• Journal of Information Technology Applications and Management
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• v.25 no.2
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• pp.109-116
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• 2018

In this study, we was compared the reliability performance of the software reliability model, which applied the Goel-Okumoto model developed using the exponential distribution, to the logarithmic function modifying the intensity function and the Rayleigh form. As a result, the log-type model is relatively smaller in the mean squared error compared to the Rayleigh model and the Goel-Okumoto model. The logarithmic model is more efficient because of the determination coefficient is relatively higher than the Goel-Okumoto model. The estimated determination coefficient of the proposed model was estimated to be more than 80% which is a useful model in the field of software reliability. Reliability has been shown to be relatively higher in the log-type model than the Rayleigh model and the Goel-Okumoto model as the mission time has elapsed. Through this study, software designer and users can identify the software failure characteristics using mean square error, decision coefficient. The confidence interval can be used as a basic guideline when applying the intensity function that reflects the characteristics of the lifetime distribution.

• Journal of the Korean Society of Industry Convergence
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• v.5 no.4
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• pp.373-378
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• 2002

This paper presents a method to predict tool deflection induced by the thermal distribution and the cutting force using FEM in milling operation. The thermal distribution of cutting tool was predicted using FEM after measuring the temperature of the end of tool and of the tool holder. The thermal deflection of cutting tool was predicted using FEM as well. The tool deflection induced by the cutting force was analyzed with the solid model of cutting tool. An end mill tool caused most of tool deflection comparing to tool holder. Most of thermal deflection came from Z-direction and most of tool deflection induced by the cutting force came from X and Y direction. Precision cutting will be accomplished when tool locations are generated considering the thermal deflection of cutting tool and the tool deflection induced by the cutting force in CAD/CAM.

• Journal of the Korean Society of Propulsion Engineers
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• v.22 no.2
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• pp.131-137
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• 2018

This paper analyzes the probability of failure for the equivalence ratio error. The control error of the equivalence ratio is affected by the aleatory and epistemic uncertainties. In general, reliability analysis techniques are easily incorporated to handle the aleatory uncertainty. However, the epistemic uncertainty requires a new approach, as it does not provide an uncertainty distribution. The Bayesian inference incorporates the reliability analysis results to handle both uncertainties. The result gives a distribution of failure probability, whose equivalence ratio does not meet the requirement. This technique can be useful in the analysis of most engineering systems, where the aleatory and epistemic uncertainties exist simultaneously.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.5
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• pp.533-541
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• 2007

The Zienkiewicz-Zhu(Z/Z) error estimate is slightly modified for the hierarchical p-refinement, and is then applied to L-shaped plates subjected to bending to demonstrate its effectiveness. An adaptive procedure in finite element analysis is presented by p-refinement of meshes in conjunction with a posteriori error estimator that is based on the superconvergent patch recovery(SPR) technique. The modified Z/Z error estimate p-refinement is different from the conventional approach because the high order shape functions based on integrals of Legendre polynomials are used to interpolate displacements within an element, on the other hand, the same order of basis function based on Pascal's triangle tree is also used to interpolate recovered stresses. The least-square method is used to fit a polynomial to the stresses computed at the sampling points. The strategy of finding a nearly optimal distribution of polynomial degrees on a fixed finite element mesh is discussed such that a particular element has to be refined automatically to obtain an acceptable level of accuracy by increasing p-levels non-uniformly or selectively. It is noted that the error decreases rapidly with an increase in the number of degrees of freedom and the sequences of p-distributions obtained by the proposed error indicator closely follow the optimal trajectory.

• Survey Research
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• v.11 no.3
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• pp.33-55
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• 2010

In this study, we newly define the Total Survey Error(TSE) in exit poll and investigate the TSEs of the exit poll survey for the 18th general election of 2008 to analyse the cause of the exit poll prediction error. To explore the main cause and effect of the total survey error, the total survey error was divided by the sampling error which comes from sampling process of poll stations and the non-sampling error which comes from selecting voter and collecting responses from sampled voters in each electoral district. We consider the relationship between non-response rates and total survey error as well as non-sampling error. Also, we study the representativeness of the exit poll sample by comparing the sex/age distribution of the exit poll data and the National Election Commission poll data.

• 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.

• Proceedings of the IEEK Conference
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• 2004.06a
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• pp.59-62
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• 2004

The performance of turbo code is improved by updating extrinsic information. The bit patterns are categorized by the transition characteristics of extrinsic information in this paper. And the distribution of these patterns is surveyed according to signal-to-noise ratio. Based on the results, the dominant error pattern is determined at high signal-to-noise ratio range. Thus, it is expected to improve the error performance in the error floor region by correcting the dominant error pattern which is found in this paper.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2003.10a
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• pp.159-162
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• 2003

The remeshing algorithm using the constrained Delaunay method adapted to the mesh density map is developed. In the finite element simulation of forging process, the numerical error increases as the process goes on. However, it is not desirable to use a uniformly fine mesh in the whole domain. Therefore, it is necessary to reduce the analysis error by constructing locally fine mesh at the region where the error is concentrated such as die corner. In this paper, the point insertion algorithm is used and mesh size is controlled by using a mesh density map constructed with a posteriori error estimation. And an optimized smoothing technique is adapted to have smooth distribution and improve the quality of the mesh.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.4
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• pp.124-130
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• 1996

A compensation method of color error resulting from dynamic range transformation of color image is propsoed. The color error is measured using the CIE L a b uniform color space, and the color image is compensated to minimize it. The color error is significant in the dark region of image, which is caused by the lunimance scaling factor is relatively large in that case. In the proposed method, we weight the luminance scaling factor corresponding to luminnce to minimize the error. Because the weighting factor depends on luminace distribution of image, a decisio method of weighting factor using histogram is also proposed.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.1
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• pp.64-72
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• 2016

The coverage area of a GNSS regional ionospheric delay model is mainly determined by the distribution of GNSS ground monitoring stations. Extrapolation of the ionospheric model data can extend the coverage area. An extrapolation algorithm, which combines observed ionospheric delay with the environmental parameters, is proposed. Neural network and least square regression algorithms are developed to utilize the combined input data. The bi-harmonic spline method is also tested for comparison. The IGS ionosphere map data is used to simulate the delays and to compute the extrapolation error statistics. The neural network method outperforms the other methods and demonstrates a high extrapolation accuracy. In order to determine the directional characteristics, the estimation error is classified into four direction components. The South extrapolation area yields the largest estimation error followed by North area, which yields the second-largest error.