• Asia pacific journal of information systems
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• v.24 no.2
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.5
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• pp.705-715
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• 2010

The adoption of carbon foot print system is being activated mostly in the developed countries as one of the long-term response towards tightened up regulations and standards on carbon emission in the agricultural sector. The Korean Ministry of Environment excluded the primary agricultural products from the carbon foot print system due to lack of LCI (life cycle inventory) database in agriculture. Therefore, the research on and establishment of LCI database in the agriculture for adoption of carbon foot print system is urgent. Development of LCA (life cycle assessment) methodology for application of LCA to agricultural environment in Korea is also very important. Application of LCA methodology to agricultural environment in Korea is an early stage. Therefore, this study was carried out to find out the effect of lettuce cultivation on agricultural environment by establishing LCA methodology. Data collection of agricultural input and output for establishing LCI was carried out by collecting statistical data and documents on income from agro and livestock products prepared by RDA. LCA methodology for agriculture was reviewed by investigating LCA methodology and LCA applications of foreign countries. Results based on 1 kg of lettuce production showed that inputs including N, P, organic fertilizers, compound fertilizers and crop protectants were the main sources of major emission factor during lettuce cropping process. The amount of inputs considering the amount of active ingredients was required to estimate the actual quantity of the inputs used. Major emissions due to agricultural activities were $N_2O$ (emission to air) and ${NO_3}^-$/${PO_4}^-$ (emission to water) from fertilizers, organic compounds from pesticides and air pollutants from fossil fuel combustion in using agricultural machines. The softwares for LCIA (life cycle impact assessment) and LCA used in Korea are 'PASS' and 'TOTAL' which have been developed by the Ministry of Knowledge Economy and the Ministry of Environment. However, the models used for the softwares are the ones developed in foreign countries. In the future, development of models and optimization of factors for characterization, normalization and weighting suitable to Korean agricultural environment need to be done for more precise LCA analysis in the agricultural area.

• Korean Journal of Food Science and Technology
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• v.30 no.2
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• pp.348-355
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• 1998

The developments of various processed foods and the high quality dried fruits, in particular, are urgently needed for the enhancement of fruit consumption and their competitive values. Therefore, in this study, three variables by three level factorial design and response surface methodology were used to determine optimum conditions for osmotic dehydration of kiwifruit. The relationships of moisture losses, solid gains, weight reductions, sugar contents, titratable acidities and vitamin C contents depending on changes with temperature, sugar concentration and immersion time were investigated. The moisture loss, solid gain, weight reduction and reduction of moisture content after osmotic dehydration were increased as temperature, sugar concentration and immersion time increased. The effect of concentration was more significant than those of temperature and time on mass transfer. Sugar content was increased by increasing sugar concentration, temperature, immersion time during osmotic dehydration. Titratable acidity and vitamin C content were increased by decreasing temperature, immersion time and increasing concentration during osmotic dehydration. The regression models showed a significant lack of fit (P>0.05) and were highly significant with satisfying values of $R^2$. At the given conditions such as $66{\sim}69%$ moisture content, above $24^{\circ}Brix$ sugar content and more than 23 mg% vitamin C, the optimum condition for osmotic dehydration was $37^{\circ}C,\;55^{\circ}Brix$ and 1.5 hour.

• Korean Journal of Food Science and Technology
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• v.32 no.4
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• pp.843-850
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• 2000

We have produced the microcapsule composed of ${\alpha}-tocopherol$ as a core material (Cm) and the gelatinized polysaccharide as a wall material (Wm). Firstly, we have developed a simple, sensitive, and quantitative analysis method of the microencapsulation product using 5% cupric acetate pyridine solution. We could then optimize all the conditions for the microencapsulation process such as the ratio of [Cm] to [Wm], the temperature of dispersion fluid, and the emulsifier concentration using response surface methodology (RSM). As for the microencapsulation of ${\alpha}-tocopherol$, the regression model equation for the yield of microencapsulation (YM, %) to the change of an independent variable could be predicted as follows : YM=99.77-1.76([Cm]:[Wm])-1.72$([Cm]\;:\;[Wm])^2$. From the ridge of maximum response, the optimum conditions for the microencapsulation of ${\alpha}-tocopherol$ were able to be determined as the ratio of [Cm] to [Wm] of 4.6:5.4(w/w), the emulsifier concentration of 0.49%, and dispersion fluid temperature of $25.5^{\circ}C$, respectively. Finally, the microcapsules produced under the optimal conditions were applied for the analysis of storage stability. The optimal conditions for the storage were found to be the values of pH 9.0 and $25{\sim}35^{\circ}C$. And the storage stability of the microcapsules containing ${\alpha}-tocopherol$ were higher than 99% for a week at pH 9.0 and $25^{\circ}C$.

