• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.105-111
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• 2017

This paper compares the SE-MMA (Signed Error-MMA) and QE-MMA (Quantized Error-MMA) adaptive equalization algorithm in order to compensates the intersymbol interference due to channel in the transmission of spectral efficient nonconstant modulus signal such as 16-QAM. In the currently MMA adaptive equalizer, the error signal is needed for the updating the tap coefficient. The SE-MMA uses the polarity of error signal for reduce the computational operation in that process, the QE-MMA consider the this polarity and finite bit power-of-2 quantized component in that process, so they has different equalization performance. In order to comparing these performance, the computer simulation was performed in the same channel and environment, the output signal constellation of equalizer, residual isi and maximum distortion, MSE, SER were applied. As a result of computer simulation, the QE-MMA have more superior performance than the SE-MMA in every performance index.

• International Journal of Highway Engineering
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• v.11 no.4
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• pp.17-23
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• 2009

Deformational characteristics of subgrade soils are very important input parameters for pavement design. It is necessary to make an amount of effort to estimate experimentally the modulus of subgrade soils. In case of designing simple (or lower level) pavement section, the estimation of the modulus based on experiments must cause an excessive cost. It has proposed various empirical correlation models to estimate the modulus from basic properties of the materials or more simple alternative tests. Seven subgrade soils in Korea were tested in this study. It was founded that the deformational characteristics of subgrade soils in Korea has a close relation to strength characteristics, the empirical correlation model was proposed. There was a close relation between cohesion value and modulus at low confining stress ($r^2=0.93$). By comparing with the measured modulus and the modulus determined by proposed correlation model from strength characteristics, the value of the coefficient of determination ($r^2$) is 0.75.

• Journal of the Korean Society for Railway
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• v.19 no.2
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• pp.204-212
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• 2016

The soils used as trackbed in Korea are selected using USCS utilizing basic soil properties such as Grain Size Distribution(GSD), % passing of #200 sieve ($P_{200}$), % passing of #4 sieve ($P_4$), Coefficient of uniformity ($C_u$), and Coefficient of curvature ($C_c$). Degree of compaction of the soils adapted in the code by KR should be evaluated by maximum dry density (${\gamma}_{d-max}$) and deformation modulus $E_{v2}$. The most important influencing factor that is critical to stability and deformation of the compacted soils used as trackbed is stiffness. Thus, it is necessary to construct a correlation between the modulus and the basic soil properties of trackbed soil in order to redefine a new soil classification system adaptable only to railway construction. To construct the relationship, basic soil test data is collected as a database, including GSD, maximum dry unit weight (${\gamma}_{d-max}$), OMC, $P_{200}$, $P_4$, $C_u$, $C_c$, etc.; deformation modulus $E_{v2}$ and $E_{vd}$ are obtained independently by performing a Repeated Plated Bearing Test (RPBT) and Light Weight Deflectometer Test (LWDT) for ten different railway construction sites. A linear regression analysis is performed using SPSS to obtain the relationship between the basic soil properties and the deformation modulus $E_{v2}$ and $E_v$. Based on the constructed relationship and the various obtained mechanical test data, a new soil classification system will be proposed later as a guideline for the design and construction of trackbed foundation in Korea.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.1
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• pp.83-88
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• 2017

This paper related with the performance evaluation of H-MMA (Hybrid-MMA) which is applying the adaptive modulus and adaptive step size concept to MMA adaptive equalization algorithm in order to reduce the intersymbol interference that is occurred in communication channel for digital code transmission. In the conventional MMA adaptive equalizer, the coefficient is updated by using the equalizer output and possible to compensation of amplitude and phase in 2nd dimensional QAM signal, the equalization performance were degraded due to fixed modulus and step size. For the overcomming the abovemensioned problem, it is possible to improving the equalization performance in the 2nd dimensional QAM signal by applying the adaptive modulus and adaptive step size propotional to equalizer output signal to the conventional MMA algorithm. The computer simulation was performed in the same channel for the compare the performance of MMA and proposed H-MMA which is proposed in this paper. As a result of simulation, the proposed H-MMA has slower convergence time in order to arriving the steady state than MMA. But after the steady state, H-MMA has more superior to the MMA in every performance index and the equalization noise was reduced.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.115-120
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• 2016

This paper deals with AM-SMMA (Adaptive Modulus-SMMA) adaptive equalization algorithm that is possible to improves the equalization performance using adaptive modulus which is propotional to the output signal power of equalizer in the current SMMA algorithm. The fixed statistic modulus of transmitted QAM signal is used in current SMMA algorithm in order to generate the error signal for updating the tap coefficient of equalizer. The adaptive modulus which is propotion to the equalizer output signal power is used in the proposed AM-SMMA. The computer simulation was performed in order to confirm the improved equalization performance of proposed algorithm. The performance index includes the output signal constellation, the residual isi and maximum distortion that is for the convergence characteristics, the SER. As a result of computer simulation, the residual isi, maximum distortion are better in the small weighting values. But in SER performance is better in the large weighting values.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.1404-1414
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• 2008

