• Food Science of Animal Resources
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• v.33 no.6
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• pp.763-771
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• 2013

This study was carried out to investigate the effects of various temperatures of electro-magnetic resonance and air blast freezing methods on the physicochemical quality of meat. Beef (loin and round), pork (belly and ham) and chicken (breast and leg) were purchased at a commercial market, and the meat was frozen using three methods: air blast freezing ($-20^{\circ}C$ and $-45^{\circ}C$) and electro-magnetic resonance quick freezing. Changes in the physicochemical properties of meat were analyzed by drip loss, cooking loss, water holding capacity (WHC) and proximate compositions. In comparison, regardless of the animal species and cuts of meat, electro-magnetic resonance quick freezing (2 h) resulted in a completely frozen product in a much shorter time than $-20^{\circ}C$ and $-45^{\circ}C$ air blast freezing (24 h and 8 h, respectively). Drip loss of loin which had underwent electro-magnetic resonance quick freezing were significantly (p<0.05) lower than those of the other two treatments, but cooking loss and water holding capacity were the highest at 43.7% and 60.7%, respectively (p<0.05). Characteristics such as crude protein, crude fat and moisture compositions showed significant differences, depending on the cuts and freezing methods (p<0.05). The fat composition of electro-magnetic resonance quick frozen loin and round were significantly low (p<0.05). However, moisture content was the highest compared to other freezing methods, as 67.1% and 71.9%, respectively (p<0.05). Electro-magnetic resonance quick freezing was an appropriate way to reduce the deterioration of meat quality due to freezing, and the drip loss was least for the part with low moisture, low protein, and high fat.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.11 no.6
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• pp.1-9
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• 2016

In this study, we investigate the announcement effects of M&As with a start-up as a target firm on shareholder wealth of an acquiring firm. We use M&A events in KOSPI or KOSDAQ market between 2002 and 2014 after the financial crisis. Among the total 1436 mergers and acquisitions that took place domestically during this period, 1383 cases were selected as cases to be studied, excluding 53 cases where acquiring firms were unlisted firms. The results of the analysis are as follows: First, as a result of a comparison between the acquiring firms' CARs of the whole sample group(n=1383) occurred during the (-2, +1), (-5, +2), (-10, +5) periods of M&A announcement date(t=0) and the sub-sample group(n=468) where the target firms are start-ups which were established within five years, the acquiring firms of the whole sample group do not show significat CARs, while the acquiring firms of the sub-sample group show the significantly positive CARs. This suggests that M&A with start-ups have a positive effect on firm value of acquiring firms. Second, when merging unlisted start-ups, the acquiring firms show positive CARs, showing that there exists a listing effect in the merger of start-up. Third, merging the start-ups belonging to the high-tech industry shows the higher CARs than the case of merging the start-ups belonging to the non-high-tech industry. This study has great significance as the first in Korea to investigate the effect of M&A announcement with a start-up.

• Cartoon and Animation Studies
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• s.35
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• pp.291-312
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• 2014

This study is based on the theory of R.Caillois about element of play which is motivated to infant for studying Hangul. The ultimate goal of play has to be accompanied by pleasure. And learning means permanent changes from experiences for the individual's. Play and learning, these two elements are united to the genre of serious game since the GBL (game based learning) was lead. Most importantly, in order to achieve their own Hangul learning is the fun. Coupled with fun and learning has an important issue for flow because concentration is low in infants than adults. In this case study is to know about fun factor has been applied effectively to Hangul serious mobile game. 20 Infant Hangul mobile serious games of Google Android mobile game section were selected as a case study based on more than 10,000 downloads and user's review rate by April 22, 2014. After that is currently available on the market can play a variety of cases of infant learning Hangul from previous research of R.Caillois offers four categories of play. R.Caillois of Agon, Mimicry, Alea, Ilinx have unique characteristics in comparison with its functional characteristics Hangul four are present any role in Hangul serious mobile games. As a result of the cases selected and the rules of the game will include a maximum of two of the most common types of Agon. Each attribute of the play, rather than one single factor is applied to four kinds of game play performance when properties are distributed to experience together gave the best flow. As a result of this study will be a based research for infants Hangul serious mobile game reflects the properties of the elements of a fun game that you want to combine learning.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.21 no.1
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• pp.35-40
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• 2015

