• 대한조선학회논문집
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• 제55권4호
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• pp.361-369
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• 2018

The ship surveyor makes a scheme of reasonable ship operation by examining whether the ship has been properly constructed in accordance with the rule of classification societies and international conventions or whether the facilities of the ship in operation meet the standard stipulated by law. Even though the ship surveyors of classification society generally consist of people who have the skill of design or operation of a ship, it takes a long time to train a surveyor to the maturity level. This paper describes the development of survey simulator based on virtual ship environment that enables the surveyor minimize trial and errors to survey the ships. By using VR(Virtual Reality) based survey simulator, surveyors possibly achieve improvement of competence in survey quality by means of safe and immersive training environment. In order to improve the usability and utility of the VR simulator, the ship 3D model has been generated using 3D CAD model for design and production in shipyard. Through this, we suggested the possibility of consistent use of 3D model as the digital twin of a ship.

• 한국지능시스템학회논문지
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• 제12권6호
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• pp.577-582
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• 2002

Neural network can be trained to approximate an arbitrary nonlinear function of multivariate data like the mini-mill crown values in Automatic Shape Control. The trained weights of neural network can evaluate or generalize the process data outside the training vectors. Sometimes, the blind modeling of the process data is necessary to compare with the scattered analytical model of mini-mill process in isolated electro-mechanical forms. To come up with a viable model, we propose the blind neural-based range-division domain-clustering piecewise-linear modeling scheme. The basic ideas are: 1) dividing the range of target data, 2) clustering the corresponding input space vectors, 3)training the neural network with clustered prototypes to smooth out the convergence and 4) solving the resulting matrix equations with a pseudo-inverse to alleviate the ill-conditioning problem. The simulation results support the effectiveness of the proposed scheme and it opens a new way to the data analysis technique. By the comparison with the statistical regression, it is evident that the proposed scheme obtains better modeling error uniformity and reduces the magnitudes of errors considerably. Approximatly 10-fold better performance results.

• 정보관리학회지
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• 제16권1호
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• pp.157-174
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• 1999

본 연구는 국내에서 제작된 주요 과학기술 데이터베이스 3개를 선정하고 각 데이터베이스의 검색결과를 조사하여 데이터베이스의 품질을 종합적으로 평가한 메타 연구이다. 종합적 평가로부터 지적된 문제점들을 나열하고 해결방안과 정책적인 제언을 모색하고자 하는 목적으로 진행되었다. 연구의 주요 결과는 첫째, 기준측정에서 상기한 연구대상들은 적지 않은 오류와 미비점을 보이고 있으며 둘째, 일반적으로 데이터베이스자체에 대한 공식적인 설명이나 안내가 누락되어 있고, 셋째, 검색되는 색인어나 주제어의 용어통제가 완벽하게 이루미지지 않고 있다. 넷째 최종 이용자 검색을 지원하고 있는 색인어 브라우징이나 주제별 상호참조와 같은 서비스 지원이 제대로 이루어지고 있지 않으며, 마지막으로 검색시 발생할 수 있는 오류와 그에 대한 이용자의 오류처리안내나 설명이 검색과정에서 제공되지 않거나 실질적인 도움을 주지 못하고 있는 것으로 나타났다.

• 산업공학
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• 제24권3호
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• pp.248-257
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• 2011

The amount of Meta-data to be managed increases with development of information technology. However, when trying to integrate and share product information of heterogeneous systems within or between companies, sharing of information is impossible if product information classification systems are different. Due to the situation mentioned above, engineers judge the product information classification system and maps corresponding Meta-data for document-based sharing. Judging exponentially increasing amount of data by engineers and sharing product information using documents create great amount of time delay and errors in data handling. Therefore, construction of a system for integrated management and interoperability between product information based on semantic information similar to engineer's judgment is required. This paper proposes a methodology and necessity of a system for interoperability of product information based on semantic web, and also designs a system to integrate heterogeneous systems with different product information using rule based reasoning. This paper also suggests a system base for interoperability and integration of product information between heterogeneous systems by integrating the product information classification system semantically.

• 한국세라믹학회지
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• 제42권7호
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• pp.449-454
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• 2005

A waveguide method is developed to study the materials with relatively large dielectric constants at microwave range. Basically, the method is similar to the previous waveguide methods represented by short-circuit line and transmission/reflection measurement methods. However, the complex permittivity is not determined by the shift in resonance frequencies, but by numerical analysis of measured scattering parameters. In order to enhance microwave penetration into the specimen with relatively large permittivity, a dielectric plate with lower permittivity is employed for impedance matching. The influences of air gap between the specimen and waveguide wall are evaluated, and the corresponding errors are estimated. The propagation of higher order modes is also considered. Experimental results for several reference ceramics are presented.

• Environmental Engineering Research
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• 제25권4호
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• pp.515-521
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• 2020

Nowadays, due to various pollution sources, it is essential for environmental scientists to monitor water quality. Phytoplanktons form the end of the food chain in water bodies and are one of the most important biological indicators in water pollution studies. Chlorophyll-A, a green pigment, is found in all phytoplankton. Chlorophyll-A concentration indicates phytoplankton biomass directly. Therefore, Chlorophyll-A is an indirect indicator of pollutants, including phosphorus and nitrogen, and their refinement and control are important. The present study, Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images were used to estimate the chlorophyll-A concentration in southern coastal waters in the Caspian Sea. For this purpose, Multi-layer perceptron neural networks (NNs) were applied which contained three and four feed-forward layers. The best three-layer NN has 15 neurons in its hidden layer and the best four-layer one has 5 in each. The three- and four- layer networks both resulted in similar root mean square errors (RMSE), 0.1($\frac{{\mu}g}{l}$), however, the four-layer NNs proved superior in terms of R² and also required less training data. Accordingly, a four-layer feed-forward NN with 5 neurons in each hidden layer, is the best network structure for estimating Chlorophyll-A concentration in the southern coastal waters of the Caspian Sea.

