• Communications for Statistical Applications and Methods
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• v.17 no.2
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• pp.293-308
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• 2010

In this paper, we examine the forecasting KOSPI 200 realized volatility by volatility measurements. The empirical investigation for KOSPI 200 daily returns is done during the period from 3 January 2003 to 29 June 2007. Since Korea Exchange(KRX) will launch VKOSPI futures contract in 2010, forecasting VKOSPI can be an important issue. So we analyze which volatility measurements forecast VKOSPI better. To test this hypothesis, we use 5-minute interval returns to measure realized volatilities. Also, we propose a new methodology that reflects the synchronized bidding and simultaneously takes it account the difference between overnight volatility and intra-daily volatility. The t-test and F-test show that our new realized volatility is not only different from the realized volatility by a conventional method at less than 0.01% significance level, also more stable in summary statistics. We use the correlation analysis, regression analysis, cross validation test to investigate the forecast performance. The empirical result shows that the realized volatility we propose is better than other volatilities, including historical volatility, implied volatility, and convention realized volatility, for forecasting VKOSPI. Also, the regression analysis on the predictive abilities for realized volatility, which is measured by our new methodology and conventional one, shows that VKOSPI is an efficient estimator compared to historical volatility and CRR implied volatility.

• Journal of the Korean Vacuum Society
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• v.12 no.4
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• pp.218-227
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• 2003

Pd/Si/Ti/Pt and Pd/Si/Pd/Ti/Au ohmic contacts to n-type InCaAs were investigated for applications to AlGaAs/GaAs HBT emitter ohmic contacts. In the Pd/Si/Ti/Pt ohmic contact, as-deposited contact showed non-ohmic behavior, and high specific contact resistivity of $5\times10^{-3}\Omega\textrm{cm}^2$ was achieved by rapid thermal annealing at $375^{\circ}C$/10 sec. However, the specific contact resistivity decreased remarkably to $2\times10^{-6}\Omega\textrm{cm}^2$ by annealing at $425^{\circ}C$/10sec. In the Pd/Si/Pd/Ti/Au ohmic contact, minimum specific contact resistivity of $3.9\times10^{-7}\Omega\textrm{cm}^2$ was achieved by annealing at $400^{\circ}C$/20sec. In both ohmic contacts, low contact resistivity and non-spiking planar interface between ohmic materials and InGaAs were maintained. Therefore, these thermally stable ohmic contact systems are promising candidates for compound semiconductor devices. RF performance of the AlGaAs/GaAs HBT was also examined by employing the Pd/Si/Ti/Pt and Pd/Si/Pd/Ti/Au systems as emitter ohmic contacts. Cutoff frequencies were 63.9 ㎓ and 74.4 ㎓, respectively, and maximum oscillation frequencies were 50.1 ㎓ and 52.5 ㎓, respectively. It shows very successful high frequency operations.

• Journal of the Korea Society for Simulation
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• v.20 no.4
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• pp.81-89
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• 2011

Underwater wireless network can be useful in various fields such as underwater environment observation, catastrophe prevention, ocean resources exploration, ocean organism research, and vessel sinking exploration. We need to develop an efficient design for Medium Access Control (MAC) protocol to improve multiple data communication in underwater environment. Aloha protocol is one of the basic and simple protocols, but it has disadvantage such as collision occurs oftenly in communication. If there is collision occured in RF communication, problem can be solved by re-sending the data, but using low frequency in underwater, the re-transmission has difficulties due to slow bit-rate. So, Time Division Multiple Access (TDMA) based MAC protocol is going to be used to avoid collisions, but if there is no data to send in existing TDMA, time slot should not be used. Therefore, this paper proposes dynamic TDMA protocol mechanism with reducing the time slots by sending short "I Have No Data" (IHND) message, if there is no data to transmit. Also, this paper presents mathematic analysis model in relation to data throughput, channel efficiency and verifies performance superiority by comparing the existing TDMA protocols.

