• 한국터널지하공간학회 논문집
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• 제7권1호
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• pp.89-96
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• 2005

사회 전반에 걸친 디지털 혁명에 따라 IT를 기반으로 하는 다양한 정보화 터널시공기법이 개발되고 있으며 터널시공시 의사결정체계의 일환으로 적용되고 있다. 따라서 본 연구에서는 PDA를 이용한 터널시공의 정보화에 대하여 기술하였으며, 특히 시공중 발생하는 각종 막장면 데이터를 실시간으로 입 출력 및 저장하고 이를 기반으로 지보패턴을 결정할 수 있는 의사결정체계를 구축하였다. 이를 위하여 무선 네트워크, 이동식 컴퓨터, CDMA 및 디지털카메라 등 최근 정보통신을 바탕으로 한 막장면 매핑자료의 실시간 데이터 수집 및 해석, 디지털 매핑등이 가능한 PDA용 S/W를 개발하였으며 현장적용에 대하여 고려하였다. 향후에는 실제 시공시 사용된 지보방법 및 소요 지보량을 함께 저장할 수 있는 DB를 구축하는 한편 현장적용을 통한 feedback 결과에 대하여 연구가 지속될 예정이다.

• 한국정보과학회논문지:시스템및이론
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• 제35권5호
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• pp.213-222
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• 2008

본 논문은 2D 가상 착의 시스템의 컬러 영상 분할 및 직물 텍스쳐 매핑에 관한 것이다. 제안된 시스템은 컬러 영상 분할에 의해 2D 의류 모델 영상으로부터 분할된 의류 형상 영역에, 명도 차분 맵에 기반하여 사용자가 선택한 새로운 직물 패턴을 가상적으로 착용시킬 수 있는 것이 특징이다. 제안된 시스템은 모델 의류의 색이나 명도에 상관없이, 선택된 의류 형상 영역의 음영 및 조명 특성을 유지하면서 직물 패턴이나 직물 색을 가상적으로 변경시킬 수 있다. 또한 각기 다른 스타일 혹은 전체적인 차림새를 위한 다양한 직물 패턴 조합을 신속하고 용이하게 시뮬레이션하고 비교 선택할 수 있다. 제안된 시스템은 다양한 디지털 환경에서 실시간 처리가 가능하고 비교적 자연스럽고 사실적인 가상 착의 스타일을 제공할 뿐만 아니라 수작업을 최소한으로 줄인 반자동화 처리가 가능하기 때문에 높은 실용성과 편리한 사용자 인터페이스를 제공할 수 있다. 제안된 시스템에 따르면, 실제 의복을 제작하지 않고도 직물 패턴 디자인이 의복의 외관에 미치는 영향을 시뮬레이션할 수 있으므로 직물 디자이너의 창작활동을 도와줄 수 있고, 또한 구매자의 의사결정을 지원해 B2B 또는 B2C 전자상거래 행위를 촉진할 수 있다.

• Smart Structures and Systems
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• 제8권1호
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• pp.69-92
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• 2011

This paper presents an emergent pattern recognition approach based on the immune network theory and hierarchical clustering algorithms. The immune network allows its components to change and learn patterns by changing the strength of connections between individual components. The presented immune-network-based approach achieves emergent pattern recognition by dynamically generating an internal image for the input data patterns. The members (feature vectors for each data pattern) of the internal image are produced by an immune network model to form a network of antibody memory cells. To classify antibody memory cells to different data patterns, hierarchical clustering algorithms are used to create an antibody memory cell clustering. In addition, evaluation graphs and L method are used to determine the best number of clusters for the antibody memory cell clustering. The presented immune-network-based emergent pattern recognition (INEPR) algorithm can automatically generate an internal image mapping to the input data patterns without the need of specifying the number of patterns in advance. The INEPR algorithm has been tested using a benchmark civil structure. The test results show that the INEPR algorithm is able to recognize new structural damage patterns.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.627-630
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• 2006

Sequential Pattern Mining is the mining approach which addresses the problem of discovering the existent maximal frequent sequences in a given databases. In the daily and scientific life, sequential data are available and used everywhere based on their representative forms as text, weather data, satellite data streams, business transactions, telecommunications records, experimental runs, DNA sequences, histories of medical records, etc. Discovering sequential patterns can assist user or scientist on predicting coming activities, interpreting recurring phenomena or extracting similarities. For the sake of that purpose, the core of sequential pattern mining is finding the frequent sequence which is contained frequently in all data sequences. Beside the discovery of frequent itemsets, sequential pattern mining requires the arrangement of those itemsets in sequences and the discovery of which of those are frequent. So before mining sequences, the main task is checking if one sequence is a subsequence of another sequence in the database. In this paper, we implement the subsequence matching method as the preprocessing step for sequential pattern mining. Matched sequences in our implementation are the normalized sequences as the form of number chain. The result which is given by this method is the review of matching information between input mapped sequences.

