Polynomial Coefficient(RPC) provide in the KOMPSAT-2 metadata files. In this paper, we developed the algorithm to adjust a RFM(Rational Functional Model), and could improve the accuracy of a RFM with this algorithm. Furthermore, when a RFM was adjusted with this algorithm, the effects of the number of GCPs on the accuracy of the adjusted RFM was tested. For accuracy assessment using adjusted RFM, 9 ground control points(GCPs) and 24 check points could be used. Results indicated that the root mean squared errors(RMSEs) of horizontal residual errors calculated 24 check points were 2.20(m). The achieved accuracy of three dimensional object-point determination was 1.72(m) in the X-dimension and 1.37(m) in the Y-dimension and 2.20(m) in the Z-dimension.

• Journal of the Korean Data and Information Science Society
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• v.24 no.2
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• pp.245-255
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• 2013

The object of study is to propose a method for grouping R, F, and M in RFM model. Our model uses 6 levels using standard normal distribution. First level is upper 2.5% and second level next 13.5%, third level next 34%, fourth level next 34%, fifth level next 13.5%, sixth level next 2.5%. Values are symmetric and limits are clear. We compare proposed model with traditional 5 level model and 10 level model using NDSL data of KISTI. Proposed model divides most clearly the distribution of the RFM function for all cases of weights, because it uses the distribution of customers. Comparison studies of our model with grouping using cluster analysis and studies on weights of RFM model are needed.