• Journal of the Korea Concrete Institute
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• v.20 no.2
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• pp.147-156
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• 2008

In an uniaxial compressive test of a concrete standard specimen (150$\times$300 mm) the crack initiation and extension with the stress increase are the major reason of the failure, which is similar to the breakage of the particle bonding in the simulation by using particle bonded model, especially particle flow code in 3 dimensions (PFC3D) developed by Itasca Consulting Group Inc. That is the main motive to study the possibility of an uniaxial compressive strength test simulation. It is important to investigate the relationship between the micro-parameters and the macro-properties because the 3-dimensional particle bonded model uses the spherical particles to analyze the physical phenomena. Contact bonded model used herein has eight micro-parameters and there are five macro-properties; Young's modulus, Poisson's ratio, uniaxial compressive strength and the crack initiation stress and the ratio concerning the crack propagation with the stress. To simulate the compressive test we made quantitative relationships between the micro-parameters and the macro-properties by using the fractional factorial design and various sensitivity analyses including regression analysis, which result in the good agreement with the previous studies. Also, the stress-stain curve and the crack distribution over the specimen given by PFC3D showed the mechanical behavior of the concrete standard specimen under the uniaxial compression. It is concluded that the particle bonded model can be a good tool for the analyzing the mechanical behavior of concrete under the uniaxial compressive load.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.55-71
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• 2013

The prediction model is the main factor affecting the performance of a knowledge-based system for bankruptcy prediction. Earlier studies on prediction modeling have focused on the building of a single best model using statistical and artificial intelligence techniques. However, since the mid-1980s, integration of multiple techniques (hybrid techniques) and, by extension, combinations of the outputs of several models (ensemble techniques) have, according to the experimental results, generally outperformed individual models. An ensemble is a technique that constructs a set of multiple models, combines their outputs, and produces one final prediction. The way in which the outputs of ensemble members are combined is one of the important issues affecting prediction accuracy. A variety of combination schemes have been proposed in order to improve prediction performance in ensembles. Each combination scheme has advantages and limitations, and can be influenced by domain and circumstance. Accordingly, decisions on the most appropriate combination scheme in a given domain and contingency are very difficult. This paper proposes a confidence-based selection approach as part of an ensemble bankruptcy-prediction scheme that can measure unified confidence, even if ensemble members produce different types of continuous-valued outputs. The present experimental results show that when varying the number of models to combine, according to the creation type of ensemble members, the proposed combination method offers the best performance in the ensemble having the largest number of models, even when compared with the methods most often employed in bankruptcy prediction.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.42 no.11
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• pp.41-48
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• 2005

The crosstalk effects that can be observed in the very dee submicron semiconductor chips are due to the coupling capacitances between interconnect lines. The accuracy of the full-chip timing analysis is determined by the accuracy of the estimated propagation delays of cells and interconnects within the chip. This paper presents a CMOS cell driver model and delay calculation algerian capturing the crosstalk effects due to the coupling capacitances. The proposed model and algorithm were implemented in a delay calculation program and used to estimate the propagation delays of the benchmark circuits extracted from a chip layout. We observed that the average discrepancy from HSPICE simulation results is within $1\%$ for the circuits with a victim affected by $0\~10$ aggressors.

• Tunnel and Underground Space
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• v.21 no.3
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• pp.216-224
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• 2011

In this study, Class II behavior of rock failure process under uniaxial and biaxial compression has been numerically simulated using bonded particle model. Class II behavior of rock was simulated by radial strain controlled uniaxial and biaxial compression tests using a suggested method of ISRM. Micro-parameters used in the simulation were determined based on the laboratory uniaxial compression tests carried out at ${\"{A}}sp{\"{o}}$ Hard Rock Laboratory, Sweden. Class II behavior of ${\"{A}}sp{\"{o}}$ rock was effectively simulated using newly proposed numerical technique in this study, and the results of numerical simulations show good similarity with the complete stress-strain curves for Class II behavior obtained from the laboratory tests.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.752-763
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• 2003

