• Journal of the Korean GEO-environmental Society
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• v.25 no.2
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• pp.5-14
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• 2024

Reinforced concrete bridge decks are the first to be damaged by vehicle loads and rain infiltration. Concrete deterioration primarily occurs owing to the corrosion of rebars and other metal components by chlorides used for snow and ice melting. The structural condition and concrete deterioration of the bridge decks within the pavement were evaluated using ground-penetrating radar (GPR) survey data. To evaluate concrete deterioration in bridges, it is necessary to develop GPR data analysis techniques to accurately identify deteriorated locations and rebar positions. GPR exploration involves the acquisition of reflection and diffraction wave signals due to differences in radar wave propagation velocity in geotechnical media. Therefore, a full-waveform inversion (FWI) method was developed to evaluate the deterioration of reinforced concrete bridge decks by estimating the radar wave propagation velocity in geotechnical media using GPR data. Numerical experiments using a GPR velocity model confirmed the deterioration phenomena of bridge decks, such as concrete delamination and rebar corrosion, verifying the applicability of the developed technology. Moreover, using the synthetic GPR data, FWI facilitates the determination of rebar positions and concrete deterioration locations using inverted velocity images.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.67-74
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• 2024

In this paper, we present a study aimed at analyzing how different rainfall measurement methods affect the performance of reservoir water level predictions. This work is particularly timely given the increasing emphasis on climate change and the sustainable management of water resources. To this end, we have employed rainfall data from ASOS, AWS, and Thiessen Network-based measures provided by the KMA Weather Data Service to train our neural network models for reservoir yield predictions. Our analysis, which encompasses 34 reservoirs in Jeollabuk-do Province, examines how each method contributes to enhancing prediction accuracy. The results reveal that models using rainfall data based on the Thiessen Network's area rainfall ratio yield the highest accuracy. This can be attributed to the method's accounting for precise distances between observation stations, offering a more accurate reflection of the actual rainfall across different regions. These findings underscore the importance of precise regional rainfall data in predicting reservoir yields. Additionally, the paper underscores the significance of meticulous rainfall measurement and data analysis, and discusses the prediction model's potential applications in agriculture, urban planning, and flood management.

• Journal of Biomedical Engineering Research
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• v.45 no.3
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• pp.128-137
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• 2024

It is necessary to develop a pulsatile Extracorporeal Membrane Oxygenator (p-ECMO) with counter-pulsation control(CPC), which ejects blood during the diastolic phase of the heart rather than the systolic phase, due to the known issues with conventional ECMO causing fatal complications such as ventricular dilation and pulmonary edema. A promising method to simultaneously detect the pulsations of the heart and p-ECMO is to analyze blood pressure waveforms using deep neural network technology(DNN). However, the accurate detection of cardiac rhythms by DNNs is challenging due to various noises such as pulsations from p-ECMO, reflected waves in the vessels, and other dynamic noises. This study aims to evaluate the accuracy of DNNs developed for CPC in p-ECMO, using human-like blood pressure waveforms reproduced in an in-vitro experiment. Especially, an experimental setup that reproduces reflected waves commonly observed in actual patients was developed, and the impact of these waves on DNN judgments was assessed using a multiple DNN (m-DNN) that provides accurate determinations along with a separate index for heartbeat recognition ability. In the experimental setup inducing reflected waves, it was observed that the shape of the blood pressure waveform became increasingly complex, which coincided with an increase in harmonic components, as evident from the Fast Fourier Transform results of the blood pressure wave. It was observed that the recognition score (RS) of DNNs decreased in blood pressure waveforms with significant harmonic components, separate from the frequency components caused by the heart and p-ECMO. This study demonstrated that each DNN trained on blood pressure waveforms without reflected waves showed low RS when faced with waveforms containing reflected waves. However, the accuracy of the final results from the m-DNN remained high even in the presence of reflected waves.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.32-48
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• 2023

