• 한국해안·해양공학회논문집
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• 제20권5호
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• pp.482-490
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• 2008

연안 및 항만구조물의 설계에서 최극 고조위는 매우 중요한 환경인자이다. 특히, 최극 고조위의 분포정보는 최근 부각되고 있는 신뢰성 설계에 필수적인 요소이다. 본 연구에서는 국립해양조사원에서 제시한 한국연안 주요 23개 검조소의 최극조위자료를 이용하여 극치분포 분석을 수행하였다. 특성분석에 사용된 극치분포함수는 Generalized Extreme Value, Gumbel 그리고 Weibull 분포이며, 각 분포함수의 매개변수는 모멘트법, 최우도법 그리고 확률가중모멘트법 등 3가지방법으로 추정하였다. 또한, 극치분포함수의 적합성은 95% 신뢰도 수준으로 $X^2$ 및 K-S 검정을 실시하였다. 그 결과, 23개 검조소의 최극 고조위는 Gumbel 분포형이 가장 적합한 모형으로 파악되었으며, 최적 추정된 매개변수 및 재현기간별 최극 고조위 정보를 제시하였다. 심 등(1992)이 제시한 인천, 제주, 여수, 부산, 묵호에 대한 극치해면값은 본 논문에서 산정한 결과에 비하여 작게 나타났다.

• Smart Structures and Systems
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• 제20권1호
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• pp.11-22
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• 2017

The long-term effect of ambient temperature on bridge strain is an important and challenging problem. To investigate this issue, one year data of strain and ambient temperature of a long-span cable-stayed bridge is studied in this paper. The measured strain-time history is decomposed into two parts to obtain the strains due to vehicle load and temperature alone. A linear regression model between the temperature and the strain due to temperature is established. It is shown that for every $1^{\circ}C$ increase in temperature, the stress is increased by 0.148 MPa. Furthmore, the extreme value distributions of the strains due to vehicle load, temperature and the combination effect of them during the remaining service period are estimated by the average conditional exceedance rate approach. This approach avoids the problem of declustering of data to ensure independence. The estimated results demonstrate that the 95% quantile of the extreme strain distribution due to temperature is up to $1.488{\times}10^{-4}$ which is 2.38 times larger than that due to vehicle load. The study also indicates that the estimated extreme strain can reflect the long-term effect of temperature on bridge strain state, which has reference significance for the reliability estimation and safety assessment.

• 동력기계공학회지
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• 제19권1호
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• pp.31-37
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• 2015

In this paper, it is presented the development of a new type force feedback system. It is based on a 6-DOF Stewart parallel mechanism which has six pneumatic actuated cylinders. The thrust force of each cylinder is controlled by PWM control for the solenoid valve and it is actualized by PIC controller. When the pneumatic actuator is controlled, it must be considered the influence on the compressibility of air. For this problem, we guarantee the control characteristics by the effect of the accumulator. It is confirmed that the thrust force of the cylinder can be applied to the pneumatic parallel mechanism, and is presented the experimental result of force control for vertical direction.

• Wind and Structures
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• 제18권6호
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• pp.633-650
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• 2014

The uncertainty of extreme wind speeds is one key contributor to the uncertainty of wind loads and their effects on structures. The probability distribution of annual extreme wind speeds may be characterized using a classical Gumbel Type distribution. The expression that establishes the relationship between the extreme wind speeds at different recurrence periods and the corresponding coefficients of variation is formulated, and its efficacy is validated. The coefficients of variation are calibrated to be about 0.125 and 0.184 according to defined Chinese and US design specifications, respectively. Based on the wind data of 54 cities in China, 49 meteorological stations in the US, 3 stations in Singapore, the coefficients span intervals of (0.1, 0.35), (0.08, 0.20) and (0.06, 0.14), respectively. For hurricanes in the US, the coefficients range approximately from 0.3 to 0.4. This convenient technique is recommended as one alternative tool for coefficient of variation analyses in the future revisions of related codes. The sensitivities of coefficients of variation for 49 meteorological stations in the US are quantified and demonstrated. Some contradictions and incompatibilities can be clearly detected and illustrated by comparing the coefficients of variation obtained with different combinations of recurrence period wind data.

