• Journal of the Korean Data and Information Science Society
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• v.26 no.5
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• pp.1061-1069
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• 2015

Recently, transportation big data generated in the transportation sector has been widely used in the transportation policies making and efficient system management. Bus passengers' mobility patterns are useful insight for transportation policy maker to optimize bus lines and time intervals in a city. We propose a new methodology to discover mobility patterns by using transportation card data. We first estimate the bus stations where the passengers get-off because the transportation card data don't have the get-off information in most cities. We then applies LDA (Latent Dirichlet Allocation), the most representative topic modeling technique, to discover mobility patterns of bus passengers in Cheong-Ju city. To understand discovered patterns, we construct a data warehouse and perform multi-dimensional analysis by bus-route, region, time-period, and the mobility patterns (get-on/get-off station). In the case of Cheong Ju, we discovered mobility pattern 1 from suburban area to Cheong-Ju terminal, mobility pattern 2 from residential area to commercial area, mobility pattern 3 from school areas to commercial area.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1069-1074
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• 2022

IP mobility can be handled in different layers of the protocol. Mobile IP has been proposed to handle the mobility of Internet hosts in the network layer. Recently, a new method based on the SIGMA mobility architecture has been proposed to support mobility management with reduced packet loss and latency. The location management structure is not suitable for frequent mobile handover due to the high mobility of the user with this transport layer solution. In this paper, we propose a location management optimization method in a mobile communication network by applying hierarchical location management using MMPs(Mobility Management Points) for transport layer mobility management. Therefore, we propose an efficient hierarchical mobility management structure even between heterogeneous wireless networks using MMPs for the probability that a mobile terminal can change multiple location areas between two messages and calls. The proposed method shows reduction in location update cost and data retrieval cost using MMPs, and as opposed to mobility appearing in time intervals with the minimum cost required to reach 90% of the stabilized cost, the mobility location update search, location It was found that the message processing cost per area was reduced.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.2
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• pp.160-171
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• 2008

MU's mobility patterns can be found from a movement history data. The prediction accuracy and model complexity depend on the degree of application of history data. The more data we use, the more accurate the prediction is. As a result, the location management cost is reduced, but complexity of the model increases. In this paper, we classify MU's mobility patterns into four types. For each type, we find the respective optimal number of application of history data, and predictive location area by using the simulation. The optimal numbers of four types are shown to be different. When we use more than three application of history data, the simulation time and data storage are shown to increase very steeply.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.645-654
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• 2021

This research aims to examine the influence of road transportation infrastructure on the mobility of goods transport and the regional economy in Langkat Regency in Indonesia. This type of research is an associative and explanatory research whose data is obtained through a questionnaire survey. This study took a sample of 305 respondents using probability sampling in Langkat Regency, North Sumatera, Indonesia. Data analysis techniques use path analysis. The research results showed that the road transportation infrastructure variables had a significant and positive effect on the mobility of goods transport. Road transportation infrastructure and freight mobility simultaneously have a significant and positive effect on the economy of Langkat Regency. Road transportation infrastructure with the dimensions of road accessibility and maintenance partially directly has a significant and positive effect on the economy of the Langkat Regency. Road transportation infrastructure with the dimensions of road design and road construction quality partially does not have a direct effect on the regional economy, but has a positive and significant effect through the mobility of freight transport. The mobility of goods transport becomes an intervening variable that acts to mediate or determine the relationship between road transportation infrastructure variables to the regional economy.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.39-46
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• 2019

Human mobility estimation plays a key factor in a lot of promising applications including location-based recommendation systems, urban planning, and disease outbreak control. We study the human mobility estimation problem in the case where recent locations of a person-of-interest are unknown. Since matrix decomposition is used to perform latent semantic analysis of multi-dimensional data, we propose a human location estimation algorithm based on matrix factorization to reconstruct the human movement patterns through the use of information of persons with correlated movements. Specifically, the optimization problem which minimizes the difference between the reconstructed and actual movement data is first formulated. Then, the gradient descent algorithm is applied to adjust parameters which contribute to reconstructed mobility data. The experiment results show that the proposed framework can be used for the prediction of human location and achieves higher predictive accuracy than a baseline model.

