• Journal of Internet Computing and Services
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• v.20 no.5
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• pp.87-94
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• 2019

In this paper, the method of analyzing the unformatted data of consumers accumulated on social networks in the era of the Fourth Industrial Revolution by utilizing data from the service design and social psychology aspects was proposed. First, the fandom phenomenon, which shows subjective and collective behavior in a space on a social network rather than physical space, was defined from a data service perspective. The fandom model has been transformed into a collective level of customer Persona that has been analyzed at a personal level in traditional service design, and social network analysis that analyzes consumers' big data has been presented as an efficient way to pattern and visually analyze it. Consumer data collected through social leasing were pre-processed by column based on correlation, stability, missing, and ID-ness. Based on the above data, the company's brand strategy was divided into active and passive interventions and the effect of this strategic attitude on the growth direction of the consumer's fandom community was analyzed. To this end, the fandom model of consumers was proposed by dividing it into four strategies that the brand strategy had: stand-alone, decentralized, integrated and centralized, and the fandom shape of consumers was proposed as a growth model analysis technique that analyzes changes over time.

• Journal of the Korean Geotechnical Society
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• v.37 no.5
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• pp.5-17
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• 2021

In this study, the shear behavior between pile-sandy soil interface was quantified based on series of rigorous ring shear test results. Ring shearing test was carried out to observe the shear behavior prior to failure and behavior at residual state between most commonly used pile materials - steel and concrete - and Jumunjin sand. The test was set to clarify the shear behavior under various confinement conditions and soil densities. The test results were converted in to representative friction angles for various test materials. Additional numerical analysis was executed to validate the accuracy of the test results. Based on the test results and the numerical validation, it was found that due to the dilative and contractive nature of sand, its interface behavior can be categorized in to two different types : soils with higher densities tend to show peak shear stress and moves on to residual state, while on the other hand, soils with lower densities tend to show bilinear load-transfer curves along the interface. However, the relative density and the confining stress was found to affect the friction angle only in the small train range, and converges as it progresses to large deformation. This study established a large deformation analysis method which can successfully simulate and predict the large deformation behavior such as ring shear tests. Moreover, the friction angle derived from the ring shear test result and verified by numerical analysis can be applied to numerical analysis and actual design of various pile foundations.

• Knowledge Management Research
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• v.22 no.2
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• pp.145-165
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• 2021

As of late December 2019, the spread of COVID-19 pandemic began which put the entire world in panic. In order to overcome the crisis and minimize any subsequent damage, the government as well as its affiliated institutions must maximize effects of pre-existing policy support and introduce a holistic response plan that can reflect this changing situation- which is why it is crucial to analyze social topics and people's interests. This study investigates people's major thoughts, attitudes and topics surrounding COVID-19 pandemic through the use of social media and big data. In order to collect public opinion, this study segmented time period according to government countermeasures. All data were collected through NAVER blog from 31 December 2019 to 12 December 2020. This research applied TF-IDF keyword extraction and LDA topic modeling as text-mining techniques. As a result, eight major issues related to COVID-19 have been derived, and based on these keywords, this research presented policy strategies. The significance of this study is that it provides a baseline data for Korean government authorities in providing appropriate countermeasures that can satisfy needs of people in the midst of COVID-19 pandemic.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.92-98
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• 2021

Modern society needs constantly the rationality and the efficiency, and this flow of the time has become the paradigm of the whole society. This paradigm has a large influence on the architectural design and industry. Modern technology represented by the development of digital instrument and Information Technology through internet has created and developed two big trend, Parametric Design and BIM(Building information Modeling) in the architectural design and industry. These technologies, though created for different reasons, have a lot of influence on the architectural design and industry for a common purpose such as efficiency and rationality across the boundaries. In this context, this research will be embodied through the example about how parametric design should be made in the beginning of pre-design phase for BIM application. This research aims to consider the design process of Walt Diseny Consert Hall, the work of Frank O. Ghery, a deconstructivism architect, and to embody the shape of National Nederlanden Building in Prague, the Czech Republic, using parametric design tool in pre-design phase. This research later aims to be used as the basic data that can be applied to the entire architectural industry from a planning and a detailed design to a construction for the ultimate BIM application beyond the range of parametric design in pre-design phase. Later, the plan using the parametric design algorithm and BIM application in construction document phase will be conducted.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.267-272
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• 2021

In this study, the output results of 3D printed exterior materials for application to buildings of various shapes are output tests using test specimens, in which 3D printing concrete is cast in a mold and accelerating agents are used to ensure stackability. The unit weight and strength characteristics of the body were analyzed. Compared to the unit weight of concrete placed in the mold, the unit weight of 3D printing concrete using accelerating agents tends to decrease by approximately 3.5% to 5.0%, and the compressive strength is the compressive strength of the concrete placed in the mold. In comparison, the compression strength of the output by 3D printing tended to decrease by approximately 36% to 46%. In the flexural strength, the compressive strength of the output through 3D printing decreased by approximately 36% to 46% compared to the compressive strength of concrete placed in the mold. The impact on the strength characteristics of 3D printed concrete using accelerating agents tended to decrease by approximately 2.0 to 5.8%. Therefore, 3D printing output accelerating agents can be used.

