• Journal of the Korea institute for structural maintenance and inspection
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• v.15 no.3
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• pp.142-154
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• 2011

This study predicted the probability of corrosion initiation of reinforced concrete tunnel boxes structures using the Monte Carlo Simulation. For the inner wall and outer wall in the tunnel boxes, exposed to airborne chloride ion and seawater directly respectively, statistical values of parameters like diffusion coefficient D, surface chloride content $C_s$, cover depth c, and the chloride threshold level $C_{lim}$ were examined from experiment or literature review. Their average values accounted for $3.77{\times}10^{-12}m^2/s$, 3.0% by weight of cement, 94.7mm and 45.5mm for outer wall and inner wall, respectively, and 0.69% by weight of cement for D, $C_s$, c, and $C_{lim}$, respectively. With these parametric values, the distribution of chloride contents at rebar with time and the probability of corrosion initiation of the tunnel boxes, inner wall and outer wall, was examined by considering time dependency of chloride transport. From the examination, the histogram of chloride contents at rebar is closer to a gamma distribution, and the mean value increases with time, while the coefficient of variance decreases with time. It was found that the probability of corrosion initiation and the time to corrosion were dependent on the time dependency of chloride transport. Time independent model predicted time to corrosion initiation of inner wall and outer wall as 8 and 12 years, respectively, while 178 and 283 years of time to corrosion was calculated by time dependent model for inner wall and outer wall, respectively. For time independent model, the probability of corrosion at 100 years of exposure for inner wall and outer wall was ranged 59.5 and 95.5%, respectively, while time dependent model indicated 2.9 and 0.2% of the probability corrosion, respectively. Finally, impact of $C_{lim}$, including values specified in current codes, on the probability of corrosion initiation and corrosion free life is discussed.

• Journal of the Korean Society of Food Science and Nutrition
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• v.35 no.10
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• pp.1363-1370
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• 2006

This study was designed to evaluate the effect of Agaricus blazei $\beta-glucan$ and egg shell calcium complex on bone metabolism in ovariectomized (OVX) rats. Forty Sprague-Dewley female rats, 10 weeks of age $(248{\pm}1.7g)$, were divided into 4 groups and fed on the experimental diets for 6 weeks: sham operated control treated with normal diet containing 0.5% calcium (Sham-C), OVX-control treated with normal diet containing 0.5% calcium (OVX-C), $OVX-\beta-glucan$ group treated with $\beta-glucan$ diet containing 0.5% calcium (OVX-G), and $OVX-\beta-glucan$ egg shell calcium complex treated with $OVX-\beta-glucan$ egg shell calcium complex containing 0.5% calcium (OVX-GE). Bone weight of femur was higher in the OVX-GE group than in the other OVX groups. Bone mineral density of femur was significantly different (p<0.05) among the experimental groups and showed the highest level in the OVX-GE group. Calcium absorption rate and retention were higher in the $\beta-glucan$ supplement groups than in the other groups (p<0.05). Alkaline phosphatase activities and osteocalcin levels of serum showed lower in the $\beta-glucan$ supplement groups than in the OVX-C group. Deoxypyridinoline crosslink values of urine, indicator of bone absorption, showed the lowest in the OVX-GE group. The $\beta-glucan$ supplemented groups had a lower bone resorption ratio than in the OVX-C group. We concluded that bioavailability of calcium is higher in $\beta-glucan$ supplement groups compared to those in OVX rats. From the above results, these findings suggest the possibility of using $\beta-glucan$ egg shell calcium complex as a functional food material related to bone metabolism, even though there is no significant difference between the groups of $\beta-glucan$ and $\beta-glucan-egg$ shell calcium complex supplementation.

• Journal of the Korean association of regional geographers
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• v.7 no.3
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• pp.107-120
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• 2001

This study is concerned with providing a reliable procedure of calibrating a set of places specific distance parameters and with applying it to U.S. inter-State migration flows between 1985 and 1900. It attempts to conform to recent advances in quantitative geography that are characterized by an integration of ESDA(exploratory spatial data analysis) and local statistics. ESDA aims to detect the spatial clustering and heterogeneity by visualizing and exploring spatial patterns. A local statistic is defined as a statistically processed value given to each location as opposed to a global statistic that only captures an average trend across a whole study region. Whereas a global distance parameter estimates an averaged level of the friction of distance, place-specific distance parameters calibrate spatially varying effects of distance. It is presented that a poisson regression with an adequately specified design matrix yields a set of either origin-or destination-specific distance parameters. A case study demonstrates that the proposed model is a reliable device of measuring a spatial dimension of migration, and that place-specific distance parameters are spatially heterogeneous as well as spatially clustered.

