• Journal of Korean Library and Information Science Society
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• v.45 no.2
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• pp.283-309
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• 2014

A rhetorical segment in traditional abstract displaying a sign of particular function is frequently referred to as a move. One of the most common moves is the Background, Aim, Method, Results, and Conclusion (BAMRC). The objective of this paper is to investigate the move patterns of research article abstracts in the field of social sciences based on BAMRC moves. Using the Scopus bibliographic database, a total of 467 abstracts from 298 research journals in the field of social sciences were analyzed. The result showed a wide range of move patterns. The implication of the result of this study suggests the existing traditional abstracts in social sciences might not be sufficiently "informative" due to missing moves and due to various move orders. To this end, automatically mapping moves in traditional abstracts to sub-headings in structured abstracts can be a more challenging task, requiring additional procedures to resolve these types of compatibility issues. Future studies can compare this study's result to other fields or disciplines within social sciences in order to find a more precise nature of abstracts in the field of social sciences.

• Journal of the Korea Convergence Society
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• v.10 no.12
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• pp.315-325
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• 2019

The purpose of this study is to design and construct a data mart that anyone can easily analyze subway OD movement patterns. Subway OD data of the year 2017 was downloaded from the Seoul Open Data Plaza and used as the source data. A multidimensional model was designed, and Gaussian mixed cluster analysis and visualization analysis using Tableau were performed. Interestingly, movement between suburban and Seoul accounts for 23% of the total traffic. The passengers of Suwon Station move to the suburbs much more than Seoul, while Pangyo Station mostly moves to Seoul. As a result of Gaussian mixed cluster, eight clusters of OD segments were found, and the characteristics of each cluster were characterized by segment distance and passenger size.

• Information Systems Review
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• v.7 no.1
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• pp.65-80
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• 2005

The Seoul Metropolitan Subway Corporation (SMS) and the Seoul Metropolitan Rapid Transit Corporation (SMRT), which manage the city's eight subway lines, are intending to overcome their operational inefficiencies. The two investigators of the paper realize with emphasis that it is essential for the two subway authorities to analyze subway transit data prior to put policies and plans into practice. In this paper, the investigators propose a new, and an intuitive, way of analyzing subway passenger transit patterns. To achieve this goal, they have implemented a data mart by blending the "Pass Card" log data into the multidimensional model. The subway passenger's transit patterns and the practical implications of this system are also investigated.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1805-1815
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• 2022

In 2022, wildfires broke out in Uljin-gun and Samcheok-si, which set the record for the longest forest fire in Korea, but there were no casualties. To protect local residents from wildfires, they must evacuate. Predicting the demand for evacuation in the event of wildfires is essential for the efficiency of disaster management. The purpose of this study is to analyze the human mobility patterns according to the occurrence of Uljin-gun and Samcheok-si wildfires. SKT floating population data was used in this study to analyze the human mobility patterns in Uljin-gun and Samcheok-si. The main findings are as follows. First, while the movement of the resident and visiting population decreased, the movement of the worker population was found to be similar to normal. Second, the resident population of Buk-myeon, Uljin-gun moved to the surrounding area to avoid the wildfires. Third, the region is an area judged to be safe from wildfires, and this mobility patterns are related to emergency disaster text messages. This study confirmed human mobility patterns of the population in the area where the wildfires through the floating population data, which is quantitative data. This suggests that it is important to guide residents to shelters through emergency text messages to minimize damage in the event of wildfires.

• Proceedings of the Korean Institute of Landscape Architecture Conference
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• 2018.03a
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• pp.59-59
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• 2018

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.1732-1735
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• 2012

인간은 일주일 단위로 유사한 행동 패턴을 가진다고 한다. 이런 점에서 일주일 단위의 시간-공간 기록의 형태인 인간 이동 데이터를 이용하면, 인간의 행동 패턴을 유추해 낼 수 있다. 본 논문에서 인간의 행동을 유추하기 위해 BPN알고리즘을 사용하였다. BPN알고리즘에 대해 설명하고, 인간 이동의 예측에 관한 적용에 관한 BPN알고리즘의 설계 과정을 논의한다. 그리고 해당 실험의 결과와 분석을 제시한다.