• 대한원격탐사학회지
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• 제22권5호
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• pp.457-462
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• 2006

Sequential Pattern Mining is the mining approach which addresses the problem of discovering the existent maximal frequent sequences in a given databases. In the daily and scientific life, sequential data are available and used everywhere based on their representative forms as text, weather data, satellite data streams, business transactions, telecommunications records, experimental runs, DNA sequences, histories of medical records, etc. Discovering sequential patterns can assist user or scientist on predicting coming activities, interpreting recurring phenomena or extracting similarities. For the sake of that purpose, the core of sequential pattern mining is finding the frequent sequence which is contained frequently in all data sequences. Beside the discovery of frequent itemsets, sequential pattern mining requires the arrangement of those itemsets in sequences and the discovery of which of those are frequent. So before mining sequences, the main task is checking if one sequence is a subsequence of another sequence in the database. In this paper, we implement the subsequence matching method as the preprocessing step for sequential pattern mining. Matched sequences in our implementation are the normalized sequences as the form of number chain. The result which is given by this method is the review of matching information between input mapped sequences.

• 한국실내디자인학회논문집
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• 제21권2호
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• pp.35-45
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• 2012

The development of digital media made the change of architectural paradigm from tectonic to the surface and pattern. This means the transition to the new kind of materiality and the resurrection of ornament. This study started as an aim to apply biological pattern to architectural design from the new perception of pattern. Architectural patterns in the early era appeared as ladders, steps, chains, trees, vortices. But since 21st century, we can find patterns in nature like atoms and molecular structures, fluid forms of dynamics and new geometrical pattern like fractal and first of all biological patterns like viruses and micro-organisms, Voronoi cells, DNA structure, rhizomes and various hybrids and permutations of these. Pattern became one of the most important elements and themes of contemporary architecture through the change of materiality and resurrection of ornament with the new perception of surface in architecture. One of the patterns that give new creative availability to the architectural design is biological pattern which is self-organized as an optimum form through interaction with environment. Biological patterns emerge mostly as self-replicating patterns through morphogenesis, certain geometrical patterns(in particular triangles, pentagons, hexagons and spirals). The architectural application methods of biological patterns are direct figural pattern of organism, circle pattern, polygon pattern, energy-material control pattern, differentiation pattern, parametric pattern, growth principle pattern, evolutionary ecologic pattern. These patterns can be utilized as practical architectural patterns through the use of computer programs as morphogenetic programs like L-system, MoSS program and genetic algorithm programs like Grasshoper, Generative Components with the help of computing technology like mapping and scripting.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2011년도 학술발표회
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• pp.185-185
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• 2011

Mapping of artificial levee lines, one of major tasks in river zone mapping, is critical to prevention of river flood, protection of environments and eco systems in river zones. Thus, mapping of artificial levee lines is essential for management and development of river zones. Coastal mapping including river zone mapping has been historically carried out using surveying technologies. Photogrammetry, one of the surveying technologies, is recently used technology for national river zone mapping in Korea. Airborne laser scanning has been used in most advanced countries for coastal mapping due to its ability to penetrate shallow water and its high vertical accuracy. Due to these advantages, use of LiDAR data in coastal mapping is efficient for monitoring and predicting significant topographic change in river zones. This paper introduces a method for construction of a 3D artificial levee line using a set of LiDAR points that uses normal vectors. Multiple steps are involved in this method. First, a 2.5-dimensional Delaunay triangle mesh is generated based on three nearest-neighbor points in the LiDAR data. Second, a median filtering is applied to minimize noise. Third, edge selection algorithms are applied to extract break edges from a Delaunay triangle mesh using two normal vectors. In this research, two methods for edge selection algorithms using hypothesis testing are used to extract break edges. Fourth, intersection edges which are extracted using both methods at the same range are selected as the intersection edge group. Fifth, among intersection edge group, some linear feature edges which are not suitable to compose a levee line are removed as much as possible considering vertical distance, slope and connectivity of an edge. Sixth, with all line segments which are suitable to constitute a levee line, one river levee line segment is connected to another river levee line segment with the end points of both river levee line segments located nearest horizontally and vertically to each other. After linkage of all the river levee line segments, the initial river levee line is generated. Since the initial river levee line consists of the LiDAR points, the pattern of the initial river levee line is being zigzag along the river levee. Thus, for the last step, a algorithm for smoothing the initial river levee line is applied to fit the initial river levee line into the reference line, and the final 3D river levee line is constructed. After the algorithm is completed, the proposed algorithm is applied to construct the 3D river levee line in Zng-San levee nearby Ham-Ahn Bo in Nak-Dong river. Statistical results show that the constructed river levee line generated using a proposed method has high accuracy in comparison to the ground truth. This paper shows that use of LiDAR data for construction of the 3D river levee line for river zone mapping is useful and efficient; and, as a result, it can be replaced with ground surveying method for construction of the 3D river levee line.

