• Journal of Korean Society of Transportation
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• v.28 no.4
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• pp.97-106
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• 2010

Environmental issues resulting from climate change and energy crises have become global issues, and cycling has gained greater popularity for sustainable transportation. Though many cities are trying to build bicycle roads, it is not easy to implement bicycle roads because there is little available space for bicycle facilities. Therefore, road diets have become more popular in Korea. However, there has been no intensive research to date of their impacts. The purpose of this research is to evaluate the effects of road diets and construction of bike lanes. Every benefit, including energy benefit, environmental benefit, and health benefit is considered, while only time savings benefit has been considered in previous studies. The benefit analysis for the Seoul metropolitan area as a case study shows that road diets have a (1) time saving benefit for only five percent of the mode share and (2) enough total benefit even if bicycle mode share is less than two percent.

• Journal of Urban Science
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• v.9 no.2
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• pp.63-68
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• 2020

In recent years, the planning of livable communities has emerged as a new paradigm. The concept of livable communities is related to both the spatial balance of working, playing, and living and the promotion of green modes of transportation, such as walking and biking. This study uses a disaggregate travel survey conducted by the Seoul Metropolitan Area in 2006. I applied a multi-level random intercept logit model to estimate the effects of land-use characteristics on the choice of green modes, holding a traveler's socio-demographic characteristics constant. The empirical results show that higher density and more mixed land-use development encourages people to walk and bike even when individuals have the same socio-economic characteristics. This paper demonstrates that land-use planning by itself can play a role in the creation of livable cities and the decline of greenhouse gas production.

• Korean Journal of Artificial Intelligence
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• v.10 no.1
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• pp.27-32
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• 2022

As the need for eco-friendly transportation increases due to the deepening climate crisis, many local governments in Korea are introducing shared bicycles. Due to anxiety about public transportation after COVID-19, bicycles have firmly established themselves as the axis of daily transportation. The use of shared bicycles is spread, and the demand for bicycles is increasing by rental offices, but there are operational and management difficulties because the demand is managed under a limited budget. And unfortunately, user behavior results in a spatial imbalance of the bike inventory over time. So, in order to easily operate the maintenance of shared bicycles in Seoul, bicycles should be prepared in large quantities at a time of high demand and withdrawn at a low time. Therefore, in this study, by using machine learning, the linear regression algorithm and MS Azure ML are used to predict and analyze when demand is high. As a result of the analysis, the demand for bicycles in 2018 is on the rise compared to 2017, and the demand is lower in winter than in spring, summer, and fall. It can be judged that this linear regression-based prediction can reduce maintenance and management costs in a shared society and increase user convenience. In a further study, we will focus on shared bike routes by using GPS tracking systems. Through the data found, the route used by most people will be analyzed to derive the optimal route when installing a bicycle-only road.

• Journal of the Korea Furniture Society
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• v.20 no.6
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• pp.581-589
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• 2009

Under 'The Design Street' Project, one of the urban environment improvement projects of Seoul, the facilities on the street have been greatly varied in terms of design. In addition, the municipal authority has pushed each district to develop its own identity based on the integrated design of the city. This study was aimed to propose a design which could solve the current problem in street furniture in terms of environmental improvement through an analysis on current street conditions in "Y" District as a part of Seoul Design Street Project. It has attempted to propose 11 street furnitures based on the basic strategy of 'Soft City' which has been promoted by Seoul City in accordance with the Seoul Public Facility Guidelines as 1. Airy Design, 2. Integrated Design, 3. Collaborative Design and 4. Sustainable Design. Among them, for the total design in Seoul six facilities - kiosk, manhole, traffic signal controller, public phone, road sign and waste receptacle were proposed by Seoul City have been accepted. For local differentiation, on the contrary, five items - planter bench, bollard, lifter, bike rack and fence have been newly designed and proposed. Furthermore, it is essential to carry out systematic supervision and continuous management on the detail design and construction of current regional design development projects.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.14-25
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• 2021

With the spread of COVID-19 and the government policy of social distancing, the demand for subways and buses is decreasing, whereas the demand for public bicycles and personal transportation is increasing. Hence, research is needed to understand the characteristics of this phenomenon and to prove the statistical reliability of the correlation between the subway and shared bicycle demands. In this study, the correlation between the number of confirmed COVID-19 cases and the replacement rate of subway and public bicycle demands was examined, but the statistical significance was not significant. However, during the period of September to December 2020, in which the number of confirmed COVID-19 cases in Seoul started to increase rapidly, there was a correlation between the number of confirmed COVID-19 cases and the replacement ratio. If the number of confirmed COVID-19 cases increases by more than a certain number, public bicycles are expected to play a significant role as alternates to the subways. It is expected that the role of public bicycles will increase, and that it is possible to suggest the direction of transportation operation and policy establishment for the continuation of COVID-19 countermeasures in field demonstration after elementary technology development. It is also expected that this study will suggest a direction for future development and policymaking.

