• Journal of the East Asian Society of Dietary Life
• /
• v.24 no.3
• /
• pp.407-420
• /
• 2014

A survey was carried out regarding university students' recognition of high-caffeine energy drinks in an effort to identify and improve problems as well as provide basic data. Most of the subjects had previous experience of energy drink consumption. Studies showed that most students consumed energy drinks when studying. Regarding frequency of energy drink consumption, most students' responded "1~6 times a year"; female students showed lower frequency of energy drink consumption than male students. Both male and female students used convenience stores to purchase energy drinks. In most cases, students became aware of energy drinks through advertisements on TV, radio, newspapers, and magazines. The most important factor affecting their energy drink purchase and consumption status was taste. The most frequent adverse effect they experienced after drinking an energy drink was unusual heart-pounding, whereas the biggest problem caused by energy drink consumption was addiction. This study indicates that students should have a better understanding of the problems associated with excessive and prolonged high-caffeine intake. In addition, instructions for proper purchasing and consumption of high-caffeine energy drinks should be provided as well as education and campaigns concerning symptoms caused by high-caffeine energy drink consumption so that students may refrain from excessive consumption. Further, civil organizations and the government need to devise effective measures for proper regulation of high-caffeine energy drink consumption.

• Journal of Intelligence and Information Systems
• /
• v.25 no.4
• /
• pp.105-122
• /
• 2019

Dimensionality reduction is one of the methods to handle big data in text mining. For dimensionality reduction, we should consider the density of data, which has a significant influence on the performance of sentence classification. It requires lots of computations for data of higher dimensions. Eventually, it can cause lots of computational cost and overfitting in the model. Thus, the dimension reduction process is necessary to improve the performance of the model. Diverse methods have been proposed from only lessening the noise of data like misspelling or informal text to including semantic and syntactic information. On top of it, the expression and selection of the text features have impacts on the performance of the classifier for sentence classification, which is one of the fields of Natural Language Processing. The common goal of dimension reduction is to find latent space that is representative of raw data from observation space. Existing methods utilize various algorithms for dimensionality reduction, such as feature extraction and feature selection. In addition to these algorithms, word embeddings, learning low-dimensional vector space representations of words, that can capture semantic and syntactic information from data are also utilized. For improving performance, recent studies have suggested methods that the word dictionary is modified according to the positive and negative score of pre-defined words. The basic idea of this study is that similar words have similar vector representations. Once the feature selection algorithm selects the words that are not important, we thought the words that are similar to the selected words also have no impacts on sentence classification. This study proposes two ways to achieve more accurate classification that conduct selective word elimination under specific regulations and construct word embedding based on Word2Vec embedding. To select words having low importance from the text, we use information gain algorithm to measure the importance and cosine similarity to search for similar words. First, we eliminate words that have comparatively low information gain values from the raw text and form word embedding. Second, we select words additionally that are similar to the words that have a low level of information gain values and make word embedding. In the end, these filtered text and word embedding apply to the deep learning models; Convolutional Neural Network and Attention-Based Bidirectional LSTM. This study uses customer reviews on Kindle in Amazon.com, IMDB, and Yelp as datasets, and classify each data using the deep learning models. The reviews got more than five helpful votes, and the ratio of helpful votes was over 70% classified as helpful reviews. Also, Yelp only shows the number of helpful votes. We extracted 100,000 reviews which got more than five helpful votes using a random sampling method among 750,000 reviews. The minimal preprocessing was executed to each dataset, such as removing numbers and special characters from text data. To evaluate the proposed methods, we compared the performances of Word2Vec and GloVe word embeddings, which used all the words. We showed that one of the proposed methods is better than the embeddings with all the words. By removing unimportant words, we can get better performance. However, if we removed too many words, it showed that the performance was lowered. For future research, it is required to consider diverse ways of preprocessing and the in-depth analysis for the co-occurrence of words to measure similarity values among words. Also, we only applied the proposed method with Word2Vec. Other embedding methods such as GloVe, fastText, ELMo can be applied with the proposed methods, and it is possible to identify the possible combinations between word embedding methods and elimination methods.

