• Tunnel and Underground Space
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• v.17 no.4
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• pp.322-331
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• 2007

Hundreds of rock slopes are constructed along the road, highway and railroad in mountainous Kangwon province and managed by each authorities concerned. It is practically not possible to carry out detailed rock slope investigation owing to the tremendous number of slopes and budgetary limit. Therefore, it is reasonable to perform a step-by-step investigation consisted of basic and detailed survey program and practical rock slope hazard assesment method for person in charge is strongly required. Through the development and application of KSMR (Korean Slope Mass Rating), it was found that KSMR could be practically used as an alternative of SMR though the number of inputs were reduced. In addition, the difference of hazard assessment between KSMR and experts decreased in case of considering the height of slope.

• Journal of Korean Society of Disaster and Security
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• v.15 no.3
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• pp.31-40
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• 2022

Domestic disaster risk maps are mainly produced and studied as a single disaster map by grid unit and disaster type. In particular, it is necessary to present an evaluation method of the disaster risk map that is more suitable for the relevant facility (local road) in order to utilize the work of practitioners who are mainly in charge of facility maintenance. In this study, an evaluation method was presented to evaluate the risk with a focus on local roads by using the landslide risk map and debris flow risk map provided by the Korea Forest Service. In addition, the risk was evaluated and verified for the provinces located in Gangwon-do. As a result of the evaluation, it was possible to evaluate the risk of grades 1 to 5 for 1,513 evaluation sections in the evaluation section with a total length of 234.59 km.

• Proceedings of the Korea Association of Information Systems Conference
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• 2002.11a
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• pp.348-364
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• 2002

본 연구는 기술개발상의 위험을 진단하면서, 상업화의 위험을 시장분석을 통하여 관찰하고 가격변동으로 인한 민감도를 고려하면서, 신기술 적용상의 장기적인 이익 및 수익의 예측정확도를 극대화하고 시장점유율을 예측할 수 있는 새로운 기법으로서 사례기반추론을 통한 신기술 사업성 평가시스템을 제시하고자 한다. 또한 본 연구가 새롭게 제시하는 기법과 새롭게 재무분석 분야에서 연구되고 있는 성장옵션 모형을 활용한 신기술 가격결정 시스템을 개발하고자 한다. 이 두 가지 시스템을 통하여 신기술의 마케팅적 관점, 재무걱 관점, 시스템적 관점을 모두 파악할 수 있으며 보다 객관적이고 과학적이며 예측 정확도가 높은 신기술의 화폐적 가치를 산출할 수 있게 될 것이다. 신기술의 사업성 평가에 관한 연구는 향후 한국기업의 국가경쟁력을 위해서 꼭 필요한 과업이며 신기술 기반의 중소기업을 효율적으로 지원하기 위해서도 꼭 이루어져야만 하는 중요 과업이 아닐 수 없다. 그러나 이러한 과업의 중요성에 비해서 그 동안 관련 연구는 거의 이루어지지 않았고(황규성, 2001) 다만 은행 등 금융권의 실무자들이 쉽게 적용할 수 있는 단순한 방법들이 제시되는 정도에 불과하였다. 이렇듯 관련 연구가 부족한 이유는 관련 분야가 재무관리, 회계학, 마케팅, 관련 기술분야 등 광범위하게 걸쳐져 있고 실무적인 성격이 강하여 학문적으로 일반화하기가 쉽지 않기 때문이다.