• Proceedings of the KAIS Fall Conference
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• 2009.12a
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• pp.806-809
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• 2009

본 논문에서는 FMC의 로봇 경로 분석 및 설계를 하기 위해 시뮬레이션을 이용해 FMC의 로봇 패턴을 분석하고 그 결과를 이용해 최적의 로봇 경로를 설계하는 방법을 제시하였다. 전형적인 FMC를 시뮬레이션으로 설계하고 설비에서 신호를 추출 해 순차 패턴 마이닝을 이용해 로봇의 최적 이동 경로를 도출하는 방법을 제시하였다. 이러한 신호의 패턴을 이용한 분석 방법은 로봇의 경로 설계를 도출하기가 용이하여 최적의 경로를 설계하여 FMC에 적용한 결과 기존보다 총 처리량의 증가와 총 처리시간 감소를 가져왔다. 또한 이 방법은 FMC 뿐만 아니라 로봇이 있는 모든 생산라인에 시뮬레이션을 통해 분석이 가능하기 때문에 생산성 향상에 크게 기여할 것으로 기대된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.1-1
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• 2015

최근 연구에 의하면 엘니뇨 패턴의 중심이 열대 동태평양에서 중앙태평양으로 이동하는 양상을 보이고 있는 것으로 보고되고 있으며 태평양 연안 국가를 중심으로 이에 대한 연구가 많이 진행되고 있다. 본 연구에서는 진화하는 엘니뇨패턴과 관련하여 한반도의 영향을 미치는 태풍을 중심으로 태풍의 활동특성과 그에 따른 지역별 태풍강우의 특성을 비교 분석하였다. CT/WP 엘니뇨와 관련하여 북서태평양 지역에서 발생한 태풍이 한반도에 미치는 영향을 분석하기 위하여 태풍에 의해 발생한 여름철 강우와 중호우 사상의 발생특성을 분석하였다. CT 엘니뇨해에는 한반도의 서남부 지역에서 태풍에 의한 여름철 강우가 감소하는 경향이 나타났으며, 동북부 지역에서는 증가하는 특성이 있음을 확인하였다. 또한 WP 엘니뇨 해에는 한반도 대부분 지역에서 태풍에 의한 여름철 강우가 증가하였으며, 중북부지역과 중서부 지역에서 통계적으로 유의한 증가패턴이 있는 것으로 분석되었다. 본 연구의 성과는 태풍을 고려한 지역 맞춤형 기반시설 확충 및 유역대책 수립, 수자원 확보 등에 대한 기초자료로 활용 될 수 있을 것으로 기대된다.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.2
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• pp.185-190
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• 2006

Most systems in ubiquitous computing analyze context information of users which have similar propensity with demographics methods and collaborative filtering to provide personalized recommendation services. The systems have mostly used static context information such as sex, age, job, and purchase history. However the systems have limitation to analyze users' propensity accurately and to provide personalized recommendation services in real-time, because they have difficulty in considering users situation as moving path. In this paper we use users' moving path of dynamic context to consider users situation. For the prediction accuracy we complete with a path completion algorithm to moving path which is inputted to RSOM. We train the moving path to be completed by RSOM, analyze users' moving pattern and predict a future moving path. Then we recommend the nearest product on the prediction path with users' high preference in real-time. As the experimental result, MAE is lower than 0.5 averagely and we confirmed our method can predict users moving path correctly.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.8
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• pp.321-328
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• 2014

In this paper, we present a MapReduce-based mobility pattern mining system which can predict efficiently the next place of mobile users. It learns the mobility pattern model of each user, represented by Hidden Markov Models(HMM), from a large-scale trajectory dataset, and then predicts the next place for the user to visit by applying the learned models to the current trajectory. Our system consists of two parts: the back-end part, in which the mobility pattern models are learned for individual users, and the front-end part, where the next place for a certain user to visit is predicted based on the mobility pattern models. While the back-end part comprises of three distinct MapReduce modules for POI extraction, trajectory transformation, and mobility pattern model learning, the front-end part has two different modules for candidate route generation and next place prediction. Map and reduce functions of each module in our system were designed to utilize the underlying Hadoop infrastructure enough to maximize the parallel processing. We performed experiments to evaluate the performance of the proposed system by using a large-scale open benchmark dataset, GeoLife, and then could make sure of high performance of our system as results of the experiments.