• Nuclear Engineering and Technology
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• v.53 no.7
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• pp.2195-2206
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• 2021

In order to mitigate the damage caused by accidents in nuclear power plants (NPPs), evacuation strategies are usually managed on the basis of off-site effects such as the diffusion of radioactive materials and evacuee traffic simulations. However, the interactive behavior between evacuees and the accident environment has a significant effect on the consequential gap. Agent-based modeling (ABM) is a method that can control and observe such interactions by establishing agents (i.e., the evacuees) and patches (i.e., the accident environments). In this paper, a radiological emergency evacuation model is constructed to realistically check the effectiveness of an evacuation strategy using NetLogo, an ABM toolbox. Geographic layers such as radiation sources, roads, buildings, and shelters were downloaded from an official geographic information system (GIS) of Korea, and were modified into respective patches. The dispersion model adopted from the puff equation was also modified to fit the patches on the geographic layer. The evacuees were defined as vehicle agents and a traffic model was implemented by combining the shortest path search (determined by an A ^* algorithm) and a traffic flow model incorporated in the Nagel-Schreckenberg cellular automata model. To evaluate the radiological harm to the evacuees due to the spread of radioactive materials, a simple exposure model was established to calculate the overlap fraction between the agents and the dispersion patches. This paper aims to demonstrate that the potential of ABM can handle disaster evacuation strategies more realistically than previous approaches.

• Journal of Korea Multimedia Society
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• v.24 no.7
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• pp.880-889
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• 2021

In everyday life, recognizing people's emotions from their frames is essential and is a popular research domain in the area of computer vision. Visual emotion has a severe class imbalance in which most of the data are distributed in specific categories. The existing methods do not consider class imbalance and used accuracy as the performance metric, which is not suitable for evaluating the performance of the imbalanced dataset. Therefore, we proposed a method for recognizing visual emotion using balanced data augmentation to address the class imbalance. The proposed method generates a balanced dataset by adopting the random over-sampling and image transformation methods. Also, the proposed method uses the Focal loss as a loss function, which can mitigate the class imbalance by down weighting the well-classified samples. EfficientNet, which is the state-of-the-art method for image classification is used to recognize visual emotion. We compare the performance of the proposed method with that of conventional methods by using a public dataset. The experimental results show that the proposed method increases the F1 score by 40% compared with the method without data augmentation, mitigating class imbalance without loss of classification accuracy.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.4
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• pp.821-834
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• 2019

As cyber security threats increase, there is a growing demand for highly reliable systems. Common Criteria, an international standard for evaluating information security products, requires formal specification and verification of the system to ensure a high level of security, and more and more cases are being observed. In this paper, we propose highly reliable drone systems that ensure high level security level and trust. Based on the results, we use formal methods especially Z/EVES to improve the system model in terms of scheduling in the system kernel.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3470-3493
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• 2019

IEEE 802.11s-based infrastructure Wireless Mesh Networks (iWMNs) are envisaged as a promising solution to provide ubiquitous wireless Internet access. The limited network capacity is a problem mainly caused by the medium contention between mesh users and the mesh access points (MAPs), which gets worst when the mesh clients employ the Transmission Control Protocol (TCP). To mitigate this problem, we use wireless network coding (WNC) in the MAPs. The aim of this proposal is to take advantage of the network topology around the MAPs, to alleviate the contention and maximize the use of the network capacity. We evaluate WNC when is used in MAPs. We model the formation of coding opportunities and, using computer simulations, we evaluate the formation of such coding opportunities. The results show that as the users density grows, the coding opportunities increase up to 70%; however, at the same time, the coding delay increments significantly. In order to reduce such delay, we propose to adaptively adjust the time that a packet can wait to catch a coding opportunity in an MAP. We assess the performance of moving-average estimation methods to forecast this adaptive sojourn time. We show that using moving-average estimation methods can significantly decrease the coding delay since they consider the traffic density conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2651-2673
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• 2019

In order to detect Denial of Service (DoS) attacks, victim-side detection methods are used popularly such as static threshold-based method and machine learning-based method. However, as DoS attacking methods become more sophisticated, these methods reveal some natural disadvantages such as the late detection and the difficulty of tracing back attackers. Recently, in order to mitigate these drawbacks, source-side DoS detection methods have been researched. But, the source-side DoS detection methods have limitations if the volume of attack traffic is relatively very small and it is blended into legitimate traffic. Especially, with the subtle attack traffic, DoS detection methods may suffer from high false positive, considering legitimate traffic as attack traffic. In this paper, we propose an effective source-side DoS detection method with traffic seasonality aware adaptive threshold. The threshold of detecting DoS attack is adjusted adaptively to the fluctuated legitimate traffic in order to detect subtle attack traffic. Moreover, by understanding the seasonality of legitimate traffic, the threshold can be updated more carefully even though subtle attack happens and it helps to achieve low false positive. The extensive evaluation with the real traffic logs presents that the proposed method achieves very high detection rate over 90% with low false positive rate down to 5%.

