• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.19 no.2
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• pp.8-19
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• 2023

Hydronic heated road pavement (HHP) systems have well studied and documented by many researchers. However, most of the systems run on asphalt, only a few are tested with concrete, and there rarely is a comparison between those two common road materials in their heating and cooling performance. The aim of this study is to investigate the thermal performance of the HHP, such as heat dissipation performance in winter season while focusing on the surface temperature of the concrete and asphalt pavement. For preliminary study a small-scale experimental system was designed and installed to evaluate the heat transfer characteristics of the HHP in the test field. The system consists of concrete and asphalt slabs made of 1 m in width, 1 m in length, and 0.25 m in height. In two slabs, circulating water piping was embedded at a depth of 0.12 m at intervals of 0.16 m. Heating performance in winter season was tested with different inlet temperatures of 25℃, 30℃, 35℃ and 40℃ during the entire measurement period. The results indicated that concrete's heating performance is better than that of asphalt, showing higher surface temperatures for the whole experiment cases. However, the surface temperature of both concrete and asphalt pavement slabs remained above 0℃ for all experimental conditions. The heat dissipation performance of concrete and asphalt pavements was analyzed, and the heat dissipation of concrete pavement was greater than that of asphalt. In addition, the higher the set temperature of the circulating water, the higher the heat dissipation. On the other hand, the concrete pavement clearly showed a decrease in heat dissipation as the circulating water set temperature decreased, but the decrease was relatively small for the asphalt pavement. Based on this experiment, it is considered that a circulating water temperature of 20℃ or less is sufficient to prevent road ice. However, this needs to be verified by further experiments or computational fluid dynamic (CFD) analysis.

• Journal of The Korean Association For Science Education
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• v.43 no.4
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• pp.351-368
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• 2023

The scientist-led Research and Education (R&E) program aims to strengthen gifted science students' research capabilities under the guidance of scientists. Students' actual research experiences in scientist-led R&E activities range from understanding how scientists conduct research to actively participating in research. To develop R&E that promotes student agency, i.e., student participation, this study aimed to identify the pedagogical characteristics that supported gifted science students' agentic participation in the scientist-led R&E program. We conducted interviews with learners and scientists in three teams undertaking R&E activities every three months. The interview covered their perceptions of R&E activities, student participation, and scientists' support for the activities. The recordings and transcripts of the interviews were used as primary data sources for the analysis. The trajectory of each team's activities, as well as the learners' and scientists' dynamic positioning were identified. Based on this analysis, we inductively identified the pedagogical characteristics that emerged from classes in which the scientists supported the students' learning and engagement in research. Regarding agency, three types of student participation were identified: 1) the sustained exercise of agency, 2) the initial exercise and subsequent discouragement of agency, and 3) the continuous non-exercise of agency. Two pedagogical characteristics that supported the learners' agentic participation were identified: 1) opportunities for students to take part in research management and 2) scientist-student interactions encouraging learners to present expert-level ideas. This study contributes to developing pedagogies that foster gifted science students' agentic participation in scientist-led R&E activities.

• Analytical Science and Technology
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• v.19 no.1
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• pp.107-114
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• 2006

Early diagnosis and medical intervention are critical for the treatment of patients with metabolic disorders. A rapid analytical method was developed for simultaneous quantification of organic acids and amino acids in urine without labor-intensive pre-extraction procedure showing high sensitivity and specificity. A new method consisted of simple two-step trimethylsilyl (TMS)-trifluoroacetyl (TFA) derivatization using GC/MS-selective ion monitoring (SIM). Filter paper urine specimens were dried under nitrogen after being fortified with internal standard (tropate) in a mixture of distilled water and methanol. Methyl orange was added to the residue as indicator reagent. Silyl derivative of carboxylic functional group was followed by trifluoroacetyl derivative for amino functional group. N-methyl-N-(trimethylsilyl-trifluoroacetamide) and N-methyl-bistrifluoroacetamide were consecutively added and heated for 15-20 min at $65^{\circ}C-70^{\circ}C$, for TMS-TFA derivative, respectively. This reactant was analyzed by GC/MS-SIM. Linear dynamic range showed 0.001-50 mg with the detection limit of (S/N=3) 10-200 ng, and the quantification limit of 80-900 ng in urine. Correlation coefficient of regression line was 0.994-0.998. When the method was applied to the patients 'urine, it clearly differentiated the normal from the patient with metabolic disorder. The study showed that the developed method could be the method of choices in rapid and sensitive screening for organic aciduria and amino acidopathy.

