• Communications of Mathematical Education
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• v.25 no.2
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• pp.361-379
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• 2011

The purposes of this research are to develop Engineering Mathematics materials using the relations between Engineering Mathematics contents and not only pre-study contents but also major contents and to find the effect of the mathematics study which is applying them for students majoring in electronics. To accomplish the goals, I made list of Engineering Mathematics contents which is necessary to study electronics. Based on the list, I researched relations between Engineering Mathematics contents and not only pre-study contents but also major contents. After research, I selected some subjects which are related each other, developed study materials and examined responses to the materials. Then I analysed the effects on study attitude after used developed materials in my class. As a result, the major contents which was described in the introduction of the materials helped students to be motivated to study Engineering Mathematics and Pre-study contents described before Engineering Mathematics contents helped them to concentrate on studying Engineering Mathematics. Also it showed that developed study materials were effective in increasing self-confidence which is one attitude in the subcategories for Mathematics study.

• Journal of The Korean Association For Science Education
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• v.32 no.7
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• pp.1124-1138
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• 2012

This study investigates Korean middle school students' perceptions as global citizens (i.e. ecological worldview, social and moral compassion, and socioscientific accountability) of Socioscientific Issues (SSI). We developed questionnaires that consisted of 20 Likert-type items to gauge their preceptions of the three different SSI contexts (i.e. nuclear power generation, bio-technology, climate change), and administered them to 225 9th grade students in Seoul. The results revealed that participants showed relatively high scores for ecological worldview but scored low on social and moral compassion across the SSI contexts. In addition, participants presented much higher scores for ecological worldview and socioscientific accountability regarding the issues of climate change. The participant responses indicated that they perceived more inter-connectedness with the environment and felt the responsibility of promoting sustainable development more to prevent further devastation in the context of climate change compared to nuclear power generation or biotechnology.

• Journal of Digital Convergence
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• v.14 no.10
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• pp.53-60
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• 2016

This study investigated the effect of visual mathematics education using smartphones and immediate feedback through SNS on students' understanding of basic mathematical concept and academic achievement at the tertiary level. Researchers analyzed the test results of 214 students' mid-term and final examination in 4 classes consisted of 16 weeks' classes with two hours per week. Also their 30 questionnaire survey results were analyzed. The result reveals that classes using smartphones promoted understanding mathematical concepts and induced students' motivation and affirmative reaction. This study implies that an appropriate use of technology will support dynamic visualization of mathematical modeling and its interpretation, which enables students' active participation and deeper understanding.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.600-600
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• 2016

기후변화로 인한 가뭄 및 홍수 등의 이상 현상은 유역의 수자원에 미치는 영향이 크기 때문에 이에 대한 예측 및 적응방안을 마련하는 부분이 대두되고 있다. 따라서 본 연구에서는 유역의 수자원 관리를 위하여 단위유역에서의 수자원 취약성을 평가하고자 하였다. 평가 지표는 기후 및 사회 경제 환경적 측면을 고려하여 선정하였으며, 취약성 정의에 따라 수량 및 수질/수생태에 대하여 각각 노출, 민감도, 적응능력으로 구성하였다. 이후 다기준 의사결정기법(Multi-criteria Decision Making, MCDM) 중 TOPSIS(Technique for Order Performance by Similarity to Ideal Solution)를 적용하여 각각의 통합 취약성을 도출하였다. 지표 자료는 2010년을 기준으로 국가 통계 자료를 통해 수집하였으며, 유출량과 증발산량 자료는 준분포형 장기유출모형인 SWAT(Soil and Water Assessment Tool) 모형의 모의 자료(2005~2014)를 활용하였다. 또한, 지표에 대한 가중치는 전문가 설문조사를 통해 산정한 주관적 가중치(Subjective weight)와 수집된 자료를 통하여 산정한 객관적 가중치(Objective weight)로 구분하여 적용하였다. 인구 및 산업의 밀집도가 높은 한강권역에 대하여 표준단위유역(평균 $145km^2$)의 취약성을 평가하였으며, 각각의 취약성 우선 순위를 확인하였다. 수량 취약성의 경우에는 경기 강원북부와 충정도 일부 지역이 높은 것으로 나타났으며, 수질/수생태는 수도권 등 비교적 하류에 위치한 지역의 취약성 순위가 좀 더 높았다. 가중치 적용 방법에 따른 공간분포의 차이는 수질/수생태 취약성이 더 크게 나타나는 것을 확인할 수 있었다.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1723-1735
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• 2022

