• Journal of the korean academy of Pediatric Dentistry
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• v.38 no.2
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• pp.129-136
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• 2011

Microorganisms are the main causative factors of pulpal and periapical diseases, therefore successful endodontic treatment is depend on the effective elimination of intracanal bacterial populations. Many studies have been reported antimicrobial effect of Allyl isothiocyanate (AIT) which the principle ingredient of Horseradish (Armoracia rusticana) root extracts. The purposes of this study are to evaluate the antimicrobial effectiveness of Horseradish root extracts against Enterococcus faecalis in root canals of extracted human teeth and compare to sodium hypochlorite (NaOCl). Extracted human mandibular premolar root canals were infected with E. faecalis for 21 days, and then irrigated with Horseradish root extracts, NaOCl solution and saline. After canal irrigation, first samples (S1) were taken. After first sampling, the canals were additionally incubated 7 days, and then second samples (S2) were taken. The samples were inoculated on EHI agar plate to determine the colony forming units (CFU). 1. Mean values of CFU in S1 were $5.815{\times}10^3$ CFU/ml at Horseradish groups, and $3.465{\times}10^3$ CFU/ml at NaOCI groups. There was no statistically significant differences (p=0.086). 2. Mean values of CFU in S2 were $3.100{\times}10^3$ CFU/ml at Horseradish groups, and $5.252{\times}10^5$ CFU/ml at NaOCI groups. There was statistically significant difference (p<.05). 3. There was no statistically significant differences (p=0.076) between S1 and S2 at Horseradish groups in the mean values of CFU. However, there was statistically significant differences (p<.05) between S1 and S2 at NaOCI groups in the mean values of CFU.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.2
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• pp.125-137
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• 2018

Credit unions organized and operated by the members of communities, work-places or groups are co-operative entities where customers act as owners not just transaction partners. The foregoing organizational characteristic of credit unions exerts beneficial effects on their customer relationship, and underscores the need for diversifying their relationship marketing strategies. This study sheds light on the structural relationship of credit unions in terms of principal variables of relationship marketing, i.e. relationship benefits, customer satisfaction and long-term relationship orientation. Specifically, we classify the relationship benefits into three sub-dimensions, i.e. confidence benefits, social benefits and special treatment benefits, and structuralize a causal model involving the customer satisfaction and long-term relationship orientation. From December 26, 2017 to January 26, 2018, A total of 360 questionnaires was collected. Of these, 346 were selected as the final samples, excluding 14, which are difficult to use in statistics. The reliability analysis, exploratory factor analysis, and regression analysis was performed by using the 'SPSS 24.0'. And confirmatory factor analysis, structural equation model analysis was performed by using 'AMOS 24.0'. The findings highlight the following. First, confidence benefits directly impact on the long-term relationship orientation, and indirectly influence the latter by the medium of customer satisfaction. Second, social benefits directly influence the long-term relationship orientation, without exerting any indirect effects on the latter via customer satisfaction. Third, special treatment benefits do not directly impact on the long-term relationship orientation but have indirect effects on the latter by the medium of customer satisfaction. Fourth, customer satisfaction has positive effects on the long-term relationship orientation. The findings suggest credit unions should establish a long-term relationship with their customers by providing them with confidence benefits to earn their trust and confidence, with social benefits to build a relationship of affinity and friendship, and with special treatment benefits to meet their needs in the long, not short and temporary, term.

• Korean Journal of Food Science and Technology
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• v.33 no.4
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• pp.437-443
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• 2001

Gastrodia elata blume (GEB) is considered to be a useful herbal medicine in oriental countries for the treatment of headache, migraine, dizziness, childhood convulsion, epilepsy, rheumatism, hypertension, neuralgia and neurological disorders. This study was carried out to investigate the quality of bread added with the powder of GEB. The possibility of GEB wheat flour mixture as bread was studied by adding 0%, 0.5%, 1.0%, 1.5%, 2.0% of GEB powder to wheat flour. In Farinograph data, the dough stability decreased with the increase of GEB powder. Granular size of starches ranged from $36\;{\mu}m\;to\;60{\mu}m$, and the shape of them showed a long oval figure. Amylograph showed that the increase in the ratio of GEB on the doughs slightly elevated in the maximum viscosity. The loaf volume of 0.5% powder increased by 10.2% but that of 2.0% decreased by 16.8%. The moisture content was 43.57% in the control but it increased as the powder addition. The colors of crust and crumb were not significantly different among L, b and ${\Delta}E$, but 'a' value in crumb was increased as the powder addition. The addition of the powder had no significant effect on bread texture. In sensory evaluation, the moistness increased as the increase of the powder addition. The control bread was most excellent, and the bread made by mixing additives were better than just 0.5% GEB-wheat flour in terms of quality.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.155-169
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• 2014

