• Honam Mathematical Journal
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• v.30 no.2
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• pp.283-297
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• 2008

The notion of IVF contra (${\alpha}$-)open ((${\alpha}$-)closed) mappings is introduced, and their characterizations are given. The relationship between IVF contra open (closed) mappings and IVF contra ${\alpha}$-open (${\alpha}$-closed) mappings are discussed.

• Communications of the Korean Mathematical Society
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• v.21 no.3
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• pp.497-514
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• 2006

In this paper, we used the supra fuzzy topology which generated from a fuzzy bitopological space [1] to introduce and study the concepts of continuity (resp. openness, closeness) of mapping, separation axioms and compactness for a fuzzy bitopological spaces. Our definition preserve much of the correspondence between concepts of fuzzy bitopological spaces and the associated fuzzy topological spaces.

• Journal of Information Processing Systems
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• v.10 no.1
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• pp.23-35
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• 2014

Recently, novel application areas in digital geometry processing, such as simulation, dynamics, and medical surgery simulations, have necessitated the representation of not only the surface data but also the interior volume data of a given 3D object. In this paper, we present an efficient framework for the shape approximations of spherical solid objects based on trivariate B-splines. To do this, we first constructed a smooth correspondence between a given object and a unit solid cube by computing their harmonic mapping. We set the unit solid cube as a rectilinear parametric domain for trivariate B-splines and utilized the mapping to approximate the given object with B-splines in a coarse-to-fine manner. Specifically, our framework provides user-controllability of shape approximations, based on the control of the boundary condition of the harmonic parameterization and the level of B-spline fitting. Experimental results showed that our method is efficient enough to compute trivariate B-splines for several models, each of whose topology is identical to a solid sphere.

• Journal of KIBIM
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• v.11 no.4
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• pp.42-52
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• 2021

Paneling building facades is one of the essential procedures in building construction. Traditionally, it has been an easy task of simply projecting paneling patterns drawn in drawing boards onto 3d building facades. However, as many organic or curved building shapes are designed and constructed in modern architectural practices, the traditional one-to-one projection is becoming obsolete for the building types of the kind. That is primarily because of the geometrical discrepancies between 2d drawing boards and 3d curved building surfaces. In addition, curved compound surfaces are often utilized to accommodate the complicated spatial programs, building codes, and zoning regulations or to achieve harmonious geometrical relationships with neighboring buildings in highly developed urban contexts. The use of the compound surface apparently makes the traditional paneling pattern projection more challenging. Various mapping technics have been introduced to deal with the inabilities of the projection methods for curved facades. The mapping methods translate geometries on a 2d surface into a 3d building façade at the same topological locations rather than relying on Euclidean or Affine projection. However, due to the intrinsic differences of the planar 2d and curved 3d surfaces, the mapping often comes with noticeable distortions of the paneling patterns. Thus, this paper proposes a practical method of drawing paneling patterns directly on a curved compound surface utilizing Geodesic, which is faithful to any curved surface, to minimize unnecessary distortions.

• Journal of Environmental Science International
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• v.22 no.5
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• pp.543-554
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• 2013

Acoustic Doppler Current Profilers (ADCPs) are increasingly popular in the river research and management communities being primarily used for estimation of stream flows. ADCPs capabilities, however, entail additional features that are not fully explored, such as morphological representation of river or reservoir bed based upon multi-beam depth measurements. In addition to flow velocity, ADCP measurements include river bathymetry information through the depth measurements acquired in individual 4 or 5 beams with a given oblique angle. Such sounding capability indicates that multi-beam ADCPs can be utilized as an efficient depth-sounder to be more capable than the conventional single-beam eco-sounders. The paper introduces the post-processing algorithms required to deal with raw ADCP bathymetry measurements including the following aspects: a) correcting the individual beam depths for tilt (pitch and roll); b) filtering outliers using SMART filters; d) transforming the corrected depths into geographical coordinates by UTM conversion; and, e) tag the beam detecting locations with the concurrent GPS information; f) spatial representation in a GIS package. The developed algorithms are applied for the ADCP bathymetric dataset acquired from Han-Cheon in Jeju Island to validate themselves applicability.

