• 한국측량학회지
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• 제30권6_2호
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• pp.643-651
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• 2012

Object recognition belongs to high-level processing that is one of the difficult and challenging tasks in computer vision. Digital photogrammetry based on the computer vision paradigm has begun to emerge in the middle of 1980s. However, the ultimate goal of digital photogrammetry - intelligent and autonomous processing of surface reconstruction - is not achieved yet. Object recognition requires a robust shape description about objects. However, most of the shape descriptors aim to apply 2D space for image data. Therefore, such descriptors have to be extended to deal with 3D data such as LiDAR(Light Detection and Ranging) data obtained from ALS(Airborne Laser Scanner) system. This paper introduces extension of chain code to 3D object space with hierarchical approach for segmenting point cloud data. The experiment demonstrates effectiveness and robustness of the proposed method for shape description and point cloud data segmentation. Geometric characteristics of various roof types are well described that will be eventually base for the object modeling. Segmentation accuracy of the simulated data was evaluated by measuring coordinates of the corners on the segmented patch boundaries. The overall RMSE(Root Mean Square Error) is equivalent to the average distance between points, i.e., GSD(Ground Sampling Distance).

• 한국통계학회:학술대회논문집
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• 한국통계학회 2004년도 학술발표논문집
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• pp.67-72
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• 2004

Support vector machine (SVM) has been very successful in pattern recognition and function estimation problems for crisp data. This paper proposes a new method to evaluate interval linear and nonlinear regression models combining the possibility and necessity estimation formulation with the principle of SVM. For data sets with crisp inputs and interval outputs, the possibility and necessity models have been recently utilized, which are based on quadratic programming approach giving more diverse spread coefficients than a linear programming one. SVM also uses quadratic programming approach whose another advantage in interval regression analysis is to be able to integrate both the property of central tendency in least squares and the possibilistic property In fuzzy regression. However this is not a computationally expensive way. SVM allows us to perform interval nonlinear regression analysis by constructing an interval linear regression function in a high dimensional feature space. In particular, SVM is a very attractive approach to model nonlinear interval data. The proposed algorithm here is model-free method in the sense that we do not have to assume the underlying model function for interval nonlinear regression model with crisp inputs and interval output. Experimental results are then presented which indicate the performance of this algorithm.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 추계학술대회논문집
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• pp.916-919
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• 2004

The monopole theory has long been used to model air-pumped effect from the elastic cavities in car tire. This approach models the change of an air as a piston moving backward and forward on a spring and equates local air movements exactly with the volume changes of the system. Thus, the monopole theory has a restricted domain of applicability due to the usual assumption of a small amplitude acoustic wave equation and acoustic monopole theory. This paper describes an approach to predict the air-pumping noise of a car ave with CFD/Kirchhoff integral method. The type groove is simply modeled as piston-cavity-sliding door geometry and with the aid of CFD technique flow properties in the groove of rolling car tyre are acquired. And these unsteady flow data are used as a air-pumping source in the next Cm calculation of full tyre-road geometry. Acoustic far field is predicted from Kirchhoff integral method by using unsteady flow data in space and time, which is provided by the CFD calculation of full tyre-road domain. This approach can cover the non-linearity of acoustic monopole theory with the aid of using Non-linear governing equation in CFD calculation. The method proposed in this paper is applied to the prediction of air-pumping noise of modeled car tyre and the predicted results are qualitatively compared with the experimental data.

• 한국CDE학회논문집
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• 제2권2호
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• pp.77-84
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• 1997

This paper is concerning the development of multiple neural networks system of problem domains where the complete input space can be decomposed into several different regions, and these are known prior to training neural networks. We will adopt oblique decision tree to represent the divided input space and sel ect an appropriate subnetworks, each of which is trained over a different region of input space. The overall architecture of multiple neural networks system, called the federated architecture, consists of a facilitator, normal subnetworks, and tile networks. The role of a facilitator is to choose the subnetwork that is suitable for the given input data using information obtained from decision tree. However, if input data is close enough to the boundaries of regions, there is a large possibility of selecting the invalid subnetwork due to the incorrect prediction of decision tree. When such a situation is encountered, the facilitator selects a tile network that is trained closely to the boundaries of partitioned input space, instead of a normal subnetwork. In this way, it is possible to reduce the large error of neural networks at zones close to borders of regions. The validation of our approach is examined and verified by applying the federated neural networks system to the configuration design of a midship structure.

• Communications for Statistical Applications and Methods
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• 제8권3호
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• pp.651-659
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• 2001

Preference map is a widely used graphical method for the preference data set which is frequently encountered in the field of marketing research. This provides joint configuration usually in two dimensional space between "products" and their "attributes". Whereas the classical preference map adopts the ordinary least squares method in deriving map, the present article suggests the weighted least squares approach providing the better graphical display and interpretation compared to the classical one. Internet search engine data in Korea are analysed for illustration.

• 한국정보전자통신기술학회논문지
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• 제2권3호
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• pp.31-38
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• 2009

A process of identifying moving objects from data is typical task in many computer vision applications. In this paper, we propose a motion segmentation method that generally consists from background subtraction and foreground pixel segmentation. The Approximated Median Filter (AMF) was chosen to perform background modelling. To demonstrate the effectiveness of proposed approach, we tested it gray-scale video data as well as RGB color space.

