• Convergence Security Journal
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• v.13 no.2
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• pp.15-24
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• 2013

In the 1960s, economic growth served to step up industrialization and urbanization, which was concurrent with th e urban concentration of population, and this phenomenon led to an increase in crime, and there was a rapid increase in demand for security at the same time. So the law enforcement authorities instituted the security service act in a move to secure quasi-police force. The enactment of the security service act has been put in force up to now, fueling the growth of security business. Mean while, the security industry has attained a splendid growth as one of growth industries, and it's required to look back on the past to determine new directions for the industry to make a new leap forward. Thus, the 1970s was a period to lay the groundwork for Korean private security, and the purpose of this study was to examine the social environments of the 1970s related to private security and what accelerated the development of private security.

• Information Systems Review
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• v.23 no.4
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• pp.87-102
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• 2021

Smart cities are attracting attention as a new economic growth engine based on new technologies and means to solve side effects of urbanization such as a surge in energy consumption, deepening environmental pollution, and an increase in crime rates. In particular, as demand for non-face-to-face services increases due to COVID-19, the role of smart cities that can provide various online and offline non-face-to-face services is becoming more important. Therefore, this study defined smart city non-face-to-face services based on literature research on the concept and underlying technology of smart city, and analyzed consumer utility for each service using Conjoint analysis. In particular, differences in user preferences between Sejong City and Busan City, which are currently designated as national smart city pilot cities in Korea, were compared and analyzed, and based on the derived results, measures to improve the competitiveness of smart city services were suggested.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.379-387
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• 2016

The goal of this research is to identify the planning techniques of high-rise housing estates applying a smart green city concept in order to understand the necessity of integrating 'planning & building' planning techniques and 'smart system' planning techniques and to analyze the current status of application. For the research, firstl, the definition of smart green city was established and high-rise housing estates planning was categorized according to a three space hierarchy, seven planning directions and 17 major features through literature review. Second, 28 'planning & building' planning techniques and 'smart system' planning techniques were derived through literature review and FGI analysis. Last, four cases in Multi-functional Administrative City were analyzed for the current status of application of planning techniques. In conclusion, planning techniques in 'Transportation Network', 'Environment-friendly layout planning of housing', 'Revitalization of green transportation', 'Utilization of new & renewable energy', 'Crime prevention and accident reduction', 'Use of high performance, and efficiency facility' main feature were identified as important planning techniques for Smart Green City and its implications were estimated.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.8
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• pp.927-938
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• 2014

A number of crime and disease relief situation show a clear increasing trend in domestic and overseas country. In particular, we desperately need a fast location information sharing with high accuracy for dealing with this situation efficiently. In this paper, we propose a DGPS framework and performance evaluation based on Web service enable increase location accuracy using low-cost GPS or AGPS. The framework consists of mobile station to realize the final service by receiving the correction values that are created in the base station closest to the current position from DGPS server, base station system to transmit the correct values to DPGS server by installing at base point and DGPS framework working at DGPS server. Our framework is fundamentally designed to respond based on XML to service request. In addition, for performance evaluation, we make use of 3 sites of Level 2 city base-station among the base stations being operated in Suncheon-si. Through performance evaluation, we show that our framework outperforms about 10%~15% in terms of error improvement rate, compared with the existing schemes. And we have the advantage that various services can be expanded owing to receiving the correction values through mobile device such as, smart phone, smart pad, net-book by using XML based Web services.

• Korean Security Journal
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• no.21
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• pp.121-134
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• 2009

The purpose of present study was to examine the effects of working time on fatigue and immune function in private security. The number of private guard on which this study has been conducted in 153, who work at large companies, medium or small companies and the like as located in Seoul and kyonggi. In this study blood T-lympocyte, Natural T-Killer cell and immunoglobulin(IgG, IgA and IgM) were measured to see the level of working hours. There was significant difference in Natural T-Killer cell and immunoglobulin(IgG, IgA and IgM) and fatigue between working hours(P<0.05). in view of the results of this study, it can be thought that fatigue and immune function is more affected by working hours In summary, these results are interpreted to mean that fatigue levels and immune function (Natural T-Killer cell, and immunoglobulin) decrease due to a rise in working hours.

• Journal of the Korean Institute of Landscape Architecture
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• v.45 no.6
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• pp.137-148
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• 2017

This study analyzed the opinions of residents for desirable urban regeneration and suggested an improvement plan for alley environments. This study conducted a questionnaire survey of the residents living in Alley Garden of Bisan 2,3-dong, Daegu Metropolitan City. In the analysis of the importance and satisfaction of Alley Garden components, items related to a safe, cleanly environment such as 'Lighting facility installation', 'Sewage and waste disposal' and 'CCTV installation' had a high level of importance. It was also found that items improved by the Residential Environment Improvement Project and Alley Garden such as 'Lighting facility installation', 'Quantity of herbaceous flowers' and 'Kinds of herbaceous flowers' had a high level of satisfaction. The IPA results showed that items such as 'Empty house maintenance', 'Rest facilities such as benches and pergolas', 'Space for resident interaction' and 'Public parking lot' had a high level of importance, but had a low level of satisfaction, which suggests that they should be improved by priority. As a result of factor analysis, Alley Garden components were classified into four factors: 'Safety and cleanliness', 'Greenness', 'Exchange and convenience facility' and 'Aesthetics renewal'. Based on this classification, a regression analysis was conducted regarding the effects of the four factors on overall satisfaction. Results showed that all four factors had a significant influence on the overall satisfaction and that 'Aesthetics renewal' and 'Safety and cleanliness', respectively showing levels of significance at 0.274 and 0.235, were highly influential to overall satisfaction. Therefore, it was concluded that spaces for resident interaction and rest facilities should be preferentially installed to improve the environment of alleys. For the improvement of the overall satisfaction of alley environments, it was also concluded that residents should be encouraged to engage in activities such as sculpture installation and mural drawing, along with the introduction of safety bells and crime prevention environment design and the implementation of alley beautification projects.

• 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.