• Journal of the Korea Society for Simulation
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• v.20 no.2
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• pp.19-27
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• 2011

This study investigates impact of smoothed replenishment ordering policy on the performance measures such as lead time, order fulfillment ratio, and inventory cost. We consider a two-echelon supply chain: a single retailer orders using smoothed order up to replenishment policy and a manufacturer produces the retailer's orders on a make to order basis. Simulation result confirms that lead time from the manufacturer can be reduced by smoothed ordering policy as expected. However, smoothing orders may deteriorate the customer order fulfillment ratio and inventory cost in a retailer. We also observe that variance of manufacturing time contributes more than mean of manufacturing time to both order fulfillment ratio and inventory cost. Therefore, variability of upstream manufacturing time should be minimized.

• Journal of Korean Society for Atmospheric Environment
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• v.3 no.2
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• pp.53-61
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• 1987

Automatic and manual rain smaplers wre installed at the roof of National Institute of Environmental Research (NIER), and the rain sampling and measurement were conducted during the period April to August 31, 1987. The rain sampling and measurement were carried out in the following manners: The 1st : Acidity and conductivity were measured entirely by automatic rain sampler (continuous measurement) The 2nd : Acidity and conductivity wrer measured in the laboratory with the sample that was taken out of automatic rain sampler. The 3rd : Acidity and conductivity were measured in the laboratory with the sample that was taken out of manual rain sampler. Afterwards, those different measurement values were compared each other and the following conclusions were obtained: 1) The pH of the continous measurement by the automatic sampler was lower than that of the laboratory measurement, and it was reversed in case of the conductivity. 2) The significance was recognized at 5% risk ratio for the population mean of difference of the measurement values of the pH and conductivity from both samples. 3) The significance was not recognized at 5% risk ratio by the analysis of variance by one way layout for the pH and conductivity. 4) The significance was recognized at 5% risk ratio by the analysis of variance by two way layouts for the pH conductivity. 5) The significance was recognized at 5% rrisk ratio for the differences of the pH values obtained by oboth samplers, and no significance was recognized for conductivity. 6) In comparison of the measurement values from the two samplers were shown a good correlation for pH; correlation coefficient (r) = 0.63, and regression equation Y = 0.53X + 2.78. For conductivity, the correlation was also excellent; correlation coefficient (r) = 0.53 and regression equation Y = 0.63X + 5.65.

• Journal of Nutrition and Health
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• v.37 no.3
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• pp.210-222
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• 2004

In recent years, the number and proportion of Korean elderly have grown rapidly, and elderly individuals show a disproportionate risk for poor nutritional status. The purpose of this study was to examine the relationship of sociodemographic background to nutrient intake of persons 65 years of age or older, living in 15 cities in Korea. Data on 1973 subjects (603 males, 1370 females), who participated in the Korean Elderly Nutrition Survey (2000), were analyzed. Their mean age was 72.3 years and their mean body mass index (BMI) was 24.2 kg/$m^2$. Basic sociodemographic data were obtained through personal interviews. The 98-item semi-food frequency questionnaire, developed and previously validated for Korean middle-aged and elderly subjects, was administered. “Percentage of subjects who consumed under 75％ Korean RDA,” “number of nutrients consumed below 75％ Korean RDA,” “mean nutrient adequacy ratio,” and “nutrient density” were used to determine nutritional status. Male elderly had better nutritional quality than female elderly. Nutritional quality decreased with age, especially in older elderly (over 75). Elderly who were underweight (BMI 〈 20 kg/$m^2$) showed poorer nutritional quality than those who were normal weight (BMI 20∼25 kg/$m^2$) and overweight (BMI $\geq$ 25 kg/$m^2$). Elderly who lived alone had significantly poorer nutritional quality than those who lived with a spouse, and/or with children. Lower education level and economic dependence also showed lower nutritional quality. A stepwise multiple regression analysis was performed to examine the effects of specific sociodemographic factors on nutritional quality. For number of nutrients under 75％ RDA as a dependent variable, education level explained 4.8％ of the variance, followed by living status, age, body mass index, gender, and living expense support (Model $R^2$ = 0.091). For mean nutrient adequacy ratio as a dependent variable, model $R^2$ was 0.098. Therefore, sociodemographic variables such as gender, age, body mass index, living status, educational level, and economic status influenced elderly nutrition status. These results indicate that an elderly nutrition intervention should focus on subjects who are poorly educated, living alone, age 75 or older, and/or underweight.

• The Journal of the Acoustical Society of Korea
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• v.29 no.2
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• pp.97-101
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• 2010

FIR type system identification with noisy input and output data can be solved by a total least squares (TLS) estimation. However, the performance of the TLS estimation is very sensitive to the ratio between the variances of the input and output noises. In this paper, we propose an iterative convex combination algorithm between TLS and least squares (LS). This combined algorithm shows robustness against the noise variance ratio. Consequently, the practical workability of the TLS method with noisy data has been significantly broadened.