• Korean Journal of Community Nutrition
• /
• v.26 no.3
• /
• pp.167-176
• /
• 2021

Objectives: This study was conducted to identify the awareness and practice of reducing sugar in school meals and the status of nutrition education regarding sugar reduction. Methods: An online survey was conducted on 101 nutrition teachers (dietitians) working at elementary, middle, and high schools in Daegu. Results: School nutrition teachers in Daegu recognized the need for efforts to reduce the sugar intake in the Korean diet, and it was found that elementary nutrition teachers were more aware of the implementation of the sugar reduction policy at the national level than middle and high school nutrition teachers (P = 0.002). Among the policies to reduce sugar intake at the national level, there was a high need for the promotion of self-control and limiting the sales of food with high sugar content in schools and their vicinity. The degree of practice for reducing sugar in school meals was found to be higher in the preparation, purchase, and cooking stage compared to the serving stage (P < 0.05). There was a high need for changing the preferences of the subjects for a sweet taste as a means of reducing the sugar in school meals. Thirty-six percent of nutrition teachers conducted sugar reduction education, and sending out school newsletters was the highest type of nutrition education at 80.6%. Conclusions: To effectively promote reduced sugar intake in school meals, it is necessary to change the preference of the subjects for sweetness and to conduct continuous education that can improve the awareness of people for reducing their sugar intake. For this, it is necessary to set aside time for nutrition education and to prepare an institutional framework for providing this education.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.14 no.1
• /
• pp.101-116
• /
• 2019

Technology-based start-up is important in that it encourages innovation, facilitates the development of new products and services, and contributes to job creation. Technology-based start-up activates entrepreneurship when appropriate support is provided within the ecosystem. Thus, understanding the technology-based start-up ecosystem is crucial. The purpose of this study is as follows. First, in Herrmann et al.'s(2015) study, we compare and analyze the ecosystem of each country by selecting representative regions such as Silicon Valley, Tel Aviv, London and Singapore which have the highest ranking in the start-up ecosystem. Second, we try to deeply understand the start-up ecosystem based on in-depth interviews with various stakeholders such as VC investors, start-ups, support organizations, and professors related to the Korean start-up ecosystem. Finally, based on the results of the study, we suggest development and activation of Korean technology-based start-up ecosystem. As a result, the Seoul start-up ecosystem showed a positive evaluation of government support compared to other advanced countries. In addition, it was confirmed that the ratio of tele-work and start-up company working experience of employees was higher than other countries. On the other hand, in Seoul, It was confirmed that overseas market performance, human resource diversity, attracting investment, hiring technological engineers, and the ratio of female entrepreneurs were lower than those of overseas advanced countries. In addition, according to the results of the interview analysis, Seoul was able to find that start-up ecosystems such as individual angel investors, accelerators, support institution, and media are developing thanks to the government's market-oriented policy support. However, in order for this development to continue, it is necessary to improve the continuous investment system, expansion of diversity, investment return system, and accessibility to the global market. A discussion on this issue is presented.

• Korean Security Journal
• /
• no.18
• /
• pp.169-190
• /
• 2009

Today, the rapid advance of scientific technologies has brought about fundamental changes to the types and levels of terrorism while the war against the world more than one thousand small and big terrorists and crime organizations has already begun. A method highly likely to be employed by terrorist groups that are using 21st Century state of the art technology is cyber terrorism. In many instances, things that you could only imagine in reality could be made possible in the cyber space. An easy example would be to randomly alter a letter in the blood type of a terrorism subject in the health care data system, which could inflict harm to subjects and impact the overturning of the opponent's system or regime. The CIH Virus Crisis which occurred on April 26, 1999 had significant implications in various aspects. A virus program made of just a few lines by Taiwanese college students without any specific objective ended up spreading widely throughout the Internet, causing damage to 30,000 PCs in Korea and over 2 billion won in monetary damages in repairs and data recovery. Despite of such risks of cyber terrorism, a great number of Korean sites are employing loose security measures. In fact, there are many cases where a company with millions of subscribers has very slackened security systems. A nationwide preparation for cyber terrorism is called for. In this context, this research will analyze the current status of Korea's cyber security systems and its laws from a policy perspective, and move on to propose improvement strategies. This research suggests the following solutions. First, the National Cyber Security Management Act should be passed to have its effectiveness as the national cyber security management regulation. With the Act's establishment, a more efficient and proactive response to cyber security management will be made possible within a nationwide cyber security framework, and define its relationship with other related laws. The newly passed National Cyber Security Management Act will eliminate inefficiencies that are caused by functional redundancies dispersed across individual sectors in current legislation. Second, to ensure efficient nationwide cyber security management, national cyber security standards and models should be proposed; while at the same time a national cyber security management organizational structure should be established to implement national cyber security policies at each government-agencies and social-components. The National Cyber Security Center must serve as the comprehensive collection, analysis and processing point for national cyber crisis related information, oversee each government agency, and build collaborative relations with the private sector. Also, national and comprehensive response system in which both the private and public sectors participate should be set up, for advance detection and prevention of cyber crisis risks and for a consolidated and timely response using national resources in times of crisis.

