• Journal of the Society of Disaster Information
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• v.18 no.2
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• pp.269-279
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• 2022

Purpose: The purpose of this study is to develop a deep learning-based personal protective equipment detection model for disaster prevention at construction sites, and to apply it to actual construction sites and to analyze the results. Method: In the method of conducting this study, the dataset on the real environment was constructed and the developed personal protective equipment(PPE) detection model was applied. The PPE detection model mainly consists of worker detection and PPE classification model.The worker detection model uses a deep learning-based algorithm to build a dataset obtained from the actual field to learn and detect workers, and the PPE classification model applies the PPE detection algorithm learned from the worker detection area extracted from the work detection model. For verification of the proposed model, experimental results were derived from data obtained from three construction sites. Results: The application of the PPE recognition model to construction site brings up the problems related to mis-recognition and non-recognition. Conclusions: The analysis outcomes were produced to apply the object recognition technology to a construction site, and the need for follow-up research was suggested through representative cases of worker recognition and non-recognition, and mis-recognition of personal protective equipment.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.5
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• pp.617-626
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• 2022

In Korea, annual precipitation and its variability have gradually increased since modern meteorological observations began, and the risk of disasters has also been increasing due to significant regional variations and recent abnormal climate conditions. Given that damage from storms and floods mainly occurs around rivers, it is crucial to determine the appropriate design frequency for river-related projects. This study examined existing design practices used to determine hydrological design frequencies and suggested a new method to determine appropriate design frequencies. The study collected available data pertaining to seven evaluation factors, specifically the basin areas, shape parameters, channel slopes, stream orders, backwater effect reaches, extreme rainfall frequencies, and urbanized flood inundation areasfor 413 local rivers in Chungcheongnam-do in Korea. The estimated weights for areas of extreme rainfall frequencies and urbanized flood inundation were found to be 18, having a great effect on determining the design frequency. Compared with the established design frequency in previous government reports, the estimated design frequency increased for 255 rivers and decreased for 158 rivers.

• Journal of Korean Society of Disaster and Security
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• v.14 no.4
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• pp.9-15
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• 2021

The frequency of flash floods in mountainous areas is increasing due to the abnormal weather that occurs increasingly in the recent, and it causes human and material damages is increasing. Various plans for disaster mitigation have been established, but artificial plans such as raising embankment and dredging operation are inappropriate for valleys and rivers in national parks that prioritize nature protection. In this study, flood risk assessment was conducted for Gyeryongsan National Park in Korea using the WMS (Watershed Modeling System)which is rainfall runoff model for valleys and rivers in the catchment. As the result, it was simulated that it is flooding in three sub-catchments (Jusukgol, Sutonggol, Dinghaksa) of a total in Gyeryongsan National Park when rainfall over the 50 years return period occurs, and it was confirmed that the risk of trails and facilities what visitors are using was high. The risk of trails in national parks was quantitatively presented through the results of this study, and we intend to present the safe management guidelines of national parks in the future.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.318-329
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• 2022

Plant phenology including flowering, leaf unfolding, and leaf coloring in a forest is important to understand the forest ecosystem. Temperature rise due to recent climate change, however, can lead to plant phenology change as well as snowfall in winter season. Therefore, accurate monitoring of forest environment changes such as plant phenology and snow cover is essential to understand the climate change effect on forest management. These changes can monitor using a digital camera system. This paper introduces the detection methods for plant phenology and snow cover at the mountain region using an unmanned camera system that is a way to monitor the change of forest environment. In this study, the Automatic Mountain Meteorology Stations (AMOS) operated by Korea Forest Service (KFS) were selected as the testbed sites in order to systematize the plant phenology and snow cover detection in complex mountain areas. Multi-directional Internet Protocol (IP) camera system that is a kind of unmanned camera was installed at AMOS located in Seoul, Pyeongchang, Geochang, and Uljin. To detect the forest plant phenology and snow cover, the Red-Green-Blue (RGB) analysis based on the IP camera imagery was developed. The results produced by using image analysis captured from IP camera showed good performance in comparison with in-situ data. This result indicates that the utilization technique of IP camera system can capture the forest environment effectively and can be applied to various forest fields such as secure safety, forest ecosystem and disaster management, forestry, etc.

