• 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.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 Intelligence and Information Systems
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• v.23 no.2
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• pp.89-105
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• 2017

As the advances of technology in mobile networking and the popularity of online social networks (OSNs), the mobile social networks (MSNs) provide opportunities for marketing strategy. Therefore, understanding the information diffusion in the emerging MSNs is a critical issue. The information diffusion address a problem of how to find the proper initial nodes who can effectively propagate as widely as possible in the minimum amount of time. We propose a new diffusion scheme, called Hotspot DBC, which is to find k influential nodes considering each node's mobility behavior in the hotspot zones. Our experiments were conducted in the Opportunistic Network Environment (ONE) using real GPS trace, to show that the proposed scheme results. In addition, we demonstrate that our proposed scheme outperforms other existing algorithms.

• 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.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05b
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• pp.1389-1392
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• 2003

최근 초고속인터넷의 급속한 확장과 무선 핫스팟(Hotspot)의 등장은 인터넷을 컴퓨터 통신의 중심에 두게 되었다. 이는 다양한 컴퓨터 통신의 매체들이 인터넷으로 통합되는 것을 의미하며 이러한 통합은 통신망의 물리적, 논리적인 구조에 많은 영향을 미치게 되었다. 본 논문은 Mobile IPv6와 VPN이 상호 연동하는 시나리오에서 발생되는 문제들을 추적한다. 끊김 없는 이동성을 제공하기 위해 제시된 솔루션을 분석하여, VPN 게이트웨이와 연동하는 GHA(Gateway Home Agent)의 하드웨어적인 구현을 제안하며 IPSec Based VPN이 아닌 환경과 새로이 제안된 내용들을 추가하여 성능분석이 가능한 테스트 베드의 구축을 제안한다.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2003.12a
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• pp.160-165
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• 2003

최근 들어 무선 랜에 대한 사람들의 인식이 높아지고, KT의 NESPOT과 같은 공중망 사업자들에 의한 핫스팟 서비스가 제공되면서 무선 랜의 수요 또한 급증하고 있다. 무선 랜의 사용자가 증가하면서 무선 랜 보안의 중요성 역시 증가하고 있으며, 실제로 무선 랜에서의 안전한 네트워킹을 위하여 여러 단체들이 다양한 방향에서 연구를 진행 중에 있다. 그 한 예가 802.1X인데, 이것은 인증 서버를 따로 두어 AP를 통해 네트워크에 접속하려는 사용자들을 인증하여 주는 것이다. 이 논문에서는 802.1X 인증 방법 중 X.509 기반의 인증서를 사용하여 서버와 클라이언트간의 상호 인증을 가능하게 하여 주는 EAP-TLS 환경을 분석하고, LINUX 환경에서 공개 소스로 구축하여, 실제로 무선 랜을 사용하는 환경에 적용하는 과정을 기술한다.

• 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 Korea Water Resources Association
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• v.56 no.5
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• pp.325-336
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• 2023

In August 2022, even though flood damage occurred in the metropolitan area due to heavy rain, drought warnings were issued in Jeolla province, which indicates that the regional drought is intensified recent years. To cope with regarding intensified regional droughts, many studies have been conducted to identify spatial patterns of the occurrence of meteorological drought, however, case studies of spatial clustering for water shortage are not sufficient. In this study, using the estimations of water shortage in the Han River Basin in 2030 of the Master Plans for National Water Management, the spatial characteristics of water shortage were analyzed to identify the hotspot areas based on the Local Moran's I and Getis-Ord Gi^*, which are representative indicators of spatial clustering analysis. The spatial characteristics of water shortage areas were verified based on the p-value and the Moran scatter plot. The overall results of for three anayisis periods (S0(1967-1983), S1(1984-2000), S2(2001-2018)) indicated that the lower Imjin River (#1023) was the hotspot for water shortage, and there are moving patterns of water shortage from the east of lower Imjin River (#1023) to the west during S2 compared to S0 and S1. In addition, the Yangyang-namdaecheon (#1301) was the HL area that is adjacent to a high water shortage area and a low water shortage area, and had water shortage pattern in S2 compared to S0 and S1.

• 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.