• 한국사회정책
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• v.25 no.3
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• pp.279-303
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• 2018

Since the introduction of the Riester Pension Scheme, the controversy has continued in the policy studies and the political debates. This study evaluates the achievements and limitations of the German Riester pension scheme and tries to derive policy implications for South Korea. As a result of the analysis, the most worthwhile achievement of the Riester Pension is to strengthen the role of the private pension schemes. Unlike other private pension schemes, it included a large part of lower income households. It also opened a new perspective of utilizing private pension schemes to accomplish the goals of the family policy. Despite these attainments, it does not reach the promised coverage rate. It also was revealed that the higher income households have concluded more Riester Pension Contracts than the targeted lower-income households. Due to high administration fee and incomplete information problems, benefit levels are supposed to be much lower than expected. It concludes, above all, despite some achievements, the Riester Pension Scheme will not fill completely the gap of old age income security caused by the reduction of the public pension system. The German case provides fruitful lessons for Korea. The introduction of a subsidized personal pension scheme in South Korea can be realized only when some prerequisites would be satisfied such as the consolidation and maturing of public pension schemes and the strengthening of the transparency in the private pension market.

• Korean Journal of Child Education & Care
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• v.18 no.4
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• pp.227-245
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• 2018

Objective: In this study, educational activities were organized to emphasize the importance of natural disaster safety education by reflecting the recent rapid increases in natural disasters. The study focused on story-sharing, art, and game activities to effectively conduct natural disaster safety education for four-year-old children, and in doing so, aimed to improve the children's safety problem-solving abilities and eco-friendly attitude. Methods: Based on the types of natural disasters that are handled by the Ministry of Public Administration and Security and the Chungcheongbuk-do Office of Education, earthquakes, yellow dust, heat waves, floods, typhoons, bolts of lighting, fires, snowstorms, and global warming were included as the study's educational contents, and a total 20 sessions of natural disaster safety education activities were planned. For the subjects, 20 four-year-old children at K Kindergarten attached to a school were selected as an experimental group and 20 four-year-old children at N Kindergarten attached to a school were selected as a control group. Both kindergartens were located in C City, Chungcheongbuk-do. The experimental group was instructed to perform the study's education activities, whereas the control group only carried out general activities based on the Nuri Curriculum's subjects of daily life. Results: As a result, the children in the experimental group, who received the natural disaster safety education, improved their safety problem-solving abilities and eco-friendly attitude when compared to those in the control group. This outcome proved that the natural disaster safety education conducted by the present study offers educational activities that can positively affect improvements in children's safety problem-solving abilities and eco-friendly attitude. Conclusion/Implications: Therefore, the present study is likely to provide concrete information to teachers who plan to conduct natural disaster safety education in the actual early childhood education field.

• 재활복지
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• v.21 no.3
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• pp.129-146
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• 2017

In an event of an emergency, such as fire in a building, visually impaired and blind people are prone to exposed to a level of danger that is greater than that of normal people, for they cannot be aware of it quickly. Current fire detection methods such as smoke detector is very slow and unreliable because it usually uses chemical sensor based technology to detect fire particles. But by using vision sensor instead, fire can be proven to be detected much faster as we show in our experiments. Previous studies have applied various image processing and machine learning techniques to detect fire, but they usually don't work very well because these techniques require hand-crafted features that do not generalize well to various scenarios. But with the help of recent advancement in the field of deep learning, this research can be conducted to help solve this problem by using deep learning-based object detector that can detect fire using images from security camera. Deep learning based approach can learn features automatically so they can usually generalize well to various scenes. In order to ensure maximum capacity, we applied the latest technologies in the field of computer vision such as YOLO detector in order to solve this task. Considering the trade-off between recall vs. complexity, we introduced two convolutional neural networks with slightly different model's complexity to detect fire at different recall rate. Both models can detect fire at 99% average precision, but one model has 76% recall at 30 FPS while another has 61% recall at 50 FPS. We also compare our model memory consumption with each other and show our models robustness by testing on various real-world scenarios.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.99-109
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• 2018