Effect of packaging and storage methods for enhancing the shelf life and improving the postharvest quality of lettuce (Lactuca sativa L.) was studied during high temperature period. Lettuces were packed using four packaging and storage types: (A) plastic box container (control); (B) plastic box container covered with high density polyethylene (HDPE) film; (C) plastic box container with lettuce wrapped in linear low-density polyethylene (LLD-PE) film; and (D) plastic box container with lettuce with its stem. The quality parameters, such as fresh weight loss, SPAD value, and appearance of lettuce were investigated. The lettuce wrapped with LLD-PE film inside the plastic box container showed the lowest weight loss, highest SPAD value and best appearance compared to those exposed to the other packaging and storage methods during the three-week storage at $2^{\circ}C$. The results indicate that the marketability of lettuce can be optimized if proper packaging and storing is adopted. Prolonging the freshness even on low temperature storage will increase the potential of its sale ability in the domestic market even during summer season.

• Korean Journal of Optics and Photonics
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• v.16 no.3
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• pp.182-190
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• 2005

The fiber Raman amplifier(FRA) is a distinctly advantageous technology. Due to its wider, flexible gain bandwidth, and intrinsically lower noise characteristics, FRA has become an indispensable technology of today. Various FRA modeling methods, with different levels of convergence speed and accuracy, have been proposed in order to gain valuable insights for the FRA dynamics and optimum design before real implementation. Still, all these approaches share the common platform of coupled ordinary differential equations(ODE) for the Raman equation set that must be solved along the long length of fiber propagation axis. The ODE platform has classically set the bar for achievable convergence speed, resulting exhaustive calculation efforts. In this work, we propose an alternative, highly efficient framework for FRA analysis. In treating the Raman gain as the perturbation factor in an adiabatic process, we achieved implementation of the algorithm by deriving a recursive relation for the integrals of power inside fiber with the effective length and by constructing a matrix formalism for the solution of the given FRA problem. Finally, by adiabatically turning on the Raman process in the fiber as increasing the order of iterations, the FRA solution can be obtained along the iteration axis for the whole length of fiber rather than along the fiber propagation axis, enabling faster convergence speed, at the equivalent accuracy achievable with the methods based on coupled ODEs. Performance comparison in all co-, counter-, bi-directionally pumped multi-channel FRA shows more than 102 times faster with the convergence speed of the Average power method at the same level of accuracy(relative deviation < 0.03dB).

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.1-19
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• 2010

In offline environment, unlike traditional advertising model through TV, newspaper, and radio, online advertising model draws instantaneous responses from potential consumers and it is convenient to assess. This kind of characteristics of Internet advertising model has driven the growth of advertising model among various Internet business models. There are, conventionally classified, CPM (Cost Per Mile), CPC (Cost Per Click), and CPS (Cost Per Sales) models as Internet advertising expenditure model. These can be examined in manners regarding risks that stakeholders should stand and degree of responsibility. CPM model that is based on number of advertisement exposure is mechanically exposed to users but not actually recognized by users resulting in risk of wasted expenditure by advertisers without any advertising effect. While on aspect of media, CPS model that is based on conversion action is the most risky model because of the conversion action such as product purchase is determined by capability of advertisers not that of media. In this regard, while there are issue of CPM and CPS models disadvantageously affecting only one side of Internet advertising business model value network, CPC model has been evaluated as reasonable both to advertisers and media, and occupied the largest segment of Internet advertising market. However, CPC model also can cause fraudulent behavior such as click fraud because of the competition or dishonest amount of advertising expenditure. On the user aspect, unintentionally accessed advertisements can lead to more inappropriate expenditure from advertisers. In this paper, we suggest "CPCD"(Cost Per Coupon Download) model. This goes beyond simple clicking of advertisements and advertising expenditure is exerted when users download a coupon from advertisers, which is a concept in between CPC and CPS models. To achieve the purpose, we describe the scenario of advertiser perspective, processes, participants and their benefits of CPCD model. Especially, we suggest the new value in online coupon; "possibility of storage" and "complement for delivery to the target group". We also analyze the working condition for advertiser by a comparison of CPC and CPCD models through advertising expenditure simulation. The result of simulation implies that the CPCD model suits more properly to advertisers with medium-low price products rather than that of high priced goods. This denotes that since most of advertisers in CPC model are dealing with medium-low priced products, the result is very interesting. At last, we contemplate applicability of CPCD model in ubiquitous environment.

