• Korean Journal of Weed Science
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• v.30 no.4
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• pp.330-339
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• 2010

In order to suggest correct direction of researches on Miscanthus spp. which are promising bioenergy crop, authors had reviewed and summarized various literature about botanical taxonomy, morphology and present condition of breeding, cultivation and utilization of miscanthus. Among the genus of Miscanthus which are known 17 species, the most important species are M. sinensis and M. sacchariflorus which origin are East Asia including Korea, and M. x giganteus which is inter-specific hybrid of tetraploid M. sacchariflorus and diploid M. sinensis. Miscanthus is superior to other energy crops in resistance to poor environments including cold, saline and damp soil, nitrogen utilization efficiency, budget of input energy and carbon which are required for producing biomass and output which are stored in biomass. The major species for production of energy and industrial products including construction material in Europe, USA and Canada is M. x giganteus which was introduced from Japan in 1930s. In present, many breeding programs are conducted to supplement demerits of present varieties and to develop "Miscanes" which is hybrid of miscanthus and sugar cane. In Korea, the researches on breeding and cultivation of miscanthus were initiated in 2007 by collecting germplasms, and developed "Goedae-Uksae 1" which is high biomass yield and "mass propagation method of miscanthus" which can improve propagation efficiency in 2009. In order to develop "Korean miscanthus industry" in future, the superior varieties available not only domestic but also foreign market should be developed by new breeding method including molecular markers. Researches on production process of cellulosic bio-ethanol including pre-treatment and saccharification of miscanthus biomass also should be strengthen.

• Journal of the Korean Society of Food Science and Nutrition
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• v.44 no.6
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• pp.921-927
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• 2015

The aim of this study was to investigate the effect of die temperature and repeated extrusion on physical properties of extruded white ginseng (EWG). The die temperature was adjusted to 100, 120, and $140^{\circ}C$, and extrusion was repeated under the same conditions with their corresponding samples. Specific mechanical energy input decreased as die temperature increased during extrusions. The secondary extruded white ginseng (SEWG) at a die temperature of $120^{\circ}C$ showed a higher expansion index than other extrudates. Elevation of both die temperature and repeated extrusion increased the specific length of extrudates. The highest apparent elastic modulus, breaking strength, and water solubility index obtained from SEWG at a die temperature of $100^{\circ}C$ were $7.53{\times}10^8N/m^2$, $7.49{\times}10^5N/m^2$, and 39.02%, respectively. When die temperature increased, water absorption index (WAI) decreased. The WAI of SEWG was higher than that of EWG. In conclusion, repeated extrusion affected physical properties of white ginseng and could be applied to produce improved quality of ginseng products.

• Applied Chemistry for Engineering
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• v.27 no.1
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• pp.92-100
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• 2016

Low-temperature conversion of nitrogen oxides using plasma-assisted hydrocarbon selective catalytic reduction of (HC-SCR) was investigated. Plasma was created in the catalyst-packed bed so that it could directly interact with the catalyst. The effect of the reaction temperature, the shape of catalyst, the concentration of n-heptane as a reducing agent, the oxygen content, the water vapor content and the energy density on $NO_x$ removal was examined. $NO_x$ conversion efficiencies achieved with the plasma-catalytic hybrid process at a temperature of $250^{\circ}C$ and an specific energy input (SIE) of $42J\;L^{-1}$ were 83% and 69% for one-dimensional Ag catalyst ($Ag\;(nanowire)/{\gamma}-Al_2O_3$) and spherical Ag catalyst ($Ag\;(sphere)/{\gamma}-Al_2O_3$), respectively, whereas that obtained with the catalyst-alone was considerably lower (about 30%) even with $Ag\;(nanowire)/{\gamma}-Al_2O_3$ under the same condition. The enhanced catalytic activity towards $NO_x$ conversion in the presence of plasma can be explained by the formation of more reactive $NO_2$ species and partially oxidized hydrocarbon intermediates from the oxidation of NO and n-heptane under plasma discharge. Increasing the SIE tended to improve $NO_x$ conversion efficiency, and so did the increase in the n-heptane concentration; however, a further increase in the n-heptane concentration beyond $C_1/NO_x$ ratio of 5 did not improve the $NO_x$ conversion efficiency any more. The increase in the humidity affected negatively the $NO_x$ conversion efficiency, resulting in lowering the $NO_x$ conversion efficiency at the higher water vapor content, because water molecules competed with $NO_x$ species for the same active site. The $NO_x$ conversion efficiency increased with increasing the oxygen content from 3 to 15%, in particular at low SIE values, because the formation of $NO_2$ and partially oxidized hydrocarbon intermediates was facilitated.

