• Journal of the Korean Society of Food Science and Nutrition
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• v.42 no.8
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• pp.1325-1334
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• 2013

The purposes of the study were to assess the multicultural competencies and to identify potential barriers toward improving multicultural competencies of food and nutrition majors at the university level. A total of 500 students were surveyed and 457 responses were analyzed for the study. The multicultural competencies, based on a literature review, included food culture knowledge, multicultural attitude, and multicultural skills. Approximately half of the respondents took a food culture class as a college course. The food and nutrition majors showed positive multicultural attitudes; however, food culture knowledge scores for traditional Korean food culture and 11 other food cultures remained low (average score: 63.7 out of 100 points). In addition, familiarity with cultural foods and knowledge of food-related cultures were not necessarily related. As a result of factor analysis, multicultural skills, required for dietitians, were classified into three factors: professional skills, food preparation skills, and communication skills. Overall, students rated their professional skills the highest and communication skills the lowest. Multicultural attitudes and skills increased with school years, and students who took a food culture class showed significantly higher multicultural attitudes and knowledge scores compared to their counterparts. Economical issues, lack of time, and lack of opportunities for learning multicultural competencies in majors and experiencing different cultures were highly rated potential barriers for improving multicultural competencies. Our research indicates that food and nutrition educators should review their curriculums to incorporate content that encourages food and nutrition majors to learn about other food cultures and improve their multicultural competency. These skills will be critical for food and nutrition professionals in the multicultural age.

• Journal of the Korean Society of Food Science and Nutrition
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• v.45 no.9
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• pp.1249-1256
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• 2016

Black ginseng (BG) obtained by a 9-fold steaming process of Panax ginseng has been reported to have anti-oxidative, anti-obesity, and anti-diabetes effects. The current study evaluated the protective effect of BG by steaming time in an HCl/ethanol-induced acute gastritis model. BG was divided into four samples according to steaming-drying processing (Gin1, Gin3, Gin6, and BG). High performance liquid chromatography analysis, free radical scavenging activity, and total phenol and flavonoid contents were examined in ginseng and four BG samples. Compared with ginseng, BG showed a stronger radical scavenging effect and higher contents of total phenol and flavonoids. To evaluate the anti-gastritic effect of BG, mice were distributed into five groups: normal mice (N), acute gastritic mice with distilled water (CON), acute gastritic mice with 100 mg/kg of ginseng (Gin0), acute gastritic mice with 100 mg/kg of BG (BG), and acute gastritic mice with 10 mg/kg of sucralfate (SC). After 1 hour of pre-treatment with water, extracts (Gin0 and BG), or drug (SC), experimental groups except for N were orally administered 0.5 mL of 150 mM HCl/60% ethanol (v/v) mixture. Blood was collected 1 hour later from the heart, and gastric tissue was harvested. Reactive oxygen species (ROS) levels were measured in serum, and related protein expression was examined by Western blot assay. In HCl/ethanol-induced acute gastritic mice, treatment with ginseng or BG improved mucosal damage in the histological evaluation. The serum ROS level significantly decreased in the BG-treated group compared with the CON group. Furthermore, expression of inflammatory cytokines significantly decreased in the BG-treated group compared with the CON group. Based on these results, antioxidant and anti-gastritic activities of ginseng were enhanced by streaming-drying processing, in part due to an increase in biological active compounds.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.5
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• pp.245-259
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• 2020

The development of technology and the advent of a non-face-to-face society are expected to have a direct impact on job problems. In line with this phenomenon, the government and education and training institutions are coping with job problems through the start-up support policy while at the same time inducing the creation of innovative companies. In particular, youth start-up support can be expected not only to compensate for market failures, but also to promote high-growth start-ups. Based on this background of research, this study examined the competency of young entrepreneurs to start their own businesses, their entrepreneurial self-efficacy, and their impact on success and satisfaction of start-ups. Based on the theoretical research, the research theory and research model were derived by setting entrepreneurial self-efficacy as a mediating variable after reviewing the relation between the main elements of start-up competency of young start-up entrepreneurs and start-up performance. The Youth Entrepreneurship Competency was divided into four categories: Entrepreneurial Competencies, Technical Competencies, Management Competencies, and Creative Competencies, and the hypothesis was that each had a significant impact on the start-up performance through the mediating effect of entrepreneurial self-efficacy. A survey was conducted on young entrepreneurs in their 20s and 30s in Korea for empirical research, and the analysis results were as follows. First of all, the competency of young entrepreneurs to start their own businesses affects the success of start-ups and the satisfaction of start-ups. There are differences in the competencies, and both technical and management competencies can be seen through the entrepreneurial self-efficacy to enhance the success of start-ups and the satisfaction of start-ups. Entrepreneurial competency was fully mediated to start-up success and partially mediated to start-up satisfaction. In the case of creative competency, there were only direct effects on successful start-ups, and the satisfaction of start-ups showed partial mediating effects. Thus, seven of the eight detailed hypotheses were supported and one was rejected. Based on the above findings, the implications were presented.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.6
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• pp.1075-1082
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• 2016

