• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• Journal of agricultural medicine and community health
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• v.25 no.1
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• pp.29-49
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• 2000

Objectives: To estimate the prevalence rate of hypertension, the changes of health behavior, and compliance for the drug treatment after diagnosed as hypertension. Methods: 7,030 persons who live in Cheonan City of Chungnam Province were selected by the cluster sampling method, and 5,372 persons were surveyed by questionnaire and health examination. This data is analyzed by Chi-square test on each variable. Results: 49.8%- of men and 38.8%- of women had been diagnosed as hypertension, and the prevalence rate of hypertension was significantly increased with aging in both gender. The prevalence rate tended to decrease in highly educated women group. Unemployed persons or obese persons showed relatively higher prevalence rate. The prevalence rate of hypertension increased in groups with higher total cholesterol levels over 240 mg/dl, and groups with glucose level over 200 mg/dl. 53.1%- of male patients and 66.6%- of female patients showed compliance for antihypertensive treatment. Compliance for treatment was higher in aged group or lower educated group in both gender. Among men, proportion of compliant subjects was higher in unemployed group(49.3%-), and lower in labor or primary industry than the others but among women, there was not any significant difference. And men with compliance for treatment had higher monthly income than the others, but women did not show any. Conclusion : This population had a high prevalence rate of hypertension which may lead to cardiovascular disease. Therefore health education programs and distribution of information must be emphasized in order to increase compliance to treatment and encourage the change of health behavior to promote health.

• Applied Biological Chemistry
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• v.7
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• pp.92-104
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• 1966

For the purpose of the better dietary management and to empahsize of importance in nutrition education for 552 students at the dormitories, College of Agriculture, Seoul National University, the dietary survey was conducted for each consecutive seven days, from March 7th to 13th at the boy's dormitory, from March 14th to 20th at the girl's dormitory, respectively. In comparison the average caloric and nutrient intake per caput per day at the both, girl's and boy's dormitory with the recommended dietary allowances for age of 25, the intake of calories and all nutrients except riboflavin were over the allowances for the boy, while the caloric intake by the girl was considerablly below the allowance. But it is meant that only 150 calories was actually deficient in comparison with the figure of the average energy consumption determined for the girls at the dormitory of the Sook-myung Woman's University, whose pattern of living was quite similar to those of the girls at this college. Except iron and ascorbic acid, all other nutrients were deficient for the girls. The calories in the form of protein of a diet taken by the boy was 12.9% and that by the girl was 12.8%. Protein quality of the diet taken by boy scored 70 while that by the girl scored 79. NDp Cal% of the diet taken by the boy was 7 and that by the girl was figured out to be 8. Therefore, calculated reference protein taken by the boy was 55.8 grams and that by the girl was 36.9%. Though it is generally recommended that at least 1/3 of the protein should come from animal sources, it was apparent by this survey that providing 1/5 of the protein from animal sources with remaining part of high quality vegetable protein foods in the adequate mixed diet would give satisfactory results for both girl and boy students. This was clearly demonstrated by the recommended reference protein and NDp Cal% met. Significant difference between boys and girls in the average consumption of seasonings was found. In consumption per day of seasonings, boy used 1.5 grams of red pepper powder which means they used 15 times more of red pepper than girls did. Kochujang was used 13 grams by boy-students which was as high as 21 times of that of the girl. Total salt intake by the boy was 34 grams while the girl consummed 23 grams. It is obviously recognized that boys prefer more peppery and salty flavor than girls do. To reduce the amount of protein consummed and to improve the quality of protein food, increase of riboflavin rich food and increase of fat intake in place of grain intake are recommendable to the boy. For the girl's diet, consumption of grains, particularly more intake of barley mal· be recommendable to meet the B group of vitamins allowances as well as the caloric allowance. The use of more servings of yellow green vegetables is needed to the girl.

• Journal of Nutrition and Health
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• v.52 no.1
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• pp.90-103
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• 2019

Purpose: This study examined the relationship of the nutrition of rice and the positive evaluation of the rice-based meal with the food consumption habits, physical and emotional health status, and learning efficacy of 601 middle and high school students in Jeonju area. Methods: The participants were divided into two groups using cluster analysis in that the participants belonging to the upper groups had a center score of 46.86 (n = 348), while the people belonging to the lower group had a center score of 36.89 (n = 253). Statistical differences were tested for all the relationships between the physical and emotional health symptoms and learning efficacy between the groups at the ${\alpha}=0.05$ level. Results: Significant differences in the physical self-evaluated symptoms were observed in all five items in each cluster (p < 0.05). In the case of the emotional health status, nine out of 10 items showed significant differences between the groups. Similarly, significant differences in all five items in learning efficacy questionnaire were noted (p < 0.05). Positive attitudes of the parents toward having breakfast also showed significant differences among the groups. Conclusion: The nutrition of rice and a positive evaluation of the rice-based meals significantly affect the physical and emotional health status and learning efficacy of juveniles. These findings can be used as baseline information for promoting nutrition education, particularly rice-based breakfast.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.231-252
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• 2021