Landslides are one of the most prevalent natural disasters, threating both humans and property. Also landslides can cause damage at the national level, so effective prediction and prevention are essential. Research to produce a landslide susceptibility map with high accuracy is steadily being conducted, and various models have been applied to landslide susceptibility analysis. Pixel-based machine learning models such as frequency ratio models, logistic regression models, ensembles models, and Artificial Neural Networks have been mainly applied. Recent studies have shown that the kernel-based convolutional neural network (CNN) technique is effective and that the spatial characteristics of input data have a significant effect on the accuracy of landslide susceptibility mapping. For this reason, the purpose of this study is to analyze landslide vulnerability using a pixel-based deep neural network model and a patch-based convolutional neural network model. The research area was set up in Gangwon-do, including Inje, Gangneung, and Pyeongchang, where landslides occurred frequently and damaged. Landslide-related factors include slope, curvature, stream power index (SPI), topographic wetness index (TWI), topographic position index (TPI), timber diameter, timber age, lithology, land use, soil depth, soil parent material, lineament density, fault density, normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used. Landslide-related factors were built into a spatial database through data preprocessing, and landslide susceptibility map was predicted using deep neural network (DNN) and CNN models. The model and landslide susceptibility map were verified through average precision (AP) and root mean square errors (RMSE), and as a result of the verification, the patch-based CNN model showed 3.4% improved performance compared to the pixel-based DNN model. The results of this study can be used to predict landslides and are expected to serve as a scientific basis for establishing land use policies and landslide management policies.

• The Magazine of the IEIE
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• v.41 no.3
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• pp.28-39
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• 2014

• Journal of environmental and Sanitary engineering
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• v.2 no.3 s.3
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• pp.5-6
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• 1987

• The Magazine of the IEIE
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• v.33 no.2 s.261
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• pp.52-61
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• 2006

• The Journal of Engineering Geology
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• v.23 no.3
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• pp.305-314
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• 2013

Recent international and national research trends in landslide hazards were analyzed by performing a literature search of relevant scientific journals. For obtaining data from Korea, we used 'Information for Environmental Geology' (IEG), which covers 17 journals in the field of environmental geology. A total of 54 articles related to landslide hazards were found in 5 journals published in the period 2000-2012. The most common topic was landslide prediction or susceptibility (29 articles), followed by landslide mechanisms. For international information, we analyzed 1,851 articles from the 'Web Of Science' published from 2003 to the present. Researchers in Italy have published the greatest number of papers in this field, while papers from Korea rank first in terms of the citation index.

• The Journal of Engineering Geology
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• v.34 no.1
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• pp.51-65
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• 2024

Landslides are natural disasters that causes significant property damage worldwide every year. In Korea, damage due to landslides is increasing owing to the effects of climate change, and it is important to identify the factors that increase the prevalence of landslides in order to reduce the damage they cause. Therefore, this study used a random forest model to analyze the importance of 14 factors in influencing landslide damage in a specific area of Chungju, Chungcheongbuk-do province, Korea. The random forest model performed accurately with an AUC of 0.87 and the most-important factors were ranked in the order of aspect, slope, distance to valley, and elevation, suggesting that topographic factors such as aspect and slope more greatly influence landslide damage than geological or soil factors such as rock type and soil thickness. The results of this study are expected to provide a basis for mapping and predicting landslide damage, and for research focused on reducing landslide damage.