• Proceedings of the Korean Information Science Society Conference
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• 1999.10a
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• pp.584-586
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• 1999

소프트웨어 개발 시 기존 전문가들의 개발 경험을 재사용하는 작업은 개발 기간의 단축 및 비용의 절감의 효과를 가져올 수 있다. 이러한 재사용에 관련된 연구는 소프트웨어공학 분야에서 계속되어 그 하나로 객체지향 프레임워크를 들 수 있다. 객체지향 프레임워크는 검증된 소프트웨어 재사용 부품으로 특정 도메인에 대한 비즈니스 로직을 재사용할 수 있도록 구현된다. 프레임워크 내부에는 재사용되는 로직이 포함되어 있으며 프레임워크 사용자에 의해 커스터마이징 될 모듈을 정의하고 있다. 프레임워크 사용자는 프레임워크를 기반으로 어플리케이션을 개발함으로써 처음부터 개발을 시작하지 않으며 기 개발자들의 경험을 재사용하게 된다. 본 논문에서는 근래 크게 대두되고 있는 가상상점 도메인에 대한 프레임워크를 제시한다. 본 논문에서 제시하는 가사상점 프레임워크는 제인 프레임워크와 주문, 지불, 배달의 3개 서브프레임워크로 구성되며 각각의 프레임워크가 포함한 핫스팟, 제어흐름, 프레임워크 인터페이스를 중심으로 프레임워크의 구성요소 및 설계, 구현에 관한 사항을 기술한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.983-986
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• 2013

최근 남녀노소를 불문하고 컴퓨터를 활용한 일상생활의 편리함은 누구나 알고 있는 사실이며, 현대인의 바쁜 일상은 보다 나은 효율적인 생활을 추구하고 있다. 또한, 특정 장소에 가보지 않고 그곳을 컴퓨터를 통해 간단한 조작으로 가상의 공간을 탐색하여 비용과 시간을 절약 할 수 있는 장점이 있다. 따라서 본 논문에서는 파노라마 가상현실(panoramic virtual reality)을 이용해 보다 편리한 가상 세계의 탐색의 경험을 도운다. 가상현실을 구성하는 장면을 구성하는 이미지의 스티칭, 편집 그리고 가상머신의 이용법, 핫스팟을 통한 장소와 장소간의 상호작용에 대해서 소개한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.1029-1031
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• 2010

스마트폰이 활성화 되면서 자신만의 콘텐츠(사진, 글, 메모)를 스마트폰에서 작성하는 경우가 많아지게 되었다. 하지만 맛 집이나 데이트 코스 같은 핫스팟을 담은 콘텐츠를 블로그를 통해 공유하고 싶지만 그 방법이 한정되어 있다. 본 논문에서 다루는 GPS 블로그 서비스는 스마트폰에서 직접 블로그로 업로드 함으로써, 콘텐츠에 포함된 위치 정보를 블로그에 보다 빠르게 공유할 수 있다. 또한 현재 위치 정보를 맵을 통해서 블로그에 포스팅되기 때문에, 핫 스팟을 운영하는 업체 및 기업의 홍보를 보다 쉽게 가능하게 하는 효과가 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.1096-1099
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• 2007

무선LAN 환경에서는 대체로 AP(Access Point)의 신호세기 만으로 사용할 AP를 선택하므로, 모바일 노드 사용이 한 영역으로 집중되면 특정 AP에 혼잡이 초래되어 전체 네트워크의 사용 효율이 저하된다. 본 논문에서는 각 AP의 부하 정보를 이용해 핫스팟의 혼잡을 분산시키고 AP의 데이터 전송속도를 최대한 보장하는 AP 선택 정책을 제안하고 이를 응용하는 시스템을 구현하였다. 실측 데이터를 적용하여 시험한 결과, AP의 혼잡이 분산되고 네트워크 사용 효율이 기존 방식보다 우수함을 확인하였다.

• Korean Journal of Remote Sensing
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• v.33 no.5_1
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• pp.469-480
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• 2017

This study aims to understand the relationship between lineaments and epicenters in Geochang region, Gyungsangnam-do, South Korea. An instrumental observation of earthquakes has been started by Korea Meteorological Administration (KMA) since 1978 and there were 6 earthquakes with magnitude ranging 2 to 2.5 in Geochang region from 1978 to 2016. Lineaments were extracted from LANDSAT 8 satellite image and shaded relief map displayed in 3-dimension using Digital Elevation Model (DEM). Then, lineament density was statistically examined by hotspot analysis. Hexagonal grids were generated to perform the analysis because hexagonal pattern expresses lineaments with less discontinuity than square girds, and the size of the grid was selected to minimize a variance of lineament density. Since hotspot analysis measures the extent of clustering with Z score, Z scores computed with lineaments' frequency ($L_f$), length ($L_d$), and intersection ($L_t$) were used to find lineament clusters in the density map. Furthermore, the Z scores were extracted from the epicenters and examined to see the relevance of each density elements to epicenters. As a result, 15 among 18 densities,recorded as 3 elements in 6 epicenters, were higher than 1.65 which is 95% of the standard normal distribution. This indicates that epicenters coincide with high density area. Especially, $L_f$ and $L_t$ had a significant relationship with epicenter, being located in upper 95% of the standard normal distribution, except for one epicenter in $L_t$. This study can be used to identify potential seismic zones by improving the accuracy of expressing lineaments' spatial distribution and analyzing relationship between lineament density and epicenter. However, additional studies in wider study area with more epicenters are recommended to promote the results.

