• Journal of the Korea Computer Graphics Society
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• v.28 no.3
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• pp.79-89
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• 2022

With the popularity and the advanced graphics hardware technology of mobile devices, various mobile applications that help children with physical activities have been studied. This paper presents SandUp, a mobile application that guides the play of building sand castles using artificial intelligence and augmented reality(AR) technology. In the process of building the sandcastle, children can interactively explore the target virtual sandcastle through the smartphone display using AR technology. In addition, to help children complete the sandcastle, SandUp informs the sand shape and task required step by step and provides visual and auditory feedback while recognizing progress in real-time using the phone's camera and deep learning classification. We prototyped our SandUp app using Flutter and TensorFlow Lite. To evaluate the usability and effectiveness of the proposed SandUp, we conducted a questionnaire survey on 50 adults and a user study on 20 children aged 4~7 years. The survey results showed that SandUp effectively helps build the sandcastle with proper interactive guidance. Based on the results from the user study on children and feedback from their parents, we also derived usability issues that can be further improved and suggested future research directions.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.284-298
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• 2022

It is necessary to acquire information on traffic safety facilities installed on the roadways specifically for the operation of autonomous vehicles. The purpose of this study is to prepare a Korean version of an integrated message-set design as a way to provide to autonomous vehicles standardized information on traffic safety facilities. In this study, necessary facilities are classified according to four criteria (no legal basis; not providing information to autonomous vehicles; providing duplicate information; not standardized, and too difficult to generalize) based on information that must be provided to operate autonomous vehicles. The priority of information delivery (gross negligence followed by behavior change) was classified according to the importance of the information to be provided during autonomous driving, and the form was defined for the classification code in the information delivered. Finally, the information location and delivery method of traffic facilities for compliance with SAE J2735 were identified. This study is meaningful in that it provides a plan for roadway operations by suggesting a method for providing information to autonomously driven vehicles.

• Journal of the Korean Geotechnical Society
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• v.25 no.1
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• pp.5-19
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• 2009

Most of earthquake-induced geotechnical hazards have been caused by the site effects relating to the amplification of ground motion, which is strongly influenced by the local geologic conditions such as soil thickness or bedrock depth and soil stiffness. In this study, an integrated GIS-based information system for geotechnical data, called geotechnical information system (GTIS), was constructed to establish a regional counterplan against earthquake-induced hazards at an urban area of Daejeon, which is represented as a hub of research and development in Korea. To build the GTIS for the area concerned, pre-existing geotechnical data collections were performed across the extended area including the study area and site visits were additionally carried out to acquire surface geo-knowledge data. For practical application of the GTIS used to estimate the site effects at the area concerned, seismic zoning map of the site period was created and presented as regional synthetic strategy for earthquake-induced hazards prediction. In addition, seismic zonation for site classification according to the spatial distribution of the site period was also performed to determine the site amplification coefficients for seismic design and seismic performance evaluation at any site in the study area. Based on this case study on seismic zonations in Daejeon, it was verified that the GIS-based GTIS was very useful for the regional prediction of seismic hazards and also the decision support for seismic hazard mitigation.

• Journal of the Korean Geotechnical Society
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• v.24 no.5
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• pp.65-78
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• 2008

In case of cut-slopes or shallow-depth tunnels, sliding along with discontinuities or rotation could play a critical role in judging stability. Although numerical analysis is widely used to check the stability of these cut-slopes and shallow-depth tunnels in early design process, common analysis programs are based on continuum model. Performing continuum model analysis regarding discontinuities is possible by reducing overall strength of jointed rock mass. It is also possible by applying ubiquitous joint model to Mohr-Coulomb failure criteria. In numerical analysis of cut-slope, main geotechnical properties such as cohesion, friction angle and elastic modulus can be evaluated by empirical equations. This study tried to compare two main systems, RMR and GSI system by applying them to in-situ hazardous cut-slopes. In addition, this study applied ubiquitous joint model to simulation model with inputs derived by RMR and GSI system to compare with displacements obtained by in-situ monitoring. To sum up, numerical analysis mixed with GSI inputs and ubiquitous joint model proved to provide most reliable results which were similar to actual displacements and their patterns.