• 한국전자파학회논문지
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• 제15권5호
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• pp.451-460
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• 2004

W-CDMA 시스템의 파일럿 비트 패턴은 채널 측정 및 프레임 동기 확인에 사용된다. 본 논문은 이러한 파일럿 패턴의 프레임 동기용 이원부호를 제안한다. 프레임 동기 단어라고 불리는 이러한 이원부호의 자기 상관 및 상호 상관 특성을 이용하여 이상적인 프레임 동기 특성을 구할 수 있는 회로를 제안한다. W-CDMA시스템에서는 두 개의 수신 단말기를 갖지 않고도, 다른 주파수의 측정을 가능하게 하기 위한 압축모드(compressed mode)를 두고 있다. 이 모드에서는 10 msec의 한 프레임 시간 동안에 7 슬랏까지 전송이 중단될 수 있는데, 이러한 경우에 제안된 프레임 동기용 이원부호의 우선 쌍 간의 보완 매핑(complementary mapping) 관계를 이용하면, 이상적인 프레임 동기 특성을 유지 할 수 있음을 보인다. 그리고 우선 쌍 개념, 보완 매핑(complementary mapping) 관계, 최대장부호(maximal length sequence) 개념을 이용하여 제안된 프레임 동기 단어를 생성하는 회로에 관하여 논한다.

• 수면정신생리
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• 제4권1호
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• pp.96-106
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• 1997

The clinical validity of a korean EEG and EP mapping system(Neuronics) was evaluated with schizophrenic patients(n=20), normal controls(n=19), and 10 patients with central nervous system disease(8 patients with cerebrovascular accident, 1 patient with brain mass, and 1 patient with periodic paralysis). In the normal control group, the pattern of resting computerized EEG with eyes closed showed normal parieto-occipital dominance of alpha wave. Compared with normal controls, schizophrenic patients had more delta activity in the frontal region, and less alpha activity especially in the parieto-occipital region. In most cases patients with cortical organic lesions(n=5) revealed increased delta and theta activity and decreased alpha activity on the lesion areas. These findings were compatible with their MRI and clinical findings. However in the cases of subcortical lesions(n=5) EEG showed various findings which suggest diverse influences of subcortical abnormalities on cortical activities. The P300 of schizophrenic group was smaller and more delayed than those of normal controls. These results are generally compatible with the previous studies using other EEG and EP mapping systems consequenty and suggest that the this EEG and EP mapping system(Neuronics) has clinical validity.

• 지능정보연구
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• 제12권2호
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• pp.145-165
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• 2006

정보 필터링 시스템은 사용자의 요구를 충족시킬 수 있도록 설계되어 있으나 변화가 심한 사용자의 정보 요구를 충족시키기에는 정확도 저하 등의 문제점이 있다. 본 연구에서는 인간의 뇌에서의 정보처리과정을 시뮬레이션하는 인지적 브레인 매핑의 정보 필터링 시스템을 제안한다. 특정 단어나 패턴에 기초하여 필터링하는 기존의 필터링 시스템과 비교할 때 제안하는 필터링 시스템은 키워드와 키워드간의 관계를 이용하여 필터링을 하는 시스템이다. 본 연구는 키워드와 키워드간의 관계를 이용하여 정보를 기록저장하고, 저장된 정보를 지도화하여 필터링에 응용하는 것이다. 키워드를 이용한 필터링 방법과 키워드간의 관계를 이용하여 필터링하는 방법을 통합하여 필터링을 실시하고 필터링 성능에 영향을 미치는 방법을 검증하기 위해 각 방법별로 가중치를 적용하여 최적의 결합가중치를 도출해낸다.