• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.5
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• pp.1-13
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• 2022

The damages caused by landslides are increasing worldwide due to climate change. In Korea, damages from landslides occur frequently, making it necessary to develop the effective response strategies. In particular, there is a lack of countermeasures against landslides in cultural heritage areas. The purpose of this study was to spatially analyze the relationship between Buyeo-gun's cultural heritage and landslide susceptible areas in Buyeo-gun, Chungcheongnam-do, which has a long history. Nine spatial distribution models were used to evaluate the landslide susceptibility, and the ensemble method was applied to reduce the uncertainty of individual model. There were 17 cultural heritages belonging to the landslide susceptible area. As a result of calculating the area ratio of the landslide susceptible area for cultural heritages, the cultural heritages with 100% of the area included in the landslide susceptible area were "Standing statue of Maae in Hongsan Sangcheon-ri" and "Statue of King Seonjo." More than 35% of "Jeungsanseong", "Garimseong", and "Standing stone statue of Maitreya Bodhisattva in Daejosa Temple" belonged to landslide susceptible areas. In order to effectively prevent landslide damage, the application of landslide prevention measures should be prioritized according to the proportion belonging to the landslide susceptible area. Since it is very difficult to restore cultural properties once destroyed, preventive measures are required before landslide damage occurs. The approach and results of this study provide basic data and guidelines for disaster response plans to prevent landslides in Buyeo-gun.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.37-44
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• 2022

Plug-in Hybrid electric vehicles (PHEV) show great potential to reduce gas emission, improve fuel efficiency and offer more driving range flexibility. Moreover, PHEV help to preserve the eco-system, climate changes and reduce the high demand for fossil fuels. To address this; some basic components and energy resources have been used, such as batteries and proton exchange membrane (PEM) fuel cells (FCs). However, the FC remains unsatisfactory in terms of power density and response. In light of the above, an electric storage system (ESS) seems to be a promising solution to resolve this issue, especially when it comes to the transient phase. In addition to the FC, a storage system made-up of an ultra-battery UB is proposed within this paper. The association of the FC and the UB lead to the so-called Fuel Cell Battery Electric Vehicle (FCBEV). The energy consumption model of a FCBEV has been built considering the power losses of the fuel cell, electric motor, the state of charge (SOC) of the battery, and brakes. To do so, the implementing a reinforcement-learning energy management strategy (EMS) has been carried out and the fuel cell efficiency has been optimized while minimizing the hydrogen fuel consummation per 100km. Within this paper the adopted approach over numerous driving cycles of the FCBEV has shown promising results.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.419-427
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• 2021

Due to the effects of climate change and the reduction of the labor force due to COVID-19, the crop yield, harvest time, and cultivated area are rapidly changing every year. In order to respond flexibly to this situation, attempts to apply smart farm technology based on ICT (Information and Communication Technology) to individual farms are increasing. On the other hand, various stakeholders are trying to predict the yield of crops using artificial intelligence and IoT technology, but accurate prediction is difficult due to the lack of learning data. In this study, in order to overcome the data collection problem limited to a specific institution, a smart farmer service technology based on community mapping was developed in which farmers directly participate, input and share accurate data to predict production. In the process, analysis was performed on napa cabbage, which is a vegetable with a large price change compared to production.

• The Journal of Korean Academic Society of Nursing Education
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• v.27 no.4
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• pp.436-446
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• 2021

Purpose: The purpose of this study was to identify the influences of nursing students perfectionism tendencies and their perception of instructor caring on incivility experienced by nursing students during clinical practice. Methods: A descriptive correlational study was conducted. The participants were 244 nursing students from five universities in B city. Data were analyzed using an independent t-test, ANOVA, Pearson's correlation coefficient, Scheffé test and a stepwise regression analysis. Results: The mean score for incivility in nursing students was 2.61 out of 5 points. The explanatory power of the model for incivility was in nursing students 52.8% of the variance in training in student's university hospital (𝛽=-.15, p=.002), total period of clinical practice (𝛽=.17, p<.001), confidence through caring (𝛽=-.23, p<.001), respectful sharing (𝛽=-.15, p=.005), supportive learning climate (𝛽=-.15, p=.005), self-oriented perfectionism (𝛽=.14, p=.004), and socially prescribed perfectionism (𝛽=.18, p<.001). Conclusion: The research results suggest that instructor caring is an important factor in regard to the incivility of nursing students. Organizational efforts and institutional devices will be needed to improve the incivility in clinical environments. By communicating with students and showing them respect, clinical nurses will help nursing students cope with incivility and recognize the clinical practice education environment positively.

• Journal of Advanced Navigation Technology
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• v.27 no.1
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• pp.133-138
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• 2023

As a side effect of recent rapid climate change and global warming, the frequency and scale of flood disasters are increasing worldwide. In Korea, the water level of the Han River is a major management target for preventing flood disasters in Seoul, the capital of Korea. In this paper, to improve the water level prediction of the Han River based on machine learning, we perform a comprehensive assessment of the quality of related dataset and propose data preprocessing methods to improve it. Specifically, we improve the dataset in terms of completeness, validity, and accuracy through missing value processing and cross-correlation analysis. In addition, we conduct a performance evaluation using random forest and LightGBM to analyze the effect of the proposed data improvement method on the water level prediction performance of the Han River.

