• Journal of KIBIM
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• v.4 no.2
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• pp.1-9
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• 2014

As interest in green building has increased, construction market has evolved through BIM-based architecture also, BIM-based technologies have been developed simultaneously. Due to this aspect, the need of environmental analysis software utilizing BIM data became essential. This study shows that BIM-based integrated module provides objective analysis to proceed quick decision-making for a proposal. In addition to that, this integrated module creates a model through BIM data to analyze and report residential environment and energy consumption such as, daylight, view, ventilation and privacy in order to practically apply the BIM technology from the schematic design.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2014.11a
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• pp.96-97
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• 2014

Green Frame is a column-beam structure built by steel frame joints embedded in the columns and beams. Here, the steel frame embedded in the columns and beams is not a standardized product, instead it needs to be order-produced. The quantity for each steel frame size should be calculated to estimate the quantity of steel frames to be manufactured. However, it is highly time-consuming and requires a lot of effort in calculating the quantity of steel frames, for there are a wide range of steel frame types that are embedded in the columns and beams. To solve this problem, the study proposes an algorithm for calculation of the amount of steel frames with ease and promptness. When a program is developed using the algorithm proposed in the study in connection to the information on precast concrete members prepared in the design phase, it is anticipated that the manpower required as well as the manufacturing time will be decreased.

• Proceedings of the Korean Institute of Interior Design Conference
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• 2005.05a
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• pp.207-211
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• 2005

This research is aimed to study the finishing material applied in interior space for improving residential environment. First of all, it finds out what is 'Sick Building Syndrome' and 'Sick House Syndrome', how harmful to human body about indoor air pollution substance (such as volatility organic compound, formaldehyde) and investigate the effect when the environment-friendly finishing material is used. Secondly, classify and examine all kind of finishing material applied in interior space. Finally, after emphasize the importance of environment-friendly finishing material from domestic or overseas, this research suggest the basic information of environment-friendly finishing material in order to use in the future buildings.

• Korean Journal of Remote Sensing
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• v.28 no.2
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• pp.203-214
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• 2012

The physical environment of urban areas covered mostly by concrete and asphalt is the main cause of the urban heat island effect, primarily becoming apparent through increased land surface temperature. This study examined the effect of different urban land cover types on the land surface temperature using MODIS, Landsat ETM+ and RapidEye satellite data. As a result, the remote sensing based land surface temperature showed a marked difference according to the land use pattern in the case study of Ilsan new city. The high-rise apartment residential districts with less building-to-land ratio and higher green area ratio revealed lower land surface temperature than the low-story single-family housing districts characterized by relatively high building-to-land ratio and low green area ratio. From the view of climate zone and land cover types, there is a strong linear correlation between the impervious land cover ratio and the land surface temperature; the land surface temperature increases as the impervious built-up areas expand. In contrast, vegetation;water and shadow areas affect the decrease of land surface temperature. There is also a negative (-) correlation between NDVI and land surface temperature but the seasonal variation of NDVI can be hardly corrected.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.3
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• pp.83-98
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• 2021

Urban green space is an important component for enhancing urban ecosystem health. Thus, identifying the spatial structure of urban green space is required to manage a healthy urban ecosystem. The Ministry of Environment has provided the level 3 land cover map(the highest (1m) spatial resolution map) with a total of 41 classes since 2010. However, specific urban green information such as street trees was identified just as grassland or even not classified them as a vegetated area in the map. Therefore, this study classified detailed urban green information(i.e., tree, shrub, and grass), not included in the existing level 3 land cover map, using two types of high-resolution(<1m) remote sensing data(i.e., airborne LiDAR and RGB ortho imagery) in Suwon, South Korea. U-Net, one of image segmentation deep learning approaches, was adopted to classify detailed urban green space. A total of three classification models(i.e., LRGB10, LRGB5, and RGB5) were proposed depending on the target number of classes and the types of input data. The average overall accuracies for test sites were 83.40% (LRGB10), 89.44%(LRGB5), and 74.76%(RGB5). Among three models, LRGB5, which uses both airborne LiDAR and RGB ortho imagery with 5 target classes(i.e., tree, shrub, grass, building, and the others), resulted in the best performance. The area ratio of total urban green space(based on trees, shrub, and grass information) for the entire Suwon was 45.61%(LRGB10), 43.47%(LRGB5), and 44.22%(RGB5). All models were able to provide additional 13.40% of urban tree information on average when compared to the existing level 3 land cover map. Moreover, these urban green classification results are expected to be utilized in various urban green studies or decision making processes, as it provides detailed information on urban green space.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.2
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• pp.42-54
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• 2023

