• Journal of Food Hygiene and Safety
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• v.36 no.5
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• pp.447-453
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• 2021

In this study, the effectiveness of physical control technology, a combined light sterilization (LED, UV) and hot water treatment in reducing Aspergillus ochraceus for food production environment was investigated. In brief, 1 mL aliquot of A. ochraceus spore suspension (10^7-8 spore/mL) was inoculated onto stainless steel chips, which was then dried at 37℃, and each was subjected to different physical treatment. Treatments were performed for 0.5, 1, 2, 5, 8, and 11 hours to reduce the strains using a light-emitting diode, but no significant difference was confirmed among the treatments. However, a significant reduction was observed on the chips treated with UV-C exposure and hot water immersion. After being treated solely with 360 kJ/m² of UV-C on stainless steel chip, the fungi were significantly reduced to 1.27 log CFU/cm². Concerning the hot water treatment, the initial inoculum amount of 6.49 log CFU/cm² was entirely killed by immersion in 83℃ water for 5 minutes. Maintaining a high temperature for 5 minutes at the site is difficult. Thus, considering economic feasibility and usability, we attempted to confirm the appropriate A. ochraceus reduction conditions by combining a relatively low temperature of 60℃ and UV rays. With the combined treatments, even in lukewarm water, A. ochraceus decreased significantly through the increases in the immersion time and the amount of UV-C irradiation, and the yield was below the detection limit. Based on these results, if work tools are immersed in 60℃ lukewarm water for 3 minutes and then placed in a UV sterilization device for more than 10 minutes, the possibility of A. ochraceus cross-contamination during work is expected to be reduced.

• Korean Journal of Heritage: History & Science
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• v.57 no.2
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• pp.6-25
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• 2024

This study concentrated on a report on the results of smelting experiments conducted eight times by the Jungwon National Research Institute of Cultural Heritage, put together the goals and results of the operation, and examined changes in the content of experiments and in the experimental results. First, changes related to operation, such as the ratio of raw materials to fuel and the presence or absence of additives, were reviewed depending on the operation goal. In addition, the results of metallurgical analysis of raw materials, formations, and byproducts were summarized and reviewed by comparing them with materials excavated from the ruins. The operation method varied up to the eighth smelting experiment in terms of iron ore roasting, additives, and raw material/fuel ratio. After reviewing the results again, pure iron with a low carbon content began to be confirmed through metallurgical analysis. As a result, it was confirmed that the charging ratio of raw materials and fuel plays an important role depending on the purpose of production. In addition, most of the products are gray cast iron, and it was deemed that this is due to changes in the internal structure of the pig iron while it was left in the furnace for a long time. The iron was an ingot that was in a molten state even though the carbon content did not reach 4.3%, where the process reaction takes place, and it was deemed to have been caused by excessive operating temperature. Based on the previously reviewed results and the structure and shape of the experimental furnace used in other ironmaking technology restoration experiments, this study finally attempted to restore the structure of an ancient iron smelting furnace, including the furnace's upper structure. By comprehensively referring to the remaining conditions of the excavated iron smelting furnace and the characteristics of the blow pipe, the form of the ancient iron smelting furnace was subdivided into six categories: furnace wall thickness, furnace height, blower height, blow pipe size, furnace inner wall shape, and top shape, and a restoration plan was proposed. To improve the problems of the restoration plan and the Jungwon National Research Institute of Cultural Heritage's experiments that have been conducted through continuous trial and error, an experiment that reflects changes in operating methods by lowering the furnace height and controlling the blowing volume is necessary.

