• Korean Association of Arts Management
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• no.58
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• pp.121-152
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• 2021

This study attempted to analyze the effect of the color series of artworks installed as environmental stimuli in commercial spaces on the satisfaction of visitors and the moderating effect of the relationship. To this end, based on the SOR model of Stimulate-Organism-Response applied to burial environment research in the field of environmental psychology, and the preceding research using the SOR model, artwork color series(S)-mood and spaace amenity(O)-A research framework for satisfaction(R) was developed. In the experiment, an online questionnaire was conducted for domestic college students and graduate students by producing images with two conditions depending on the case where warm colors and cold colors were installed for the color series of artworks. As a result of verifying the difference in satisfaction of respondents corresponding to the two conditions through regression analysis, it was found that the warm color(vs. cold color) of the artwork color series induces higher visitor satisfaction. In addition, as a result of verifying the controlling factors of mood and space amenity variables in this relationship of influence, a significant moderating effect was found when the positive mood of warm colors(vs. cold colors) in the artwork color series was felt higher than the average. And, of the four types of space amenity, it was found that a significant moderating effect appeared when only comfort and aesthetics were measured as moderating variables. The result of this study proves that the warm color series of artworks that stimulate the physical environment of commercial spaces has a more positive effect on the satisfaction of visitors than the cold color series, and this is reinforced by positive mood, comfort, and aesthetics. It adds understanding and provides useful implications for marketing strategies for building an effective spatial image.

• Journal of the Korean Regional Science Association
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• v.38 no.4
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• pp.45-58
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• 2022

This study intends to compare the factors influencing the location of international schools on apartment sales and monthly rent prices for Songdo International School in Incheon, which has a history of more than 10 years. At the latest point, 10 years after the opening of the school, apartments in areas near international schools are divided into sales and monthly rent markets and analyzed. Songdo International City, designed as a planned city, was set as a spatial scope, and 2018-19, which is a relatively stable real estate period, was set as a temporal analysis period to avoid the overheating period of real estate after COVID-19. Considering the urban image of the "New Special Education Zone," such as the opening of Songdo Campus by private academies formed around international schools and domestic and foreign universities, the multiple regression model was applied based on the traditional Hedonic price model. As a result of the empirical analysis, first, differences in the price determinants of sales and monthly rent were confirmed. Second, the price influence of international schools was much higher than that of the variables. Third, the influence of international schools was more pronounced in the monthly rent market than in the sales market.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.3
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• pp.11-20
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• 2022

The main purpose of this study is to investigate the applicability of the shear wave tomography technology as a non-destructive testing method to evaluate the debonding between the track concrete layer (TCL) and the hydraulically stabilized based course (HSB) of concrete slab tracks for the Korea high-speed railway system. A commercially available multi-channel shear wave measurement device (MIRA) is used to evaluate debonding defects in full-scaled mock-up test specimen that was designed and constructed according to the Rheda 200 system. A part of the mock-up specimen includes two artificial debonding defects with a length and a width of 400mm and thicknesses of 5mm and 10mm, respectively. The tomography images obtained by a MIRA on the surface of the concrete specimens are effective for visualizing the debonding defects in concrete. In this study, a simple image processing method is proposed to suppress the noisy signals reflected from the embedded items (reinforcing steel, precast sleeper, insert, etc.) in TCL, which significantly improves the readability of debonding defects in shear wave tomography images. Results show that debonding maps constructed in this study are effective for visualizing the spatial distribution and the depths of the debondiing defects in the railway concrete slab specimen.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.979-986
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• 2022

In this study, the virtual exhibition using 3D architectural space was analyzed in terms of the viewer's experience. For this purpose, the analysis items of the virtual architectural space include whether the actual architectural space is reproduced, the introduction of surreal elements, the degree of freedom of movement and circulation, the level of photorealism of spatial expression, the level of reproduction of the exhibits and information provision method, and the interaction with other participants. Six virtual exhibition projects designed by a well-known architect were selected and analyzed. Three directions were found through the analysis. First, even when designing a virtual exhibition space with a high degree of freedom, there is a tendency to present a familiar architectural environment. Second, the current method of creating a virtual architectural space is that the method using a 360-degree rendering image and the method using a game engine coexist with pros and cons. Third, the interaction between participants in the virtual exhibition is implemented only by using a game engine. It is expected that the virtual space production environment using the game engine to be developed will become more advantageous in the future.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.30-31
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• 2009

