• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.1
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• pp.68-76
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• 2011

Acoustic emission(AE) has emerged as a powerful nondestructive tool to detect any further growth or expansion of preexisting defects or to characterize failure mechanisms. Recently, this kind of technique, that is an in-situ monitoring of inside damages of materials or structures, becomes increasingly popular for monitoring the integrity of large structures like a huge wind turbine blade. Therefore, it is required to find a symptom of damage propagation before catastrophic failure through a continuous monitoring. In this study, a new damage location method has been proposed by using signal mapping algorithm, and an experimental verification is conducted by using small wind turbine blade specimen; a part of 750 kW real blade. The results show that this new signal mapping method has high advantages such as a flexibility for sensor location, improved accuracy, high detectability. The newly proposed method was compared with traditional AE source location method based on arrival time difference.

• Korean Journal of Health Education and Promotion
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• v.24 no.1
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• pp.93-108
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• 2007

Background: School is a primary health education setting for children and the continuous support should be provided to renew school health education curriculum correspondent to socio-cultural changes in Korean society. Objectives: This study was conducted to identify the principals' and teachers' needs of health education topics for their students and to analyze their conceptual map for health education curriculum in Korean elementary school. Methods: The sample size of the first survey was 179 and that of the second survey was 691 of elementary school principals and teachers from stratified sampling over Korea. The self-administered mailing survey was conducted to o identify the factor structure of the health education topics and to analyze the conceptual properties with exploratory factor analysis and multidimensional scaling analysis in SPSS 12.0. Results: A total of 21 health education topics were collected from the first survey and 31 topics were, comprehensively, generated for the second survey. The five factors were determined: 'life health promotion behavior,' 'drug control and mental health,' 'bulling and aggression prevention,' 'safety perception and injury prevention,' and 'sex education and sexual harassment.' The educational need scores were the highest in 'safety perception and injury prevention.' The two-dimensional cooperates were generated for the 31 health education topics and the two dimensional properties which divided the conceptual space were 'health-safety' for one and 'public/environmental-individual/personal' for the other. Conclusions: Health education curriculum and textbook should be developed considering teachers' needs and conditions for health education in school fields. The field-based health education programs or textbook would make more possible problem-solving health education for children in real school fields.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.1
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• pp.40-47
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• 2009

Recently, dynamic proxy caching has been proposed on the distributed environment so that media objects by user's requests can be served directly from the proxy without contacting the server. However, it makes caching challenging due to multimedia large sizes, low latency and continuous streaming demands of media objects. To solve the problems caused by streaming demands of media objects, this paper has been proposed the grouping scheme with fuzzy filtering based on partition and mapping. For partition and mapping, this paper divides media block segments into fixed partition reference block(R$_f$P) and variable partition reference block(R$_v$P). For semantic relationship, it makes fuzzy relationship to performs according to the fixed partition temporal synchronization(T$_f$) and variable partition temporal synchronization(T$_v$). Simulation results show that the proposed scheme makes streaming service efficiently with a high average request response time rate and cache hit rate and with a low delayed startup ratio compared with other schemes.

• Journal of KIISE
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• v.42 no.5
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• pp.621-628
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• 2015

The rapid growth of network technology makes the high-tech weapon. Thus, in the modern war, the ability to immediately use of the high-tech weapon is important. To realize this ability, continuous trainning is necessary but, this trainning spends many money. To improve the budget efficiency, Modeling and Simulation(M&S) are used. However, they seriously decrease the reality. Recently, the system which can support the combination of Live with Virtual simulation is on the rise. The typical example is L-V-C Environment and many kind of middleware which can support the L-V-C Envrionment are already proposed. Previous middleware can support the interoperability between different simulations but, it cannot completely interoperate three(Live, Virtual, Constructive) simulation environments. In this paper, to solve this problem, we propose the scheme which is combination between different middlewares. And we conduct the API mapping between HLA and DDS which are typical middleware and verify the scheme.

• Korean Journal of Construction Engineering and Management
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• v.17 no.3
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• pp.32-42
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• 2016

