• Journal of Korean Society of Rural Planning
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• v.16 no.4
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• pp.157-169
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• 2010

This study has intended to devise a comprehensive rural planning, driven by residents based on ecological rural amenity paradigm for Busu area, Boeun-gun, South Korea. To reach the goal, this study has performed the following processes. First, we have analyzed the elements of threat, opportunity, weakness, and strength in both inside and outside village through 'SWOT analysis. Second, through strategic analysis and consultation, we have proposed developmental directions of Busu area. Third, based on an ecological rural amenity planning system composed of ecological economy system, ecological environment system, ecological history-culture system, ecological image system, and ecological society system, we have suggested research projects of each system Fourth, we selected projects through a general meeting with all stakeholders. Fifth, the selected projects were applied to Busu area by village residents and experts. Finally, the projects, which were appraised and revised by experts, residents, and governmental officers, were composed of ecological scenic agriculture center, resident's site for city dweller, energy independent village, eco-road, eco-pond, ecological park and parking lot, restoration of traditional culture, zone of ecological scenic agriculture, eco-tunnel, eco-fence, landmark, corporate identity, community center, forum and seminar, and education for residents' empowerment.

• Journal of Korean Society of Rural Planning
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• v.16 no.4
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• pp.53-60
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• 2010

This study aims at suggesting the attributes and limitations of each methods through the evaluation of the verified analysis results, so that it will be possible to select an efficient method that may be applied to assess the green coverage ratio. Green coverage areas of each sites subject to this study were assessed utilizing the following four methods. First, assessment of green coverage area through direct planimetry of satellite images. Second, assessment of green coverage area using land cover map. Third, assessment of green coverage area utilizing the band value in satellite images. Forth, assessment of green coverage area using and land cover map and reference materials. For this study, four urban zones of the City of Seosan in Chungcheongnam-do. As a result, this study show that the best calculation method is the one that combines the merits of first and second methods. This method is expected to be suitable for application in research sites of middle size and above. It is also deemed that it will be possible to apply this method in researches of wide area, such as setting up master plans for parks and green zones established by each local self-government organizations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.3955-3971
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• 2020

Due to the significant increase in the use of autonomous car technology, it is essential to integrate this technology with high-precision digital map data containing more precise and accurate roadway information, as compared to existing conventional map resources, to ensure the safety of self-driving operations. While existing map technologies may assist vehicles in identifying their locations via Global Positioning System, it is however difficult to update the environmental changes of roadways in these maps. Roadway vision algorithms can be useful for building autonomous vehicles that can avoid accidents and detect real-time location changes. We incorporate a hybrid architectural design that combines unsupervised classification of vision data with supervised joint fusion classification to achieve a better noise-resistant algorithm. We identify, via a deep learning approach, an intelligent hybrid fusion algorithm for fusing multimodal vision feature data for roadway classifications and characterize its improvement in accuracy over unsupervised identifications using image processing and supervised vision classifiers. We analyzed over 93,000 vision frame data collected from a test vehicle in real roadways. The performance indicators of the proposed hybrid fusion algorithm are successfully evaluated for the generation of roadway digital maps for autonomous vehicles, with a recall of 0.94, precision of 0.96, and accuracy of 0.92.

• Journal of Digital Convergence
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• v.14 no.8
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• pp.223-232
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• 2016

This study focuses on the new teaching assistance robot platform and the cloud-based education service model to support the server. In the client area we would like to use the teacher assistant robot in elementary school classrooms to utilize the language education service platform. Emerging IoT technology will be adopted to provide a comfortable classroom environment and various media interfaces. Extensive precedent review and case study have been conducted to identify basic requirements of proposed service platform. Embedded system and technology for image recognition, speech recognition, autonomous movement, display, touch screen, IR sensor, GPS, and temperature-humidity sensor were extensively investigated to complete the service. Key findings of this paper are optimized service platform with cloud server system and possibilities of potential smart classroom with intelligent robot by adopting IoT and BIM technology.

• Journal of Digital Contents Society
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• v.18 no.5
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• pp.977-982
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• 2017

In this paper, we propose an AR system which enables monitoring and managing of the operation process of the construction site. In case of the conventional construction managing system, a worker takes several images of the construction site and sends them directly to the supervisory headquarter, which manages the progress of the construction process and checks weather the construction is achieved according to the architectural design or not. Due to the nature of the offline process, the conventional management system has time and monetary constraints, and there exists a disadvantage that it is impossible to make quick decision-making and real-time communication with the work site. In order to minimize these disadvantages, we proposes an AR real-time construction monitoring/management system. In particular, we aim to developed a system based on mobile device so that it can maximize usability. The efficiency of the proposed system is verified through several experiments and implementation results.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.2
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• pp.109-120
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• 2017

Groundwater seepage into a tunnel is one of the main causes triggering tunnel collapse and the consequent ground subsidence. Thus, it is important to estimate adequately the groundwater inflow rate and porewater pressure change during tunneling with time elapse. In current practice, Goodman's analytical solution (or image tunnel method) assuming homogeneous ground condition around a tunnel is commonly used for estimating groundwater inflow rate. However, the generally-used analytical solution for estimating groundwater inflow rate does not consider groundwater level drawdown and permeability change with depth, and the inflow rate can be overestimated in design phase. In this study, parametric study was performed in order to investigate the effect of groundwater level drawdown and permeability reduction with depth, and transient flow analysis was carried out for studying the inflow rate change as well as groundwater level and porewater pressure change around a tunnel with time elapse.

