• Korean Journal of Culture and Social Issue
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• v.14 no.1_spc
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• pp.415-425
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• 2008

There are many social issues that should be solved through activity in the local community, such as community development, social service, environmental protection and disaster prevention. Despite a large number of activities, they are not always effective. In this investigation, we examine some alternative approaches to disaster prevention in local communities based on Japanese research and practices. Activity theory (Engestr öm, 1987) was adopted as a theoretical viewpoint. Implications for community education, which is another important issue in the community, are also discussed.

• Journal of Internet of Things and Convergence
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• v.6 no.1
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• pp.83-95
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• 2020

Being a dense and complex task of precisely detecting the weeds in practical crop field environment, previous approaches lack in terms of speed of processing image frames with accuracy. Although much of the attention has been given to classify the plants diseases but detecting crop weed issue remained in limelight. Previous approaches report to use fast algorithms but inference time is not even closer to real time, making them impractical solutions to be used in uncontrolled conditions. Therefore, we propose a detection model for the complex rice weed detection task. Experimental results show that inference time in our approach is reduced with a significant margin in weed detection task, making it practically deployable application in real conditions. The samples are collected at two different growth stages of rice and annotated manually

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.885-890
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• 2023

As satellite technology progresses, a growing number of satellites-like CubeSat and radar satellites-are available with a higher spectral and spatial resolutions than previous. National initiatives used to be the main force behind satellite development, but current trendsindicate that private enterprises are also actively exploring and developing new satellite technologies. This special issue examines the recent research results and advanced technology in remote sensing approaches for Earth environment analysis. These results provide important information for the development of satellite sensors in the future and are of great interest to researchers working with artificial intelligence in thisfield. The special issue introduces the latest advances in remote sensing technology and highlights studies that make use of data to monitor and forecast Earth's environment. The objective is to provide direction for the future of remote sensing research.

• Korean Journal of Environmental Biology
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• v.39 no.4
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• pp.581-589
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• 2021

Using visible-near infrared(Vis-NIR) spectra combined with machine learning methods, the feasibility of quick and non-destructive classification of Convolvulaceae species was studied. The main aim of this study is to classify six Convolvulaceae species in the field in different geographical regions of South Korea using a handheld spectrometer. Spectra were taken at 1.5 nm intervals from the adaxial side of the leaves in the Vis-NIR spectral region between 400 and 1,075 nm. The obtained spectra were preprocessed with three different preprocessing methods to find the best preprocessing approach with the highest classification accuracy. Preprocessed spectra of the six Convolvulaceae sp. were provided as input for the machine learning analysis. After cross-validation, the classification accuracy of various combinations of preprocessing and modeling ranged between 43.4% and 98.6%. The combination of Savitzky-Golay and Support vector machine methods showed the highest classification accuracy of 98.6% for the discrimination of Convolvulaceae sp. The growth stage of the plants, different measuring locations, and the scanning position of leaves on the plant were some of the crucial factors that affected the outcomes in this investigation. We conclude that Vis-NIR spectroscopy, coupled with suitable preprocessing and machine learning approaches, can be used in the field to effectively discriminate Convolvulaceae sp. for effective weed monitoring and management.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.508-518
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• 2023

This paper presents a new approach for the automatic mapping of discontinuities in a tunnel face based on its 3D digital model reconstructed by LiDAR scan or photogrammetry techniques. The main idea revolves around the identification of discontinuity areas in the 3D digital model of a tunnel face by segmenting its 2D projected images using a deep-learning semantic segmentation model called U-Net. The proposed deep learning model integrates various features including the projected RGB image, depth map image, and local surface properties-based images i.e., normal vector and curvature images to effectively segment areas of discontinuity in the images. Subsequently, the segmentation results are projected back onto the 3D model using depth maps and projection matrices to obtain an accurate representation of the location and extent of discontinuities within the 3D space. The performance of the segmentation model is evaluated by comparing the segmented results with their corresponding ground truths, which demonstrates the high accuracy of segmentation results with the intersection-over-union metric of approximately 0.8. Despite still being limited in training data, this method exhibits promising potential to address the limitations of conventional approaches, which only rely on normal vectors and unsupervised machine learning algorithms for grouping points in the 3D model into distinct sets of discontinuities.

• Journal of the Korean Society of Earth Science Education
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• v.12 no.1
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• pp.1-17
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• 2019

The importance of education in formulating and complementing climate change response has been widely recognized by international and national frameworks, agendas, strategies and action plans. Climate change education has the potential to meet the needs of communities to access updated information and knowledge on climate change, supporting policy development and the enhancing effectiveness of climate change response. This study develops an innovative model of Integrated Urban Climate Education (IUCE) as one suitable method for teaching and learning climate change and urbanization. This paper presents approaches, methodology and key lessons learned from the case study of IUCE in Cam Le District of Da Nang City. Findings from the study identify a number of important characteristics about the development and implementation of IUCE in a way that effectively contributes to urban resilience building. These characteristics include (1) multidimensional approaches, (2) teacher - centered base, (3) school-family-community connection, and (4) symbiosis principle.

• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.180-187
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• 2021

This thesis explores the place and role of a performer's action from a perspective of a director and playwright David Mamet's concept for performer training. This thesis takes inspiration from the idea of Mamet's simple and practical investigation specifically in text-based approach with a performer's bodily function on stage. For Mamet, the writings and practices of many different body-centered training are not rooted in the principle and nature of acting/performance. Reconsidering complicated approaches particularly psychological-oriented theory, practice, and assumption draw on several practitioners takes us beyond the field of visible and/or outer appearance of a performer which in turn leads the performer's body to be as abstract therefore not to being in the moment on stage. Arming the points, we argue that whatever disciplines and/or methods necessarily need to meet the principles and demands of acting/performance/theatre to connect to the materials, an action/objective given by a specific playwright which the performer must inhabit through his/her body. Out of the context, any 'method' serves no purpose. That is, the mechanics of an action is an extension of addressing what a performer's specific needs which shifts his/her body to respond appropriately to the theatrical demands. Taking this argument further, we claim that the purpose of performer training should not be understood as learning and improving techniques or skills for his/her self-perfection. The research finding shows that this resembles to the phenomenon that the visible very often precedes the invisible where the performer's body lose a clarity with no more chance to happen and/or change the event(s). Rather, it is a process of learning what/how to learn which in turn brings us back to the central question of why we do training for what purpose in this contemporary era. Exploring and answering these questions is not only a way to employ the key materials applicable to the theatrical demands but also to achieve the identify as a professional performer/doer on stage.

• Journal of the Korean earth science society
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• v.41 no.3
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• pp.261-272
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• 2020

The purpose of this study was to compare the earth science curriculums of South Korea and North Korea. Aspects such as the content of the curriculums and the timing of learning were analyzed, in order to provide basic data that can be used to design a revised and integrated Korean curriculum. The objects of this study were South Korean Science textbooks from grades 5-9, and the high school Unity of Science and Earth Science I and II textbooks. Additionally, from North Korea, the junior middle school Natural Science 1 and 2 textbooks and the senior middle school Chosun Geography 2 and Geography 1 textbooks were analyzed. The results of this study obtained through an analysis that used the Trends in International Mathematics and Science Study (TIMSS 2019) grade 8 earth science assessment framework were as follows. First, South Korea needs to adopt iterative learning. Repetitive learning, which is effective for understanding what is being learned, is applied to only 1 by 8th grade. Second, South Korea needs to adjust the time when certain content is learned. This is because there is a disparity between when content is learned in comparison to North Korea, and the timing of learning of about 50% of the TIMSS standards have not been followed. Third, it is necessary to reflect the content present within the TIMSS that have not been learned. This can be a way to increase the nations' educational competitiveness in the international community. This paper proposed a comparative analysis of South korean and North Korean approaches to the earth science curriculum and conducted practical research to facilitate the construction of an integrated curriculum.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.57-65
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• 2021

We propose a novel method to detect abnormal data of specific symptoms using deep learning in air pollution measurement system. Existing methods generally detect abnomal data by classifying data showing unusual patterns different from the existing time series data. However, these approaches have limitations in detecting specific symptoms. In this paper, we use DeepLab V3+ model mainly used for foreground segmentation of images, whose structure has been changed to handle one-dimensional data. Instead of images, the model receives time-series data from multiple sensors and can detect data showing specific symptoms. In addition, we improve model's performance by reducing the complexity of noisy form time series data by using 'piecewise aggregation approximation'. Through the experimental results, it can be confirmed that anomaly data detection can be performed successfully.

• School Mathematics
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• v.18 no.1
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• pp.193-214
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• 2016

Teachers' questioning plays an important role in mathematics teaching and learning by asking students to react or to participate in mathematical discourse. Previous studies on teachers' questioning have not focused on how to questioning to formulate an effective mathematical discourse which is contributed by students because studies mostly analyzed and categorized teachers' questions according to cognitive levels of questions without consideration of context. Therefore, this study explored characteristics of teachers' questioning to formulate an effective characteristics of teachers' questioning to formulate an effective mathematical discourse in mathematics classrooms. By reviewing and analyzing mathematics discourse and studies on teachers' questioning theoretically, we presented openness, sharedness, and productivity as characteristics of teachers' questioning. Through a middle school mathematics teacher's case, we examined three characteristics were necessary to formulate an effective mathematical discourse. Based on results from theoretical analysis and case analysis, we discussed that openness, sharedness, and productivity would be useful as a framework to analyze teachers' questioning.