• Journal of Aerospace System Engineering
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• v.16 no.3
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• pp.105-114
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• 2022

The purpose of this study was to present a conceptual design of the 6U micro-satellite system for optical image of 3 m GSD. An optical camera system with a payload of 3 m GSD image was designed and optimized. The optical system has a diameter of Ø78 mm, length 250 mm, and 1400 mm focal length. The requirement and constraints were configured for the 6U micro-satellite bus system with the payload. Satisfying the requirement and constraints, the subsystems of the 6U bus were designed such as attitude and orbit control, propulsion, command and data handling, electrical power, communication, structures and mechanisms, and thermal control subsystem. The mass budget, power budget, and communication link budget were also confirmed for the 6U micro-satellite comprising the optical payload and the subsystems of bus. To take optical images, a mission operation concept is proposed for the 6U micro-satellite in a low-Earth orbit. A constellation comprising many 6U micro-satellites studied in this paper, can provide with various data for reconnaissance and disaster tracking.

• Journal of the Society of Disaster Information
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• v.19 no.1
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• pp.1-9
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• 2023

In order to carry out construction work, it is urgent to introduce a proper wage system so that the cost burden of projects that have been won due to bleeding competition among original government buildings based on low-priced bids can be transferred to subcontractors. Purpose: Construction with illegal multi-level industrial structure needs to improve the wage reduction environment leading to order (100%) → original contractor (80%) → subcontractor (65%) → load contractor (65%) and aims to ensure wages for end workers. Method: Investigate the current status of labor cost appropriate payment plan in the construction industry, and investigate the case of the appropriate wage system (P.W) in the United States. In addition, the effect and direction of the appropriate wage system are presented. Result: Individual minimum wage security was also mentioned in the Constitution, and many researchers suggested that only the introduction of an appropriate wage system could solve the problem of reducing worker labor and ensure quality and safety. Conclusion: The proper wage system in the construction industry will block illegal multi-level and illegal foreign work, improve the labor environment in the construction market, create an influx of young workers, and have a significant impact on the construction industry's competitive structure, safety, and quality.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.80-90
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• 2022

Currently, the domestic early warning system is issued differently for each disaster, and is operated independently by relevant organizations from central government to local governments. Representative domestic disaster warning systems include disaster broadcasting using CBS(Cell Broadcasting Service) and DMB(Digital Multimedia Broadcasting) Automatic Emergency Alert Service, DITS(Disaster Information Transform System) transmitted and displayed on TV screens, automatic response system, automated rainfall warning system, and disaster message board. However, due to the difference in the method of issuing each emergency alert at the site of an emergency disaster, the alerts are issued at different times for each media, and the delivered content is also not integrated. If these systems are integrated, it is expected that damage to people's property and lives will be minimized by sharing and integrated management of disaster information such as voice, video, and data to comprehensively judge and make decisions about disaster situations. Therefore, in this study, we present a plan for the integration of the disaster warning system along with the analysis of the operation status of the domestic early warning system.

• The Journal of Engineering Geology
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• v.33 no.2
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• pp.307-322
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• 2023

Rock-mass grouting plays a crucial role in the construction of dams and deep caverns, effectively preventing seepage in the foundations, enhancing stability, and mitigating hazards. Most rock grouting is affected by hydrogeological and rock engineering indices such as rock quality designation (RQD), rock mass quality (Q-value), geological strength index (GSI), joint spacing (Js), joint aperture (Ap), lugeon value (Lu), secondary permeability index (SPI), and coefficient of permeability (K). Therefore, accurate geological analysis of basic rock properties and guidelines for grouting construction are essential for ensuring safe and effective grouting design and construction. Such analysis has been applied in dam construction sites, with a particular focus on the geological characteristics of bedrock and the development of prediction methods for grout take. In South Korea, many studies have focused on grout injection materials and construction management techniques. However, there is a notable lack of research on the analysis of hydrogeological and rock engineering information for rock masses, which are essential for the development of appropriate rock grouting plans. This paper reviews the current state of research into the correlation between the grout take with important hydrogeological and rock engineering indices. Based on these findings, future directions for the development of rock grouting research in South Korea are discussed.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.261-261
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• 2020

