• Journal of Life Science
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• v.33 no.11
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• pp.915-922
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• 2023

Lactic acid bacteria (LAB) are widespread in a variety of environments including fermented dairy products, gastroinstetinal and urogenital tracts of human and animals, plant, soil and water. Leuconostoc mesenteroides DB3 was detected by the strongest antibacterial activities among 24 Leuconostoc strains isolated from Camellia japonica flowers. Acid tolerance of L. mesenteroides DB3 existed up to pH 2.5, but the resistance did not show at pH 2.0, which relatively excellent acid resistance existed. Bile acid tolerance was very stable within the test range to 1.2%. L. mesenteroides DB3 exhibited the optimal growth at 30℃, and showed a slight slow growth when compared with L. mesenteroides KCTC3505, which reached a stationary phase at 18 hr. The pH was changed along with the growth curve, but was maintained above pH 3.98. L. mesenteroides DB3 had higher initial antibacterial activities when compared to L. mesenteroides KCTC3505, but it showed similar activities with the standard strain after the latter part of the logarithmic growth phase. Although lactic acid production in L. mesenteroides DB3 was induced by lower amount in the initial part to the standard strain, it was exhibited by similar amounts after the late logarithmic growth phase. Muicin adhesion of L. mesenteroides DB-3 maintained superior to L. mesenteroides KCTC3505. Both strains showed excellent emulsification ability for kerosene. In summary, we evaluate that L. mesenteroides DB-3 has a high potential for application as probiotics owing to its excellent antibacterial activity, acid resistance, bile acid resistance, and muicin adhesion.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.53-73
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• 2023

Although it is mandatory to wear a seat belt that can minimize human injury when traffic accident occurs, the number of traffic accident casualties not wearing seat belts still accounts for a significant proportion.The seat belt wearing detection system for all seats is a system that identifies whether all seat passengers wear a seat belt and encourages their usage, also it can be a useful technical countermeasure. Firstly, this study established the viability of system implementation by assessing the factors influencing the severity of injuries in traffic accidents through the development of an ordered probit model. Analysis results showed that the use of seat belts has statistically significant effects on the severity of traffic accidents, reducing the probability of death or serious injury by 0.054 times in the event of a traffic accident. Secondly, a meta-analysis was conducted based on prior research related to seat belts and injuries in traffic accidents to estimate the expected reduction in accident severity upon the implementation of the system.The analysis of the effect of accident severity reduction revealed that wearing seat belts would lead to a 63.3% decrease in fatal accidents, with the front seats showing a reduction of 75.7% and the rear seats showing a reduction of 58.1% in fatal accidents. Lastly, Using the results of the meta-analysis and traffic accident statistics, the expected decrease in the number of traffic accident casualties with the implementation of the system was derived to analyze the traffic safety effects of the proposed detection system. The analysis demonstrated that with an increase in the adoption rate of the system, the number of casualties in accidents where seat belts were not worn decreased. Specifically, at a system adoption rate of 60%, it is anticipated that the number of fatalities would decrease by more than three times compared to the current scenario. Based on the analysis results, operational strategies for the system were proposed to increase seat belt usage rates and reduce accident severity.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.34 no.5
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• pp.536-544
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• 2001

