• Land and Housing Review
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• v.3 no.3
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• pp.241-248
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• 2012

Although infrastructure cost comprises the great proportion of residential development cost, all of it tends to be borne by land developers which develop large area. This brings about free-riding by adjacent small development or built-up area, followed by the equity problem in terms of infrastructure development cost sharing and the privatization of development gain. This study aims to establish the method to analyze free-riding on the transportation infrastructure(roads) and investigate empirically how much the free-riding occurs. It sets several development scenarios to calculate the part generated by Bucheon Sangdong district, the case area of this study, of all the traffic flow on the roads. The Network analysis is used to estimate the proportion, by development scenarios, of traffic flow, travel time, and travel cost. As a result, the developer of Bucheon Sangdong district is responsible for 83% of the construction cost of selected roads. The methodology and empirical result of this study would contribute to determine who are liable for the infrastructure facilitation and to estimate how much of the cost the obligators have to share.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.4
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• pp.327-333
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• 2016

An autonomous vehicle is a convergence of artificial intelligence and a vehicle which can drive itself while analyzing the real-time situation on a road without a driver. A lot of research achievements have been revealed through the media and Google is considered to be the best leading company in this field. The use of patent information which contains various information such as bibliographic data and information about technologies is a good way to find out the R&D direction of a company and develop a reasonable strategy. This study is aimed at investigating the direction to which Google focuses its R&D capabilities and establishing strategies for technology development. Google's patents about autonomous vehicles were collected and the degree of research bias was analyzed using Social Network Analysis based on citations indicating the quality of a patent. Based on the results, the strategies for technology development was eventually proposed. As a result, it was revealed that Google focused its R&D capabilities on the part of hardware control to make up for its lack of hardware-oriented technologies. As of now, Google obtained remarkable achievements, so it seems reasonable that last-movers consider cooperative research with Google.

• Journal of the Korean Institute of Landscape Architecture
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• v.45 no.6
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• pp.90-97
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• 2017

Construction of urban emergency shelters based on disaster-prevention green space is an important part of an urban disaster response plan. The accessibility of disaster-prevention green space is directly related to the disaster prevention service effect of green space. Taking the Jung-gu and Nam-gu districts of Ulsan city as research targets, the accessibility of three green spaces was analyzed by a network analysis method based on information regarding the distribution of population and green space and the urban road network. Two indicators for evaluating the service effect of green spaces were service population rate and service area rate. The results showed that the accessibility of the emergency refuge parks (5min) and central refuge parks was relatively good but the service area rate and service population rate of the emergency refuge parks (3min) and temporary refuge parks was less than 60%. In view of the overall situation, the service effect of disaster-prevention green space is at this point only general in Ulsan and there is great room for improvement.

• Korean Journal of Heritage: History & Science
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• v.48 no.3
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• pp.204-219
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• 2015

International society, including the United Nations, has recently been making efforts to further promote a rapprochement of cultures in relation to alleviating military and political conflicts and other social clashes. In line with these efforts at the international level, there has been a growing interest on Central Asia and, in particular, on the Silk Road, which functioned as a trade route among ancient civilizations in the region and is also seen as a route that promoted cultural dialogue and exchanges. Given the amount of cross cultural dialogue and exchange, it is no surprise that intangible cultural heritage has historically been abundant and easily found in the region. However, this heritage was placed in considerable risk because heritage transmission critically weakened for seventy years under Soviet rule. Fortunately, since independence, there has been increasing interest in restoring community identity and reviving intangible heritage. Nevertheless, in spite of this interest, a lack of policies and cultural support in each country has made heritage safeguarding difficult. In this paper, I analyze the various phenomena that took place after the concept and international trends on ICH were introduced and speak about the experiences and outcomes obtained from collaborative network projects by ICHCAP and the Central Asian countries over the last six year. In addition, I would like take this opportunity to discuss how we can understand and develop collaboration in the intangible heritage field in Central Asia in a long-term perspective.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1579-1590
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• 2020

In this paper, spatially-adaptive denormalization (SPADE) based U-Net is proposed to detect changes by using high-resolution satellite images. The proposed network is to preserve spatial information using SPADE. Change detection methods using high-resolution satellite images can be used to resolve various urban problems such as city planning and forecasting. For using pixel-based change detection, which is a conventional method such as Iteratively Reweighted-Multivariate Alteration Detection (IR-MAD), unchanged areas will be detected as changing areas because changes in pixels are sensitive to the state of the environment such as seasonal changes between images. Therefore, in this paper, to precisely detect the changes of the objects that consist of the city in time-series satellite images, the semantic spatial objects that consist of the city are defined, extracted through deep learning based image segmentation, and then analyzed the changes between areas to carry out change detection. The semantic objects for analyzing changes were defined as six classes: building, road, farmland, vinyl house, forest area, and waterside area. Each network model learned with KOMPSAT-3A satellite images performs a change detection for the time-series KOMPSAT-3 satellite images. For objective assessments for change detection, we use F1-score, kappa. We found that the proposed method gives a better performance compared to U-Net and UNet++ by achieving an average F1-score of 0.77, kappa of 77.29.