• Structural Engineering and Mechanics
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• v.81 no.5
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• pp.565-574
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• 2022

The infrastructures such as offshore, bridges, power plant, oil and gas piping and aircraft operate in a harsh environment during their service life. Structural integrity of engineering components used in these industries is paramount for the reliability and economics of operation. Two regression models based on the concept of Gaussian process regression (GPR) and Minimax probability machine regression (MPMR) were developed to predict stress intensity factor range (𝚫K). Both GPR and MPMR are in the frame work of probability distribution. Models were developed by using the fatigue crack growth data in MATLAB by appropriately modifying the tools. Fatigue crack growth experiments were carried out on Eccentrically-loaded Single Edge notch Tension (ESE(T)) specimens made of API 5L X65 Grade steel in inert and corrosive environments (2.0% and 3.5% NaCl). The experiments were carried out under constant amplitude cyclic loading with a stress ratio of 0.1 and 5.0 Hz frequency (inert environment), 0.5 Hz frequency (corrosive environment). Crack growth rate (da/dN) and stress intensity factor range (𝚫K) values were evaluated at incremental values of loading cycle and crack length. About 70 to 75% of the data has been used for training and the remaining for validation of the models. It is observed that the predicted SIF range is in good agreement with the corresponding experimental observations. Further, the performance of the models was assessed with several statistical parameters, namely, Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Coefficient of Efficiency (E), Root Mean Square Error to Observation's Standard Deviation Ratio (RSR), Normalized Mean Bias Error (NMBE), Performance Index (ρ) and Variance Account Factor (VAF).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.10A
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• pp.1566-1575
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• 2000

This paper studies mismatched scalar quantization of a generalized gamma source by a quantizer that is optimally (in the mean square error sense) designed for another generalized gamma source. Specifically, it considers variance-mismatched quantization which occurs when the variance of the source to be quantized differs from tat of the designed-for source. The main result is the two distortion formulas derived from Bennett's integral. The first formula is an approximation expression that uses the outermost threshold of an optimum scalar quantizer, and the second formula, in turn, uses an approximation formula for this outermost threshold. Numerical results are obtained for Laplacian sources, which are example of a generalized gamma source, and comparisons are made between actual mismatched distortions and the two formulas. These numerical results show that the two formulas become more accurate, as the number of quantization points gets larger and the ratio of the source variance to that of the designed-for source gets bigger. For example, the formulas are within 2~4% of the actual distortion for approximately 64 quantization points or more. In conclusion, the proposed approximation formulas are considered to have contribution as closed formulas and for their accuracy.

• The Journal of Advanced Prosthodontics
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• v.8 no.3
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• pp.181-186
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• 2016

PURPOSE. The opacity of zirconia is an esthetic disadvantage that hinders achieving natural and shade-matched restorations. The aim of this study was to evaluate the translucency of non-colored and colored framework zirconia and monolithic zirconia. MATERIALS AND METHODS. The three groups tested were: non-colored framework zirconia, colored framework zirconia with the A3 shade according to Vita Classic Scale, and monolithic zirconia (n=5). The specimens were fabricated in the dimensions of $15{\times}12{\times}0.5mm$. A spectrophotometer was used to measure the contrast ratio, which is indicative of translucency. Three measurements were made to obtain the contrast ratios of the materials over a white background ($L^*w$) and a black background ($L^*b$). The data were analyzed using the one-way analysis of variance and Tukey HSD tests. One specimen from each group was chosen for scanning electron microscope analysis. The determined areas of the SEM images were divided by the number of grains in order to calculate the mean grain size. RESULTS. Statistically significant differences were observed among all groups (P<.05). Non-colored zirconia had the highest translucency with a contrast ratio of 0.75, while monolithic zirconia had the lowest translucency with a contrast ratio of 0.8. The mean grain sizes of the non-colored, colored, and monolithic zirconia were 233, 256, and 361 nm, respectively. CONCLUSION. The translucency of the zirconia was affected by the coloring procedure and the grain size. Although monolithic zirconia may not be the best esthetic material for the anterior region, it may serve as an alternative in the posterior region for the bilayered zirconia restorations.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.39-55
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• 2019

