• Journal of the Society of Disaster Information
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• v.19 no.3
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• pp.656-664
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• 2023

Purpose: The Ministry of Employment and Labor manages disasters based on the standard manual for risk management of large-scale human accidents in workplaces when large-scale disasters such as fires and collapses occur in workplaces. We are going to check the standard manual currently in operation and suggest improvement plans for the insufficient items. Method: Accordingly, the standard manual was checked together with internal and external experts in the disaster management manual and disaster management staff at headquarters and local government offices, and items to be improved were identified with priority. Result: In case of a collapse accident, it is necessary for the Ministry of Public Administration and Security to accurately present the selection criteria in order to eliminate the controversy over the selection of the disaster management department. In addition, it seems necessary to supplement the details of the disaster safety communication network operation and evacuation guidelines. Conclusion: In the future, in order to improve the disaster management system that meets the public's eye level, it is expected to prepare a standard manual for risk management of large-scale human accidents in workplaces that guarantees the lives and safety of workers through the collection of opinions from experts in the relevant field, disaster management personnel, and the general public.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.67-76
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• 2023

Although deep learning models are making innovative achievements in the field of computer vision, the problem of vulnerability to adversarial examples continues to be raised. Adversarial examples are attack methods that inject fine noise into images to induce misclassification, which can pose a serious threat to the application of deep learning models in the real world. In this paper, we propose a model that detects adversarial examples using differences in predictive values between edge-learned classification models and underlying classification models. The simple process of extracting the edges of the objects and reflecting them in learning can increase the robustness of the classification model, and economical and efficient detection is possible by detecting adversarial examples through differences in predictions between models. In our experiments, the general model showed accuracy of {49.9%, 29.84%, 18.46%, 4.95%, 3.36%} for adversarial examples (eps={0.02, 0.05, 0.1, 0.2, 0.3}), whereas the Canny edge model showed accuracy of {82.58%, 65.96%, 46.71%, 24.94%, 13.41%} and other edge models showed a similar level of accuracy also, indicating that the edge model was more robust against adversarial examples. In addition, adversarial example detection using differences in predictions between models revealed detection rates of {85.47%, 84.64%, 91.44%, 95.47%, and 87.61%} for each epsilon-specific adversarial example. It is expected that this study will contribute to improving the reliability of deep learning models in related research and application industries such as medical, autonomous driving, security, and national defense.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.175-181
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• 2024

The U.N. Security Council's North Korea Sanctions Committee estimated that the amount of North Korea's cyberattacks on virtual asset-related companies from 2017 to 2023 was about 4 trillion won. North Korea's cyberattacks have secured funds through cryptocurrency hacking as it has been restricted from securing foreign currency due to economic sanctions by the international community, and it also shows the form of technology theft against defense companies, and illegal assets are being used to maintain the Kim Jong-un regime and develop nuclear and missile development. When North Korea conducted its sixth nuclear test on September 3, 2017, and declared the completion of its national nuclear armament following the launch of an intercontinental ballistic missile on November 29 of the same year, the U.N. imposed sanctions on North Korea, which are considered the strongest economic sanctions in history. In these difficult economic situations, North Korea tried to overcome the crisis through cyberattacks, but as a result of analyzing the changes through the North's cyber attack cases, the strategic goal from the first period from 2009 to 2016 was to verify and show off North Korea's cyber capabilities through the neutralization of the national network and the takeover of information, and was seen as an intention to create social chaos in South Korea. When foreign currency earnings were limited due to sanctions against North Korea in 2016, the second stage seized virtual currency and secured funds to maintain the Kim Jong-un regime and advance nuclear and missile development. The third stage is a technology hacking of domestic and foreign defense companies, focusing on taking over key technologies to achieve the five strategic weapons tasks proposed by Chairman Kim Jong-un at the 8th Party Congress in 2021. At the national level, security measures for private companies as well as state agencies should be established against North Korea's cyberattacks, and measures for legal systems, technical problems, and budgets related to science are urgently needed. It is also necessary to establish a system and manpower to respond to the ever-developing cyberattacks by focusing on cultivating and securing professional manpower such as white hackers.

• Journal of Korean Society of Transportation
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• v.19 no.1
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• pp.101-114
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• 2001

Transportation enterprises should maintain constant and qualitative operation. Thus, in short period, transportation enterprises don't change supply in accordance with demand. In the result, transportation enterprises don't reduce operation in spite of management deficit at will. In freight transportation type, less-than-truckload(LTL) has more relation with above transportation feature than truckload(TL) does. Because freight transportation supply of TL is more flexible than that of LTL in correspondence of freight transportation demand. Relating to above mention, it appears that shortage of road and freight terminal of LTL is larger than that of TL. Especially in road and freight terminal comparison, shortage of freight terminal is larger than that of road. Shortage of road is the largest in 1990, and improved after-ward. But shortage of freight terminal is serious lately. So freight terminal needs more expansion than road, and shows better investment condition than road. Freight terminal expansion brings road expansion in LTL, on the contrary, freight terminal expansion substitutes freight terminal for road in TL. In transportation revenue, freight terminal's contribution to LTL is larger than that to TL. However, when we adjust quasi-fixed factor - road and freight terminal - to optimal level in the long run, in TL, diseconomies of scale becomes large, but in LTL, economies of scale becomes large. Consequently, it is necessary for TL to make counterplans to activate management of small size enterprises and owner drivers. And LTL should make use of economies of scale by solving the problem, such as nonprofit route, excess of rental freight handling of office, insufficiency of freight terminal, shortage of driver, and unpreparedness of freight insurance.

• The KIPS Transactions:PartC
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• v.10C no.5
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• pp.625-634
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• 2003

More than a decade after its initial proposal, deployment of IP Multicast has been limited due to the problem of traffic control in multicast routing, multicast address allocation in global internet, reliable multicast transport techniques etc. Lately, according to increase of multicast application service such as internet broadcast, real time security information service etc., overlay multicast is developed as a new internet multicast technology. In this paper, we describe an overlay multicast protocol and propose fast join mechanism that considers switching of the tree. To find a potential parent, an existing search algorithm descends the tree from the root by one level at a time, and it causes long joining latency. Also, it is try to select the nearest node as a potential parent. However, it can't select the nearest node by the degree limit of the node. As a result, the generated tree has low efficiency. To reduce long joining latency and improve the efficiency of the tree, we propose searching two levels of the tree at a time. This method forwards joining request message to own children node. So, at ordinary times, there is no overhead to keep the tree. But the joining request came, the increasing number of searching messages will reduce a long joining latency. Also searching more nodes will be helpful to construct more efficient trees. In order to evaluate the performance of our fast join mechanism, we measure the metrics such as the search latency and the number of searched node and the number of switching by the number of members and degree limit. The simulation results show that the performance of our mechanism is superior to that of the existing mechanism.