• Journal of the Society of Naval Architects of Korea
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• v.55 no.4
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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.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.6
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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.

• Journal of the Korean Society for information Management
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• v.16 no.1
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• pp.157-174
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• 1999

This investigation used meta-analysis to examine the quality of data of domestic ST(Science & Technical) databases. Analyses measured the quality of data itself, determined whether these databases have any critical errors in terms of accuracy, completeness, and consistency by conducting the data retrieval experiments. The purpose of this study was to diagnose the science & technical databases and to find out the problems of them and also to provide possible suggestions for their improvements. The researcher concluded the results by mentioning the three research questions.

• IE interfaces
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• v.24 no.3
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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.

• Journal of the Korean Ceramic Society
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• v.42 no.7 s.278
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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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• v.25 no.4
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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.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.25 no.2
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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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• v.43 no.5
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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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• v.21 no.2
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• pp.45-54
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• 2013

Analytical and simulation error models have the ability to describe (or realize) error-corrupted versions of spatial data. But the different approaches for modeling positional errors require an internal validation that ascertains whether the analytical and simulation error models predict correct positional errors in a defined set of conditions. This paper presents stochastic simulation models of a point and a line segm ent to be validated w ith analytical error models, which are an error ellipse and an error band model, respectively. The simulation error models populate positional errors by the Monte Carlo simulation, according to an assumed error distribution prescribed by given parameters of a variance-covariance matrix. In the validation process, a set of positional errors by the simulation models is compared to a theoretical description by the analytical error models. Results show that the proposed simulation models realize positional uncertainties of the same spatial data according to a defined level of positional quality.

• Journal of the Korean School Mathematics Society
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• v.5 no.1
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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.