• Journal of Korean Society for Geospatial Information Science
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• v.22 no.3
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• pp.71-77
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• 2014

People in the modern society want to live under safe and comfortable circumstances. As our society, however, is sharply developing, crimes are getting smarter and more difficult to treat. Above all, they often take place around us, and we are trying to cope with them variously in order to make our lives more comfortable and safer. In particular, five major crimes(Murde, Robber, Rape, Violence, Theft ) that most frequently occur in the real life are very threatening and fearful so it is necessary to deal with them with "the scientific method." In this study, therefore, we searched the frequency of crime by its type and analyzed spatial characteristics between crimes and criminal factors by using regression analysis and correlation analysis based on the crime data that has occurred around Geumjeng-gu, Busan so that we can confront five major crimes.

• Korean Journal of Culture and Social Issue
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• v.13 no.3
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• pp.127-153
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• 2007

The study aims to examine the effects of crime on societal anxiety. For this purpose, two studies were conducted. In study 1, the data were collected from 286 students(male 160, female 126) regarding perceived seriousness of crime, estimation of crime occurrence, societal anxiety, and estimation of change in these 3 variables every 3 years from 1993 to 2011. The means of the 3 variables were higher than the midpoint of the scale. And the means of all the 3 variables gradually increased from 1993 to 2011 and the change patterns were very similar. Furthermore, the estimation of crime occurrence and perceived seriousness of crime were significant predictors of societal anxiety. Study 2 was conducted to explore the effect of frequency estimation of the criminal acts on the societal anxiety. The data from 259 subjects(male 141, female 118) were analysed. The occurrence of frequency of 7 types of crimes including 25 criminal acts were estimated and societal anxiety was measured. The results of study 2 showed that only the major crime was significant a predictor of societal anxiety, and among the major crimes, arson was a significant predictor of the dependent variable. Implications and limits of the studies are discussed.

• Korean Security Journal
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• no.48
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• pp.147-176
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• 2016

Korean Peninsula is surrounded by ocean on three sides. Because of this geographical quality over 97% of export and import volumes are exchange by sea. Foreign ship and international passenger vessels carries foreign tourist and globalization and internationalization increases this trends. Leisure population grows with national income increase and interest of ocean. And accidents and incidents rates are also increases. Korea Coast Guard's jurisdiction area is 4.5 times bigger than our country. The length of coastline is 14,963km including islands. One patrol vessel is responsible for 24,068km and one coast guard substation is responsible for 94km. Efficient patrol activities can not be provided. This research focus on this problem. Analyze the status and trends of maritime crime and suggest efficient patrol activities. To deal with increasing maritime crime rate this study suggest to use geographical profile method which developed early 1900s in USA. This geographical profile analyse the spatial characteristic and mapping this result. With this result potential crime zone can be predicted. One of the result is hot spot management which gives data about habitual crime zone. In Korea National Police Agency adopt this method in 2008 and apply on patrol and crime prevention activity by analysis of different criteria. Korea National Police Agency analyse the crime rate with crime type, crime zone and potential crime zone, and hourly, regionally criteria. Korea Coast Guard need to adopt this method and apply on maritime to make maritime crime map, which shows type of crime with regional, periodical result. With this geographical profiling we can set a Criminal Point which shows the place where the crime often occurs. The Criminal Points are set with the data of numerous rates such as homicide, robbery, burglary, missing, collision which happened in ocean. Set this crime as the major crime and manage the data more thoroughly. I expect to enhance the reinforcement of marine crime using this Criminal Points. Because this points will give us efficient way to prevent the maritime crime by placing the patrol vessel where they needed most.

• Spatial Information Research
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• v.8 no.2
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• pp.213-232
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• 2000

It is important to scrutinize spatial patterns in crime analysis since crime data has geographical attribute in itself. We focus on the development of ¨Crime Analysis GIS¨ prototype which can discover spatial patterns in crime data by integrating mapping functions of GIS and spatial analysis techniques. The structure of this system involves integration of DBMS and GIS, and the major functions of the system include (i) exploring spatial distribution of point data, (ii) mapping hot-spot, (iii) clustering analysis of crime occurrence, and (iv) analyzing aggregated areal data. The process of design and implementation of this system is based on object-oriented methodologies. A web-based extension of the prototype using 3-tier architecture is currently under development.