• Journal of Korea Entertainment Industry Association
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• v.15 no.2
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• pp.169-178
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• 2021

The Korean girl group "Kara" has suffered the trilemma of its de facto failure to debut, the crisis of team breakup, and the CEO crisis of the agency. But the group has made an outstanding achievement in the history of Korean pop music after overcoming all odds. Their success strategy has never been disclosed by insiders involved in Kara's total music projects. This study has been carried out in the analysis of the strategy to provide academic implications and to honor the contribution of the late CEO Ho-yeon Lee and Kara's key member Ha-ra Gu. Therefore, between Nov. and Dec. 2020, we conducted in-depth interviews with managers, composers, stylists and Ha-ra Gu(Only in 2019, before her death) who took part in the project. The research model is set up by combining Porter's Competitive Advantage Strategy and the music value chain model into categories of "Product Innovation Differentiation (PD)" (producing, album production, performance activities) and "Marketing Differentiation (MD)" (market targeting, image specialization, promotion and communication). The analysis showed that the PD focused on complete rediscovered harmonization and revalued members' personality and sincerity with peppy songs and dainty dances as well as emission of "bright energy" which caused healing effects instead of mimicking other star singers recklessly. In terms of MD, they selected Japan's 10-20s as their main market, increasing intimacy with fans and media with the image of cute+pretty+classy+sexy. The result suggests that Poter's differentiation can function as a meaningful strategy frame in the fostering, hit, and revival of idol groups. In addition, it reaffirmed that spontaneous and passionate activities of early-stage or celebrity fan may serve as a valid catalyst for realizing differentiation, as Kara's caller of Japanese actor Gekidan Hitori caused a strong "priming effect" that drove Kara's unexpected wonderful success in Japan.

• Journal of the Korea Organic Resources Recycling Association
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• v.30 no.3
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• pp.13-22
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• 2022

In order to improve water quality of the water system contaminated with dyes, biochars prepared using discarded waste resources were applied in this study. Biochars with a large specific surface area were manufactured using street tree pruning products or waste wood, and were applied to remove an organic dye in synthetic water. Biochars were made by pyrolysis of typical street tree porch products (Platanas, Ginkgo, Aak) and waste wood under air-controlled conditions. Methylene blue (MB), which is widely used in phosphofibers, paper, leather, and cotton media, was selected in this study. The adsorption capacity of Platanas for MB was the highest and the q_max value obtained using the Langmuir model equation was 78.47 mg/g. In addition, the adsorption energy (E) (kJ/mol) of MB using the Dubinin-Radushkevich (D-R) model equation was 4.891 kJ/mol which was less than 8 kJ/mol (a criteria distinguishing physical adsorption from chemical adsorption). This result suggests a physical adsorption with weak interactions such as van der Waals force between the biochar and MB. In addition, the physical adsorption may resulted from that Platanas-based biohar has the largest specific surface area and pore volume. The ∆G value obtained through the adsorption experiment according to temperature variation was -3.67 to -7.68, which also suggests a physical adsorption. Considering these adsorption results, the adsorption of MB onto Platanas-based biochar seems to occur through physical adsorption. Overall, it was possible to suggest that adsorption capacity of the biochr prepared from this study was equal to or greater than that of commercial activated carbon reported in other studies.

• Asia Marketing Journal
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• v.13 no.3
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• pp.103-134
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• 2011

The recent economic recession and price rise reduces excessive consumption as a whole. So companies take more interest in and use discount coupons as a means of sales promotion to reinforce their competitiveness. The combination of Internet and mobile communication technology leads to an explosive increase in the use of mobile Internet service, which promotes commercialization of mobile coupons. Nevertheless, there are absolutely insufficient researches on mobile coupons than those on paper ones. In this context, this study tries to consider intention of accepting and using mobile coupons. The innovated Technology Acceptance Model (TAM) was used to see factors of using mobile coupons considered important by customers. Through the combination of characteristics of mobile coupon service and values obtained from mobile coupons, effects of variables to enhance intention of using mobile coupons were empirically analyzed. In particular, this study suggested importance of psychological as well as economic values of mobile coupons and emphasized good considerations of the psychological aspect, such as shame, stinginess, and reputation sensitivity, in using mobile coupons as an important factor for intention of using the coupons. Another empirical analysis was made of what moderating roles consumers' self-construalplayed in the effects of mobile coupon values perceived by consumers on intention of using coupons. As a result, immediate connectivity and situational provision among characteristics of mobile coupon service were found to affect ease and usability. It was also shown that perceived ease and usability had significant effects on both economic and psychological values, which then had significant effects on intention of using a mobile system. After testing moderating effects of self-construal, the degree of effects of perceived mobile coupon values on intention of using mobile coupons was greater among inter-dependent self-construal users than among independent ones. This study considered various schemes of improving intention to use mobile coupons and provided a foundation to help companies make a strategy for mobile coupons to be activated in the future.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.91-107
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• 2023

