• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.2
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• pp.3-11
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• 2018

Korea has achieved a rapid economic development and with the increase in population and national income and the expansion of social and economic activities, energy consumption has rapidly increased too. Energy consumption per head has constantly increased and currently, power consumption per head is 7.5 times bigger than in 1985. Buildings occupy 25% of total energy consumption and especially, 50% of total energy is consumed for heating and cooling. In this situation, multi-family housing, which has constantly been increased, has an energy saving rate of 1.9%, which is the lowest level and this makes the government's energy policy for sustainable energy system development useless. Besides, energy consumption leads to secondary problems, such as air, water and marine pollution and heat pollution and wastewater/drainage and the increased use of fossil fuel is a fundamental reason for ozone layer destruction and global warming. Therefore, efficient energy consumption plans are required. This study aims to analyze energy performance in each block type of high-rise and diversified multi-family housing that accounts for 60% of all the housing forms, depending on the variations in stories through BIM-based energy simulation. For this study, four representative block types were selected, based on the multi-family floor plan, which is certified for energy performance evaluation and they were applied to the floor plan of a multi-family house that is scheduled to be built. Then BIM modeling was conducted from the fifth story to the 40th story at an intervals of 5 stories and based on the finding, energy characteristics of each block type and energy performance depending on the variations in stories were analyzed. It is considered that this would serve as objective data for block type and block story decision of energy performance-based multi-family housing.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.2
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• pp.55-67
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• 2023

This study aims to develop a model that can automatically identify the rooftop shape of apartment buildings using GIS and machine learning algorithms, and apply it to analyze the relationship between rooftop shape and characteristics of apartment complexes. A database of rooftop data for each building in an apartment complex was constructed using geospatial data, and individual buildings within each complex were classified into flat type, tower type, and mixed types using the random forest algorithm. In addition, the relationship between the proportion of rooftop shapes, development density, height, and other characteristics of apartment complexes was analyzed to propose the potential application of geospatial information in the real estate field. This study is expected to serve as a basic research on AI-based building type classification and to be utilized in various spatial and real estate analyses.

• Journal of the Korean Geosynthetics Society
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• v.14 no.4
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• pp.117-127
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• 2015

Recently, there has been a string of negligent accidents for the retaining wall and slope. In order to measure the ground deformation for the MSE wall, the authors carried out the model test to assess behavioral characteristics of geogrid MSE walls in active failure state with different conditions of geogrid reinforcement. The models are built in the soil container box having dimension, 100 cm long, 90 cm height, and 10 cm wide. The reinforcement used in the model test is geogrid (polyvinyl chloride, PVC). Three geogrids are sized by $30cm{\times}60cm$, $30cm{\times}70cm$, $30cm{\times}80cm$ (width ${\times}$ length) respectively. In this study, the laboratory model tests represented for several conditions of the MSE wall, and then its results were compared to 2D FE analysis.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.653-659
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• 2018

The accurate prediction of construction cost is a key factor in a project's success. However, it is hard to predict the construction costs in the planning stages rapidly and precisely when drawings, specifications, construction cost calculation statements are incomplete, among other factors. Accurate construction-cost prediction in the planning stage of a project is also important for project feasibility studies and successful completion. Therefore, various techniques have been applied to accurately predict construction costs at an early stage when project information is limited. There are many factors that affect the construction cost prediction. This paper presents a construction-cost prediction method as multiple regression model with seven construction factors as independent variables. The method was used to predict the construction cost of a local housing union project, and the error rate was 4.87%. It is not possible to compare the cost of the project at the planning stage of the local housing union project, but it has high prediction accuracy compared to the unit price of an existing unit area. It is likely to be applied in construction-cost calculation work and to contribute to the establishment of the budget for the local housing union project.

• Journal of the Korean Society of Food Science and Nutrition
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• v.40 no.2
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• pp.235-244
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• 2011

The physicochemical properties and quality changes in salted and dried brown croaker products using deep seawater salt were investigated for preparation with different pretreatment, salting and drying conditions. Optimum salt concentration, salting time and drying time for product were 20% of body weight, 12 hrs at room temperature ($25{\pm}2^{\circ}C$), and 24 hrs at $30{\pm}2^{\circ}C$, respectively. The volatile basic nitrogen (VBN), peroxide value (POV), viable cell count and acid value (AV) of viscera and blade removed products were 18.9~22.4 mg%, 21.0~32.5 meq/L, and 2.3~4.4 mg/mL, $2.0\sim3.5{\times}10^3$ CFU/g, respectively and only viscera removed products were 31.2~38.1 mg%, 40~55.2 meq/L, 7.0~11.5 mg/mL, $4.1\sim5.5{\times}10^3$ CFU/g, respectively. Changes in quality of salted and dried brown croaker products were investigated during storage at room temperature and $5{\pm}2^{\circ}C$. The POV, AV and viable cell counts of salted and dried brown croaker products increased in commercial salt used and only viscera removed products compared with deep seawater salt used and viscera and blade removed products during storage time. Results in this study showed that the deep seawater salt was very effective for quality control of salted and dried brown croaker products and pretreatment method was a very important factor for preparation products. The optimum conditions for preparation of salted and dried brown croaker product were 20% of body weight for salt concentration, 12 hrs at $25{\pm}2^{\circ}C$ for salting time, and 24 hrs at $30{\pm}2^{\circ}C$ for drying time. Optimum storage time for quality maintenance was 14 days at $5{\pm}2^{\circ}C$.