In order to calculate the optimum installation interval between a speed hump and hump type crosswalk that are installed continuously in succession, this study examined the speed of a vehicle that passes different intervals between speed humps and hump type crosswalks from the approach section of a roundabout having a maximum speed limit of 30km/h; analyzed the effects of speed humps and hump type crosswalks installed continuously in succession on vehicle driving speed; and simulated the optimum installation height of hump type crosswalk. As a result, the following conclusion was drawn. First, it was found that the optimum interval between a speed hump and hump type crosswalk, which are the representative traffic calming techniques for reducing vehicle speed, to control vehicle speed under 30km/h is 30m. Second, as a result of comparing the deceleration of a vehicle that pass hump type crosswalks, it was found that if the installation interval is 65 m and above, a speed hump and hump type crosswalk had no effect. Therefore, it is desirable that the maximum installation interval between a speed hump and hump type crosswalk for controlling vehicle speed within a fixed road section should not exceed 65m. Third, the analysis showed that the optimum installation height of hump type crosswalk is 6-8cm in case vehicle speed at the approach section is 20km/h or lower, 8-10cm in case of 30km/h, and 10cm in case of 30km/h or higher, respectively. Fourth, even at a road section on which a speed hump and hump type crosswalk are installed, speed reduction effects may sometimes be insignificant due to a driver's studying effect, traffic conditions and so on. Thus, it is judged that speed reduction effects will be greater if several traffic calming techniques such as speed hump, chicane, and choker are applied at the same time. Therefore, in case of applying traffic calming techniques for the purpose of reducing vehicle speed in order to promote pedestrian safety, the composite application of several techniques should be considered.

• Information Systems Review
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• v.11 no.1
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• pp.161-179
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• 2009

Nowadays an increasing number of Internet users are running individual websites as Blog or Cyworld. As this type of personal media has a great influence on communication among people, business comes to care about Network Effect, Network Software, and Social Network. For instance, Cyworld created the web service called 'Minihompy' for individual web-logs, and acquired 2.4milion users in 2007. Although many people assumed that the popularity of Minihompy, or Blog would be a passing fad, Cyworld has improved its service, and expanded its Network with various contents. This kind of expansion reflects survival efforts from infinite competitions among ISPs (Internet Service Provider) with focus on enhancing usability to users. However, Cyworld's Network Effect is gradually diminished in these days. Both of low production cost of service vendors and the low searching/conversing costs of users combine to make ISPs hard to keep their market share sustainable. To overcome this lackluster trend, Cyworld has adopted new strategies and try to lock their users in their service. Various efforts to improve the continuance and expansion of Network effect remain unclear and uncertain. If we understand beforehand how a service would improve Network effect, and which service could bring more effect, ISPs can get substantial help in launching their new business strategy. Regardless many diverse ideas to increase their user's duration online ISPs cannot guarantee 'how the new service strategies will end up in profitability. Therefore, this research studies about Network effect of Cyworld's 'Minihompy' using System-Dynamics method which could analyze dynamic relation between users and ISPs. Furthermore, the research aims to predict changes of Network Effect based on the strategy of new service. 'Page View' and 'Duration Time' can be enhanced for the short tenn because they enhance the service functionality. However, these services cannot increase the Network in the long-run. Limitations of this research include that we predict the future merely based on the limited data. We also limit the independent variables over Network Effect only to the following two issues: Increasing the number of users and increasing the Service Functionality. Despite of some limitations, this study perhaps gives some insights to the policy makers or others facing the stiff competition in the network business.

