• KIPS Transactions on Software and Data Engineering
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• v.10 no.10
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• pp.391-398
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• 2021

Since the leased line is a structure that exclusively uses two connected areas for data transmission, a stable quality level and security are ensured, and despite the rapid increase in the number of switched lines, it is a line method that is continuously used a lot in companies. However, because the cost is relatively high, one of the important roles of the network operator in the enterprise is to maintain the optimal state by properly arranging and utilizing the resources of the network leased line. In other words, in order to properly support business service requirements, it is essential to properly manage bandwidth resources of leased lines from the viewpoint of data transmission, and properly predicting and managing leased line usage becomes a key factor. Therefore, in this study, various prediction models were applied and performance was evaluated based on the actual usage rate data of leased lines used in corporate networks. In general, the performance of each prediction was measured and compared by applying the smoothing model and ARIMA model, which are widely used as statistical methods, and the representative models of deep learning based on artificial neural networks, which are being studied a lot these days. In addition, based on the experimental results, we proposed the items to be considered in order for each model to achieve good performance for prediction from the viewpoint of effective operation of leased line resources.

• Journal of the Korea Convergence Society
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• v.12 no.5
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• pp.373-383
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• 2021

Our society is aging rapidly. In this super-aged society, the increase in healthcare costs are considered a national problem that undermines the sustainability of social security. Various services for healthcare for the elderly have been promoted to address this. However, most of them have focused on healthcare after the outbreak of chronic diseases and lack preventive healthcare. Most of the preventive healthcare projects are only pilots. In this paper, the current status of health care services for senior citizens at home and abroad was analyzed and based on this, the limitations and improvements were analyzed to propose the establishment of IoT-based Total Silver Care Center. IoT-based Total Silver Care Center may be conveniently monitored the health status of the elderly through various sensors, medical devices, and smart bands. And based on this, it can improve the quality of nursing services through time-saving and work efficiency of nursing providers. In addition, health care interventions may be provided in a timely manner if there is a change in the health status of users. And real-time imaging systems can help overcome mental difficulties.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.29-39
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• 2021

As damages to individuals, private sectors, and businesses increase due to newly occurring cyber attacks, the underlying network security problem has emerged as a major problem in computer systems. Therefore, NIDS using machine learning and deep learning is being studied to improve the limitations that occur in the existing Network Intrusion Detection System. In this study, a deep learning-based NIDS model study is conducted using the Convolution Neural Network (CNN) algorithm. For the image classification-based CNN algorithm learning, a discrete algorithm for continuity variables was added in the preprocessing stage used previously, and the predicted variables were expressed in a linear relationship and converted into easy-to-interpret data. Finally, the network packet processed through the above process is mapped to a square matrix structure and converted into a pixel image. For the performance evaluation of the proposed model, NSL-KDD, a representative network packet data, was used, and accuracy, precision, recall, and f1-score were used as performance indicators. As a result of the experiment, the proposed model showed the highest performance with an accuracy of 85%, and the harmonic mean (F1-Score) of the R2L class with a small number of training samples was 71%, showing very good performance compared to other models.

• Safety and Health at Work
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• v.12 no.4
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• pp.530-535
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• 2021

Background: Despite the lack of official COVID-19 statistics, various workplaces and occupations have been at the center of COVID-19 outbreaks. We aimed to compare legal measures and governance established for managing COVID-19 infection risks at workplaces in nine Asia and Pacific countries and to recommend key administrative measures. Methods: We collected information on legal measures and governance from both general citizens and workers regarding infection risks such as COVID-19 from industrial hygiene professionals in nine countries (Indonesia, India, Japan, Malaysia, New Zealand, Republic of the Philippines, Republic of Korea, Taiwan, and Thailand) using a structured questionnaire. Results: A governmental body overseeing public health and welfare was in charge of containing the spread and occurrence of infectious diseases under an infectious disease control and prevention act or another special act, although the name of the pertinent organizations and legislation vary among countries. Unlike in the case of other traditional hazards, there have been no specific articles or clauses describing the means of mitigating virus risk in the workplace that are legally required of employers, making it difficult to define the responsibilities of the employer. Each country maintains own legal systems regarding access to the duration, administration, and financing of paid sick leave. Many workers may not have access to paid sick leave even if it is legally guaranteed.

• 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.