• Korean Journal of Computational Design and Engineering
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• v.9 no.2
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• pp.175-182
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• 2004

As a bridge between design and manufacturing, process planning is to generate a sequenced set of instructions to manufacture the specified part. Automatic interpretation of manufacturing information incorporated in the design documentation such as CAD file has been a knotty subject for manufacturing engineers since no current data exchange format for product data provides a perfect interface between heterogeneous systems. The recent neutral data exchange format STEp, standard for the exchange of product model data, includes not only geometry but also technical and managerial information. STEP AP(Application Protocol) 224 is specifically dedicated to the mechanical product definition for process planning using machining features. Given a design information in STEP AP 224 format, process planning can be made without human intervention. This paper describes a method to determine the sequence of machining features by using the machining features and the manufacturing information expressed in STEP AP224.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.1
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• pp.81-89
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• 2009

Performance tests on the 3-Dimensional Flow-Structure-Interactions-Measurement System(FSIMS) have been carried out. Experimental data obtained by the FSIMS on a floating cylinder have been used to generate a set of artificial images. Comparisons between the data obtained by the use of the artificial images and those original experimental data have been made. Another set of artificial images have also been generated based on theoretically modulated sinusoidal motions, and comparisons between the data obtained by the use of these artificial images and the theoretical ones have been carried out. It has been verified that the FSIMS has a measurement uncertainty of 0.04-0.06mm/frame for velocity vectors and 0.002-0.01mm for the cylinder's positions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.40
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• pp.143-155
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• 1996

Presented in this paper are a CAPP(Computer Automated Process Planning) scheme and a generating method of intelligent NC data for unmaned machining of mold die. Mold die surfaces usually have free-formed geometry of complex shapes. So it is easy to overcut the die surface and to overload the cutting tools. It takes tens of hours to prepare process plans and to generate NC data for each processes. Therefore a classification of unit machining operation(UMO) for mold die manufacture, a backward recursive capp algorithm and a generating method of intelligent NC data are presented in this paper in order to provide a unmaned machining architecture of mold die.

• Transactions of the Korean Society of Automotive Engineers
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• v.5 no.5
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• pp.197-212
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• 1997

The performance of a torque converter can be expressed by the performance parameters such as flow radius and flow angle, on the mean flow path. The geometric analysis of the torque converter is required to determine these parameters for the modeling of the torque converter. In general, the blade shape is depicted by three dimensional data at the mid-surface of blade or those of the pressure and suction side. To generate three dimensional model of the blade using the data mentioned above, a consistent data format and a shape generation algorithm are required. This paper presents a useful consistent data format of the blades and an algorithm for the geometrical shape generation. By the geometric analysis program to which the shape generation algorithm is embedded, the variation of blade angles in rotating element analyzed. Then finally, the analyzed results of geometric profile of a blade are compared with those of the blade design principle, so called forced vortex theorem.

• The Korean Journal of Applied Statistics
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• v.22 no.1
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• pp.205-220
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• 2009

For modeling skewed semicircular data, we derive new family of the exponential distributions. We extend it to the l-axial exponential distribution by a transformation for modeling any arc of arbitrary length. It is straightforward to generate samples from the f-axial exponential distribution. Asymptotic result reveals two things. The first is that linear exponential distribution can be used to approximate the l-axial exponential distribution. The second is that the l-axial exponential distribution has the asymptotic memoryless property though it doesn't have strict memoryless property. Some trigonometric moments are also derived in closed forms. Maximum likelihood estimation is adopted to estimate model parameters. Some hypotheses tests and confidence intervals are also developed. The Kolmogorov-Smirnov test is adopted for goodness of fit test of the l-axial exponential distribution. We finally obtain a bivariate version of two kinds of the l-axial exponential distributions.

• Journal of Information Processing Systems
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• v.2 no.2
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• pp.67-75
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• 2006

In order to acquire a precise and quick response to an analytical query, proper selection of the views to materialize in the data warehouse is crucial. In traditional view selection algorithms, all relations are considered for selection as materialized views. However, materializing all relations rather than a part results in much worse performance in terms of time and space costs. Therefore, we present an improved algorithm for selection of views to materialize using the clustering method to overcome the problem resulting from conventional view selection algorithms. In the presented algorithm, ASVMRT (Algorithm for Selection of Views to Materialize using Reduced Table), we first generate reduced tables in the data warehouse using clustering based on attribute-values density, and then we consider the combination of reduced tables as materialized views instead of a combination of the original base relations. For the justification of the proposed algorithm, we reveal the experimental results in which both time and space costs are approximately 1.8 times better than conventional algorithms.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.1182-1185
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• 1995

This paper presents a novel technology for unattented continuous monitoring of radioactive material in hot cell environments. In this monitoring system, the surveillance camera data and NDA data are time synchronized and integrated into the same dimension through data processing. The integrated information is then fed into a neural network to generate diagnostics through data processing. the integrated information of the concept is tested for a spent nuclear fuel transprotation in an operational hot cell at KAERI. The presented integral part of the multi-sensory system and the analytical paradigm may provide an effective technologyical alternative for safeguarding new conceptual hot cell facilities, namely the Dupic facility.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.4
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• pp.27-43
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• 2005

This paper presents a new hybrid data mining technique using error pattern modeling to improve classification accuracy when the data type of a target variable is binary. The proposed method increases prediction accuracy by combining two different supervised learning methods. That is, the algorithm extracts a subset of training cases that are predicted inconsistently by both methods, and models error patterns from the cases. Based on the error pattern model, the Predictions of two different methods are merged to generate final prediction. The proposed method has been tested using practical 10 data sets. The analysis results show that the performance of proposed method is superior to the existing methods such as artificial neural networks and decision tree induction.

• Magazine of the Korean Society of Agricultural Engineers
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• v.39 no.6
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• pp.31-40
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• 1997

Potential impacts for unfavourable weather conditions and the assessment of the magnitudes of their adverse effects on crop yields were studied. EPIC model was investigated for its capability on crop yield predictions for rice and soybean. Weather generationmodel was used to generate long-term climatic data. The model was verified with ohserved climate data of Suwon city. Fifty years weather data including abnormal conditions were generated and used for crop yield simulation by EPIC model. Crop yield probability function was derived from simulated crop yield data, which followed normal distribution. Probable crop yield reductions due to abnormal weather conditions were also analyzed.

• Journal of Welding and Joining
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• v.9 no.3
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• pp.52-61
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• 1991

In the recent years the computer-numerical controlled cutting process such as a plasma arc cutting and a laser cutting is widely applied to reduce the time and cost expense for generating NC part program of the parts to be cut. In the present study, a CAD system(C-CAD) was developed to generate automatically the NC part programs with CLDAT(Cutter Location Data)for the CNC plasma arc cutting system. The NC part programs are composed of the 2-dimensional drawing of the parts to be cut and the technological data. The shape data of the parts drawn in the Auto-CAD can be also used in the C-CAD, since the data file generated by the C-CAD is compatible with that by the Auto-CAD. In order to check its applicability, the C-CAD and CAM system were applied to cut the parts, and which showed the satisfactory results.