• Proceedings of the Korea Water Resources Association Conference
• /
• 2017.05a
• /
• pp.55-55
• /
• 2017

가뭄은 국민생활 및 경제 등에 막대한 손실을 초래하며, 지역사회 공동체나 사회기능에 심각한 영향을 끼칠 수 있는 재해이다. 가뭄피해 최소화를 위해서는 단기대응, 복구지원 등의 사후대책에서 사전대비 및 예방으로의 정책 전환이 필요하며, 이러한 정책 수립을 뒷받침하기 위해서는 가뭄에 따른 정량적인 피해영향 평가가 우선적으로 필요하다. 하지만 가뭄 피해의 범위 및 형태는 워낙 광범위하기 때문에, 피해추정을 위한 잣대라 할 수 있는 영향평가 기법조차 제대로 정립되지 못하고 있는 실정이다. 국내에서는 분야별(기상, 농업, 수문)로 지수화 된 지표를 이용한 가뭄 평가가 주로 수행되고 있으며, 경제적 영향평가는 방법론에 대한 시범 연구 수준이다. 가뭄기록조사 등 과거 가뭄피해 자료에서도 피해액의 금액환산이 되지 않은 사례가 대부분이며 급수차지원, 관정개발 등 사후복구비 위주의 일부 자료만이 피해금액으로 제시되어 있을 뿐이다. 댐, 저수지 등에 의한 용수공급 안정성으로 인해, 기상학적인 가뭄이 즉시 물부족으로 인한 피해로 이어지지는 않지만, 물부족이 발생하거나 부족량이 예측되는 상황에서 피해규모를 시스템적으로 추정 및 비교할 수 있는 기법 개발의 필요성에 의해 잠재피해액 개념의 공급지장비용 추정기법을 개발하였다. 공급지장비용 또는 편익 도출을 위한 이론적 배경으로, 경제적 가치 또는 파급효과를 분석하기 위한 방법은 경제학적 접근법과 비경제학적 접근법으로 구분된다. 경제학적 접근법에서 사용하는 진술선호 기법의 경우 전국을 대상으로 설문 등의 과정을 거쳐 지불의사액을 도출하는 과정이 필요하기 때문에 많은 조사비용이 소요된다. 비경제학적 또는 공학적 접근법으로 분류되는 대체비용법은 이론적 배경이 약하고 대체항목의 선택에 주의가 필요하다는 단점이 있으나, 물가자료, 산업통계, 수자원통계 등 기초자료의 주기적 업데이트가 유리하며, 정신적 피해를 제외할 경우 피해비용 추정결과의 편차가 진술선호기법 보다는 작은 장점이 있다. 본 연구에서는 피해비용의 과대추정에 유의하여 대체비용법에 기반한 일본 후생노동성의 감 단수피해추정기법을 우리나라 자료에 맞게 수정하여 공급지장비용을 추정하였으며, 경제학적 접근법에 의한 용수의 한계가치비용 등과 비교를 통해 적용성을 검토하였다.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.24 no.6
• /
• pp.583-598
• /
• 2022

As human-based tunnel inspections are affected by the subjective judgment of the inspector, making continuous history management difficult. There is a lot of deep learning-based automatic crack detection research recently. However, the large public crack datasets used in most studies differ significantly from those in tunnels. Also, additional work is required to build sophisticated crack labels in current tunnel evaluation. Therefore, we present a method to improve crack detection performance by inputting existing datasets into a deep learning model. We evaluate and compare the performance of deep learning models trained by combining existing tunnel datasets, high-quality tunnel datasets, and public crack datasets. As a result, DeepLabv3+ with Cross-Entropy loss function performed best when trained on both public datasets, patchwise classification, and oversampled tunnel datasets. In the future, we expect to contribute to establishing a plan to efficiently utilize the tunnel image acquisition system's data for deep learning model learning.

