• Human Ecology Research
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• v.62 no.1
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• pp.81-100
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• 2024

This paper presents a case study in which a lesson was designed and applied to enhance preservice home economics teachers' instructional design competence using the metaverse. For 15 weeks from March 6 to June 14, 14 students enrolled on the course 'Multimedia Home Economics Education' for preservice home economics teachers used the metaverse to engage in problem-based learning to solve instructional design problems in home economics classes. In accordance with the ADDIE design model, in the analysis stage, we assessed preservice home economics teachers' level of knowledge of lessons using the metaverse, and their perceptions of the possibility, necessity, and usefulness of using the metaverse in home economics lessons. In the design and development stage, lesson plans, questions for problem-based learning, assessment tools, and teaching and learning materials were developed. The implementation was conducted in parallel with training on understanding multimedia and the metaverse, and instructional design competence was evaluated through pre- and post-testing and reflection journals. The results revealed that the preservice home economics teachers acquired a good understanding of lessons using the metaverse, learned how to design lessons for self-directed learning by applying the metaverse to their home and classroom, and gained confidence in applying it to their teaching practice or in-service work. It is expected that the results of this study will be used as support materials for prospective and current home economics teachers to design home economics lessons using the metaverse, thereby expanding the horizons of home economics education.

• Journal of Service Research and Studies
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• v.9 no.2
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• pp.55-76
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• 2019

This study conducted empirical analyses to investigate the factors affecting the intention to use smart home services. Based on the previous relevant studies, the characteristics of smart home service were found to influence on the intention to use smart home service, and four variables(ubiquitous connectivity, reliability, context awareness, and security) concerning the service characteristics could be derived. And referring to the technology acceptance model(TAM), the updated TAM, IS success model, and the theory of reasoned action(TRA), three variables such as perceived ease of use, perceived usefulness and subjective norm were also likely to affect the intention to use smart home service, and the user innovativeness was inferred to play a role of moderating variable. In order to examine the research model and the hypotheses which could describe the relationship of the above mentioned variables, this study surveyed 447 people who were currently using or would use the smart home services, and then tested the hypotheses for 436 valid responses. The results of hypotheses testing showed that reliability, context awareness, and security have a significant effect on perceived usefulness and on perceived ease of use. However, it was found that ubiquitous connectivity significantly affected perceived usefulness but did not affect perceived ease of use. And perceived ease of use, perceived usefulness and subjective norm had significant effect on the intention to use smart home services. Also, user innovativeness as moderating variable was found to significantly influence on the magnitude of the relationship between ubiquitous connectivity and perceived usefulness and on that between reliability and perceived ease of use. This can be interpreted as the findings implying that innovative smart home-service users are likely to feel the smart home-services more useful than ordinary users when the degree of ubiquitous connectivity is higher, and are likely to perceive the use of smart home-services to be easier than ordinary ones when the degree of reliability is higher.

• Management & Information Systems Review
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• v.28 no.2
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• pp.69-94
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• 2009

As the internet environment develops, internet has already been being established as important tool of business marketing and branding. The goal of this study is in search for internet brand community quality characteristics, testing an effect of internet brand community quality on usage intention of community user. Data has been collected from 294 respondents during september of 2006. The questionnaire method was adopted to collect the data for this study. The research was conducted by using SPSS 12.0 and AMOS 5.0. It was found that as follows; First, Internet brand communities are characterized by system quality, service quality, and information quality which are also the traits of free contents in ordinary websites and on-line community site. Second, Traits of Internet brand community were related positively to perceived ease of use, usefulness, flow and social interaction of internet brand community user. Third, the factor that affects internet brand community usage intention was perceived ease of use, usefulness, flow, enjoyment and social interaction. Based on the results, the study offers marketing strategic implications for internet brand community site provider.

• The Korean Journal of Financial Management
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• v.22 no.1
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• pp.119-146
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• 2005

This study applies extreme value theory to get extreme value-VAR for Korean Stock market and showed the usefulness of the approach. Block maxima model and POT model were used as extreme value models and tested which model was more appropriate through back testing. It was shown that the block maxima model was unstable as the variation of the estimate was very large depending on the confidence level and the magnitude of the estimates depended largely on the block size. This shows that block maxima model was not appropriate for Korean Stock market. On the other hand POT model was relatively stable even though extreme value VAR depended on the selection of the critical value. Back test also showed VAR showed a better result than delta VAR above 97.5% confidence level. POT model performs better the higher the confidence level, which suggests that POT model is useful as a risk management tool especially for VAR estimates with a confidence level higher than 99%. This study picks up the right tail and left tail of the return distribution and estimates the EVT-VAR for each, which reflects the asymmetry of the return distribution of the Korean Stock market.