Three harmful algal bloom species with similar morphology, Cochlodinium polykrikoides, Gyodinium impudicum and Gymodinium catenatum have damaged to aquatic animals or human health by either making massive blooms or intoxication of shellfishes in a food chain. Eco-physiological and hydrodynamic studies on the harmful algae offer useful informations in the understanding their bloom mechanism by giving promising data for the prediction and modelling of harmful algal blooms event. Thus, we studied the abundance of these species in the coastal area of South Sea of Korea and their effects of temperature, salinity, irradiance and nutrient on the growth for the isolates. The timing for initial appearance of the three species around the coastal area of Namhaedo, Narodo and Wando was between Bate July and late August in 1999 when water temperature ranged from $22.8^{\circ}C\;to\;26.5^{\circ}C$ Vegetative cells of C. polykrikoides and G. impudicum were abundant until late September when water temperature had been dropped to less than $23^{\circ}C$. By contrast, vegetative cell of G. catenatum disappeared before early September, showing shorter period of abundance than the other two species in the South Sea. Both G. impudicum and G. catenatum revealed comparatively low density with a maximal cell density of 3,460 cells/L and 440 cells/L, respectively without making any bloom, while C. polykrikoides made massive blooms with a maximal cell density more than $40\times10^6$cells/L, The three species showed a better growth at the relatively higher water temperature ranging from 22 to $28^{\circ}C$ with their maximal growth rate at $25^{\circ}C$ in culture, which almost corresponded with the water temperature during the outbreak of C. polykrikoides in the coastal area of South Sea. Also, they all showed a relatively higher growth at the salinity from 30 to $35\%$. Specially, G. impudicum showed the euryhalic characteristics among the species, On the other hand, growth rate of G. catenatum decreased sharply with the increase of water temperature at the experimental ranges more than $35\%$. The higher of light intensities showed the better growth rates for the three species, Moreover, C. polykrikoides and G. impudirum continued their exponential growth even at 7,500 lux, the highest level of light intensity in the experiment, Therefore, It is assumed that C. polykrikoides has a physiological capability to adapt and utilize higher irradiance resulting in the higher growth rate without any photo inhibition response at the sea surface where there is usually strong irradiance during its blooming season. Although C. poiykikoides and G. impudicum continued their linear growth with the increase of nitrate ($NO_3^-$) and ammonium ($NH_4^-$) concentrations at less than the $40{\mu}M$, they didn't show any significant differences in growth rates with the increase of nitrate and ammonium concentrations at more than $40{\mu}M$, signifying that the nitrogen critical point for the growth of the two species stands between 13.5 and $40{\mu}M$. Also, even though both of the two species continued their linear growth with the increase of phosphate ($PO_4^{2-}$) concentrations at less than the $4.05{\mu}M$, there were no any significant differences in growth rates with the increase of phosphate concentrations at more than $4.05{\mu}M$, signifying that the phosphate critical point for the growth of the two species stands between 1.35 and $4.05{\mu}M$. On the other hand, C. polykrikoides has made blooms at the oligotrophic environment near Narodo and Namhaedo where the concentration of DIN and DIP are less than 1.2 and $0.3{\mu}M$, respectively. We attributed this phenomenon to its own ecological characteristics of diel vertical migration through which C. polykrikoides could uptake enough nutrients from the deep sea water near bottom during the night time irrespective of the lower nutrient pools in the surface water.

• Journal of Radiation Protection and Research
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• v.23 no.3
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• pp.139-147
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• 1998

Purpose: Tissue inhomogeneity such as lung affects tumor dose as well as transmission dose in new concept of on-line dosimetry which estimates tumor dose from transmission dose using the new algorithm. This study was carried out to confirm accuracy of correction by tissue density in tumor dose estimation utilizing transmission dose. Methods: Cork phantom (CP, density $0.202\;gm/cm^3$) having similar density with lung parenchyme and polystyrene phantom (PP, density $1.040\;gm/cm^3$) having similar density with soft tissue were used. Dose measurement was carried out under condition simulating human chest. On simulating AP-PA irradiation, PPs with 3 cm thickness were placed above and below CP, which had thickness of 5, 10, and 20 cm. On simulating lateral irradiation, 6 cm thickness of PP was placed between two 10 cm thickness CPs additional 3 cm thick PP was placed to both lateral sides. 4, 6, and 10 MV x-ray were used. Field size was in the range of $3{\times}3$ cm through $20{\times}20$ cm, and phantom-chamber distance (PCD) was 10 to 50 cm. Above result was compared with another sets of data with equivalent thickness of PP which was corrected by density. Result: When transmission dose of PP was compared with equivalent thickness of CP which was corrected with density, the average error was 0.18 (${\pm}0.27$) % for 4 MV, 0.10 (${\pm}0.43$) % for 6 MV, and 0.33 (${\pm}0.30$) % for 10 MV with CP having thickness of 5 cm. When CP was 10 cm thick, the error was 0.23 (${\pm}0.73$) %, 0.05 (${\pm}0.57$) %, and 0.04 (${\pm}0.40$) %, while for 20 cm, error was 0.55 (${\pm}0.36$) %, 0.34 (${\pm}0.27$) %, and 0.34 (${\pm}0.18$) % for corresponding energy. With lateral irradiation model, difference was 1.15 (${\pm}1.86$) %, 0.90 (${\pm}1.43$) %, and 0.86 (${\pm}1.01$) % for corresponding energy. Relatively large difference was found in case of PCD having value of 10 cm. Omitting PCD with 10 cm, the difference was reduced to 0.47 (${\pm}$1.17) %, 0.42 (${\pm}$0.96) %, and 0.55 (${\pm}$0.77) % for corresponding energy. Conclusion When tissue inhomogeneity such as lung is in tract of x-ray beam, tumor dose could be calculated from transmission dose after correction utilizing tissue density.

• 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.