• Spatial Information Research
• /
• v.23 no.3
• /
• pp.123-132
• /
• 2015

Recently both the importance and the interests of field-experience learning have kept increasing since the Education of Ministry encourages students to take a field-experience learning with the self-driven and creative education as the main issue in the 7th revised education curriculum in 2009. As the importance of field-experience learning goes up continuously, not only the release of its related mobile applications is increasing, but also a variety of researches for supporting the field-experience learning are ongoing. In this research we perform two things. First, we define the basic concept of authoring tool for which support the field-experience learning based on its characteristics and user requirements analysis. We confirmed that the authoring tool for the field-experience learning has to 1) support all activities that happen in pre-field, field-experience and post-field phases, 2) be possible to write the location-based field work, 3) have the authoring function which reflects the characteristics of curriculum such as history, science and geography, etc. that the field learning can be realized, 4) be designed as the structure that the results of inquiring activity after the field experience activity can be reused. Second, we create a conceptual design after confirming the authoring tool.

• Journal of the Korean Institute of Educational Facilities
• /
• v.23 no.4
• /
• pp.21-30
• /
• 2016

This study considers the concept of schools and their spatial composition by John Dewey through literature review who argued for a new, children-centered education in the early 19th century, and it also mentions some suggestions for improvement of the elementary school facilities in Korea that the size and number of students in school has decreased sharply. John Dewey claimed that a school is a big household as well as a small society in which one studies the current occupation and experience in connection between the household-school-society. At the same time, he pursued an organic and open spatial composition which can effectively and efficiently enable educational curriculum's application, social occupation and project learning based on children's native impulse and stage in child growth. Korea's education policy should shift from quantity-based education production to quality-based production due to the reduction of school age population among other reasons. Especially this study emphasizes that small size schools need to be changed to local community facilities with environment-friendly, children-centered and open learning spatial composition with basis on John Dewey's educational philosophy.

• ETRI Journal
• /
• v.44 no.6
• /
• pp.1034-1046
• /
• 2022

The learning-based multiview stereo (MVS) methods for three-dimensional (3D) reconstruction generally use 3D volumes for depth inference. The quality of the reconstructed depth maps and the corresponding point clouds is directly influenced by the spatial resolution of the 3D volume. Consequently, these methods produce point clouds with sparse local regions because of the lack of the memory required to encode a high volume of information. Here, we apply the atrous spatial pyramid pooling (ASPP) module in MVS methods to obtain dense feature maps with multiscale, long-range, contextual information using high receptive fields. For a given 3D volume with the same spatial resolution as that in the MVS methods, the dense feature maps from the ASPP module encoded with superior information can produce dense point clouds without a high memory footprint. Furthermore, we propose a 3D loss for training the MVS networks, which improves the predicted depth values by 24.44%. The ASPP module provides state-of-the-art qualitative results by constructing relatively dense point clouds, which improves the DTU MVS dataset benchmarks by 2.25% compared with those achieved in the previous MVS methods.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2021.07a
• /
• pp.549-550
• /
• 2021

사용자에게 맞춘 개인화된 제품과 서비스를 제공하는 기술의 발전으로 개인화의 수요는 점점 늘어날 것으로 전망하고 있다. 또한 개인 맞춤형으로 전문 스포츠 선수화, 족부 장애우를 위한 정형 제화 등 전문적인 기능 중심의 개인화나 패션을 위한 스타일 중심의 개인화 등 개인 맞춤 제작 신발을 제작할 때 기존의 아날로그적인 방식으로 발 변인을 측정했을 때 각 변인에 대해 기준점이 명확하지 않아서 재현성이 떨어진다. 따라서 본 논문에서는 자를 이용해 간단히 측정 가능한 기본적인 발 변인 이용하여 다른 변인들을 학습하고 딥러닝을 이용해 추정하는 방법에 대해 서술한다. 이를 위해 20개의 발 변인을 휙득 하였고 그 중 6개의 기본적인 발 변인을 이용해 14개 변인을적합 방지를 위해 Dorpout을 적용해 학습하고 학습한 데이터를 이용해 학습하지 않은 데이터를 테스트해 각 변인별 결과를 보여준다.

• Journal of Elementary Mathematics Education in Korea
• /
• v.20 no.4
• /
• pp.737-760
• /
• 2016

This study analyzed the 2009 revised curriculum 6th grade math geometric domain and developed virtual operation tool contents based RME theory. These materials were examine to find out how to effect on the spatial sense and mathematical attitudes by applying it to teach the 6th grade students. The results were as follows. First, it is more effective for improving spatial sense to study mathematics based RME theory with virtual operation tool contents than normal one. This means that mathematics study based RME theory with virtual operation contents overcomes the limitations of flat learning environment. And it is great educational and effective method for students to improve their spatial sense. Second, it is more effective for improving mathematical attitudes to study mathematics based RME theory with virtual operation tool contents than normal one. This means that Mathematics study based RME theory with virtual operation contents makes student more participate learning actively. It helps the students who have passive learning habits to have self-directed learning habits, ability to cooperation and communicate. The results of this study suggest that mathematics study based RME theory is very helpful for student to improve their spatial sense and have positive effect on self-concept in mathematics, attitudes toward mathematics and improving study habits in mathematical attitudes.

