• Journal of Korean Society on Water Environment
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• v.26 no.3
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• pp.532-539
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• 2010

The synthetic unit hydrograph is developed and verified using Nash model and characteristic velocities considering geomorphological dispersion in this present study. Application watersheds are selected 5 subwatersheds of Bocheong basin. The mean and variance of hillslope and stream path length are estimated in each watershed with GIS. Characteristic velocities are calculated using estimated path lengths and moment characteristics of rainfall-runoff data. Characteristic velocities of random devised 7 ungauged watersheds are estimated through regional analysis of chracteristic velocities in guaged watershed. And Nash model parameters and IUH are derived using characteristic velocities and path length in the gauged and ungauged watershed. The result to compare of IUH about gauged watershed and random devised ungauged watershed in application watershed presents coherently hydrologic response characteristics that peak discharge is reduced and peak time is extended. In conclusion, Developed synthetic unit hydrograph in this study expects that it is useful method to estimate runoff discharge for managing of water pollution in ungauged watershed.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1003-1006
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• 2002

In the communications systems with diversity, we are commonly faced on needing of new source coding technique, error resilient coding. The error resilient coding addresses the coding algorithm that has the robustness to unreliability of communications channel. In recent years, many error resilient coding techniques were proposed such as data partitioning, resynchronization, error detection, concealment, reference picture selection and multiple description coding (MDC). Especially, the MDC using correlating transform explicitly adds correlation between two descriptions to enable the estimation of one set from the other. However, in the conventional correlating transform method, there is a critical problem that decoder must know statistics of original image. In this paper, we propose an enhanced method, the MDC using whitening transform that is not necessary additional statistical information to decode image because the DCT coefficients to apply whitening transform to an image have uni-variance statistics. Our experimental results show that the proposed method achieves a good trade-off between the coding efficiency and the reconstruction quality. In the proposed method, the PSNR of images reconstructed from two descriptions is about 0.7dB higher than conventional method at the 1.0 BPP and from only one description is about 1,8dB higher at the same rate.

• Transactions of the Korean Society of Mechanical Engineers
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• v.12 no.4
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• pp.694-704
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• 1988

A recursive parameter estimation scheme utilizing the variance perturbation method is applied to the workpiece deflection model during CNC turning process, in order to improve the cylindricity of slender workpiece. It features that it is based on exponentially weighted recursive least squares method with post-process measurement of finish surfaces at two locations and it does not require a priori knowledge on the time varying deflection model parameter. The measurements of finish surfaces by using two proximity sensors mounted face to face enable one to identify the straightness, guide-way, run-out eccentricity errors. Preliminary cutting tests show that the straightness error of the finish surface due to workpiece deflection during cutting is most dominant. Identifying the errors and recursive updating the parameter, the off-line control is carried out to compensate the workpiece deflection error, through single pass cutting. Experimental results show that the proposed method is superior to the conventional multi-pass cutting and the direct compensation control in cutting accuracy and efficiency.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.11
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• pp.22-33
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• 1999

This paper presents the method for the automatic tuning of a design weighting polynomial parameters of a generalized minimum-variance stochastic ultivariable self-tuning controller which adapts to changes in the higher order nonminimum phase system parameters with time delays and noises. The self-tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optimizing the design weighting polynomial parameters of the controller. The proposed multivariable self-tuning method is simple and effective compared with pole restriction method. The computer simulation results are presented to adapt the higher order multivariable system with nonminimum phase and with changeable system parameters.

• Korean Journal of Poultry Science
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• v.25 no.3
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• pp.103-111
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• 1998

This study was carried out to estirnate the heritabilities and genetic correlations on egg shape index and internal egg qualities ; shell thickness, alburnin heights and Haugh units for breeding plan and selection in Korean native chicken. Data analyzed were the records of 46,908 eggs from 43() layers from April, 1994 to September, 1995. The egg shape index at the first egg, 300 days and 500 days of ages were 74.771, 74.468 and 73.702; the shell thickness were 0.345, 0.344 and 0. 334mm; the alburnen heights were 6.579, 6.130 and 5.318mm; the Haugh units were 86.859, 81.014 and 73.565 respectively. The heritability estimates of egg shape index and internal egg qualities based on the variance of sire, dam and combined components at 300 days of age were 0.136, 0.954 and 0.545 for egg shape index; 0.201, 0.622 and 0.421 for shell thickness; 0.410, 0.961 and 0.633 for albumen height ; 0.353, 0.962 and': 0.608 for Haugh units. The genetic correlation coefficient between shell thickness and albumen height was -0.044~0.824; 0.016~0.949 between Haugh units and shell thickness 0.313~0.941 between albumen height and Haugh units, respectively.