Artificial intelligence (AI) is a key technology that will change the future the most. It affects the industry as a whole and daily life in various ways. As data availability increases, artificial intelligence finds an optimal solution and infers/predicts through self-learning. Research and investment related to automation that discovers and solves problems on its own are ongoing continuously. Automation of artificial intelligence has benefits such as cost reduction, minimization of human intervention and the difference of human capability. However, there are side effects, such as limiting the artificial intelligence's autonomy and erroneous results due to algorithmic bias. In the labor market, it raises the fear of job replacement. Prior studies on the utilization of artificial intelligence have shown that individuals do not necessarily use the information (or advice) it provides. Algorithm error is more sensitive than human error; so, people avoid algorithms after seeing errors, which is called "algorithm aversion." Recently, artificial intelligence has begun to be understood from the perspective of the augmentation of human intelligence. We have started to be interested in Human-AI collaboration rather than AI alone without human. A study of 1500 companies in various industries found that human-AI collaboration outperformed AI alone. In the medicine area, pathologist-deep learning collaboration dropped the pathologist cancer diagnosis error rate by 85%. Leading AI companies, such as IBM and Microsoft, are starting to adopt the direction of AI as augmented intelligence. Human-AI collaboration is emphasized in the decision-making process, because artificial intelligence is superior in analysis ability based on information. Intuition is a unique human capability so that human-AI collaboration can make optimal decisions. In an environment where change is getting faster and uncertainty increases, the need for artificial intelligence in decision-making will increase. In addition, active discussions are expected on approaches that utilize artificial intelligence for rational decision-making. This study investigates the impact of artificial intelligence on decision-making focuses on human-AI collaboration and the interaction between the decision maker personal traits and advisor type. The advisors were classified into three types: human, artificial intelligence, and human-AI collaboration. We investigated perceived usefulness of advice and the utilization of advice in decision making and whether the decision-maker's personal traits are influencing factors. Three hundred and eleven adult male and female experimenters conducted a task that predicts the age of faces in photos and the results showed that the advisor type does not directly affect the utilization of advice. The decision-maker utilizes it only when they believed advice can improve prediction performance. In the case of human-AI collaboration, decision-makers higher evaluated the perceived usefulness of advice, regardless of the decision maker's personal traits and the advice was more actively utilized. If the type of advisor was artificial intelligence alone, decision-makers who scored high in conscientiousness, high in extroversion, or low in neuroticism, high evaluated the perceived usefulness of the advice so they utilized advice actively. This study has academic significance in that it focuses on human-AI collaboration that the recent growing interest in artificial intelligence roles. It has expanded the relevant research area by considering the role of artificial intelligence as an advisor of decision-making and judgment research, and in aspects of practical significance, suggested views that companies should consider in order to enhance AI capability. To improve the effectiveness of AI-based systems, companies not only must introduce high-performance systems, but also need employees who properly understand digital information presented by AI, and can add non-digital information to make decisions. Moreover, to increase utilization in AI-based systems, task-oriented competencies, such as analytical skills and information technology capabilities, are important. in addition, it is expected that greater performance will be achieved if employee's personal traits are considered.

• Journal of Bio-Environment Control
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• v.30 no.1
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• pp.77-84
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• 2021