• Asia Marketing Journal
• /
• v.12 no.2
• /
• pp.27-52
• /
• 2010

It is not new that today's business organizations are expected to exhibit ethical and moral management and to carry out social responsibility as a good corporate citizen. Since South Korea emerged as a newly industrialized country during the 1980s, Korean corporations have become active in carrying out their social responsibility as a good corporate citizen to society. In spite of the short history of corporate social responsibility, Korean companies have actively participated in corporate philanthropy. Corporations' significant donations to various social causes, no-lay-off policies, corporate volunteerism and green marketing are evidences of their commitment to corporate citizenship. Corporate social responsibility is now an essential management practice whereby corporation can strengthen its sustainable value creation processes by enhancing the trust assets underlying the relationships between the business and the stakeholders. Much of the conceptual work in the area of corporate social responsibility(CSR) has originated from researches conducted in the management field. Carroll(1979) proposed that corporations have four types of social responsibilities: economic, legal, ethical and philanthropic responsibility. Most past research has investigated CSR and its impact on consumers' attitudes toward the corporations and corporate performances. Although there exists a large body of literature on how consumers perceive and respond to CSR, the majority of past studies were conducted in the United States. The stability and applicability of past findings need to be tested across different national/cultural settings, especially since corporate social responsibility is a reflection of implicit conformation with the expectations and criticism that society may have toward a corporation(Matten and Moon, 2004). In this study, we explored whether people in Korea perceive CSR of Korean corporations in the same four dimensions as done in the United States and what were the measurement items tapping each of these four dimensions. In order to investigate the dimensions of CSR and the measurement items for CSR perceived by Korean people, nine focus group interviews were conducted with several stakeholder groups(two with undergraduate students, two with graduate students, three with general consumers, and two with NGO groups). Scripts from the interviews revealed that the Korean stakeholders perceived four types of CSR which are the same as those proposed by Carroll(1979). However we found CSR issues unique to Korean corporations. For example for the economic responsibility, Korean people mentioned that the corporation needed to contribute to the economic development of the country by generating corporate profits. For the legal responsibility, Koreans included the "corporation need to follow the consumer protection law." For the ethical responsibility, they considered that the corporation needed to not promote false advertisement. In addition, Koreans thought that an ethical company should do transparent management. For the philanthropic responsibility, people in Korea thought that a corporation needed to return parts of its profits to the society for the betterment of society. The 28 items were developed based on the results of the nine focus group interviews, while considering the scale developed by Maignan and Ferrell(2001). Following the procedure proposed by Churchill(1979), we started by developing an item poll consisting of 28 items and purified the initial pool of items through exploratory, confirmatory factor analyses. 176 samples were sued for this analysis. Confirmatory factor analysis was performed on the 28 items in order to verify the underlying four factor structure. Study 1 provided new measurement items for tapping the Korean CSR dimensions, which can be useful for the future studies exploring the effects of CSR on Korean consumers' attitudes toward the corporations and corporate performances. And we found the CSR scale(17 items) has good reliability, discriminant validity and nomological validity. Economic Responsibility: "XYZ company continuously improves the quality of our products", "XYZ company has a procedure in place to respond to customer complaint", "XYZ company contributes to the economic development of our country by generating profits", "XYZ company is eager to hire people". Legal Responsibility: "XYZ company's products meet legal standards", "XYZ company seeks to comply with all laws regulating hiring and employee benefits", "XYZ company honors contractual obligations to its suppliers", "XYZ company's managers try to comply with the law related to the business operation". Ethical Responsibility: "XYZ company has a comprehensive code of conduct", "XYZ company does not promote a false or misleading advertisement", "XYZ company seems to conduct a transparent business", "XYZ company does a fair business with its suppliers or sub-contractors". Philanthropic Responsibility: "XYZ company encourages partnerships with local businesses and schools", "XYZ company supports sports and cultural activities", "XYZ company gives adequate contributions to charities considering its business size", "XYZ company encourages employees to support our community". Study 2 was condusted for comprehensive validity. 655 samples were used for this anlysis. Collected samples were tested by factor analysis and Crnbach's Alpha coefficiednts and were found to be satisfactory in terms of validity and reliability. Furthermore, fitness of the measurement model was tested by using conformatory factor analysis. χ²=880.73(df=160), GFI=0.891, AGFI=0.854, NFI=0.908, NNFI=0.913, RMR=0.059, RMESA=0.070. We hope that CSR scale could greatly facilitate research on Corporate social resposibility, it is by no means the final answer.