• Korean Business Review
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• v.17
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• pp.153-183
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• 2004

The Gaisong Merchants can be regarded to playa pioneering role to activate the Korea's trade with foreign countries. In the early period of Yi-Dynasty, the Gaisong Merchants focused on personal trade, but in the middle period of Yi-Dynasty, they entered to the realm of governmental trade. Furthermore, their business activities widened to various forms of trades, for example, smuggling. Utilizing accumulated capital, Gaisong merchants expanded their trading activities to their neighboring countries such as Japan and China. In recent times, it is necessary for modem Korean companies to diversify risks through the establishment of corporations for production, marketing and R&D abroad or through joint venture, M&A and strategic alliance with foreign companies in order to reduce the risks originated from volatile economic and political situations. In this study, we utilize tools of comparative study to compare Gaisong Merchants' foreign trade strategies with those of modem companies such as AMOREPACIFIC, HANILCEMENT and SHINDORICO. The purpose of the paper is to test the hypothesis that modem Korean companies grew up by following the cases of Gaisong Merchants' business activities. We summarize our main findings as follows. First, both Gaisong Merchants and modem Korean companies have common functional core capability in the field of marketing, manufacturing technology, R&D, and human resources development. Second, both Gaisong Merchants and modem Korean companies have common organizational core capability. Third, both Gaisong Merchants and modem Korean companies have common infrastructures such as planning, finance, accounting and MIS. It constitutes the infrastructure of Korea's foreign trade sector. Fourth, both Gaisong Merchants and modem companies have common organizational culture in the field of management policy and philosophy. Actually, those factors are evaluated to be driving forces of Koera's success in foreign trade. In conclusion, the business activities of Gaisong Merchants who represented the peculiarity of Korean business spirit are partially inherited to current Korean business management. The value system and behavior pattern of modern Korean companies is succeeded from the spirit of Gaisong Merchants and it playa major role to specify the identity of Korean business administration.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.127-141
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• 2017

Advances in Internet technologies and the proliferation of mobile devices enabled consumers to approach a wide range of goods and services, while causing an adverse effect that they have hard time reaching their congenial items even if they devote much time to searching for them. Accordingly, businesses are using the recommender systems to provide tools for consumers to find the desired items more easily. Association Rule Mining (ARM) technology is advantageous to recommender systems in that ARM provides intuitive form of a rule with interestingness measures (support, confidence, and lift) describing the relationship between items. Given an item, its relevant items can be distinguished with the help of the measures that show the strength of relationship between items. Based on the strength, the most pertinent items can be chosen among other items and exposed to a given item's web page. However, the diversity of the measures may confuse which items are more recommendable. Given two rules, for example, one rule's support and confidence may not be concurrently superior to the other rule's. Such discrepancy of the measures in distinguishing one rule's superiority from other rules may cause difficulty in selecting proper items for recommendation. In addition, in an online environment where a web page or mobile screen can provide a limited number of recommendations that attract consumer interest, the prudent selection of items to be included in the list of recommendations is very important. The exposure of items of little interest may lead consumers to ignore the recommendations. Then, such consumers will possibly not pay attention to other forms of marketing activities. Therefore, the measures should be aligned with the probability of consumer's acceptance of recommendations. For this reason, this study proposes a model-based approach to combine those measures into one unified measure that can consistently determine the ranking of recommended items. A regression model was designed to describe how well the measures (independent variables; i.e., support, confidence, and lift) explain consumer's acceptance of recommendations (dependent variables, hit rate of recommended items). The model is intuitive to understand and easy to use in that the equation consists of the commonly used measures for ARM and can be used in the estimation of hit rates. The experiment using transaction data from one of the Korea's largest online shopping malls was conducted to show that the proposed model can improve the hit rates of recommendations. From the top of the list to 13th place, recommended items in the higher rakings from the proposed model show the higher hit rates than those from the competitive model's. The result shows that the proposed model's performance is superior to the competitive model's in online recommendation environment. In a web page, consumers are provided around ten recommendations with which the proposed model outperforms. Moreover, a mobile device cannot expose many items simultaneously due to its limited screen size. Therefore, the result shows that the newly devised recommendation technique is suitable for the mobile recommender systems. While this study has been conducted to cover the cross-selling in online shopping malls that handle merchandise, the proposed method can be expected to be applied in various situations under which association rules apply. For example, this model can be applied to medical diagnostic systems that predict candidate diseases from a patient's symptoms. To increase the efficiency of the model, additional variables will need to be considered for the elaboration of the model in future studies. For example, price can be a good candidate for an explanatory variable because it has a major impact on consumer purchase decisions. If the prices of recommended items are much higher than the items in which a consumer is interested, the consumer may hesitate to accept the recommendations.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.8 no.2
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• pp.129-139
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• 2013

