• 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.

• The Mathematical Education
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• v.60 no.3
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• pp.321-340
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• 2021

As many changes in the future society represented by the age of artificial intelligence(AI) are expected to come, efforts are being made to draw the shape of the future education and various research methods are being employed to support the attempts. While many research studies use methods for deriving generalized results such as expert survey and trend analysis in along with a review of literature, there are attempts to apply the scenario methodology to explore ideas and information needed within a changing context. A scenario method, one of the experiential learning strategies, aims to seek various and alternative approaches by establishing a plan from the present conditions considering future changes. In this study, in-service teachers' perceptions and expectations of the interactivity between human and AI teachers were visualized by applying the role-play presentation technique that grafted the concept of role-play game to the scenario method. In addition, the mandal-art method was introduced to support in conducting productive discussion during the teachers' collaboration. This method appeared to help to depict teachers' perceptions of AI teachers in the detailed and concrete form, which may flow in the abstract otherwise. Through analyses of the teachers' role-play presentations with the implementation of the madal-art method it was suggested that most teachers would want to collaborate with an AI teacher for improved instruction and individualized student learning while they would take the instructional authority over the AI teacher in the classroom.

• Journal of KIISE:Information Networking
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• v.29 no.4
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• pp.412-427
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• 2002

This paper proposes a restoration scheme based on mobility learning and prediction in the presence of the failure of mobility databases in mobile communication systems. In mobile communication systems, mobility databases must maintain the current location information of users to provide a fast connection for them. However, the failure of mobility databases may cause some location information to be lost. As a result, without an explicit restoration procedure, incoming calls to users may be rejected. Therefore, an explicit restoration scheme against the failure of mobility databases is needed to guarantee continuous service availability to users. Introducing mobility learning and prediction into the restoration process allows systems to locate users after a failure of mobility databases. In failure-free operations, the movement patterns of users are learned by a Neuro-Fuzzy Inference System (NFIS). After a failure, an inference process of the NFIS is initiated and the users' future location is predicted. This is used to locate lost users after a failure. This proposal differs from previous approaches using checkpoint because it does not need a backup process nor additional storage space to store checkpoint information. In addition, simulations show that our proposal can reduce the cost needed to restore the location records of lost users after a failure when compared to the checkpointing scheme

• The Korean Journal of Applied Statistics
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• v.29 no.6
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• pp.1007-1023
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• 2016

This paper explores the conditions and potential of newly designed and tried methodology of big data analysis that apply to Korean history subject matter. In order to advance them, we need to pay more attention to quantitative analysis methodologies over pre-existing qualitative analysis. To obtain our new challenge, I propose 'digital history' methods along with associated disciplines such as linguistics and computer science, data science and statistics, and visualization techniques. As one example, I apply interdisciplinary convergence approaches to the principle and mechanism of elite reproduction during the Korean medieval age. I propose how to compensate for a lack of historical material by applying a semi-supervised learning method, how to create a database that utilizes text-mining techniques, how to analyze quantitative data with statistical methods, and how to indicate analytical outcomes with intuitive visualization.

• Journal of Korea Multimedia Society
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• v.15 no.5
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• pp.606-614
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• 2012

Face detection using AdaBoost algorithm is one of the fastest and the most robust face detection algorithm so many improvements or extensions of this method have been proposed. However, almost all previous approaches deal with only frontal face and suffer from limited discriminant capability for inclined face because these methods apply the same features for both frontal and inclined face. Also conventional approaches for detecting inclined face which apply frontal face detecting method to inclined input image or make different detectors for each angle require heavy computational complexity and show low detection rate. In order to overcome this problem, a method for detecting inclined face using JointBoost is proposed in this paper. The computational and sample complexity is reduced by finding common features that can be shared across the classes. Simulation results show that the detection rate of the proposed method is at least 2% higher than that of the conventional AdaBoost method under the learning condition with the same iteration number. Also the proposed method not only detects the existence of a face but also gives information about the inclined direction of the detected face.