• Journal of the Korean Society of Radiology
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• v.15 no.4
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• pp.437-444
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• 2021

To evaluate the usefulness of Volume Axial Mode by comparing analyzing the exposure dose of the patients and the quality of each images from CT images obtained from high pitch mode using the local phantom or volume axial mode to determine the usefulness of he volume axial mode in diagnosing the head and cervical disease in adults. High Pitch Mode, Helical Mode, and Volume axial Mode as adult phantom were tested according to 70 kVp, 80 kVp, and 100 kVp tube voltages during an adult frontal CT scans. The equipment used was GE's Revolution (GE Healthcare, Wisconsin USA) model and iMED X-ray Phantom. The exposure dose of phantom was compared using the images obtained from each protocol, and the image quality was compared by calculating SNR and CNR by setting ROI on each image. When examined using Volume Axial Mode, the exposure dose of phantom was measured 17.12% lower than Helical Mode, 5.35% lower than High Pitch Mode, and both SNR and CNR were improved. Volume Axial Mode is a useful test that reduces investigation time without table movement using high speed rotary scanner, and in which exposure dose is reduced and image quality is improved by acquiring images in a short time of 0.28 seconds of phantom than using High Pitch Mode and Helical Mode. In addition, the fast testing time of Volume Axial Mode can be seen as the biggest advantage CT scans of emergency patients or patients with physical discomfort.

• Industry Promotion Research
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• v.8 no.1
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• pp.103-110
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• 2023

This study targeted KakaoTalk app users, mainly in Seoul and the metropolitan area, and verified the factors that had a significant impact on the intention to continuously use the app through KakaoTalk contents. Among various content characteristics, five variables were used to verify the variables that had the greatest influence on the intention to continue using, and the ones that did not. As a result of testing the five hypotheses, it was found that convenience, enjoyment, informativeness, and perceived usefulness had a significant positive(+) effect on the intention to continue using, but intimacy did not. From this, it can be determined that the majority of users use the app content because it is useful and informative, rather than because they have a sense of familiarity. In this way, the purpose of this study is to provide empirical help to factors closely related to the intention of continuous use in deriving priorities to be considered in the service planning stage as well as in terms of technical design of contents when developing mobile apps in the mobile app industry as a whole and in the field in the future. I want to provide it, but there is a meaning.

• Convergence Security Journal
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• v.24 no.2
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• pp.89-104
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• 2024

This study is an empirical study to examine the factors that influence the intention to use artificial intelligence (AI) technology for SW engineering-related tasks, and the purpose of the study is to understand the key factors that influence the use in terms of AI augmentation characteristics and interactive UI/UX characteristics. For this purpose, a survey was conducted among information and communication workers who have experience in using AI-related technologies and the collected data was analyzed. The results of the empirical analysis showed that perceived usefulness was positively influenced by the factors of expertise, interestingness, realism, aesthetics, efficiency, and flexibility, and perceived ease of use was positively influenced by the factors of expertise, interestingness, realism, aesthetics, and flexibility. Variety had no effect on both perceived ease of use and perceived usefulness. Perceived ease of use had a significant effect on perceived immersion, which positively influenced intention to use. These findings are significant in that they provide an academic understanding of the factors that influence the use of AI-enhanced tools in SW engineering-related tasks such as application design, development, testing, and process automation, as well as practical directions for the creators of tools that provide AI-enhanced development services to develop user acquisition strategies.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.25-38
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• 2019