• Journal of Families and Better Life
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• v.7 no.2
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• pp.127-144
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• 1989

The resulting rapid urbanization in the several decades caused increasing residential mobility. The purpose of this study is to analyse systematically the effects of residential mobility on the family quality of life and the factors that cause residential mobility. For this purpose, 976 housewives were sampled from the households in Seoul. The data were analysed by such statistical methods as multiple regression, crosstabulation, ANOVA test and path analysis. The main results obtained are as follows; 1) A significant proportion of the urban households are experienced frequent residential mobility. 2) Among the factors that affect residential mobility, the most important factors are family income, tenure type, and residential satisfaction. 3) Residential satisfaction is an important intervening variable in residential mobility. 4) It has been observed that family quality of life was affected by residential mobility patterns. Analysis has revealed that quality of life de eloped remarkably by changing for residential location, especially in education environment for their children.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.88-103
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• 2023

With the recent advancement of 4th Industrial Revolution technology, transportation systems are generating large amounts of mobility data related to the individual movement trajectories of vehicles and people. There are many constraints on utilizing mobility data containing personal information. Thus, in South Korea, the processing and generation of pseudonymized information and the analysis and utilization of this information have been managed in a dual manner by applying separate agencies and technologies through the revision of the Data 3 Act and the enactment of the Data Basic Act. However, this dual approach fails to securely support the entire data lifecycle and suffers from inefficiencies in terms of processing time and cost. Therefore, to compensate for the problems of the existing Expert Data Combination System and Data Safety Zone, this study proposes an Integrated Data Safety Zone Framework that integrates and unifies the process of generating, processing, analyzing, and utilizing mobility data. The integrated process for data processing was redesigned, and common requirements and core technologies were derived. The result is an architecture for a next-generation Integrated Data Safety Zone system that can manage and utilize the entire life cycle of mobility data at one stop.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.388-394
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• 2007

In wireless network, we propose a predictive location update scheme which considers mobile user's(MU's) mobility patterns. MU's mobility patterns can be found from a movement history data. The prediction accuracy and model complexity depend on the degree of application of history data. The more data we use, the more accurate the prediction is. As a result, the location management cost is reduced, but complexity of the model increases. In this paper, we classify MU's mobility patterns into four types. For each type, we find the respective optimal number of application of history data, and predictive location area by using the simulation. The optimal numbers of four types are shown to be different. When we use more than three application of history data, the simulation time and data storage are shown to increase very steeply.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.647-655
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• 2020

This study introduced income mobility analysis using pseudo-longitudinal panel data from Family Income and Expenditure Survey (FIES) to consider the dynamic process of individual's well-being through time. Since there is no comprehensive measurement of income mobility because of its dynamic process, various income mobility indices such as Chi-square, Average Jump Index, Atkinson et al. Mobility Ratio, and Shorrocks' Mobility Index were used. These indices revealed that Filipino households' income movements are more mobile than expected, and their income status improved from 2000 to 2015. As income mobility takes place, income inequality is reduced by 91.80 percent (91.80%). Furthermore, the growth effect is the main factor of income mobility. This indicates that households took the economic opportunities from economic growth to earn more. However, income mobility due to transfer effect (transfer of income from one household to another through lottery winning and borrowing) increased when the economy is not good. The higher income mobility due to growth effect compared to transfer effect, whether the economy is good or bad, means that households learned how to use their income in savings, investments, and entrepreneurship. This is the result of a successful financial literacy program of the government wherein households realized financial stability and security.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1034-1051
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• 2016

Mobility models are invaluable for determining the performance of routing protocols in opportunistic networks. The movement of nodes has a significant influence on the topological structure and data transmission in networks. In this paper, we propose a new mobility model called the campus-based community mobility model (CBCNM) that closely reflects the daily life pattern of students on a real campus. Consequent on a discovery that the pause time of nodes in their community follows a power law distribution, instead of a classical exponential distribution, we abstract the semi-Markov model from the movement of the campus nodes and analyze its rationality. Then, using the semi-Markov algorithm to switch the movement of the nodes between communities, we infer the steady-state probability of node distribution at random time points. We verified the proposed CBCNM via numerical simulations and compared all the parameters with real data in several aspects, including the nodes' contact and inter-contact times. The results obtained indicate that the CBCNM is highly adaptive to an actual campus scenario. Further, the model is shown to have better data transmission network performance than conventional models under various routing strategies.