Early detection of schedule delay in field construction activities is vital to project management. It provides the opportunity to initiate remedial actions and increases the chance of controlling such overruns or minimizing their impacts. This entails project managers to design, implement, and maintain a systematic approach for progress monitoring to promptly identify, process and communicate discrepancies between actual and as-planned performances as early as possible. Despite importance, systematic implementation of progress monitoring is challenging: (1) Current progress monitoring is time-consuming as it needs extensive as-planned and as-built data collection; (2) The excessive amount of work required to be performed may cause human-errors and reduce the quality of manually collected data and since only an approximate visual inspection is usually performed, makes the collected data subjective; (3) Existing methods of progress monitoring are also non-systematic and may also create a time-lag between the time progress is reported and the time progress is actually accomplished; (4) Progress reports are visually complex, and do not reflect spatial aspects of construction; and (5) Current reporting methods increase the time required to describe and explain progress in coordination meetings and in turn could delay the decision making process. In summary, with current methods, it may be not be easy to understand the progress situation clearly and quickly. To overcome such inefficiencies, this research focuses on exploring application of unsorted daily progress photograph logs - available on any construction site - as well as IFC-based 4D models for progress monitoring. Our approach is based on computing, from the images themselves, the photographer's locations and orientations, along with a sparse 3D geometric representation of the as-built scene using daily progress photographs and superimposition of the reconstructed scene over the as-planned 4D model. Within such an environment, progress photographs are registered in the virtual as-planned environment, allowing a large unstructured collection of daily construction images to be interactively explored. In addition, sparse reconstructed scenes superimposed over 4D models allow site images to be geo-registered with the as-planned components and consequently, a location-based image processing technique to be implemented and progress data to be extracted automatically. The result of progress comparison study between as-planned and as-built performances can subsequently be visualized in the D4AR - 4D Augmented Reality - environment using a traffic light metaphor. In such an environment, project participants would be able to: 1) use the 4D as-planned model as a baseline for progress monitoring, compare it to daily construction photographs and study workspace logistics; 2) interactively and remotely explore registered construction photographs in a 3D environment; 3) analyze registered images and quantify as-built progress; 4) measure discrepancies between as-planned and as-built performances; and 5) visually represent progress discrepancies through superimposition of 4D as-planned models over progress photographs, make control decisions and effectively communicate those with project participants. We present our preliminary results on two ongoing construction projects and discuss implementation, perceived benefits and future potential enhancement of this new technology in construction, in all fronts of automatic data collection, processing and communication.

• Korea Science and Art Forum
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• v.27
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• pp.101-114
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• 2017

Based on the relationship between urban public space, urban lighting and the sense of place, this paper aims to analyze the lighting environment types with the sense of place and their characteristics. First, with the theory study as the research foundation, it extracts six spatial factors of public space lighting design and then analyzes 12 relevant cases on the basis. Finally, it divides the 12 cases into four types, Basic types, Storytelling, Interactive and Multi-Media and analyzes the core design factor and characteristics of various types. The results show that: first, functionality, sustainability and aesthetics are the basic factors to realize the urban public space lighting places. Second, the six cases of "Storytelling" show that the theme of specific areas, namely the exploration of "story" is conducive for lighting design to form clear and definite environment recognition. Third, for "Interactive" and "Multi-Media", the intervention of new media technology and new lighting way has made the wide expansion of urban lighting design connotation and extension. The research results show that strengthening the urban location performance by the lighting design could improve the city image, which provides the basis for the development of urban public space lighting design.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.407-415
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• 2008

