• Education of Primary School Mathematics
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• v.27 no.3
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• pp.199-226
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• 2024

In response to the era of transformation necessitating the introduction of Artificial Intelligence (AI) and digital technologies, educational innovation is undertaken with the implementation of AI digital textbooks in Mathematics, English, and Information subjects by 2025 in Korea. Within this context, this study analyzed the perceptions and needs of elementary school teachers regarding mathematics AI digital textbook. Based on a survey conducted in November 2023, involving 132 elementary school teachers across the country, the analysis revealed that the majority of elementary school teachers had a low perception of the introduction and need for mathematics AI digital textbooks. However, some recognized the potential for personalized learning and effective teaching support. Furthermore, among the core technologies of the AI digital textbook, teachers highly valued the necessity of learning diagnostics and teacher reconfiguration functions and had the most positive perception of their usefulness in math lessons, while their perception of interactivity was relatively low. These findings suggest the need for changing teachers' perceptions through professional development and information provision to ensure the successful adoption and use of mathematics AI digital textbooks. Specifically, providing concrete and practical ways to use the AI digital textbook, exploring alternatives to digital overload, and continuing development and research on core technologies.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.4
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• pp.10-27
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• 2014

HAZUS-MH is a GIS-based computer program that estimates potential losses from multi-hazard phenomena: earthquakes, floods and hurricanes. With respect to seismic disaster, characteristics of a hypothetical or actual earthquake are entered into HAZUS. Then HAZUS estimates the intensity of ground shaking and calculates the correspondent losses. In this study, HAZUS was used as a part of the preparations of the future seismic events at a coastal plant facility area. To reliably characterize the target facility area, many geotechnical characteristics data were synthesized from the existing site investigation reports. And the buildings and facilities were sorted by analyzing their material and structural characteristics. In particular, the study area was divided into 17 blocks taking into account the situation of both land development and facility distribution. The ground conditions of blocks were categorized according to the site classification scheme for earthquake-resistant design. Moreover, seismic fragility curves of a main facilities were derived based on the numerical modeling and were incorporated into the database in HAZUS. The results estimated in the study area using HAZUS showed various seismic damage and loss potentials depending on site conditions and structural categories. This case study verified the usefulness of the HAZUS for estimating earthquake losses in coastal facility areas.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.71-82
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• 2022

In order to replace the sampling tensile test of products produced in the tab welding process, which is one of the automotive battery manufacturing processes, vision inspectors are currently being developed and used. However, the vision inspection has the problem of inspection position error and the cost of improving it. In order to solve these problems, there are recent cases of applying deep learning technology. As one such case, this paper tries to examine the usefulness of applying Faster R-CNN, one of the deep learning technologies, to existing product inspection. The images acquired through the existing vision inspection machine are used as training data and trained using the Faster R-CNN ResNet101 V1 1024x1024 model. The results of the conventional vision test and Faster R-CNN test are compared and analyzed based on the test standards of 0% non-detection and 10% over-detection. The non-detection rate is 34.5% in the conventional vision test and 0% in the Faster R-CNN test. The over-detection rate is 100% in the conventional vision test and 6.9% in Faster R-CNN. From these results, it is confirmed that deep learning technology is very useful for detecting welding error of lead tabs in automobile batteries.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.411-422
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• 2022

The purpose of this study was to identify factors that affect the characteristics and intentions of the elderly to use digital wealth management services. The subjects of this study were 312 elderly people over 50 years old. Based on the Value-based Adoption Model(VAM), the research model added price value, social influence, and perceived risk as research variables. As a result of empirical analysis, it was found that usefulness, enjoyment, price value, and social influence all had a significant positive (+) effect on perceived value. It was found that technicality had a significant negative (-) effect. On the other hand, no significant effect relationship was tested on perceived risk. The perceived value had a significant positive (+) effect on the intention to use. This study was meaningful in the academic research that it applied a research model that reflected the characteristics of the elderly who were not treated as mainstream in the technology acceptance model for digital wealth management services. In addition, it provided practical implications for providers' marketing strategies and government/public institution policy establishment to increase the use of digital wealth management services for the elderly.

• Information Systems Review
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• v.12 no.1
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• pp.209-227
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• 2010

One type of innovative multimedia platform environments is mobile data services (MDS), exemplified by Nate, Show, and OZ. In the context of MDS, enhancing user's continuance intention is a significant challenge to the continuing growth and long-term viability of MDS. Because the cost of using MDS is borne mainly by users, they are likely to evaluate it based on perceptions of what is received and what is given. This study identifies perceived usefulness and perceived enjoyment as the 'get'components, and perceived fee and perceived anxiety as the 'give' components. To understand the role of get and give components in the MDS post-adoption environment, this study incorporates these components into expectation confirmation model. We collected data from 204 users who had direct experiences with MDS within recent 3 months. The data was analyzed by employing PLS (partial least squares). Theoretical and practical implications of our findings are discussed.

