• Korean journal of food and cookery science
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• v.26 no.5
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• pp.665-675
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• 2010

This study applied high-pressure extraction cooking, which has been proven superior in processibility and stock extraction, for the preparation of stock, which is widely used as a basic material of dishes, and examined the physicochemical and sensory properties of the extracted stock by adding salt. We observed changes in the chromaticity of brown stock according to salt content, and pH decreased with increased the salt content, suggesting that stock was acidified. Regarding the mineral content, Na was the highest, followed by K and P. Regarding total free amino acid content, the content of essential amino acids, enhancing free amino acids, and other amino acids also showed the highest level in S2, which contented 0.3% salt. In the sensory test, saltiness grew stronger with an increase in salt content, and overall palatability was highest in S2. Regarding ranking, preference was highest for S2. Utilize to data that study finding of above is actual in development for mass production of brown stock product licensed cooks' traditional mesh dipper technology quality that make mass production direction that change and normalizes product that can keep excellent taste and improve conservative property develop. Culture formation and our country foodservice industry development that reduce damage of informed people ashes through development of brown stock product that is changed in large quantity, and improve quality of food more positively contributing to reappear diversification of menu, systematization and taste of specialty store as well as can contribute in rationalization of informed people ashes purchase, personnel expense (labor power) curtailment, waste decrease etc. but is developed still more being utilized.

• The Journal of the Korea Contents Association
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• v.18 no.9
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• pp.623-632
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• 2018

Both investors and researchers are attentive to the prediction of stock price movement directions since the accurate prediction plays an important role in strategic decision making on stock trading. According to previous studies, taken together, one can see that different factors are considered depending on stock markets and prediction periods. This paper aims to analyze what data mining techniques show better performance with some representative index and stock price datasets in the Korea stock market. In particular, extreme gradient boosting technique, proving itself to be the fore-runner through recent open competitions, is applied to the prediction problem. Its performance has been analyzed in comparison with other data mining techniques reported good in the prediction of stock price movement directions such as random forests, support vector machines, and artificial neural networks. Through experiments with the index/price datasets of 12 years, it is identified that the gradient boosting technique is the best in predicting the movement directions after 1 to 4 days with a few partial equivalence to the other techniques.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.7
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• pp.3000-3006
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• 2012

We investigate whether the belief in good luck of stock traders influences their satisfaction with and their loyalty to a stock trading service. In particular, we tested whether the online stock traders who have irrational beliefs in good luck (e.g., I am a lucky person) (1) are satisfied with their online stock trading service more strongly and (2) stay with it longer than the online stock traders who have rational beliefs in good luck (e.g., luck does not exist). We have tested satisfaction, loyalty, and belief in good luck among 412 online stock traders and tested our two hypotheses. Our findings contribute to the academic research on service satisfaction and loyalty as well as provide implications to online stock trading service providers.

• Journal of Korea Multimedia Society
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• v.14 no.9
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• pp.1152-1164
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• 2011

Stock price is stream data to change continuously. The characteristics of these data, stock trends according to flow of time intervals may differ. therefore, stock price should be continuously prediction when the price is updated. In this paper, we propose the new prediction system that continuously predicts the stock price according to the predefined time intervals for the selected stock item using HTM model. We first present a preprocessor which normalizes the stock data and passes its result to the stream sensor. We next present a stream sensor which efficiently processes the continuous input. In addition, we devise a storage node which stores the prediction results for each level and passes it to next upper level and present the HTM network for prediction using these nodes. We show experimented our system using the actual stock price and shows its performance.

• Journal of the Korean Society for Railway
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• v.12 no.6
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• pp.1049-1058
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• 2009

Korea's Rolling stock workshop were established with the introduction of a railway, and became the center of industrial construction in the modern age of Korea. There still exist a lot of Rolling stock workshop buildings in the Youngsan Rolling stock workshop, the representative case of Korean Rolling stock workshop, and especially the study aims to look into modern architectural properties centered on those well-preserved buildings. Korea's Rolling stock workshop were built considering the proper conditions of location such as the neighboring districts from the port to transport vehicles and materials, the place where railroad lines are centralized, the short returning distance of railroad cars for entry and departure, and had the facility layout according to the order of a working process of vehicles, and the unique structure and the section facade shape with proper functions and sizes according to each purpose. In particular, they actively adopted steel-frame structure and reinforced concrete structure, and came to have the initial characteristics of Korea's modern industrial building which is called the structural transition. Therefore, this study aims to highlight the importance of Rolling stock workshop including the Youngsan Rolling stock workshop as industrial architecture heritage in the modern age of Korea.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.279-288
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• 2011

