• KNOM Review
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• v.22 no.3
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• pp.25-30
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• 2019

For meteorological applications, meaningful results must be derived and provided within time and resource limits. Forecasts through numerous historical data are time-consuming and still have resource limitations in the case of disaster safety-related analyses/predictions such as local typhoon forecasts. Suitable forecasts should be provided without any problems caused by limited physical environmental conditions and when results are to be drawn under time constraints, such as typhoon forecasts and forecast services for flooded areas by road. In this paper, we analyze the application of weather and climate forecasting to provide a suitable forecasting service in both temporal and resource conditions. Through the analysis of execution time according to mesh sizes, it was confirmed that a mesh adjustment can cope with the case of the temporal constraint. In addition, by analyzing the execution time through memory resource control, we confirmed the minimum resource condition that does not affect the performance and the resource usage pattern of the application through the swap and mlock analysis.

• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.69.3-69.3
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• 2020

우주개발과 활용이 주요 화두가 된 현대에 보다 빠르고 정확한 우주환경 예보는 전략적으로 매우 중요하다. 이에 우리는 광대역태양영상분광망원경(Wide-Field Solar Spectro-Imaging Telescope, Post SOlar Flare Telescope: PSOFT)을 활용한 태양전면 영상분광감시체계를 구성하고자 한다. 전세계 세 곳에 PSOFT를 배치하여 우주환경에 중대한 영향을 주는 요소인 태양의 플레어와 홍염 분출과 같은 현상과 표면의 다양한 활동들을 실시간으로 관측 분석하고자 한다. PSOFT는 30cm 구경의 광학계에 고속영상분광기를 결합하여 태양 전면의 분광영상을 약 1초각의 영상해상도와 5분의 시간해상도로 획득한다. 태양 전면을 슬릿으로 스캔하는 방식으로 H alpha와 Ca II 854.2nm선의 분광정보를 획득하는데 팁틸트 미러를 이용하여 1차적인 시상보정과 함께 스캔모션을 함께 구현함으로써 1)광학계 구조를 단순화하고, 2) 빠른 스캔이 가능하다. PSOFT로 얻은 태양전면 채층분광영상 데이터는 정밀한 우주환경 예보에 필요한 플레어나 홍염분출의 발생초기 정보를 제공할 뿐 아니라 태양 저층대기에서 발생하는 자기재연결, 파동 등에 대한 통계적 연구자료를 제공할 것으로 기대한다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3A
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• pp.357-366
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• 2008

This study addresses the analysis of the behavioral characteristics of bridge expansion joints under wheel loading through wheel load test and the proposal of relevant wheel load specifications for expansion joints. To that goal, specimens of rail and finger expansion joints that are widely used in Korea were fabricated and subjected to static wheel load test using a real tire wheel. The wheel load distribution factor in the rail and finger expansion joints in contact with the wheel load was evaluated. The evaluation revealed that the portion of load sustained by the central rail of rail expansion joint was decreasing with larger wheel load, and that the portion of load sustained by the finger expansion joint was practically insensitive to the increase of the contact area and remained nearly constant. Since the wheel load characteristics showed large difference compared to former design specifications, it appears necessary to prepare rational specifications relative to the distribution of the wheel load contact pressure for the design of expansion joints.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6D
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• pp.819-829
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• 2008

Fatigue cracking occurs over long time period because dynamic strength of slab continuously decreases by vehicle loading repetitively applied to the concrete pavement. To more accurately predict the fatigue life of the concrete pavement, the stress due to environmental loading should be considered prior to calculating the stress due to the vehicle loading because the stress due to temperature and moisture distribution always exists within the slab. Accordingly, a new fatigue model considering the environmental loading was developed in this research by evaluating factors of existing fatigue models most widely used and by making data points from the models. The applicability of the new model was evaluated by performing a fatigue analysis on the general concrete pavement structure using local climatic and traffic conditions in Korea. It was concluded that the top-down cracking due to the tensile stress at top of the slab is dominant cause of the fatigue failure than the bottom-up cracking occurred at bottom of the slab. More advanced fatigue analysis considering vehicle speed is expected by developing this study.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5D
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• pp.597-607
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• 2008

ATIS(Advanced Traffic Information System) provide valuable information as the travel time and traffic congestion, detour, traffic accident information to drivers, so it is being in the spotlight. But so far, the study on the consumer satisfaction with providing traffic information is incomplete. So, this study run a Canonical discriminant analysis and a Canonical correlation analysis by a QuantificationIItheory based on a Traffic Information Satisfaction image data through questionnaires, and found out the factors with influence on the consumer satisfaction. And this study definitely found out the correlation between consumer's recognition and traffic information satisfaction through understanding the change on the recognition about traffic information satisfaction by a QuantificationItheory. Finally, this study found out the change on the sensibility recognition of drivers by running the principal component anlysis, developed the traffic information satisfaction evaluation model considering the change on the recognition by using the structural equation model.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.541-547
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• 2006