• The Journal of Korean Academy of Sensory Integration
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• v.9 no.2
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• pp.51-60
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• 2011

Objective : The characteristics of physiological responses of ADHD children to sensory stimulation were examined by types of sensory stimulation, measurement tools, and responses. In addition the behavioral characteristics were examined by analyzing items of common problems according to the measuring tool, frequency, and measurement tools. Methods : A systematic review methods were used. Papers published in the Journal between January, 1990 and December 31, 2011 were searched through Riss4U, MEDLINE /PubMed, CINAH. The main terms searched were "ADHD, Children, Sensory processing, Sensory integration, SP, SSP, SOR, TIE, CSP, SEP, EDR", and 15 papers were analyzed. Results : 1. The number of studies on physiological responses of children with ADHD to sensory stimulation was five (33.33 percent), the number of studies on behavioral responses was ten(66.67%), and the number of studies combined the two kinds of study was two (13.33%), where a total of 15 (100%) papers were analyzed. 2. In five studies on the physiological response, there were three studies using tactile and proprioceptive stimulations and two studies using olfactory, auditory, visual, tactile, and vestibular sensories. 3. In ten studies on the behavioral responses, there were five studies using SP, three studies using SSP, two studies using SOR, one study using TIE, and one study using CSP. Conclusion : In the characteristics of physiological responses of children with ADHD children to sensory stimulation, there was in the action potential of the cells in hand region of the primary sensorimotor cortex neurons. It was analyzed that there was an initial state and it appeared show a obvious and fast habituation in the later state; the time of recovery seemed to have many non-specific responses. In the characteristics of behavioral responses, there were inattention / distraction, vestibular processing, sensory processing related to endurance / tone, modulation of sensory input affecting emotional responses, low energy/weak.

• Journal of the Korean Society of Food Science and Nutrition
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• v.44 no.6
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• pp.912-920
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• 2015

The study was designed to investigate the effects of die temperature and $CO_2$ injection on the physical and antioxidant properties of extruded rice with tomato flour. Moisture content and screw speed were fixed at 25% and 150 rpm, respectively. Die temperatures and $CO_2$ injection were adjusted to 80, 110, and $140^{\circ}C$ and 0, and 300 mL/min, respectively. Specific mechanical energy input decreased as die temperature increased from 80 to $140^{\circ}C$. The expansion index increased, while bulk density decreased with $CO_2$ injection. All extrudates showed increased water soluble index (WSI) and water absorption index through the extrusion process. WSI increased as die temperature increased. 1,1-Diphenyl-2-picrylhydrazyl (DPPH) radical-scavenging activity and total phenolic compounds increased as die temperature increased from 80 to $140^{\circ}C$. Total carotenoid and lycopene contents decreased through the extrusion process. Total carotenoid and lycopene contents upon 0 mL/min $CO_2$ injection and $140^{\circ}C$ die temperature were highest at $6.65{\mu}g/g$ and 2.69 mg/kg, respectively. In conclusion, $CO_2$ injection affects expansion properties while an increased die temperature leads to increased DPPH radical scavenging activity and total phenols.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.