• Korean Security Journal
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• no.26
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• pp.29-58
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• 2011

Since 11 September 2001, warnings of risk in the nexus of terrorism and nuclear weapons and materials which poses one of the gravest threats to the international community have continued. The purpose of this study is to analyze the aim, principles, characteristics, activities, impediments to progress and developmental recommendation of the Global Initiative to Combat Nuclear Terrorism(GICNT). In addition, it suggests implications of the GICNT for the ROK policy. International community will need a comprehensive strategy with four key elements to accomplish the GICNT: (1) securing and reducing nuclear stockpiles around the world, (2) countering terrorist nuclear plots, (3) preventing and deterring state transfers of nuclear weapons or materials to terrorists, (4) interdicting nuclear smuggling. Moreover, other steps should be taken to build the needed sense of urgency, including: (1) analysis and assessment through joint threat briefing for real nuclear threat possibility, (2) nuclear terrorism exercises, (3) fast-paced nuclear security reviews, (4) realistic testing of nuclear security performance to defeat insider or outsider threats, (5) preparing shared database of threats and incidents. As for the ROK, main concerns are transfer of North Korea's nuclear weapons, materials and technology to international terror groups and attacks on nuclear facilities and uses of nuclear devices. As the 5th nuclear country, the ROK has strengthened systems of physical protection and nuclear counterterrorism based on the international conventions. In order to comprehensive and effective prevention of nuclear terrorism, the ROK has to strengthen nuclear detection instruments and mobile radiation monitoring system in airports, ports, road networks, and national critical infrastructures. Furthermore, it has to draw up effective crisis management manual and prepare nuclear counterterrorism exercises and operational postures. The fundamental key to the prevention, detection and response to nuclear terrorism which leads to catastrophic impacts is to establish not only domestic law, institution and systems, but also strengthen international cooperation.

• Korean Security Journal
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• no.43
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• pp.205-230
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• 2015

This study aims to compare the differences of crucial factors that are associated with probation warning tickets between sex offenders and non-sex offenders in South Korea. Serious high-profile cases have occurred in recent years which resulted in public and political conners for successful sex offender management and monitoring strategy through community corrections. The official response has been to initiate a series of legislative probation and parole measures by using GPS electronic monitoring system, chemical castration, and sex offender registry and notification. In this context, the current study is designed to explore the major factors that could affect the failure of probation by comparing the differences between sex offenders and non-sex offenders in terms of their major factors which are related to the failure of probation. The failure of probation is measured by the number of warning tickets which would be issued when there is the violation of probation conditions. The data is obtained from Seoul Probation office from January, 29, 2014 to February, 28, 2014. The sample number of sex offenders is 144 and the number of non-sex offenders is 1,460. The data includes the information regarding the offenders who completed their probation order after they were assigned to Seoul Probation in 2013. Furthermore, this study uses the chi-square and logistic regression analysis by using SPSS statistical package program. The result demonstrated that only prior criminal history was statistically significant factor that was related to the number of warning tickets in the sex offender group when other variables were controlled($X^2=25.15$, p<0.05, Nagelkerke $R^2=0.23$)(b=0.19, SE=0.08, p<0.05). By contrast, there were various factors that were associated with the number of warning tickets in non-sex offender group. Specifically, the logistic regression analysis for the non-sex offenders showed that demographic variable(marital status and employment type), offender-victim relationships, alcohol addiction, violent behavior, prior criminal history, community service order, and attendance order were statistically significant factors that were associated with the odds of warning tickets. Further policy implication will be discussed.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.spc
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• pp.30-36
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• 2022

