• KIPS Transactions on Software and Data Engineering
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• v.10 no.5
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• pp.169-178
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• 2021

Recently, a bike-sharing system (BSS) has become popular as a convenient "last mile" transportation. Rebalancing of bikes is a critical issue to manage BSS because the rents and returns of bikes are not balanced by stations and periods. For efficient and effective rebalancing, accurate traffic prediction is important. Recently, cluster-based traffic prediction has been utilized to enhance the accuracy of prediction at the station-level and the clustering step is very important in this approach. In this paper, we propose a k-means based clustering algorithm that overcomes the drawbacks of the existing clustering methods for BSS; indeterministic and hardly converged. By employing the centroid initialization and using the temporal proportion of the rents and returns of stations as an input for clustering, the proposed algorithm can be deterministic and fast.

• The Journal of the Korea Contents Association
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• v.21 no.7
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• pp.259-270
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• 2021

Recently, interests in the use of Sharing Bike is increasing in consideration of eco-friendly transportation and safety from viruses. As the technology for collecting and storing data is improved with the development of ICTs, research on mobility using the Sharing Bike Data is also actively progressing. Therefore, this paper analyzes the properties of Sharing Bike Data and cases of researches on it through literature review, and based on the results of the review, data of Eoulling, the Sharing Bike System of Sejong City is analyzed as a way to utilize Sharing Bike Data. Most of the selected literature used structured data, and analyzed it through statistical methods or data mining. Through data analysis, it identified the current status, found out problems of the Sharing Bike System, proposed a solution to solve them, developed plans to activate the use of Sharing Bike. This provides basic data for efficient management and operation plans for Sharing Bike System. Ultimately, it will be possible to explore ways to improve mobility in urban spaces by utilizing Sharing Bike Data.

• Journal of Service Research and Studies
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• v.8 no.4
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• pp.53-75
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• 2018

Bicycle-sharing as a product service system in the sharing economy, its characteristic is that users can go to nearby places by the public bike at any time however they don't need to have their own bicycle. However, the service quality of bicycle-sharing and satisfaction of users continuously decrease with the rapid growth number of bicycle-sharing users in China. Based on the double diamond model and from the perspective of service design, this research studies the service experience of bicycle-sharing of Chinese users, focuses on the potential pain points of Chinese users when using the public bike, and designs the optimum proposal to promote users' satisfaction. According to the research result, the research builds a new concept which can satisfy users' demand for communication, enjoyment and option during the cycling. The experience of new service system of bicycle-sharing makes humanized and subconscious interaction possible.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.1061-1064
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• 2017

자전거 이용자 수가 천만 명을 넘으면서, 자전거 사업은 우리의 삶에 중요 요소로 자리 잡게 되었다. 본 연구에서는 자전거 사용자들에게 편의를 제공하기 위해 GPS정보를 기반으로 한 자전거 전용 네비게이션과 사용자들을 자전거 사고로부터 보호할 수 있는 사고 대처 시스템을 개발하였다. 이를 위해 우리는 아두이노기반의 시스템을 토대로 개발되었으며 스마트폰과 블루투스 송신기술을 사용하여 다양한 정보를 주고 받을 수 있도록 설계하였다. 우리의 사고 대처시스템은 실시간으로 자전거 운행 정보를 공유하도록 하여 보다 효율적으로 자전거 사고를 예방 할 수 있도록 하는데 그 목적이 있다. 이를 위해 우리의 시스템은 아두이노를 통해 측정한 센서 값들을 스마트폰을 통해 자전거 사용자들에게 실시간으로 공유되도록 하고 이를 통해 다른 자전거 사용자들이 자전거 도로의 상태, 사고 내용들을 파악하도록 하여 안전하고 편리한 자전거 운행이 가능하도록 하여 향후 자전거 사업이 발전시킬 수 있는 계기를 마련할 것으로 기대한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.8
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• pp.1123-1132
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• 2018