• Journal of Distribution Research
• /
• v.17 no.2
• /
• pp.29-62
• /
• 2012

As distribution environment is changing rapidly and competition is more intensive in the channel of distribution, the importance of retailer image and retailer equity is increasing as a different competitive advantages. Also, consumers are not functionally oriented and that their behavior is significantly affected by the symbols such as retailer image which identify retailer in the market place. That is, consumers do not choose products or retailers for their material utilities but consume the symbolic meaning of those products or retailers as expressed in their self images. The concept of self-image congruence has been utilized by marketers and researchers as an aid in better understanding how consumers identify themselves with the brands they buy and the retailer they patronize. Although self-image congruity theory has been tested across many product categories, the theory has not been tested extensively in the retailing. Therefore, this study attempts to investigate the impact of self image congruence between retailer image and self image of consumer on retailer equity such as retailer awareness, retailer association, perceived retailer quality, and retailer loyalty. The purpose of this study is to find out whether retailer-self image congruence can be a new antecedent of retailer equity. In addition, this study tries to examine how four-dimensional retailer equity constructs (retailer awareness, retailer association, perceived retailer quality, and retailer loyalty) affect customers' repatronage intention. For this study, data were gathered by survey and analyzed by structural equation modeling. The sample size in the present study was 254. The reliability of the all seven dimensions was estimated with Cronbach's alpha, composite reliability values and average variance extracted values. We determined whether the measurement model supports the convergent validity and discriminant validity by Exploratory factor analysis and Confirmatory Factor Analysis. For each pair of constructs, the square root of the average variance extracted values exceeded their correlations, thus supporting the discriminant validity of the constructs. Hypotheses were tested using the AMOS 18.0. As expected, the image congruence hypotheses were supported. The greater the degree of congruence between retailer image and self-image, the more favorable were consumers' retailer evaluations. The all two retailer-self image congruence (actual self-image congruence and ideal self-image congruence) affected customer based retailer equity. This result means that retailer-self image congruence is important cue for customers to estimate retailer equity. In other words, consumers are often more likely to prefer products and retail stores that have images similar to their own self-image. Especially, it appeared that effect for the ideal self-image congruence was consistently larger than the actual self-image congruence on the retailer equity. The results mean that consumers prefer or search for stores that have images compatible with consumer's perception of ideal-self. In addition, this study revealed that customers' estimations toward customer based retailer equity affected the repatronage intention. The results showed that all four dimensions (retailer awareness, retailer association, perceived retailer quality, and retailer loyalty) had positive effect on the repatronage intention. That is, management and investment to improve image congruence between retailer and consumers' self make customers' positive evaluation of retailer equity, and then the positive customer based retailer equity can enhance the repatonage intention. And to conclude, retailer's image management is an important part of successful retailer performance management, and the retailer-self image congruence is an important antecedent of retailer equity. Therefore, it is more important to develop and improve retailer's image similar to consumers' image. Given the pressure to provide increased image congruence, it is not surprising that retailers have made significant investments in enhancing the fit between retailer image and self image of consumer. The enhancing such self-image congruence may allow marketers to target customers who may be influenced by image appeals in advertising.

• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.85-109
• /
• 2018

Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.