• Journal of the Korean Regional Science Association
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• v.39 no.2
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• pp.47-61
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• 2023

Satisfaction on the residential environment is a major factor influencing the choice of residence and migration, and is directly related to the quality of life in the city. As online services of real estate increases, people's evaluation on the residential environment can be easily checked and it is possible to analyze their satisfaction and its determining factors based on their evaluation. This means that a larger amount of evaluation can be used more efficiently than previously used methods such as surveys. This study analyzed the residential environment reviews of about 30,000 apartment residents collected from 'Zigbang', an online real estate service in Seoul. The apartment review of Zigbang consists of an evaluation grade on a 5-point scale and the evaluation content directly described by the dweller. At first, this study labeled apartment reviews as positive and negative based on the scores of recommended reviews that include comprehensive evaluation about apartment. Next, to classify them automatically, developed a model by using Bidirectional Encoder Representations from Transformers(BERT), a deep learning-based natural language processing model. After that, by using SHapley Additive exPlanation(SHAP), extract word tokens that play an important role in the classification of reviews, to derive determining factors of the evaluation of the residential environment. Furthermore, by analyzing related keywords using Word2Vec, priority considerations for improving satisfaction on the residential environment were suggested. This study is meaningful that suggested a model that automatically classifies satisfaction on the residential environment into positive and negative by using apartment review big data and deep learning, which are qualitative evaluation data of residents, so that it's determining factors were derived. The result of analysis can be used as elementary data for improving the satisfaction on the residential environment, and can be used in the future evaluation of the residential environment near the apartment complex, and the design and evaluation of new complexes and infrastructure.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.217-242
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• 2022

With the launch of Artificial Intelligence(AI)-based intelligent products on the market, innovative changes are taking place not only in business but also in consumers' daily lives. Intelligent products have the potential to realize technology differentiation and increase market competitiveness through advanced functions of artificial intelligence. However, there is no new product development methodology that can sufficiently reflect the characteristics of artificial intelligence for the purpose of developing intelligent products with high market acceptance. This study proposes a KANO-QFD integrated model as a methodology for intelligent product development. As a specific example of the empirical analysis, the types of consumer requirements for hair loss prediction and treatment device were classified, and the relative importance and priority of engineering characteristics were derived to suggest the direction of intelligent medical product development. As a result of a survey of 130 consumers, accurate prediction of future hair loss progress, future hair loss and improved future after treatment realized and viewed on a smartphone, sophisticated design, and treatment using laser and LED combined light energy were realized as attractive quality factors among the KANO categories. As a result of the analysis based on House of Quality of QFD, learning data for hair loss diagnosis and prediction, micro camera resolution for scalp scan, hair loss type classification model, customized personal account management, and hair loss progress diagnosis model were derived. This study is significant in that it presented directions for the development of artificial intelligence-based intelligent medical product that were not previously preceded.

• Journal of The Korean Association For Science Education
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• v.43 no.3
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• pp.237-251
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• 2023

This study explores the possibility of automated scoring for scientific graph answers by designing an automated scoring model using convolutional neural networks and applying it to students' kinematics graph answers. The researchers prepared 2,200 answers, which were divided into 2,000 training data and 200 validation data. Additionally, 202 student answers were divided into 100 training data and 102 test data. First, in the process of designing an automated scoring model and validating its performance, the automated scoring model was optimized for graph image classification using the answer dataset prepared by the researchers. Next, the automated scoring model was trained using various types of training datasets, and it was used to score the student test dataset. The performance of the automated scoring model has been improved as the amount of training data increased in amount and diversity. Finally, compared to human scoring, the accuracy was 97.06%, the kappa coefficient was 0.957, and the weighted kappa coefficient was 0.968. On the other hand, in the case of answer types that were not included in the training data, the s coring was almos t identical among human s corers however, the automated scoring model performed inaccurately.

