• Journal of Korean Tunnelling and Underground Space Association
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• v.7 no.1
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• pp.89-96
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• 2005

Due to fast development of digital equipments, various information techniques have been applied to the tunneling and a decision aid system based on IT has also been used during excavation stage. A PDA based informative tunneling method is, therefore, studied in this paper and the decision aids for tunneling using digital face mapping data as well as geologic information in terms of digital data is developed. For this, wireless network, mobile computer, CDMA and digital camera have been combined to generate the digital map of the tunnel face and reinforcement or excavation pattern can be estimated based on digitalized geologic conditions. Future studies will be concentrated on the enhancement of the PDA S/W so that reinforcement method as well as the amount of reinforcements can also be stored in the same DB. Furthermore, field application of the S/W will be undertaken and a virtual reality technique will also be introduced to visualize all the tunneling work on the computer monitor.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.5
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• pp.213-222
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• 2008

This paper is related to color image segmentation and textile texture mapping for the 2D virtual wearing system. The proposed system is characterized as virtually wearing a new textile pattern selected by user to the clothing shape section, based on its intensity difference map, segmented from a 2D clothes model image using color image segmentation technique. Regardless of color or intensity of model clothes, the proposed system is possible to virtually change the textile pattern or color with holding the illumination and shading properties of the selected clothing shape section, and also to quickly and easily simulate, compare, and select multiple textile pattern combinations for individual styles or entire outfits. The proposed system can provide higher practicality and easy-to-use interface, as it makes real-time processing possible in various digital environment, and creates comparatively natural and realistic virtual wearing styles, and also makes semi-automatic processing possible to reduce the manual works to a minimum. According to the proposed system, it can motivate the creative activity of the designers with simulation results on the effect of textile pattern design on the appearance of clothes without manufacturing physical clothes and, as it can help the purchasers for decision-making with them, promote B2B or B2C e-commerce.

• Smart Structures and Systems
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• v.8 no.1
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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.

• Proceedings of the KSRS Conference
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• v.2
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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.

• Korean Journal of Remote Sensing
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• v.22 no.5
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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.

• Korean Institute of Interior Design Journal
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• v.21 no.2
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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.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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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.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.5
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• pp.451-460
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• 2004

The pilot bit pattern of W-CDMA system is used for the channel estimation and frame synchronization confirmation. This paper proposes the binary sequences for the frame synchronization for wideband code division multiple access (W-CDMA) system. We present the circuit for the generation of ideal frame synchronization property using the binary sequences called frame synchronization word(FSW). W-CDMA system uses compressed mode where up to 7 slots per one 10 msec frame are not transmitted to make measurements from another frequency without a full dual receiver terminal. It is shown that the proposed frame synchronization words also maintain the optimal frame synchronization property in the compressed mode by using the complementary mapping relationship of preferred pair. And we discuss the realization circuit for the generation of frame synchronization words by using the concept of preferred pairs, complementary mapping relationship, and maximal length sequence.

• Sleep Medicine and Psychophysiology
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• v.4 no.1
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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.

• Journal of Intelligence and Information Systems
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• v.12 no.2
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• pp.145-165
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• 2006

Information filtering systems, which are designed fur users' needs, do not satisfy user's diverse requests as their filtering accuracy is unstable sometimes. This study suggests an information filtering system based on cognitive brain mapping by simulating the processes of information in human brain. Compared to traditional filtering systems, which use specific words or pattern in their filtering systems, the method suggested in this article uses both key words and relationships among these words. The significance of this study is on simulating information storing processes in human brain by mapping both key words and their relationships among them together. To combine these two methods, this study finds balances in representing two methods by searching optimal weights of each of them.