In this paper, we design and implement a public bicycle sharing system based on smart phone application capable of distributing access codes via internet connection. When smartphone user uses the application to request a bicycle unlock code, server receives the request and sends an encrypted code, which is used to unlock the bicycle at the station and the same code is used to return the bicycle. The station's hardware prototypes were built on top of Internet devices such as raspberry pi, arduino, keypad, and motor driver, and smartphone application basically includes shared bike rental and return functionality. It also includes an additional feature of reservation for a certain time period. We tested the implemented system, and found that it is efficient because it shows the average of 3-4 seconds delay. The system can be implemented to manage multiple bikes with a single control box, and as the user can use a smartphone application, this makes the system more cost effective.

• Journal of Service Research and Studies
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• v.9 no.4
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• pp.19-40
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• 2019

Mobility as a Service is a service conception to achieve the intelligent transportation system. Its aims to improve the travel experience. In one platform, it connects various transportation modes to offer service and users only need to pay in one time for the whole travel. But the single MaaS platform easily faces the problems such as low user traffic, low retention rate and the access to markets of the this service is still unfound. From the perspective of bicycle-sharing, this research makes the MaaS concept into bicycle-sharing to build a better service model. The bicycle-sharing combine with the MaaS concept is innovative in business model, travel model and service architecture. In addition, this research also tests users' expectations for service model. The research shows that MaaS-based bicycle-sharing could offer flexible and convenient travel experience in the aspects of combined transportation, travel, transfer and payment, and it also makes it possible to make travel services according to need, and sustainable transport.

• 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.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.861-866
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• 2022

Seoul introduced the shared bicycle system, "Seoul Public Bike" in 2015 to help reduce traffic volume and air pollution. Hence, to solve various problems according to the supply and demand of the shared bicycle system, "Seoul Public Bike," several studies are being conducted. Most of the research is a strategic "Bicycle Rearrangement" in regard to the imbalance between supply and demand. Moreover, most of these studies predict demand by grouping features such as weather or season. In previous studies, demand was predicted by time-series-analysis. However, recently, studies that predict demand using deep learning or machine learning are emerging. In this paper, we can show that demand prediction can be made a little better by discovering new features or ordering the importance of various features based on well-known feature-patterns. In this study, by ordering the selection of new features or the importance of the features, a better coefficient of determination can be obtained even if the well-known deep learning or machine learning or time-series-analysis is exploited as it is. Therefore, we could be a better one for demand prediction.

• Journal of Advanced Navigation Technology
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• v.22 no.1
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• pp.43-47
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• 2018

In recent years, bicycle craze has been blowing in Korea, and bicycle has become a means of transportation near. In addition, there is a lot of interest in the Internet of things, and recently there is a lot of interest in the Internet of things. However, despite the development of the bicycle market, the bicycle cradle does not have such a development, and it still has a drawback in that it requires a separate lock for the lock. In this regard, I would like to find some problems and solve them. In this paper, we have implemented a system that can control the location and use of the bicycle cradle in real time by communicating with the app and Arduino so that it can help the collection and retrieval of the bicycle which is the problem of the current bicycle cradle. n addition, we propose a method to establish a shared economic system based on Internet of things by providing shared services with acquaintances and others, and to improve user convenience by providing real - time services.

• The Journal of the Korea Contents Association
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• v.19 no.1
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• pp.132-140
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• 2019

Recently, many cities around the world introduced and operated shared bicycle system to reduce the traffic and air pollution. Seoul also provides shared bicycle service called as "Ddareungi" since 2015. As the use of shared bicycle increases, the demand for bicycle in each station is also increasing. In addition to the restriction on budget, however, there are managerial issues due to the different demands of each station. Currently, while bicycle rebalancing is used to resolve the huge imbalance of demands among many stations, forecasting uncertain demand at the future is more important problem in practice. In this paper, we develop forecasting model for demand for Seoul shared bicycle using statistical time series analysis and apply our model to the real data. In particular, we apply Holt-Winters method which was used to forecast electricity demand, and perform sensitivity analysis on the parameters that affect on real demand forecasting.