• Korean Journal of Construction Engineering and Management
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• v.22 no.1
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• pp.3-12
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• 2021

In the remodeling projects, clients without architectural expertise have limitations in presenting requirements accurately. In some cases, designers and contractors may not recognize their demands exactly, and deliver final products that are different from the clients' intentions. 3D modeling visualizing final products in previous has been regarded as a solution to enhance understanding and communication. However, this approach has the limitation that the final results are presented as a virtual outputs. In the remodeling project, an alternative, mixed-reality, is likely to reinforce the reality as it enables to present remain structure and the parts to be built together. This paper examines the mixed reality as a solution to support decision making of clients and practitioners in remodeling projects. The examinations is conducted in high-rise office remodeling projects by means of action-research. Clients and practitioners, overview product models presented in the format of 2D drawings, BIM and mixed reality asked to evaluate the effectiveness of each methods in 12 standards. The results have shown that mixed reality has improved the sense of reality, making it easier to predict results, but recognizing patterns is difficult in some areas such as the floor, and it caused dizziness.

• Korean Journal of Construction Engineering and Management
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• v.22 no.1
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• pp.36-46
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• 2021

With an increasing trend toward high-rise modular construction, the simultaneous use of tower cranes at a modular construction site has recently been observed. Tower crane layout planning (TCLP) has a significant effect on cost, duration, safety and productivity of a project. In a modular construction project, particularly, poor decision about the layout of tower cranes is likely to have negative effects like additional employment of cranes and redesign, which will lead to additional costs and possible delays. It is, therefore, crucial to conduct thorough inspection of field conditions, lifting materials, tower crane capacity to make decisions on the layout of tower cranes. However, several challenges exist in planning for a multi-crane construction site in terms of safety and collaboration, which makes planning with experience and intuition complicated. This paper suggests a multi-objective optimization model for selection of the number of tower cranes, their models and locations, which minimizes cost and conflict. The proposed model contributes to the body of knowledge by showing the feasibility of using multi-objective optimization for TCLP decision-making process with consideration of trade-offs between cost and conflict.

• Korean Journal of Legislative Studies
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• v.24 no.1
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• pp.135-170
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• 2018

The recent success of populist parties and candidates in the US and European countries leads to a massive amount of empirical research on populism, a deviant form of representative democracy. Much ink has been spilled to define populism and to identify the causes of its rise and continued success in democratic political system. However, little is known about populist attitudes of individual voters. Using a large-scale online survey fielded in the context of the South Korean presidential election in 2017, this study examines (1) what determines populist attitudes of South Korean voters and (2) how populist attitudes are associated with evaluations of political parties, candidates, and political issues. Statistical analysis reveals that people high on populism are more likely to support an underdog left-wing political party and its presidential candidate, and are less likely to support policies implemented or proposed under the auspices of the Park Geun-hye administration. These findings do not necessarily suggest the inherent affinity between populism and left-wing ideology; rather, it implies populist attitudes happened to appear in 2017, in reactions to lack of confidence in the previous government.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.426-433
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• 2021

Investment in public sector information services has been on the rise in recent years. The supply of high-speed Internet and smartphones has become more common, and the stability of the information system provided to the public in the public sector has become an important management factor. In other words, tasks such as handling civil complaints and issuing certificates by public institutions, financial transactions by banks, customs clearance work, and e-commerce by individuals or institutions are mostly done online. Therefore, how to deal with obstacles arising from the information system, which is in charge of important civil service affairs, is becoming a very important issue. In other words, in the case of a disability that does not function normally even for a short period of time, various problems can occur when the work is delayed, as well as causing serious financial damage to the civil petitioner. This could be accompanied by a decline in public confidence and various other damages such as filing civil complaints. The reasons for the occurrence of information system failures are very diverse and realistically difficult to predict when. Among the various measures to cope with disability, this paper proposed a plan to establish a disability situation notification system that can minimize confusion caused by disability in the event of a homepage malfunction. The proposed disability situation notification system was established in the public IDC environment to show the possibility of utilization.

• Journal of IKEEE
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• v.25 no.2
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• pp.267-272
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• 2021

Recently, attention has been focused on renewable energy and carbon neutrality to resolve fossil energy depletion and environmental problems. In addition, high-rise urban buildings and an increase in building energy are rapidly increasing. There are many restrictions on installing solar power in urban areas. In addition, as buildings become taller, a lot of low-light environments in which shade is formed occur. Therefore, in this study, we intend to develop a power plant capable of generating electric power in an outdoor low-light environment and indoor lighting environment. The power plant in a low-light environment used a dye-sensitized solar cell. A unit cell and a 20cm×20cm module were manufactured, and the electrical characteristics of the power plant were measured using light sources of LED, halogen lamp, and 3-wavelength lamp. The photoelectric conversion efficiency of the unit cell was 17.2%, 1.28%, 19,2% for each LED, halogen lamp, and 3-wavelength lamp, and the photoelectric conversion efficiency of the 20cm×20cm module was 10.9%, 8.7%, and 11.8%, respectively. In addition, the maximum power value of the module was 13.1mW, 15.7 mW, and 14.2 mW for each light source, respectively, confirming the possibility of power generation in a low-light environment

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.2
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• pp.93-101
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• 2021

