• Korea journal of population studies
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• v.24 no.2
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• pp.149-177
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• 2001

This is a study on age-crime curve in Korea. Three data was used in this study as following: First is the crime statistics as aggregated data. Second is the police record(N=3.541 offences) of the male ex-offenders(N=988) who have been released in eleven prisons in 1987 as individual data. Third is the self-reported group-interview data(N=10.198 offences) administered to the male prisoners(N=979) in ten correctional facilities including eight adult prisons, one juvenile prison and one juvenile training center as another individual data. Generally, the right-skewness of age-crime curve has been explained through the difference of crime rate between early starters and late starters. Moffitt explains that this is because of the higher participation rate of the juvenile period of adolescence-limited offenders, but Godttfredson and Hirschi explain that this is because of a similar distribution in the crime rate of both early starters and late starters. the analysis of this study shows that Godttfredson and Hirschi’s explanation on the generality of age-crime-curve distribution is correct, but this can be modified by various factors like a economic crisis. And the peak age of juvenile period is consistent with the Moffitt’s hypothesis that the peak age is contributed to the increase of crime rate of late starters, not with Godttfredson and Hirschi’s one.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.1
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• pp.12-25
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• 2009

The aim of this study is to analyze the periodical and spatial characteristics of urban crime and to find out the factors that affect the crime occurrence. For these, crime data of Masan City was examined and crime occurrence pattern is ploted on a map using crime density and criminal hotspot analysis. The spatial relationship of crime occurrence and factors affecting crime were also investigated using ESDA (Exploratory Spatial Data Analysis) and SAR (Spatial Auto-Regression) model. As a result, it was found that crimes had strong tendency of happening during a certain period of time and with spatial contiguity. Spatial contiguity of crimes was made clear through the spatial autocorrelation analysis on 5 major crimes. Especially, robbery revealed the highest spatial autocorrelation. However as a autocorrelation model, Spatial Error Model(SEM) had statistically the highest goodness of fit. Moreover, the model proved that old age population ratio, property tax, wholesale-retail shop number, and retail & wholesale number were statistically significant that affect crime occurrence of 5 most major crimes and theft crime. However population density affected negatively on assault crime. Lastly, the findings of this study are expected to provide meaningful ideas to make our cities safer with U-City strategies and services.

• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.283-288
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• 2021

The purpose of this paper is to provide basic data for related studies by comparing and analyzing crimes committed by security guards through criminal statistical analysis, and to contribute to the sound development of the private security industry by strengthening the professional ethics of security guards and reducing guard crimes. The purpose. As a results of a comparative analysis of the number of crimes by security guards and the crime rate are as follows. Although the total number of crimes committed in Korea and the number of crimes committed by security guards decreased every year, the crime rate of security guards was higher than the average crime rate. felonious crimes, violent crimes, customs crimes, and special economic crimes were consistently high. As a countermeasure against the results, first, interest in security guard crimes as perpetrators rather than as victims, second, reinforcement of professional ethics education through new training and job training, third, academic development and systematic It appeared as a specification of the definition and current status of security guards for the study.

• Journal of the Economic Geographical Society of Korea
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• v.12 no.2
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• pp.179-194
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• 2009

The spatial distribution of crime incidences in urban neighborhoods is a reflection of their socio-economic environment and spatial inter-relations. Spatial interactions between offenders and victims lead to spatial autocorrelation of the crime incidences. The spatial autocorrelation among the incidences biases the interpretation of the ecological model in OLS framework. This research investigates residential crimes using residential burglaries and robberies occurred in the city of Columbus, Ohio, for 2000. In particular, the spatial distribution of incidence rates of residential crimes are accounted in OLS framework using eigenvectors, which reflect spatial dependence in crime patterns. Result presents that handling spatial autocorrelation enhanced model estimation, and both economic deprivation and crime opportunity are turned out significant in estimating residential crime rates.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.1143-1145
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• 2012

본 연구에서는 인천 지역의 범죄의 특성 지역을 분석하기 위하여 기존의 이론적인 논의에 기초하며 AHP와 GIS와 연계를 통해 분석하고자 하였다. 이를 위해 인천의 범죄 우발지역을 볼 수 있는 공간적 패턴과 경찰서 내지 파출소의 적지를 선정하고 자료 분석 및 데이터 수집과 통틀어 공간 분석을 수행하며 이러한 분석을 통해 얻어진 여러 가지 요인들과 범죄 율을 나타내어 최종 자료를 구현하기 위한 연구를 한다. 범죄 율의 공간적 표현을 위해서 수식을 이용하여 범죄 율을 구했으며 인구 및 정확한 데이터들을 수집하여 분석하고 그대로 반영한다. AHP를 이용하여 설문조사 및 객관적인 판단과 가중치를 판단할 수 있는 중요한 척도가 되었으며, 이것들을 반영하여 최종 결과물에 현실성을 더하여, 실제로 예방조치를 취할 수 있도록 할 수 있을 것이다. 또한 GIS 소프트웨어에서 제공되는 좌표체계와 데이터베이스 및 SQL 등을 이용하여 현실성과 정밀성을 더하여 활용될 수 있음을 확인하였다.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.1
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• pp.49-56
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• 2019