• International Commerce and Information Review
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• v.15 no.1
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• pp.3-34
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• 2013

This research, which was experimented by dividing tangible and intangible products, established the influence that affects recovery for consumers' complaint behavior and behavioral intention as per each different compensation program. In Experiment 1, the consumers, who experienced complaint behavior owing to company's mistake, have preferably recovered through the compensation program offered by the company. However, there was a significant difference in preference recovery between products that caused complaint behavior. According to the study result, the more clear preference recovery was shown in the case of purchasing laptop than the case of dining in family restaurant. Additionally, the consumers' emotion recovery was possible through compensation.; There was a emotion recovery disparity depending on product type between purchasing laptop case and dining in family restaurant case. The consumers, who experienced complaints, were only able to recover their preference, emotion, and behavioral intention through compensation of which recovery was greater in tangible product case than ordinary service. Meanwhile, there was no distinct difference between recovery compensation types even though the products were identical-type ones whereas it appeared that such tangible product which showed greater purchasing effort as laptop computer was more effective in stimulating emotion response. In Experiment 2, the purpose was to find out the difference between complaint behavior and its recovery process shown after purchase by Korean and Japanese college students, who have different consumer purchasing habits. The both consumers of the two countries, who experienced complaint behavior, demonstrated precise difference in preference recovery while the emotion and behavioral intention exhibited no disparity between the two consumer groups. In this experiment, it was learned that Korean college students were show-off purchase type consumers while on the other hand, the Japanese college students were famous product purchase type consumers. Thus, there was a clear difference in laptop computer purchase process and post-purchase evaluation between these two groups. In particular, the Korean college students had quicker preference recovery through compensation than the Japanese college students on account of their tendency to be consciousness of others. Nevertheless, there was no difference between the emotion recovery and re-purchase recovery and therefore, the compensation program for complaints was proven to affect the emotion and behavioral intention.

• Journal of the Korean Society of Food Science and Nutrition
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• v.46 no.11
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• pp.1336-1342
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• 2017

The study examined and compared the physicochemical and characteristics of various rice brand varieties and private brand products on the market. The moisture content in the proximate composition of rice was 15.67~17.03%, crude protein content was 5.73~6.30%, crude lipid content was 0.38~0.95%, and crude ash content was 0.23~0.56 %. Ilmi and Ilpum had high moisture content, whereas Gosihikkari and Hopyeong had high crude protein content. In the Hunter's color value of rice flour, L value was 96.76~97.27, a value was -1.63~-0.63, and b value was 2.00~2.60. The WAI was 1.21~1.39, WSI was 0.63~0.93%, and amylose content was 14.63~20.86%, respectively; Gosihikkari and Ilmi showed the lowest values. The X-ray diffraction patterns of rice flours of all varieties showed an A shape. For the amylogram properties of rice flour, initial pasting temperature was $59.57{\sim}63.23^{\circ}C$, maximum viscosity was 569.00~718.67 B.U. (Brabender Units), breakdown was 303.00~423.67 B.U., and setback was 212.67~265.33 B.U.. For differential scanning calorimeter (DSC) of rice flour, onset temperature was $54.66{\sim}58.63^{\circ}C$, peak temperature was $65.87{\sim}68.14^{\circ}C$, end temperature was $73.37{\sim}75.54^{\circ}C$, and enthalpy was 1.98~2.95 cal/g. The rice varieties with high internal density and initial pasting temperature as well as low crude protein content, WAI, amylose content, and setback can be classified as good. Gosihikkari in Gyeonggi Province, Ilmi and Hopyeong in Jeollanam-do, and Samgwang in Chungcheongnam-do are among them.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.139-153
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• 2017