• 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.

• Spatial Information Research
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• v.20 no.1
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• pp.71-80
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• 2012

Carbon Point system is Climate Change Action Program by providing incentives in proportion to voluntary reduction of energy consumption such as electricity, gas and water for houses, commercial facilities. So far, existing researches have been limited to construction of GHG(Green House Gas) Inventory and have little attention to empirical impact analysis on carbon reduction policy regarding the residential section. Therefore, this paper is intended to provide convincing findings of impact analysis on carbon reduction, revolving around the carbon point system. For this, we firstly calculated the carbon emission by using electricity and gas usage data in household targeting to Seongbuk-Gu. Carrying out IPA and spatio-temporal analysis. Then, we are capable of visualizing spatial patterns from 2007 to 2009 as a macro analysis. Following that, we explored the effect on carbon point system through Ex ante-Ex post Analysis by paired t-test. To conclude, we can spatially identify the distribution with a significant difference between carbon emissions according to energy use as a micro analysis by Hot Spot to Analysis on point entities. It is to be hoped that this method will be utilized to establish various policies and to evaluate the effect of reduction of GHG.

• Journal of Cadastre & Land InformatiX
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• v.47 no.2
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• pp.5-18
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• 2017

The AMOEBA approach in this study supplements the Hotspot method that had not been fully capable of dealing with the ecotone issues in designating the Development Impact Fee (DIF) zones as had been seen in the preceding study by Kim and Choei (2017). The AMOEBA procedure shares the common Getis-Ord statistic with the Hotspot technique but is more adequate to figure out the ecotones. For the comparative purpose, simulations are run by both methods for a series of different scenarios in terms of analytic spatial units (here, the square grids) from 100m up to 400m; and the zonal outcomes by both methods are compared using a set of evaluative indicators. In terms of the numerical scores, the performances by the two methods are much comparable except that the former is slightly superior with respect to the avoidance of the oversized spread of the selected zones whereas so is the latter with respect to the ease of infrastructure installation. It remains yet to be investigated by the extended studies that include in-depth field surveys to figure out the causes as well as the meanings of such differences in zonal determinations.

• Journal of the Korean association of regional geographers
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• v.23 no.2
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• pp.376-387
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• 2017

This paper attempts to analyze the geographical characters of Twitter data and presents analysis potentials for social network analysis in geography. First, this paper suggests a methodology for a topic modeling-based approach in order to identify the geographical characteristics of tweets, including an analysis flow of Twitter data sets, tweet data collection and conversion, textural pre-processing and structural analysis, topic discovery, and interpretation of tweets' topics. GPS coordinates referencing tweets(geotweets) were extracted among sampled Twitter data sets because it contains the tweet place where it was created. This paper identifies a correlated relationship between some specific topics and local places in Jeju. This correlation is closely associated with some place names and local sites in Jeju Island. We assume it is the intention of tweeters to record their tweet places and to share and retweet with other tweeters in some cases. A surface density map shows the hotspots of tweets, detecting around some specific places and sites such as Jeju airport, sightseeing sites, and local places in Jeju Island. The hotspots show similar patterns of the floating population of Jeju, especially the thirty-year age group. In addition, a topic modeling algorithm is applied for the geographical topic discovery and comparison of the spatial patterns of tweets. Finally, this empirical analysis presents that Twitter data, as social network data, provide geographical significance, with topic modeling approach being useful in analyzing the textural features reflecting the geographical characteristics in large data sets of tweets.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.3
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• pp.14-28
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• 2010

The aim of this study is to investigate crime hotspot areas using the spatio-temporal cluster analysis which is possible to search simultaneously time range as well as space range as an alternative method of existing hotspot analysis only identifying crime occurrence distribution patterns in urban area. As for research method, first, crime data were collected from criminal registers provided by official police authority in M city, Gyeongnam and crime occurrence patterns were drafted on a map by using Geographic Information Systems(GIS). Second, by utilizing Ripley K-function and Space-Time Scan Statistics analysis, the spatio-temporal distribution of crime was examined. The results showed that the risk of crime was significantly clustered at relatively few places and the spatio-temporal clustered areas of crime were different from those predicted by existing spatial hotspot analysis such as kernel density analysis and k-means clustering analysis. Finally, it is expected that the results of this study can be not only utilized as a valuable reference data for establishing urban planning and crime prevention through environmental design(CPTED), but also made available for the allocation of police resources and the improvement of public security services.