• Journal of Industrial Technology
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• v.27 no.A
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• pp.149-155
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• 2007

The counter emf(electromotive forces) of a permanent magnet multi-phase brushless motor is generally a non-sinusoidal wave or a non-ideal trapezoid. So, conventional modeling using a sinusoidal wave or an ideal trapezoid counter emf can result in errors. In order to reduce modeling errors for simulation and analysis the properties of a multi-phase brushless AC motor, this paper proposes a phase variable model that is a mixed modeling technique using both Finite Element Analysis(FEA) based circuits and motor voltage equations. The phase model parameters including the counter emf voltage waveform are obtained by using of FEA, and the mixed modeling technique based on circuits and equations is used to implement a simulation model for multi-phase brushless AC motors with any counter emf voltage waveforms. Adequacy of the proposed model is established from the simulation and experimental results for a seven-phase brushless motor.

• Journal of Korea Game Society
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• v.9 no.5
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• pp.127-136
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• 2009

This paper describes a 3D modeling system in Augmented Reality environment, named 3DARModeler. It can be considered a simple version of 3D Studio Max with necessary functions for a modeling system such as creating objects, applying texture, adding animation, estimating real light sources and casting shadows. The 3DARModeler introduces convenient, and effective human-computer interaction to build 3D models. The 3DARModeler targets nontechnical users. As such, they do not need much knowledge of computer graphics and modeling techniques. All they have to do is select basic objects, customize their attributes, and put them together to build a 3D model in a simple and intuitive way as if they were doing in the real world.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.1
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• pp.13-27
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• 2014

In this paper, we deal with a Steiner Ring Star (SRS) problem arising from the design of survivable telecommunication networks. We develop two mixed integer programming formulations for the SRS problem by implementing Miller-Tucker-Zemlin (MTZ) and Sarin-Sherali-Bhootra (SSB) subtour elimination constraints, and then apply the reformulation-linearization technique (RLT) to enhance the lower bound obtained by the LP relaxation. By exploiting the ring-star structure of underlying network, we devise some valid inequalities that tighten the LP relaxation. Computational results demonstrate the effectiveness of the proposed solution procedure.

• The Journal of the Acoustical Society of Korea
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• v.18 no.2E
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• pp.24-30
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• 1999

In this paper, we propose a weighting dependent mixed source model (WD-MSM) coder that is an improved version of a CELP-based mixed source model (C-MSM) coder. The coder classifies speech segments into three types : voiced, unvoiced and mixed. The excitation for a voiced frame is an adaptive source, and the excitation for an unvoiced frame is a stochastic source. The coder has a modified mixed source for a mixed frame. We apply different weighting functions for three classes. Simulation results show that the proposed coder at 4 kbits/s yields very good performance both subjectively and objectively.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2012.05a
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• pp.592-596
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• 2012

The details of engine data are essentially needed for engine modeling and simulation. But, the engine data are kept secret because the information is company's experiential property. In this paper performed the performance modeling of the mixed flow turbofan engine cycles from the general available engine data, and verify the validity.

• Communications for Statistical Applications and Methods
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• v.25 no.1
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• pp.61-70
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• 2018

Modeling of the random effects covariance matrix in generalized linear mixed models (GLMMs) is an issue in analysis of longitudinal categorical data because the covariance matrix can be high-dimensional and its estimate must satisfy positive-definiteness. To satisfy these constraints, we consider the autoregressive and moving average Cholesky decomposition (ARMACD) to model the covariance matrix. The ARMACD creates a more flexible decomposition of the covariance matrix that provides generalized autoregressive parameters, generalized moving average parameters, and innovation variances. In this paper, we analyze longitudinal count data with overdispersion using GLMMs. We propose negative binomial loglinear mixed models to analyze longitudinal count data and we also present modeling of the random effects covariance matrix using the ARMACD. Epilepsy data are analyzed using our proposed model.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.739-744
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• 2002

