• Journal of Information Processing Systems
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• 제14권5호
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• pp.1176-1194
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• 2018

The object classification using the images' contents is a big challenge in computer vision. The superpixels' information can be used to detect and classify objects in an image based on locations. In this paper, we proposed a methodology to detect and classify the image's pixels' locations using enhanced bag of words (BOW). It calculates the initial positions of each segment of an image using superpixels and then ranks it according to the region score. Further, this information is used to extract local and global features using a hybrid approach of Scale Invariant Feature Transform (SIFT) and GIST, respectively. To enhance the classification accuracy, the feature fusion technique is applied to combine local and global features vectors through weight parameter. The support vector machine classifier is a supervised algorithm is used for classification in order to analyze the proposed methodology. The Pascal Visual Object Classes Challenge 2007 (VOC2007) dataset is used in the experiment to test the results. The proposed approach gave the results in high-quality class for independent objects' locations with a mean average best overlap (MABO) of 0.833 at 1,500 locations resulting in a better detection rate. The results are compared with previous approaches and it is proved that it gave the better classification results for the non-rigid classes.

• 소성∙가공
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• 제16권7호
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• pp.538-548
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• 2007

In this paper, a novel approach which enables rapid die surface modification for sheet metal forming process is proposed. In this method an implicit surface which interpolates a given set of control points and displacement constraints is generated to compute the displacements at arbitrary points located on die surface. The proposed method does not depend on the underlying surface representation type and is affected neither by its complexity nor by its quality. In addition, the domain decomposition method is introduced in order to treat large surface model. The global domain of interest is divided into smaller domains where the problem can be solved locally. And then the local solutions are combined together to obtain a global solution. In order to verify the validity and effectiveness of the proposed method, various surface modifications are carried out fur three kinds of die surface model including polygonal surface composed of triangular and rectangular meshes, polynomial surface and NURBS surface.

• Journal of Computing Science and Engineering
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• 제4권3호
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• pp.207-224
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• 2010

This paper presents a compression scheme for mesh geometry, which is suitable for mobile graphics. The main focus is to enable real-time decoding of compressed vertex positions while providing reasonable compression ratios. Our scheme is based on local quantization of vertex positions with mesh partitioning. To prevent visual seams along the partitioning boundaries, we constrain the locally quantized cells of all mesh partitions to have the same size and aligned local axes. We propose a mesh partitioning algorithm to minimize the size of locally quantized cells, which relates to the distortion of a restored mesh. Vertex coordinates are stored in main memory and transmitted to graphics hardware for rendering in the quantized form, saving memory space and system bus bandwidth. Decoding operation is combined with model geometry transformation, and the only overhead to restore vertex positions is one matrix multiplication for each mesh partition. In our experiments, a 32-bit floating point vertex coordinate is quantized into an 8-bit integer, which is the smallest data size supported in a mobile graphics library. With this setting, the distortions of the restored meshes are comparable to 11-bit global quantization of vertex coordinates. We also apply the proposed approach to compression of vertex attributes, such as vertex normals and texture coordinates, and show that gains similar to vertex geometry can be obtained through local quantization with mesh partitioning.

• 한국컴퓨터정보학회논문지
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• 제11권3호
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• pp.31-39
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• 2006

본 논문에서는 지능로봇. 지능형자동차. 지능형빌딩 등에 다양하게 활용될 수 있는 3차원 환경과 여기에 포함된 물체의 실시간 인식을 위한 새로운 접근 방법을 제안한다. 본 논문에서는 먼저 사람이 환경을 인식하고 상호작용하는 데 사용하는 3가지 기본 원칙을 설정하고, 이 기본 원칙들을 이용하여 실시간 3차원 환경 및 물체 인식을 위한 통합된 방법을 제시한다. 이들 3가지 기본 원칙은 다음과 같다. 첫째, 전역 적인 평면 특징들을 인식함으로써 작업환경의 기하학적 구조에 대한 개략적 특성화를 고속으로 진행한다. 둘째, 작업환경 속에서 기존에 알려진 물체를 먼저 빠르게 인식하고 이를 데이터베이스 내에 저장되어 있는 물체의 모델로 교체한다. 셋째, 다중 해상도 Octree 표현 방법을 이용하여 기타 영역을 주어진 작업의 필요에 따라 적응적으로 실시간 모델링 한다. 본 논문에서는 3차원 SIFT로 언급되는 3차원 좌표를 가지는 SIFT특징들을 3차원 좌표정보와 함께 확장하여 사용함으로서 전역적 평면 특징의 빠른 추출, 고속의 물체 인식, 빠른 장면 정합 등의 기능에 활용하고 이와 동시에 스테레오 카메라로부터 입력되는 3차원 좌표의 잡음과 불완전성을 극복한다.

