• Spatial Information Research
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• v.15 no.3
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• pp.311-322
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• 2007

Geovisual analytics is the new research area that looks fur the way to enable a truly synergetic work of human and visualization tool in analyzing spatio-temporal data. The research challenge for geovisual analytics is developing new geovisualization tools and enhancing human capabilities to analyse, envision, and reason a lot of spatio-temporal changes. With this research area, geovisual analytics is expected to be a new methodology for developing spatial decision support tools. This research is to integrate T scatter plot with computational method to classify the several patterns of the regional fright generation in Korea. The result of this work shows the capabilities provided by geovisual analytics to support spatial decision making.

• Journal of the Economic Geographical Society of Korea
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• v.20 no.2
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• pp.158-172
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• 2017

This study analyzes the time-space variability for the weekly passenger flow of the Seoul Subway system based on the dynamic visualization methods. For the purpose, we utilize one-week T-card transaction databases. By applying data mining algorithms, we extract passenger data for edge flows, on/off passengers at each subway station per minute interval time. It is practically intractable to analyze such spatio-temporal passenger flows by general statistical techniques. We employ dynamic visualization methods to analyze intuitively and to grasp effectively characteristics of the diurnal passenger flows on the Seoul Metropolitan Subway system during one week. As the result, we found that substantial differences exist on the spatio-temporal distribution patterns among days as well as between weekdays and weekend. We also investigates the time-space variability among eight major centers, and we found wide differences in their spatio-temporal distribution patterns.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.433-433
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• 2018

한국은 지진에 대한 관심이 낮았으나, 2016년 09월 12일 경상북도 경주에서 가장 큰 규모인 5.8의 지진이 발생하였으며, 강력한 지진이 발생할 수 있다는 경고가 이어지고 있다. 지진과 관련된 정확한 원인 분석과 정량적인 평가가 체계적으로 이루어지지 않고 있어, 규모와 빈도, 위험지역 분석 등 정밀한 평가와 예방대책을 마련해야 한다. 정량적인 지진 발생 분석을 위해 본 연구에서는 지진 발생과 지하수와 같은 수문기상학적인 인자에 의해 영향을 받는다는 가설을 세우고 지하수의 변동 패턴과 지진의 발생 패턴의 유사점을 추정하였다. 이를 위해 지진자료의 통계적인 특성을 분석하였다. 그리고 지질특성이나 지각 판 운동 외에도 수문순환이 영향을 미치는지 확인하기 위해 육지와 바다에서 발생한 지진으로 구분하여 지진발생횟수와 에너지를 분석하였다. 분석결과, 육지와 바다로 구분했을 때 바다에서 더 많은 지진이 일어났다. 또한 Wilcoxon rank-sum test 비모수 추정기법을 통하여 분석한 결과 서로 다른 성질을 보여 따로 분석하였다. 그 결과, 동해와 남해, 서해와 동해가 같은 성질을 보이는 것으로 분석되었다. 그리고 육지는 8월부터 이듬해 7월까지 지진발생의 한 주기를 이룰 가능성을 보였다. 그러나 바다는 육지와 정반대로 2월부터 7월까지 많은 지진 에너지가 발생하고 있으며, 1월까지는 에너지 수준이 상대적으로 낮은 것으로 분석되었다. 이와 같이 지하수가 육지에서 바다까지 유동하는 시간으로 인해 6개월의 시간지연이 발생하는 것으로 판단된다.

• Korean Journal of Cognitive Science
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• v.33 no.2
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• pp.109-133
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• 2022

Episodic memory consists of a core event and the associated contexts. Although the role of the hippocampus and its neighboring regions in contextual representations during encoding has become increasingly evident, it remains unclear how these regions handle various context-specific information other than spatio-temporal contexts. Using high-resolution functional MRI, we explored the patterns of the medial temporal lobe (MTL) and cortical regions' involvement during the encoding of various types of contextual information (i.e., journalism principle 5W1H): "Who did it?," "Why did it happen?," "What happened?," "When did it happen?," "Where did it happen?," and "How did it happen?" Participants answered six different contextual questions while looking at simple experimental events consisting of two faces with one object on the screen. The MTL was divided to sub-regions by hierarchical clustering from resting-state data. General linear model analyses revealed a stronger activation of MTL sub-regions, the prefrontal lobe (PFC), and the inferior parietal lobule (IPL) during social (Who), behavioral (How), and intentional (Why) contextual processing when compared with spatio-temporal (Where/When) contextual processing. To further investigate the functional networks involved in contextual encoding dissociation, a multivariate pattern analysis was conducted with features selected as the task-based connectivity links between the hippocampal subfields and PFC/IPL. Each social, behavioral, and intentional contextual processing was individually and successfully classified from spatio-temporal contextual processing, respectively. Thus, specific contexts in episodic memory, namely social, behavior, and intention, involve distinct functional connectivity patterns that are distinct from those for spatio-temporal contextual memory.