This paper is targeted on proposing ameliorating alternative to performance assessment method of GSEM through evaluating the current one, which is initiated by SMBA to induce fair competition among 5 GSEM across the country and accommodate the quality improvement of entrepreneurship education since 2005 after beginning the SMBA support, from the perspective of BSC(Balanced Scorecard) tool. Ultimately, it complements the policy defects of SMBA over GSEM, in particular, in the process of performance assessment and management. This paper carries out two studies as follow. First, throughout reviewing the previous studies relating to BSC applications to non-profit organization, it set out the direction of introducing BSC in assessing performance of GSEM in order to enhance its effectiveness. Second, it evaluate the rationality of performance assessing tools apllied to GSEM by SMBA on the basis of BSC application over non-profit organization, especially in education institution. Research results shows the following implications. First, the current evaluation system over GSEM is just merely assessment itself and not much contributions for the post performance management. Second, The annual evaluation just remains to check up whether the policy goals are met or not. Third, the current evaluation puts much emphasis just on financial inputs and hardware infra, not considering human resources and utilization of government policy and institution. Fourth, the policy goals are unilaterally focused on entrepreneurs. Fifth, the current evaluation systems do not contain any indexes relating to learning and growth perspectives for concerning sustainable and independent growing up. However, lack of empirical testing require this paper to need the further study in the future.

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.187-206
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• 2007

The development of computer and information technology has been combined with the information superhighway internet infrastructure, so information widely spreads not only in special fields but also in the daily lives of people. Information ubiquity influences the traditional way of transaction, and leads a new E-commerce which distinguishes from the existing E-commerce. Not only goods as physical but also service as non-physical come into E-commerce. As the scale of E-Commerce is being enlarged as well. It keeps people from finding information they want. Recommender systems are now becoming the main tools for E-Commerce to mitigate the information overload. Recommender systems can be defined as systems for suggesting some Items(goods or service) considering customers' interests or tastes. They are being used by E-commerce web sites to suggest products to their customers who want to find something for them and to provide them with information to help them decide which to purchase. There are several approaches of recommending goods to customer in recommender system but in this study, the main subject is focused on collaborative filtering technique. This study presents a possibility of pre-evaluation for the prediction performance of customer's preference in collaborative filtering before the process of customer's preference prediction. Pre-evaluation for the prediction performance of each customer having low performance is classified by using the statistical features of ratings rated by each customer is conducted before the prediction process. In this study, MovieLens 100K dataset is used to analyze the accuracy of classification. The classification criteria are set by using the training sets divided 80% from the 100K dataset. In the process of classification, the customers are divided into two groups, classified group and non classified group. To compare the prediction performance of classified group and non classified group, the prediction process runs the 20% test set through the Neighborhood Based Collaborative Filtering Algorithm and Correspondence Mean Algorithm. The prediction errors from those prediction algorithm are allocated to each customer and compared with each user's error. Research hypothesis : Two research hypotheses are formulated in this study to test the accuracy of the classification criterion as follows. Hypothesis 1: The estimation accuracy of groups classified according to the standard deviation of each user's ratings has significant difference. To test the Hypothesis 1, the standard deviation is calculated for each user in training set which is divided 80% from MovieLens 100K dataset. Four groups are classified according to the quartile of the each user's standard deviations. It is compared to test the estimation errors of each group which results from test set are significantly different. Hypothesis 2: The estimation accuracy of groups that are classified according to the distribution of each user's ratings have significant differences. To test the Hypothesis 2, the distributions of each user's ratings are compared with the distribution of ratings of all customers in training set which is divided 80% from MovieLens 100K dataset. It assumes that the customers whose ratings' distribution are different from that of all customers would have low performance, so six types of different distributions are set to be compared. The test groups are classified into fit group or non-fit group according to the each type of different distribution assumed. The degrees in accordance with each type of distribution and each customer's distributions are tested by the test of ${\chi}^2$ goodness-of-fit and classified two groups for testing the difference of the mean of errors. Also, the degree of goodness-of-fit with the distribution of each user's ratings and the average distribution of the ratings in the training set are closely related to the prediction errors from those prediction algorithms. Through this study, the customers who have lower performance of prediction than the rest in the system are classified by those two criteria, which are set by statistical features of customers ratings in the training set, before the prediction process.

