• Journal of the Korean housing association
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• v.25 no.4
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• pp.59-72
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• 2014

This study proposes a data-mining analysis method for examining variable multi-attribute big-data, which is considered to be more applicable in social science using a Correspondence Analysis of variables obtained by AIC model selection. The proposed method was applied on the Seoul Survey from 2005 to 2010 in order to extract interesting rules or patterns on characteristics of single household. The results found as follows. Firstly, this paper illustrated that the proposed method is efficiently able to apply on a big dataset of huge categorical multi attributes variables. Secondly, as a result of Seoul Survey analysis, it has been found that the more dissatisfied with residential environment the higher tendency of residential mobility in single household. Thirdly, it turned out that there are three types of single households based on the characteristics of their demographic characteristics, and it was different from recognition of home and partner of counselling by the three types of single households. Fourthly, this paper extracted eight significant variables with a spatial aggregated dataset which are highly correlated to the ratio of occupancy of single household in 25 Seoul Municipals, and to conclude, it investigated the relation between spatial distribution of single households and their demographic statistics based on the six divided groups obtained by Cluster Analysis.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.97-112
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• 2023

The purpose of this study is to design and test a new way of public transportation route guidance system for persons with disabilities, including wheelchair users. The guidance system is smartphone app-based, using, routes that involve disabled-friendly facilities in the vicinity can be searched. A database that contains publicly available data on low-floor bus services, location and extent of disabled-friendly facilities, and suitable subways and stations, was developed for this purpose. The app uses the database to access and query the required information. A pilot study was conducted to test the effectiveness of the guidance system. It was found that the system was able to convey information about the disabled-friendly routes and related guidance information even inside subway stations, effectively. The performance of the system was compared with route guidance services that do not explicitly use data on disabled-friendly services. A notable difference was observed in the travel time estimated by this program and other guidance services. The difference was around 4 to 15 minutes. This is significant savings for persons with disabilities if they use the app and service. The study thus shows that exclusive use of disabled-friendly data in route guidance will bring more benefits for persons with disabilities.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.463-476
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• 2022

After industrialization in the past, the automobile industry has continued to grow centered on internal combustion engines, but is facing a major change with the recent 4th industrial revolution. Most companies are preparing for the transition to electric vehicles and autonomous driving. Therefore, in this study, topic modeling was performed based on LDA algorithm by collecting 4,002 domestic papers and 68,372 overseas papers that contain keywords related to CASE (Connectivity, Autonomous, Sharing, Electrification), which represent future automobile trends. As a result of the analysis, it was found that domestic research mainly focuses on macroscopic aspects such as traffic infrastructure, urban traffic efficiency, and traffic policy. Through this, the government's technical support for MaaS (Mobility-as-a-Service) is required in the domestic shared car sector, and the need for data opening by means of transportation was presented. It is judged that these analysis results can be used as basic data for the future automobile industry.

• Smart Media Journal
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• v.11 no.11
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• pp.49-62
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• 2022

Recently, with the development of Smart City Solutions such as Big data, AI, IoT, Autonomous driving, and Digital twins around the world, the proliferation of various smart devices and social media, and the record of the deeds that people have left everywhere, the construction of Smart Cities using the "Big Data" environment in which so much information and data is produced that it is impossible to gauge the scale is actively underway. The Purpose of this study is to construct an objective and systematic analysis Model based on Big Data to improve the transportation convenience of citizens and formulate efficient policies in Urban Information and Public Transportation accessibility in sustainable Smart Cities following the 4th Industrial Revolution. It is also to derive the methodology of developing a Big Data-Based public transport accessibility and policy management Platform using a sustainable Urban Public DB and a Private DB. To this end, Detailed Living Areas made a division and the accessibility of basic living amenities of Gwangju Metropolitan City, and the Public Transportation system based on Big Data were analyzed. As a result, it was Proposed to construct a Big Data-based Urban Information and Public Transportation accessibility Platform, such as 1) Using Big Data for public transportation network evaluation, 2) Supporting Transportation means/service decision-making based on Big Data, 3) Providing urban traffic network monitoring services, and 4) Analyzing parking demand sources and providing improvement measures.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.118-133
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• 2020

Research interest in the Mobility-as-a-Service (MaaS) concept for enhancing users' mobility experience is increasing. In particular, dynamic pricing techniques based on reinforcement learning have emerged since adjusting prices based on the demand is expected to help mobility services, such as taxi and car-sharing services, to gain more profit. This paper provides a simulation framework that considers more practical factors, such as demand density per location, preferred prices, the distance between users and drivers, and distance to the destination that critically affect the probability of matching between the users and the mobility service providers (e.g., drivers). The aforementioned new practical features are reflected on a data structure referred to as the Matching Matrix. Using an efficient algorithm of computing the probability of matching between the users and drivers and given a set of precisely identified high-demand locations using HDBSCAN, this study developed a better reward function that can gear the reinforcement learning process towards finding more realistic dynamic pricing policies.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.2
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• pp.195-206
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• 2023