• The Journal of the Korea Contents Association
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• v.7 no.6
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• pp.9-21
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• 2007

In this paper, the hybrid methods are suggested, which use the direction angle information to present running trajectory and track the past locations through a small amount of vehicle's location information. In order to prove the effectiveness of the new technique suggested here, vehicle's location information are collected by running the vehicles moving objects under various conditions. Using the location informations and direction angle information collected with time intervals, the vehicl e's location information is abstracted, compared and analyzed. and I have proved that the suggested techniques are more effective by comparing them with others in various methods such as GPS TrackMaker, difference image techniques, consistency comparison, quantity comparison, vehicle's running distances and so on.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.1
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• pp.113-123
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• 2007

This study analyzed the appropriateness of the spatial distribution of fire stations and emergency medical facilities, the main providers of emergency medical care, in Busan. The area over which the 119 emergency medical services were situated in relation to the dispatch and transport of urgent rescue services was examined. Addresses of patients requiring 119 emergency services were obtained and stored as individual units so that they could be analyzed in a Geographic Information System(GIS). The time taken by emergency services to reach patients and transport them to a hospital or other facility was measured in seconds. By inputting additional information such as the location of the 119 dispatch centers, jurisdictions, and emergency medical facilities, the GIS allowed for analyses not only of the temporal but also the spatial aspects of emergency medical services. The results showed that of 16 Gu/Gun and 226 Eup/Myen/Dong in the Busan area, only 41% of Busan's emergency medical services could respond to and transport patients within five minutes. In all districts, most emergency medical services were provided within five to ten minutes. However, the pattern of hospital use to transfer patients to hospitals was inefficient. Based on the temporal and spatial distributions of fire stations and emergency medical agencies, and on their dispatch and transport times, this study sets out and compares ideal dispatch and transportation patterns for the efficient use of Busan's emergency medical services and resources.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.55-57
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• 2005

유비쿼터스 환경이 도래함에 따라 데이터 흐름이 신속하고 연속적으로 변화하고 있다. 이러한 스트림형태의 데이터는 데이터의 치명적 변화, 자주 발생하지 않는 패턴 등의 관점에서 데이터 분석을 필요로 하고 있다. 본 논문에서는 다단계의 추상화 데이터 분석이 용이한 다차원 분석에 기반하여 고정적인 공간활용만이 가능했던 기존 방식을 살펴본 후 이를 유동적으로 보완하여 공간 비용을 최소화 하면서 평균응답시간을 줄여주는 방법에 대해 논의한다. 또한 제안 방법의 시공간 비용을 수식으로 증명하고 기존 방법과의 비교 실험을 통하여 성능을 평가해 본다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.1
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• pp.451-458
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• 2011

In order to provide the optimal location based services such as the optimal moving path search or the scheduling pattern prediction, the extraction of significant moving pattern which is considered the temporal and spatial properties of the location-based historical data of the moving objects is essential. In this paper, for the extraction of significant moving pattern we propose the location generalization method which translates the location attributes of moving object into the spatial scope information based on $R^*$-tree for more efficient patterning the continuous changes of the location of moving objects and for indexing to the 2-dimensional spatial scope. The proposed method generates the moving sequences which is satisfied the constraints of the time interval between the spatial scopes using the generalized spatial data, and extracts the significant moving patterns using them. And it can be an efficient method for the temporal pattern mining or the analysis of moving transition of the moving objects to provide the optimal location based services.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1135-1139
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• 2006

가뭄은 홍수와 함께 인류역사상 가장 큰 재해로 인식되어 있다. 미해양대기청의 발표에 따르면 20세기 최대 자연재해의 상위 5위 안에 4개의 가뭄이 포함되어 있다. 이러한 기록은 가뭄이 동서고금을 막론하고 국가의 흥망성쇠를 좌우할 만큼 막대한 피해를 입혀왔음을 의미한다. 그러나 가뭄의 해석은 가뭄의 정의 자체가 확실하지 않고 서서히 찾아오는 자연재해이기 때문에 그 시작과 끝을 인식하기 어렵다. 아울러 그 진행속도도 굉장히 느리며 또한 장기간에 걸쳐 지속되는 특성을 가지고 있고 시공간적으로 전파된다. 따라서 가뭄의 해석은 굉장히 까다로운 것이라 할 수 있으며 그 해석방법 또한 다양할 수 밖에 없다. 본 연구에서는 우리나라 전역 59개 지점의 표준강수지수(Standard Precipitation Index) 시계열 자료에 대한 공간적 패턴분석과 시간적인 자료확장을 시도하였다. 경험적 직교함수(Emperical Orthogonal function) 해석을 이용하여 자료의 공간적인 패턴을 확인하였고 EOF 해석에서 나타난 EOF Coefficient Time Series를 추계학적 모형에 적용하여 시간적인 자료 확장을 수행하였다. 이렇게 확장된 긴 기간의 자료를 이용하면 재현기간에 대한 평균적인 가뭄심도를 추출할 수 있으며 실제 나타난 사상의 재현기간이 어느 정도인지 평가할 수 있다. 또한 이렇게 나타난 가뭄심도를 강수부족량으로 환산하여 우리나라 대권역별 물부족량을 평가하였다.

• Journal of Korean Society of Transportation
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• v.18 no.4
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• pp.75-85
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• 2000

The Purpose of this study is to analyze wether the composition of training sample have a relation with the Predictive ability and the learning results of ANNs(Artificial Neural Networks) fur predicting one cycle ahead of the queue length(veh.) in a signalized intersection. In this study, ANNs\` training sample is classified into the assumption of two cases. The first is to utilize time-series(Per cycle) data of queue length which would be detected by one detector (loop or video) The second is to use time-space correlated data(such as: a upstream feed-in flow, a link travel time, a approach maximum stationary queue length, a departure volume) which would be detected by a integrative vehicle detection systems (loop detector, video detector, RFIDs) which would be installed between the upstream node(intersection) and downstream node. The major findings from this paper is In Daechi Intersection(GangNamGu, Seoul), in the case of ANNs\` training sample constructed by time-space correlated data between the upstream node(intersection) and downstream node, the pattern recognition ability of an interrupted traffic flow is better.