• Asia pacific journal of information systems
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• v.22 no.4
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• pp.7-29
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• 2012

Smartphone and its applications (i.e. apps) are increasingly penetrating consumer markets. According to a recent report from Korea Communications Commission, nearly 50% of mobile subscribers in South Korea are smartphone users that accounts for over 25 million people. In particular, the importance of smartphone has risen as a geospatially-aware device that provides various location-based services (LBS) equipped with GPS capability. The popular LBS include map and navigation, traffic and transportation updates, shopping and coupon services, and location-sensitive social network services. Overall, the emerging location-based smartphone apps (LBA) offer significant value by providing greater connectivity, personalization, and information and entertainment in a location-specific context. Conversely, the rapid growth of LBA and their benefits have been accompanied by concerns over the collection and dissemination of individual users' personal information through ongoing tracking of their location, identity, preferences, and social behaviors. The majority of LBA users tend to agree and consent to the LBA provider's terms and privacy policy on use of location data to get the immediate services. This tendency further increases the potential risks of unprotected exposure of personal information and serious invasion and breaches of individual privacy. To address the complex issues surrounding LBA particularly from the user's behavioral perspective, this study applied the privacy calculus model (PCM) to explore the factors that influence the adoption of LBA. According to PCM, consumers are engaged in a dynamic adjustment process in which privacy risks are weighted against benefits of information disclosure. Consistent with the principal notion of PCM, we investigated how individual users make a risk-benefit assessment under which personalized service and locatability act as benefit-side factors and information privacy risks act as a risk-side factor accompanying LBA adoption. In addition, we consider the moderating role of trust on the service providers in the prohibiting effects of privacy risks on user intention to adopt LBA. Further we include perceived ease of use and usefulness as additional constructs to examine whether the technology acceptance model (TAM) can be applied in the context of LBA adoption. The research model with ten (10) hypotheses was tested using data gathered from 98 respondents through a quasi-experimental survey method. During the survey, each participant was asked to navigate the website where the experimental simulation of a LBA allows the participant to purchase time-and-location sensitive discounted tickets for nearby stores. Structural equations modeling using partial least square validated the instrument and the proposed model. The results showed that six (6) out of ten (10) hypotheses were supported. On the subject of the core PCM, H2 (locatability ${\rightarrow}$ intention to use LBA) and H3 (privacy risks ${\rightarrow}$ intention to use LBA) were supported, while H1 (personalization ${\rightarrow}$ intention to use LBA) was not supported. Further, we could not any interaction effects (personalization X privacy risks, H4 & locatability X privacy risks, H5) on the intention to use LBA. In terms of privacy risks and trust, as mentioned above we found the significant negative influence from privacy risks on intention to use (H3), but positive influence from trust, which supported H6 (trust ${\rightarrow}$ intention to use LBA). The moderating effect of trust on the negative relationship between privacy risks and intention to use LBA was tested and confirmed by supporting H7 (privacy risks X trust ${\rightarrow}$ intention to use LBA). The two hypotheses regarding to the TAM, including H8 (perceived ease of use ${\rightarrow}$ perceived usefulness) and H9 (perceived ease of use ${\rightarrow}$ intention to use LBA) were supported; however, H10 (perceived effectiveness ${\rightarrow}$ intention to use LBA) was not supported. Results of this study offer the following key findings and implications. First the application of PCM was found to be a good analysis framework in the context of LBA adoption. Many of the hypotheses in the model were confirmed and the high value of $R^2$ (i.,e., 51%) indicated a good fit of the model. In particular, locatability and privacy risks are found to be the appropriate PCM-based antecedent variables. Second, the existence of moderating effect of trust on service provider suggests that the same marginal change in the level of privacy risks may differentially influence the intention to use LBA. That is, while the privacy risks increasingly become important social issues and will negatively influence the intention to use LBA, it is critical for LBA providers to build consumer trust and confidence to successfully mitigate this negative impact. Lastly, we could not find sufficient evidence that the intention to use LBA is influenced by perceived usefulness, which has been very well supported in most previous TAM research. This may suggest that more future research should examine the validity of applying TAM and further extend or modify it in the context of LBA or other similar smartphone apps.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.157-178
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• 2009

