• Journal of Aerospace System Engineering
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• v.10 no.1
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• pp.103-110
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• 2016

This study shows the statistical properties of the domestic composite material prepregs test result. During the last three years(2012.5~2015.6) the prepreg specimen tests have been performed by referring to NCAMP developed test procedure which was approved by FAA. The database of (1) Carbon Tape, (2) Glass Fabric, and (3) Carbon Fabric composite material prepregs' characteristics have been established for certified aircraft structures. This qualified materials can be used for aircraft structural design through proper material equivalency procedures.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.37
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• pp.41-51
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• 1996

This paper evaluates the clustering performance of a neural network and a statistical method. Algorithms which are used in this paper are the GLVQ(Generalized Learning vector Quantization) for a neural method and the k-means algorithm fer a statistical clustering method. For comparison of two methods, we calculate the Rand's c statistics. As a result, the mean of c value obtained with the GLVQ is higher than that obtained with the k-means algorithm, while standard deviation of c value is lower. Experimental data sets were the Fisher's IRIS data and patterns extracted from handwritten numerals.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.2
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• pp.114-122
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• 2004

In statistical process control applications, variable sample size (VSS) $\bar{X}$ chart is often used to detect the assignable cause quickly. However, it is usually assumed that only one assignable cause results in the out-of-control in the process. In this paper, we propose the algorithm to minimize the function of cost per unit time and compare the economic design and the statistical design by use of the value of cost per unit time. We consider double assignable causes to occur with compound in the process and adopt the Markov chain approach to investigate the statistical properties of VSS $\bar{X}$ chart. A procedure that can calculate the control chart's parameters is proposed by the economic design.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.38
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• pp.117-129
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• 1996

This Study intends to analysis what 3 factors, which are indices of Capital, Labor and Distribution, really affect to Value-Added Productivity through Statistical Analysis. For this, We selected 12 indices of Value-Added from the edition of 'Annual report of Korean companies' published in 'Korea Investors Service., Inc', especially in parts of Chemicals and Chemical products of total 85 companies. Using this data, Multivariate Statistical Analysis such as Principal Component Analysis, Factor Analysis, Covariance Structure Analysis is taken for modeling the effect of 3 factor(Labor Productivity, Capital Productivity and the Index of Distribution) on Value-Added Productivity.

• Journal of KSNVE
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• v.8 no.4
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• pp.609-615
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• 1998

In recent years there has been an increasing emphasis on shortening design cycles for bringing products to market. This requires the development of computer aided engineering tools which allow analysts to quickly evaluate the effect of design changes on noise, vibration, and harshness. Statistical Energy Analysis (SEA) modeling is a valuable tool for predicting noise and vibration as SEA models are inherently simpler and more robust than deterministic models. SEA modeling can be combined with design sensitivity analysis(DSA) to identify design changes which give the largest performance benefit. This paper describes SEA modeling of an equipment cab. SEA predictions are compared to test data, showing good agreement. The use of design sensitivity analysis in improving cab design is then demonstrated.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2003.11a
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• pp.74-78
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• 2003

This paper shows the dosimetric uncertainties of electromagnetic field at in-vivo and in-vitro experiments. For more accurate consequences of these researches, we have tried to find out any correlations among output power, power density and specific absorption rate(SAR) with the results of in-vivo, in-vitro tests and SAR reports of cellular phone and PDA. In the case of in-vivo tests, the power density has close statistical correlations with SAR value and in the event of in-vitro tests, the output power has considerable statistical correlations with SAR containing duty factor. On the other hand, we found that both power density and output power don't have any close correlations with SAR. And, we obtained fitted regression form among frequency, power density and SAR containing duty factor through multiple linear regression analysis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.4
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• pp.667-673
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• 2006

In this paper, we present a visual inspection system for a CoG using statistical features. After rotational error of an input image is compensated using Hough transformation, an inspection area is obtained by using projection method. Then the final result is derived from statistical features of segmented pad areas.

• Communications for Statistical Applications and Methods
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• v.16 no.6
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• pp.959-969
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• 2009

Decision tree is a typical tool for data classification. This tool is implemented in DAVIS (Huh and Song, 2002). All the visualization tools and statistical clustering tools implemented in DAVIS can communicate with the decision tree. This paper presents methods to apply data visualization techniques to the decision tree using a real data set.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.13 no.1
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• pp.33-39
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• 2003

Interior parts of a vehicle are getting important to reduce interior noise. Therefore, prior analysis of cabin noise related with interior parts are necessary at first design stage. Recently, Statistical Energy Analysis(SEA) has been suggested as a possible way for high frequency range noise analysis of interior parts. The validity of noise analysis with SEA to interior parts has been preyed by comparing with experimental result, and the developed method with SEA has been applied in finding optimized interior parts package.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.10
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• pp.103-112
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• 1998

The evolution of semiconductor manufacturing technology has accelerated the reduction of device dimensions and the increase of integrated circuit density. In order to improve yield within a short turn around time and maintain it at high level, a system that can rapidly determine problematic processing steps is needed. The statistical process control detects abnormal process variation of key parameters. Expert systems in SPC can serve as a valuable tool to automate the analysis and interpretation of control charts. A set of IF-THEN rules was used to formalize knowledge base of special causes. This research proposes a strategy to apply expert system to SPC in semiconductor manufacturing. In analysis, the expert system accomplishes the instability detection of process parameter, In diagnosis, an engineer is supported by process analyzer program. An example has been used to demonstrate the expert system and the process analyzer.