In the large scale B2B transaction like buying ´Express-Train´ or selling ´Daewoo Motor`, a tremendous amount of variables and factors of chaos functionate in it directly or indirectly. To get the effective information processing on the so called complex system like this, it should be possible to unite the human´s ability on the implicit information processing and the agent´s ability on the explicit information processing. In this paper, we suggested a union model for uniting these two heterogeneous abilities and showed how the suggested model can be used for processing the information of such a complex system as B2B negotiation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.1
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• pp.20-28
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• 1992

Co-articulation is one of major factors that make connected word recognition difficult. This Study Considers the fact that the head Part Of the following word is changed by the Preceding word in a connection point, by applying the co-articulation model, and adj usting the following word .We choose a critical damping second order linear system for the co-articulation model, combining a one-stage DP matching recognition algorithm with this model, and Investigating the effects. The recognition experiment is carried out for 35 Korean 4 connected digits spoken by 5 male speakers, and recognition rate Is upgraded by 4.7 percent.

• The Journal of the Acoustical Society of Korea
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• v.36 no.3
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• pp.202-210
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• 2017

For the target tracking in cluttered environment using a bistatic sonar whose transmitter and receiver are separately positioned, it is necessary to use data association algorithm via applying a proper measurement modelling to the bistatic sonar. The measurements obtained from the interval of ownship's maneuver have an increased error due to uncertainty of the position of transmitter and receiver. Using the measurements from this interval results in poor target tracking performance. In this paper, an improved tracking performance for the proposed data association based multiple model algorithm is validated by a monte carlo simulation.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.1
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• pp.24-31
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• 2006

In the present study, a strongly coupled analysis code is developed for transonic flutter analysis. For aerodynamic analysis, two dimensional Reynolds-Averaged Navier-Stokes equation was used for governing equation, and ε-SST for turbulence model, DP-SGS(Data Parallel Symmetric Gauss Seidel) Algorithm for parallelization algorithm. 2 degree-of-freedom pitch and plunge model was used for structural analysis. To obtain flutter response in the time domain, dual time stepping method was applied to both flow and structure solver. Strongly coupled method was implemented by successive iteration of fluid-structure interaction in pseudo time step. Computed results show flutter speed boundaries and limit cycle oscillation phenomena in addition to typical flutter responses - damped, divergent and neutral responses. It is also found that the accuracy of transonic flutter analysis is strongly dependent on the methodology of fluid-structure interaction as well as on the choice of turbulence model.

• The Journal of the Acoustical Society of Korea
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• v.36 no.4
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• pp.261-266
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• 2017

In this paper, we propose a vocal and nonvocal separation method which uses a combination of kernel model and LSTM (Long-Short Term Memory) networks. Conventional vocal and nonvocal separation methods estimate the vocal component even in sections where only non-vocal components exist. This causes a problem of the source estimation error. Therefore we combine the existing kernel based separation method with the vocal/nonvocal classification based on LSTM networks in order to overcome the limitation of the existing separation methods. We propose a parallel combined separation algorithm and series combined separation algorithm as combination structures. The experimental results verify that the proposed method achieves better separation performance than the conventional approaches.

• Journal of the Korean Geographical Society
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• v.49 no.3
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• pp.423-437
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• 2014

Districting is a spatial decision making process to make a new regional framework for affecting human activities. Natural barriers such as rivers and mountains located within a reorganized district may reduce the efficiency of reorganized human activities. This implies that it is necessary to consider boundary characteristics in a districting process. The purpose of this research is to develop a new spatial optimization model based on boundary characteristics for districting problems. The boundary characteristics are evaluated as continuous value expressing the possibility of combining adjacent two basic spatial units rather than a dichotomous value with 1 or 0 and are defined as an objective function in the model. In addition, the model has explicitly formulated contiguity constraints as well as constraints enforcing demand balance among districts such as population and area. The boundary attributes are categorized into physical and relational characteristics. Suitability analysis is used to combine various variables related to each boundary characteristic and to evaluate the coupling possibility between two neighboring basic units. The model is applied to an administrative redistricting problem. The analytical results demonstrate that various boundary characteristics could be modeled in terms of mixed integer programming (MIP).