This study attempted to find a way to maintain the quality of mixing baby wild leaf vegetables with existing baby leaf vegetables in various ratios. The crops for mixing baby leaf vegetables were Peucedanum japoincum Thunberg and Ligularia stenocephala, as wild vegetables, and red romaine, which is widely used in young leafy vegetables. The mixing ratio of red romaine and wild vegetables was red romaine 0: mantilla oil 5: L. stenocephala ratio 5 (R0: P5: L5), red romaine 3.3: P. japoincum 3.3: L. stenocephala ratio 3.3 (R3.3: P3.3: L3.3), red romaine 5: P. japoincum 2.5: L. stenocephala 2.5 (R5: P2.5: L2.5), red romaine 8: P. japoincum 1: L. stenocephala 1 (R8: P1: L1), red romaine 10: P. japoincum 0: L. stenocephala 0 (R10: P0: L0). All treatments were packaged in OTR (oxygen transmittance) 10,000 cc m-2·day-1·atm-1 film and stored for 27 days at 2℃/85% RH conditions. Fresh weight, carbon dioxide, oxygen, and ethylene concentrations of the baby leaf packages were examined approximately every 3 days, and visual quality, chlorophyll content, and chromaticity were examined on the 27th day of storage. The oxygen and carbon dioxide concentration in the packages were affected by the respiration rate of the crop. As the mixing ratio of lettuce, which had a low respiration rate, increased, the oxygen concentration in the packages was higher and the carbon dioxide concentration was lower. Oxygen concentration decreased significantly after 15 days, but was remained above 16%, and on the contrary, carbon dioxide concentration was kept at 1-4% until the 15th, and then gradually increased to 2-5% on the 27th day. The concentration of ethylene was maintained at 3-6 µL·L-1 until the end of storage (27th day). Visual quality score measured at the end of storage was slightly less than 3.0, which is the limit of marketability of all treatments. Although there was no significant difference, the chlorophyll content (SPAD) of red romaine and P. japoincum were most similar with an initial value in R8:P1:1 treatment, and L. stenocephala was higher value in R8:P1:L1 and R5:P2.5:L2.5 treatments at the end of storage. The leaf color (L∗, a∗, b∗, chroma) of the three crops at end of storage compared with the heat map showed the least change in the R5:P2.5:L2.5 and R8:P1:L1 treatments at the end of storage. Among them, R8:P1:L1 treatment maintained the highest chlorophyll content, the second lowest ethylene concentration, and adequate carbon dioxide concentration of 2-3%. Therefore, it is judged that the mixed ratio of red romaine 8: P. japoincum 1: L. stenocephala 1 (R8: P1: L1) is most suitable for the mixed package of baby leaf vegetables of these three crops.

• Asia Marketing Journal
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• v.12 no.2
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• pp.155-175
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• 2010

Most of the service industries including finance and telecommunications have become matured and saturated. The competitions have become severe while the differences among brands become smaller. Therefore maintaining good relationships with customers has been critical for the service providers. In case of credit card and debit card, the similar patterns are shown. It is important for them to maintain good relationships with customers, and therefore, they have used marketing program which provides customized services to customers and utilizes the membership programs. Not only do they build and maintain good relationships, but also highlight their brands from the emotional aspects. For example, KB Card or Hyundai Card uses well-known designers' works for their credit card design. As well, they differentiate the designs of credit cards to stress on their brand personalities. BC Card introduced the credit card with perfume that a customer would like. Even though the credit card is small and not shown to public easily, it becomes more important for those companies to touch the customers' feelings with the brand personalities and their images. This is partly because of changes in consumers' lifestyles. Y-generations becomes highly likely to express themselves in many different ways and more emotional than X-generations. For the Y-generations, therefore, even credit cards in the wallet should be personalized and well-designed. In line with it, credit cards with good design can be seen as an example of brand identity, where different design for each customer can be used to recognize the membership groups that customers want to belong. On the other hand, these credit card companies offer the special treatment benefits for those customers who are heavy users for the cards. For example, those customers who love sports will receive some special discounts when they use their credit cards for sports related products. Therefore this study attempted to explore the relationships between relational benefits, brand identification and loyalty. It has been well known that relational benefits and brand identification lead to loyalty independently from many other studies, but there has been few study to review all the three variables all together in a research model. Furthermore, as reviewed above, in the card industry, many companies attempt to associate the brand image with their products to fit their customers' lifestyles while relational benefits are still playing an important role for their business. Therefore in our research model, relational benefits, brand identification, and loyalty are all included. We focus on the mediating effect of brand identification. From the relational benefits perspective, only special treatment benefit and confidence benefit are included. Social benefit is not applicable for this credit card industry because not many cases of face-to-face interaction can be found. From the brand identification perspective, personal brand identity and social brand identity are reviewed and included in the model. Overall, the research model emphasizes that the relationships between relational benefits and loyalty will be mediated by the effect of brand identification. The effects of relational benefits which are confidence benefit and special treatment benefits on loyalty will be realized when they fit to the personal brand identity and social brand identity. In the research model, therefore, the relationships between confidence benefit and social brand identity, and between confidence benefit and personal identity are hypothesized while the effects of special treatment benefit on social brand identity and personal brand identity are hypothesized. Loyalty, then, is hypothesized to have positive relationships with personal brand identity and social brand identity. In addition, confidence benefit among the relational benefits is expected to have a direct, positive relationship with loyalty because confidence benefit has been recognized as a critical factor for good relationships and satisfaction. Data were collected from college students who have been using either credit cards or debit cards. College students were regarded good subjects because they are in Y-generation cohorts and have tendency to express themselves more. Total sample size was two hundred three at the beginning, but after deleting those data with many missing values, one hundred ninety-seven data points were remained and used for the model testing. Measurement items were brought from the previous literatures and modified for this research. To test the reliability, using SPSS 14, chronbach's α was examined and all the values were from .874 to .928 exceeding over .7. Using AMOS 7.0, confirmatory factor analysis was conducted to investigate the measurement model. The measurement model was found good fit with χ²(67)=188.388 (p= .000), GFI=.886, AGFI=.821, CFI=.941, RMSEA=.096. Using AMOS 7.0, structural equation modeling has been used to analyze the research model. Overall, the research model fit were χ²(68)=188.670 (p= .000), GFI=.886, AGFI=,824 CFI=.942, RMSEA=.095 indicating good fit. In details, all the paths hypothesized in the research model were found significant except for the path from social brand identity to loyalty. Personal brand identity leads to loyalty while both confidence benefit and special treatment benefit have a positive relationships with personal and social identities. As well, confidence benefit has a direct positive effect on loyalty. The results indicates the followings. First, personal brand identity plays an important role for credit/debit card usage. Therefore even for the products which are not shown to public easy, design and emotional aspect can be important to fit the customers' lifestyles. Second, confidence benefit and special treatment benefit have a positive effects on personal brand identity. Therefore it will be needed for marketers to associate the special treatment and trust and confidence benefits with personal image, personality and personal identity. Third, this study found again the importance of confidence and trust. However interestingly enough, social brand identity was not found to be significantly related to loyalty. It can be explained that the main sample of this study consists of college students. Those strategies to facilitate social brand identity are focused on high social status groups while college students have not been established their status yet.

