• Proceedings of the Korean Society of Computer Information Conference
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• 2020.01a
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• pp.255-256
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• 2020

생산 현장에서 발생되는 다양한 형태의 데이터는 스마트한 제조관리를 가능하게 하는 원동력으로 이를 효율적으로 저장하고 처리, 분석하는 일련의 과정이 4차 산업혁명 기반의 제조혁신에 능동적으로 대응하기 위한 핵심요소로서, 이와 관련한 다양한 연구들이 활발히 이루어지고 있다. 특히, 제조데이터 분석이라는 영역은 단순하게 기존의 데이터를 통계적인 접근 수단으로만 보는 것이 아니라 다양한 산업별 업종 도메인의 특성에 기반하여 빅데이터 분석과 기계학습 등의 인공지능 모델로 발전하고 있다. 본 논문에서는 다양한 산업별 제조현장을 이해하는 도메인 경험 및 특성을 고려하여 데이터를 효과적으로 저장, 처리, 분석할 수 있는 클라우드 형태의 빅데이터 시스템을 제안한다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.1
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• pp.73-80
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• 2012

It is important to design the optimal shape in the initial process because the influences on the design and construction are large according to the shape and pattern of spatial structures. However, the existing optimal shape designs for spatial structure are performed by the designer's intuition and experiences. Therefore, this study proposes the integrated process using the topology optimization and cellular automata model. First, the initial optimal shapes are obtained by using the topology optimization, and then the spatial truss structural patterns are created through the application of cellular automata rules. Finally, the optimal shapes to satisfy the various design conditions are generated by the structural analysis and size optimization.

• Smart Media Journal
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• v.8 no.3
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• pp.70-79
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• 2019

Implementing UX design that meets user expectations has become an important variable that determines the prominence of smart home appliances. This study addresses the UX design evaluation issues in mobile application development of smart home appliances. As an experimental research subject, the UX design evaluation contents were set up for the mobile application of , the demand of which is surging recently. The purpose of the research is to explore the significance of the UX design user evaluation method in smart home applications, and to suggest how to achieve the mixing of quantitative and qualitative evaluation methods. The main findings are as follows. First, we found that user evaluation can positively impact the direction of UX design. Secondly, we found that the mixing of 'quantitative' and 'qualitative' methods works complementarily to UX design evaluation. Research implications are as follows. The UX design evaluation process can be performed efficiently as long as we distinguish between the roles of quantitative evaluation and qualitative evaluation. For example, through qualitative evaluation such as 'Honeycomb model', can be identified in terms of 'exploratory', and through qualitative evaluation such as 'in-depth user interview', can be identified in terms of 'assessment' and 'validation'.

• Journal of the Korean Geotechnical Society
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• v.22 no.1
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• pp.25-34
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• 2006

In this study an effective stress numerical procedure is used to assess the results of dynamic centrifuge tests under high effective stress. The centrifuge models consist of loose Nevada sand with an initial vertical effective stress of 380kPa at depth, and they are modeled as a one-dimentional soil column. Liquefaction occurred up to 37m or 22m at depth, and the onset of liquefaction triggering was opposite to the conventional liquefaction evaluation procedure. In other words, liquefaction occurs first at the top and propagates downward as shaking continues. The results observed in centrifuge tests are reasonably predicted by the effective stress model. It is noted that the degree of initial saturation and additional densification at depth arising from the application of the high acceleration field play a key role in capturing the results of dynamic centrifuge tests.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.31 no.6
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• pp.458-467
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• 2019

The purpose of this study is the suggestion of optimized parameters in OI (Optimal Interpolation) by experimental study. The observation of applying optimal interpolation is ADCP (Acoustic Doppler Current Profiler) data at the southwestern sea of Korea. FVCOM (Finite Volume Coastal Ocean Model) is used for the barotropic model. OI is to the estimation of the gain matrix by a minimum value between the background error covariance and the observation error covariance using the least square method. The scaling factor and correlation radius are very important parameters for OI. It is used to calculate the weight between observation data and model data in the model domain. The optimized parameters from the experiments were found by the Taylor diagram. Constantly each observation point requires optimizing each parameter for the best assimilation. Also, a high accuracy of numerical model means background error covariance is low and then it can decrease all of the parameters in OI. In conclusion, it is expected to have prepared the foundation for research for the selection of ocean observation points and the construction of ocean prediction systems in the future.

• Journal of KIISE:Software and Applications
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• v.29 no.12
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• pp.860-872
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• 2002

Fault tree analysis is the most widely used saftly analysis technique in industry. However, the analysis is often applied manually, and there is no systematic and automated approach available to validate the analysis result. In this paper, we demonstrate that a real-time model checker UPPAAL is useful in formally specifying the required behavior of safety-critical software and to validate the accuracy of manually constructed fault trees. Functional requirements for emergency shutdown software for a nuclear power plant, named Wolsung SDS2, are used as an example. Fault trees were initially developed by a group of graduate students who possess detailed knowledge of Wolsung SDS2 and are familiar with safety analysis techniques including fault tree analysis. Functional requirements were manually translated in timed automata format accepted by UPPAAL, and the model checking was applied using property specifications to evaluate the correctness of the fault trees. Our application demonstrated that UPPAAL was able to detect subtle flaws or ambiguities present in fault trees. Therefore, we conclude that the proposed approach is useful in augmenting fault tree analysis.