• Journal of the Society of Disaster Information
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• v.15 no.3
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• pp.440-449
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• 2019

Purpose: Fire-fighting organizations are the very first agencies that take actions at a disaster scene, and emergency rescue training is carried out for prompt and systematic response. However, there is a need for a change due to the limitations in emergency rescue trainings such as perfunctory trainings or trainings without considering regional or environmental characteristics. Method: This study is to conduct theoretical review with regard to emergency rescue training and present a measure to improve the emergency rescue training through attitude survey targeting fire-fighting organizations in Gangwon area. Result: Facilities that cause difficulties when doing emergency rescue activity were mostly hazardous material storage and processing facilities. In terms of the level of emergency rescue and response task, most respondents answered that the emergency rescue was insufficient. The respondents answered that the effectiveness of emergency rescue training was helpful, but some responses showed that the training was not helpful because of scenario-based training, seeming training, similar training carried out every year, unrealistic training, and lack of competent authorities' interest and perfunctory participations. Most respondents answered for the appropriateness of emergency rescue training and evaluation that they were satisfied, however, they were not satisfied with the evaluation methods irrelevant to the type of training, evaluation methods requiring unnecessary training scale, and evaluation methods leading perfunctory participations of competent authorities. Lastly, respondents mostly answered that training reflecting various damage situations are necessary regarding the demand on the improvement of emergency rescue training. Conclusion: The improvement measures for emergency rescue training are as follows. First, it is necessary to set and prepare various training contents in accordance with regional characteristics by reviewing major disasters occurred in the region. Second, it is necessary to revise the emergency rescue training guidelines and manuals for appropriate training plan for each fire station, provide education and training for working-level staff members, and establish training in a way that types, tactics, and strategies of emergency rescue training could be utilized practically. Third, it is necessary to prepare a scheme that can lead participation and provide incentive or penalty from the planning stage of training in order to increase the participation of supporting and competent authorities when an actual disaster occurs. Fourth, it is necessary to establish support arrangements and cooperative systems by authority through training by fire stations or zones in preparation for disaster situations that may occur simultaneously. Fifth, it is necessary to put emphasis on the training process rather than the result for emergency rescue training and evaluation, pay attention to the identification of supplement points for each disaster situation and make improvements. Especially, type or form of training should be considered rather than evaluating the execution status of detailed processes, and the evaluation measure that can consider the completeness (proficiency) of training and the status of role performance rather than the scale of training should be prepared. Sixth, type and method of training should be improved in accordance with the characteristics of each fire station by identifying the demand of working-level staff members for an efficient emergency rescue training.

• Journal of Korean Society of Disaster and Security
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• v.13 no.1
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• pp.59-75
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• 2020

This study is a case study that applied 'UNDRR's Urban Disaster Resilience Scorecard', an evaluation tool necessary for Incheon Metropolitan City to be certified as an international safe city. I would like to present an example that the results derived from this scorecard contributed to the Incheon Metropolitan City Disaster Reduction Plan. Of course, the Disaster Resilience Scorecard can't provide a way to improve the resilience of every disaster facing the city. However, it is to find the weakness of the resilience that the city faces, and to propose a solution to reduce the city's disaster risk. This is to help practitioners to recognize the disaster risks that Incheon Metropolitan City faces. In addition, the solution recommended by UNDRR was suggested to provide resilience in areas vulnerable to disasters. It was confirmed that this process can contribute to improving the disaster resilience of Incheon Metropolitan City. UNDRR has been spreading 'Climate Change, Disaster-resistant City Creation Campaign', aka MCR (Making Cities Resilient) Campaign, to cities all over the world since 2010 to reduce global cities' disasters. By applying the disaster relief guidelines adopted by UNDRR, governments, local governments, and neighboring cities are encouraged to collaborate. As a result of this study, Incheon Metropolitan city's UN Urban Resilience Scorecard was evaluated as a strong resilience field by obtaining scores of 4 or more (4.3~5.0) in 5 of 10 essentials; 1. Prepare organization for disaster resilience and prepare for implementation, 4. Strong resilience Urban development and design pursuit, 5. Preservation of natural cushions to enhance the protection provided by natural ecosystems, 9. Ensure effective disaster preparedness and response, 10. Rapid restoration and better reconstruction. On the other hand, in the other five fields, scores of less than 4 (3.20~3.85) were obtained and evaluated as weak resilience field; 2. Analyze, understand and utilize current and future risk scenarios, 3. Strengthen financial capacity for resilience, 6. Strengthen institutional capacity for resilience, 7. Understanding and strengthening social competence for resilience, 8. Strengthen resilience of infrastructure. In addition, through this study, the risk factors faced by Incheon Metropolitan City could be identified by priority, resilience improvement measures to minimize disaster risks, urban safety-based urban development plans, available disaster reduction resources, and integrated disasters. Measures were prepared.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.109-125
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• 2020