In Korea, the absence of BIM use in existing civil structures and buildings is driving a demand for as-built BIM. As-built BIMs are often created using laser scanners that provide dense 3D point cloud data. Conventional static laser scanning approaches often suffer from limitations in their operability due to the difficulties in moving the equipment, the selection of scanning location, and the requirement of placing targets or extracting tie points for registration of each scanned point cloud. This paper aims at reducing the manual effort using a kinematic 3D laser scanning system based on graph-based simultaneous localization and mapping (SLAM) for continuous indoor mapping. The robotic platform carries three 2D laser scanners: the front scanner is mounted horizontally to compute the robot's trajectory and to build the SLAM graph; the other two scanners are mounted vertically to scan the profiles of surrounding environments. To reduce the accumulated error in the trajectory of the platform through loop closures, the graph-based SLAM system incorporates AdaBoost loop closure approach, which is particularly suitable for the developed multi-scanner system providing more features than the single-scanner system for training. We implemented the proposed method and evaluated it in two indoor test sites. Our experimental results show that the false positive rate was reduced by 13.6% and 7.9% for the two dataset. Finally, the 2D and 3D mapping results of the two test sites confirmed the effectiveness of the proposed graph-based SLAM.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.5
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• pp.404-411
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• 2009

We introduce in this paper a new method for smooth foldover-free warping of images, based on the vector field deformation technique proposed by Von Funck et al. It allows users to specify the constraints in two different ways: positional constraints to constrain the position of a point in the image and gradient constraints to constrain the orientation and scaling of some parts of the image. From the user-specified constraints, it computes in the image domain a C1-continuous velocity vector field, along which each pixel progressively moves from its original position to the target. The target positions of the pixels are obtained by solving a set of partial derivative equations with the 4th order Runge-Kutta method. We show how our method can be useful for texture mapping with hard constraints. We start with an unconstrained planar embedding of a target mesh using a previously known method (Least Squares Conformal Map). Then, in order to obtain a texture map that satisfies the given constraints, we use the proposed warping method to align the features of the texture image with those on the unconstrained embedding. Compared to previous work, our method generates a smoother texture mapping, offers higher level of control for defining the constraints, and is simpler to implement.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.2
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• pp.233-237
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• 2010

The recent advance of sensor networks and ubiquitous techniques allow collecting and analyzing of the data which overcome the limitation imposed by time and space in real-time for making decisions. Also, analysis and prediction of collected data can support useful and necessary information to users. The collected data in sensor networks environment is the stream data which has continuous, unlimited and sequential properties. Because of the continuous, unlimited and large volume properties of stream data, managing stream data is difficult. And the stream data needs dynamic processing method because of the memory constraint and access limitation. Accordingly, we analyze correlation stream data using principal component analysis. And using result of analysis, it helps users for making decisions.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.4
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• pp.391-396
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• 2003

This paper proposes a new approach that converts continuous-valued attributes to categorical-valued ones considering the distribution of target attributes(classes). In this approach, It can be possible to get optimal interval boundaries by considering the distribution of data itself without any requirements of parameters. For each attributes, the distribution of target attributes is projected to one-dimensional space. And this space is clustered according to the criteria like as the density value of each target attributes and the amount of overlapped areas among each density values of target attributes. Clusters which are made in this ways are based on the probabilities that can predict a target attribute of instances. Therefore it has an interval boundaries that minimize a loss of information of original data. An improved performance of proposed discretization method can be validated using C4.5 algorithm and UCI Machine Learning Data Repository data sets.

• Journal of Intelligence and Information Systems
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• v.7 no.1
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• pp.135-147
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• 2001

This study proposes bankruptcy prediction model using fuzzy neural networks. Neural networks offer preeminent learning ability but they are often confronted with the inconsistent and unpredictable performance for noisy financial data. The existence of continuous data and large amounts of records may pose a challenging task to explicit concepts extraction from the raw data due to the huge data space determined by continuous input variables. The attempt to solve this problem is to transform each input variable in a way which may make it easier fur neural network to develop a predictive relationship. One of the methods selected for this is to map each continuous input variable to a series of overlapping fuzzy sets. Appropriately transforming each of the inputs into overlapping fuzzy membership sets provides an isomorphic mapping of the data to properly constructed membership values, and as such, no information is lost. In addition, it is easier far neural network to identify and model high-order interactions when the data is transformed in this way. Experimental results show that fuzzy neural network outperforms conventional neural network for the prediction of corporate bankruptcy.

• Communications of the Korean Mathematical Society
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• v.29 no.3
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• pp.401-408
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• 2014

If A is a unital Banach algebra, then the spectrum can be viewed as a function ${\sigma}$ : 𝕬 ${\rightarrow}$ 𝕾, mapping each T ${\in}$ 𝕬 to its spectrum ${\sigma}(T)$, where 𝕾 is the set, equipped with the Hausdorff metric, of all compact subsets of $\mathbb{C}$. This paper is concerned with the continuity of the spectrum ${\sigma}$ via Browder's theorem. It is shown that ${\sigma}$ is continuous when ${\sigma}$ is restricted to the set of essentially hyponormal operators for which Browder's theorem holds, that is, the Weyl spectrum and the Browder spectrum coincide.