• 천문학회보
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• 제38권2호
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• pp.33-33
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• 2013

We are developing empirical space weather (solar flare, solar proton event, and geomagnetic storm) forecast models based on solar data. In this talk we will review our main results and recent progress. First, we have examined solar flare (R) occurrence probability depending on sunspot McIntosh classification, its area, and its area change. We find that sunspot area and its increase (a proxy of flux emergence) greatly enhance solar flare occurrence rates for several sunspot classes. Second, a solar proton event (S) forecast model depending on flare parameters (flare strength, duration, and longitude) as well as CME parameters (speed and angular width) has been developed. We find that solar proton event probability strongly depends on these parameters and CME speed is well correlated with solar proton flux for disk events. Third, we have developed an empirical storm (G) forecast model to predict probability and strength of a storm using halo CME - Dst storm data. For this we use storm probability maps depending on CME parameters such as speed, location, and earthward direction. We are also looking for geoeffective CME parameters such as cone model parameters and magnetic field orientation. We find that all superstorms (less than -200 nT) occurred in the western hemisphere with southward field orientations. We have a plan to set up a storm forecast method with a three-stage approach, which will make a prediction within four hours after the solar coronagraph data become available. We expect that this study will enable us to forecast the onset and strength of a geomagnetic storm a few days in advance using only CME parameters and the WSA-ENLIL model. Finally, we discuss several ongoing works for space weather applications.

• Journal of Astronomy and Space Sciences
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• 제31권3호
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• pp.235-240
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• 2014

The communications link in a space program is a crucial point for upgrading its performance by handling data between spacecraft bus and payloads, because spacecraft's missions are related to the data handling mechanism using communications ports such as a controlled area network bus (CAN Bus) and a universal asynchronous receiver and transmitter (UART). The NEXTSat-1 has a lot of communications ports for performing science and technology missions. However, the top level system requirements for the NEXTSat-1 are mass and volume limitations. Normally, the communications for units shall be conducted by using point to point link which require more mass and volume to interconnect. Thus, our approach for the novel communications link in the NEXTSat-1 program is to use CAN and serializer and deserializer low voltage differential signal (SerDesLVDS) to meet the system requirements of mass and volume. The CAN Bus and SerDesLVDS were confirmed by using already defined communications link for our missions in the NEXTSat-1 program and the analysis results were reported in this study in view of data flow and size analysis.

• 한국우주과학회:학술대회논문집(한국우주과학회보)
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• 한국우주과학회 2004년도 한국우주과학회보 제13권2호
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• pp.347-350
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• 2004

A space radiation analysis has been used to evaluate an ability of electronic equipment boxes or spacecrafts to endure various radiation effects, so it helps design thicknesses of structure and allocate components to meet the radiation requirements. A comparison study of space radiation dose analysis programs SPENVIS Sectoring Tool (SST) and SIGMA II is conducted through some structure cases, simple sphere shell, box and representative satellite configurations. The results and a discussion of comparison will be given. A general comparison will be shown for understanding those programs. The both programs use the same strategy, solid angle sectoring with ray-tracing method to produce an approximate dose at points in representative simple and complex models of spacecraft structures. Also the particle environment data corresponding to mission specification and radiation transport data are used as input data. But there are distinctions between them. The specification of geometry model and its input scheme, the assignment of dose point and the numbers, the prerequisite programs and ways of representing results will be discussed. SST is a web-based interactive program for sectoring analysis of complex geometries. It may be useful for a preliminary dose assessment with user-friendly interfaces and a package approach. SIGMA II is able to obtain from RSICC (Radiation Safety Information Computational Center) as a FOR-TRAN 77 source code. It may be suitable for either parametric preliminary design or detailed final design, e.g. a manned flight or radiation-sensitive component configuration design. It needs some debugs, recompiling and a tedious work to make geometrical quadric surfaces for actual spacecraft configuration, and has poor documentation. It is recommend to vist RSICC homepage and GEANT4/SSAT homepage.

• 한국실내디자인학회논문집
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• 제14권2호
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• pp.169-177
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• 2005

The purpose of this study was to find the characteristics of the exhibition space planning methodology as 'Spatialization of Knowledge' through analyzation of the spatial structure in the contemporary museum architecture. The result of this study is expected to apply in designing an exhibition space and may become a target point. Further more this study can result a museum design to assist actual museum to fully function and play a role as a service facility for users by containing broad knowledge and fair understanding of user's needs in museum planning. Basic survey of museum architecture history will help visualizing conceptual structure of the museum exhibition and the 'Space Syntax' method has been used to make this conceptual data more objective. This study found that the contemporary museums most likely to include in its planning the various spatial organization in order to convey knowledge. The result reflects the needs of modern society which shows the design accepting individuality in society with variety of needs. And this also explains that museum space organization has to reflect various ways or methods of conveying knowledge. In addition, users have tendency to prefer more open space organization for easy access and approach in exhibition environment. It is clear to see the change in today's viewing pattern that the users prefer flexible exhibition space where they can be more proactive in receiving knowledge by following their own circulation over architecturally constrained circulation pattern within the exhibition area.