• Analytical Science and Technology
• /
• v.34 no.6
• /
• pp.241-250
• /
• 2021

Calibration curves are essential in quantitative methods and for improving the accuracy of analyte measurements in biological samples. In this study, a statistical analysis model built in the R language (The R Foundation for Statistical Computing) was used to identify a set of weighting factors and regression models based on a stepwise selection criteria. An LC-MS/MS method was used to detect the presence of urinary methamphetamine, amphetamine, and 11-nor-9-carboxy-Δ⁹ -tetrahydrocannabinol in a sample set. Weighting factors for the calibration curves were derived by calculating the heteroscedasticity of the measurements, where the presence of heteroscedasticity was determined via variance tests. The optimal regression model and weighting factor were chosen according to the sum of the absolute percentage relative error. Subsequently, the order of the regression model was calculated using a partial variance test. The proposed statistical analysis tool facilitated selection of the optimal calibration model and detection of methamphetamine, amphetamine, and 11-nor-9-carboxy-Δ⁹-tetrahydrocannabinol in urine. Thus, this study for the selection of weighting and the use of a complex regression equation may provide insights for linear and quadratic regressions in analytical and bioanalytical measurements.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.5
• /
• pp.162-170
• /
• 2021

The Smart City Living Lab is becoming important as a local innovation platform to develop urban solutions. In January 2018, the 4th industrial innovation committee, which was a direct subordinate from the president, empathized citizens' participation and their roles within the Smart City [Urban Innovation and Future Growth Engine-Creating Smart City Strategy]. This was the starting point of the living lab. The central government and local governments have been promoting various types of living labs to encourage citizens to participate. On the other hand, due to the lack of systematic concepts and theories for practicing and structuring living labs, the practice is not performed well. This study aimed to develop systematic approaches and implementation methods of the public-led Smart City Living Lab. The Full-cycle Smart City living Lab model was designed by integrating smart city living lab work processes, as suggested in the standards of the national land plan, double design diamond framework, which is a type of innovative design methodology, and design thinking process. The entire cycle Smart City living lab model requires four components to practice the living lab, such as framework, module, process, and methodologies. In the future, this model is expected to be incorporated in the Smart City Living Lab.

• Journal of Space Technology and Applications
• /
• v.1 no.2
• /
• pp.160-177
• /
• 2021

The Solar and Space Environment Division of the Korean Space Science Society investigated the use and possession of ground and satellite observations and models of solar and planetary data operated by domestic research institutes and universities. Based on the findings, we would like to introduce observational instruments, data, and models in solar and interplanetary fields in this paper to improve understanding and use of each data and explore opportunities for interdisciplinary research. The ground and satellite observations, which require a lot of investment, were mainly held by research institutes (National Meteorological Satellite Center, Polar Research Institute, Korean Space Weather, Korea Astronomy and Space Science Institute and KAIST Satellite Research Institute), and model development was overwhelmingly carried out at Kyung Hee University. In solar and interplanetary fields, we introduce Fast Imaging Solar Spectrograph (FISS), neutron monitors, and the analysis models [for the Solar Dynamics Observatory/Atmospheric Imaging Assembly (SDO/AIA) and Hinode/X-Ray Telescope (XRT) observations] in nonequilibrium ionization state as representatives. Survey on solar and interplanetary fields can be downloaded from the website of the Korean Space Science Society (http://ksss.or.kr/). The paper makes know the importance of long-term and continuous management of space science-related materials, and hopes to contribute to enhancing the status of domestic space science data by utilizing locally produced data by various personnel participating in space science research.

• Journal of the Korean Geotechnical Society
• /
• v.38 no.5
• /
• pp.35-46
• /
• 2022

The in-situ resource utilization (ISRU) for sustainable lunar surface and deep space explorations has recently gained attention. Also, research on the development of construction material preparation technology using lunar regolith is in progress. Microwave sintering technology for construction material preparation does not require a binder and is energy efficient. This study applies microwave sintering technology to KLS-1, a Korean lunar simulant. It is crucial to secure the homogeneity to produce a sintered specimen for construction material. Therefore, understanding the interactions between microwaves, cavities, and raw materials is required. Using a numerical model in terms of efficient assessment of several cases and establishment of equipment operating conditions is a very efficient approach. Therefore, this study also proposes and verifies a coupled electric-thermal numerical model through cross-validation and comparison with experimental results. The numerical model proposed in this study will be used to present an efficient method for producing construction material using microwave sintering technology.

• Journal of Digital Convergence
• /
• v.20 no.2
• /
• pp.325-338
• /
• 2022

This study was conducted to explore the acceptance behavior of undergraduate students toward telemedicine, which is temporarily allowed in the COVID-19. We applied social cognitive theory and technology acceptance model in order to reflect the convergence characteristics between medical service and digital technology of telemedicine. Based on these theoretical backgrounds, we investigated perception toward telemedicine and determinants of intention to accept telemedicine. To examine the research model and hypothesis, an online survey was conducted for college students who have not used telemedicine from September 8 to 10, 2021. A total of 184 data were collected, and multiple regression analysis was conducted using the SPSS 28.0 program. The results showed that health technology self-efficacy, usefulness and convenience benefits, social norm, and trust in telemedicine providers had positive effects on intention to accept telemedicine. This study is meaningful in that it selected undergraduate students, who are digital natives, as new targets for telemedicine, and presented the basic direction of strategies to target them.