With the rapid advances in technologies, organizations are more likely to depend on information systems in their decision-making processes. Business Intelligence (BI) systems, in particular, have become a mainstay in dealing with complex problems in an organization, partly because a variety of advanced computational methods from statistics, machine learning, and artificial intelligence can be applied to solve business problems such as demand forecasting. In addition to the ability to analyze past and present trends, these predictive analytics capabilities provide huge value to an organization's ability to respond to change in markets, business risks, and customer trends. While the performance effects of BI system use in organization settings have been studied, it has been little discussed on the use of predictive analytics technologies embedded in BI systems for forecasting tasks. Thus, this study aims to find important factors that can help to take advantage of the benefits of advanced technologies of a BI system. More generally, a BI system can be viewed as an advisor, defined as the one that formulates judgments or recommends alternatives and communicates these to the person in the role of the judge, and the information generated by the BI system as advice that a decision maker (judge) can follow. Thus, we refer to the findings from the advice-giving and advice-taking literature, focusing on the role of explanations of the system in users' advice taking. It has been shown that advice discounting could occur when an advisor's reasoning or evidence justifying the advisor's decision is not available. However, the majority of current BI systems merely provide a number, which may influence decision makers in accepting the advice and inferring the quality of advice. We in this study explore the following key factors that can influence users' advice taking within the setting of a BI system: explanations on how the box-office grosses are predicted, types of advisor, i.e., system (data mining technique) or human-based business advice mechanisms such as prediction markets (aggregated human advice) and human advisors (individual human expert advice), users' evaluations of the provided advice, and individual differences in decision-makers. Each subject performs the following four tasks, by going through a series of display screens on the computer. First, given the information of the given movie such as director and genre, the subjects are asked to predict the opening weekend box office of the movie. Second, in light of the information generated by an advisor, the subjects are asked to adjust their original predictions, if they desire to do so. Third, they are asked to evaluate the value of the given information (e.g., perceived usefulness, trust, satisfaction). Lastly, a short survey is conducted to identify individual differences that may affect advice-taking. The results from the experiment show that subjects are more likely to follow system-generated advice than human advice when the advice is provided with an explanation. When the subjects as system users think the information provided by the system is useful, they are also more likely to take the advice. In addition, individual differences affect advice-taking. The subjects with more expertise on advisors or that tend to agree with others adjust their predictions, following the advice. On the other hand, the subjects with more knowledge on movies are less affected by the advice and their final decisions are close to their original predictions. The advances in predictive analytics of a BI system demonstrate a great potential to support increasingly complex business decisions. This study shows how the designs of a BI system can play a role in influencing users' acceptance of the system-generated advice, and the findings provide valuable insights on how to leverage the advanced predictive analytics of the BI system in an organization's forecasting practices.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.6 no.3
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• pp.179-187
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• 2008

After Canada has struggled with a radioactive waste problem over for 20 years, the Canadian government finally found out that its approach by far has been lack of social acceptance, and needed a program such as public and stakeholder engagement (PSE) which involves the public in decision-making process. Therefore, the government made a special law, called Nuclear Fuel Waste Act (NFWA), to search for an appropriate nuclear waste management approach. NFWA laid out three possible approaches which were already prepared in advance by a nuclear expert group, and required Nuclear Waste Management Organization (NWMO) to be established to report a recommendation as to which of the proposed approaches should be adopted. However, NFWA allowed NWMO to consider additional management approach if the other three were not acceptable enough. Thus, NWMO studied and created a fourth management approach after it had undertaken an comparison of the benefits, risks and costs of each management approach: Adaptive Phased Management. This approach was intended to enable the implementers to accept any technological advancement or changes even in the middle of the implementation of the plan. The Canadian PSE case well shows that technological R&D are deeply connected with social acceptance. Even though the developments and technological advancement are carried out by the scientists and experts, but it is important to collect the public opinion by involving them to the decision-making process in order to achieve objective validity on the R&D programs. Moreover, in an effort to ensure the principles such as fairness, public health and safety, security, and adoptability, NWMO tried to make those abstract ideas more specific and help the public understand the meaning of each concept more in detail. Also, they utilized a variety of communication methods from face-to-face meeting to e-dialogue to encourage people to participate in the program as much as possible. Given the fact that Korea has been also having a hard time in dealing with spent nuclear fuel management, all of these efforts that Canada has made with a PSE program would give good lessons and implications to the Korean case. In conclusion, as a deliberative participation program, PSE could be a possible breakthrough approach for the Korean spent nuclear fuel management.