Corporate credit rating is a very important factor in the market for corporate debt. Information concerning corporate operations is often disseminated to market participants through the changes in credit ratings that are published by professional rating agencies, such as Standard and Poor's (S&P) and Moody's Investor Service. Since these agencies generally require a large fee for the service, and the periodically provided ratings sometimes do not reflect the default risk of the company at the time, it may be advantageous for bond-market participants to be able to classify credit ratings before the agencies actually publish them. As a result, it is very important for companies (especially, financial companies) to develop a proper model of credit rating. From a technical perspective, the credit rating constitutes a typical, multiclass, classification problem because rating agencies generally have ten or more categories of ratings. For example, S&P's ratings range from AAA for the highest-quality bonds to D for the lowest-quality bonds. The professional rating agencies emphasize the importance of analysts' subjective judgments in the determination of credit ratings. However, in practice, a mathematical model that uses the financial variables of companies plays an important role in determining credit ratings, since it is convenient to apply and cost efficient. These financial variables include the ratios that represent a company's leverage status, liquidity status, and profitability status. Several statistical and artificial intelligence (AI) techniques have been applied as tools for predicting credit ratings. Among them, artificial neural networks are most prevalent in the area of finance because of their broad applicability to many business problems and their preeminent ability to adapt. However, artificial neural networks also have many defects, including the difficulty in determining the values of the control parameters and the number of processing elements in the layer as well as the risk of over-fitting. Of late, because of their robustness and high accuracy, support vector machines (SVMs) have become popular as a solution for problems with generating accurate prediction. An SVM's solution may be globally optimal because SVMs seek to minimize structural risk. On the other hand, artificial neural network models may tend to find locally optimal solutions because they seek to minimize empirical risk. In addition, no parameters need to be tuned in SVMs, barring the upper bound for non-separable cases in linear SVMs. Since SVMs were originally devised for binary classification, however they are not intrinsically geared for multiclass classifications as in credit ratings. Thus, researchers have tried to extend the original SVM to multiclass classification. Hitherto, a variety of techniques to extend standard SVMs to multiclass SVMs (MSVMs) has been proposed in the literature Only a few types of MSVM are, however, tested using prior studies that apply MSVMs to credit ratings studies. In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-AIL (3) DAGSVM, (4) ECOC, (5) Method of Weston and Watkins, and (6) Method of Crammer and Singer. In addition, we examined the prediction accuracy of some modified version of conventional MSVM techniques. To find the most appropriate technique of MSVMs for corporate bond rating, we applied all the techniques of MSVMs to a real-world case of credit rating in Korea. The best application is in corporate bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. For our study the research data were collected from National Information and Credit Evaluation, Inc., a major bond-rating company in Korea. The data set is comprised of the bond-ratings for the year 2002 and various financial variables for 1,295 companies from the manufacturing industry in Korea. We compared the results of these techniques with one another, and with those of traditional methods for credit ratings, such as multiple discriminant analysis (MDA), multinomial logistic regression (MLOGIT), and artificial neural networks (ANNs). As a result, we found that DAGSVM with an ordered list was the best approach for the prediction of bond rating. In addition, we found that the modified version of ECOC approach can yield higher prediction accuracy for the cases showing clear patterns.

• Information Systems Review
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• v.16 no.3
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• pp.49-68
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• 2014

These days, consumers have increasingly preferred to digital real-time streamlining and downloading to listen to music because this is convenient and affordable for the consumers. Accordingly, sales of music in compact disk formats have steadily declined. In this regards, online digital music has become a new communication channel to listen musics, where digital files can be delivered over various online networks to people's computing devices. The majority of online digital music distributors has Music Recommender Systems for sales of digital music on their websites. Music Recommender Systems are parts of information filtering systems that provide the ratings or preferences that users give to music. Korean online digital music distributors have Music Recommender Systems. But those online music distributors didn't provide any rules or clear procedures that recommend music. Therefore, we raise important questions as follows: "Is Music Recommender Systems Fair?", "What is the impact of Music Recommender Systems on online music rankings and sales?" While previous studies have focused on usefulness of Music Recommender Systems, this study investigates not only fairness of Current Music Recommender Systems but also Relationship between Music Recommender Systems and online Music Charts. This study examines these issues based on Bandwagon effect, ranking effect, Slot effect theories. For our empirical analysis, we selected the most famous five online digital music distributors in terms of market shares. We found that all recommended music is exposed to the top of 'daily music charts' in online digital music distributors' websites. We collected music ranking data and recommended music data from 'daily music chart' during a one month. The result shows that online music recommender systems are not fair, since they mainly recommend particular music that supported by a specific music production company. In addition, the recommended music are always exposed to the top of music ranking charts. We also find that recommended music usually appear at the top 20 ranking charts within one or two days. Also, the most music in the top 50 or 100 ranks are the recommended music. Moreover, recommended music usually remain the ranking charts more than one month while non-recommended music often disappear at the ranking charts within two week. Our study provides an important implication to online music industry. Because music recommender systems and music ranking charts are closely related, music distributors may improperly use their recommender systems to boost the sales of music that related to their own companies. Therefore, online digital music distributor must clearly announce the rules and procedures about music recommender systems for the better music industry.