The Ministry of National Defense is pushing for the Defense Acquisition Program to build strong defense capabilities, and it spends more than 10 trillion won annually on defense improvement. As the Defense Acquisition Program is directly related to the security of the nation as well as the lives and property of the people, it must be carried out very transparently and efficiently by experts. However, the excessive diversification of laws and regulations related to the Defense Acquisition Program has made it challenging for many working-level officials to carry out the Defense Acquisition Program smoothly. It is even known that many people realize that there are related regulations that they were unaware of until they push ahead with their work. In addition, the statutory statements related to the Defense Acquisition Program have the tendency to cause serious issues even if only a single expression is wrong within the sentence. Despite this, efforts to establish a sentence comparison system to correct this issue in real time have been minimal. Therefore, this paper tries to propose a "Comparison System between the Statement of Military Reports and Related Laws" implementation plan that uses the Siamese Network-based artificial neural network, a model in the field of natural language processing (NLP), to observe the similarity between sentences that are likely to appear in the Defense Acquisition Program related documents and those from related statutory provisions to determine and classify the risk of illegality and to make users aware of the consequences. Various artificial neural network models (Bi-LSTM, Self-Attention, D_Bi-LSTM) were studied using 3,442 pairs of "Original Sentence"(described in actual statutes) and "Edited Sentence"(edited sentences derived from "Original Sentence"). Among many Defense Acquisition Program related statutes, DEFENSE ACQUISITION PROGRAM ACT, ENFORCEMENT RULE OF THE DEFENSE ACQUISITION PROGRAM ACT, and ENFORCEMENT DECREE OF THE DEFENSE ACQUISITION PROGRAM ACT were selected. Furthermore, "Original Sentence" has the 83 provisions that actually appear in the Act. "Original Sentence" has the main 83 clauses most accessible to working-level officials in their work. "Edited Sentence" is comprised of 30 to 50 similar sentences that are likely to appear modified in the county report for each clause("Original Sentence"). During the creation of the edited sentences, the original sentences were modified using 12 certain rules, and these sentences were produced in proportion to the number of such rules, as it was the case for the original sentences. After conducting 1 : 1 sentence similarity performance evaluation experiments, it was possible to classify each "Edited Sentence" as legal or illegal with considerable accuracy. In addition, the "Edited Sentence" dataset used to train the neural network models contains a variety of actual statutory statements("Original Sentence"), which are characterized by the 12 rules. On the other hand, the models are not able to effectively classify other sentences, which appear in actual military reports, when only the "Original Sentence" and "Edited Sentence" dataset have been fed to them. The dataset is not ample enough for the model to recognize other incoming new sentences. Hence, the performance of the model was reassessed by writing an additional 120 new sentences that have better resemblance to those in the actual military report and still have association with the original sentences. Thereafter, we were able to check that the models' performances surpassed a certain level even when they were trained merely with "Original Sentence" and "Edited Sentence" data. If sufficient model learning is achieved through the improvement and expansion of the full set of learning data with the addition of the actual report appearance sentences, the models will be able to better classify other sentences coming from military reports as legal or illegal. Based on the experimental results, this study confirms the possibility and value of building "Real-Time Automated Comparison System Between Military Documents and Related Laws". The research conducted in this experiment can verify which specific clause, of several that appear in related law clause is most similar to the sentence that appears in the Defense Acquisition Program-related military reports. This helps determine whether the contents in the military report sentences are at the risk of illegality when they are compared with those in the law clauses.