Autonomous driving technology is shaping the future of personalized travel, encouraging personalized travel, and traffic impact could be influenced by individualized travel behavior during the transition of driving entity from human to machine. In order to evaluate traffic impact, it is necessary to estimate the total number of trips based on an understanding of individual travel characteristics. The Activity-based model(ABM), which allows for the reflection of individual travel characteristics, deals with all travel sequences of an individual. Understanding the relationship between travel and travel must be important for assessing traffic impact using ABM. However, the ABM has a limitation in the data hunger model. It is difficult to adjust in the actual demand forecasting. Therefore, we utilized a Tour-based model that can explain the relationship between travels based on household travel survey data instead. After that, vehicle registration and population data were used for correction. The result showed that, compared to the KTDB one, the traffic generation exhibited a 13% increase in total trips and approximately 9% reduction in working trips, valid within an acceptable margin of error. As a result, it can be used as a generation correction method based on Tour, which can reflect individual travel characteristics, prior to building an activity-based model to predict demand due to the introduction of autonomous vehicles in terms of road operation, which is the ultimate goal of this study.

• Communications of Mathematical Education
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• v.38 no.1
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• pp.1-26
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• 2024

As the limitations of professional development programs and individual attempts to improve teaching expertise have been reported, mathematics teachers have operated various types of teacher learning communities as alternative teacher professional programs. A teacher learning community can be considered a Community of Practice(CoP) in that it satisfies three factors of Cop, which are common purpose, mutual participation, and shared repertoire, so the 'learning' of a teacher community can be interpreted based on the theory of CoP. The purpose of this study is to investigate the process of identity development of five mathematics teachers who have been continuously involved in teacher communities. For this, the researcher collected data on the entire process of community activities through participant observation and conducted individual follow-up interviews to explore mathematics teachers' narratives and personal experiences. Results indicated that mathematics teachers experienced the development of practical knowledge related to mathematics teaching and learning, improvement of teaching practice through continuous reflection and introspection, and recognization the shared value of togethering through community immersion. Based on these experiences, implications for the effective operation of learning communities such as national support of teacher learning communities and horizontal and cooperative teacher norms were discussed, and follow-up research was proposed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.27-34
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• 2024

The direct and indirect damages caused by fires in underground utility tunnels have a great impact on society as a whole, so efforts are needed to prevent and manage them in advance. To this end, research is ongoing to prevent disasters such as fire flooding by applying digital twin technology to underground utility tunnels. A network is required to transmit the sensed signals from each sensor to the platform. In essence, it is necessary to analyze the application of wireless networks in the underground utility tunnel environments because the tunnel lacks the reception range of external wireless communication systems. Within the underground utility tunnels, electromagnetic interference caused by transmission and distribution cables, and diffuse reflection of signals from internal structures, obstacles, and metallic pipes such as water pipes can cause distortion or size reduction of wireless signals. To ensure real-time connectivity for remote surveillance and monitoring tasks through sensing, it is necessary to measure and analyze the wireless coverage in underground utility tunnels. Therefore, in order to build a wireless network environment in the underground utility tunnels. this study minimized the shaded area and measured the actual cavity environment so that there is no problem in connecting to the wireless environment inside the underground utility tunnels. We analyzed the data transmission rate, signal strength, and signal-to-noise ratio for each section of the terrain of the underground utility tunnels. The obtained results provide an appropriate wireless planning approach for installing wireless networks in underground utility tunnels.

• Journal of The Korean Association For Science Education
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• v.44 no.1
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• pp.105-117
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• 2024

