• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.5-8
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• 2014

This paper presents a parallel approach of formant synthesis method for haegeum on graphics processing units (GPU) using spectral modeling. Spectral modeling synthesis (SMS) is a technique that models time-varying spectra as a combination of sinusoids and a time-varying filtered noise component. A second-order digital resonator by the impulse-invariant transform (IIT) is applied to generate deterministic components and the results are band-pass filtered to adjust magnitude. The noise is calculated by first generating the sinusoids with formant synthesis, subtracting them from the original sound, and then removing some harmonics remained. The synthesized sounds are consequently by adding sinusoids, which are shown to be similar to the original Haegeum sounds. Furthermore, GPU accelerates the synthesis process enabling- real time music synthesis system development, supporting more sound effect, and multiple musical sound compositions.

• Journal of the Korean Society for Railway
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• v.3 no.2
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• pp.43-50
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• 2000

The corrugated panels are the prime candidate structure for the floor, roof and wall of Korean high speed train. The equivalent continuum modeling approach panels can be used for the efficient design and evaluation of their structural characteristics. The equivalent continuum models, derived from the true complex corrugated panels, should have the same structural behavior as the original structures have. This paper briefly reviews three representative continuum modeling methods: the static analysis method and two plate-models based on modal analysis methods (MAM). These methods are evaluated through some numerical examples by comparing the natural frequencies and static deflections. It is observed that the plate-model based on Rayleigh-Ritz method seems to provide the best results when used in conjunction with the cantilever-type boundary conditions. The equivalent elastic constants of various corrugated panels, depending on the changes in their configurations, are tabulated for efficient use in structural design.

• Computational Structural Engineering
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• v.9 no.2
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• pp.163-171
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• 1996

A hybrid knowledge model which amalgamates an object-oriented modeling approach and logic programming implementation is presented for structural health monitoring and diagnosis of instrumented structures. Domain knowledge in structural monitoring and diagnosis is formalized and represented in a logic-based object-oriented modeling environment. The model and environment have been implemented and illustrated in the context of a laboratory case study of damage detection in a successively damaged steel structure.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.3
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• pp.237-246
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• 1989

A sliding memory covariance circular lattice (SMC-CL) filter and an efficient ARMA modeling method using the SMC-CL filter are presented. At first, SMC-CL filter is derived based on the geometric approach. Then ARMA process is converted into 2 channel AR process, and SMC-CL filter is applied to it. The structure of SMC-CL filter becomes simpler in case of ARMA modeling due to the whiteness of a driving input process. The parameters of ARMR process can be obtained by the Levinson recursions from the PARCOR coefficients of the second channel of the filter. Computer simulations are performed to show the effctiveness of the proposed algorithm.

• 한국연소학회:학술대회논문집
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• 2015.12a
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• pp.23-24
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• 2015

In this talk, we will present what we believe is the state-of-the-art of the numerical modeling and simulation of the combustion processes as they relate to typical scramjet engines. The free-stream Mach number is hypersonic, but the speed is not sufficiently decelerated at the inlet/isolator, as in ramjets, so that combustion takes place under supersonic conditions. This creates some difficulties for most turbulence-combustion models. We delve into the details of these problems, by discussing the software programs that have a long track record for scramjet combustion simulation; with a focus on the accuracy of the baseline numerical methods used, the turbulence modeling/simulation approach, the comparative fidelity of the turbulence-combustion interaction models, ability to simulate premixed/non-premixed/partially-premixed, quenching/re-ignition capabilities, the numerical spark-plug method, Damkholer number regimes supported, and the effects of variable Prandtl, Schmidt, and Lewis numbers. Validation results from high-speed and low-speed combustion applications will also be presented.

• Transactions of the Korean Society of Automotive Engineers
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• v.6 no.6
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• pp.1-6
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• 1998

A leaf spring plays an important role in a passenger bus. Since characteristic of a leaf spring has a hysteresis behaviour, modeling technique for a leaf spring is an important issue for passenger bus analysis. In this paper, modeling technique for a leaf spring is presented. First, non-linear FEM model of a leaf spring is constructed then it is used to make an approximated model to be used in dynamic analysis. The modeling procedure is ex-plained in step by step approach. Then, this model is applied to dynamic analysis of a mini-bus with flexible body and non-linear dynamic force element. The results are compared with test data.

• Journal of Korean Institute of Industrial Engineers
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• v.18 no.1
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• pp.81-89
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• 1992

After much research on qualitative reasoning, the problem of ambiguities still hampers the practicality of this important AI tool. In this paper, the sources of ambiguities are examined in depth with a systems engineering point of view and possible directions to disambiguation are suggested. This includes some modeling strategies and an architecture of temporal inference for building unambiguous qualitative models of practical complexity. It is argued that knowledge of multiple levels in abstraction hierarchy must be reflected in the modeling to resolve ambiguities by introducing the designer's decisions. The inference engine must be able to integrate two different types of temporal knowledge representation to determine the partial ordering of future events. As an independent quantity management system that supports the suggested modeling approach, LIQUIDS(Linear Quantity-Information Deriving System) is described. The inference scheme can be conjoined with ordinary rule-based reasoning systems and hence generalized into many different domains.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.3
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• pp.264-270
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• 2011

A new method for creating a logical data model is proposed. The logical data model developed by the method defines table, primary key, foreign key, and fields. The framework of the logical data model is constructed by modeling the relationships between events and their related entity types. The proposed method consists of a series of objective and quantitative decisions such as maximum cardinality of relationships and functional dependency between the primary key and attributes. Even beginners to database design can use the methology as long as they understand such basic concepts about relational databases as primary key, foreign key, relationship cardinality, parent-child relationship, and functional dependency. The simple and systematic approach minimizes decision errors made by a database designer. In practial database design the method creates a logical data model in Boyce-Codd normal form unless the user of the method makes a critical decision error, which is very unlikely.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.1952-1954
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• 2001

In this paper, we propose the neuro-fuzzy modeling method using VmGA (Virus messy Genetic Algorithm) for the complex nonlinear system. VmGA has more effective and adaptive structure than sGA. in this paper, we suggest a new coding method for applying the model's input and output data to the optimal number of rules in fuzzy models and the structure and parameter identification of membership functions simultaneously. The proposed method realizes the optimal fuzzy inference system using the learning ability of neural network. For fine-tune of parameters identified by VmGA, back- propagation algorithm is used for optimizing the parameter of fuzzy set. The proposed fuzzy modeling method is applied to a nonlinear system to prove the superiority of the proposed approach through comparing with ANFIS.

• The Korean Journal of Applied Statistics
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• v.25 no.6
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• pp.947-958
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• 2012

When modeling event times in biomedical studies, the outcome might be incompletely observed. In this paper, we assume that the outcome is recorded as current status failure time data. Despite well-developed literature the routine practical use of many current status data modeling methods remains infrequent due to the lack of specialized statistical software, the difficulty to assess model goodness-of-fit, as well as the possible loss of information caused by covariate grouping or discretization. We propose a model based on pseudo-observations that is convenient to implement and that allows for flexibility in the choice of the outcome. Parameter estimates are obtained based on generalized estimating equations. Examples from studies in bile duct hyperplasia and breast cancer in conjunction with simulated data illustrate the practical advantages of this model.