Urban green spaces have been contributing to the improvement of environmental, mental, and physical health for humans. In addition, recent studies showed the potential role of vegetation in reducing the amount of crime in inner-city neighborhoods at the micro-scale level. However, little is known about the positive role of urban green areas in improving urban safety at the regional level. The purpose of this study is to examine the relationship between urban green areas and actual outdoor crime rates, while also considering socio-demographic factors. The study area is the city of Austin, Texas, USA, which consists of 506 block groups. This study utilized socio-demographic factors based on U.S. Census data and vegetation-related factors utilizing GIS and ENVI software. For analyses, the analysis of variance (ANOVA) and an ordinary least square (OLS) regression were utilized. The results from ANOVA showed that yearly crime rates per acre for areas having 0%~25% trees in their neighborhoods were 0.46% and 1.05% higher than those of having 25%~50% and >50% trees in the neighborhoods, respectively. The results from the OLS regression represented that income, NDVI and park rates in neighborhoods were negatively associated with the crime rate per acre, whereas the percentage of minorities and the percentage of teenage school dropouts were positively associated with the crime rate per acre. This study implies that urban green areas may help to improve the safety of urban areas.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.125-133
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• 2016

In recent years, various crimes such as "random killing' crime continue to rise. Despite the government's crime prevention efforts and crime related researches, crime increases and a different approach is needed. Therefore, this study proposes the alternative for crime prevention by analyzing big data. To achieve this objective, this study was to perform visualization utilizing the histogram, the bubble chart and the hit map and association analysis. To analyze the relationship between crime and some variables, this study analyzed data of Seongnam city, Korea National Police Agency and etc. The results of analysis showed that CCTV will be to reduce the crime rate and security light is not significantly relevant. And the result showed that other types of crime focused by time of the day and day of the week and showed that an increase of the foreigners and crime increase are associated. This study presents a scheme for reducing the crime rate on the basis of this analysis result.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.351-353
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• 2020

급변하는 현대사회에서 각종 범죄가 고도로 지능화, 전문화 되고 있을 뿐 만 아니라 매년 범죄율이 증가하고 있다. 범죄수사에서 범죄자를 검거하기 위해서는 '골든 타임'인 초기 단계가 가장 중요하다. 따라서 CCTV를 일일이 돌려보던 기존의 비효율적인 수사방식이 아닌, 얼굴인식기술을 활용해 골든타임 안에 범죄자를 검거 할 수 있도록 도와주는 얼굴인식기반 범죄수사 시스템을 제안한다. 얼굴인식 프로그램을 사용하여 CCTV 영상 속 범죄자가 있다면, 곧바로 얼굴을 인식해 표시 해줌으로써 단시간 안에 범죄자의 이동경로를 파악한다. 이후 이동경로 및 수사정보를 웹페이지를 통해 다른 경찰관들과 공유해 범죄자를 빠르게 검거하는 시스템을 제작하였다. 제작과정에서 얼굴인식관련 기술은 Deep Metric CNN(triplet), Resnet, Knn classification을 사용해 python으로 구현하였다. 통신을 위한 웹서버는 Bitnami를 통해 구축했으며, NAT, DHCP, Port Fowarding 기술을 사용했다. 마지막으로 웹페이지는 HTML, PHP, CSS 등을 통해 제작해 수사정보를 주고 받을 수 있게 제작하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.251-254
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• 2020

매년 1인 가구를 대상으로 한 범죄가 증가하고 있다. 이에 따라 지문인식, 스마트키와 같은 도어록 제품들이 출시되었지만 오히려 범죄에 악용되는 사례들이 발생하였다. 본 논문에서는 얼굴인식장치(face identifier, FI)를 통해 객체를 인식하고, 원격 도어록 관리자(remote door lock manager, RDM)를 통해 잠금제어부(locking control unit, LCU)를 관리하는 긴급 상황 인식 스마트 도어록을 제안한다. 사용자의 얼굴을 얼마나 빠르고 정확하게 인식하는지 속도와 신뢰도에 대한 테스트를 진행하였고, 긴급 상황 시 사용자가 안전하게 집으로 들어갈 수 있음을 확인하였다. 본 제품을 통해 주거 침입, 스토킹 등 1인 가구 대상 범죄율과 도어록 악용 범죄율이 낮아질 것으로 사료된다.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.1 s.39
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• pp.3-7
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• 2007

To deal with the modern intellectual criminal acts, various efforts have been tried. Especially, it is not difficult to watch the recent activities to analyze the criminal characteristics spatially using computing and GIS technology. In this study, the spatial features and patterns of crime are investigated. Based on the real criminal record in Seoul Korea, the crime is reconstituted with four major categories such as assault, larceny, robbery, and rape. Then the variables are derived based on the theory of criminology. The kernal density analysis is performed to investigate the criminal distribution, and the correlation between the main criminal causes and the criminal outbreak is examined by buffering analysis. In addition, the land price and land usages are correlated with social-economic factors of criminal patterns to produce the final crime map.