• The Journal of Asian Finance, Economics and Business
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• 제7권2호
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• pp.131-141
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• 2020

This study examines the poverty indicators in Northeast region of Thailand by adopting the global Multidimensional Poverty Index (MPI) methodology and the national survey of Minimum Basic Needs (MBN) of Thailand. Data are collected from three different districts in Khon Kaen province namely: Khok Po Chai, Sam Sung, and Nam Pong. The sample size is 187 households. Data analysis uses Ordinary Least Square (OLS) regression approach and includes 7 dimensions of poverty (health, environment, education, economy, Thai value, asset? empowerment, and digital literacy) with a total of 41 indicators. This study has found that poverty indicators in Khon Kaen province remains centered around the aspects of health and employment dimensions. While a change of family structure in the Thai society since 1960s reduces the family size, household saving substantially increases over the years. The effects of health dimension in poverty, on the other hand, appears on the other poverty dimension of Thai value, which include (1) a bad living habit of head of household (smoke or alcohol consumption) that links with illness and disease, (2) religious practice, and (3) chronic illness. Lastly, there are income gaps of different careers in the area, which suggests the issue of income inequality.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.522-524
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• 1999

This paper addresses the systematic approach to the fuzzy modeling of the class of complex and uncertain nonlinear systems. While the conventional genetic algorithm (GA) only searches the global solution, Virus-Evolutionary Genetic Algorithm(VEGA) can search the global and local optimal solution simultaneously. In the proposed method the parameter and the structure of the fuzzy model are automatically identified at the same time by using VEGA. To show the effectiveness and the feasibility of the proposed method, a numerical example is provided. The performance of the proposed method is compared with that of conventional GA.

• Journal of Mechanical Science and Technology
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• 제17권3호
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• pp.449-456
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• 2003

In this study, numerical and experimental analysis on the spray atomization characteristics of a GDI injector is performed. For numerical approach, four hybrid models that are composed of primary and secondary breakup model are considered. Concerning the primary breakup, a conical sheet disintegration model and LISA model are used. The secondary breakup models are made based on the DDB model and RT model. The global spray behavior is also visualized by the shadowgraph technique and local Sauter mean diameter and axial mean velocity are measured by using phase Doppler particle analyzer Based on the comparison of numerical and experimental results, it is shown that good agreement is obtained in terms of spray developing process and spray tip penetration at the all hybrid models. However, the hybrid breakup models show different prediction of accuracy in the cases of local SMD and the spatial distribution of breakup.

• Management Science and Financial Engineering
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• 제8권1호
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• pp.53-75
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• 2002

In this Paper, an attempt is made to establish a learning framework for robust planning and real-time execution control. Necessary definitions and concepts are clearly presented to describe real-time operational control in response to Plan disruptions. A general mathematical framework for disruption recovery is also laid out. Global disruption model is decomposed into suitable number of local disruption models. Execution Pattern is designed to capture local disruptions using decomposed-reverse neural mappings, and to further demonstrate how the decomposed-reverse mappings could be applied for solving disrubtion recovery problems. Two decomposed-reverse neural mappings, N-K-M and M-K-N are employed to produce transportation solutions in react-time. A potential extension is also discussed using the proposed mapping principle and other hybrid heuristics. Experimental results are provided to verify the proposed approach.

• 대한전기학회논문지:전력기술부문A
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• 제48권12호
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• pp.1498-1506
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• 1999

In this paper, a hybridization of Evolutionary Strategy (ES) and a Two-Phase Neural Network(TPNN) is applied to the optimal environmental and economic operation. As the evolutionary computation, ES is to search for the global optimum based on natural selection and genetics but it shows a defect of reducing the convergence rate in the latter part of search, and often does not search the exact solution. Also, neural network theory as a local search technique can be used to search a more exact solution. But it also has the defect that a solution frequently sticks to the local region. So, new algorithm is presented as hybrid methods by combining merits of two methods. The hybrid algorithm has been tested on Emission Constrained Economic Dispatch (ECED) problem and Weighted Emission Economic Dispatch (WEED) problem for optimal environmental and economic operation. The result indicated that the hybrid approach can outperform the other computational efficiency and accuracy.

• 영어어문교육
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• 제12권2호
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• pp.127-152
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• 2006

For the past 20 years the process approach to writing has been popular in second language writing classrooms. However, there have been very few studies conducted in Korea with regard to the composing processes and the effects of proficiency on writers' usage. The present study attempts to begin to fill this gap. Three groups of college students with different writing proficiency participated in the study: the advanced group, the intermediate group, and the beginning group. The verbal protocol of their writing processes revealed that they approached writing tasks differently. While the advanced writers focused on generating texts and ideas and examined their writing at both global and local levels, the other two groups of students tended to focus on evaluating text at the local level and generated fewer ideas and less text. The findings from this study are then compared to those of some major studies of the composing process as conclusions are subsequently drawn about the specific needs of Korean college writers.