• Korean Journal of Cognitive Science
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• v.28 no.4
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• pp.315-328
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• 2017

Even though assessment using information and communication technology will most likely lead the future of educational assessment, there is little domestic research on this topic. Computerized assessment will not only cut costs but also measure students' performance in ways not possible before. In this context, this study introduces a tool which can overcome the problems of multiple choice tests, which are most widely used type of assessment in current Korean educational setting. Multiple-choice tests, in which options are presented with the questions, are efficient in that grading can be automated; however, they allow for students who don't know the answer, to find the correct answer from the options. Park(2005) has developed a modified multiple-choice testing system (CMMT) using the interactivity of computers, that presents questions first, and options later for a short time when the student requests for them. The present study was conducted to find out if penalizing wrong answers could lower the possibility of students choosing an answer among the options when they don't know the correct answer. 116 students were tested with the directions that they will be penalized for wrong answers, but not for no response. There were 4 experimental conditions: 2 conditions of high or low percentage of penalizing, each in traditional multiple-choice or CMMT format. The results were analyzed using a two-way ANOVA for the number of no response, the test score and self-report score. Analysis showed that the number of no response was significantly higher for the CMMT format and that test scores were significantly lower when the penalizing percentage was high. The possibility of applying CMMT format tests while penalizing wrong answers in actual testing settings was addressed. In addition, the need for further research in the cognitive sciences to develop computerized assessment tools, was discussed.

• Asia pacific journal of information systems
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• v.22 no.2
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• pp.39-69
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• 2012

With the advent of communication technologies including electronic collaborative tools and conferencing systems provided over the Internet, virtual collaboration is becoming increasingly common in organizations. Virtual collaboration refers to an environment in which the people working together are interdependent in their tasks, share responsibility for outcomes, are geographically dispersed, and rely on mediated rather than face-to face, communication to produce an outcome. Research suggests that new sets of individual skill, knowledge, and ability (SKAs) are required to perform effectively in today's virtualized workplace, which is labeled as individual virtual competence. It is also argued that use of online social networking sites may influence not only individuals' daily lives but also their capability to manage their work-related relationships in organizations, which in turn leads to better performance. The existing research regarding (1) the relationship between virtual competence and task performance and (2) the relationship between online networking and task performance has been conducted based on different theoretical perspectives so that little is known about how online social networking and virtual competence interplay to predict individuals' task performance. To fill this gap, this study raises the following research questions: (1) What is the individual virtual competence required for better adjustment to the virtual collaboration environment? (2) How does online networking via diverse social network service sites influence individuals' task performance in organizations? (3) How do the joint effects of individual virtual competence and online networking influence task performance? To address these research questions, we first draw on the prior literature and derive four dimensions of individual virtual competence that are related with an individual's self-concept, knowledge and ability. Computer self-efficacy is defined as the extent to which an individual beliefs in his or her ability to use computer technology broadly. Remotework self-efficacy is defined as the extent to which an individual beliefs in his or her ability to work and perform joint tasks with others in virtual settings. Virtual media skill is defined as the degree of confidence of individuals to function in their work role without face-to-face interactions. Virtual social skill is an individual's skill level in using technologies to communicate in virtual settings to their full potential. It should be noted that the concept of virtual social skill is different from the self-efficacy and captures an individual's cognition-based ability to build social relationships with others in virtual settings. Next, we discuss how online networking influences both individual virtual competence and task performance based on the social network theory and the social learning theory. We argue that online networking may enhance individuals' capability in expanding their social networks with low costs. We also argue that online networking may enable individuals to learn the necessary skills regarding how they use technological functions, communicate with others, and share information and make social relations using the technical functions provided by electronic media, consequently increasing individual virtual competence. To examine the relationships among online networking, virtual competence, and task performance, we developed research models (the mediation, interaction, and additive models, respectively) by integrating the social network theory and the social learning theory. Using data from 112 employees of a virtualized company, we tested the proposed research models. The results of analysis partly support the mediation model in that online social networking positively influences individuals' computer self-efficacy, virtual social skill, and virtual media skill, which are key predictors of individuals' task performance. Furthermore, the results of the analysis partly support the interaction model in that the level of remotework self-efficacy moderates the relationship between online social networking and task performance. The results paint a picture of people adjusting to virtual collaboration that constrains and enables their task performance. This study contributes to research and practice. First, we suggest a shift of research focus to the individual level when examining virtual phenomena and theorize that online social networking can enhance individual virtual competence in some aspects. Second, we replicate and advance the prior competence literature by linking each component of virtual competence and objective task performance. The results of this study provide useful insights into how human resource responsibilities assess employees' weakness and strength when they organize virtualized groups or projects. Furthermore, it provides managers with insights into the kinds of development or training programs that they can engage in with their employees to advance their ability to undertake virtual work.