• Asia Marketing Journal
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• v.12 no.1
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• pp.1-30
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• 2010

Customers often experience waiting for buying service. Managing customers' waiting time is important for service providers since customers who are dissatisfied with waiting, secede from a service place at last. Not a few studies have been done to solve waiting time problem and improve customers' waiting experience. Hui & Tse(1996) identify evaluation factors in customers' behavioral mechanism as customers wait. That is, customers experience perceived waiting time, waiting acceptability and emotional response to the wait when they wait. Since customers evaluate the wait using these factors, service provider should manage these factors in order to minimize customers' dissatisfaction. Therefore, this study explores that evaluation factors of waiting are influenced by customers' situational and experiential characteristics, which include customer loyalty, transaction importance for customer and waiting expectation level. Those situational and experiential characteristics are usually given to service providers so they can't control these at waiting point. The major findings derived from two exploratory studies can be summarized as follows. First, according to the result from the study 1 (restaurant setting), customers' transaction importance has the greatest positive influence on waiting experience. The results show restaurant service provider could prevent customers' separation effectively through strategies which raise customers' transaction importance, like giving special coupons for important events. Second, in study 2 (amusement part setting) customer loyalty has large positive impact on waiting experience as well as transaction importance. This results show that service provider could minimize customers' dissatisfaction using strategies which raise customer loyalty continuously. This results show customer perceives waiting experience differently according to characteristics of service place and service itself. Therefore, service provider should grasp the unique customers' situational and experiential characters for each service and service place. It could provide an effective strategy for waiting time management. Third, the study finds transaction importance and waiting expectation level have direct influence customers' waiting experience as independent variables, while existing studies treated them as moderators. Customer loyalty which has not been incorporated in previous waiting time research is known to affect waiting experience. It suggests that marketing strategy which builds up customer loyalty for long period of time is also quite effective, compared to short term tactics to help customers endure waiting time. Fourth, this study reveals the importance of actual waiting time along with perceived waiting time. So far most studies only focus on customers' perceived waiting time. Especially, this study incorporates the concept of patient limit on waiting time to investigate effect of actual waiting time. The results show that there were various responses to the wait depending on how actual waiting time exceeds individual's patent limit on waiting time or not, even though customers wait about the same period of time. Finally, using structural equation model, conceptual path between behavioral responses is verified. As customer perceives waiting time, then she decides whether she can endure it or not, and then her emotional response occurs. This result are somewhat different from Hui & Tse(1996)'s study. The study also includes theoretical contributions as well as practical implications.