• Information Systems Review
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• v.8 no.1
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• pp.63-80
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• 2006

This paper suggests a normative performance measurement model for B2B e-marketplace. The model is for the neutral and systematic sourcing B2B e-marketplace. It is based on BSC that is very powerful and sound tool among all the available performance measurement systems. In addition, we used AHP to make the model more structured and to draw weights of performance measures from experts. We derived main features and factors affecting performance of e-business companies and especially of B2B e-marketplaces based on literature. In order to make the model usefulness, we co-worked with some experts who are engaged in real Korean B2B e-marketplaces. They included venture capitalists, top managers of B2B e-marketplaces, and consultants. By their assistances, we could find important evaluating factors and define the hierarchical structure. After defining the hierarchical structure, the expert group decided weights of performance indicators through the designed questionnaires. The weight for each measure was calculated using geometric mean of the questionnaire response. We made the case studies of two real Korean B2B e-marketplaces to apply the suggested model with some adjustments. The results of the case studies were so satisfactory that the suggested performance measurement model for B2B e-marketplace is useful and applicable to the real world.

• The Korean Journal of Applied Statistics
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• v.28 no.6
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• pp.1275-1288
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• 2015

A microscale weather analysis module (about 1km or less) is a microscale numerical weather prediction model designed for operational forecasting and atmospheric research needs such as radiant energy, thermal energy, and humidity. The accuracy of the module is directly related to the usefulness and quality of real-time microscale weather information service in the metropolitan area. This paper suggests an object based verification method useful for spatio-temporal evaluation of the accuracy of the microscale weather analysis module. The method is a graphical method comprised of three steps that constructs a lattice field of evaluation statistics, merges and identifies objects, and evaluates the accuracy of the module. We develop lattice fields using various evaluation spatio-temporal statistics as well as an efficient object identification algorithm that conducts convolution, masking, and merging operations to the lattice fields. A real data application demonstrates the utility of the verification method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.4
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• pp.1652-1662
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• 2013

As smart devices like smartphones and smart pads are prevalent recently, dramatic changes so called 'smart evolution' deployed in many socioeconomic areas. These changes lead the TV industry to develop a smart TV differentiated from a conventional TV by enabling internet connectivity and applications execution. In this study the factors affecting the acceptance of a smart TV are extracted by reviewing the previous works and the structural relationships among these factors are analyzed. Adding 'Social Influence' to consider an environmental factor and 'Innovativeness' for personal characteristics, we build an extended Technology Acceptance Model and analyzed the structural relationships among the factors in the model using Structural Equation Model. In the results we can find that the environmental factors affect the perceived characteristics. The moderating effects of gender and level of experience in smart devices have also been investigated. No difference is found between gender groups. In much-experienced group, Innovativeness affects Perceived Usefulness and acceptance of a smart TV. In less-experienced group, however, Innovativeness affects Perceived Ease of Use, Expected Enjoyment and finally acceptance of a smart TV.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.507-520
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• 2003

In this paper, an automatic construction method of theme melody index for large music database and an associative content-based music retrieval mechanism in which the constructed theme melody index is mainly used to improve the users' response time are proposed. First, the system automatically extracted the theme melody from a music file by the graphical clustering algorithm based on the similarities between motifs of the music. To place an extracted theme melody into the metric space of M-tree, we chose the average length variation and the average pitch variation of the theme melody as the major features. Moreover, we added the pitch signature and length signature which summarize the pitch variation pattern and the length variation pattern of a theme melody, respectively, to increase the precision of retrieval results. We also proposed the associative content-based music retrieval mechanism in which the k-nearest neighborhood searching and the range searching algorithms of M-tree are used to select the similar melodies to user's query melody from the theme melody index. To improve the users' satisfaction, the proposed retrieval mechanism includes ranking and user's relevance feedback functions. Also, we implemented the proposed mechanisms as the essential components of content-based music retrieval systems to verify the usefulness.

• Journal of the Korea Society of Computer and Information
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• v.18 no.11
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• pp.255-264
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• 2013

This research was conducted to analyze parents' attitudes on the issues related to the Smart Education Initiative Korea. The questions included the usefulness of major digital tools for educational purposes, knowledge on the Smart Education, necessity for better educational methods, and Bring Your Own Devices (BYOD) policy. A total of 432 response cases from the parents were analyzed considering the parents' age, academic level, and income. As a result, parents regarded desktop PCs as more effective tools for learning when compared to tablet PCs. Meanwhile, mobile devices and SNSs were hardly considered as instructional tools. Second, familarity and understanding of the Smart Education were proportional to household income and mothers' education levels. Third, parents needed for the change in educational methods and agreed with the importance of students' self-regulated learning, collaboration, inquiry ability and creativity. Fourth, regarding BYOD, parents were willing to buy devices with a reasonable price. In conclusion, it is required to reflect the results of the study when implementing the Smart Education throughout the nation.