• The Journal of the Convergence on Culture Technology
• /
• v.8 no.5
• /
• pp.279-284
• /
• 2022

As a study of the blended learning method on design education through the blended learning method, I would like to propose that more advanced learner-led customized design education is possible. Understanding in face-to-face classes and advantages in non-face-to-face classes can be supplemented in an appropriate way in remote classes. Advanced artificial intelligence and big data technology can provide personalized and subdivided learning materials and effective learning methods tailored to learners' levels and interests based on quantified data in design classes. In this paper, it was proposed to maximize the efficiency of the class by applying a method that exceeds the limitations of time and space through the proposal of the A La Carte model (A La Carte). It is a remote class that can be heard anytime, anywhere, and it is also possible to bridge the educational quality and educational gap provided to students living in underprivileged areas. As the goal of fostering creative convergence-type future talents, it is changing with a rapid technological development speed. It is necessary to adapt to the change in learning methods in line with this. An analysis of the infographic virtual space design and construction process through the A La Carte model (A La Carte) proposal was presented. Rather than simply acquiring knowledge, it is expected that knowledge can be sorted, distinguished, learned, and easily reborn with its own knowledge.

• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.8
• /
• pp.315-324
• /
• 2022

In this paper, we propose KoEPT, a Transformer-based generative model for automatic math word problems solving. A math word problem written in human language which describes everyday situations in a mathematical form. Math word problem solving requires an artificial intelligence model to understand the implied logic within the problem. Therefore, it is being studied variously across the world to improve the language understanding ability of artificial intelligence. In the case of the Korean language, studies so far have mainly attempted to solve problems by classifying them into templates, but there is a limitation in that these techniques are difficult to apply to datasets with high classification difficulty. To solve this problem, this paper used the KoEPT model which uses 'expression' tokens and pointer networks. To measure the performance of this model, the classification difficulty scores of IL, CC, and ALG514, which are existing Korean mathematical sentence problem datasets, were measured, and then the performance of KoEPT was evaluated using 5-fold cross-validation. For the Korean datasets used for evaluation, KoEPT obtained the state-of-the-art(SOTA) performance with 99.1% in CC, which is comparable to the existing SOTA performance, and 89.3% and 80.5% in IL and ALG514, respectively. In addition, as a result of evaluation, KoEPT showed a relatively improved performance for datasets with high classification difficulty. Through an ablation study, we uncovered that the use of the 'expression' tokens and pointer networks contributed to KoEPT's state of being less affected by classification difficulty while obtaining good performance.

• Journal of the Korean Geotechnical Society
• /
• v.22 no.6
• /
• pp.15-26
• /
• 2006

Although numerous investigations have been performed over the years to predict the behavior and bearing capacity of piles, the mechanisms are not yet entirely understood. The prediction of bearing capacity is a difficult task, because large numbers of factors affect the capacity and also have complex relationship one another. Therefore, it is extremely difficult to search the essential factors among many factors, which are related with ground condition, pile type, driving condition and others, and then appropriately consider complicated relationship among the searched factors. The present paper describes the application of Artificial Neural Network (ANN) in predicting the capacity including its components at the tip and along the shaft from dynamic load test of the driven piles. Firstly, the effect of each factor on the value of bearing capacity is investigated on the basis of sensitivity analysis using ANN modeling. Secondly, the authors use the design methodology composed of ANN and genetic algorithm (GA) to find optimal neural network model to predict the bearing capacity. The authors allow this methodology to find the appropriate combination of input parameters, the number of hidden units and the transfer structure among the input, the hidden and the out layers. The results of this study indicate that the neural network model serves as a reliable and simple predictive tool for the bearing capacity of driven piles.

• KIPS Transactions on Software and Data Engineering
• /
• v.12 no.7
• /
• pp.295-302
• /
• 2023

Software requirements written in natural language may have different meanings from the stakeholders' viewpoint. When designing an architecture based on quality attributes, it is necessary to accurately classify quality attribute requirements because the efficient design is possible only when appropriate architectural tactics for each quality attribute are selected. As a result, although many natural language processing models have been studied for the classification of requirements, which is a high-cost task, few topics improve classification performance with the imbalanced quality attribute datasets. In this study, we first show that the classification model can automatically classify the Korean requirement dataset through experiments. Based on these results, we explain that data augmentation through EDA(Easy Data Augmentation) techniques and undersampling strategies can improve the imbalance of quality attribute datasets, and show that they are effective in classifying requirements. The results improved by 5.24%p on F1-score, indicating that handling imbalanced data helps classify Korean requirements of classification models. Furthermore, detailed experiments of EDA illustrate operations that help improve classification performance.

• Korean Journal of Social Welfare Studies
• /
• v.41 no.3
• /
• pp.5-27
• /
• 2010

The objective of this study is to examine the dicourse of East Asian Welfare Models and its applicability to explain the development of the Korean Welfare State(regime). The Confucianist Welfare State, representing East Asian Welfare Models has limitations in explaining the current features and dynamics of east asian welfare states. Compared to the western and northern european welfare states, the Welfare State(Regime) of Korea, one of the east asian countries show the clear differences in terms of its origin, the background of formulation, the orientation of the policy and the actors. Thus, a new approach to examine the East Asian Welfare Model is needed. As a theoretical framework, the origin and the growth of the Korean Welfare State(Regime) can be understood and explained in the boundary of concept and the theoretical framework of the Authoritative Developmental State; Historically, the democratization of the 1980s and the financial crisis of the end of 1990s in Korea contributed to the growth of the welfare policies and institutions in Korea. Japan, Taiwan and other east asian counties, such as Hong Kong and Singapore have many similarities with Korea in terms of welfare policies and institutions. Comparative studies of these countries can create significant and useful results to develop a new concept and model of East Asian Welfare States. Case studies and active academic exchanges among welfare state researchers in these east asian countries are very important to develop a new concept of East Asian Welfare State Models.