A sensor is needed to continuously and automatically measure the change in HNS concentration in industrial facilities that directly discharge to the sea after water treatment. The basic function of the sensor is to be able to detect ppb levels even at room temperature. Therefore, a method for increasing the sensitivity of the existing sensor is proposed. First, a method for increasing the conductivity of a film using a conductive carbon-based additive in a nanoparticle thin film and a method for increasing ion adsorption on the surface using a catalyst metal were studied.. To improve conductivity, carbon black was selected as an additive in the film using ITO nanoparticles, and the performance change of the sensor according to the content of the additive was observed. As a result, the change in resistance and response time due to the increase in conductivity at a CB content of 5 wt% could be observed, and notably, the lower limit of detection was lowered to about 250 ppb in an experiment with organic solvents. In addition, to increase the degree of ion adsorption in the liquid, an experiment was conducted using a sample in which a surface catalyst layer was formed by sputtering Au. Notably, the response of the sensor increased by more than 20% and the average lower limit of detection was lowered to 61 ppm. This result confirmed that the chemical resistance sensor using metal oxide nanoparticles could detect HNS of several tens of ppb even at room temperature.

• Journal of Korean Society of Disaster and Security
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• v.14 no.4
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• pp.69-80
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• 2021

This study tried to suggest improvement measures by discovering problems or matters requiring improvement among the annual regional safety evaluation systems. Briefly introducing the structure and contents of the study, which is the introduction, describes the regional safety evaluation method newly applied by the Ministry of Public Administration and Security in 2020. Utilization plans were also introduced according to the local safety level that was finally evaluated by the local government. In this paper, various views of previous researchers related to regional safety are summarized and described. In addition, problems were drawn in the composition of the index of local safety, the method of calculating the index, and the application of the current index. Next, the problems of specific regional safety evaluation indicators were analyzed and solutions were presented. First, "Number of semi-basement households" is replaced with "Number of households receiving basic livelihood" of 「Social Vulnerability Index」 in the field of disaster risk factors is replaced with "the number of households receiving basic livelihood". In addition, the "Vinyl House Area" is evaluated by replacing "the number of households living in a Vinyl House, the number of container households, and the number of households in Jjok-bang villages" with data. Second, in the management and evaluation of habitual drought disaster areas, local governments with a water supply rate of 95% or higher in Counties, Cities, and Districts are treated as "missing". This is because drought disasters rarely occur in the metropolitan area and local governments that have undergone urbanization. Third, the activities of safety sheriffs, safety monitor volunteers, and disaster safety silver monitoring groups along with the local autonomous prevention foundation are added to the evaluation of the evaluation index of 「Regional Autonomous Prevention Foundation Activation」 in the field of response to disaster prevention measures. However, since the name of the local autonomous disaster prevention organization may be different for each local government, if it is an autonomous disaster prevention organization organized and active for disaster prevention, it would be appropriate to evaluate the results by summing up all of its activities. Fourth, among the Scorecard evaluation items, which is a safe city evaluation tool used by the United Nations Office for Disaster Risk Reduction(UNDRR), the item "preservation of natural buffers to strengthen the protection functions provided by natural ecosystems" is borrowed, which is closely related to natural disasters. The Scorecard evaluation is an assessment index that focuses on improving the disaster resilience of local governments while carrying out the campaign "Creating cities resilient to climate crises and disasters" emphasized by UNDRR. Finally, the names of "regional safety level" and "local safety index" are similar, so the term of local safety level is changed to "natural disaster safety level" or "natural calamity safety level". This is because only the general public can distinguish the local safety level from the local safety index.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.77-85
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• 2024

In this dissertation, a we designed and implemented a patrol robot that integrates a thermal imaging camera, speed dome camera, PTZ camera, radar, lidar sensor, and smartphone. This robot has the ability to monitor and respond efficiently even in complex environments, and is especially designed to demonstrate high performance even at night or in low visibility conditions. An orbital movement system was selected for the robot's mobility, and a smartphone-based control system was developed for real-time data processing and decision-making. The combination of various sensors allows the robot to comprehensively perceive the environment and quickly detect hazards. Thermal imaging cameras are used for night surveillance, speed domes and PTZ cameras are used for wide-area monitoring, and radar and LIDAR are used for obstacle detection and avoidance. The smartphone-based control system provides a user-friendly interface. The proposed robot system can be used in various fields such as security, surveillance, and disaster response. Future research should include improving the robot's autonomous patrol algorithm, developing a multi-robot collaboration system, and long-term testing in a real environment. This study is expected to contribute to the development of the field of intelligent surveillance robots.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.