Tampering involves illegally removing technologies from a protected system through reverse engineering or developing a system without proper authorization. As tampering of a weapon system is a threat to national security, anti-tampering measures are required. Precedent studies on anti-tampering have discussed the necessity, related trends, application cases, and recent cybersecurity-based or other protection methods. In a domestic situation, the Defense Technology Protection Act focuses on how to prevent technology leakage occurring in related organizations through personnel, facilities and information systems. Anti-tampering design needs to determine which technologies are protected while considering the effects of development cost and schedule. The objective of our study is to develop methods of how to select target technologies and determine counter-measures to protect these technologies. Specifically, an evaluation matrix was derived based on the risk analysis concept to select the protection of target technologies. Also, based on the concept of risk mitigation, the classification of anti-tampering techniques was performed according to its applicability and determination of application levels. Results of the case study revealed that the methods proposed can be systematically applied for anti-tampering in weapon system development.

• Journal of the Korean society of biological therapies in psychiatry
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• v.24 no.3
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• pp.184-193
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• 2018

Objectives : This study investigated the effects of social support and chronic medical conditions on depressive symptoms in elderly people living alone in a rural community. Methods : Sociodemographic information on 173 subjects aged 65 years or older who lived alone in a rural community and were recipients of National Basic Livelihood Security was collected and analyzed. All participants completed the Korean Form of the Geriatric Depression Scale and the Lubben Social Network Scale. Additionally, the current prevalence of chronic medical conditions that interfere with the activities of daily living was examined. Multiple logistic regression analysis was conducted to analyze the associations of social support and chronic medical conditions with depressive symptoms. Results : Social support(odds ratio: OR, 0.96; 95% confidence interval: 95% CI, 0.92-0.99) and chronic medical conditions(OR, 1.59; 95% CI, 1.23-2.05) were significantly associated with depressive symptoms in all subjects. When analyzed by gender, social support served as a protective factor against depressive symptoms in elderly men only(OR, 0.91; 95% CI, 0.83-0.99), and chronic medical conditions increased the risk of depressive symptoms in elderly women only(OR, 1.74; 95% CI, 1.26-2.40). Furthermore, osteoarthritis and lumbar pain were risk factors for depressive symptoms in all subjects(OR, 2.24; 95% CI, 1.10-4.56 and OR, 2.10; 95% CI, 1.08-4.12) and in elderly women(OR, 4.07; 95% CI, 1.68-9.84 and OR, 3.34; 95% CI, 1.47-7.57), respectively. Conclusion : This study indicates that improving the social support and managing the chronic medical conditions of elderly people living alone are important for the prevention of depression in this population. Additionally, the present results suggest that it is necessary to establish different depression-prevention strategies for elderly men and women living alone.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.3
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• pp.177-188
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• 2019

Recently, citizens are feeling anxious as 'Motiveless Crime' increases. The quality of citizens life is degraded and the degree of crime fear is increasing. In this study, based on various variables related to crime other than actual crime occurrence status, crime occurrence points (point line polygon) felt by citizens are created by using mental map methodology. And the purpose of this study is to derive the area of concern for crime through spatial overlap analysis using kernel density estimation analysis. It also uses spatial overlay analysis using kernel density estimation to derive areas of concern for crime occurrence. As a result, the local residents' request point and the areas of concern for crime were overlapped. In addition, the mental map indicating the fear of crime was constructed by mapping mainly the areas between the facilities, the non-construction area such as the narrow area, the security CCTV, the streetlight. This study is meaningful in that it tried to derive a crime occurrence concern area by using mental map method unlike the previous study related to crime. The results of this study, such as mental map, could be used in various fields such as construction of fragile crime map, guideline of crime prevention through environment design.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.1-12
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• 2021

With the recent 4th Industrial Revolution, the growth and value of big data are continuously increasing, and the government is also actively making efforts to open and utilize public data. However, the situation still does not reach the level of demand for public data use by citizens, At this point, it is necessary to identify research trends in the public data field and seek directions for development. In this study, in order to understand the research trends related to public data, the analysis was performed using topic modeling, which is mainly used in text mining techniques. To this end, we collected papers containing keywords of 'Public data' among domestic and foreign research papers (1,437 domestically, 9,607 overseas) and performed topic modeling based on the LDA algorithm, and compared domestic and foreign public data research trends. After analysis, policy implications were presented. Looking at the time series by topic, research in the fields of 'personal information protection', 'public data management', and 'urban environment' has increased in Korea. Overseas, it was confirmed that research in the fields of 'urban policy', 'cell biology', 'deep learning', and 'cloud·security' is active.