• Journal of the Society of Disaster Information
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• v.17 no.1
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• pp.165-175
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• 2021

Purpose: The purpose of this study is to quantitatively present the carbon dioxide(CO₂) emission change according to the application of autonomous driving technology at the network level for waste vehicles in the metropolitan area. Method: The target year was set to 2030, and the analysis method estimated the carbon dioxide (CO₂) emissions for each road link through user equilibrium assignment when unapplied scenario. The application scenario performed traffic assignment using route data on the premise that the group was running in accordance with the application of autonomous driving technology to waste vehicles. In addition, the other means estimated the carbon dioxide emissions through user balance allocation by reflecting the results of the waste vehicle allocation. Result: As a result of the analysis, carbon dioxide(CO₂) emissions were found to be reduced by about 56.9ton/day from the national network level, and the Seoul metropolitan area was analyzed to be reduced by about 54.7ton/day. Conclusion: This study quantitatively presented environmental impacts among various social effects that autonomous driving technology will bring, and in the future, development of various analytical methodologies and related studies should be continuously conducted.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.791-802
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• 2021

In Korea, the cities continue to deteriorate, while the vacant houses in the small local towns emerge as a serious social problem. Despite the vacant houses emerge as a serious social problem in the small local towns as well as in the large cities, the basic researches into them are yet to be conducted on a full scale. Thus, in order to know about the spatial distribution of the vacant houses, this study conducted the square analysis and the kernel density analysis. As a result, it was confirmed that the vacant houses in Okcheon-gun had certain crowding forms and characteristics at the level of statistical significance. Next, in order to examine the distribution of the vacant houses in terms of the accessibility to the living SOC facilities, the GIS network analysis was performed, focusing on the major facilities and road networks. As a result, it was found that the better the accessibility to the living SOC facilities such as medical and well-being was, the ratio of the vacant houses was lower. In contrast, it was found that the accessibility to the obligatory facilities such as public administration and educational facilities did not have any important effects on the distribution of the vacant houses. All in all, through this study, the spatial distribution of the vacant houses in the small local town and their accessibility to the major SOC facilities could be analyzed.

• 한국체육학회지인문사회과학편
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• v.55 no.6
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• pp.661-676
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• 2016

The purpose of this study is to draw a systematic access method of career intervention for dance majors. This study conducted Delphi survey and Analytic Hierarchy Process(AHP). As a result of study, 16 elements of career intervention were produced in total 4 areas. Results show that vocational guidance puts emphasis on the understanding of the various vocations, career education on the career planning and goal, career counseling on the macro-narrative to the life and career intervention network on the dance job fair and workshop. In the complex weight of all factors, ratings of weight show that dance vocation guidance and career education are demanded significantly. Results show that expansion of career alternatives, application of diversified dance career development road map to the curriculum, development of test tool and outcome standard, dance educators' systematic career intervention education and systematization of network for career support were suggested as measures for dance career intervention. This study discussed about dynamic reality and systematic access method for dance majors based on theories of Holland(1997), Super(1990), and Savickas(2005).

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2D
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• pp.191-197
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• 2009

This study choose the Criteria by conducting survey questionnaire of expertise, ANP analysis, and reviewing literature to samples of School Zone in a synthetic and reasonable way. It draws the estimating factors including a variety of existing aspects (user, facility, operation and management, and education and institution) from the analyses and applies ANP to reflect the decision making process. The results show as follows: first, first level of weights presents proportion of 'facility' and 'user' takes 65% of total weights. It implies that the facility protects children from obstacles is the top priority of the settings. second, the second level of weights present similar importance with the first level. Facility management, road to school, surroundings, safety facility, decelerating facility hold approximately 72% of overall levels. This indicates that improving and repairing surroundings, and safety and decelerating facility are the first priority to consider. These estimating indicators will be properly utilized to rationally appoint prevention zone with reflecting various factors and social class.

• Journal of the Korean Geotechnical Society
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• v.39 no.7
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• pp.31-37
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• 2023

Since tunnels are built underground, it is impossible to check visually the location and degree of deterioration of steel ribs. Therefore, in tunnel maintenance, GPR images are generally used to detect steel ribs. While research on GPR image analysis employing artificial neural networks has primarily focused on detecting underground pipes and road damage, there have been limited applications for analyzing tunnel GPR data, specifically for steel rib detection, both internationally and domestically. In this study, a one-step object detection algorithm called YOLO, based on a convolutional neural network, was utilized to automate the localization of steel ribs using GPR data. The performance of the algorithm is then analyzed. Two datasets were employed for the analysis. A dataset comprising 512 original images and another dataset consisting of 2,048 augmented images. The omission rate, which represents the ratio of undetected steel ribs to the total number of steel ribs, was 0.38% for the model using the augmented data, whereas the omission rate for the model using only the original data was 7.18%. Thus, from an automation standpoint, it is more practical to employ an augmented dataset.