Lean startup is a concept that combines the words "lean," meaning an efficient way of running a business, and "startup," meaning a new business. It is often cited as a strategy for minimizing failure in early-stage businesses, especially in software-based startups. By scrutinizing the case of a startup L, this study suggests that lean startup methodology(LSM) can be useful for hardware and manufacturing companies and identifies ways for early startups to successfully implement LSM. To this end, the study explained the core of LSM including the concepts of hypothesis-driven approach, BML feedback loop, minimum viable product(MVP), and pivot. Five criteria to evaluate the successful implementation of LSM were derived from the core concepts and applied to evaluate the case of startup L . The early startup L pivoted its main business model from defecation alert system for patients with limited mobility to one for infants or toddlers, and finally to a smart bottle for infants. In developing the former two products, analyzed from LSM's perspective, company L neither established a specific customer value proposition for its startup idea and nor verified it through MVP experiment, thus failed to create a BML feedback loop. However, through two rounds of pivots, startup L discovered new target customers and customer needs, and was able to establish a successful business model by repeatedly experimenting with MVPs with minimal effort and time. In other words, Company L's case shows that it is essential to go through the customer-market validation stage at the beginning of the business, and that it should be done through an MVP method that does not waste the startup's time and resources. It also shows that it is necessary to abandon and pivot a product or service that customers do not want, even if it is technically superior and functionally complete. Lastly, the study proves that the lean startup methodology is not limited to the software industry, but can also be applied to technology-based hardware industry. The findings of this study can be used as guidelines and methodologies for early-stage companies to minimize failures and to accelerate the process of establishing a business model, scaling up, and going global.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.109-125
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• 2019

As interest on intelligent search engines increases, various studies have been conducted to extract and utilize the features related to products intelligencely. In particular, when users search for goods in e-commerce search engines, the 'color' of a product is an important feature that describes the product. Therefore, it is necessary to deal with the synonyms of color terms in order to produce accurate results to user's color-related queries. Previous studies have suggested dictionary-based approach to process synonyms for color features. However, the dictionary-based approach has a limitation that it cannot handle unregistered color-related terms in user queries. In order to overcome the limitation of the conventional methods, this research proposes a model which extracts RGB values from an internet search engine in real time, and outputs similar color names based on designated color information. At first, a color term dictionary was constructed which includes color names and R, G, B values of each color from Korean color standard digital palette program and the Wikipedia color list for the basic color search. The dictionary has been made more robust by adding 138 color names converted from English color names to foreign words in Korean, and with corresponding RGB values. Therefore, the fininal color dictionary includes a total of 671 color names and corresponding RGB values. The method proposed in this research starts by searching for a specific color which a user searched for. Then, the presence of the searched color in the built-in color dictionary is checked. If there exists the color in the dictionary, the RGB values of the color in the dictioanry are used as reference values of the retrieved color. If the searched color does not exist in the dictionary, the top-5 Google image search results of the searched color are crawled and average RGB values are extracted in certain middle area of each image. To extract the RGB values in images, a variety of different ways was attempted since there are limits to simply obtain the average of the RGB values of the center area of images. As a result, clustering RGB values in image's certain area and making average value of the cluster with the highest density as the reference values showed the best performance. Based on the reference RGB values of the searched color, the RGB values of all the colors in the color dictionary constructed aforetime are compared. Then a color list is created with colors within the range of ${\pm}50$ for each R value, G value, and B value. Finally, using the Euclidean distance between the above results and the reference RGB values of the searched color, the color with the highest similarity from up to five colors becomes the final outcome. In order to evaluate the usefulness of the proposed method, we performed an experiment. In the experiment, 300 color names and corresponding color RGB values by the questionnaires were obtained. They are used to compare the RGB values obtained from four different methods including the proposed method. The average euclidean distance of CIE-Lab using our method was about 13.85, which showed a relatively low distance compared to 3088 for the case using synonym dictionary only and 30.38 for the case using the dictionary with Korean synonym website WordNet. The case which didn't use clustering method of the proposed method showed 13.88 of average euclidean distance, which implies the DBSCAN clustering of the proposed method can reduce the Euclidean distance. This research suggests a new color synonym processing method based on RGB values that combines the dictionary method with the real time synonym processing method for new color names. This method enables to get rid of the limit of the dictionary-based approach which is a conventional synonym processing method. This research can contribute to improve the intelligence of e-commerce search systems especially on the color searching feature.