• Industry Promotion Research
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• v.8 no.1
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• pp.83-94
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• 2023

This study explored the effect of corporate field teacher and corporate education satisfaction on apprenticeship education satisfaction and student job competency development focusing on NCS job standards and industry-academia-integrated apprenticeship school project group. As a result of the study, satisfaction with corporate field teachers in the electrical, electronic, and food service sectors was found to have a positive influence on improving students' job competency, while satisfaction with corporate education was important in the management, accounting, office, and information and communication sectors. In the analysis by type of project group, the satisfaction of corporate field teachers in the joint practice type and industry-led type had a strong influence on improving job competency, but in the base school type and single school type, corporate education satisfaction had a greater influence on capacity improvement. Therefore, it is necessary to redefine the competencies of corporate field teachers and to establish and implement an industry-academic integrated apprenticeship school operation plan with the relationship between the type of project group and NCS job standard classification.

• Journal of Environmental Health Sciences
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• v.49 no.3
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• pp.134-148
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• 2023

Background: The conducting of health effect surveys (HESs) in environmentally contaminated vulnerable areas (ECVAs) by the central and local governments has been increasing apace with the increase in demand for HESs since the Environmental Health Act was enacted in South Korea in 2008. Objectives: This study aimed to review the HESs of residents in ECVAs conducted in South Korea. Methods: An analysis was performed on 125 reports obtained from the Environment Digital Library, PRISM, and local government websites after selecting from 803 projects obtained as ECVAs from the Korea ON-Line E-Procurement System (1997~2021), National Institute Environment Research (2000~2021), and Korea Environmental Industry and Technology Institute (2009~2021). The reports were classified by background (residents' demand, HES, and more), research design (cross-sectional study, cohort, ecological study, and panel), pollution source (abandoned metal mine (AMM), industrial complex (IC), and more), and assessment method of exposure and health effects. The survey area was converted into administrative district codes for geographical mapping. Results: There were 37, 34, 18, and 10 cases associated with AMM, IC, waste incinerators, and coal-fired power plants, respectively. Most of the studies conducted were cross-sectional studies and ecological studies. The proportion of epidemiological investigations by residents' demand showed an increase from 0.0% to 8.9% for the central government while decreasing from 16.7% to 14.3% for local governments after 2008 compared to before 2008. HESs increased at both the central and local government levels since 2014. For the evaluation method, 365 environmental hazards, 319 health outcomes, and 302 biological markers were investigated, with the most commonly investigated items being metals, cancer, and blood metals. Conclusions: HESs of residents in ECVAs in South Korea have been continuously developed both quantitatively and qualitatively. Future improvements are expected, and systematic review and classification of the HESs is warranted.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.1C
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• pp.65-76
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• 2010

Recent earthquake events revealed that severe seismic damages were concentrated mostly at sites composed of soil sediments rather than firm rock. This indicates that the site effects inducing the amplification of earthquake ground motion are associated mainly with the spatial distribution and dynamic properties of the soils overlying bedrock. In this study, an integrated GIS-based information system for geotechnical data was constructed to establish a regional counterplan against ground motions at a representative metropolitan area, Seoul, in Korea. To implement the GIS-based geotechnical information system for the Seoul area, existing geotechnical investigation data were collected in and around the study area and additionally a walkover site survey was carried out to acquire surface geo-knowledge data. For practical application of the geotechnical information system used to estimate the site effects at the area of interest, seismic zoning maps of geotechnical earthquake engineering parameters, such as the depth to bedrock and the site period, were created and presented as regional synthetic strategy for earthquake-induced hazards prediction. In addition, seismic zonation of site classification was also performed to determine the site amplification coefficients for seismic design at any site and administrative sub-unit in the Seoul area. Based on the case study on seismic zonations for Seoul, it was verified that the GIS-based geotechnical information system was very useful for the regional prediction of seismic hazards and also the decision support for seismic hazard mitigation particularly at the metropolitan area.