• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.71-81
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• 2019

To extend the potential benefits of error, the current study examined factors that affect students' error perception in the classroom. An experimental design was used to measure relations of classroom goal structure, feedback, and social relationships on students' perception of error. A total of 316 fourth-, fifth-, and sixth-grade elementary students participated as part of their regular class curriculum. Self-reported questionnaires were administered to measure students' perception of errors and relationships with teacher and peers, and then students were manipulated by classroom goal structure and feedback. Multiple regression analysis results suggested that students' perception of learning from error was affected mostly by relationships with peers, followed by relationships with teacher and the type of feedback. Students' perception of risk taking for error was also affected by relationships with peers and teacher, followed by the classroom goal structure. However, classroom goal structure and feedback did not affect their perception of thinking about error to improve their learning as well as error strain. These results imply how the classroom climate should be structured to improve perception of errors to improve student's learning.

• Journal of the Society of Disaster Information
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• v.15 no.3
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• pp.409-417
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• 2019

Purpose: Since the implementation of the Chemical Substance Management Act, data on the number of occurrences by annual chemical accident in Korea and the contractor's contract data received from the competent authority were used. After the implementation of the contract reporting system, the contribution to the reduction of chemical accidents is summarized by statistical data. The characteristics of each region, month, type and those of similar industries and human life were compared and analyzed. Method: 4 years of chemical accident statistics from 2015 to 2018 and since 2003, we have used data from the Chemical Safety Clearing-House (CSC), which provides safety information on cases of chemical accidents. Results and Conclusion: The risk of accidents increases as a number of unskilled workers are put into the workplace during the period when the hazardous chemical handling process is temporarily suspended. Through the reporting for awarding a contract, the operators are strengthening the safety management of chemical accidents by educating unskilled workers and wearing personal protective equipment.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.3
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• pp.305-316
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• 2021

Construction accidents occur due to a number of reasons-worker carelessness, non-adoption of safety equipment, and failure to comply with safety rules are some examples. Because much construction work is done outdoors, weather conditions can also be a factor in accidents. Past construction accident data are useful for accident prevention, but since construction accident data are often in a text format consisting of natural language, extracting construction hazards from construction accident data can take a lot of time and that entails extra cost. Therefore, in this study, we extracted construction hazards from 2,026 domestic construction accident reports using text mining and performed a seasonal analysis of construction hazards through frequency analysis and centrality analysis. Of the 254 construction hazards defined by Korea's Ministry of Land, Infrastructure, and Transport, we extracted 51 risk factors from the construction accident data. The results showed that a significant hazard was "Formwork" in spring and autumn, "Scaffold" in summer, and "Crane" in winter. The proposed method would enable construction safety managers to prepare better safety measures against outdoor construction accidents according to weather, season, and climate.

• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.35-40
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• 2022

In the agricultural environment, pesticide control requires a high risk of work and a high labor force for farmers. The effectiveness of pesticide control using unmanned aerial vehicles varies according to climate, land type, and characteristics of unmanned aerial vehicles. Therefore, an effective method for pesticide control by unmanned aerial vehicles considering the spraying conditions and environmental conditions is required. In this paper, we propose an efficient pesticide control system based on agricultural unmanned aerial vehicles considering the application conditions and environmental information for each crop. The effectiveness of the proposed model was demonstrated by measuring the drop uniformity of pesticides according to the change in altitude and speed after attaching the sensory paper and measuring the penetration rate of the drug inside the canopy according to the change in crop growth conditions. Experiment result, the closer the height of the UAV is to the ground, the more evenly the crops are sprayed, but for safety reasons, 2m more is suitable, and on average a speed of 2m/s is most suitable for control. The proposed control system is expected to help develop intelligent services based on the use of various unmanned aerial vehicles in agricultural environments.

• Journal of Environmental Health Sciences
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• v.48 no.2
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• pp.66-74
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• 2022

Background: The health effects of particulate matter (PM_2.5) bonded with various harmful chemicals differ based on their composition, so investigating and managing their concentrations and composition is vital for long-term management. As industrial complexes emit considerable quantities of pollutants, higher PM_2.5 concentrations and chemical component effects are expected than in other places. Objectives: We investigated the concentration distribution ratios of PM_2.5 chemical components to provide basic data to inform future major emissions control and PM_2.5 reduction measures in industrial complexes. Methods: We monitored five sites near the Ansan and Siheung industrial complexes from August 2020 to July 2021. Samples were collected and analyzed twice per week in spring/winter and once per week in summer/autumn according to the National Institute of Environmental Research in the Ministry of Environments' Air Pollution Monitoring Network Installation and Operation Guidelines. We investigated and compared composition ratios of 29 ions, carbon, and elemental components in PM_2.5. Results: The analysis of PM_2.5 components at the five sites revealed that ion components accounted for the greatest total mass at approximately 50% while carbon components and elemental components contributed 23~28% and 8~10%, respectively. Among the ionic components, NO₃^- occupies the greatest proportion. OC occupies the greatest proportion of the carbon components and sulphur occupies the greatest proportion of elemental components. Conclusions: This study investigated the concentration distribution ratios of PM_2.5 chemical components in industrial complexes. We believe these results provide basic chemical component concentration ratio data for establishing future air management policies and plans for the Ansan and Siheung industrial complexes.