Recently banks and large financial institutions have introduced lots of Robo-Advisor products. Robo-Advisor is a Robot to produce the optimal asset allocation portfolio for investors by using the financial engineering algorithms without any human intervention. Since the first introduction in Wall Street in 2008, the market size has grown to 60 billion dollars and is expected to expand to 2,000 billion dollars by 2020. Since Robo-Advisor algorithms suggest asset allocation output to investors, mathematical or statistical asset allocation strategies are applied. Mean variance optimization model developed by Markowitz is the typical asset allocation model. The model is a simple but quite intuitive portfolio strategy. For example, assets are allocated in order to minimize the risk on the portfolio while maximizing the expected return on the portfolio using optimization techniques. Despite its theoretical background, both academics and practitioners find that the standard mean variance optimization portfolio is very sensitive to the expected returns calculated by past price data. Corner solutions are often found to be allocated only to a few assets. The Black-Litterman Optimization model overcomes these problems by choosing a neutral Capital Asset Pricing Model equilibrium point. Implied equilibrium returns of each asset are derived from equilibrium market portfolio through reverse optimization. The Black-Litterman model uses a Bayesian approach to combine the subjective views on the price forecast of one or more assets with implied equilibrium returns, resulting a new estimates of risk and expected returns. These new estimates can produce optimal portfolio by the well-known Markowitz mean-variance optimization algorithm. If the investor does not have any views on his asset classes, the Black-Litterman optimization model produce the same portfolio as the market portfolio. What if the subjective views are incorrect? A survey on reports of stocks performance recommended by securities analysts show very poor results. Therefore the incorrect views combined with implied equilibrium returns may produce very poor portfolio output to the Black-Litterman model users. This paper suggests an objective investor views model based on Support Vector Machines(SVM), which have showed good performance results in stock price forecasting. SVM is a discriminative classifier defined by a separating hyper plane. The linear, radial basis and polynomial kernel functions are used to learn the hyper planes. Input variables for the SVM are returns, standard deviations, Stochastics %K and price parity degree for each asset class. SVM output returns expected stock price movements and their probabilities, which are used as input variables in the intelligent views model. The stock price movements are categorized by three phases; down, neutral and up. The expected stock returns make P matrix and their probability results are used in Q matrix. Implied equilibrium returns vector is combined with the intelligent views matrix, resulting the Black-Litterman optimal portfolio. For comparisons, Markowitz mean-variance optimization model and risk parity model are used. The value weighted market portfolio and equal weighted market portfolio are used as benchmark indexes. We collect the 8 KOSPI 200 sector indexes from January 2008 to December 2018 including 132 monthly index values. Training period is from 2008 to 2015 and testing period is from 2016 to 2018. Our suggested intelligent view model combined with implied equilibrium returns produced the optimal Black-Litterman portfolio. The out of sample period portfolio showed better performance compared with the well-known Markowitz mean-variance optimization portfolio, risk parity portfolio and market portfolio. The total return from 3 year-period Black-Litterman portfolio records 6.4%, which is the highest value. The maximum draw down is -20.8%, which is also the lowest value. Sharpe Ratio shows the highest value, 0.17. It measures the return to risk ratio. Overall, our suggested view model shows the possibility of replacing subjective analysts's views with objective view model for practitioners to apply the Robo-Advisor asset allocation algorithms in the real trading fields.

• Fibers and Polymers
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• v.7 no.4
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• pp.424-431
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• 2006

Roll drafting, a mechanical operation attenuating fiber bundles to an appropriate thickness, is an important operation unit for manufacturing staple yams. It influences not only the linear density regularity of the slivers or staple yams that are produced, but also the quality of the textile product and the efficiency of the thereafter processes. In this research, the dynamic states of the fiber bundle in the roll drafting zone were analyzed by simulation, based on the mathematical model that describes the dynamic behavior of the flowing bundle. The state variables are the linear density and velocity of the fiber bundles and we simulated the dynamics states of the bundle flow, e.g., the profiles of the linear density and velocity in the draft zone for various values of the model parameters and boundary conditions, including the initial conditions to obtain their influence on the dynamic state. Results showed that the mean velocity profile of the fiber bundle was strongly influenced by draft ratio and process speed, while the input sliver linear density has hardly affected the process dynamics. Velocity variance of individual fibers that could be supposed to be a disturbing factor in drafting was also influenced by the process speed. But the major disturbance occurred due to the velocity slope discontinuity at the front roll, which was strongly influenced by the process speed. Thickness of input sliver didn't play any important role in the process dynamics.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.10C
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• pp.991-999
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• 2006

This paper shows that the support growth of an optimum (minimum mean square-error) scalar quantizer for a Laplacian density is logarithmic with the number of quantization points. Specifically, it is shown that, for a unit-variance Laplacian density, the ratio of the support-determining threshold of an optimum quantizer to $\frac 3{\sqrt{2}}1n\frac N 2$ converges to 1, as the number of quantization points grows. Also derived is a limiting upper bound that says that the optimum support cannot exceed the logarithmic growth by more than a constant. These results confirm the logarithmic growth of the optimum support that has previously been derived heuristically.