• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.2
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• pp.24-35
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• 2019

In this study, a hotspot analysis was conducted to suggest a new method for interpreting soil heavy-metal contamination data of abandoned metal mines according to statistical significance level. The spatial autocorrelation of the data was analyzed using the Getis-Ord $Gi{\ast}$ statistic in order to check whether soil heavy metal contamination data showing abnormal values appeared concentrated or dispersed in a specific space. As a result, the statistically significant data showing abnormal values in the mine area could be classified as follows: (1) the contamination degree and the hotspot value (z-score) were both high, (2) the contamination degree was high but the z-score was low, (3) the contamination degree was low but the z-score was high and (4) the contamination degree and the z-score were both low. The proposed method can be used to interpret the soil heavy metal contamination data according to the statistical significance level and to support a rational decision for soil contamination management in abandoned mines.

• Journal of the Economic Geographical Society of Korea
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• v.17 no.2
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• pp.402-419
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• 2014

This study attempts to investigate the spatial characteristics of private tutoring markets for adults which have been expanded rapidly with labor market changes in Korea. In particular, For the purpose, we examine thoroughly various indies of labor markets and private tutoring markets for adults in Korea in first and then analyze the spatial characteristics. We classify private tutoring institutes for adults into two categories by job-statuses and education levels, and analyze the spatial distribution patterns of the attendants of the classes. In order to understand the spatial characteristic of their distributions, we distinguish whether there exist the spatial autocorrelation or not by applying Moran's I values for each categories in first. We also examine the spatial cluster patterns by Hot spots analysis utilizing $G^*$ statistics. Multiple linear regression models are developed for each category to explain the relationships between the spatial distributions of private tutoring institutes and geographical variables.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.4
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• pp.65-76
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• 2017

The purpose of this study was to present a prediction model that reflects crime risk area analysis, including factors and spatial characteristics, as a precursor to preparing an alternative plan for crime prevention and design. This analysis of criminal cases in high-risk areas revealed clusters in which approximately 25% of the cases within the study area occurred, distributed evenly throughout the region. This means that using a multiple linear regression model might overestimate the crime rate in some regions and underestimate in others. It also suggests that the number of deserted houses in an analyzed region has a negative relationship with the dependent variable, based on the multiple linear regression model results, and can also have different influences depending on the region. These results reveal that closure signs in a study area affect the dependent variable differently, depending on the region, rather than a simple or direct relationship with the dependent variable, as indicated by the results of the multiple linear regression model.

• Journal of Convergence for Information Technology
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• v.8 no.1
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• pp.161-171
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• 2018

This study set out to identify crime vulnerable areas with the GIS spatial analysis technique for the prediction of crimes. Crime vulnerable areas were extracted from the statistics of crimes with the GIS hotspot analysis technique and the inverse distance weighted(IDW) method applied to different crimes according to places and use districts. The scope of surveillance and weight were calculated for each of CPTED surveillance elements including CCTV, streetlamp, patrol division, and police substation. Maps of crime vulnerable areas were overlapped one after another to make a CPTED-based one expressed in four grades(safety, attention, warning, and risk).

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.4
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• pp.119-119
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• 2023

• Korean Security Journal
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• no.45
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• pp.243-271
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• 2015

The primary aim of this study is to provide effective operational directions of multi-purpose maneuver patrol via practical analysis on the fear of crime and its impact factors in the Hot Spots Policing target region. Comparative Analysis on fear of crime and its impact factors such as informal social control, disorder, and the perception of police activities is conducted in regions of maneuver patrol against its neighborhood. In Conclusion, no evident differences in fear of crime between the regions of maneuver patrol and its neighborhood were found. However, regions of maneuver patrol displayed significant distinctions in informal social control and perception of crime frequency in comparison to its neighborhood of no such patrol. In addition, it was noticed that in both regions disorder and perception of crime frequency served as the impact factors of fear of crime, which in part exhibits positive relationship with perception of hot spots policing. This study concludes that criterion in deciding on the regions of maneuver patrol should include subjective impact factors such as fear of crime. Furthermore, it suggests that along with the current unsatisfactory maneuver patrol system there needs specific guideline to enhance the perception of police activities including strengthened interactions with residents, improvement in social disorder.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.54-69
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• 2023