• Journal of The Korean Society of Grassland and Forage Science
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• v.30 no.3
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• pp.257-266
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• 2010

This study was carried out to investigate the effect of feeding whole crop barley silage (WBS) on the growth performance, gain, feed requirement, carcass grade and beef quality of Hanwoo steers in 1999 to 2001. Twenty one steers were allocated, and divided into three treatment groups which fed rice straw only (control), WBS only, and fresh rice straw silage plus WBS during overall period ad libitum. Concentrates were fed at 1.5% level of live-body weight during growing stages, 4~12 months of age, at 1.8% level of live-body weight during early fattening stages, 13~18 months of age, and ad libitum after late fattening stages, 19~27months of age. The production yields of WBS were 17,135 kg as a silage, and 6,011 kg as a dry matter per ha, and the quality of WBS was 2~3 grade, while that of rice straw silage was 4grade. The daily gain with feeding of WBS (0.70 kg) during experimental period was higher than that of control group (0.65 kg), and the concentrate requirement (7.31 kg) per kg gain in WBS was lower than that of control (8.95 kg). The effects of gain and feed efficiency were very distinct during growing stage. i.e., the daily gain of WBS (0.84 kg) was increased by 65% compared to control (0.51 kg), and the concentrate requirement (4.16 kg) per kg gain in feeding of WBS was decreased by 35%, compared to control (6.39 kg). Meat quality with WBS was higher than that of control. Frequency rate of 1 and/or $1^+$ grade, and marbling score of feeding of WBS were 62.5% and 4.38, while those of control were 37.5% and 2.75, respectively. The results of the sensory evaluation showed that Hanwoo beef fed with WBS were better than that of control. In conclusion, feeding of WBS was desirable to improve daily gain, reduction of concentrates, feed efficiency and meat quality of Hanwoo steers.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.2
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• pp.201-219
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• 2014

The Republic of Korea in the real economy to a knowledge economy, and a center of creativity and imagination in the creative economy is changing the paradigm. As the core of creating economic, creative industries with the technology and information play an important role in the industry individuals. In order to solve the problem of the polarization of the economy and high youth unemployment rate of Korea, to recognize the role of the creative industries, as objection part, dimensions pan-national and one creative companies in industries of Mobile Apps various policies that support has been promoted. Support these policies to be able to contribute to the establishment of the success of mobile apps one-person creating company, we performed this study targeting one-person company that creates mobile apps area, we conducted a demonstration study of success factors, and thus more effective and efficient in an attempt to seek out support measures. In this study, we derive a research 4 hypothesis about the success factors of one creative enterprise through literature discussion, a study was made on the basis of empirical data of one-person company that creates mobile apps. The results of the analysis, first, if the development rate of the mobile application technology is fast and a new competition associated product is appeared, it was possible to find a tendency to be higher at the performance quantitative companies. Second, if the founder is a founding for the benefit and rewarding work and come to terms with the risk, it was possible to discover tends to be higher achievement quantitative. Third, if one-person company select a target market with capture intensively, it was possible to find a tendency for higher qualitative results. Fourth, it could be found that the reliability of the contact frequency of the network related performance business environment these characteristics enterprise management strategy and act as a significant modulatory effect. Provision of information relating to management and entrepreneurship education to be one creative enterprise is required, these results suggest that there is a provision continuing need for the opportunity to be able to meet and network and reliable variety have. In this study, to take advantage to promote the elimination measures that can increase the likelihood of success of the company of institutions to support one company that creates knowledge-based, such as in the field of mobile application.

• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.5
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• pp.53-63
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• 2010

The purposes of this study are to classify the characteristics of parks by park use patterns and the understanding of design concepts and to analyze the difference of cognition of design concept between designers and park users. The literature studies and surveys were performed to analyze park use patterns and understanding of design concepts for Seoul Forest Park, Yeouido Park and Seonyudo Park. Several statistical methods have been used such as descriptive analysis and importance-performance analysis. The results of this research are as follows. As the results of an analysis of park use patterns, Seonyudo Park may he qualified as an urban landmark park, while Yeouido Park can he classified as a neighborhood park. Seoul Forest Park bas characteristics of both. Second, the higher frequency of visits generally leads higher preference. Third, the overall cognition of the design concepts of parks shows 3.51 on average, which is comparatively high. The functional concepts are better transmitted to the users compared to abstract concepts. The cognition of the design concepts of each park are evaluated in the higher order of Seonyudo Park, Seoul Forest Park and Yeouido Park. Fourth, the cognition levels of detailed design concepts for each place are lower than the overall design concepts. On the other hand, levels of satisfaction are increased after the design concepts are noticed. It would he necessary make the effort to give information about the design concept of each space. The results of this study are limited in that it covers only three parks in Seoul, and did not consider seasonal variables. Nevertheless, this study may he significant in that it dealt with the cognition of design concepts for urban parks, focusing on the difference between designers and visitors.

