• Korean Journal of Food Science and Technology
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• v.22 no.5
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• pp.539-542
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• 1990

The effects of immersion temperature $(20,\;40\;and\;60^{\circ}C)$ and immersion times (6. 12 and 18 min) in a distilled water prior to air dehydration upon the browning reaction and pyruvic acid content of air dried onions to a 4.071 moisture content (wet basis) were analyzed by a response surface methodology (RSM). Those values were also predicted by using a second degree polynomial regression model. Immersion temperature had more influence to browning reaction and pyruvic acid content than immersion time in these experimental ranges. The processing conditions to minimize the browning reaction of dried onions at $50^{\circ}C$ of air temperature (O.D.=0.071) were $60^{\circ}C$ of immersion temperature and 18 min of immersion time compared to control (O.D.=0.168) of air dehydration at $50^{\circ}C$ Pyruvic acid contents of dried onions at $50^{\circ}C$ of air temperature were maximized $(39.85{\mu}mole/g\;onion\;solid)$ at $60^{\circ}C$ of immersion temperature and 12 min of immersion time compared to control $(24.08{\mu}mole/g\;onion\;solid)$ of air dehydration at $50^{\circ}C$.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.4A
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• pp.385-393
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• 2009

This study grasped the relationship between relative humidity in concrete and concrete shrinkage followed by pre-absorbed water of porous lightweight aggregates through measurements of concrete shrinkage and humidity and comparisons with established research results. It was showed that shrinkage reduction effect of lightweight concrete is 36% at 7 days early ages and 25% at 180 days long-term ages when water-binder ratio is 0.3. It also showed that shrinkage reduction effect is 19% at 7 days and 16% at 180 days when water-binder ratio is 0.4 and 37%, 32% when water-binder ratio is 0.5. The moisture supply effect of lightweight aggregates was remarkable at early age within 7~10 days irrespective of water-binder ratio. In case of waterbinder ratio is 0.3, the relationship between shrinkage and internal humidity of concrete has been underestimated regardless of applied existing model type and in case of water-binder ratio is 0.4, 0.5, measurement values are relatively similar with existing model equations. Finally this study did regression analyses about the relation among the humidity change and the shrinkage strain as a high-degree polynomial and derived parameters that can connect moisture movement analysis with differential shrinkage analysis in case of considering relative humidity at the time by moisture movement analysis of concrete.

• Journal of Korean Society of Forest Science
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• v.78 no.2
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• pp.143-150
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• 1989

This research was performed to estimate the influence of relative light intensity and planting density on the growth of dry weight of needles and other organs growth in Korean white pine seedlings raised in the transplanting bed. 1. As treated with various light intensities, relationships between needle dry weight and growth of other organs(dry weight of shoot, root and diameter of seedlings) had significantly positive correlations and linear regressions, but regression between needle dry weight and seedling elongation was a second degree polynomial. As treated with various planting densities, the second degree regression curve was found between needle dry weight and shoot dry weight, and seedling elongation, And linear regression between needle dry weight and root dry weight, and seedling dry weight could be estimated, while any regression between needle dry weight and diameter was not recognized. 2. As treated with various light intensities, linear regression between leaf area and shoot dry weight, and seedling dry weight, exponential regression between leaf area and seedling elongation were significantly recognized, while a tendency of logarithmic regression between leaf area and diameter appeared. According to the different density treatment, logarithmic regression between leaf area and shoot dry weight, linear regression between leaf area and root dry weight, and seedling dry weight, but quadric regression between leaf area and seedling elongation and diameter were significantly found.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.2
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• pp.23-34
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• 2004

Video camera can be a useful tool to capture images for use in colorimeter. However the RGB signals generated by different video camera are not equal for the same scene. The video camera for use in colorimeter is characterized based on the CIE standard colorimetric observer. One method of deriving a colorimetric characterization matrix between camera RGB output signals and CIE XYZ tristimulus values is least squares polynomial modeling. However it needs tedious experiments to obtain camera transfer matrix under various white balance point for the same camera. In this paper, a new method to obtain camera transfer matrix under different white balance by using 3${\times}$3 camera transfer matrix under a certain white balance point is proposed. According to the proposed method camera transfer matrix under any other white balance could be obtained by using colorimetric coordinates of phosphor derived from 3${\times}$3 linear transfer matrix under the certain white balance point. In experimental results, it is demonstrated that proposed method allow 3${\times}$3 linear transfer matrix under any other white balance having a reasonable degree of accuracy compared with the transfer matrix obtained by experiments.

• 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.