• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.535-537
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• 2001

3D MMORPG(Massive Multi-play Outline Role Playing Game) 게임은 넓은 3차원원지형을 실시간으로 표현되어야 하며, 많은 어려움이 따른다. 본 논문에서는 이러한 지형 처리를 위하여 메쉬나 버텍스, 혹은 폴리곤으로 사실적인 지형처리와 렌드링 속도 향상을 위하여 3차원 폴리곤을 동적으로 생성시키는 방법을 이용하려고 한다. 넓은 지형을 처리하기 위해서는 전체를 한번에 표현하기보다는 페이지 단위로 처리하기 위하여 격자화된 타일로 이루어진 맵으로 처리할 수 있다. Height field 처리 기법은 일정한 영역을 페이지 단위로 구분하고 처리할 수 있다. 옥트리를 이용하여 공간을 입체적인 컬링 방법으로 분할하고, 이를 세부 수준으로 나누어 처리하기 위해 CLOD(Continuous Level of Detail) 개념을 적용할 수 있다. 거리의 변화에 따라 지명을 표현하는 vertex들을 병합 또는 삭제함으로써 그 표현의 정도를 동적으로 달리 할 수 있는 CLOD를 이용하여 카메라의 위치와 방향에 따라 적절한 폴리곤을 생성해 낼 수 있다. 본 논문은 3 차원의 넓은 외부 지형을 실시간으로 처리할 경우 발생되는 그래픽 문제를 해결하기 위해 사용되는 방법 중에서 대표적인 방법을 통하여 효율적인 처리 기법을 제시하려 한다.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.6
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• pp.11-20
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• 1997

This paper proposes a modified dynamic programming for finding the correspondence between right and left images. A dynamic programming is based on the intensity of images for stereo matching. But htis method is intended to mismatch at uniformed intensity region. To reduce thd mismatching, the stereo images are segmented to various regions with respective uniform intensity, and the different cost function has applied to the segmented region during the dynamci programming. Cost function costains jump cost. And jump cost included two parameter .alpha. and .beta. which have influence on minimum cost path. Experimental results show that the 3D shape of some stereo pairs cna be finely obtained by this proposed algorithm.

• The KIPS Transactions:PartA
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• v.14A no.7
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• pp.435-442
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• 2007

This paper is concerned with the mesh segmentation problem that can be applied to diverse applications such as texture mapping, simplification, morphing, compression, and shape matching for 3D mesh models. The mesh segmentation is the process of dividing a given mesh into the disjoint set of sub-meshes. We propose a method for segmenting meshes by simultaneously reflecting global and local geometric characteristics of the meshes. First, we extract sharp vertices over mesh vertices by interpreting the curvatures and convexity of a given mesh, which are respectively contained in the local and global geometric characteristics of the mesh. Next, we partition the sharp vertices into the $\kappa$ number of clusters by adopting the $\kappa$-means clustering method [29] based on the Euclidean distances between all pairs of the sharp vertices. Other vertices excluding the sharp vertices are merged into the nearest clusters by Euclidean distances. Also we implement the proposed method and visualize its experimental results on several 3D mesh models.

• Journal of the Korea Society of Computer and Information
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• v.16 no.8
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• pp.57-66
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• 2011

In this paper, it is proposed for algorithm to detect human efficiently using a edge symmetry and gradient directional characteristics in realtime by the feature extraction in a single input image. Proposed algorithm is composed of three stages, preprocessing, region partition of human candidates, verification of candidate regions. Here, preprocessing stage is strong the image regardless of the intensity and brightness of surrounding environment, also detects a contour with characteristics of human as considering the shape features size and the condition of human for characteristic of human. And stage for region partition of human candidates has separated the region with edge symmetry for human and size in the detected contour, also divided 1st candidates region with applying the adaboost algorithm. Finally, the candidate region verification stage makes excellent the performance for the false detection by verifying the candidate region using feature vector of a gradient for divided local area and classifier. The results of the simulations, which is applying the proposed algorithm, the processing speed of the proposed algorithms is improved approximately 1.7 times, also, the FNR(False Negative Rate) is confirmed to be better 3% than the conventional algorithm which is a single structure algorithm.

• Journal of Microbiology and Biotechnology
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• v.12 no.3
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• pp.522-525
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• 2002

A very rapid and efficient separation technique for cellular rhizobial cyclosophoraoses was developed based on fractional precipitation and partition chromatography. Cyclosophoraoses are known to function in the osmotic regulation and root nodule formation of legumes during the nitrogen fixation process. Cyclosophoraoses are produced as unbranched cyclic (1longrightarrow12)-${\beta}$-D-glucans in Agrobacterium or Rhizobium species. Recent research has shown that cyclosophoraoses can form inclusion complexation with various unstable or insoluble guest chemicals, thereby implying great potential for industrial application. Typical separation of pure cellular cyclosophoraoses has been so far carried out by several time-consuming steps, including size exclusion, anion exchange, and desalting liquid chromatographies, with a relatively poor recovery. However, the proposed method demonstrated that the successive application of fractional ethanol precipitation and one step of silica gel-based flash column chromatography was enough to simultaneously purify neutral or anionic forms of cyclosophoraoses. This novel technique is very rapid and provides a high recovery.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.31-40
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• 2012