Most of the Micro-mobility parking in Korea use Dockless system. However, Dockless can result in cluttering, infrastructure deficiencies, and safety challenges as has been observed in cities. It is necessary to introduce a Station Parking system in order to solve the drawbacks of the dockless, but the introduction without engineering has low accessibility and induces side effects. In this study, to decide optimal location about number of the Micro-mobility Station, we has been applied the MCLP model about the coverage range, usage demand, usage time in order to classify the type of Micro-mobility Station. For the MCLP, User Date input to reflect realistic demand in Bundang new town, Korea. The result show that the optimal number of facilities in 400 m was 146, and the coverage ratio was 99.83 %, which was most suitable coverage for solving the parking problem. We also classified the demand into 4 levels and the usage time into 3 levels, and by crossing them, we were able to classify the Parking lot types into 12 types. It is possible to propose strategic policies in the installation and operation of Micro-mobility Parking System.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.217-233
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• 2020

This study evaluated the urban vitality of Daegu metropolitan city in 2018 using emerging geographic data such as spatial big data, Wi-Fi AP(access points) and nighttime light satellite image. The emerging geographic data were used in this research to quantify human activities in the city more directly at various spatial and temporal scales. Three spatial big data such as mobile phone data, credit card data and public transport smart card data were employed to reflect social, economic and mobility aspects of urban vitality while public Wi-Fi AP and nighttime light satellite image were included to consider virtual and physical aspects of the urban vitality. With PCA (Principal Component Analysis), five indicators were integrated and transformed to the urban vitality index at census output area by temporal slots. Results show that five clusters with high urban vitality were identified around downtown Daegu, Daegu bank intersection and Beomeo intersection, Seongseo, Dongdaegu station and Chilgok 3 district. Further, the results unveil that the urban vitality index was varied over the same urban space by temporal slots. This study provides the possibility for the integrated use of spatial big data, Wi-Fi AP and nighttime light satellite image as proxy for measuring urban vitality.

• Proceedings of the CALSEC Conference
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• 2004.02a
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• pp.60-64
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• 2004

The rapidly improving price-performance of wireless technologies is providing an unprecedented platform for the development of wireless applications for the business. Such applications are able to take advantage of a new paradigm of mobility for data services, with the ability to sensitize to location, time and personal features. While big business has been a central feature of wireless implementation, it is now clear that small- and medium-sized enterprises (SMEs) are beginning to take advantage of the strategic benefits of wireless data communications. This study examines the state-of-the-art of wireless data services in New Zealand. It provides a survey of 127 current applications in use, as well as two short illustrative cases of application use. The paper rounds off with a summary and conclusions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2398-2415
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• 2017

Content-Centric Networking (CCN) is a new Internet architecture with routing and caching centered on contents. Through its receiver-driven and connectionless communication model, CCN natively supports the seamless mobility of nodes and scalable content acquisition. In-network caching is one of the core technologies in CCN, and the research of efficient caching scheme becomes increasingly attractive. To address the problem of unbalanced cache load distribution in some existing caching strategies, this paper presents a neighbor cooperation based in-network caching scheme. In this scheme, the node with the highest betweenness centrality in the content delivery path is selected as the central caching node and the area of its ego network is selected as the caching area. When the caching node has no sufficient resource, part of its cached contents will be picked out and transferred to the appropriate neighbor by comprehensively considering the factors, such as available node cache, cache replacement rate and link stability between nodes. Simulation results show that our scheme can effectively enhance the utilization of cache resources and improve cache hit rate and average access cost.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.182-187
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• 2022

This study aims to study non-rechargeable wrist-type smart bands for those vulnerable to the digital environment. The transition to the digital age means improving the efficiency of human life and the convenience of management. In the digital age, it can be a very convenient infrastructure for the digital generation, but otherwise, it can cause inconvenience. COVID-19 is spreading non-face-to-face culture. The reality is that the vulnerable are complaining of discomfort in non-face-to-face culture. The core of the digital environment is smartphones. Digital life is spreading around smartphones. Technology that drives the digital environment is the core technology of the Fourth Industrial Revolution. The technologies are lot, big data, Blockchain, Smart Mobility, and AI. Related technologies based on these technologies include digital ID cards, digital keys, and nfc technologies. Non-rechargeable wrist-type smart bands based on related technologies can be conceptualized. Through these technologies, blind people can easily access books and manage their ID cards conveniently and efficiently. In particular, access authentication is required wherever you go due to COVID-19, which can be used as a useful tool for the elderly who feel uncomfortable using smartphones. It can also eliminate the inconvenience of the elderly finding or losing their keys.