• Journal of Intelligence and Information Systems
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• v.12 no.1
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• pp.1-15
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• 2006

In Korea, a resident registration card has various personal information such as a present address, a resident registration number, a face picture and a fingerprint. A plastic-type resident card currently used is easy to forge or alter and tricks of forgery grow to be high-degree as time goes on. So, whether a resident card is forged or not is difficult to judge by only an examination with the naked eye. This paper proposed an automatic recognition method of a resident card which recognizes a resident registration number by using a refined ART2-based RBF network newly proposed and authenticates a face picture by a template image matching method. The proposed method, first, extracts areas including a resident registration number and the date of issue from a resident card image by applying Sobel masking, median filtering and horizontal smearing operations to the image in turn. To improve the extraction of individual codes from extracted areas, the original image is binarized by using a high-frequency passing filter and CDM masking is applied to the binaried image fur making image information of individual codes better. Lastly, individual codes, which are targets of recognition, are extracted by applying 4-directional contour tracking algorithm to extracted areas in the binarized image. And this paper proposed a refined ART2-based RBF network to recognize individual codes, which applies ART2 as the loaming structure of the middle layer and dynamicaly adjusts a teaming rate in the teaming of the middle and the output layers by using a fuzzy control method to improve the performance of teaming. Also, for the precise judgement of forgey of a resident card, the proposed method supports a face authentication by using a face template database and a template image matching method. For performance evaluation of the proposed method, this paper maked metamorphoses of an original image of resident card such as a forgey of face picture, an addition of noise, variations of contrast variations of intensity and image blurring, and applied these images with original images to experiments. The results of experiment showed that the proposed method is excellent in the recognition of individual codes and the face authentication fur the automatic recognition of a resident card.

• Food Science of Animal Resources
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• v.27 no.1
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• pp.53-59
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• 2007

This study was conducted to determine the effects of dietary supplementation with probiotics on the growth and meat quality of finishing pigs. A total of forty eight ($Landrace{\times}Yorkshire{\times}Duroc$) pigs ($55.3{\pm}1.5 kg$ average initial body weight) were randomly assigned to four groups and fed on a diet supplemented with 0, 0.2, 0.5 or 1% probiotics for 58 days. The pigs were slaughtered at approximately 105 kg live weight. Supplementation with 0.2% probiotics significantly (p<0.05) increased daily gain compared to the control. The daily gain of pigs in the 0.2% probiotic group was 0.95 kg whereas that of the control was 0.85 kg. The average feed intake was 2.79-2.84 kg and there were no significant differences in feed intake between the control and test groups. The feed conversion of the 0.2% probiotic group was 2.96 kg whereas the control showed a feed conversion of 3.28 kg. The results of this study imply that supplementation with 0.2% probiotics may improve the feed conversion of pigs. There were significant differences in carcass weight, carcass ratio, backfat thickness, and frequency percentage of A grade carcasses between the control and probiotic test groups. In addition, the moisture, crude protein and crude ash contents of the probiotic treated groups did not differ significantly from the control group, however the crude fat values of the 0.2% probiotic test group was significantly tower than the other groups. The muscle pH levels of all samples ranged from 5.63-5.67 which is the normal pH of pork. The supplementation of probiotics resulted in decreased lightness ($L^*$) values and increased redness ($a^*$) values. Furthermore, the saturated fatty acid contents of the 0.2% and 0.5% probiotic test groups decreased and the unsaturated fatty acid contents increased relative to the control.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.307-325
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• 2023

Due to the prolonged COVID-19 pandemic, the frequency of people who are tired of living indoors visiting nearby mountains and national parks to relieve depression and lethargy has exploded. There is a place where thousands of people who came out of nature stop walking and breathe and rest, that is the mineral spring. Even in mountains or national parks, there are about 600 mineral springs that can be found occasionally in neighboring parks or trails in the metropolitan area. However, due to irregular and manual water quality tests, people drink mineral water without knowing the test results in real time. Therefore, in this study, we intend to develop a model that can predict the quality of the spring water in real time by exploring the factors affecting the quality of the spring water and collecting data scattered in various places. After limiting the regions to Seoul and Gyeonggi-do due to the limitations of data collection, we obtained data on water quality tests from 2015 to 2020 for about 300 mineral springs in 18 cities where data management is well performed. A total of 10 factors were finally selected after two rounds of review among various factors that are considered to affect the suitability of the mineral spring water quality. Using AutoML, an automated machine learning technology that has recently been attracting attention, we derived the top 5 models based on prediction performance among about 20 machine learning methods. Among them, the catboost model has the highest performance with a prediction classification accuracy of 75.26%. In addition, as a result of examining the absolute influence of the variables used in the analysis through the SHAP method on the prediction, the most important factor was whether or not a water quality test was judged nonconforming in the previous water quality test. It was confirmed that the temperature on the day of the inspection and the altitude of the mineral spring had an influence on whether the water quality was unsuitable.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.