This study presents the methodology to link with aerial photos for advancing the accuracy of topographic survey data that is used to calculate water volume in urban stream. First, GIS spatial interpolation technique as Inverse Distance Weight (IDW) and Kriging was applied to construct the terrain morphology to the sand-bar and grass area using cross-sectional survey data, and also validation point data was used to estimate the accuracy of created topographic data. As the result of comparison, IDW ($d^{-2}_{ij}$, 2nd square number) in Sand-bar area and Kriging Spherical model in grass area showed more efficient results in the construction of topographic data of river boundary. But the differences among interpolation methods are very slight. Image classification method, Minimum Distance Method (MDM) was applied to extract sand-bar and grass area that are located to river boundary efficiently and the elevation value of extracted layers was allocated to the water level point value. Water volume with topographic data from aerial photos shows the advanced accuracy of 13% (in sand-bar) and 12% (in grass) compared to the water volume of original terrain data. Therefore, terrain analysis method in river linking with aerial photos is efficient to the monitoring about sand-bar and grass area that are located in the downstream of Dam in flooding season, and also it can be applied to calculate water volume efficiently.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.245-257
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• 2023

The representative crop in the Republic of Korea, rice, is cultivated over extensive areas every year, which resulting in reduced resistance to pests and diseases. One of the major rice diseases, rice blast disease, can lead to a significant decrease in yields when it occurs on a large scale, necessitating early detection and effective control of rice blast disease. Drone-based crop monitoring techniques are valuable for detecting abnormal growth, but frequent image capture for potential rice blast disease occurrences can consume significant labor and resources. The purpose of this study is to early detect rice blast disease using remote sensing data, such as drone and satellite images, along with weather data. Satellite images was helpful in identifying rice cultivation fields. Effective detection of paddy fields was achieved by utilizing vegetation and water indices. Subsequently, air temperature, relative humidity, and number of rainy days were used to calculate the risk of rice blast disease occurrence. An increase in the risk of disease occurrence implies a higher likelihood of disease development, and drone measurements perform at this time. Spectral reflectance changes in the red and near-infrared wavelength regions were observed at the locations where rice blast disease occurred. Clusters with low vegetation index values were observed at locations where rice blast disease occurred, and the time series data for drone images allowed for tracking the spread of the disease from these points. Finally, drone images captured before harvesting was used to generate spatial information on the incidence of rice blast disease in each field.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1679-1692
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• 2023

South Korea is a country that emits a large amount of pollutants as a result of population growth and industrial development and is also severely affected by transboundary air pollution due to its geographical location. As pollutants from both domestic and foreign sources contribute to air pollution in Korea, the location of air pollutant emission sources is crucial for understanding the movement and distribution of pollutants in the atmosphere and establishing national-level air pollution management and response strategies. Based on this background, this study aims to effectively acquire spatial information on domestic and international air pollutant emission sources, which is essential for analyzing air pollution status, by utilizing high-resolution optical satellite images and deep learning-based image segmentation models. In particular, industrial parks and quarries, which have been evaluated as contributing significantly to transboundary air pollution, were selected as the main research subjects, and images of these areas from multi-purpose satellites 3 and 3A were collected, preprocessed, and converted into input and label data for model training. As a result of training the U-Net model using this data, the overall accuracy of 0.8484 and mean Intersection over Union (mIoU) of 0.6490 were achieved, and the predicted maps showed significant results in extracting object boundaries more accurately than the label data created by course annotations.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1693-1705
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• 2023

Rural areas, which account for about 90% of the country's land area, are increasing in importance and value as a space that performs various public functions. However, facilities that adversely affect residents' lives, such as livestock facilities, factories, and solar panels, are being built indiscriminately near residential areas, damaging the rural environment and landscape and lowering the quality of residents' lives. In order to prevent disorderly development in rural areas and manage rural space in a planned manner, detection and monitoring of hazardous facilities in rural areas is necessary. Data can be acquired through satellite imagery, which can be acquired periodically and provide information on the entire region. Effective detection is possible by utilizing image-based deep learning techniques using convolutional neural networks. Therefore, U-Net model, which shows high performance in semantic segmentation, was used to classify potentially hazardous facilities in rural areas. In this study, KOMPSAT ortho-mosaic optical imagery provided by the Korea Aerospace Research Institute in 2020 with a spatial resolution of 0.7 meters was used, and AI training data for livestock facilities, factories, and solar panels were produced by hand for training and inference. After training with U-Net, pixel accuracy of 0.9739 and mean Intersection over Union (mIoU) of 0.7025 were achieved. The results of this study can be used for monitoring hazardous facilities in rural areas and are expected to be used as basis for rural planning.