• Korean Journal of Remote Sensing
• /
• v.37 no.6_3
• /
• pp.2027-2034
• /
• 2021

Using multi-temporal KOMPSAT-3/3A high-resolution satellite images, the Normalized Difference Vegetation Index (NDVI) for the area around the Fukushima daiichi nuclear power plant was determined, and the pattern of vegetation changes was analyzed. To calculate the NDVI, surface reflectance from the KOMPSAT-3/3A satellite image was used. Satellite images from four years were used, and the zones where the images overlap was designated as the area of interest (AOI) for the study, and by setting a profile passing through highly vegetated area as a data analysis method, the changes by year were examined. In addition, random points were extracted within the AOI and displayed as a box plot to quantitatively indicate change of NDVI distribution pattern. The main results of this study showed that the NDVI in 2014 was low within AOI in the vicinity of the nuclear power plant, but vegetated area continued to expand until 2021. These results were also confirmed in the change monitoring results shown in a profile or box plot. In disaster areas where access is restricted, such as the Fukushima nuclear power plant area, where it is difficult to collect field data, obtaining land cover classification products with high accuracy using satellite images is challenging, so it is appropriate to analyze them using primary outputs such as vegetation indices obtained from high-resolution satellite imagery. It is necessary to establish an international cooperation system for jointly utilizing satellite images. Meanwhile, to periodically monitor environmental changes in neighboring countries that may affect the Korean peninsula, it is necessary to establish utilization models and systems using high-resolution satellite images.

• Journal of Practical Engineering Education
• /
• v.13 no.2
• /
• pp.333-349
• /
• 2021

The fourth industrial revolution based on information and communication technology has increased the need for an environment where contents in new technologies can be learned for the development of lifelong vocational capabilities. To prepare for this, K University's online lifelong education center has established STEP, a smart learning platform. In this study, we conducted a study and other platform case analysis for STEP learner types, a survey of learners, and a comprehensive analysis based on these results to classify characteristics by learner types. It also intended to establish a plan to provide customized services to meet the needs of STEP learners in the future. The derived results are as follows. It is necessary to constantly manage learning content difficulty and learning motivation survey, and also needs to refine the operation of learning content in terms of learning composition. In addition, it is important to secure specialized content, to manage vulnerable learners, to actively introduce a learner support system and various educational methods.

• Convergence Security Journal
• /
• v.21 no.2
• /
• pp.11-18
• /
• 2021

To protect tangible and intangible assets, most of the companies are conducting information protection monitoring by using various security equipment in the IT service network. As the security equipment that needs to be protected increases in the process of upgrading and expanding the service network, it is difficult to monitor the possible exposure to the attack for the entire service network. As a countermeasure to this, various studies have been conducted to detect external attacks and illegal communication of equipment, but studies on effective monitoring of the open service ports and construction of illegal communication monitoring system for large-scale service networks are insufficient. In this study, we propose a framework that can monitor information leakage and illegal communication attempts in a wide range of service networks without large-scale investment by analyzing 'Netflow statistical information' of backbone network equipment, which is the gateway to the entire data flow of the IT service network. By using machine learning algorithms to the Netfllow data, we could obtain the high classification accuracy of 94% in identifying whether the Telnet service port of operating equipment is open or not, and we could track the illegal communication of the damaged equipment by using the illegal communication history of the damaged equipment.

• Korean Journal of Environment and Ecology
• /
• v.35 no.2
• /
• pp.204-219
• /
• 2021

This study was conducted to investigate and analyze the characteristics of the plant community structure of vegetation distributed on the western slope and ridge connecting Mt. Noja to Mt. Gara. This basic research was executed not only to restore and manage forest vegetation, but also to monitor the trend of change in the long term. As a result of classifying the communitise in 86 survey quadrats, the Pinus thunbergii-Platycarya strobilacea comm. and P. thunbergii-P. densiflora comm. were distributed around the lowlands. The Carpinus tschonoskii-Deciduous broad-leaved comm., Styrax japonicus-Deciduous broad-leaved comm., Acer pictum subsp. Mono-Deciduous broad-leaved comm., Deciduous broad-leaved comm., and Zelkova serrata comm. appeared in the valley and all stone areas. Quercus serrata comm., Q. serrata-S. japonicus comm., S. japonicus-Carpinus cordata comm., Euonymus oxyphyllus comm. were classified as being distributed on steep slopes with relatively high altitude. According to the succession trend of the forest, evergreen conifers will be transition to deciduous broad-leaved trees. However, deciduous broad-leaved arboreous forests, such as Carpinus tschonoskii, zelkova serrata, and Acer pictum subsp. Mono, were considered to maintain their current succession stage because not only the stratified structure was developed over about 50 years tree age, but also ecologically stabilized. As environmental factors, it was analyzed that altitude, pH, content of clay and silt, Mg⁺⁺, Ca⁺⁺, etc. directly or indirectly affect the distribution of plant communities.