• Journal of the Korean Society of Safety
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• v.28 no.3
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• pp.1-5
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• 2013

In order to evaluate fatigue endurance for an MTB(mountain bike) frame, FEM(finite element method) analysis was performed. For evaluating the fatigue endurance of the MTB frame, the S-N data for Al-6061 fillet weldment were compared with the stress analysis results through FEM analysis of the frame. Three loading condition, pedalling, horizontal and vertical loading conditions were considered for fatigue endurance evaluation. Horizontal loading(+1200 N) condition was found to be the most severe to the frame. The maximum von Mises stress of the frame under horizontal loading(+1200 N) condition was determined 294 MPa through FEM analysis of the frame. Conclusively, on the basis of fatigue strength of 200 MPa at the number of cycles of 50,000, the MTB frame has an improper safety factor of approximately 0.25, suggesting that this frame needs reinforcement.

• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.1
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• pp.1-14
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• 2020

Various policies and studies regarding use of PBSS (Public Bike Sharing System) and Programs (PBSP) have been conducted worldwide as the number systems or programs has increased. Although various phenomena and demands have been generated by the use of PBSS in everyday life, the majority of research and the policies in South Korea have been implemented focused on commuting life. The purpose of this study aimed to understand various PBSS demands using PBSS usage data in 2018 in the Yeouido districts through classifying usage patterns and analyzing features. The rental stations were classified into three types based on weekday/weekend usage rates. The usage of Yeouido's PBSS accounted for 4.3% of the total usage in Seoul Metropolitan City, while the number of PBSS rental stations accounted for 2% of all rental stations in the Seoul urban areas. Rental stations with a higher weekday utilization rates showed high utilization rates in all four seasons and were mainly distributed in work and residential areas. Other stations showed a concentrated usage pattern in spring (April-May) and autumn (September-October) seasons, and their locations were close to the entrance of nearby parks. Besides, renting and returning were often concentrated at certain rental stations for high weekend utilization as compared to the pattern of high weekday usage. Therefore, PBSS management and programs should be operated to reflect various usage demands rather than uniform PBSS operations. The result of this study is meaningful to provide basic data for effective PBSS operation by monitoring the demand for PBSS usage in spatio-temporal terms.

• Korean Journal of Artificial Intelligence
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• v.10 no.1
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• pp.9-14
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• 2022

The demand for public bicycles operated by the Seoul Metropolitan Government is increasing every year. The size of the Seoul public bicycle project, which first started with about 5,600 units, increased to 3,7500 units as of September 2021, and the number of members is also increasing every year. However, as the size of the project grows, excessive budget spending and deficit problems are emerging for public bicycle projects, and new bicycles, rental office costs, and bicycle maintenance costs are blamed for the deficit. In this paper, the Azure Machine Learning Studio program and the Boosted Decision Tree Regression technique are used to predict the number of public bicycle rental over environmental factors and time. Predicted results it was confirmed that the demand for public bicycles was high in the season except for winter, and the demand for public bicycles was the highest at 6 p.m. In addition, in this paper compare four additional regression algorithms in addition to the Boosted Decision Tree Regression algorithm to measure algorithm performance. The results showed high accuracy in the order of the First Boosted Decision Tree Regression Algorithm (0.878802), second Decision Forest Regression (0.838232), third Poison Regression (0.62699), and fourth Linear Regression (0.618773). Based on these predictions, it is expected that more public bicycles will be placed at rental stations near public transportation to meet the growing demand for commuting hours and that more bicycles will be placed in rental stations in summer than winter and the life of bicycles can be extended in winter.

• Management & Information Systems Review
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• v.36 no.4
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• pp.129-148
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• 2017

Conventional exhibition management information systems recommend tourist attractions that are close to the place in which an exhibition is held. Some recommended attractions by the location-based recommendation could be meaningless when nothing is related to the exhibition's topic. Our goal is to recommend attractions that are related to the content presented in the exhibition, which can be coined as content-based recommendation. Even though human exhibition curators can do this, the quality is limited to their manual task and knowledge. We propose an automatic way of discovering attractions relevant to an exhibition of interests. Language resources are incorporated to discover attractions that are more meaningful. Because a typical single machine is unable to deal with such large-scale language resources efficiently, we implemented the algorithm on top of Apache Spark, which is a well-known distributed computing framework. As a user interface prototype, a web-based system is implemented that provides users with a list of relevant attractions when users are browsing exhibition information, available at http://bike.snu.ac.kr/WARP. We carried out a case study based on Korean Tourism Organization Linked Open Data with Korean Wikipedia as a language resource. Experimental results are demonstrated to show the efficiency and effectiveness of the proposed system. The effectiveness was evaluated against well-known exhibitions. It is expected that the proposed approach will contribute to the development of both exhibition and tourist industries by motivating exhibition visitors to become active tourists.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.607-610
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• 2016

최근 자전거 이용인구가 급격하게 증가함에 따라 자전거 교통사고 역시 증가하고 있다. 이에 DB를 통해 이용자에게 알맞은 자전거 도로에 대한 정보를 제공하여 자전거 도로를 활성화하고자 다음과 같은 프로젝트를 진행하게 되었다. 서울시를 중심으로 사용자의 지역, 선호하는 길이, 난이도에 따른 DB를 제공하여 알맞은 자전거 도로를 선택하도록 하였으며, 기업에게는 자전거 이용자의 DB를 제공하여 마케팅에 활용할 수 있도록 하였다.