• Journal of Intelligence and Information Systems
• /
• v.25 no.3
• /
• pp.117-140
• /
• 2019

As the aging phenomenon accelerates and various social problems related to the elderly of the vulnerable are raised, the need for effective elderly care solutions to protect the health and safety of the elderly generation is growing. Recently, more and more people are using Smart Toys equipped with ICT technology for care for elderly. In particular, log data collected through smart toys is highly valuable to be used as a quantitative and objective indicator in areas such as policy-making and service planning. However, research related to smart toys is limited, such as the development of smart toys and the validation of smart toy effectiveness. In other words, there is a dearth of research to derive insights based on log data collected through smart toys and to use them for decision making. This study will analyze log data collected from smart toy and derive effective insights to improve the quality of life for elderly users. Specifically, the user profiling-based analysis and elicitation of a change in quality of life mechanism based on behavior were performed. First, in the user profiling analysis, two important dimensions of classifying the type of elderly group from five factors of elderly user's living management were derived: 'Routine Activities' and 'Work-out Activities'. Based on the dimensions derived, a hierarchical cluster analysis and K-Means clustering were performed to classify the entire elderly user into three groups. Through a profiling analysis, the demographic characteristics of each group of elderlies and the behavior of using smart toy were identified. Second, stepwise regression was performed in eliciting the mechanism of change in quality of life. The effects of interaction, content usage, and indoor activity have been identified on the improvement of depression and lifestyle for the elderly. In addition, it identified the role of user performance evaluation and satisfaction with smart toy as a parameter that mediated the relationship between usage behavior and quality of life change. Specific mechanisms are as follows. First, the interaction between smart toy and elderly was found to have an effect of improving the depression by mediating attitudes to smart toy. The 'Satisfaction toward Smart Toy,' a variable that affects the improvement of the elderly's depression, changes how users evaluate smart toy performance. At this time, it has been identified that it is the interaction with smart toy that has a positive effect on smart toy These results can be interpreted as an elderly with a desire to meet emotional stability interact actively with smart toy, and a positive assessment of smart toy, greatly appreciating the effectiveness of smart toy. Second, the content usage has been confirmed to have a direct effect on improving lifestyle without going through other variables. Elderly who use a lot of the content provided by smart toy have improved their lifestyle. However, this effect has occurred regardless of the attitude the user has toward smart toy. Third, log data show that a high degree of indoor activity improves both the lifestyle and depression of the elderly. The more indoor activity, the better the lifestyle of the elderly, and these effects occur regardless of the user's attitude toward smart toy. In addition, elderly with a high degree of indoor activity are satisfied with smart toys, which cause improvement in the elderly's depression. However, it can be interpreted that elderly who prefer outdoor activities than indoor activities, or those who are less active due to health problems, are hard to satisfied with smart toys, and are not able to get the effects of improving depression. In summary, based on the activities of the elderly, three groups of elderly were identified and the important characteristics of each type were identified. In addition, this study sought to identify the mechanism by which the behavior of the elderly on smart toy affects the lives of the actual elderly, and to derive user needs and insights.

• Journal of Life Science
• /
• v.28 no.3
• /
• pp.307-313
• /
• 2018

Alopecia cause psychological stress due to their effect on appearance. Thus, the global market size of the alopecia treatment products are growing quickly. Timosaponin A III is the well known active ingredient of Anemarrhenae Rhizoma. In this study, we investigated and compared the binding affinity of timosaponin A III with finasteride (5-beta reductase antagonist) and minoxidil (androgen receptor antagonist) on the target protein active site by in silico computational docking studies. The three dimensional crystallographic structure of 5-beta reductase (PDB ID : 3G1R) and androgen receptor (PDB ID: 4K7A) was obtained from PDB database. In silico computational autodocking analysis was performed using PyRx, Autodock Vina, Discovery Studio Version 4.5, and NX-QuickPharm option based on scoring functions. The timosaponin A III showed optimum binding affinity (docking energy) with 5-beta reductase as -12.20 kcal/mol as compared to the finasteride (-11.70 kcal/mol) and with androgen receptor as -9.00 kcal/mol as compared to the minoxidil (-7.40 kcal/mol). The centroid X, Y, Z grid position of the timosaponin A III on the 5-beta reductase was similar (overlap) to the finasteride, but the X, Y, Z centroid grid of the timosaponin A III on the androgen receptor was significantly far from the minoxidil centroid position. These results significantly indicated that timosaponin A III could be more potent antagonist to the 5-beta reductase and androgen receptor. Therefore, the extract of Anemarrhenae Rhizoma or timosaponin A III containing biomaterials can substitute the finasteride and minoxidil and can be applied to the alopecia protecting product and related industrial fields.