With the new paradigm of ubiquitous in the developed computing technology, it is urgently necessary to research GIS fields centering around positioning techniques. The intention of this study is to propose implementation methods for integrating topographic and cadastral data. For this purpose an integrated data model is formed to coincide the graphic data of cadastral map with that of topographic map. As a result, the integrated data model could be built by harmonizing cadastral map with topographic map. We suggest data model for connecting with other information systems in the conditions of data uniformity and implementation. This data implementation models suggested in this research can provide a good reference for the future implementation of other systems. This results will be efficiently used as basis for practical use in ubiquitous environments of spatial informations.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3D
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• pp.231-240
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• 2010

As majority of the traffic accidents in intersections is caused by human factor, a close examination is required on its contributing factors through measuring the psychological and physiological response according to the driving characteristics of the drivers and the road conditions. In this study, for the safety evaluation of individual intersection considering human factors of the drivers, electroencephalography reaction was measured utilizing cutting-edge measuring equipment and survey on drivers' cognitive characteristics in ordinary times and while driving test was conducted. The relationship between the electroencephalography response when approaching the intersection and cognitive evaluation survey data in driving test was clarified, and individual intersection safety evaluation model was built considering cognitive evaluation factor and the reaction of a bio-response electroencephalography data. As a result, I could find out that cognitive evaluation was made through the reaction of a bio-response (Electroencephalography) process because electroencephalography reaction of a bio-response showed differently by the physical characteristics of the intersection and cognitive evaluation had a difference.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.35-38
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• 2023

포트홀은 주행하는 자동차와 접촉이 이뤄지면 차체나 운전자에게 충격을 주고 제어를 잃게 하여 도로 위 안전을 위협할 수 있다. 포트홀의 검출을 위한 국내 동향으로는 진동을 이용한 방식과 신고시스템 이용한 방식과 영상 인식을 기반한 방식이 있다. 이 중 영상 인식 기반 방식은 보급이 쉽고 비용이 저렴하나, 컴퓨터 비전 알고리즘은 영상의 품질에 따라 정확도가 달라지는 문제가 있었다. 이를 보완하기 위해 영상 인식 기반의 딥러닝 모델을 사용한다. 따라서, 본 논문에서는 사전 학습된 딥러닝 모델의 정확도 향상을 위한 Feature Level Ensemble 기법을 제안한다. 제안된 기법은 사전 학습된 CNN 모델 중 Test 데이터의 정확도 기준 Top-3 모델을 선정하여 각 딥러닝 모델의 Feature Map을 Concatenate하고 이를 Fully-Connected(FC) Layer로 입력하여 구현한다. Feature Level Ensemble 기법이 적용된 딥러닝 모델은 평균 대비 3.76%의 정확도 향상을 보였으며, Top-1 모델인 ShuffleNet보다 0.94%의 정확도 향상을 보였다. 결론적으로 본 논문에서 제안된 기법은 사전 학습된 모델들을 이용하여 각 모델의 다양한 특징을 통해 기존 모델 대비 정확도의 향상을 이룰 수 있었다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.59-64
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• 2024

Recently, research on the convergence of drones and artificial intelligence technologies have been conducted in various industrial fields. In this paper, we propose an illegal parking vehicle recognition model using deep learning-based object recognition and classification algorithms. The model of object recognition and classification consist of YOLOv8 and ResNet18, respectively. The proposed model was trained using image data collected in general road environment, and the trained model showed high accuracy in determining illegal parking. From simulation results, it was confirmed that the proposed model has generalization performance to identify illegal parking vehicles from various images.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.1
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• pp.13-25
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• 2024

In traffic management, gaps in understanding traffic conditions continue to exist. While the self-belonging problem indicator develops relative to speed, belonging, and self-based relative inclination, it does not apply elimination criteria that may indicate situations that contrast with attribute-specific problems. In this study, we develop integrated indicators that specify communication situations and safety levels for modeling. We review indicators of changes in traffic conditions and raise safety issues, reviewing the indicators so that ITS data can be applied, analyzing the relationships between indicators through factor analysis. We develop combined, integrated indicators that can show changes and stability in traffic situations and that can be applied in traffic information centers to contribute to the development of a traffic environment that can monitor related traffic conditions.