Selecting high-quality information that meets the interests and needs of users among the overflowing contents is becoming more important as the generation continues. In the flood of information, efforts to reflect the intention of the user in the search result better are being tried, rather than recognizing the information request as a simple string. Also, large IT companies such as Google and Microsoft focus on developing knowledge-based technologies including search engines which provide users with satisfaction and convenience. Especially, the finance is one of the fields expected to have the usefulness and potential of text data analysis because it's constantly generating new information, and the earlier the information is, the more valuable it is. Automatic knowledge extraction can be effective in areas where information flow is vast, such as financial sector, and new information continues to emerge. However, there are several practical difficulties faced by automatic knowledge extraction. First, there are difficulties in making corpus from different fields with same algorithm, and it is difficult to extract good quality triple. Second, it becomes more difficult to produce labeled text data by people if the extent and scope of knowledge increases and patterns are constantly updated. Third, performance evaluation is difficult due to the characteristics of unsupervised learning. Finally, problem definition for automatic knowledge extraction is not easy because of ambiguous conceptual characteristics of knowledge. So, in order to overcome limits described above and improve the semantic performance of stock-related information searching, this study attempts to extract the knowledge entity by using neural tensor network and evaluate the performance of them. Different from other references, the purpose of this study is to extract knowledge entity which is related to individual stock items. Various but relatively simple data processing methods are applied in the presented model to solve the problems of previous researches and to enhance the effectiveness of the model. From these processes, this study has the following three significances. First, A practical and simple automatic knowledge extraction method that can be applied. Second, the possibility of performance evaluation is presented through simple problem definition. Finally, the expressiveness of the knowledge increased by generating input data on a sentence basis without complex morphological analysis. The results of the empirical analysis and objective performance evaluation method are also presented. The empirical study to confirm the usefulness of the presented model, experts' reports about individual 30 stocks which are top 30 items based on frequency of publication from May 30, 2017 to May 21, 2018 are used. the total number of reports are 5,600, and 3,074 reports, which accounts about 55% of the total, is designated as a training set, and other 45% of reports are designated as a testing set. Before constructing the model, all reports of a training set are classified by stocks, and their entities are extracted using named entity recognition tool which is the KKMA. for each stocks, top 100 entities based on appearance frequency are selected, and become vectorized using one-hot encoding. After that, by using neural tensor network, the same number of score functions as stocks are trained. Thus, if a new entity from a testing set appears, we can try to calculate the score by putting it into every single score function, and the stock of the function with the highest score is predicted as the related item with the entity. To evaluate presented models, we confirm prediction power and determining whether the score functions are well constructed by calculating hit ratio for all reports of testing set. As a result of the empirical study, the presented model shows 69.3% hit accuracy for testing set which consists of 2,526 reports. this hit ratio is meaningfully high despite of some constraints for conducting research. Looking at the prediction performance of the model for each stocks, only 3 stocks, which are LG ELECTRONICS, KiaMtr, and Mando, show extremely low performance than average. this result maybe due to the interference effect with other similar items and generation of new knowledge. In this paper, we propose a methodology to find out key entities or their combinations which are necessary to search related information in accordance with the user's investment intention. Graph data is generated by using only the named entity recognition tool and applied to the neural tensor network without learning corpus or word vectors for the field. From the empirical test, we confirm the effectiveness of the presented model as described above. However, there also exist some limits and things to complement. Representatively, the phenomenon that the model performance is especially bad for only some stocks shows the need for further researches. Finally, through the empirical study, we confirmed that the learning method presented in this study can be used for the purpose of matching the new text information semantically with the related stocks.

• Journal of the Korean Society for Nondestructive Testing
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• v.15 no.4
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• pp.549-560
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• 1996

The purpose of this study is to investigate the usefulness of small punch(SP) test using miniaturized specimens as a method for fracture strength evaluation of CANDU pressure tube embrittled by hydrogen. According to the test results, the fracture strength evaluation as a function of hydrogen concentration at $-196^{\circ}C$ was much better than that at room temperature, as the difference of SP fracture energy(Esp) with hydrogen concentration was more significant at $-196^{\circ}C$ than at room temperature for the hydrogen concentration up to 300ppm-H. It was also observed that the peak of average AE energy, the cumulative average AE energy and the cumulative average AE energy per equivalent fracture, strain increased with the increase of hydrogen concentration. From the results of load-displacement behaviors, Esp behaviors, macro- and micro-SEM fractographs and AE test it has been concluded that the SP test method using miniaturized specimen($10mm{\times}10mm{\times}0.5mm$) will be a useful test method to evaluate the fracture strength for CANDU pressure tube embrittled by hydrogen.

• Journal of the Korea Institute of Building Construction
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• v.11 no.3
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• pp.229-237
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• 2011

The pullout test is a nondestructive testing method certified by the American Society for Testing and Materials (ASTM) and British Standards (BS). Research has shown that it is very reliable in terms of evaluating the concrete strength of reinforced concrete members. However, the pullout test is rarely performed on domestic construction sites due to the complex procedures and high costs involved. This study proposes a new pullout test composed of a post installable break-off bolt, an insert nut, and a pullout tester, which satisfy both economical and practical purposes on a construction site. Three different types of special fastening methods, a temporary fixed bolt, a plastic fixed panel, and a fixed bar, have been developed. A pullout tester is proposed that is driven by the circle force introduced into a handle composed of eight gears without a load cell and a hydraulic cylinder. The serviceability and reliability of these instruments were investigated through experiments at construction sites. Furthermore, the sample pullout test with a wall specimen was conducted to estimate the usefulness of the temporary fixed bolt type of fastening methods and pullout devices. Eventually, the developed instruments will be useful on construction sites if minor requirements are met.