• Advances in concrete construction
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• v.8 no.4
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• pp.321-333
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• 2019

The present study targets to access the consequence of utilization of coarse aggregates retrieved from waste concrete as a substitution of coarse fraction of natural aggregates and silica nano-particles as partial substitution of cement using principles of factorial design. Furthermore, procedures of design of experiments are employed to examine the effect of use of recycled aggregates and nano-silica. In this investigation, compressive strength found after at 7, 28, 90 and 365 days, split and flexural tensile strength, ultrasonic pulse velocity and rebound number and are chosen as responses, whereas the percentages of recycled coarse aggregates (RCA%) and nano-silica (NS(%)) are selected as factors. Analysis of Variance has been conducted on the experimental results for the selected responses with consideration the both factors, which indicates that RCA (%) and NS (%) have substantial impact on the various responses. However, the present analysis depicts that interaction between factors has considerable effect on the chosen parameters of concrete. Furthermore, validation experiments are carried to validate these models for compressive and tensile strength for 100% RCA and 1% NS. The results of comparative study indicates that that the error of the estimation determined using the relevant models are found to be small (±5%) in comparison with the analogous experimental results, which authenticates the calculated models.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.1
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• pp.26-31
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• 2012

The highest frequency band of wavelet decomposition band is divided into 4 equal subbands and by the minimum power of the subbands and by the monotonic transform, the level adapted threshold is obtained. The adapted threshold is applied to the soft threshold technique to denoise high and middle frequency band noise of image signals. And the results of PSNRs are compared with the results obtained by the VisuShrink technique and by the technique using the monotonic transform and the weight value. The results showed the validity of this technique.

• Journal of Distribution Science
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• v.17 no.3
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• pp.5-19
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• 2019

Purpose - The purpose of this research is to investigate the factors contributing to sustainable competitive advantage for multi-level marketing (MLM) firms in Malaysia. The selected variables in this study are company image, product innovation, leadership, distributor rewards system and distributor training system. Research design, data, and methodology - Quantitative research method is employed with collected sample size of 398 respondents using judgmental sampling technique. Normality and reliability test were performed in the first stage utilizing SPSS 22 and Confirmatory Factory Analysis (CFA) and variance analysis were obtained in the subsequent stage, following up with the overall fit of the measurement model, Structural Equation Model (SEM) using AMOS 22 with maximum likelihood estimation to assess the internal consistency, convergent validity and discriminant validity. Results - The research findings show that company image, leadership, distributor rewards system and distributor training system were supported and are factors affecting the sustainable competitive advantage of MLM companies in Malaysia. However, in this study, product innovation was not supported but this result does not depict that it is trivial and inconsequential in maintain sustainable advantage. Conclusion - Companies can build sustainable competitive advantage by focusing on these contributing factors. Several other comments and implications were brought to light and discussed in the paper.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2001.04a
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• pp.102-109
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• 2001

In order to take account of the statistical properties of probability variables used in the structural analysis, the conventional approach using the safety factor based on past experience usually estimated the safety of a structure. The real structures could only be analyzed with the error in estimation of loads, material characters and the dimensions of the members. But the errors should be considered systematically in the structural analysis. Structural safety could not precisely be appraised by the traditional structural design concept. Recently, new approach based on the probability concept has been applied to the assessment of structural safety using the reliability concept. Thus, the computer program by the Probabilistic FEM is developed by incorporating the probabilistic concept into the conventional FEM method. This paper estimated for the reliability of a plane stress structure by Advanced First-Order Second Moment method using von Mises, Tresca and Mohr-Coulomb failure criterions. The reliability index and failure probability of attained by the Monte Carlo Simulation method with the von Mises criterion were same as PFEM, but the Monte Carlo Simulation were very time-consuming. The variance of member thickness and load could influence the reliability and failure probability most sensitively among the design variables from the results of the parameter analysis. And proper failure criterion must be used to design safely.

• Journal of the Korea Society of Computer and Information
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• v.21 no.8
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• pp.77-84
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• 2016

In general statistical analysis, we need to make a normal assumption. If this assumption is not satisfied, we cannot expect a good result of statistical data analysis. Most of statistical methods processing the outlier and noise also need to the assumption. But the assumption is not satisfied in big data because of its large volume and heterogeneity. So we propose a methodology based on box-plot and data smoothing for controling outlier and noise in big data analysis. The proposed methodology is not dependent upon the normal assumption. In addition, we select patent documents as target domain of big data because patent big data analysis is a important issue in management of technology. We analyze patent documents using big data learning methods for technology analysis. The collected patent data from patent databases on the world are preprocessed and analyzed by text mining and statistics. But the most researches about patent big data analysis did not consider the outlier and noise problem. This problem decreases the accuracy of prediction and increases the variance of parameter estimation. In this paper, we check the existence of the outlier and noise in patent big data. To know whether the outlier is or not in the patent big data, we use box-plot and smoothing visualization. We use the patent documents related to three dimensional printing technology to illustrate how the proposed methodology can be used for finding the existence of noise in the searched patent big data.