Recently we have discovered that sediments should be separated from lithosphere, and soil should be separated from biosphere, both sediment and soil will be mixed sediments-soil-sphere (Seso-sphere), which is using particulate mechanics to be solved. Erosion and sediment both are moving by particulate matter with water or wind. But ancient sediments will be erosion same to soil. Nowadays, real soil has already reduced much more. Many places have only remained sediments that have ploughed artificial farming layer. Thus it means sediments-soil-sphere. This paper discusses sediments-soil-sphere erosion modeling. In fact sediments-soil-sphere erosion is including water erosion, wind erosion, melt-water erosion, gravitational water erosion, and mixed erosion. We have established geographical remote sensing information modeling (RSIM) for different erosion that was using remote sensing digital images with geographical ground truth water stations and meteorological observatories data by remote sensing digital images processing and geographical information system (GIS). All of those RSIM will be a geographical multidimensional gray non-linear equation using mathematics equation (non-dimension analysis) and mathematics statistics. The mixed erosion equation is more complex that is a geographical polynomial gray non-linear equation that must use time-space fuzzy condition equations to be solved. RSIM is digital image modeling that has separated physical factors and geographical parameters. There are a lot of geographical analogous criterions that are non-dimensional factor groups. The geographical RSIM could be automatic to change them analogous criterions to be fixed difference scale maps. For example, if smaller scale maps (1:1000 000) that then will be one or two analogous criterions and if larger scale map (1:10 000) that then will be four or five analogous criterions. And the geographical parameters that are including coefficient and indexes will change too with images. The geographical RSIM has higher precision more than mathematics modeling even mathematical equation or mathematical statistics modeling.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.6
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• pp.206-219
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• 1996

This paper describes a data structure and evaluation algorithm to improve the perofmrances MOS logic-with-timing simulation in computation and accuracy. In order to efficiently simulate the logic and timing of driver-load networks, (1) a tree data structure to represent the mutual interconnection topology of switches and nodes in the driver-lod network, and (2) an algebraic modeling to efficiently deal with the new represetnation, (3) an evaluation algorithm to compute the linear resistive and capacitive behavior with the new modeling of driver-load networks are developed. The higher modeling presented here supports the structural and functional compatibility with the linear switch-level to simulate the logic-with-timing of digital MOS circuits at a mixed-level. This research attempts to integrate the new approach into the existing simulator RSIM, which yield a mixed-klevel logic-with-timing simulator MIXIM. The experimental results show that (1) MIXIM is a far superior to RSIM in computation speed and timing accuracy; and notably (2) th etiming simulation for driver-load netowrks produces the accuracy ranged within 17% with respect ot the analog simulator SPICE.

• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.177-183
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• 2010

In continuous vocabulary recognition system by statistical method vocabulary recognition to be performed using probability distribution it also modeling using phoneme clustering for based sample probability parameter presume. When vocabulary search that low recognition rate problem happened in express vocabulary result from presumed probability parameter by not defined phoneme and insert phoneme and it has it's bad points of gaussian model the accuracy unsecure for one clustering modeling. To improve suggested probability distribution mixed gaussian model to optimized for based resemble Euclidean and Bhattacharyya distance measurement method mixed clustering modeling that system modeling for be searching phoneme probability model in clustered model. System performance as a result of represent vocabulary dependence recognition rate of 98.63%, vocabulary independence recognition rate of 97.91%.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.12 no.3
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• pp.363-370
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• 1999

This study presented an modeling method for the connections in mixed structure with reinforced concrete columns and steel beam using finite element method. The contacting surfaces between concrete and steel are modeled using master-slave contact algorithm and the incompatible mode elements were used in the steel tube subjected to bending. The characteristics of mixed structure was that diaphragm was used for transferring force from beam to column. The three dimensional nonlinear analysis was performed and the analytical results compared with experimental results in order to prove modeling method.