• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.729-733
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• 2003

The presence of local features within clusters incurred by multi-modal nature of data prohibits many conventional clustering techniques from working properly. Especially, the clustering of datasets with non-Gaussian distributions within a cluster can be problematic when the technique with implicit assumption of Gaussian distribution is used. Current study proposes a simple tandem clustering method composed of k-means type algorithm and hierarchical method to solve such problems. The multi-modal dataset is first divided into many small pre-clusters by k-means or fuzzy k-means algorithm. The pre-clusters found from the first step are to be clustered again using agglomerative hierarchical clustering method with Kullback- Leibler divergence as the measure of dissimilarity. This method is not only effective at extracting the multi-modal clusters but also fast and easy in terms of computation complexity and relatively robust at the presence of outliers. The performance of the proposed method was evaluated on three generated datasets and six sets of publicly known real world data.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.20 no.2
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• pp.137-147
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• 2008

A reliability analysis has been performed to investigate the systematic stability of multi-failure modes of rubble-mound breakwaters. The reliability functions of four different failure modes are established straightforwardly. AFDA(Approximate Full Distribution Approcah) reliability models for each failure modes are directly developed and satisfactorily calibrated through the comparison with CIAD's results. In the reliability analysis of single failure mode, the probabilities of failure are calculated and the influence coefficients of random variables in the failure modes are properly evaluated. Meanwhile, three different models such as uni-modal bounds, bimodal bounds, and PNET are applied to evaluate the probabilities of failure of multi-failure modes for rubble-mound breakwaters. It may be found that uni-modal bounds tend to overestimate the probability of failure of multi-failure modes. Therefore, for the systematic reliability analysis of multi-failure modes, it is recommended to use bi-modal bounds or PNET which consider the correlation between the failure modes for rubble-mound breakwaters. By introducing the reliability analysis of multi-failure modes, it could be possible to find out the additional probabilities of failure occurred by the multi-failure modes of a multi-component system such as rubble-mound breakwaters.

• Structural Engineering and Mechanics
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• v.25 no.1
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• pp.53-73
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• 2007

In this study, an effective load increment method for multi modal adaptive non-linear static (pushover) analysis (NSA) for building type structures is presented. In the method, lumped plastisicity approach is adopted and geometrical non-linearties (second-order effects) are included. Non-linear yield conditions of column elements and geometrical non-linearity effects between successive plastic sections are linearized. Thus, load increment needed for formation of plastic sections can be determined directly (without applying iteration or step-by-step techniques) by using linearized yield conditions. After formation of each plastic section, the higher mode effects are considered by utilizing the essentials of traditional response spectrum analysis at linearized regions between plastic sections. Changing dynamic properties due to plastification in the system are used on the calculation of modal lateral loads. Thus, the effects of stiffness changes and local mechanism at the system on lateral load distribution are included. By using the proposed method, solution can be obtained effectively for multi-mode whereby the properties change due to plastifications in the system. In the study, a new procedure for determination of modal lateral loads is also proposed. In order to evaluate the proposed method, a 20 story RC frame building is analyzed and compared with Non-linear Dynamic Analysis (NDA) results and FEMA 356 Non-linear Static Analysis (NSA) procedures using fixed loads distributions (first mode, SRSS and uniform distribution) in terms of different parameters. Second-order effects on response quantities and periods are also investigated. When the NDA results are taken as reference, it is seen that proposed method yield generally better results than all FEMA 356 procedures for all investigated response quantities.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.15 no.3
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• pp.421-432
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• 2002

In this study the modal characteristics and responses of an asymmetric structure with added viscoelastic dampers were investigated for design parameters such as eccentricity of stiffness and added dampers, the loss factor of the damping materials used. For modal characteristics, variation of the quantities such as natural frequencies, modal damping ratios, modal participation factors, and dynamic amplification factors were observed, and displacements at flexible and stiff edges, and at center of mass were obtained. Based on the results, the problem of the optimum damper distribution to minimize the torsional effects was addressed, and the proposed method for optimum damper distribution was applied to a multi-story structure to verify the applicability Finally the effect of viscous and viscoelastic dampers were compared by varying the loss factor of the viscoelastic material.