• Journal of the korean academy of Pediatric Dentistry
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• v.31 no.4
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• pp.569-578
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• 2004

The purpose of this study was to clarify the palatal arch length, width and height in the primary and permanent dentition. Samples were consisted of normal occlusions both in the primary dentition(50 males and 50 females) and in the permanent dentition(50 males and 50 females). With their upper plaster casts were used and through 3-dimensional laser scanning(3D Scanner, DS4060, LDI, U.S.A.), cloud data, polygonization, section curve and loft surface, fit and horizontal plane were based to measure the palatal arch length, width and height(Surfacer 10.0, Imageware, U.S.A.). T-tests were applied for the statistical analyze of the data. The results were as follows : 1. In the measurement values, the values of the male were higher than those of the female except primary anterior palatal height. There were not only statistically significant differences in anterior palatal width(p<0.05) and posterior palatal width(p<0.01) in primary dentition but palatal width(p<0.05), anterior palatal length(p<0.01), middle and posterior palatal length(p<0.05) in permanent dentition between male and female. 2. In the indices of palate, there were statistically significant differences in height-length index(p<0.05) and width-length index(p<0.01) between male and female in primary dentition. In permanent dentition, there was statistically difference between male and female. 3. In the measurement values, posterior palatal width was increased most greatly. Posterior palatal height, anterior palatal width and anterior palatal length were followed by descending order. On the other hand, anterior palatal height and posterior palatal length were decreased. 4. In the indices of palate, the height-length index, the width-length index and posterior height-width index were increased, but the others were decreased.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.219-239
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• 2019

As the importance of providing customized services to individuals becomes important, researches on personalized recommendation systems are constantly being carried out. Collaborative filtering is one of the most popular systems in academia and industry. However, there exists limitation in a sense that recommendations were mostly based on quantitative information such as users' ratings, which made the accuracy be lowered. To solve these problems, many studies have been actively attempted to improve the performance of the recommendation system by using other information besides the quantitative information. Good examples are the usages of the sentiment analysis on customer review text data. Nevertheless, the existing research has not directly combined the results of the sentiment analysis and quantitative rating scores in the recommendation system. Therefore, this study aims to reflect the sentiments shown in the reviews into the rating scores. In other words, we propose a new algorithm that can directly convert the user 's own review into the empirically quantitative information and reflect it directly to the recommendation system. To do this, we needed to quantify users' reviews, which were originally qualitative information. In this study, sentiment score was calculated through sentiment analysis technique of text mining. The data was targeted for movie review. Based on the data, a domain specific sentiment dictionary is constructed for the movie reviews. Regression analysis was used as a method to construct sentiment dictionary. Each positive / negative dictionary was constructed using Lasso regression, Ridge regression, and ElasticNet methods. Based on this constructed sentiment dictionary, the accuracy was verified through confusion matrix. The accuracy of the Lasso based dictionary was 70%, the accuracy of the Ridge based dictionary was 79%, and that of the ElasticNet (${\alpha}=0.3$) was 83%. Therefore, in this study, the sentiment score of the review is calculated based on the dictionary of the ElasticNet method. It was combined with a rating to create a new rating. In this paper, we show that the collaborative filtering that reflects sentiment scores of user review is superior to the traditional method that only considers the existing rating. In order to show that the proposed algorithm is based on memory-based user collaboration filtering, item-based collaborative filtering and model based matrix factorization SVD, and SVD ++. Based on the above algorithm, the mean absolute error (MAE) and the root mean square error (RMSE) are calculated to evaluate the recommendation system with a score that combines sentiment scores with a system that only considers scores. When the evaluation index was MAE, it was improved by 0.059 for UBCF, 0.0862 for IBCF, 0.1012 for SVD and 0.188 for SVD ++. When the evaluation index is RMSE, UBCF is 0.0431, IBCF is 0.0882, SVD is 0.1103, and SVD ++ is 0.1756. As a result, it can be seen that the prediction performance of the evaluation point reflecting the sentiment score proposed in this paper is superior to that of the conventional evaluation method. In other words, in this paper, it is confirmed that the collaborative filtering that reflects the sentiment score of the user review shows superior accuracy as compared with the conventional type of collaborative filtering that only considers the quantitative score. We then attempted paired t-test validation to ensure that the proposed model was a better approach and concluded that the proposed model is better. In this study, to overcome limitations of previous researches that judge user's sentiment only by quantitative rating score, the review was numerically calculated and a user's opinion was more refined and considered into the recommendation system to improve the accuracy. The findings of this study have managerial implications to recommendation system developers who need to consider both quantitative information and qualitative information it is expect. The way of constructing the combined system in this paper might be directly used by the developers.