• Journal of the Korean Geotechnical Society
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• v.16 no.4
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• pp.107-116
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• 2000

In this study, the permeability reduction in the soil-filter systems due to clogging phenomenon was evaluated. An extensive research program was performed using two typical weathered residual soils which were sampled at Shinnae-dong and Poi-dong area in Seoul. Two separate simulation tests with weathered residual soil were performed: one was the filtration test(cross-plane flow test); and the other was the drainage material in the field. The compatibility of the sol-filter system was investigated with emphasis on the clogging phenomenon. The hydraulic behaviour of the soil-filter system was evaluated by changing several testing conditions. Also, experimental results of the permeability reduction are compared with the results obtained from the theoretical model which can monitor the spatial variation of the permeability with time.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.430-430
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• 2016

범용토양유실공식(RUSLE)은 연간 토양유실량을 산정하기 위해 제시된 경험식이며, 강우침식인자(R factor)는 유실량을 결정하는 요소 중 강우강도의 특성을 고려하는 주요인자이다. 토지피복, 식생 등에 대한 타 인자의 경우 한정된 실험에 의해 도출된 경험치를 대상지역에 맞게 적용하는데 반해 강우침식인자는 강우강도 기반 강우에너지 산정법을 적용하여 계산과정이 비교적 복잡하고 다양하다. 국내에서도 강우침식인자 산정법이 개발된 바 있으나 현제까지 간편법을 비롯한 다양한 공식들이 적용되고 있다. 본 연구에서는 강우침식인자를 산정하는 과정에서 다른 강우 운동에너지식을 적용하거나 연평균 강수량 등을 대체지수로 활용한 간편법 적용시 결과의 결과의 다양성에 대해 분석하고자 하였다. 합리적인 30분 강우강도 산정을 위해 79개 기상청 종관기상관측 지점에 대한 분단위 강우자료(1997~2014)를 수집하고 기존의 국내외 강우운동에너지 식과 대체지수를 적용하여 산정된 결과를 비교 분석하였다. 연구결과 간편법을 사용한 결과가 대부분 지점에 대해 강우에너지식을 사용한 강우침식인자보다 과대산정(지점평균 약 74%)하였으며 다른 강우에너지식 적용에 따른 평균 변동계수가 약 0.12로 나타나 지점간 차이를 보였으나 적용방법에 따른 침식인자의 분포가 다소 다르게 나타남을 확인하였다. 관측자료가 부족한 토양유실량 예측에 있어 강우 침식인자 산정을 위한 최적 방법론 도출이 어려운 만큼 다중모델 결과를 조합하는 방법론 개발이 필요하다고 판단된다.

• Journal of the Korean Institute of Gas
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• v.24 no.6
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• pp.11-17
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• 2020

In order to guarantee safe storage and transportation of a flammable liquid solution, it is very important to know its flash point information. In this paper, flash points of n-octane+n-nonane system and n-nonane+n-decane system were measured by Seta flash apparatus and an empirical equation is proposed for the accurate estimation of flash point. Empirical equation is used to predict flash point of n-octane+n-nonane system and n-nonane+n-decane system, which were also compared to Unifac-based model. Absolute average errors of flash point data predicted by Unifac-based model are 0.7℃ and 0.6℃ for n-octane+n-nonane system and n-nonane+n-decane system, respectively. Absolute average errors of flash point data predicted by empirical equation are 0.2℃ and 0.4℃ for n-octane+n-nonane system and n-nonane+n-decane system, respectively. In conclusion, empirical equation proposed in this paper, presented the most satisfactory.

• Journal of the Korean Geotechnical Society
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• v.39 no.4
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• pp.5-17
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• 2023

The advancement in large-scale underground excavation in urban areas necessitates monitoring and predicting technologies that can pre-emptively mitigate risk factors at construction sites. Traditionally, two methods predict the deformation of retaining walls induced by excavation: empirical and numerical analysis. Recent progress in artificial intelligence technology has led to the development of a predictive model using machine learning techniques. This study developed a model for predicting the deformation of a retaining wall under construction using a boosting-based algorithm and an ensemble model with outstanding predictive power and efficiency. A database was established using the data from the design-construction-maintenance process of the underground retaining wall project in a manifold manner. Based on these data, a learning model was created, and the performance was evaluated. The boosting and ensemble models demonstrated that wall deformation could be accurately predicted. In addition, it was confirmed that prediction results with the characteristics of the actual construction process can be presented using data collected from ground measurements. The predictive model developed in this study is expected to be used to evaluate and monitor the stability of retaining walls under construction.