• Korean Journal of Culture and Social Issue
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• v.24 no.1
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• pp.1-27
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• 2018

The purpose of this study was to identify the persistent and dynamic association between bullying and victimization. Gender differences in patterns of school bullying was hypothesized based on the literature. Analysis were based on waves 3-6 of the Korea Children and Youth Panel Survey, a nationally representative data of primary and secondary school students in South Korea (N = 1,881). Autoregressive cross-lagged model was employed to identify the reciprocal association between bullying and victimization in longitudinal data. As hypothesized, regardless of gender, lagged effects were statistically significant between each time points such that current bullying caused future bullying and current victimization led to future victimization. However, there was no cross-lagged effects of current victimization on future bullying nor current perpetration on future victimization for both male and female youth. Findings from this study may have implications for designing policies against school bulling. Not only is short-term intervention for handling immediate psycho-social maladjustment important, but so are long-term plans that prevent youth from falling into continued perpetration and victimization in the system of school bullying.

• Journal of Korea Port Economic Association
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• v.39 no.2
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• pp.129-141
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• 2023

This study analyzes the dynamic characteristics of daily freight rates of dry bulk and tanker shipping markets and their forecasting accuracy by using the error correction models. In order to calculate the error terms from the co-integrated time series, this study uses the common stochastic trend model (CSTM model) and vector error correction model (VECM model). First, the error correction model using the error term from the CSTM model yields more appropriate results of adjustment speed coefficient than one using the error term from the VECM model. Furthermore, according to the adjusted determination coefficients (adjR²), the error correction model of CSTM-model error term shows more model fitness than that of VECM-model error term. Second, according to the criteria of mean absolute error (MAE) and mean absolute scaled error (MASE) which measure the forecasting accuracy, the results show that the error correction model with CSTM-model error term produces more accurate forecasts than that of VECM-model error term in the 12 cases among the total 15 cases. This study proposes the analysis and forecast tasks 1) using both of the CSTM-model and VECM-model error terms at the same time and 2) incorporating additional data of commodity and energy markets, and 3) differentiating the adjustment speed coefficients based the sign of the error term as the future research topics.

• Journal of Environmental Impact Assessment
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• v.32 no.5
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• pp.318-337
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• 2023

This study utilizes system dynamics to examine the effects of fine dust reduction policies on PM10 concentration and health. System dynamics has the advantage of modeling the dynamic and circular relationship between PM₁₀ emission sources, reduction policies, PM₁₀ concentration, and health effect. The study created policy scenarios for Korea's representative fine dust reduction policies - industrial PM₁₀ emission control, diesel vehicle regulation, expansion of electric vehicles, and expansion of parks and green areas - and compared the results with the 2030 baseline if the current trend is maintained. The analysis showed that the policy of supporting electric vehicles reduced PM₁₀ concentration by 0.21 ㎍/m³ and reduced the number of people with circulatory diseases by 494, and the effect was evenly distributed across the country. The industrial emissions regulation scenario resulted in the highest PM₁₀ concentration reduction of 0.22 ㎍/m³, but had a lower reduction in the number of people affected (358) than the EV support strategy, which could be attributed to the fact that this policy had a particularly high PM₁₀ reduction effect in industrial areas such as Danyang-gun, Chungcheongbuk-do, and Sahagu, Busan. As a policy implication, this study suggests that it is necessary to apply fine dust policies tailored to the characteristics of local emission sources.

• KIPS Transactions on Software and Data Engineering
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• v.13 no.1
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• pp.35-49
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• 2024

Video captioning technology, as a significant outcome of the integration between computer vision and natural language processing, has emerged as a key research direction in the field of artificial intelligence. This technology aims to achieve automatic understanding and language expression of video content, enabling computers to transform visual information in videos into textual form. This paper provides an initial analysis of the research trends in deep learning-based video captioning and categorizes them into four main groups: CNN-RNN-based Model, RNN-RNN-based Model, Multimodal-based Model, and Transformer-based Model, and explain the concept of each video captioning model. The features, pros and cons were discussed. This paper lists commonly used datasets and performance evaluation methods in the video captioning field. The dataset encompasses diverse domains and scenarios, offering extensive resources for the training and validation of video captioning models. The model performance evaluation method mentions major evaluation indicators and provides practical references for researchers to evaluate model performance from various angles. Finally, as future research tasks for video captioning, there are major challenges that need to be continuously improved, such as maintaining temporal consistency and accurate description of dynamic scenes, which increase the complexity in real-world applications, and new tasks that need to be studied are presented such as temporal relationship modeling and multimodal data integration.