• Journal of the Korean Society of Earth Science Education
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• v.10 no.2
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• pp.140-160
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• 2017

The purpose of this study was to develop computational thinking (CT) analysis tool that can be used to analyze CT practices; first, by defining what CT practices are, and then, by identifying which components of CT are reflected in STEAM classes. Exploring various kinds of CT practices, which can be identified while applying the proposed CT analysis tool for exemplary STEAM classes, is another goal of this study. Firstly, to answer the question of "What is CT in science education" and thereby to develop the proposed CT practice analysis tool, three types of published documents about CT definition as the main data in this study have been considered. In the first "analysis tool development" part of this study, the following five elements have been identified as the main components of CT analysis tool as follows; (1) connecting open problems with computing, (2) using tools or computers to develop computing artifact, (3) abstraction process, (4) analyzing and evaluating computing process and artifact, and (5) communicating and cooperating. Based on the understandings that there is a consistent flow among the five components due to their interactions, a flow chart of CT practice has also been developed. In the second part of this study, which is an implementation study, the proposed CT practice analysis tool has been applied in one exemplary STEAM program. To select the candidate STEAM program, four selection criteria have been identified. Then, the proposed CT practice analysis tool has been applied for the selected STEAM program to determine the degree of CT practice reflected in the program and furthermore, to suggest a way of improving the proposed CT analysis tool if it shows some weak points. Through the findings of this study, we suggest that the actual definition of computational thinking will be helpful to converge Technology and Engineering to STEAM education and a strong complement to reinforce STEAM education.

• Journal of Food Hygiene and Safety
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• v.31 no.6
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• pp.439-444
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• 2016

In the present study, the performance of culture methods using two selective agars and real-time PCR were compared for selective isolation of Cronobacter in powdered infant formula and dried pumpkin. Two food samples were spiked with the pathogen and then preenriched in distilled water. A small portion of preenrichment (10 mL) was incubated in Enterobacteriaceae enrichment both, followed by inoculation onto Druggan-Forsythe-Iversen agar (DFI agar) and Cronobacter sakazakii chromogenic plating agar (R&F agar). The preenrichment and enrichment (1 mL each) was used in real-time PCR assay. In powdered infant formula (PIF), no statistical difference was observed between both culture methods and real-time PCR with preenrichemt (p > 0.05). However, the number of positives obtained by R&F agar and real-time PCR was much higher than that of culture method using DFI agar in dried pumpkin (p < 0.05). In particular, R&F agar yielded a significantly greater selectivity than DFI agar in dried pumpkin (p < 0.05). Real-time PCR and R&F agar, which are currently recommended by US FDA, could be used as an alternative detection tools for the isolation of Cronobacter in PIF and ingredient of child foods such as dried pumpkin that has high number of competing natural microflora.