• 한국소음진동공학회논문집
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• 제25권2호
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• pp.101-107
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• 2015

Field balancing is required in any kind of phase information for the determination location balancing mass toward a rotor unbalance mass. Phase or phase angle is a measurement of the relationship of how one vibration signal which relates to another vibration signal and is commonly used to calculate the placement of balance weight. In this paper, A right guideline shows the photo optical speed sensor as the external KeyPhasor is a very useful when diagnosing machinery vibration problems on considering a phase lag comparing to the laser optical speed sensor. Some experimental results generate the interesting phase errors when appling to a wrong conditions. So, Usage of photo optical speed sensor which is used primarily to measure the shaft rotating speed serves as a reference for measuring vibration phase information has effect on the placement of phase angle how it was misunderstood. This paper will help a right method to search for the position of balancing weight and serves as baseline for further measurements using low cost and much easier user convenience. It is concluded that the propose baseline is likely to be applicable to apply to the practical field balancing weight.

• Steel and Composite Structures
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• 제43권5호
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• pp.625-637
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• 2022

Axial compression capacity (P_u) is a significant yet complex parameter of concrete-filled steel tube (CFST) columns. This study offers a novel ensemble tool, adaptive neuro-fuzzy inference system (ANFIS) supervised by equilibrium optimization (EO), for accurately predicting this parameter. Moreover, grey wolf optimization (GWO) and Harris hawk optimizer (HHO) are considered as comparative supervisors. The used data is taken from earlier literature provided by finite element analysis. ANFIS is trained by several population sizes of the EO, GWO, and HHO to detect the best configurations. At a glance, the results showed the competency of such ensembles for learning and reproducing the P_u behavior. In details, respective mean absolute errors along with correlation values of 4.1809% and 0.99564, 10.5947% and 0.98006, and 4.8947% and 0.99462 obtained for the EO-ANFIS, GWO-ANFIS, and HHO-ANFIS, respectively, indicated that the proposed EO-ANFIS can analyze and predict the behavior of CFST columns with the highest accuracy. Considering both time and accuracy, the EO provides the most efficient optimization of ANFIS and can be a nice substitute for experimental approaches.

• Spatial Information Research
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• 제21권2호
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• pp.45-54
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• 2013

해석적 또는 시뮬레이션 오차 모델은 공간 데이터가 가지는 위치오차의 분포를 설명 하는데 유용하다. 그러나 두 오차 모델은 위치오차를 모델링을 하기위하여 다른 접근 방법을 이용하므로 정의된 조건 내에서 올바른 위치오차를 예측 하는지 확인하는 내적 검증을 필요로 한다. 이에 본 논문은 오차타원과 에러밴드 모델을 이용하여 제시한 포인트와 라인 세그먼트 시뮬레이션 오차 모델을 내부적으로 검증하는 방법을 제안하였다. 시뮬레이션 오차 모델은 분산-공분산 행렬(variance-covariance matrix)의 변수에 의해 규정된 확률분포에 따라 몬테카를로 시뮬레이션을 이용하여 위치오차들을 생성한다. 검증절차에서는 시뮬레이션 모델에 의한 위치오차의 집합을 해석적 오차 모델에 의한 이론적 위치오차와 비교하였다. 결과적으로 제안된 시뮬레이션 오차 모델은 정의된 위치오차에 따라 동일한 공간 데이터의 위치적 불확실성을 실현함을 확인할 수 있었다.

• 한국학교수학회논문집
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• 제5권1호
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• pp.111-122
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• 2002

The purpose of this study was to examine high school second graders' understanding of the basic nature of logarithm, the major type of error they made about logarithmic function and the cause of such an error, and to seek ways to instruct it better. For that purpose, three research questions were posed: 1. Investigate how much high school students in their second year comprehend the nature of logarithm. 2. Analyze what type of error they make about logarithmic function. 3. Analyze the cause of their error according to the selected error models and how it could be taught more efficiently. The findings of this study were as below: First, the natural science students had a better understanding of the basic nature of logarithm than the academic students. What produced the widest gap between the two groups' understanding was applying the nature of logarithm to the given problems, and what caused the smallest gap was the definition of logarithm and the condition of base. Second, the academic students had a poorer understanding of the basic nature of logarithmic function graph and of applying the nature of logarithm to the given problems. Third, the natural science students didn't comprehend well the basic nature of logarithmic function graph, the nature of characteristics and mantissa. Fourth, for all the students from academic and natural science courses, the most common errors were caused by the poor understanding of theorem or nature of the ［E4] model. Fifth, the academic students made more frequent errors due to the unfamiliar signs of the ［El］ model, the imperfect understanding of theorem or nature of the ［E4］ model, and the technical part of the ［E6］ model. Sixth, the natural science students made more frequent errors because of the improper problem interpretation of the ［E2］ model and the logically improper inference of the ［E3］ model.