• Journal of Mushroom
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• v.16 no.3
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• pp.155-161
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• 2018

In this study, we analyze the growth environment using smart farm technology in order to develop the optimal growth model for the precision cultivation of the bottle-grown oyster mushroom 'Suhan'. Experimental farmers used $88m^2$ of bed area, 2 rows and 5 columns of shelf shape, 5 hp refrigerator, 100T of sandwich panel for insulation, 2 ultrasonic humidifiers, 12 kW of heating, and 5,000 bottles for cultivation. Data on parameters such as temperature, humidity, carbon dioxide concentration, and illumination, which directly affect mushroom growth, were collected from the environmental sensor part installed at the oyster mushroom cultivator and analyzed. It was found that the initial temperature at the time of granulation was $22^{\circ}C$ after the scraping, and the mushroom was produced and maintained at about $25^{\circ}C$ until the bottle was flipped. On fruiting body formation, mushrooms were harvested while maintaining the temperature between $13^{\circ}C$ and $15^{\circ}C$. Humidity was approximately 100% throughout the growth stage. Carbon dioxide concentration gradually increased until 3 days after the beginning of cultivation, and then increased rapidly to approximately 2,600 ppm. From the 6th day, $CO_2$ concentration was gradually decreased through ventilation and maintained at 1,000 ppm during the harvest. Light was not provided at the initial stage of oyster mushroom cultivation. On the $3^{rd}$ and $4^{th}$ day, mushrooms were irradiated by 17 lux light. Subsequently, the light intensity was increased to 115-120 lux as the growth progressed. Fruiting body characteristics of 'Suhan' cultivated in a farmhouse were as follows: Pileus diameter was 30.9 mm and thickness was 4.5 mm; stipe thickness was 11.0 mm and length was 76.0 mm; stipe and pileus hardness was 0.8 g/mm and 2.8 g/mm, respectively; L values of the stipe and pileus were 79.9 and 52.3, respectively. The fruiting body yield was 160.2 g/850 ml, and the individual weight was 12.8 g/10 unit.

• Neonatal Medicine
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• v.18 no.1
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• pp.137-142
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• 2011

Purpose: In relation to perinatal healthcare, medical institutions and resources are limitative and also are in a state of flux due to the therapeutic specialty. We analyzed requests for interhospital transfers received by Busan 1339 Emergency Medical Information Center (EMIC) to grasp the state of perinatal healthcare delivery system. Methods: This study was conducted on the basis of data inputted into the computing system of Busan 1339 EMIC, between January 1 and December 31, 2009. In connection with 378 pregnant women and 136 newborns who were required to transfer, retrospective analyses were made of the success rate of transfer (SR), the number of contacted hospitals, the time required for transfer and the reason of transfer and refusal. Results: In the case of pregnant women, the SR were 65.5%. They came in contact with 2.7 hospitals, and it took 24.4 minutes. As for the reason of transfer, preterm labor accounted for the highest proportion. In the case of newborns, the SR were 71.3%. They came in contact with 2.4 hospitals, and it took 15.6 minutes. The most common reason of transfer were respiratory symptoms. In the reason of refusal with pregnant women and newborn, the lack of medical staff, medical equipments and wards accounted for great. Conclusion: Many pregnant women and newborns have been transferred to hospitals by EMIC, but the SR has not been higher yet. Accordingly, there is a need to evaluate the propriety of perinatal treatment system, as well as to set up effective perinatal healthcare delivery system.