The population is concentrated in the metropolitan areas in Korea, and low-density residential areas are transforming into high density residential areas through redevelopment to meet this demand. However, large-scale redevelopment in a short period of time has a negative impact on the urban climate, such as generating a heat island effect due to the reduction of urban green areas. In this study, the change in surface temperature from 2013 to 2022 in the redevelpment areas of Godeok-dong and Dunchon-dong, Gangdong-gu, Seoul, was analyzed using Landsat 8 satellite images. In the Godeok-dong area, the difference in surface temperature was analyzed for the target redevelopment area, forest area, mixed forest and urban area, and low density residential area. In the Dunchon-dong area, the difference in surface temperature was analyzed for the target redevelopment area, forest area, and low density residential area. The difference in surface temperature was analyzed through multiple regression analysis conducted yearly over the three different stages in redevelopment period. The results from the multiple regression analysis show that in both areas, the land surface temperature of target redevelopment area was higher than that of the forest area and lower than low density residential area. It can be seen that these results occurred because the low-density residential area in Godeok-dong and Dunchon-dong had a lower green area ratio and a higher building-to-land ratio than the target redevelopment area. The results of this study suggest that even if low-density residential areas are transforming into high-density areas, adjusting the management of green areas and building-to-land ratio can contribute to lessen urban heat island effect.

• Journal of Korean Society of Forest Science
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• v.100 no.2
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• pp.273-282
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• 2011

This study was aimed to identify determinants of users' satisfaction and behavioral intention in Jirisan trail of Korea and provide effective trail building and management strategy. The result of survey by 645 trail users showed that four dimensions were derived from 14 satisfaction items, which were experiential resources, cost resources, information, amenities. Of these dimensions, experiential resources along trails including natural environment, the level of trail development, trail condition, cultural & tourist resources, kindness of residents had the greatest effect on overall satisfaction and behavioral intention, which included revisit intention, recommendation intention and continuance intention. According to analysis by detailed variables, natural environment, road signs, kindness of residents and related information significantly affected overall satisfaction and behavioral intention.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4345-4363
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• 2021

Deep Learning as a Service (DLaaS), utilizing the cloud-based deep neural network models to provide customer prediction services, has been widely deployed on mobile cloud computing (MCC). Such services raise privacy concerns since customers need to send private data to untrusted service providers. In this paper, we devote ourselves to building an efficient protocol to classify users' images using the convolutional neural network (CNN) model trained and held by the server, while keeping both parties' data secure. Most previous solutions commonly employ homomorphic encryption schemes based on Ring Learning with Errors (RLWE) hardness or two-party secure computation protocols to achieve it. However, they have limitations on large communication overheads and costs in MCC. To address this issue, we present LeHE4SCNN, a scalable privacy-preserving and communication-efficient framework for CNN-based DLaaS. Firstly, we design a novel low-expansion rate homomorphic encryption scheme with packing and unpacking methods (LeHE). It supports fast homomorphic operations such as vector-matrix multiplication and addition. Then we propose a secure prediction framework for CNN. It employs the LeHE scheme to compute linear layers while exploiting the data shuffling technique to perform non-linear operations. Finally, we implement and evaluate LeHE4SCNN with various CNN models on a real-world dataset. Experimental results demonstrate the effectiveness and superiority of the LeHE4SCNN framework in terms of response time, usage cost, and communication overhead compared to the state-of-the-art methods in the mobile cloud computing environment.

• Korean Journal of Construction Engineering and Management
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• v.13 no.6
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• pp.133-142
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• 2012

With the recent changes in building environments such as low-carbon green growth, there have been increasing demands for the new building system that is eco-friendly and can maximize efficiency such as the unit modular system. For the unit modular system, more than 80% of the whole process is carried out in the factory while in the field, mostly unit module assembling and finish work are done. Thus, the quality at the pre-construction stage when design and manufacturing are done determines the quality of the building as a whole. In the country, the unit modular method was first applied in 2003 to school buildings and has gradually expanded afterwards, but due to the lack of examples and related information as well as the small scale of modular manufacturers, its characteristics have not been sufficiently reflected in design, manufacturing and field constructions. This study, as an attempt to improve the design quality of unit modular buildings, points to the problem in manufacturing and field construction, compares and analyzes its causes, and suggests major points to be considered in the early stage of designing the unit modular buildings.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2010.06a
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• pp.94-102
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• 2010

These days the land category is the most specific basis of legal for land use or land use form that is determined by the main use of land. Even if same land building site, it is used very various like a detached house, a row house, a multiplex house, a villa, an apartment, a mixed-use Apartments, commercial building, fallow land etc. There is a need of variety analysis in order to apply greenhouse gas emission or statistics assessment for standard of classification. Therefore, This study measured carbon dioxide by for different government agencies of maps by land use time, season, elevation, space, area of floating population. As a result, The emission characteristic was high l.78 times, on average of l.35 times in winter compared with summer, when the temperatures increased 11C, the carbon dioxide is 22ppm high in the afternoon, A commercial building is high 4.04 times compare with detached house.