• Journal of Nutrition and Health
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• v.48 no.3
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• pp.248-257
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• 2015

Purpose: The aim of this study was to estimate total sugar intake and sugar intake-related dietary habit and nutrient intake of middle school students. Methods: Subjects included 1,184 middle school students (476 males and 708 females) residing in Jeju. This research analyzed daily dietary intakes of subjects using the 24 hour recall method and surveyed the dietary habit related to total sugar intake using questionnaires. Descriptive analysis, chi-square test, t-test, and ANOVA, using the SAS program were used for analysis of data. Results: The average daily total sugar intake was 60.3 g (male 50.5 g, female 66.9 g). Total sugar intake per meal was 6.5 g (10.8%) from breakfast, 9.0 g (14.9%) from lunch, 11.8 g (19.6%) from dinner, and 33.0 g (54.7%) from snacks. Food groups that contribute to the majority of total sugar intake were grains and their products (23.0 g), milk (11.0 g), fruits and their products (7.3 g), sugars and sweets (6.1 g), and vegetables and their products (5.8 g). In terms of total sugar intakes by cooking methods, desserts showed a greater amount than main and side dishes, and indicated in order of amount as follows: bread and cookies (11.5 g), dairy products (7.5 g), ice cakes (6.2 g), beverages (5.3 g), and fruits (4.5 g). Total sugar consumption was high for rice and side dishes such as noodles (10.2 g), fried foods (2.9 g), stir-fried foods (2.0 g), and cooked rice with seasoning (1.7 g). The daily intake of natural sugar, added sugar, and natural and added sugar was 18.3 g, 35.8 g, and 6.2 g, respectively. The high sugar intake group, which was over 20% of the energy from total sugar intakes, consumed significantly less Fe, Zn, vitamin B6, niacin, and vitamin E than the low sugar intake group, which was below 20%. Conclusion: Total sugar intake of second graders of middle schools on Jeju Island was 60.3 g/day, mostly obtained from snacks (54.7%). Therefore, nutritional education for proper selection of better snacks and for reduction of dietary sugar intake is needed for middle school students.

• The Journal of Society for e-Business Studies
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• v.17 no.4
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• pp.69-93
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• 2012

Various influence-related relationships in Social Network Services (SNS) among users, posts, and user-and-post, can be expressed using links. The current research evaluates the influence of specific users or posts by analyzing the link structure of relevant social network graphs to identify influential users. We applied the concept of mutual interactions proposed for ranking semantic web resources, rather than the voting notion of Page Rank or HITS, to blogosphere, one of the early SNS. Through many experiments with network models, where the performance and validity of each alternative approach can be analyzed, we showed the applicability and strengths of our approach. The weight tuning processes for the links of these network models enabled us to control the experiment errors form the link weight differences and compare the implementation easiness of alternatives. An additional example of how to enter the content scores of commercial or spam posts into the graph-based method is suggested on a small network model as well. This research, as a starting point of the study on identifying influential users in SNS, is distinctive from the previous researches in the following points. First, various influence-related properties that are deemed important but are disregarded, such as scraping, commenting, subscribing to RSS feeds, and trusting friends, can be considered simultaneously. Second, the framework reflects the general phenomenon where objects interacting with more influential objects increase their influence. Third, regarding the extent to which a bloggers causes other bloggers to act after him or her as the most important factor of influence, we treated sequential referencing relationships with a viewpoint from that of PageRank or HITS (Hypertext Induced Topic Selection).