물관리의 기본이 되는 연속적인 유량 자료 확보를 위해서는 정확도 높은 수위-유량 관계 곡선식 개발이 필수적이다. 수위-유량 관계곡선식은 모든 수문시설 설계의 기초가 되며 홍수, 가뭄 등 물재해 대응을 위해서도 중요한 의미를 가지고 있다. 그러나 일반적으로 유량 측정은 많은 비용과 시간이 들고, 식생성장, 단면변화 등의 통제특성(control)이 변함에 따라 구간분리, 기간분리와 같은 비선형적인 양상이 나타나 자료 해석에 어려움이 존재한다. 특히, 국내 하천의 경우 자연적 및 인위적인 환경 변화가 다양하여 지점 및 기간에 따라 세밀한 분석이 요구된다. 머신러닝(Machine Learning)이란 데이터를 통해 컴퓨터가 스스로 학습하여 모델을 구축하고 성능을 향상시키는 일련의 과정을 뜻한다. 기존의 수위-유량 관계곡선식은 개발자의 판단에 의해 데이터의 종류와 기간 등을 설정하여 회귀식의 파라미터를 산출한다면, 머신러닝은 유효한 전체 데이터를 이용해 스스로 학습하여 자료 간 상관성을 찾아내 모델을 구축하고 성능을 지속적으로 향상 시킬 수 있다. 머신러닝은 충분한 수문자료가 확보되었다는 전제 하에 복잡하고 가변적인 수자원 환경을 반영하여 유량 추정의 정확도를 지속적으로 향상시킬 수 있다는 이점을 가지고 있다. 본 연구는 머신러닝의 대표적인 알고리즘들을 활용하여 유량을 추정하는 모델을 구축하고 성능을 비교·분석하였다. 대상지역은 안정적인 수량을 확보하고 있는 한강수계의 거운교 지점이며, 사용자료는 2010~2018년의 시간, 수위, 유량, 수면폭 등 이다. 프로그램은 파이썬을 기반으로 한 머신러닝 라이브러리인 사이킷런(sklearn)을 사용하였고 알고리즘은 랜덤포레스트 회귀, 의사결정트리, KNN(K-Nearest Neighbor), rgboost을 적용하였다. 학습(train) 데이터는 입력자료 종류별로 조합하여 6개의 세트로 구분하여 모델을 구축하였고, 이를 적용해 검증(test) 데이터를 RMSE(Roog Mean Square Error)로 평가하였다. 그 결과 모델 및 입력 자료의 조합에 따라 3.67~171.46로 다소 넓은 범위의 값이 도출되었다. 그 중 가장 우수한 유형은 수위, 연도, 수면폭 3개의 입력자료를 조합하여 랜덤포레스트 회귀 모델에 적용한 경우이다. 비교를 위해 동일한 검증 데이터를 한국수문조사연보(2018년) 내거운교 지점의 수위별 수위-유량 곡선식을 이용해 유량을 추정한 결과 RMSE가 3.76이 산출되어, 머신러닝이 세분화된 수위-유량 곡선식과 비슷한 수준까지 성능을 내는 것으로 확인되었다. 본 연구는 양질의 유량자료 생산을 위해 기 구축된 수문자료를 기반으로 머신러닝 기법의 적용 가능성을 검토한 기초 연구로써, 국내 효율적인 수문자료 측정 및 수위-유량 곡선 산출에 도움이 될 수 있을 것으로 판단된다. 향후 수자원 환경 및 통제특성에 영향을 미치는 다양한 영향변수를 파악하기 위해 기상자료, 취수량 등의 입력 자료를 적용할 필요가 있으며, 머신러닝 내 비지도학습인 딥러닝과 같은 보다 정교한 모델에 대한 추가적인 연구도 수행되어야 할 것이다.

• Journal of the Korea Safety Management & Science
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• v.25 no.2
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• pp.71-83
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• 2023

Since last year, the government has enforced the 'Act on the Punishment of Severe Accidents, Etc.' (hereafter referred to as the 'Serious Accident Punishment Act'), which punishes business owners and business managers who fail to fulfill their duty of safety measures with 'imprisonment of one year or more' and the Occupational Safety and Health Act. Based on this, various occupational safety and health policies were developed, including the operation of a system related to entrusting the work of safety managers. Despite these efforts, the effect of implementing the Severe Accident Punishment Act is a groundbreaking change in the current disaster prevention policy, which has increased by 0.02%P and 0.03‱P, respectively, from the previous year to 0.65% of the total accident rate and 1.10‱ of the death rate per 10,000 people as of 2022. As the need emerged, attention was paid to 'collaboration and governance with safety management institutions' in the 'Severe Disaster Reduction Roadmap' announced by the Ministry of Employment and Labor in November 2022. In this study, a meaningful result was derived by comparing and analyzing the industrial accident status of workplaces entrusted by "A" safety management institutions with the national average based on the industrial accident survey table, and the types of industrial accidents that occurred in consigned workplaces were selected as intensive management targets. The policy direction for industrial accident prevention was established. It is necessary to develop safety management work manuals based on the results of this study, expertise, discover best cases of risk assessment and develop guides, and educate and train consigned workers. In addition, it suggests that the government's guidance and supervision are needed to advance the professionalism of safety management entrusted tasks, and that safety management institutions should strengthen their roles and functions for preventing and reducing industrial accidents. However, due to difficulties in disclosing information of specialized safety management institutions, the limitation of the provision, collection, and viewing of research-related data to "A" specialized safety management institutions remains a limitation of the research. It seems likely that more thorough research will be conducted.