• Journal of Industrial Convergence
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• v.21 no.6
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• pp.13-21
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• 2023

The purpose of this study is to investigate the relationship between the amount of media coverage related to drug crimes and the actual number of drug-related arrests. It aims to determine the implications of this relationship for the formulation of police policies in response to drug crimes. To achieve this, we collected and analyzed 50,355 domestic online media coverage data from 2001 to 2022 and drug crime arrest data compiled by the National Police Agency. The analysis confirmed a significant causal relationship between the amount of online media coverage of drug crimes and the actual number of drug crime arrests. This relationship was found to be influenced by the existence of dominant issues and the relevance of famous incidents. It was determined that media coverage was also influenced by public interest beyond drug crime arrest numbers. Based on these research findings, the police have proposed the need to monitor the amount of crime-related media coverage and enhance security capabilities for crimes that receive public attention in order to gain the trust of the citizens.

• Korean Institute of Interior Design Journal
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• v.22 no.2
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• pp.211-219
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• 2013

The purpose of this study is to propose the environmental planning guidelines of elementary school settings for a crime safety. The research methodologies To achieve the goal, the literature review analysis and the survey were used as main research methodologies. The survey is organized as follows. First, elementary education facilities were divided into 20 spaces based on the major space. Second, after analyzing the domestic and foreign CPTED Guidelines, elements of environmental planning were classified to fit in the space. Based on this, the expert survey was conducted. The results of this study are as follows; First, it is necessary to consider specific places such as 'toilets', 'parking lot', 'in-between space', 'main access road', 'sub-access road' and 'harmful facilities around school' for safer school environment. Second, it is significant to plan 'equipment facilities' and 'outdoor space in the school setting' with priority for elementary education environment. Third, environmental planning elements for safer elementary schools can be classified into 9 factors(types) including 'natural surveillance planning', 'territoriality reinforcement planning', 'mechanical surveillance planning', 'access control planning' and 'neighborhood reinforcement planning'. Forth, regarding 'indoor space', crime-free elementary school environment can be build through 'natural surveillance planning' and 'territoriality reinforcement planning'. Finally, regarding 'outdoor space', the crime can be prevented through 'natural surveillance planning' and 'access control planning'.

• 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.

• Information Systems Review
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• v.21 no.3
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• pp.1-26
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• 2019

Now we are facing with a possibility of having crimes, which have been only possible offline, in cyber spaces as well.Especially, a recent growth in the use of SNS, promoted by popularization of smart phones, also has led an abrupt increase in cyber crime. It would be important to have a understanding of cyber crime and its characteristics by type as well as factors associated with each type of cyber crime in order to devise appropriate preventive measures against cyber crime. However, most of the previous studies on cyber crimesolely made through literature review or indirect approaches. Therefore, this study has been designed to conduct the interview with actual suspects(criminals) of cyber crime to address factors of cyber crime and to devise specific preventive measures and countermeasures against cyber crime. Especially, among various types of cyber crime, this study aims at addressing the 'trades' and 'financial transaction' of crimes committed using the information and communication network and the 'cyber libel/insult'of crimes committed using unlicensed contents, which have been soared recently and become significant issues. The findings of this study could be beneficial for the society since it has managed to conduct the interview and reveal relationships among major factors of cyber crime. The findings of this study could be used for devising and developing proper preventive and countermeasures against cyber crime, in turn reducing and preventing its damage.

• Journal of the Society of Disaster Information
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• v.11 no.4
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• pp.634-638
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• 2015

Four major social safety indexes including industrial accident, traffic accident, fire, and violent crime were selected, and transition of those values by time series data analysis since 2003 was presented. Comparing with the 2003 figure, the index of industrial accident was reduced by 27.8%, which was the most improved safety index. The indicators describing the traffic accident and violent crime rate were reduced by approximately 12%. However, the fire safety index showed an increase of 40% compared with the base year because national fire classification system was changed so that minor fire is also included in the counting since 2006.

• Journal of Multimedia Information System
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• v.7 no.3
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• pp.205-214
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• 2020

Crime has become one of the major problems in modern society. Even though visual surveillances through closed-circuit television (CCTV) is extensively used for solving crime, the number of crimes has not decreased. This is because there is insufficient workforce for performing 24-hour surveillance. In addition, CCTV surveillance by humans is not efficient for detecting dangerous situations owing to accuracy issues. In this paper, we propose the autonomous detection of dangerous situations in CCTV scenes using a deep learning model with relational inference. The main feature of the proposed method is that it can simultaneously perform object detection and relational inference to determine the danger of the situations captured by CCTV. This enables us to efficiently classify dangerous situations by inferring the relationship between detected objects (i.e., distance and position). Experimental results demonstrate that the proposed method outperforms existing methods in terms of the accuracy of image classification and the false alarm rate even when object detection accuracy is low.