• Journal of the HCI Society of Korea
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• v.11 no.1
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• pp.47-55
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• 2016

Three Dimensional Printing (herein, 3D printing) not only gives novelty and interests to modern people but is also a spotlighted technology that could herald a new industrial revolution. The introduction of various 3D printing service platforms has enabled individuals to easily possess products designed through 3D printing. However, there are still many issues to consider until the era of new manufacturing, when 3D printing becomes available to the general public so that anyone can make and design products with 3D printing. For instance, there needs to be sufficient consideration and research on whether the current 3D printing services can prove their higher capability to produce products conventionally done by machines and hands through 3D printing, and on the meaning of selling a wide range of product families like those of most 3D printing service platforms to the consumers. This study, which was initiated in this context, aimed to gain insight on the directions that 3D printing services need to advance going forward by letting consumers have first-hand experience on 3D printing online service platforms with a wide range of product families and those with relatively limited services, and then asking them to answer multiple-choice and short-answer survey questions on the websites they wish to purchase from, diversity of designs, design satisfaction, perceived technical skills, perceived purchase satisfaction, perceived after-sales service(A/S). As a result, we were able to witness that consumers generally had a strong preference for services with a wide range of product families (e.g. Shapeways) compared to services with a narrow range (e.g. Digital Forming). We also verified that design diversity and the possibility of realizing the designs were the crucial aspects that need to be considered with 3D printing services. Moreover, we also carried out discussions on carrying out design consulting by securing a pool of designers from diverse fields, on providing web-based designing software that can be utilized even by beginners, and on operating shops both online and offline in order to provide more competitive 3D printing services.

• Investigative Magnetic Resonance Imaging
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• v.12 no.2
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• pp.100-106
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• 2008

The purpose of this study was to confirm the exactitude of in vitro nuclear magnetic resonance spectroscopy(NMRS) and to complement the defect of in vivo NMRS. It has been difficult to understand the metabolism of a cerebellum using in vivo NMRS owing to the generated inhomogeneity of magnetic fields (B0 and B1 field) by the complexity of the cerebellum structure. Thus, this study tried to more exactly analyze the metabolism of a canine cerebellum using the cell extraction and high resolution NMRS. In order to conduct the absolute metabolic quantification in a canine cerebellum, the spectrum of our phantom included in various brain metabolites (i.e., NAA, Cr, Cho, Ins, Lac, GABA, Glu, Gln, Tau and Ala) was obtained. The canine cerebellum tissue was extracted using the methanol-chloroform water extraction (M/C extraction) and one group was filtered and the other group was not under extract processing. Finally, NMRS of a phantom solution and two extract solution (90% D2O) was progressed using a 500MHz (11.4 T) NMR machine. Filtering a solution of the tissue extract increased the signal to noise ratio (SNR). The metabolic concentrations of a canine cerebellum were more close to rat’s metabolic concentration than human’s metabolic concentration. The present study demonstrates the absolute quantification technique in vitro high resolution NMRS with tissue extraction as the method to accurately measure metabolite concentration.

• The Journal of Society for e-Business Studies
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• v.25 no.2
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• pp.15-27
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• 2020

This study starts with the idea that the process of creating a Gantt Chart for schedule planning is similar to Tetris game with only a straight line. In Tetris games, the X axis is M machines and the Y axis is time. It is assumed that all types of orders can be worked without separation in all machines, but if the types of orders are different, setup cost will be incurred without delay. In this study, the game described above was named Gantris and the game environment was implemented. The AI-scheduling table through in-depth reinforcement learning compares the real-time scheduling table with the human-made game schedule. In the comparative study, the learning environment was studied in single order list learning environment and random order list learning environment. The two systems to be compared in this study are four machines (Machine)-two types of system (4M2T) and ten machines-six types of system (10M6T). As a performance indicator of the generated schedule, a weighted sum of setup cost, makespan and idle time in processing 100 orders were scheduled. As a result of the comparative study, in 4M2T system, regardless of the learning environment, the learned system generated schedule plan with better performance index than the experimenter. In the case of 10M6T system, the AI system generated a schedule of better performance indicators than the experimenter in a single learning environment, but showed a bad performance index than the experimenter in random learning environment. However, in comparing the number of job changes, the learning system showed better results than those of the 4M2T and 10M6T, showing excellent scheduling performance.