The purpose of this study was to explore changes in elementary teachers' modeling pPCK (personal PCK) resulting from knowledge exchange within the realms of PCK described in the Refined Consensus Model (hereafter RCM). For this purpose, a professional learning community (hereafter PLC) was established for three elementary school teachers to facilitate knowledge exchange specifically focused on science modeling instructions. The study then analyzed the CoRe (content representations) written by the research participants twice to explore any changes in modeling pPCK (personal PCK). In addition, the discourse shared by the participants in the PLC and the data from the in-depth interviews were also analyzed using grounded theory research methods. The results of the study showed that there was no significant change in knowledge of the science curriculum in elementary teachers' modeling pPCK, but there were changes in orientations toward teaching science, knowledge of students' understanding in science, knowledge of instructional strategies and representations, and knowledge of assessment of science learning. Furthermore, the analysis of PLC discourse and in-depth interviews showed that modeling instructions reflection (ePCK; enacted PCK) and educational research-based modeling cPCK (collective PCK) influenced these changes in teachers' modeling pPCK. Accordingly, this study suggests recommendations for pedagogical approaches aimed at improving teachers' modeling PCK.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.539-549
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• 2024

This study employed text mining techniques like frequency analysis, word clouds, and LDA topic modeling to assess consumer satisfaction and dissatisfaction with Hyundai Motor Company in the Chinese market, compared to brands such as Toyota, Volkswagen, Buick, and Geely. Focusing on compact vehicles from these brands between 2021 and 2023, this study analyzed customer reviews. The results indicated Hyundai Avante's positive factors, including a long wheelbase. However, it also highlighted dissatisfaction aspects like Manipulate, engine performance, trunk space, chassis and suspension, safety features, quantity and brand of audio speakers, music membership service, separation band, screen reflection, CarLife, and map services. Addressing these issues could significantly enhance Hyundai's competitiveness in the Chinese market. Previous studies mainly focused on literature research and surveys, which only revealed consumer perceptions limited to the variables set by the researchers. This study, through text mining and comparing various car brands, aims to gain a deeper understanding of market trends and consumer preferences, providing useful information for marketing strategies of Hyundai and other brands in the Chinese market.

• Journal of Korean Home Economics Education Association
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• v.35 no.3
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• pp.117-133
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• 2023

This study investigates the perceptions, Stages of Concern (SoC), and Levels of Use (LoU) regarding process-based assessment among Home Economics (HE) teachers to determine the necessary support for its implementation in schools. Data were gathered from a survey administered to HE teachers. The results are as follows. First, HE teachers viewed process-based assessment favorably, valuing its multifaceted evaluation approach over result-based assessment. The feedback from process-based assessments was seen as an opportunity for reflection for both educators and students. While some teachers expressed uncertainty about the optimal timing of implementation, they generally demonstrated a sound understanding of the feedback concept within the assessment process. HE teachers were predominantly concerned with their own professional expertise and the learning outcomes of their students. The majority of HE teachers have utilized process-based assessments for at least one semester. None deemed it irrelevant to their practice or showed disinterest in its adoption. Those who had yet to implement it were either in the first(introduction) or the second(preparation) stages.

• Journal of Christian Education in Korea
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• v.77
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• pp.85-105
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• 2024

The purpose of this study is to formulate the direction of Church education, taking into account the negative effects of digital technologies in the era of the Great Digital Transformation. Firstly, the study discussed comprehension of the Great Digital Transformation and negative effects of digital technologies. The term "Great Digital Transformation" signifies a fundamental shift into a world where everything that surrounds us becomes digital-based. In this era of the Great Digital Transformation, the negative effects of digital technologies are intensifying. Secondly, the study discussed the issue of education and church education during the great digital transformation period. The use of digital technologies has been widespread in schools. However, academic circles have raised concerns about the negative effects of digital technology on both the classroom environment and basic academic skills such as reading ability. Since digital education is becoming more popular, there is a fear that church education may fall behind in a rapidly changing society. In conclusion, the study proposed recommendations for reshaping Church education in the era of the Great Digital Transformation, considering the negative effects of digital technologies. The first is Christian worldview education, which is centered around the faith community. Education in the Christian worldview, learned through the interaction with various faiths within the faith community, encourages critical thinking and reflection on the risks posed by the digital age that are associated with capitalism and meritocracy. The second is Christian care, which is centered around the faith community. Christian care in the era of the Great Digital Transformation will help us to form genuine connections with discriminated, isolated, and lonely souls who suffer from negative effects of digital technologies, guiding them towards the path of salvation.