• Journal of Cadastre & Land InformatiX
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• v.47 no.2
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• pp.233-254
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• 2017

The purpose of this study is to analyze the main factors influencing the severity of traffic accidents and to visualize spatiotemporal characteristics of traffic accidents in Seoul. To do this, we collected the traffic accident data that occurred in Seoul for four years from 2012 to 2015, and classified as slight, serious, and death traffic accidents according to the severity of traffic accidents. The analysis of spatiotemporal characteristics of traffic accidents was performed by kernel density analysis, hotspot analysis, space time cube analysis, and Emerging HotSpot Analysis. The factors affecting the severity of traffic accidents were analyzed using decision tree model. The results show that traffic accidents in Seoul are more frequent in suburbs than in central areas. Especially, traffic accidents concentrated in some commercial and entertainment areas in Seocho and Gangnam, and the traffic accidents were more and more intense over time. In the case of death traffic accidents, there were statistically significant hotspot areas in Yeongdeungpo-gu, Guro-gu, Jongno-gu, Jung-gu and Seongbuk. However, hotspots of death traffic accidents by time zone resulted in different patterns. In terms of traffic accident severity, the type of accident is the most important factor. The type of the road, the type of the vehicle, the time of the traffic accident, and the type of the violation of the regulations were ranked in order of importance. Regarding decision rules that cause serious traffic accidents, in case of van or truck, there is a high probability that a serious traffic accident will occur at a place where the width of the road is wide and the vehicle speed is high. In case of bicycle, car, motorcycle or the others there is a high probability that a serious traffic accident will occur under the same circumstances in the dawn time.

• Journal of KIISE:Databases
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• v.27 no.2
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• pp.165-174
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• 2000

Recent researches about range queries in OLAP are only concerned with applying an aggregation operator over a certain region. However, data analysts in real world need not only the simple range query pattern but also an extended range query pattern that finds ranges which satisfy a special condition specified by using several aggregation operators. In this work, we define the general form of the extended range query and propose an efficient processing method for the 'MAX -of-SUM' query, which is the representative form of the extended range query pattern. The MAX-of-SUM query finds the range which has the maximum range sum value in data cube where the size of the range is given. The proposed query processing method is based on the prediction of the scope of the range sum values. That is, the search space on the query processing can be reduced by using the result of the prediction, and hence, the query response time is also reduced.

• Journal of Korea Multimedia Society
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• v.12 no.10
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• pp.1363-1373
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• 2009

In a ubiquitous computing environment, people more and more become to use multiple displays. When using such ubiquitous displays, it is needed for users to seamlessly interact with the displays for a certain content. In this paper, we propose a seamless interface that allows users to see photos across multiple displays. Many photos can be displayed on a screen at the same time because they are shown in 3D space. And a group of photos is represented using a cube metaphor. A user can manipulate photos directly using a touch screen and also see the photos continuously using PDAs when the user moves to other places. In addition, the user can interact with the photos seamlessly using another display. The developed system was designed to interact according to user's movements and not to draw user's attention too much as a kind of ambient display. Using RFID and ultrasonic sensors it recognizes a user and the user's proximity to the display, and then automatically determines the screen image and the user interface accordingly.