• Journal of the Korean Data and Information Science Society
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• 제26권5호
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• pp.1061-1069
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• 2015

최근 교통 분야에서 발생하는 교통 빅데이터 (교통카드 데이터, ATMS 데이터 등)의 분석결과를 교통 정책에 활용하는 사례가 늘어나고 있는 추세이다. 또한 교통 데이터 분석 기법을 기존의 단순 빈도 분석 기법에서 다양한 데이터 마이닝 기법으로 확장하여 교통 데이터 속에 숨어있는 의미를 파악하려는 연구도 진행되고 있다. 본 연구에서는 교통카드 데이터에 대하여 토픽모델링 기법 중의 하나인 LDA (Latent Dirichlet Allocation) 기법을 적용하여 청주시 버스 승객들의 이동패턴을 분석한다. 이를 위해 교통카드 데이터의 하차 결측치를 추정하고, LDA 기법을 적용하여 이동패턴을 추출하였다. 또한 LDA 분석으로 도출된 값을 측정값으로 하여 다차원적 분석을 함으로써 청주시 버스 승객들의 이동패턴 특징을 파악할 수 있다. 분석 결과, 청주시의 경우 크게 1) 시외지역에서 터미널을 이용해 청주시에서 유입되는 패턴, 2) 주거지역에서 상업지역으로 이동하는 패턴, 3) 청주 인근 학교에서 상업 지역 (청주 중심가)로 이동하는 패턴을 발견할 수 있었다. 이동패턴은 도시 계획, 대중교통서비스 향상, 버스 노선 신설 등 다양한 교통정책의 수립에 활용될 수 있을 것으로 기대된다.

• 한국멀티미디어학회논문지
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• 제25권8호
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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.

• 대한산업공학회지
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• 제34권2호
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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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• 제8권3호
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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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• 제8권2호
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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.

• 가정과삶의질연구
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• 제7권2호
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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.

• 한국ITS학회 논문지
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• 제22권3호
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• pp.88-103
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• 2023

최근 4차 산업혁명 기술의 발전에 힘입어 교통시스템은 차량 및 사람의 개별 이동궤적과 관련된 모빌리티 데이터를 대용량으로 산출하고 있다. 개인정보가 포함된 모빌리티 데이터를 활용하는 데에는 많은 제약이 존재하므로, 우리나라는 데이터 3법 개정과 데이터 기본법 제정을 통해 가명정보의 생성 및 가공과 이에 대한 분석 및 활용을 별도의 기관 및 기술을 적용하여 이원적으로 관리하고 있다. 그러나 이러한 이원적 접근은 데이터 생명주기 전 과정을 안전하게 지원하지 못할 뿐만 아니라 처리 시간 및 비용 측면의 비효율성의 문제를 갖고 있다. 따라서 본 연구는, 기존의 결합전문기관과 데이터안심구역이 갖는 문제점을 보완하기 위하여, 모빌리티 데이터의 생성 및 가공, 그리고 분석 및 활용 과정을 통합 및 일원화한 통합 데이터안심구역 프레임워크를 제시한다. 즉, 데이터 처리를 위한 통합 프로세스를 재설계하고 공통 요구사항 및 핵심요소기술을 도출하여 모빌리티 데이터의 생명주기 전체를 원스톱으로 활용, 관리할 수 있는 차세대형 통합 데이터안심구역 시스템의 아키텍처를 제시한다.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2007년도 추계학술대회 및 정기총회
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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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• 제7권12호
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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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• 제10권3호
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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.