• Journal of the Society of Disaster Information
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• v.18 no.1
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• pp.10-18
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• 2022

Purpose: For smooth performance of flood analysis due to heavy rain disasters at energy storage facilities in the Incheon area, field surveys, observational surveys, and pre-established reports and drawings were analyzed. Through the field survey, the characteristics of pipelines and rivers that have not been identified so far were investigated, and based on this, the input data of the SWMM model selected for inundation analysis was constructed. Method: In order to determine the critical duration through the probability flood analysis according to the calculation of the probability rainfall intensity by recurrence period and duration, it is necessary to calculate the probability rainfall intensity for an arbitrary duration by frequency, so the research results of the Ministry of Land, Transport and Maritime Affairs were utilized. Result: Based on this, the probability of rainfall by frequency and duration was extracted, the critical duration was determined through flood analysis, and the rainfall amount suggested in the disaster prevention performance target was applied to enable site safety review. Conclusion: The critical duration of the base was found to be a relatively short duration of 30 minutes due to the very gentle slope of the watershed. In general, if the critical duration is less than 30 minutes, even if flooding occurs, the scale of inundation is not large.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.5
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• pp.617-626
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• 2022

In Korea, annual precipitation and its variability have gradually increased since modern meteorological observations began, and the risk of disasters has also been increasing due to significant regional variations and recent abnormal climate conditions. Given that damage from storms and floods mainly occurs around rivers, it is crucial to determine the appropriate design frequency for river-related projects. This study examined existing design practices used to determine hydrological design frequencies and suggested a new method to determine appropriate design frequencies. The study collected available data pertaining to seven evaluation factors, specifically the basin areas, shape parameters, channel slopes, stream orders, backwater effect reaches, extreme rainfall frequencies, and urbanized flood inundation areasfor 413 local rivers in Chungcheongnam-do in Korea. The estimated weights for areas of extreme rainfall frequencies and urbanized flood inundation were found to be 18, having a great effect on determining the design frequency. Compared with the established design frequency in previous government reports, the estimated design frequency increased for 255 rivers and decreased for 158 rivers.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.707-721
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• 2022

In this study, a state-of-the-art review on urban inundation simulation technology was presented summarizing major achievements and limitations, and future research recommendations and challenges. More than 160 papers published in major domestic academic journals since the 2000s were analyzed. After analyzing the core themes and contents of the papers, the status of technological development was reviewed according to simulation methodologies such as physically-based and data-driven approaches. In addition, research trends for application purposes and advances in overseas and related fields were analyzed. Since more than 60% of urban inundation research used Storm Water Management Model (SWMM), developing new modeling techniques for detailed physical processes of dual drainage was encouraged. Data-based approaches have become a new status quo in urban inundation modeling. However, given that hydrological extreme data is rare, balanced research development of data and physically-based approaches was recommended. Urban inundation analysis technology, actively combined with new technologies in other fields such as artificial intelligence, IoT, and metaverse, would require continuous support from society and holistic approaches to solve challenges from climate risk and reduce disaster damage.

• Korean Journal of Plant Taxonomy
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• v.52 no.3
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• pp.184-195
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• 2022

The invasive alien species Brassica tournefortii Gouan (Brassicaceae) is herein reported for the first time in Korea, from Gunsan-si, Gochang-gun, and Jeju-si. Brassica tournefortii can easily be distinguished from B. juncea and B. napus by its dense stiff hairs at the base of the stem and leaves, basally and distally branched stems, partially dehiscent fruits, and seeds that become mucilaginous in the presence of moisture. Although some taxonomists have classified this species as belonging to Coincya Rouy based on its fruit and seed characteristics, the existence of one vein on the fruit valves and our maximum likelihood analysis using internal transcribed spacer sequences placed it in Brassica. Distribution data, photographs, and a description of B. tournefortii are presented herein. Moreover, potential changes in the distribution of B. tournefortii were predicted under different climate scenarios, but our analysis showed that the probability of the spreading of this species is low. Nevertheless, continuous monitoring is necessary for an accurate assessment. The results of the present study can be used to conduct an invasion risk assessment and can assist with the effective management of this invasive alien species.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.8
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• pp.339-346
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• 2022

Recently, the resource depletion and climate change problem caused by the massive usage of fossil fuels for electric power generation has become a critical issue worldwide. According to this issue, interest in renewable energy resources that can replace fossil fuels is increasing. Especially, photovoltaic power has gaining much attention because there is no risk of resource exhaustion compared to other energy resources and there are low restrictions on installation of photovoltaic system. In order to use the power generated by the photovoltaic system efficiently, a more accurate photovoltaic power forecasting model is required. So far, even though many machine learning and deep learning-based photovoltaic power forecasting models have been proposed, they showed limited success in terms of interpretability. Deep learning-based forecasting models have the disadvantage of being difficult to explain how the forecasting results are derived. To solve this problem, many studies are being conducted on explainable artificial intelligence technique. The reliability of the model can be secured if it is possible to interpret how the model derives the results. Also, the model can be improved to increase the forecasting accuracy based on the analysis results. Therefore, in this paper, we propose an explainable photovoltaic power forecasting scheme based on BiLSTM (Bidirectional Long Short-Term Memory) and SHAP (SHapley Additive exPlanations).