• Journal of the Korea Institute of Building Construction
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• v.22 no.3
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• pp.281-291
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• 2022

This study attempts to use big data to determine the indicators necessary for a fire risk assessment of buildings. Because most of the causes affecting the fire risk of buildings are fixed as indicators considering only the building itself, previously only limited and subjective assessment has been performed. Therefore, if various internal and external indicators can be considered using big data, effective measures can be taken to reduce the fire risk of buildings. To collect the data necessary to determine indicators, a query language was first selected, and professional literature was collected in the form of unstructured data using a web crawling technique. To collect the words in the literature, pre-processing was performed such as user dictionary registration, duplicate literature, and stopwords. Then, through a review of previous research, words were classified into four components, and representative keywords related to risk were selected from each component. Risk-related indicators were collected through analysis of related words of representative keywords. By examining the indicators according to their selection criteria, 20 indicators could be determined. This research methodology indicates the applicability of big data analysis for establishing measures to reduce fire risk in buildings, and the determined risk indicators can be used as reference materials for assessment.

• Korea Science and Art Forum
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• v.31
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• pp.355-365
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• 2017

The future population of Korea is expected to reach the second highest level in the world by 2060 for the elderly. It is because of the rapid development of low fertility and medical technology. The burden of society for the elderly is expected to increase steadily. The elderly person firstly appears functional disorder. They have low ability in memory and in cognitive will be. Their activities are therefore limited. And economic production capacity is sharply reduced. Self-sufficiency is a difficult situation. They need help in economic and social aspects. Products for them need research and development. The elderly have a Mild Cognitive Impairment(MCI) stage with poor cognitive abilities. It is effective to combine pharmacological and non-pharmacological treatment methods for people with mild cognitive impairment. The effects of non-pharmacological treatments on music have been proven. This paper is a study on the appearance from the viewpoint of design in the development of ancillary instruments using music therapy techniques with Digital Convergence. For this study, we investigated the preference for external appearance of mild cognitive impairment. Two times surveys were conducted. As a result, the design of home care product for the hard cognitive impaired was different from that of a conventional game machine or set top box. It should be designed according to the user's special circumstances. They are memory and cognitive abilities. Products that meet physical and mental changes must be developed.

• Design Convergence Study
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• v.16 no.6
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• pp.169-184
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• 2017

There is a lot of needs that are not expressed as much as the expressed needs in familiar products and services that are used in daily life such as a smartphone. Finding the 'Inconveniences in familiar use' make it possible to create opportunities for value expanding in the existing products and service area. There are a lot of related works, which have studied the definition of hidden needs and the methods to find it. But, they are making it difficult to address the hidden needs in the cases of familiar use due to focus on the new product or service developing typically. In this study, we try to redefine the hidden needs in the daily familiarity and approach it in the new way to find out. Because of the users' unability to express what they want and the complexity of needs which can not be explained clearly, we can not approach it as the quantitative issue. For this reason, the basic data type selected as the user behavior data excluding all description is the screen-shot of the smartphone. We try to apply the integrated rules and patterns to the individual data using the qualitative coding techniques to overcome the limitations of qualitative analysis based on unstructured data. From this process, We can not only extract meaningful clues which can make to understand the hidden needs but also identify the possibility as a way to discover hidden needs through the review of relevance to actual market trends. The process of finding hidden needs is not easy to systemize in itself, but we expect the possibility to be conducted a reference frame for finding hidden needs of other further studies.

• 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.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.1
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• pp.43-52
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• 2016

Due to the characteristics of microwave signals, Radar satellite image has been used for flood detection without weather and time influence. The more methods of flood detection were developed, the more detection rate of flood area has been increased. Since flood causes a lot of damages, flooded area should be distinguished from non flooded area. Also, the detection of flood area should be accurate. Therefore, not only image resolution but also the filtering process is critical to minimize resolution degradation. Although a resolution of radar images become better as technology develops, there were a limited focused on a highly suitable filtering methods for flood detection. Thus, the purpose of this study is to find out the most appropriate filtering method for flood detection by comparing three filtering methods: Lee filter, Frost filter and NL-means filter. Therefore, to compare the filters to detect floods, each filters are applied to the radar image. Comparison was drawn among filtered images. Then, the flood map, results of filtered images are compared in that order. As a result, Frost and NL-means filter are more effective in removing the speckle noise compared to Lee filter. In case of Frost filter, resolution degradation occurred severly during removal of the noise. In case of NL-means filter, shadow effect which could be one of the main reasons that causes false detection were not eliminated comparing to other filters. Nevertheless, result of NL-means filter shows the best detection rate because the number of shadow pixels is relatively low in entire image. Kappa coefficient is scored 0.81 for NL-means filtered image and 0.55, 0.64 and 0.74 follows for non filtered image, Lee filtered image and Frost filtered image respectively. Also, in the process of NL-means filter, speckle noise could be removed without resolution degradation. Accordingly, flooded area could be distinguished effectively from other area in NL-means filtered image.