This study investigated the distribution of users in urban parks to overcome the limitations of existing research, which made it difficult to determine where data came was collected. It aimed to provide implications for park planning and management based on user distribution using mobile signal data. Five urban parks in Seongdong-gu, Seoul, with various physical characteristics, were selected. Mobile signal data provided by the Seoul Big Data Campus was used to identify the distribution of user inflow through hot spot analysis per park. The relationship between urban context and park influence area was derived. Seoul Forest (P1) and Seongsu Park (P3), which have a high proportion of commercial spaces around the park, showed wider user hotspots compared to Eungbong Park (P2), Dokseodang Park (P4), and Daehyunsan Park (P5), which were located in residential areas. Parks with a significant presence of commercial spaces had a broader influence, while parks with larger sizes and gentle slopes exhibited wider influence areas. This study proposed a novel data-based approach to urban park planning and management based on the inflow distribution of park users. Through this research, valuable insights were derived that could be utilized for urban park planning and management, aiming to enhance the effectiveness and efficiency of park utilization.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.2
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• pp.95-104
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• 2018

This study has the purpose of suggesting the method to analyze the spatiotemporal change of satisfaction concerning the officially assessed land price using geostatistical analysis. Analyzing the spatial distribution characteristic of officially assessed land price using present GIS (Geographic Information System) or is staying at qualitatively suggesting the improvement method of the officially assessed land price system. Grouping the appeal strength based on the official price and opinion price of officially assessed land price, GIS DB (Database) was constructed and the time seriate satisfaction were analyzed and compared through spatial density analysis and spatial autocorrelation analysis. As a result, it was found that the difference between the official price and the applicant's price differed depending on individual land, but most of the respondents requested the increase or the reduction of the average land price, which resulted in a large number of request. Analyzing the satisfaction of the officially assessed land price by using GIS, it was known that satisfaction of officially assessed land price could be analyzed by using the difference of the opinion price and not only the officially assessed land price. Spatiotemporal change of officially assessed land price satisfaction was known to be possible through spatiotemporal pattern analysis method such as spatiotemporal auto-corelation analysis and hotspot analysis etc using GIS. In short, regionally positive or negative significant relationship was investigated through spatiotemporal analysis using annual data.

• 한국정보통신설비학회:학술대회논문집
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• 2003.08a
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• pp.240-243
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• 2003

본 논문에서는 Agere Systems사의 네트워크 프로세서를 사용한 고성능 IP-DiffServ/IP-MPLS 시스템의 구조를 제안하고 성능을 분석한다. 제안한 시스템은 기가비트 이더넷 뿐만 아니라 ATM과 POS 등 다양한 인터페이스를 제공하며 코어 및 에지 라우터로서 MPLS LER 또는 LSR로의 역할을 수행한다. 성능분석은 OPNET을 사용하여 시스템을 모델링한 후 입력 트래픽에 대해서 DiffServ 클래스별 지연시간과 지연의 주된 원인을 분석한다. 그리고 이를 바탕으로 시스템의 성능을 극대화할수 있는 네트워크 프로세서의 최적 파라메터를 도출한다. 성능분석 결과, 시스템이 각 서비스 클래스에 대해서 원활한 서비스를 제공하기 위해서는 프리미엄 서비스에는 최고의 우선순위를 부여하여 큐에 데이터 블럭들이 찰 때 마다. 즉시 서비스해 주어야 한다는 것을 알 수 있었다. 그리고 트래픽이 특정 출구 라인카드로 몰리는 핫스팟이 발생할 경우 트래픽의 지연이 증가하게되는데 이 지연의 주요 원인은 출구 라인카드에서의 큐잉에 의한 것임을 알 수 있었다.

• Journal of KIISE:Software and Applications
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• v.27 no.9
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• pp.920-930
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• 2000

컴포넌트 기반의 소프트웨어 개발이 소프트웨어 복잡성, 비용, 그리고 품질을 해결하기 위한 새로운 대안으로 소개되고 있다. COM, Enterprise JavaBeans, CORBA 컴포넌트 모델등과 같은 다양한 컴포넌트 아키텍쳐들이 소개되고 있으며 컴포넌트 기반의 소프트웨어 개발 방법론과 여러 CASE 도구들이 이를 지원하고 있다.[1,2,3,4]. 그러나 현재 컴포넌트를 구현할 수 있는 기술은 제시되어 있지만 컴포넌트를 모델링하는 기법들에 대한 연구는 미약한 상태이다. 본 논문에서는 도메인 분석에서 공통성과 가변성 추출 및 클러스터링 기법을 이용한 컴포넌트를 분석하는 기법을 제시한다. 즉 컴포넌트 추출 기법, 컴포넌트의 핫스팟(또는 가변성)표현 기법, 컴포넌트 요구사항 정의 기법 등을 제시한다. 컴포넌트 개발에 있어서 이러한 모델링 기법을 적용함으로써 컴포넌트를 효율적으로 개발할 수 있을 뿐만 아니라 재사용성이 높은 고품질의 컴포넌트 개발을 지원할 수 있다.