Corporate bankruptcy can cause great losses not only to stakeholders but also to many related sectors in society. Through the economic crises, bankruptcy have increased and bankruptcy prediction models have become more and more important. Therefore, corporate bankruptcy has been regarded as one of the major topics of research in business management. Also, many studies in the industry are in progress and important. Previous studies attempted to utilize various methodologies to improve the bankruptcy prediction accuracy and to resolve the overfitting problem, such as Multivariate Discriminant Analysis (MDA), Generalized Linear Model (GLM). These methods are based on statistics. Recently, researchers have used machine learning methodologies such as Support Vector Machine (SVM), Artificial Neural Network (ANN). Furthermore, fuzzy theory and genetic algorithms were used. Because of this change, many of bankruptcy models are developed. Also, performance has been improved. In general, the company's financial and accounting information will change over time. Likewise, the market situation also changes, so there are many difficulties in predicting bankruptcy only with information at a certain point in time. However, even though traditional research has problems that don't take into account the time effect, dynamic model has not been studied much. When we ignore the time effect, we get the biased results. So the static model may not be suitable for predicting bankruptcy. Thus, using the dynamic model, there is a possibility that bankruptcy prediction model is improved. In this paper, we propose RNN (Recurrent Neural Network) which is one of the deep learning methodologies. The RNN learns time series data and the performance is known to be good. Prior to experiment, we selected non-financial firms listed on the KOSPI, KOSDAQ and KONEX markets from 2010 to 2016 for the estimation of the bankruptcy prediction model and the comparison of forecasting performance. In order to prevent a mistake of predicting bankruptcy by using the financial information already reflected in the deterioration of the financial condition of the company, the financial information was collected with a lag of two years, and the default period was defined from January to December of the year. Then we defined the bankruptcy. The bankruptcy we defined is the abolition of the listing due to sluggish earnings. We confirmed abolition of the list at KIND that is corporate stock information website. Then we selected variables at previous papers. The first set of variables are Z-score variables. These variables have become traditional variables in predicting bankruptcy. The second set of variables are dynamic variable set. Finally we selected 240 normal companies and 226 bankrupt companies at the first variable set. Likewise, we selected 229 normal companies and 226 bankrupt companies at the second variable set. We created a model that reflects dynamic changes in time-series financial data and by comparing the suggested model with the analysis of existing bankruptcy predictive models, we found that the suggested model could help to improve the accuracy of bankruptcy predictions. We used financial data in KIS Value (Financial database) and selected Multivariate Discriminant Analysis (MDA), Generalized Linear Model called logistic regression (GLM), Support Vector Machine (SVM), Artificial Neural Network (ANN) model as benchmark. The result of the experiment proved that RNN's performance was better than comparative model. The accuracy of RNN was high in both sets of variables and the Area Under the Curve (AUC) value was also high. Also when we saw the hit-ratio table, the ratio of RNNs that predicted a poor company to be bankrupt was higher than that of other comparative models. However the limitation of this paper is that an overfitting problem occurs during RNN learning. But we expect to be able to solve the overfitting problem by selecting more learning data and appropriate variables. From these result, it is expected that this research will contribute to the development of a bankruptcy prediction by proposing a new dynamic model.

• Journal of Korean Ophthalmic Optics Society
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• v.13 no.3
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• pp.65-71
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• 2008

Purpose: This paper studied the effect of eyes on the comparison between the distance optical centers problem of dispensing reading glasses made by optician and finished reading glasses in the current market. Methods: The method of this study has been measured by eleven different categories from +1.00D to +4.00D. This study also separated into three groups by their optical frame size and measured optical center point (O.C) and optical center height (O.H) with 200 peoples of man and females over 40 years old without ocular disease living in Gwang-san gu, Gwang-Ju city. Results: As a result, optical center point ranged from 57 mm to 80 mm and it turned to be most common range is from 61 mm to 65 mm (64.6%). Moreover, the optical center height ranged from 1 mm to 8mm and most common ranged (23%) were 4 mm. In other words, finished reading glasses have irregular optical ranges. After observing 200 people who are over 40 years old men and women, result shows that more than 75.5% (151 people) currently use finished reading glasses. Survey of 151 people, most common error between the finished reading glasses's O.C and the wearers P.D were 4 mm (45%). Furthermore, the most common error between the finished reading glassses's O.H and the wearers O.H ranged from 3 mm to 4 mm. Astonishingly, the entire 151 people who wear finished reading glasses appeal that they feel tiredness on their eyes when they wear finished reading glasses. 53 people (35%) claimed that they feel tiredness on their eyes after 10 to 20 minutes wearing finished reading glasses. Base on the research, We conducted more experiment to find the value of prism of optical centers err because it will tell us whether the finished reading glasses are good enough to wear or not. We multiplied diopter by the difference between finished reading glasses's O.C. and wearer's P.D. Consequently, We found out that the finished reading glasses counter to the German RAL-RG 915 policy. And We also found that it is relative to the diopter of lenses. In conclusion, based on the researched that wearing finished reading glasses have a dangerous factor for our vision. Therefore optician must need to recommend correctly made dispensing reading glasses based on the optical center point.