• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.6 s.165
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• pp.837-847
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• 2007

1,098 pieces of photographs($1995{\sim}2002$) of men's suit style have been classified according to fashion images in order to examine features and change aspects with statistical analysis. The findings of examining features of the trend by year with test of homogeneity, correspondence analysis, biplots, correlation analysis and regression analysis are as follows: (a) there are significant differences on fashion images as the trend by yew with test of homogeneity, (b) there are remarkable differences on the fashion trend by year with correspondence analysis and biplots. (c) There are significant correlations for appearance among fashion images by its frequency through correlation analysis, and (d) it is assumed that fashion images are going to be gradually outstanding according to regression analysis.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.27 no.4
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• pp.413-433
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• 1994

Jinhae Bay once was a productive area of fisheries. It is, however, now notorious for its red tides; and oxygen deficient water-masses extensively develop at present in summer. Therefore the shellfish production of the bay has been decreasing and mass mortality often occurs. Under these circumstances, the three-dimensional numerical hydrodynamic and the material cycle models, which were developed by the Institute for Resources and Environment of Japan, were applied to analyze the processes affecting the oxygen depletion and also to evaluate the environment capacity for the reception of pollutant loads without dissolved oxygen depletion. In field surveys, oxygen deficient water-masses were formed with concentrations of below 2.0mg/l at the bottom layer in Masan Bay and the western part of Jinhae Bay during the summer. Current directions, computed by the $M_2$ constituent, were mainly toward the western part of Jinhae Bay during flood flows and in opposite directions during ebb flows. Tidal currents velocities during the ebb tide were stronger than that of the flood tide. The comparision between the simulated and observed tidal ellipses showed fairly good agreement. The residual currents, which were obtained by averaging the simulated tidal currents over 1 tidal cycle, showed the presence of counterclockwise eddies in the central part of Jinhae Bay. Density driven currents were generated southward at surface and northward at the bottom in Masan Bay and Jindong Bay, where the fresh water of rivers entered. The material cycle model was calibrated with the data surveyed in the field of the study area from June to July, 1992. The calibrated results are in fairly good agreement with measured values within relative error of $28\%$. The simulated dissolved oxygen distributions of bottom layer were relatively high with the concentration of $6.0{\sim}8.0mg/l$ at the boundaries, but an oxygen deficient water-masses were formed within the concentration of 2.0mg/l at the inner part of Masan Bay and the western part of Jinhae Bay. The results of sensitivity analyses showed that sediment oxygen demand(SOD) was one of the most important influence on the formation of oxygen depletion. Therefore, to control the oxygen deficient water-masses and to conserve the coastal environment, it is an effective method to reduce the SOD by improving the polluted sediment. As the results of simulations, in Masan Bay, oxygen deficient water-masses recovered to 5.0mg/l when the $50\%$ reduction in input COD loads from Masan basin and $70\%$ reduction in SOD was conducted. In the western part of Jinhae Bay, oxygen deficient water-masses recovered to 5.0mg/l when the $95\%$ reduction in SOD and $90\%$ reduction in culturing ground fecal loads was conducted.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.20 no.3
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• pp.131-140
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• 2015

To set up unicellular cyanobacterial strains with photo-biological $H_2$ production potential, live samples were repeatedly collected from 68 stations in the coastal zone of Korea for the four years since 2005. Among 77 cyanobacterial strains established six (KNU strains, CB-MAL002, 026, 031, 054, 055 and 058) were finally chosen as the excellent strains for $H_2$ production with $H_2$ accumulation over 0.15 mL $H_2\;mL^{-1}$ under general basic $H_2$ production conditions as well as positive $H_2$ production for more than 60 hr. To explore optimum procedures for higher $H_2$ production efficiency of the six cyanobacterial strains, the inter-strain differences in the growth rate under the gradients of water temperature and salinity were investigated. The maximum daily growth rates of the six strains ranged from 1.78 to 2.08, and all of them exhibited $N_2-fixation$ ability. Based on the similarity of the 16S rRNA sequences, all the test strains were quite close to Cyanothece sp. ATCC51142 (99%). The six strains, however, were grouped into separate clades from strain ATCC51142 in the molecular phylogeny diagram. Chlorophyll- a content was 3.4~7.8% of the total dried weight, and the phycoerythrin and phycocyanin contents were half of those in the Atlantic strain, Synechococcus sp. Miami BG03511. The growth of the six strains was significantly suppressed at temperatures above the optimal range, $30{\sim}35^{\circ}C$, to be nearly stopped at $40^{\circ}C$. The growth was not inhibited by high salinities of 30 psu salinity in all the strains while strain CB055 maintained its high growth rate at low salinities down to 15 psu. The euryhaline strains like CB055 might support massive biotechnological cultivation systems using natural basal seawater in temperate latitudes. base seawater. The biological and ecophysiological characteristics of the test strains may contribute to designing the optimal procedures for photo-biological $H_2$ production by unicellular cyanobacteria.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.135-149
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• 2020