• Korean Journal of Remote Sensing
• /
• v.38 no.6_2
• /
• pp.1623-1631
• /
• 2022

Since oil spills can be a significant threat to the marine ecosystem, it is necessary to obtain information on the current contamination status quickly to minimize the damage. Satellite-based detection of marine oil spills has the advantage of spatiotemporal coverage because it can monitor a wide area compared to aircraft. Due to the recent development of computer vision and deep learning, marine oil spill detection can also be facilitated by deep learning. Unlike the existing studies based on Synthetic Aperture Radar (SAR) images, we conducted a deep learning modeling using PlanetScope optical satellite images. The blind test of the DeepLabV3+ model for oil spill detection showed the performance statistics with an accuracy of 0.885, a precision of 0.888, a recall of 0.886, an F1-score of 0.883, and a Mean Intersection over Union (mIOU) of 0.793.

• Journal of Cadastre & Land InformatiX
• /
• v.53 no.2
• /
• pp.5-18
• /
• 2023

As the development of drones and sensors accelerates, new services and values are created by fusing data acquired from various sensors mounted on drone. However, the construction of spatial information through data fusion is mainly constructed depending on the image, and the quality of data is determined according to the specification and performance of the hardware. In addition, it is difficult to utilize it in the actual field because expensive equipment is required to construct spatial information of high-quality. In this study, super-resolution was performed by applying deep learning to low-resolution images acquired through RGB and THM cameras mounted on a drone, and quantitative evaluation and feature point extraction were performed on the generated high-resolution images. As a result of the experiment, the high-resolution image generated by super-resolution was maintained the characteristics of the original image, and as the resolution was improved, more features could be extracted compared to the original image. Therefore, when generating a high-resolution image by applying a low-resolution image to an super-resolution deep learning model, it is judged to be a new method to construct spatial information of high-quality without being restricted by hardware.

• Korean Journal of Cognitive Science
• /
• v.22 no.2
• /
• pp.103-121
• /
• 2011

This study investigated how spatial dimension information and dimensional consistency between learning and testing phase would influence the target search performance. The participants learned spatial layouts of Lego blocks shown in either two- (2D) or three-dimension (3D) and were tested with the rotated stimuli ($0^{\circ}$, $90^{\circ}$, $180^{\circ}$, or $270^{\circ}$ from the initial view) in consistent or inconsistent dimension. Significantly better performance was observed when initial learning display appeared in 2D than in 3D. Particularly, the participants showed difficulties in flexible usage of spatial information presented in 3D especially if the dimensional information in the testing phase also was 3D and required mental rotation. The present study indicates that spatial map presented in 2D may be more useful than 3D in driving situations in which acquired spatial information from navigating device, such as GPS, and location of driver continuously changes.

• The Mathematical Education
• /
• v.48 no.1
• /
• pp.1-20
• /
• 2009

The study was to investigate an effect of students' learning for enhancing spatial ability, using a geometric manipulative recently designed. A mixed methodology was chosen to achieve the purpose of the study. To find students' achievement, 152 of the 8th graders in Kyunggi Do participated in data collection. At the same time. students' performance of the class was videotaped and analyzed to see students' responses, The results showed that the effect of using the manipulative was statistically significant at level, p<.05 to enhance the spatial ability. Specifically, in comparison of each component. spatial orientation was more effective than spatial visualization. In the spatial orientation, the part of field was more effective than the reorganized whole. It showed that students were given more opportunities to find mathematical properties and relations between 2nd and 3rd-dimensional figures through their intuitive observation, and also the manipulative helped the students find the property of the part of field because it gave an easy way to manipulate the property of the find parts of whole which was composed of the frame of the solid figures without surfaces. In using the manipulative, students were very flexible in finding the number of plane figures, but the relations between the 2nd and 3rd dimensional figures need to be clearly guided in consideration of the characteristics of the manipulative, based on the definitions of geometric properties(cf. points can make lines, not surfaces directly).

• The KIPS Transactions:PartD
• /
• v.18D no.5
• /
• pp.385-392
• /
• 2011

Recently, the concern of IT-in-Agriculture convergence technology that combines information technology and agriculture is increasing rapidly. Especially, the crop cultivation related prediction services by spatial data mining (SDM) can play an important role in reducing the damage of natural disaster and enhancing crop productivity. However, the data conversion and integration procedure to acquire the learning dataset of SDM for the prediction service need a lot of effort and time, because of their heterogeneity between distributed data. In addition, calculating spatial neighborhood relationships between spatial and non-spatial data necessitates requires the complicated calculation procedure for large dataset. In this paper, we suggest a SOA-based data integration framework that can effectively integrate distributed heterogeneous data by treating each data source as a service unit and support to find the optimal prediction service by improving productivity of learning dataset for SDM. In our experiment, we confirmed that our framework can be effectively applied to find the optimal prediction service for the frost damage area, by considering the case of peach crop cultivation in Icheon in Korea.