• Microbiology and Biotechnology Letters
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• v.26 no.5
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• pp.435-441
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• 1998

Optimal conditions for the production of natural color, betacyanin were investigated by varying light intensity, C/N ratio, concentrations of phosphate and kinds of elicitors. Batch cultivation was employed to characterize cell growth and betacyanin production of 32 days. The maximum specific growth rate, ${\mu}$$\sub$max/, was 0.3 (1/day) for batch cultivation. The maximum specific production rate, q$\^$max/$\sub$p/, was enhanced 0.11 (mg/g-cell/day) at 3 klux. A light intensity of 3 klux was shown to the best for both cell growth and betacyanin production. The maximum specific production rate was 0.125 (mg/g-cell/day) at 0.242 (1/day), the maximum specific growth rate. The dependence of specific growth rate on the light lintensity is fit to the photoinhibition model. The correlation between ${\mu}$ and q$\sub$p/ showed that the product formation parameters, ${\alpha}$ and ${\beta}$$\sub$p/ were 0.3756 (mg/cell) and 0.001 (mg/g-cell/day), respectively. The betacyanin production was partially cell growth related process, which is different from the production of a typical product in plant cell cultures. In C/N ratio experiment, high carbon concentration, 42.1 (w/w) improved cell growth rate while lower concentration, 31.6 (w/w) increased the betacyanin production rate. The ${\mu}$$\sub$max/ and q$\^$max/$\sub$p/ were 0.26 (1/day) and 0.075 (mg/g-cell/day), respectively. Beta vulgaris L. cells under 1.25 mM phosphate concentration produced 10.15 mg/L betacyanin with 13.46 (g-dry wt./L) of maximum cell density. The production of betacyanin was elongated by adding 0.1 ${\mu}$M of kinetin. This also increased the cell growth. Optimum culture conditions of light intensity, C/N, phosphate concentration were obtained as 5.5 klux, 27 (w/w), 1.25 mM, respectively by the response surface methodology. The maximum cell density, X$\sub$max/, and maximum production, P$\sub$max/, in optimized conditions were 16 (g-dry wt./L), 12.5 (mg/L) which were higher than 8 (g-dry wt./L), 4.48 (mg/L) in normal conditions. The ${\mu}$$\sub$max/ and q$\^$max/$\sub$p/ were 0.376 (1/day) and 0.134 (mg/g-cell/day) at the optimal condition. The overall results may be useful in scaling up hairy root cell culture system for commercial production of betacyanin.

• Microbiology and Biotechnology Letters
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• v.36 no.1
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• pp.61-66
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• 2008

The proteins in whey are separated and used as food additives. The remains (mainly lactose) are spray-dried to produce sweet whey powder, which is widely used as an additive for animal feed. Sweet whey powder is also used as a carbon source for the production of valuable products such as polysaccharides. Glucose, fructose, galactose, and sucrose as asupplemental carbon source were evaluated for the production of PS-7 from Azotobacter indicus var. myxogenes L3 grown on whey based MSM media. Productions of PS-7 with 2% (w/v) fructose and sucrose were 2.05 and 2.31g/L, respectively. The highest production of PS-7 was 2.82g/L when 2% (w/v) glucose was used as the carbon source. Galactose showed low production of PS-7 among the carbon sources tested. The effects of various carbon sources addition to whey based MSM medium showed that glucose could be the best candidate for the enhancement of PS-7 production using whey based MSM medium. To evaluate the effect of glucose addition to whey based media on PS-7 production, fermentations with whey and glucose mixture (whey 1, 2, 3%; whey 1% + glucose 1%, whey 1% + glucose 2% and glucose 2%, w/v) were carried out. Significant enhancement of PS-7 production with addition of 1% (w/v) and 2% (w/v) glucose in 1% (w/v) whey media was observed. The PS-7 concentration of 2% glucose added whey lactose based medium was higher than that of 1% glucose addition, however, the product yield $Y_{p/s}$ was higher in 1% glucose added whey lactose based MSM medium. Therefore, the optimal condition for the PS-7 production from the Azotobacter indicus var.myxogenes L3, was 1% glucose addition to 1% whey lactose MSM medium.

• Microbiology and Biotechnology Letters
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• v.37 no.3
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• pp.231-237
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• 2009

This paper aimed to develop a solvent extraction and purification process to recover high-purified ${\beta}$-carotene from recombinant Escherichia coli. Cells harvested from the culture broth were treated through numerous steps: dehydration, solvent extraction, crystal formation and separation. To optimize the extracting condition, experiments were carried out to investigate the effect of cell disruption, temperature, organic solvents, solvent-biomass ratio on the yield of ${\beta}$-carotene extracted from cells. The result indicated that no significant differences of extraction yield were observed from cells with or without step of cell disruption. Among different extracting solvents, the highest extraction yield of ${\beta}$-carotene, 30.3 mg-${\beta}$-carotene/g-dry cells, was obtained with isobutyl acetate at solvent-biomass ratio 25 mL/g-dry cells at $50^{\circ}C$. Notably, in case of acetone, the extraction yield was quite low when using acetone itself, but increased almost up to the highest value when combining this solvent and olive oil. The purity of ${\beta}$-carotene crystals obtained from crystallization and separation was 89%. The purity degree was further improved up to 98.5% by treating crude crystals with additional ethanol washing.