• The Journal of Korea Robotics Society
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• v.9 no.2
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• pp.104-110
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• 2014

Mapping is a fundamental element for robotic services. There are available many types of map data representation such as grid map, metric map, topology map, etc. As more robots are deployed for services, more chances of exchanging map data among the robots emerge and standardization of map data representation (MDR) becomes more valuable. Currently, activities in developing MDR standard are underway in IEEE Robotics and Automation Society. The MDR standard is for a common representation and encoding of the two-dimensional map data used for navigation by mobile robots. The standard focuses on interchange of map data among components and systems, particularly those that may be supplied by different vendors. This paper aims to introduce MDR standard and its application to map merging. We have applied the basic structure of the MDR standard to a grid map and Voronoi graph as a kind of topology map and performed map merging between two different maps. Simulation results show that the proposed MDR is suitable for map data exchange among robots.

• The KIPS Transactions:PartB
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• v.8B no.5
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• pp.515-522
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• 2001

Feature-based similarity retrieval become an important research issue in image database systems. The features of image data are useful to discrimination of images. In this paper, we propose the highspeed k-Nearest Neighbor search algorithm based on Self-Organizing Maps. Self-Organizing Map(SOM) provides a mapping from high dimensional feature vectors onto a two-dimensional space. A topological feature map preserves the mutual relations (similarity) in feature spaces of input data, and clusters mutually similar feature vectors in a neighboring nodes. Each node of the topological feature map holds a node vector and similar images that is closest to each node vector. We implemented about k-NN search for similar image classification as to (1) access to topological feature map, and (2) apply to pruning strategy of high speed search. We experiment on the performance of our algorithm using color feature vectors extracted from images. Promising results have been obtained in experiments.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.4
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• pp.429-438
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• 2011

LiDAR technology is a combination of laser ranging, satellite positioning technology and digital image technology for study and determination with high accuracy of the true earth surface features in 3 D. Laser scanning data is typically a points cloud on the ground, including coordinates, altitude and intensity of laser from the object on the ground to the sensor (Wehr & Lohr, 1999). Data from laser scanning can produce products such as digital elevation model (DEM), digital surface model (DSM) and the intensity data. In Vietnam, the LiDAR technology has been applied since 2005. However, the application of LiDAR in Vietnam is mostly for topological mapping and DEM establishment using point cloud 3D coordinate. In this study, another application of LiDAR data are present. The study use the intensity image combine with some other data sets (elevation data, Panchromatic image, RGB image) in Bacgiang City to perform land cover classification using neural network method. The results show that it is possible to obtain land cover classes from LiDAR data. However, the highest accurate classification can be obtained using LiDAR data with other data set and the neural network classification is more appropriate approach to conventional method such as maximum likelyhood classification.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.507-517
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• 2003

Self-organizing map (SOM) has been developed mainly by T. Kohonen and his colleagues as a unsupervised learning neural network. Because of its topological ordering property, SOM is known to be very useful in pattern recognition and text information retrieval areas. Recently, data miners use Kohonen´s mapping method frequently in exploratory analyses of large data sets. One problem facing SOM builder is that there exists no sensible criterion for evaluating goodness-of-fit of the map at hand. In this short communication, we propose valid evaluation procedures for the Kohonen SOM of any size. The methods can be used in selecting the best map among several candidates.

• Korean Journal of Mathematics
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• v.28 no.2
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• pp.361-378
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• 2020

The most apparent aspect of the present study is to introduce a new sequence space 𝚽^⋆(𝓛_p) derived by double Euler-Totient matrix operator. We examine its topological and algebraic properties and give an inclusion relation. In addition to those, the α-, β(bp)- and γ-duals of the space 𝚽^⋆(𝓛_p) are determined and finally, some 4-dimensional matrix mapping classes related to this space are characterized.