In the mechanistic-empirical trackbed design of railways, the resilient modulus is the key input parameter. This study focused on the resilient modulus prediction model, which is the functions of mean effective principal stress and axial strain, for three types of railroad trackbed materials such as crushed stone, weathered soil, and crushed-rock soil mixture. The model is composed with the maximum Young's modulus and nonlinear values for higher strain in parallel with dynamic shear modulus. The maximum values is modeled by model parameters, $A_E$ and the power of mean effective principal stress, $n_E$. The nonlinear portion is represented by modified hyperbolic model, with the model parameters of reference strain, ${\varepsilon}_r$ and curvature coefficient, a. To assess the performance of the prediction models proposed herein, the elastic response of a test trackbed near PyeongTaek, Korea was evaluated using a 3-D nonlinear elastic computer program (GEOTRACK) and compared with measured elastic vertical displacement during the passages of freight and passenger trains. The material types of sub-ballasts are crushed stone and weathered granite soil, respectively. The calculated vertical displacements within the sub-ballasts are within the order of 0.6mm, and agree well with measured values with the reasonable margin. The prediction models are thus concluded to work properly in the preliminary investigation.

• Journal of the Korean GEO-environmental Society
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• v.15 no.2
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• pp.53-58
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• 2014

The uniaxial compressive strength and Young's modulus of intact rocks are the most important analytical parameters for design of rock mass structures. But the preparation of the samples for uniaxial compressive test is a hard and time consuming task. By using ultrasonic test, engineers can predict the analytical parameters that is the uniaxial compressive strength and Young's modulus. The uniaxial compressive test and ultrasonic test were carried out 115 samples of igneous rocks, 74 samples of metamorphic rocks and 55 samples of sedimentary rocks and, after regression analysis of the test results, best fit equations for predicting the uniaxial compressive strength and Young's modulus are proposed. In order to obtain a better correlations coefficient between uniaxial compressive strength and P-wave velocity, the P-wave velocity were multiplied by density values. The proposed equations for predicting uniaxial compressive strength and Young's modulus using ultrasonic test provide reliable results.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.79-84
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• 2019

This paper compare the performance of CM-MMA (Constellation Matching-MMA) and RMMA (Region-based MMA) blind equalization algorithm for improve the QoS by minimizing the intersymbol interference that is occurred in nonlinear communication channel when transmitting the QAM signal. In the tap coefficient update for adaptive, CM-MMA use the error of nonconstant modulus signal adding the current MMA cost fuction and constellation matching error terms of sinusoidal power function, and the RMMA use the error by transfoms the nonconstant modulus signal of equalizer output constellation to 4-QAM constant modulus signal. They has different equalization performance by these error signal, it were compared in this paper by simulation, and performance index such as output signal constellation of equalizer, residual isi, maximum distortion, SER curves are applied for this. As a result of computer simulation, the RMMA has more better performance in the every performance index, convergence speed, residual value, noise robustness compared to CM-MMA.

• Journal of Korean Tunnelling and Underground Space Association
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• v.14 no.1
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• pp.37-53
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• 2012

There is considerable uncertainty in ground properties used in tunnel designs. In this study, a back analysis was performed to find optimal ground properties based on the artificial neural network facility of MATLAB program of using tunnel monitoring data. Total 81 data were constructed by changing elastic modulus and coefficient of lateral pressure which have great influence on tunnel convergence. A sensitivity analysis was conducted to establish an optimal training model by varying the number of hidden layers, the number of nodes, learning rate, and momentum. Meanwhile, the optimal training model was selected by comparing MSE (Mean Squared Error) and coefficient of determination ($R^2$) and was used to find the correct elastic moduli of layers and the coefficient of lateral pressure. In future, it is expected that the suggested method of this study can be applied to determine the optimum tunnel support pattern under given ground conditions.

• Journal of the Society of Disaster Information
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• v.19 no.1
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• pp.31-43
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• 2023

Purpose: In this study, an analysis of the differences between the elastoplastic analysis and the numerical analysis and a study of the design ground constant recalculation method to derive similar trends in the analysis results were conducted. Method: The relational expression between the ground reaction force coefficient and the ground deformation coefficient at the time when the wall displacement becomes the same according to shallow excavation and deep excavation was derived. Result: Based on the measurement results, reverse analysis was performed to re-calculate the ground properties suitable for the site ground, and as a result of comparing and verifying the wall displacement using the derived formula and the literature formula, the proposed formula showed the most similar value. Conclusion: If the proposed formula is used, it will be helpful in practice because it is possible to infer the most similar ground properties to the actual at the time of design.