Recently, with the urban redevelopment and the spread of the planned cities, there is increasing interest in the wind environment, which is related not only to design of buildings and landscaping but also to the comfortability of pedestrians. Numerical analysis for wind environment prediction is underway in many fields, such as dense areas of high-rise building or composition of the apartment complexes, a precisive 3D building model is essentially required in this process. Many studies conducted for wind environment analysis have typically used the method of creating a 3D model by utilizing the building layer included in the GIS (Geographic Information System) data. These data can easily and quickly observe the flow of atmosphere in a wide urban environment, but cannot be suitable for observing precisive flow of atmosphere, and in particular, the effect of a complicated structure of a single building on the flow of atmosphere cannot be calculated. Recently, drone photogrammetry has shown the advantage of being able to automatically perform building modeling based on a large number of images. In this study, we applied photogrammetry technology using a drone to evaluate the flow of atmosphere around two buildings located close to each other. Two 3D models were made into an automatic modeling technique and manual modeling technique. Auto-modeling technique is using an automatically generates a point cloud through photogrammetry and generating models through interpolation, and manual-modeling technique is a manually operated technique that individually generates 3D models based on point clouds. And then the flow of atmosphere for the two models was compared and analyzed. As a result, the wind environment of the two models showed a clear difference, and the model created by auto-modeling showed faster flow of atmosphere than the model created by manual modeling. Also in the case of the 3D mesh generated by auto-modeling showed the limitation of not proceeding an accurate analysis because the precise 3D shape was not reproduced in the closed area such as the porch of the building or the bridge between buildings.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1615-1627
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• 2020

The purpose of this study is to compare and analyze the performance of KOMPSAT-3 Digital Surface Model (DSM) made in overseas testbed area. To that end, we collected the KOMPSAT-3 in-track stereo image taken in San Francisco, the U.S. The stereo geometry elements (B/H, converse angle, etc.) of the stereo image taken were all found to be in the stable range. By applying precise sensor modeling using Ground Control Point (GCP) and DSM automatic generation technique, DSM with 1 m resolution was produced. Reference materials for evaluation and calibration are ground points with accuracy within 0.01 m from Compass Data Inc., 1 m resolution Elevation 1-DSM produced by Airbus. The precision sensor modeling accuracy of KOMPSAT-3 was within 0.5 m (RMSE) in horizontal and vertical directions. When the difference map was written between the generated DSM and the reference DSM, the mean and standard deviation were 0.61 m and 5.25 m respectively, but in some areas, they showed a large difference of more than 100 m. These areas appeared mainly in closed areas where high-rise buildings were concentrated. If KOMPSAT-3 tri-stereo images are used and various post-processing techniques are developed, it will be possible to produce DSM with more improved quality.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.4
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• pp.55-63
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• 2021

Interest in smart parks has been increasing due to the recent rapid rise of smart cities, but concerns are growing over the development of technology-oriented smart parks. The purpose of this study is to evaluate the relative importance of park services through Focus Group Interviews and the Analytic Hierarchy Process (AHP) to develop user-oriented smart parks in the future. To this end, literature on park functions and services was reviewed, and interviews with experts in the field of landscape architecture and IT were conducted to derive service items. The AHP model consisted of four values, and 15 park services were established and used to survey 38 landscape experts. As a result, services for improving the park's essential functions, such as contact with nature, relaxation, and exercise-walking, were deemed important. Services related to the environment and safety in response to climate change, such as the amelioration of pollution and heatwaves were also high. The importance of social integration services was relatively low, but it was considered an important service to when enhancing community participation. Future smart parks should enhance the health benefits of contact with nature rather than implementing excessive artificial facilities and technology. Additionally, smart technology will need to be applied based on users' needs while reflecting local characteristics. Efforts should be made to enhance user intimacy and improve the understanding of smart parks by strengthening public relations education.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1709-1722
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• 2022

The rise in temperature induced by global warming caused in El Nino and La Nina, and abnormally changed the temperature of seawater. Rainfall concentrates in some locations due to abnormal variations in seawater temperature, causing frequent abnormal floods. It is important to rapidly detect flooded regions to recover and prevent human and property damage caused by floods. This is possible with synthetic aperture radar. This study aims to generate a model that directly derives flood-damaged areas by using modified U-NET and TerraSAR-X images based on Multi Kernel to reduce the effect of speckle noise through various characteristic map extraction and using two images before and after flooding as input data. To that purpose, two synthetic aperture radar (SAR) images were preprocessed to generate the model's input data, which was then applied to the modified U-NET structure to train the flood detection deep learning model. Through this method, the flood area could be detected at a high level with an average F1 score value of 0.966. This result is expected to contribute to the rapid recovery of flood-stricken areas and the derivation of flood-prevention measures.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.3
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• pp.179-189
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• 2022

Ice and water droplets rise and fall above the freezing altitude under the effects of strong updrafts and downdrafts, grow into hail, and then fall to the ground in the form of balls or irregular lumps of ice. Although such hail, which occurs in a local area within a short period of time, causes great damage to the agricultural and forestry sector, there is a paucity of domestic research toward predicting hail. The objective of this study was to introduce Land-Atmosphere Modeling Package (LAMP) hail prediction and measure its performance for 50 hail events that occurred from January 2020 to July 2021. In the study period, the frequency of occurrence was high during the spring and during afternoon hours. The average duration of hail was 15 min, and the average diameter of the hail was 1 cm. The results showed that LAMP predicted hail events with a detection rate of 70%. The hail prediction performance of LAMP deteriorated as the hail prediction time increased. The radar reflectivity of actual cases of hail indicated that the average maximum reflectivity was greater than 40 dBZ regardless of altitude. Approximately 50% of the hail events occurred when the reflectivity ranged from 30~50 dBZ. These results can be used to improve the hail prediction performance of LAMP in the future. Improved hail prediction performance through LAMP should lead to reduced economic losses caused by hail in the agricultural and forestry sector through preemptive measures such as net coverings.