• Korean Chemical Engineering Research
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• v.47 no.6
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• pp.762-767
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• 2009

In this study, the feasibility of using vegetable oil extracted from tropical crop seed as a biodiesel feedstock was investigated by producing biodiesel and analysing the quality parameters as a transport fuel. In order to produce biodiesel efficiently, two step reaction process(pre-treatment and transesterificaion) was required because the tropical crop oil have a high content of free fatty acids. To determine the suitable acid catalyst for the pre-esterification, three kinds of acid catalysts were tested and sulfuric acid was identified as the best catalyst. After constructing the experimental matrix based on RSM and analysing the statistical data, the optimal pre-treatment conditions were determined to be 26.7% of methanol and 0.982% of sulfuric acid. Trans-esterification experiments of the pre-esterified oil based on RSM were carried out, then discovered 1.24% of KOH catalyst and 22.76% of methanol as the optimal trans-esterification conditions. However, the quantity of KOH was higher than the previously established KOH concentration of our team. So, we carried out supplemental experiment to determine the quantity of catalyst and methanol. As a result, the optimal transesterification conditions were determined to be 0.8% of KOH and 16.13% of methanol. After trans-esterification of tropical crop oil, the produced biodiesel could meet the major quality standard specifications; 100.8% of FAME, 0.45 mgKOH/g of acid value, 0.00% of water, 0.04% of total glycerol, $4.041mm^2/s$ of kinematic viscosity(at $40^{\circ}C$).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.481-491
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• 2018

As the global business environment is dynamic, uncertain, and complex, supply chain management determines the performance of the supply chain in terms of the utilization of resources and capabilities of companies involved in the supply chain. Companies pursuing open innovation gain greater access to the external environment and accumulate knowledge flows and learning experiences, and may generate better business performance from dynamic capabilities. This study analyzed the effects of supply chain dynamic capabilities, open innovation, and supply uncertainty on supply chain performance. Through questionnaires on 178 companies listed on KOSDAQ, empirical results are as follows: First, integration and reactivity capabilities among supply chain dynamic capabilities have a positive effect on supply chain performance. Second, the moderating effect of open innovation showed a negative correlation in the case of information exchange, and a positive correlation in the cases of integration, cooperation and reactivity. Third, two of the 3-way interaction terms, "information exchange*open innovation*supply uncertainty" and "integration*open innovation*supply uncertainty" were statistically significant. The implications of this study are as follows: First, as the supply chain needs to achieve optimization of the whole process between supply chain components rather than individual companies, dynamic capabilities play an important role in improving performance. Second, for KOSDAQ companies featuring limited capital resources, open innovation that integrates external knowledge is valuable. In order to increase synergistic effects, it is necessary to develop dynamic capabilities accordingly. Third, since resources are constrained, managers must determine the type or level of capabilities and open innovation in accordance with supply uncertainty. Since this study has limitations in analyzing survey data, it is necessary to collect secondary data or longitudinal data. It is also necessary to further analyze the internal and external factors that have a significant impact on supply chain performance.

• Progress in Medical Physics
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• v.23 no.1
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• pp.8-14
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• 2012

In order to develop a Patient respiratory management system includinga biofeedback function for4-dimentional radiation therapy, this study investigated anoptimal tracking algorithmfor moving target using IR (Infra-red) camera as well as commercial camera. A tracking system was developed by LabVIEW 2010. Motion phantom images were acquired using a camera (IR or commercial). After image process were conducted to convert acquired image to binary image by applying a threshold values, several edge enhance methods such as Sobel, Prewitt, Differentiation, Sigma, Gradient, Roberts, were applied. The targetpattern was defined in the images, and acquired image from a moving targetwas tracked by matching pre-defined tracking pattern. During the matching of imagee, thecoordinateof tracking point was recorded. In order to assess the performance of tracking algorithm, the value of score which represents theaccuracy of pattern matching was defined. To compare the algorithm objectively, we repeat experiments 3 times for 5 minuts for each algorithm. Average valueand standard deviations (SD) of score were automatically calculatedsaved as ASCII format. Score of threshold only was 706, and standard deviation was 84. The value of average and SD for other algorithms which combined edge detection method and thresholdwere 794, 64 in Sobel, 770, 101 in Differentiation, 754, 85 in Gradient, 763, 75 in Prewitt, 777, 93 in Roberts, and 822, 62 in Sigma, respectively. According to score analysis, the most efficient tracking algorithm is the Sigma method. Therefore, 4-dimentional radiation threapy is expected tobemore efficient if threshold and Sigma edge detection method are used together in target tracking.