• Journal of the Korea Institute of Building Construction
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• v.15 no.4
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• pp.433-439
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• 2015

The aim of this study is to suggest basic data about efficient motivation plans for improving the image of the design and Construction Management (CM) field and enhancing professional consciousness of employees. The major findings and conclusions of this study are as follows. First, the employees in design firms had a relatively high level of dissatisfaction with the 'Reduction of work hours', and those in CM companies had a relatively high level of dissatisfaction with the 'Fringe benefit conditions'. Second, when the effects of the items of job satisfaction on overall job satisfaction were analyzed through factor analysis, job performance satisfaction had the biggest effect on the employees in design firms, and intrinsic reward and opportunity satisfaction had the biggest effect on those in CM companies.

• PNF and Movement
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• v.17 no.2
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• pp.329-337
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• 2019

Purpose: Ultrasound imaging is commonly used to measure the pennation angle of human skeletal muscles in vivo. However, manual assessment of the pennation angle using ultrasound images is subjective and time-consuming and requires a high level of examiner skill. The architectural analysis of human skeletal muscles is thus challenging. Automated approaches using image processing techniques are therefore required to estimate the pennation angle in ultrasound images. The purpose of this study was thus to assess the intra-tester and inter-tester reliability and validity of the pennation angle using an automatic measurement program. Methods: Twenty-two healthy young adults (mean age = 22.55 years) with no medical history of neurological or musculoskeletal disorders voluntarily participated in this study. Ultrasound imaging was used to measure the pennation angle of the gastrocnemius muscle at rest. One examiner acquired images from all the participants. The intra-tester and inter-tester reliability were evaluated using the intraclass correlation coefficient (ICC) to estimate reliability. Validity was measured using Pearson's correlation coefficient. Results: The intra-rater reliability was excellent for the automatic pennation angle measuring program and the manual pennation angle assessment method (ICC>0.95). The inter-rater reliability was also excellent for both methods (ICC>0.93). All the correlation coefficients for the automatic pennation angle measuring program and the manual pennation angle assessment method were 0.79, which indicated a significantly positive correlation (p<0.05). Conclusion: Pennation angle measurement using the automatic pennation angle measuring program showed acceptable reliability and validity. This study therefore demonstrated that the automatic measuring program was able to automatically measure the pennation angle of skeletal muscles using ultrasound images, and thus made it easy to investigate skeletal muscle architecture.

• Journal of Industrial Convergence
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• v.20 no.7
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• pp.73-78
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• 2022

This paper is a study on locality in architecture in Jeju with the theme of locality of architecture. This paper, as the last research paper in this series of studies, is a paper that verifies whether there is anything other than the locality revealed in the categories of 'hermeneutic' and 'phenomenal'. To this end, in this paper, the regional characteristics of the buildings of five Jeju IT companies were analyzed. As a result, the elements reflected in the architecture in terms of the locality of Jeju were quite insufficient. This can be seen as a result of the fact that the corporate image is important in terms of the architecture of an IT company. Nevertheless, if we summarize the elements that reflect the characteristics of Jeju in IT architecture, it is the wind and oreum used as architectural concepts, and Jeju stone used as the exterior finish. In conclusion, it could be seen that the regional characteristics of wind, oreum, and Jeju stone were used in IT architecture, and it was also found that these characteristics were within the scope of interpretive locality and phenomenal locality. Soon, it was found that the locality of Jeju architecture was within the hermeneutic and phenomenal category.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.4
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• pp.621-631
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• 2023

Adversarial training improves the robustness of deep neural networks for adversarial examples. However, the previous adversarial training method focuses only on the adversarial loss function, ignoring that even a small perturbation of the input layer causes a significant change in the hidden layer features. Consequently, the accuracy of a defended model is reduced for various untrained situations such as clean samples or other attack techniques. Therefore, an architectural perspective is necessary to improve feature representation power to solve this problem. In this paper, we apply an attention module that generates an attention map of an input image to a general model and performs PGD adversarial training upon the augmented model. In our experiments on the CIFAR-10 dataset, the attention augmented model showed higher accuracy than the general model regardless of the network structure. In particular, the robust accuracy of our approach was consistently higher for various attacks such as PGD, FGSM, and BIM and more powerful adversaries. By visualizing the attention map, we further confirmed that the attention module extracts features of the correct class even for adversarial examples.