Artificial intelligences are changing world. Financial market is also not an exception. Robo-Advisor is actively being developed, making up the weakness of traditional asset allocation methods and replacing the parts that are difficult for the traditional methods. It makes automated investment decisions with artificial intelligence algorithms and is used with various asset allocation models such as mean-variance model, Black-Litterman model and risk parity model. Risk parity model is a typical risk-based asset allocation model which is focused on the volatility of assets. It avoids investment risk structurally. So it has stability in the management of large size fund and it has been widely used in financial field. XGBoost model is a parallel tree-boosting method. It is an optimized gradient boosting model designed to be highly efficient and flexible. It not only makes billions of examples in limited memory environments but is also very fast to learn compared to traditional boosting methods. It is frequently used in various fields of data analysis and has a lot of advantages. So in this study, we propose a new asset allocation model that combines risk parity model and XGBoost machine learning model. This model uses XGBoost to predict the risk of assets and applies the predictive risk to the process of covariance estimation. There are estimated errors between the estimation period and the actual investment period because the optimized asset allocation model estimates the proportion of investments based on historical data. these estimated errors adversely affect the optimized portfolio performance. This study aims to improve the stability and portfolio performance of the model by predicting the volatility of the next investment period and reducing estimated errors of optimized asset allocation model. As a result, it narrows the gap between theory and practice and proposes a more advanced asset allocation model. In this study, we used the Korean stock market price data for a total of 17 years from 2003 to 2019 for the empirical test of the suggested model. The data sets are specifically composed of energy, finance, IT, industrial, material, telecommunication, utility, consumer, health care and staple sectors. We accumulated the value of prediction using moving-window method by 1,000 in-sample and 20 out-of-sample, so we produced a total of 154 rebalancing back-testing results. We analyzed portfolio performance in terms of cumulative rate of return and got a lot of sample data because of long period results. Comparing with traditional risk parity model, this experiment recorded improvements in both cumulative yield and reduction of estimated errors. The total cumulative return is 45.748%, about 5% higher than that of risk parity model and also the estimated errors are reduced in 9 out of 10 industry sectors. The reduction of estimated errors increases stability of the model and makes it easy to apply in practical investment. The results of the experiment showed improvement of portfolio performance by reducing the estimated errors of the optimized asset allocation model. Many financial models and asset allocation models are limited in practical investment because of the most fundamental question of whether the past characteristics of assets will continue into the future in the changing financial market. However, this study not only takes advantage of traditional asset allocation models, but also supplements the limitations of traditional methods and increases stability by predicting the risks of assets with the latest algorithm. There are various studies on parametric estimation methods to reduce the estimated errors in the portfolio optimization. We also suggested a new method to reduce estimated errors in optimized asset allocation model using machine learning. So this study is meaningful in that it proposes an advanced artificial intelligence asset allocation model for the fast-developing financial markets.

• Development and Reproduction
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• v.11 no.3
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• pp.187-193
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• 2007

Ethane 1,2-dimethane sulfonate(EDS), a Leydig cell specific toxicant, has been widely used to create the reversible testosterone withdrawal rat model. Though the maintenance of epididymal structure and function is highly dependent on the testosterone secreted from testis, its derivatives, dihydroxytestosterone(DHT) and estrogen, might have crucial roles. The aim of present study was to monitor the expression patterns of sex steroid receptors, cytochrome P450 aromatase(P450arom) and $5{\alpha}$-reductase in the rat epididymis up to 7 weeks after EDS injection. Adult male rats($350{\sim}400g$) were injected with a single does of EDS(75 mg/kg i.p.) and sacrificed on weeks 0, 1, 2, 3, 4, 5, 6 and 7. The transcriptional activities of the target genes were evaluated by semi-quantitative RT-PCRs. The transcript level of estrogen receptor alpha($ER{\alpha}$) in EDS group was significantly higher than control level on week 1(P<0.01). After week 2, there was no significant difference in $ER{\alpha}$ levels between EDS group and control. The transcript level of estrogen receptor beta($ER{\beta}$) in EDS group was significantly higher than control level on week 1(P<0.05), lowered on weeks 2 and 3(P<0.05 and P<0.01, respectively), fluctuated during weeks 4 and 6, and elevated on week 7(P<0.05). The androgen receptor (AR) message levels increased significantly week 2(P<0.01), then returned to control level on week 3. In contrast, expression of cytochrome P450 aromatase(P450arom) decreased sharply during weeks $1{\sim}3$(P<0.01 on weeks 1 and 2; P<0.05 on week 3), then went back to control level on week 4. The mRNA level of $5{\alpha}$-reductase type 2($5{\alpha}$-RT2) increased significantly on week 4(P<0.01), then returned to control level. The present study indicated that EDS administration could induce reversible alterations in the transcriptional activities of sex steroid hormone receptors and androgenconverting enzymes in rat epididymis. EDS injection model will be useful to clarify the regulation mechanism of mammalian epididymal physiology.