• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.2
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• pp.44-58
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• 2014

In this study, a standard vector data model was developed for interoperability of river-geospatial information and for verification purpose the applicability of the standard vector model was evaluated using a model to RIMGIS vector data at Changnyeong-Hapcheon & Gangjung-Goryeong irrigation watershed. The standards from ISO and OGC were analyzed and the river geospatial data model standard was established by applying the standards. The ERD was designed based on the analysis information on data characteristics and relationship. The verification of RIMGIS vector data included points, lines and polygon to develope GDM was carried out by comparing with the data by layer. This conducting comparison of basic spatial data and attribute data to each record and spatial information vertex. The error in the process of conversion was 0 %, indicating no problem with model. Our Geospatial Data Model presented in this study provides a new and consistent format for the storage and retrieval of river geospatial data from connected database. It is designed to facilitators integrated analysis of large data sets collected by multiple institutes.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.634-636
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• 2004

3차원 공간상에 분포되어 있는 정들로부터 기하정보를 재구성하여 렌더링 할 때 법선 벡터가 필요하다. 이 점들은 서로간의 연결성 정보가 없고 법선 벡터가 없기 때문에 음영 효과를 표현 할 수 없다. 본 논문에서는 점들의 연결성 정보를 추정하여 법선 벡터를 구하는 과정에서 GPU를 사용하는 방법을 제안한다 GPU로 법선 벡터를 계산할 경우 CPU의 부하가 줄게 되고 계산 시간도 감소된다 이 방법을 점 렌더링에 적용하여 법선 벡터를 신속하게 계산하고 가시성 검사와 음영처리를 효과적으로 할 수 있도록 한다.

• Journal of Korea Multimedia Society
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• v.16 no.4
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• pp.418-429
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• 2013

This paper presents a GIS vector map data compression scheme based on hybrid polyline simplification method and SEC(spatial energy compaction). The proposed method extracts all layers which contain polylines in the GIS vector map and compress all polylines in extracted layers by the hybrid polyline simplification and SEC based on MAE(minimum area error) for each segment in the line. The proposed simplification and SEC increase the compression ratio while preserving the shape quality. We analyze the visual aspects and compression efficiency between the original GIS vector map and the compressed map. From experimental results, we verify that our method has the higher compression efficiency and visual quality than conventional methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.48-52
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• 2008

In this paper, we propose a new selective subspace projection method in order to recognize the occlusive face image effectively. The conventional subspace projection method is project to basis image using a full image of face. The face recognition rate has reduced because the face characteristic is easy to be distorted by occlusion. To overcome this problem, the proposed method first decide to occlusion. If it hasn't an occlusion, we get the feature vectors with total basis projection using the conventional subspace projection method. If it has an occlusion, we get one with partial basis projection. We get better recognition rate than conventional PCA and NMF using AR face database with occlusive face images.

• Journal of the Korea Society of Computer and Information
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• v.19 no.11
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• pp.53-61
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• 2014

In this paper, we propose a method using an image received by the depth camera in order to separate the wall in a three-dimensional space indoor environment. Results of the paper may be used to provide valuable information on the three-dimensional space. For example, they may be used to recognize the indoor space, to detect adjacent objects, or to project a projector on the wall. The proposed method first detects a normal vector at each point by using the three dimensional coordinates of points. The normal vectors are then clustered into several groups according to similarity. The RANSAC algorithm is applied to separate out planes. The domain knowledge helps to determine the wall among planes in an indoor environment. This paper concludes with experimental results that show performance of the proposed method in various experimental environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.4A
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• pp.269-277
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• 2012

When there are mismatches between the beamforming steering vector and the array response vector for the desired signal, the performance can be severely degraded as the adaptive array attempts to suppress the desired signal as well as interferences. In this paper, an robust method is proposed for the adaptive array in the presence of both direction errors and random errors in the steering vector. The proposed method first finds a signal-plus-interference subspace (SIS) from the correlation matrix, which in turn is exploited to extract an interference subspace based on the structure of a uniform linear array (ULA), the effect of the desired signal direction vector being reduced as much as possible. Then, the weight vector is attained to be orthogonal to the interference subspace. Simulation shows that the proposed method, in terms of signal-to-interference plus noise ratio (SINR), outperforms existing ones such as the doubly constrained robust Capon beamformer (DCRCB).

• The Korean Journal of Applied Statistics
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• v.37 no.6
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• pp.751-768
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• 2024

In this paper, we consider a classification model based on support vector machines (SVM) for shape data, which is utilized in various application areas such as computer vision, medical imaging, and so on. When shape is represented as a function, we need a shape distance invariant to translation, scaling, rotation, and reparameterization. We adopt the elastic shape analysis framework based on the square-root velocity function (SRVF) representation. The framework enables us to analyze shape data on a unit hypersphere instead of a Riemannian manifold, the original representation space. The data could be even linearized using a tangent space at the mean of the transformed sample shapes. We apply the SVM to the tangent Euclidean vectors after projection. We design simulation studies for shape classification by generating planar curves from a mixture of von Mises-Fisher distributions. We analyze real data of algal shapes, and compare its performance with other statistical classification methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.227-232
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• 2016

3D body scan data are used widely in various fields to make products and living spaces for superior human body fitness. Based on the 3D measurements of human bodies for teens in Size Korea 2013, this research provides a way of finding the representative body sizes and 3D body scan data. First, a multi-dimensional vector space consisting of many measurement items was projected onto a 2D vector space with circumference and length components via factor analysis. The representative body sizes and 3D scan data close to these values were obtained via the Mahalanobis distance in 2D space. Considering the adolescent growth pattern shown on this 2D space, males were divided into 4 age groups and females were divided into 3 age groups. Using the eigenbodies corresponding to the column vectors of the component score coefficient matrix, the representative body sizes of 13 measurement items (male) and 14 measurement items (female) for each age group were calculated. The representative body sizes and 3D scan data are very useful for modeling representative 3D human figures.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.11A
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• pp.1946-1956
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• 2001

In this paper, we propose a novel 2-D partial matching algorithm based on model-based stochastic analysis of feature correspondences in a relation vector space, which is quite robust to shape variations as well as invariant to geometric transformations. We represent an object using the ARG (Attributed Relational Graph) model with features of a set of relation vectors. In addition, we statistically model the partial occlusion or noise as the distortion of the relation vector distribution in the relation vector space. Our partial matching algorithm consists of two-phases. First, a finite number of candidate sets areselected by using logical constraint embedding local and structural consistency Second, the feature loss detection is done iteratively by error detection and voting scheme thorough the error analysis of relation vector space. Experimental results on real images demonstrate that the proposed algorithm is quite robust to noise and localize target objects correctly even inseverely noisy and occluded scenes.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.4
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• pp.498-503
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• 2019

Electric propulsion ships are gaining widespread interest in the marine industry owing to extreme air pollution concerns. Consequently, several studies are actively being conducted for improving the power quality. Various methods have been developed that incorporate passive filters, notch filters, and active filters for reducing the harmonic content in the input current of a conventional diode front end rectifier. Among such filters, the active front end (AFE) rectifier is considered as an excellent technology. In this paper, current control for an AFE rectifier employing space vector PWM (Pulse Width Modulation) is proposed. Conventional current control methods for the AFE rectifier, hysteresis, SPWM (Sinusoidal Pulse Width Modulation), and SVPWM (Space Vector Pulse Width Modulation) were simulated by employing the PSIM software tool for analysis and comparisons. The results corroborate that SVPWM has the simplest structure and provides the best performance.