• Journal of the Korea Society of Computer and Information
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• v.28 no.9
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• pp.149-158
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• 2023

With the global paradigm shift towards climate change, the shipbuilding industry is also considering propulsion systems that utilize eco-friendly fuels various propulsion systems are gaining attention as a result. In conventional propulsion systems, typically consisting of propellers and rudders, have evolved into a diverse range of systems due to the development of a special propulsion system known as the azimuth thruster. While azimuth thrusters were previously commonly installed on tugboats, they are now extensively used on offshore plant operation ships equipped with dynamic positioning systems. However, these azimuth thrusters require different steering methods compared to conventional propulsion systems, leading to a significant learning curve for the crew members boarding such vessels. Furthermore the availability of education related to these special propulsion systems is limited. This study aims to analyze accidents caused by inadequate control of vessels equipped with azimuth thrusters using the STAMP technique. And it proposes the necessity of standard steering commands for the safe operation of vessels equipped with special propellers.

• Journal of Christian Education in Korea
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• v.72
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• pp.7-24
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• 2022

Christian education for the world after COVID-19 needs to use rapid changes in the surrounding situation as an opportunity to overcome a new crisis so that the church can achieve its educational mission. If the biggest dilemma in the post-Corona era is that there is no authoritative educational prescription anywhere, the most reasonable option for church education in this situation is to emphasize and cultivate learners' ability to flexibly cope with rules that are completely different than before COVID-19. As a natural result of the crisis, Christian education needs to be more interested in the trend of social change in the pandemic era(glocalization, digital transformation, economic inequality, educational environment change, church crisis) and actively reflect its contents in education. In addition, while operating a mobile(or online) church school that combines offline and online, there is an urgent need for an innovative transition to a core church school where certain church schools and churches cooperate with each other, a church school that guarantees a safe learning space, and an ecological church school that is interested in education dealing with climate change and ecology.

• Journal of Korean Society of Rural Planning
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• v.29 no.4
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• pp.27-34
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• 2023

Recently, worldwide to respond to climate change and secure sustainability. Korea aimed to increase water use efficiency by implementing integrated management according to the water management unification policy. Therefore, the necessity of establishing and operating governance is expanding to ensure the sustainability of agricultural water. In this study aims to evaluate the importance of agricultural water governance components and provide essential data for the participation of stakeholders in the efficient use of agricultural water in Korea. For this study, a total of 19 respondents to the ANP survey for this study were composed of experts in agricultural water and governance in Korea. As a result, the ranking for the main components was in the order of law, policy, and systems(0.222), core subjects(0.191), information sharing and communication(0.180), budget support(0.178), mutual learning(0.124), and external experts(0.105). The most important components for the operation of agricultural water governance are laws, policies, and systems. Since Korea's agricultural water management is a public management system, national standards are considered the first priority. This study, which is the purpose of the agricultural water governance model, evaluated the importance of the constituent components for participating in demand management with a sense of responsibility. Moreover, if agricultural water governance is expanded nationwide by reflecting agricultural and water resource policies in the future, it is believed that positive effects can be achieved in increasing utilization efficiency and securing sustainability through agricultural water saving.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1577-1589
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• 2023

Recently, the necessity of predicting changes for monitoring ocean is widely recognized. In this study, we performed a time series prediction of remote-sensing reflectance (Rrs), which can indicate changes in the ocean, using Geostationary Ocean Color Imager (GOCI) data. Using GOCI-I data, we trained a multi-scale Convolutional Long-Short-Term-Memory (ConvLSTM) which is proposed in this study. Validation was conducted using GOCI-II data acquired at different periods from GOCI-I. We compared model performance with the existing ConvLSTM models. The results showed that the proposed model, which considers both spatial and temporal features, outperformed other models in predicting temporal trends of Rrs. We checked the temporal trends of Rrs learned by the model through long-term prediction results. Consequently, we anticipate that it would be available in periodic change detection.

• Convergence Security Journal
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• v.23 no.5
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• pp.135-142
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• 2023

In addressing the prominent issues of climate change, resource scarcity, and environmental pollution associated with household waste, extensive research has been conducted on intelligent waste classification methods. These efforts range from traditional classification algorithms to machine learning and neural networks. However, challenges persist in effectively classifying waste in diverse environments and conditions due to insufficient datasets, increased complexity in neural network architectures, and performance limitations for real-world applications. Therefore, this paper proposes i-YOLOX as a solution for rapid classification and improved accuracy. The proposed model is evaluated based on network parameters, detection speed, and accuracy. To achieve this, a dataset comprising 10,000 samples of household waste, spanning 17 waste categories, is created. The i-YOLOX architecture is constructed by introducing the Involution channel convolution operator and the Convolution Branch Attention Module (CBAM) into the YOLOX structure. A comparative analysis is conducted with the performance of the existing YOLO architecture. Experimental results demonstrate that i-YOLOX enhances the detection speed and accuracy of waste objects in complex scenes compared to conventional neural networks. This confirms the effectiveness of the proposed i-YOLOX architecture in the detection and classification of multiple household waste objects.