The purpose of this research is to develop a standardization model for available stock management process among the entire Enterprise Resource Planning System modules of Automobile Parts Manufacturing Industry. The standardization model system is constructed through the phased method based on the development methodology of information establishment suggested by the Small and Medium Business Administration and Korea Technology and Information Promotion Agency for Small & Medium Enterprises. The standardization model is to develop the process modules of ordering management, storing management, delivering management, and stock management for available stock management process. The study will help the manufacturing business and related IT business which want to construct available stock management process under the ERP system to establish the system more effectively by applying the standardization model and also will provide them with construction availability and reliability. By application of this study results, the businesses will not only prevent the excessive possession of raw materials and products and reserve adequate and steady stock but also will check real-time stock, observe customer due date, decrease over-production and reduce stock cost.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.463-474
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• 2020

This study aims to investigate the impact of COVID-19 pandemic on the stock markets of sixteen countries. Pooled OLS regression, conventional t-test and Mann-Whitney test are used to estimate the results of the study. We construct a weekly panel data of COVID-19 new cases and stock returns. Pooled OLS estimation result shows that the growth rate of weekly new cases of COVID-19 negatively predicts the return in stock market. Next, the returns on leading stock indices of these countries during the COVID-19 outbreak period are compared with returns during the non-COVID period. We use a t-test and Mann-Whitney test to compare the returns. The results reveal that investors in these countries do not react to the media news of COVID-19 at the early stage of the pandemic. However, once the human-to-human transmissibility had been confirmed, all of the stock market indices negatively reacted to the news in the short- and long-event window. Interestingly, we noticed that the Shanghai Composite Index, which was severely affected during the short-event window, bounced back during the long-event window. This indicates that the Chinese government's drastic measures to contain the spread of the pandemic regained the confidence of investors in the Shanghai Stock Market.

• Culinary science and hospitality research
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• v.14 no.3
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• pp.210-222
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• 2008

This study showed that the brown stock, which is the base of demi-glace sauce, extracted by using a high pressure heating extractor is more advantageous than that extracted by the traditional extraction method for the mass production. We compared the former with the latter in terms of minerals and free amino acids. The results of this study are summarized as follows. When mineral contents were compared, the brown stock extracted by high.pressure heating extraction showed the tendency of increase in mineral contents in proportion to heating temperature and heating time, but, from extraction temperature of 140$^{\circ}C$, the contents of K, Mg, Na and P decreased with the increase of extraction time. In addition, mineral contents in the brown stock extracted by high-pressure heating extraction were generally lower than those in brown stock extracted by the traditional extraction method. This result was produced probably because materials were added repeatedly in the traditional method. Amino acids contents in brown stock according to the extraction methods were also examined. They increased with the increase in the number of extractions in the brown stock extracted by the traditional method, and those in the brown stock extracted using a high pressure heating extractor increased with the increase in heating temperature and extraction time. The results of this study are expected to be useful as a practical material for the mass production of brown stock products.

• The Journal of Society for e-Business Studies
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• v.22 no.2
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• pp.153-168
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• 2017

Recent studies focus on the role of investor attention and transparency in stock-related information in explaining stock return and trading volume. Moreover, recent literatures predict that firm opacity will increase the likelihood of future stock price crashes. In this paper, we investigate, using Naver Trend, the relation between portal search intensity and stock price crash. Using various alternative measures of stock price crash risk and search intensity, we demonstrate that stocks with larger volume of portal search are less likely to experience stock price crashes. These results are consistent with our hypothesis that accumulated firm opacity cause future stock price crash. Finally, our results still hold even after we control for the potential effect of endogeneity in the regression specifications.

• The Journal of the Korea Contents Association
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• v.6 no.6
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• pp.26-32
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• 2006

Predictions on stock prices have been a hot issue in stock market as people get more interested in stock investments. Assuming that the stock price is moving by a trend in a specific pattern, we believe that a model can be derived from past data to describe the change of the price. The best model can help predict the future stock price. In this paper, our model derivation is based on automata over temporal data to which the model is explicable. We use Bayesian Information Criterion(BIC) to determine the best number of states of the model. We confirm the validity of Bayesian Information Criterion and apply it to building models over stock price indices. The model derived for predicting daily stock price are compared with real price. The comparisons show the predictions have been found to be successful over the data sets we chose.