• Smart Structures and Systems
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• v.24 no.1
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• pp.67-81
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• 2019

Rows of closely adjacent buildings with similar dynamic characteristics are common building arrangements in residential areas. In this paper, we present a vibration control strategy for the seismic protection of this kind of multibuilding systems. The proposed approach uses an advanced Linear Matrix Inequality (LMI) computational procedure to carry out the integrated design of distributed multiactuation schemes that combine interbuilding linking devices with interstory actuators implemented at different levels of the buildings. The controller designs are formulated as static output-feedback H-infinity control problems that include the interstory drifts, interbuilding approachings and control efforts as controlled-output variables. The advantages of the LMI computational procedure are also exploited to design a fully-decentralized velocity-feedback controller, which can define a passive control system with high-performance characteristics. The main ideas are presented by means of a system of three adjacent five-story identical buildings, and a proper set of numerical simulations are conducted to demonstrate the behavior of the different control configurations. The obtained results indicate that interstory-interbuilding multiactuation schemes can be used to design effective vibration control systems for adjacent buildings with similar dynamic characteristics. Specifically, this kind of control systems is able to mitigate the vibrational response of the individual buildings while maintaining reduced levels of pounding risk.

• Journal of Arbitration Studies
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• v.29 no.1
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• pp.91-113
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• 2019

The fashion industry has been growing in Korea, but the law and the dispute resolution have been less than effective so far. Copyright and patent law have proven only minimally effective in fashion, ending up with designers and fashion companies relying on their trademarks to protect their design. Litigating trademark disputes in the fashion industry presents a host of problems and leads to resorting to the Alternative Dispute Resolution (ADR). ADR methods, especially arbitration, however, are emerging as substitutes to litigation. Using these methods, the fashion industry should sincerely consider a self-regulating program in which its members-both fashion designers and corporations alike-can resolve disputes in a manner mutually beneficial to all parties in order to preserve the industry's growth, solidarity, and esteem. From 2016, KCAB's Fashion Industry Dispute Advisory Committee (FIDAC) for ADR has promoted a better solution for disputes in the fashion industry. Therefore, stakeholders in the fashion industry should commit to procuring innovation in fashion on a long-term basis by establishing a panel handling an alternate dispute resolution process. The ADR process can mitigate the uncertainty created by relevant legislation or any other disputes, which could result in shying away from any business in the fashion industry.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.29 no.2
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• pp.226-235
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• 2019

Objectives: The purpose of this study was to investigate whether there were differences in manufacturing industry worker's health issues depending on job stress, fatigue, and health and safety services. Methods: The purpose of the questionnaire survey and its contents were explained to manufacturing industry health personnel, and the questionnaires were collected from 666 workers from 17 manufacturing workplaces. Questionnaires with missing data were excluded from the analysis so a total of 632 questionnaires were included. Results: Overall, 74.1% of the respondents had experienced health issues during the preceding month. The factors affecting worker health were number of workers(OR=1.000034, p=.013), job demand(OR=1.82, p=.009), MFS(OR=1.85, p=.003), provision of safety & health information(OR=1.85, p=.048), wearing protector(OR=2.58, p=.021). Conclusion: It is necessary to strengthen the safety and health education to mitigate hazardous and risk factors. Employers should provide health managers in charge of safety and health education to control workplace risk factors. In case of small businesses, it may be necessary to strengthen safety and health education in existing worker health centers and government support projects.

• Korean Journal of Occupational Health Nursing
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• v.28 no.2
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• pp.104-113
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• 2019

Purpose: This study aimed to investigate the factors affecting general hospital nurses' intention to stay in their jobs. Methods: A descriptive research design was used with a convenience sample of 286 nurses. Data were collected from March 15 to April 14, 2017using self-reported questionnaires and analyzed by descriptive statistics, t-test, analysis of variance, Pearson's correlation coefficient, and multiple regression analysis using the SPSS/WIN 21.0 program. Results: The mean scores for intention to stay, resilience, and emotional labor were 5.28 out of 8, 57.40 out of 100, and 3.23 out of 5, respectively. Intention to stay was positively correlated with overall career (r=.30), workplace (r=.18), shift work (r=-.20), position (r=.28), salary (r=.13), job satisfaction (r=.51), hospital satisfaction (r=.46), and resilience (r=.41). Factors influencing the intention to stay were job satisfaction and resilience, which explained 28% of the variance. Conclusion: Overall career, job satisfaction, and resilience are critical factors affecting general hospital nurses' intention to stay. Based on the findings of this study, efforts to improve nurses' job satisfaction and resilience should be implemented to mitigate the loss of this expert group among healthcare professionals.

• The Plant Pathology Journal
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• v.35 no.1
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• pp.1-10
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• 2019

Wheat blast occurred in Bangladesh for the first time in Asia in 2016. It is caused by a fungal pathogen, Magnaporthe oryzae Triticum (MoT) pathotype. In this review, we focused on the current status of the wheat blast in regard to host, pathogen, and environment. Despite the many efforts to control the disease, it expanded to neighboring regions including India, the world's second largest wheat producer. However, the disease occurrence has definitely decreased in quantity, because of many farmers chose to grow alternate crops according to the government's directions. Bangladesh government planned to introduce blast resistant cultivars but knowledges about genetics of resistance is limited. The genome analyses of the pathogen population revealed that the isolates caused wheat blast in Bangladesh are genetically close to a South American lineage of Magnaporthe oryzae. Understanding the genomes of virulent strains would be important to find target resistance genes for wheat breeding. Although the drier winter weather in Bangladesh was not favorable for development of wheat blast before, recent global warming and climate change are posing an increasing risk of disease development. Bangladesh outbreak in 2016 was likely to be facilitated by an extraordinary warm and humid weather in the affected districts before the harvest season. Coordinated international collaboration and steady financial supports are needed to mitigate the fearsome wheat blast in South Asia before it becomes a catastrophe.