• International Journal of Computer Science & Network Security
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• v.24 no.7
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• pp.157-169
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• 2024

The article presents an analysis of innovative teaching technologies as a way to increase students' competitiveness. The author found that innovative technologies in education are information and communication technologies relying on computer-based learning. The structure, content of educational software, organization of Web-space are important when using innovative teaching technologies in English classes. We conducted the study in several stages: comparative analysis, synthesis, classification and systematization of the results of psychological and pedagogical, educational and methodological research; study of legislative acts, periodicals in order to identify the state of the research issue, and determining the directions of its solution, as well as subject, goal and objectives of the study. We used modelling to create situations of foreign language professional communication of future IT specialists. Empirical methods involved questionnaires used for identifying the motives of professional development and determining the features of the educational activities of future IT specialists in the process of training. The methods of mathematical statistics allowed to scientifically describe and systematize the obtained data, to identify the quantitative relationship between the studied phenomena, to analyse and summarize the results. We conducted a socio-psychological study during 2016 - 2019. It involved 255 first- and fourth-year students of National Technical University of Ukraine "Igor Sikorsky Kyiv Poly-technic Institute." Innovative information and communication technologies that improve the educational and cognitive activity of students, as well as increase the level of their knowledge have become important in teaching a foreign language in higher educational institutions. These technologies include MOODLE - Modular Object-Oriented Dynamic Learning Environment, business game, integrated pedagogical technology, case study technology. Thus, the information-rich learning process in combination with the use of innovative technologies, well-organized e-learning, interactive training courses, multimedia tools improves the program of teaching and learning foreign languages in general, and English in particular, improves the level of knowledge of future IT specialists and motivation to study and learn foreign languages, allows students to use a variety of authentic materials. We state that all these factors influence the process of individualization of learning and contribute to the successful mastery of a foreign language.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.5 no.4
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• pp.267-275
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• 2000

In an effort to assess the reliability of satellite altimeter system, we conducted a comparative analysis of sea level data that were collected using the TOPEX/POSEIDON (T/P) altimeter and the 10 tide gauge (TG) stations in the satellite passing track. The analysis was made using data sets collected from marginal sea regions surrounding the Korean Peninsula at T/P cycles of 2 to 230, which correspond to October 1992 to December 1998. Because of strong tidal activity in the study area, treatment of tidal errors is a very critical step in data processing. Hence in the computation of dynamic heights from the Tn data, we adapted the procedures of Park and Gamberoni (1995) to reduce errors associated with it. When these T/P data were treated, the alias periods of M$_2$, S$_2$, and K$_1$ constitutions were found at 62.1, 58.7, and 173 days. The compatibility of the T/P and TG data sets were examined at various filtering periods. The results indicate that the low-frequency signal of Tn data can be interpreted more safely with longer filtering periods (such as up to the maximum selected values of 200 days). When RMS errors for 200-day low-pass filter period was compared among the whole 10 tidal stations, the values spanned in the range of 2.8 to 6.7 cm. The results of correlation analysis at this filtering period also showed a strong agreement between the Tn and TG data sets over the whole stations investigated (e.g., P values consistently less than 0.0001). According to our analysis, we conclude that the analysis of surface sea level using satellite altimeter data can be made safely and reasonably long filtering periods such as 200 days.

• Journal of the Korean Society of Radiology
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• v.12 no.6
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• pp.755-762
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• 2018

The purpose of this study was to compare the FA(faractional anisotropy) and ADC(apparent diffusion coefficient) values, which were derived from diffusion tensor imaging in breast cancer patients. The diffusion gradient used in this study was derived from quantitative diffusion indices using 20 directions(b-value, 0 and $1,000s/mm^2$). Quantitative analysis was analyzed using Pearson's correction and qualitative analysis using for correction coefficients. As a result, $FA_{min}$, $FA_{mean}$ and $FA_{max}$ were $0.098{\pm}0.065$, $0.302{\pm}0.142$ and $0.634{\pm}0.236$, respectively(p > 0.05). The $ADC_{min}$, $ADC_{mean}$ and $ADC_{max}$ were $0.741{\pm}0.403$, $1.095{\pm}0.394$ and $1.530{\pm}0.447$, respectively(p > 0.05). The $FA_{min}$, $FA_{mean}$, and $FA_{max}$ mean values were $0.132{\pm}0.050$, $0.418{\pm}0.094$, and $0.770{\pm}0.164$ for Category 6 and Kinetic Curve Pattern III, respectively. $ADC_{min}$, $ADC_{mean}$, and $ADC_{max}$ were $0.753{\pm}0.189$, $1.120{\pm}0.236$, and $1.615{\pm}0.372$, respectively. Quantitative analysis showed negative correlation between $ADC_{mean}-FA_{mean}$ and $ADC_{max}-FA_{max}$(p = 0.001, 0.003). The qalitative analysis showed ADC 0.628(p = 0.001), FA 0.620(p = 0.001) in the internal evaluations, ADC 0.677(p = 0.001), FA 0.695(p = 0.001) in external evaluations. In conclusion, based on the morphological examination, time to signal intensity graph is the form of wash-out(pattern III) in the dynamic contrast enhance examination, As a result, the $ADC_{mean}$ $1.120{\pm}0.236$ and $FA_{mean}$ values were $0.032{\pm}0.142$ with a negative correlation (Y=1.44-1.12X). Therefore, If we understand the shape of time to signal intensity graph and the relationship between ADC and FA, It will be a criterion for distinguishing malignant diseases in breast cancer.