• Journal of KIISE:Software and Applications
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• v.34 no.4
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• pp.377-388
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• 2007

In this paper, we propose a multi-modal biometric system based on face, iris and fingerprint recognition system. To effectively aggregate two systems, we use statistical distribution models based on matching values for genuine and impostor, respectively. And then, We performed reveal fusion algorithms including weighted summation, Support Vector Machine(SVM), Fisher discriminant analysis, Bayesian classifier. From the various experiments, we found that the performance of multi-modal biometric system was influenced with the normalization methods and classifiers.

• The KIPS Transactions:PartB
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• v.11B no.7 s.96
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• pp.885-892
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• 2004

In this paper, we propose a multi-modal biometrics system based on face and signature recognition system. Here, the face recognition system is designed by fuzzy LDA, and the signature recognition system is implemented with the LDA and segment matching methods. To effectively aggregate two systems, we obtain statistical distribution models based on matching values for genuine and impostor, respectively. And then, the final verification is Performed by the support vector machine. From the various experiments, we find that the proposed method shows high recognition rates comparing with the conventional methods.

• Communications for Statistical Applications and Methods
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• v.14 no.3
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• pp.517-530
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• 2007

We studied a modelling process for unimodal and multimodal circular data by using von Mises and its mixture distribution. In particular we suggested EM algorithm to find ML estimates of the mixture model. Simulation results showed the suggested methods are very accurate. Applications to two kinds of real data sets are also included.

• Design & Manufacturing
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• v.15 no.1
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• pp.66-71
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• 2021

In this study, die turning injection(DTI) mold design for manufacturing reservoir fluid tanks used for cooling in-vehicle batteries, inverters, and motors was conducted based on multi-field CAE. Part design, performance evaluation, and mold design of the reservoir fluid tank was performed. The frequency response characteristics through modal and harmonic response analysis to satisfy the automotive performance test items for the designed part were examined. Analysis of re-melting characteristics and structural analysis of the driving part for designing the rotating die of the DTI mold were performed. Part design was possible when the natural frequency performance value of 32Hz or higher was satisfied through finite element analysis, and the temperature distribution and deformation characteristics of the part after injection molding were found through the first injection molding analysis. In addition, it can be seen that the temperature change of the primary part greatly influences the re-melting characteristics during the secondary injection. The minimum force for driving the turning die of the designed mold was calculated through structural analysis. Hydraulic system design was possible. Finally, a precise and efficient DTI mold design for the reservoir fluid tank was possible through presented multi-field CAE process.

• Management Science and Financial Engineering
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• v.19 no.2
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• pp.49-53
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• 2013

A Markov-chain Monte Carlo sampling algorithm samples a new point around the latest sample due to the Markov property, which prevents it from sampling from multi-modal distributions since the corresponding chain often fails to search entire support of the target distribution. In this paper, to overcome this problem, mode switching scheme is applied to the conventional MCMC algorithms. The algorithm separates the reducible Markov chain into several mutually exclusive classes and use mode switching scheme to increase mixing rate. Simulation results are given to illustrate the algorithm with promising results.

• Magazine of the Korean Society of Agricultural Engineers
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• v.38 no.4
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• pp.110-124
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• 1996

This study was conducted to simulate long seres of synthetic monthly flows by multi-season first order Markov model with selection of best fitting frequency distribution, harmonic synthetic and harmonic regression models and to make a comparison of statistical parameters between observes and synthetic flows of five watersheds in Geum river system. The results obtained through this study can be summarized as follow. 1. Both gamma and two parameter lognormal distributions were found to be suitable ones for monthly flows in all watersheds by Kolmogorov-Smirnov test. 2. It was found that arithmetic mean values of synthetic monthly flows simulated by multi-season first order Markov model with gamma distribution are much closer to the results of the observed data in comparison with those of the other models in the applied watersheds. 3. The coefficients of variation, index of fluctuation for monthly flows simulated by multi-season first order Markov model with gamma distribution are appeared closer to those of the observed data in comparison with those of the other models in Geum river system. 4. Synthetic monthly flows were simulated over 100 years by multi-season first order Markov model with gamma distribution which is acknowledged as a suitable simulation modal in this study.