• KIPS Transactions on Computer and Communication Systems
• /
• v.10 no.7
• /
• pp.191-198
• /
• 2021

Since the size of training dataset become large and the model is getting deeper to achieve high accuracy in deep learning, the deep neural network training requires a lot of computation and it takes too much time with a single node. Therefore, distributed deep learning is proposed to reduce the training time by distributing computation across multiple nodes. In this study, we propose hybrid allreduce strategy that considers the characteristics of each layer and communication and computational overlapping technique for synchronization of distributed deep learning. Since the convolution layer has fewer parameters than the fully-connected layer as well as it is located at the upper, only short overlapping time is allowed. Thus, butterfly allreduce is used to synchronize the convolution layer. On the other hand, fully-connecter layer is synchronized using ring all-reduce. The empirical experiment results on PyTorch with our proposed scheme shows that the proposed method reduced the training time by up to 33% compared to the baseline PyTorch.

• International Area Studies Review
• /
• v.15 no.3
• /
• pp.513-532
• /
• 2011

Green supply chain management(GSCM) has emerged as a key approach for firms seeking to become sustainable environmentally. GSCM is a system in which the firm takes life cycle responsibility of the products through material recycling, environment-friendly production, and reverse logistics in addition to the classical operations in a supply chain. This paper endeavors to identify the relationship between the GSCM practice implementation and firms' performance among a sample of Korean manufacturing firms. Based on a literature review, eight hypotheses are put forward. First of all, a factor analysis was conducted to derive groupings of GSCM practice from the survey data which included 54 responses. Then, the first regression was conducted to examine the link between GSCM practice implementation and firms' financial performance. The result shows that green purchasing and green production are significant. The second regression was conducted to examine the impact of GSCM practice implementation on the firms' competitiveness. The result reveals that green purchasing, green production, and reverse logistics are positively signifiant.

• Food Engineering Progress
• /
• v.15 no.2
• /
• pp.136-142
• /
• 2011

The objective of this research was to classify intact soybeans and foreign objects using near-infrared (NIR) spectroscopy. Intact soybeans and foreign objects were scanned using a NIR spectrometer equipped with scanning monochromator. NIR spectra of intact soybeans and foreign objects in the wavelength range from 900 to 1800 nm were collected. The classification of intact soybeans and foreign objects were conducted by using partial least-square discriminant analysis (PLS-DA) and soft independent modelling of class analogy (SIMCA) multivariate methods. Various types of data pretreatments were tested to develop the classification models. Intact soybeans and foreign objects were successfully classified by the PLS-DA prediction model with mean normalization pretreatment. These results showed the potential of NIR spectroscopy combined with multivariate analysis as a method for classifying intact soybeans and foreign objects.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.18 no.2
• /
• pp.58-76
• /
• 2019

As the number of reported injuries has tended to increase over time, large hospitalization expenditure from excessive medical treatments and hospitalization, and insurance frauds associated with moral hazard in minor collisions have caused a global societal problem. Many occupants of rear-ended vehicles involved in rear-end collisions complain of whiplash injury, which is also known as neck injury, without any anatomical and radiological evidence. With only clinical symptoms, stating that a whiplash injury is a type of injury defined by the Abbreviated Injury Scale would be difficult. Therefore, this study focuses on minor rear-end collisions, where the rear-ender vehicle collides with the rear-ended vehicle at rest. The mathematics dynamic model is employed to simulate a total of 100 rear-end collision scenarios based on various weights and collision speeds and identify how the weights and speeds of both vehicles influence the risk of whiplash injury in occupants involved in minor rear-end collisions. The possibility of an injury is very high when the same-weight vehicles are involved in accidents at collision speeds of 15 km/h or higher. The possibilities are 36% and 84% with collision speeds of 15 km/h and 20 km/h, respectively, if weights are disregarded.