• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.11C
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• pp.1085-1091
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• 2006

The major goal of this paper is to develop a practically implemental radial basis function (RBF) neural network based multi-user detector (MUD) for direct sequence (DS)-CDMA system. This work is expected to provide an efficient solution for RBF based MUD by quickly setting up the proper number of RBF centers and their locations required in training. The basic idea in this research is to estimate all the possible RBF centers by using supervised ${\kappa-means$ clustering technique, and select the only centers which locate near seemingly decision boundary between centers, and reduce further by grouping the some of centers adjacent each other. Therefore, it reduces the computational burden for finding the proper number of RBF centers and their locations in the existing RBF based MUD, and ultimately, make its implementation practical.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.4
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• pp.460-465
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• 2006

This paper presents a new fuzzy learning rule which considers the Euclidean distances between the input vector and the prototypes of classes. The new fuzzy learning rule is integrated into the supervised IAFC neural network 4. This neural network is stable and plastic. We used iris data to compare the performance of the supervised IAFC neural network 4 with the performances of back propagation neural network and LVQ algorithm.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.141-144
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• 2007

Given a number of training data, a traditional BPN is normally trained by minimizing the absolute difference between target outputs and approximate outputs. When BPN is used as a meta-model for inequality constraint function, approximate optimal solutions are sometimes actually infeasible in a case where they are active at the constraint boundary. The paper describes the development of the efficient BPN based meta-model that enhances the constraint feasibility of approximate optimal solution. The modified BPN based meta-model is obtained by including the decision condition between lower/upper bounds of a constraint and an approximate value. The proposed approach is verified through a simple mathematical function and a ten-bar planar truss problem.

• Atmosphere
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• v.11 no.2
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• pp.6-12
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• 2001

The East Asian monsoon is generally accompanied with the quasi-stationary front along the northern and northwestern periphery of the subtropical anticyclone in the boundary zone of the polar cold air mass and the tropical warm air mass. The rainy season in Korea has been called as Changma since the middle of 1500s. In meteorology, the rainy season with the quasi-stationary front, the Changma front, during the early summer has been defined as the Changma since 1905. The difference of meaning on Changma between meteorologists and the general public sometime does give a confusion. For example, the heavy rainfall event after the retreat of Changma is recognized as Changma by the general public, but not by most of meteorologists. The decision of the onset and retreat dates of Changma among the meteorologists is also ambiguous because of different viewpoints on the definition of Changma. In this study we survey the etymology and definition of Changma.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.18-21
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• 2003

In general it has been considered to be the difficult problem that we divide continuous speech into short interval with having identical phoneme quality. In this paper we used Gaussian Mixture Model (GMM) related to probability density to divide speech into phonemes, an initial, medial, and final sound. From them we peformed continuous speech recognition. Decision boundary of phonemes is determined by algorithm with maximum frequency in a short interval. Recognition process is performed by Continuous Hidden Markov Model(CHMM), and we compared it with another phoneme divided by eye-measurement. For the experiments result we confirmed that the method we presented is relatively superior in auto-segmentation in korean speech.

• Cross-Cultural Studies
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• v.21
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• pp.189-211
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• 2010

The purpose of this paper is to 1)examine the current state of cultural studies in Korea with a focus on recent discourses about its 'crisis' and 2)attempt to find some ways out of these dilemmas in drama/theatre/performance studies. As Raymond Williams redefined 'culture' as 'a whole way of life,' performance studies has expanded the boundary of 'performance' from traditional performing arts onto almost everything that can be studied and analyzed 'as' performance. Performance is not only the final product on display but a whole process that includes training, workshop, and rehearsal of culture. According to Richard Schechner, workshop and rehearsal are the most critical and creative 'liminal' phases that allow traditional knowledge and alternative challenges to coexist in conflict and intentionally delay the final decision by putting itself in a perpetual process. From this view, this essay attempts to find an-no matter how limited and temporary-answer to or a possible exit from political and theoretical aporias of cultural studies.

• Journal of Biomedical Engineering Research
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• v.21 no.3 s.61
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• pp.239-246
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• 2000

In this paper. we propose a semi-automatic segmentation algorithm to extract organ in 3D medical data by using a manually segmentation result in a sing1e slice. Generally region glowing based tracking method consists of 3 steps object projection. seed extraction and boundary decision by region growing. But because the boundary between organs in medical data is vague, improper seeds make the boundary dig into the organ or extend to the false region. In the proposed algorithm seeds are carefully extracted to find suitable boundaries between organs after region growing. And the jagged boundary at low gradient region after region growing is corrected by post-processing using Fourier descriptor. Also two-path tracking make it possible to catch up newly appeared areas. The proposed algorithm provides satisfactory results in segmenting 1 mm distance kidneys from X-rav CT body image set of 82 slices.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.192-200
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• 2008

Multimodal biometrics is a method for personal authentication and verification using more than two types of biometrics data. RBF based score-level fusion uses pattern recognition algorithm for multimodal biometrics, seeking the optimal decision boundary to classify score feature vectors each of which consists of matching scores obtained from several unimodal biometrics system for each sample. In this case, all matching scores are assumed to have the same reliability. However, in recent research it is reported that the quality of input sample affects the result of biometrics. Currently the matching scores having low reliability caused by low quality of samples are not currently considered for pattern recognition modelling in multimodal biometrics. To solve this problem, in this paper, we proposed the RBF based score-level fusion approach which employs quality information of input biometrics data to adjust decision boundary. As a result the proposed method with Qualify information showed better recognition performance than both the unimodal biometrics and the usual RBF based score-level fusion without using quality information.

• Journal of Cadastre & Land InformatiX
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• v.51 no.1
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• pp.79-95
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• 2021

This study evaluates the applicability of determining cadastral surveying results using drone photogrammetry during the phase of determining cadastral surveying results, which is the most important stage of cadastral surveying, but known to be hardly objective and highly probable in causing a subjective misjudgment or mistake made by a surveyor. In the experiment to analyze the accuracy of boundary point extraction from drone photogrammetry results, by comparing the coordinate area of 22 parcels extracted from 2D and 3D images with the coordinate area measured from ground survey, the difference could be quantified as RMSE of 1.44m² for 2D and 0.32m² for 3D images. In addition, experiments to evaluate the determination of cadastral surveying result based on drone photogrammetry survey showed the RMSE measure of 0.346m towards N direction and 0.296m towards Y direction in comparison to the existing surveying results through data investigation. Based on these experiments, it is judged that cadastral surveying result based on drone photogrammetry can be determined without needing to conduct a location survey with an accuracy of approximately 0.3m in the graphical area, which also leads to possibility of reducing individual errors if drones images are used along with ground survey by objectifying the process of cadastral surveying results.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.95-103
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• 2023

This paper proposes an artificial intelligence convergence education program for teaching the main concept and principle of Support Vector Machines(SVM) at elementary schools. The developed program, based on Jeju's natural environment theme, explains the decision boundary and margin of SVM by vertical and parallel from 4th grade mathematics curriculum. As a result of applying the developed program to 3rd and 5th graders, most students intuitively inferred the location of the decision boundary. The overall performance accuracy and rate of reasonable inference of 5th graders were higher. However, in the self-evaluation of understanding, the average value was higher in the 3rd grade, contrary to the actual understanding. This was due to the fact that junior learners had a greater tendency to feel satisfaction and achievement. On the other hand, senior learners presented more meaningful post-class questions based on their motivation for further exploration. We would like to find effective ways for artificial intelligence convergence education for elementary school students.