• Journal of the Korean Society of Manufacturing Process Engineers
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• v.13 no.5
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• pp.64-69
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• 2014

This article presents machining experiments to assess the relationship between the profile accuracy and the workpiece hardness using a natural diamond tool on an ultra-precision diamond turning machine. The study is intended to secure a corner cube prism pattern for reflective film capable of high-quality outcomes. The optical performance levels and edge images of corner cubes having various hardness levels of the copper-coated layer on a carbon steel plate are analyzed. The hardness of the workpiece has a considerable effect on the profile accuracy. The higher the hardness of the workpiece, the better the profile accuracy and the worse the edge wear of the diamond tool.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.2
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• pp.175-179
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• 2014

The histogram specification turns the shape of a histogram into that we want to specify. This technique can be applied usefully in various image processing fields such as machine vision. However, the histogram specification technique has its basic limits. For instance, the histogram does not have location information of pixels. Also, the accuracy of the specification drops because of quantization errors of the digitized image. In this paper, we proposed a multiresolution histogram specification method in order to improve the accuracy of specification in terms of resemblance between destination and source image. The experimental results show that the proposed method enhances the accuracy of the specification compared to the conventional methods.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.1
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• pp.88-94
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• 1999

This paper presents an accuracy evaluation method for muzzle velocity measurement systems. Among various measuring techniques, the solenoid coil scheme and the doppler radar scheme are considered due to their popularity in applications. The error sources are first identified and their effects on the accuracy of the measuring systems are quantified using mathmatical equations. The theoritic accuracy limits are then verified through comparison with experimental results. From the accuracy point of view, they turn out to be standard velocity measuring systems.

• International Journal of Naval Architecture and Ocean Engineering
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• v.9 no.4
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• pp.429-438
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• 2017

Cranke-Nicolson scheme in native OpenFOAM source libraries was not able to provide 2nd order temporal accuracy of velocity and pressure since the volume flux of convective nonlinear terms was 1st accurate in time. In the present study the simplest way of getting the volume flux with 2nd order accuracy was proposed by using old fluxes. A possible numerical instability originated from an explicit estimation of volume fluxes could be handled by introducing a weighting factor which was determined by observing the ratio of the finally corrected volume flux to the intermediate volume flux at the previous step. The new calculation of volume fluxes was able to provide temporally accurate velocity and pressure with 2nd order. The improvement of temporal accuracy was validated by performing numerical simulations of 2D Taylor-Green vortex of which an exact solution was known and 2D vortex shedding from a circular cylinder.

• The Journal of Information Technology and Database
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• v.2 no.2
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• pp.71-85
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• 1995

Many research results conducted by neural network researchers have claimed that the classification accuracy of neural networks is superior to, or at least equal to that of conventional methods. However, in series of neural network classifications, it was found that the classification accuracy strongly depends on the characteristics of training data set. Even though there are many research reports that the classification accuracy of neural networks can be different, depending on the composition and architecture of the networks, training algorithm, and test data set, very few research addressed the problem of classification accuracy when the basic assumption of data monotonicity is violated, In this research, development project of automated credit evaluation system is described. The finding was that arrangement of training data is critical to successful implementation of neural training to maintain monotonicity of the data set, for enhancing classification accuracy of neural networks.

• Korean Journal of Occupational Health Nursing
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• v.19 no.2
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• pp.217-222
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• 2010

Purpose: The purpose of this study was to assess the accuracy of references in articles published in Korean Journal of Occupational Health Nursing. Methods: All references in articles from 2007 to 2009 were compared with PubMed for authors, years, titles, journals, volume, and page accuracy. Four hundred twenty six references were reviewed. Errors were classified either major or minor. Results: Overall rate of inaccurate reference was 46.5%. 34.5% were major errors and 18.8% were minor errors. Most common major errors occurred in the authors, whereas most common minor errors occurred in the titles. Conclusion: It is necessary that authors, reviewers, and editorial committees make more efforts to enhance the reference accuracy.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.2
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• pp.53-58
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• 2003

It is very important to measure linear cycle plane positioning accuracy of NC lathe as it effects all other parts of machines machined by them in industries. If the plane positioning accuracy of NC lathe is bad, the dimension accuracy and the change-ability of works will be bad in the assembly of machine parts. In this paper, computer software systems are organized to measure linear cycle plane positioning displacement of ATC(Automatic tool changer) on zx plane of NC lathe using two linear scales. And each sets of error data obtained from the test is descriptions to plots and the results of linear cycle plane positioning errors are expressed as nutriments by computer treatment.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.11 no.2
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• pp.65-70
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• 2002

The rotational performance off machine tool spindle has a direct influence upon the surface finish of the finished workpiece. This running accuracy of the spindle is improved by increasing preload on the bearings, while it results in higher temperature rise and larger thermal deformation. Therefore, finding the optimal preload condition for high speed spindle is very important factors in spindle motion. in spindle motion. In this study, the effect of the preload on the roundness accuracy has been examined at the different cutting conditions. Experiments were carried out to investigate the effects of the bearing preload on the running accuracy of high speed spindle which was supported by two angular contact bearings.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.42-45
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• 2004

Electrochemical discharge machining (ECDM) has been found to be suitable for the micro-hole machining of nonconductive materials such as ceramics or glass compared with existing conventional and also non-conventional machining methods. However this machining process has some problems such as low geometric accuracy and low machining efficiency due to the random spark generation at the end of the electrode. This paper proposes the methods to improve the geometric accuracy of micro-hole using powder mixed ECDM process. The experimental results show the effects of powder producing improved geometric accuracy of machined hole and decreased concentration of spark energy.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.787-790
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• 2017

Data quality is the main issue in the classification problems; generally, the presence of noisy instances in the training dataset will not lead to robust classification performance. Such instances may cause the generated decision tree to suffer from over-fitting and its accuracy may decrease. Decision trees are useful, efficient, and commonly used for solving various real world classification problems in data mining. In this paper, we introduce a preprocessing technique to improve the classification accuracy rates of the C4.5 decision tree algorithm. In the proposed preprocessing method, we applied the naive Bayes classifier to remove the noisy instances from the training dataset. We applied our proposed method to a real e-commerce sales dataset to test the performance of the proposed algorithm against the existing C4.5 decision tree classifier. As the experimental results, the proposed method improved the classification accuracy by 8.5% and 14.32% using training dataset and 10-fold crossvalidation, respectively.