Face recognition refers to the process of identifying individuals based on their facial features. It has recently become one of the most popular research areas in the fields of computer vision, machine learning, and pattern recognition because it spans numerous consumer applications, such as access control, surveillance, security, credit-card verification, and criminal identification. However, illumination variation on face generally cause performance degradation of face recognition systems under practical environments. Thus, this paper proposes an novel face recognition system using a fusion approach based on local binary pattern and two-dimensional principal component analysis. To minimize illumination effects, the face image undergoes the local binary pattern operation, and the resultant image are divided into two sub-images. Then, two-dimensional principal component analysis algorithm is separately applied to each sub-images. The individual scores obtained from two sub-images are integrated using a weighted-summation rule, and the fused-score is utilized to classify the unknown user. The performance evaluation of the proposed system was performed using the Yale B database and CMU-PIE database, and the proposed method shows the better recognition results in comparison with existing face recognition techniques.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.32 no.3
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• pp.241-248
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• 1996

The relationship between width of line target and distance at the limit of discrimination was examined by means of the behavioral method, for filefish Stephanolepis cirrhifer from 11 to 15cm body length. Target distance was distance from beginning of partition board to target plate, and was varied from 50cm to 200cm. The target plate was made of white acrylic resin with a vertical black line in the center. The width of line target was varied from 0.2mm to 8.0mm. Fish were trained to respond to a line target and the width of line target reduced until the minimum width required to elicit a response was established. Rate of success was expressed as the percentage of target choices in 90 trials. The line acuity of filefish was found to be 0.58 at a target distance of 50cm. The rate of success decreased slowly as line target width decreased from 8.0mm to 1.5mm, and decreased suddenly for target widths less than about 1.5mm. The width of the line target D(mm) at the limit of discrimination was shown to be an exponential function of the target distance L(cm) as follows : D=exp(9.947$\times$$10^-3$.L+0.146)

• Korean Chemical Engineering Research
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• v.61 no.4
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• pp.523-541
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• 2023

As accessibility to 3D printers increases, there is a growing frequency of exposure to chemicals associated with 3D printing. However, research on the toxicity and harmfulness of chemicals generated by 3D printing is insufficient, and the performance of toxicity prediction using in silico techniques is limited due to missing molecular structure data. In this study, quantitative structure-activity relationship (QSAR) model based on data-centric AI approach was developed to predict the toxicity of new 3D printing materials by imputing missing values in molecular descriptors. First, MissForest algorithm was utilized to impute missing values in molecular descriptors of hazardous 3D printing materials. Then, based on four different machine learning models (decision tree, random forest, XGBoost, SVM), a machine learning (ML)-based QSAR model was developed to predict the bioconcentration factor (Log BCF), octanol-air partition coefficient (Log Koa), and partition coefficient (Log P). Furthermore, the reliability of the data-centric QSAR model was validated through the Tree-SHAP (SHapley Additive exPlanations) method, which is one of explainable artificial intelligence (XAI) techniques. The proposed imputation method based on the MissForest enlarged approximately 2.5 times more molecular structure data compared to the existing data. Based on the imputed dataset of molecular descriptor, the developed data-centric QSAR model achieved approximately 73%, 76% and 92% of prediction performance for Log BCF, Log Koa, and Log P, respectively. Lastly, Tree-SHAP analysis demonstrated that the data-centric-based QSAR model achieved high prediction performance for toxicity information by identifying key molecular descriptors highly correlated with toxicity indices. Therefore, the proposed QSAR model based on the data-centric XAI approach can be extended to predict the toxicity of potential pollutants in emerging printing chemicals, chemical process, semiconductor or display process.

• The Journal of the Korea Contents Association
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• v.9 no.4
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• pp.34-44
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• 2009

Integrating 3D data acquired in multiple views is one of the most important techniques in 3D modeling. However, due to the presence of surface scanning noise and the modification of vertices consisting of surface, the existing integration methods are inadequate to some applications. In this paper, we propose a method of integrating surfaces by using the local surface topology. We first find all boundary vertex pairs satisfying a prescribed geometric condition on adjacent surfaces and then compute 2D planes suitable to each vertex pairs. Using each vertex pair and neighbouring boundary vertices projected to their 2d plane, we produce polygons and divide them to the triangles which will be inserted to empty space between the adjacent surfaces. A proposed method use local surface topology and not modify the vertices consisting of surface to integrate several of surfaces to one surface, so that it is robust and simple. We also integrate the transformed textures to a 2D image plane computed by using a cylindrical projection to composite 3D textured model. The textures will be integrated according to the partition lines which considering attribute of face object. Experimental results on real object data show that the suggested method is simple and robust.

• Korean Journal of Computational Design and Engineering
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• v.4 no.3
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• pp.173-179
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• 1999

In reverse engineering, when a shape containing multi-patched surfaces is digitized, the boundaries of these surfaces should be detected. The objective of this paper is to introduce a computationally efficient segmentation technique for extracting edges, ad partitioning the 3D measuring point data based on the location of the boundaries. The procedure begins with the identification of the edge points. An automatic edge-based approach is developed on the basis of local geometry. A parametric quadric surface approximation method is used to estimate the local surface curvature properties. the least-square approximation scheme minimizes the sum of the squares of the actual euclidean distance between the neighborhood data points and the parametric quadric surface. The surface curvatures and the principal directions are computed from the locally approximated surfaces. Edge points are identified as the curvature extremes, and zero-crossing, which are found from the estimated surface curvatures. After edge points are identified, edge-neighborhood chain-coding algorithm is used for forming boundary curves. The original point set is then broke down into subsets, which meet along the boundaries, by scan line algorithm. All point data are applied to each boundary loops to partition the points to different regions. Experimental results are presented to verify the developed method.