• Journal of Korean Academy of Dental Administration
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• v.7 no.1
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• pp.39-43
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• 2019

Smartphone usage has become so common that it has reached 2 billion people in the last year. As a result of this, hospitals have started making use of smartphones at various medical sites and research services for patients. This study aimed to establish support for developing a long distance program for patients with implants who have difficulty visiting clinics or with busy modern lives, by using smartphones for oral hygiene management instruction. The data were collected for 12 weeks, from July 24 to October 21, 2015, for patients who agreed to participate in the study. Although the subjects found the process of transferring photos via smartphone to be cumbersome (75%), the satisfaction level of the oral hygiene management program was excellent for all participating patients, and they all wanted to continue with further management using this process. The results from the phone satisfaction survey showed that oral hygiene self-management after oral hygiene control training by smartphones was mostly equal to previous habits (87.5%) or had partially increased but had not decreased. The need for data on more varied age groups and the issues of protecting the security of personal information on smartphones require further study. However, our study confirmed the efficacy of using electronic media (smartphones) for oral hygiene management in patients with a dental implant due to their improvement of oral hygiene performance as evidenced by less bleeding from probing on post-program visit.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.4
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• pp.117-122
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• 2021

In recent years, human damage and loss of money due to various disasters such as typhoons, earthquakes, forest fires, landslides, and wars are steadily occurring, and a lot of manpower and funds are required to prevent and recover them. In this paper, we designed and developed a disaster drone system based on artificial intelligence in order to monitor these various disaster situations in advance and to quickly recognize and respond to disaster occurrence. In this study, multiple disaster drones are used in areas where it is difficult for humans to monitor, and each drone performs an efficient search with an optimal path by applying a deep learning-based optimal path algorithm. In addition, in order to solve the problem of insufficient battery capacity, which is a fundamental problem of drones, the optimal route of each drone is determined using Ant Colony Optimization (ACO) technology. In order to implement the proposed system, it was applied to a forest fire situation among various disaster situations, and a forest fire map was created based on the transmitted data, and a forest fire map was visually shown to the fire fighters dispatched by a drone equipped with a beam projector. In the proposed system, multiple drones can detect a disaster situation in a short time by simultaneously performing optimal path search and object recognition. Based on this research, it can be used to build disaster drone infrastructure, search for victims (sea, mountain, jungle), self-extinguishing fire using drones, and security drones.

• Journal of Convergence for Information Technology
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• v.12 no.1
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• pp.76-82
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• 2022

Recently, natural and social disasters in Korea are increasing, and new disasters such as COVID 19 and sinkholes, and large-scale disasters that combine natural and social disasters are occurring frequently. In order to reduce damage caused by disasters and effectively respond to disasters, the importance of disaster safety education is emerging because it is necessary to understand the awareness of disaster situations and the functional response process. Ministry of Public Interior and Security is providing disaster safety education for emergency managers through 54 specialized disaster safety education institutions. There is also a lack of experience facilities. This has a problem in that it makes it difficult for disaster safety personnel to effectively respond to disasters due to lack of experience in actual disaster sites. Also, unlike other education fields, the connection between disaster safety education contents and new technologies such as AI is still lacking. In this study, focusing on natural disaster, the current status and problems of domestic disaster safety education institutions and their contents are investigated and analyzed, and based on this, this study suggested improvement plans for domestic disaster safety education contents such as establishment of a unified disaster safety standard curriculum, production and distribution of disaster safety education experience contents using virtual reality technology and infotainment technology, and development of mobile AI tutoring service.