• Structural Engineering and Mechanics
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• 제60권2호
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• pp.193-209
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• 2016

In this study, wave force tests were carried out for the four types of offshore support structures with scale factor 1:25 and wave forces to the support structure shapes were investigated. As the results of this study, it was found that, as the wave period increased at the normal wave condition, wave force decreased for the most cases. Extreme wave force was affected by the impact wave force. Impact wave force of this study significantly effect on Monopile and slightly on GBS and Hybrid type. Accordingly, Hybrid type indicated even lower wave force at the extreme and irregular wave conditions than the Monopile although Hybrid type indicated higher wave force at the normal wave condition of the regular wave because of the larger wave area of wave body. In respects of the structural design, since critical loading is extreme wave force, it should be contributed to improve structural safety of offshore support structure. However, since the impact wave force has nonlinearity and complication dependent on the support structure shape, wave height, wave period, and etc., more research is needed to access the impact wave force for other support structure shapes and wave conditions.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 추계학술대회 논문집(제1권)
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• pp.195-201
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• 2006

해양구조물에 유기되는 파랑력과 해양파에 의한 해양구조물의 운동특성에 대한 연구는 선형이론에 근거한 통계적인 방법에 의해 꾸준히 연구되어왔다. 이러한 연구는 선형이론의 제한성으로 인해 파 스펙트럼의 극한에 해당하는 극한파에 대해서는 적용하기 어려운 점이 있다. 본 연구에서는 간단한 구조물에 대하여 극한파에 의한 파랑력을 추정하는 수치기법을 개발하였다. 극한파는 선형 파랑 집중법을 이용하여 수치적으로 구현하여 바닥면에 고정된 수직 실린더에 작용하는 파랑력을 추정하였다. 또한 수직 실린더의 유탄성 응답을 고려하여 강체인 경우와 탄성체의 경우에서 극한파에 의한 파랑력 변화를 고찰하였다.

• 한국해안·해양공학회논문집
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• 제21권6호
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• pp.480-494
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• 2009

장기간의 극치 파랑자료는 연안 및 항만구조물의 계획 및 설계에서 매우 중요한 인자이다. 그러나, 한국 연안 심해파는 관측 자료가 한정되어 있으므로 기상정보로부터 사후추정한 장기간의 파랑자료를 이용하고 있다. 한국해양연구원(2005)에서는 1979년부터 2003년까지의 한국연안 106개 지점의 극치 파랑 자료를 제시하였다. 본 연구에서는 이 자료를 활용하여 최적 극치분포 함수를 분석하고, Goda(2004)가 제안한 확산모수를 산정하였다. 산정된 확산모수는 모멘트법으로 산정한 결과와 잘 일치하였다. 그러나, 확산모수가 외국사례보다 큰 1.0에서 2.8에 이르고 있기 때문에 차후 설계파에 대한 검토가 필요하다.

• IEIE Transactions on Smart Processing and Computing
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• 제2권6호
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• pp.323-331
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• 2013

An extreme learning machine (ELM) is an efficient learning algorithm that is based on the generalized single, hidden-layer feed-forward networks (SLFNs), which perform well in classification applications. Many studies have demonstrated its superiority over the existing classical algorithms: support vector machine (SVM) and BP neural network. This paper presents a novel face recognition approach based on a multi-class project extreme learning machine (MPELM) classifier and 2D Gabor transform. First, all face image features were extracted using 2D Gabor filters, and the MPELM classifier was used to determine the final face classification. Two well-known face databases (CMU-PIE and ORL) were used to evaluate the performance. The experimental results showed that the MPELM-based method outperformed the ELM-based method as well as other methods.

• 한국정보컨버전스학회:학술대회논문집
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• 한국정보컨버전스학회 2008년도 International conference on information convergence
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• pp.59-62
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• 2008

When performing a project, the most important thing is building a result with planned quality within development period. Particularly, if the project is delayed or has no good quality in the case of the mobile game development project which is sensitive to the release time and quality, it is immediately connected to the failure of the project. Extreme Programming is a methodology that divides the development cycle into smaller units for reducing the risk factor of the project in which the development period is important. In this paper, we suggest the Expanded Extreme Programming for mobile game development environment in which the development period and quality are important

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권1호
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• pp.451-465
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• 2017

This paper presents a novel discriminative visual tracking algorithm with an adaptive incremental extreme learning machine. The parameters for an adaptive incremental extreme learning machine are initialized at the first frame with a target that is manually assigned. At each frame, the training samples are collected and random Haar-like features are extracted. The proposed tracker updates the overall output weights for each frame, and the updated tracker is used to estimate the new location of the target in the next frame. The adaptive learning rate for the update of the overall output weights is estimated by using the confidence of the predicted target location at the current frame. Our experimental results indicate that the proposed tracker can manage various difficulties and can achieve better performance than other state-of-the-art trackers.